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Summary vs Analysis
 
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A quick video reviewing differences between summary and analysis. The resource link on the last page is to http://www.aum.edu/docs/default-source/Learning-Center-Docs/tell-the-difference-between-analysis-and-summary-.pdf?sfvrsn=0
The Difference Between Structure & Form in Poetry Analysis
 
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Views: 36446 mrbruff
How to Identify Between Summary and Analysis by Shmoop
 
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This video identifies the difference between a summary essay (just a restatement of the text) and an analysis essay (a breakdown of the text). One doesn’t require as much brain power to write (spoiler alert: it’s the summary), but both are opinion-free zones. Learn more about writing on our website: http://www.shmoop.com/essay-lab/
Views: 13188 Shmoop
Choosing which statistical test to use - statistics help
 
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Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together videos about Helen, her brother, Luke and the choconutties.
Views: 646342 Dr Nic's Maths and Stats
How to analyze your data and write an analysis chapter.
 
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In this video Dr. Ziene Mottiar, DIT, discusses issues around analyzing data and writing the analysing chapter. The difference between Findings and Analysis chapters is also discussed. This video is useful for anyone who is writing a dissertation or thesis.
Views: 63073 ZieneMottiar
Chapter 21 Explaining the difference between linear and non linear analysis
 
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Using SolidWorks and examples to show the difference between linear and non-linear analysis. Three basic forms of non-linearities are discussed. CORRESPONDING BOOK AVAILABLE VIA THIS LINK: https://www.amazon.com/educational-experiments-FEM-Jos-Kreij/dp/1518686400/ref=sr_1_1_twi_pap_2?ie=UTF8&qid=1511249438&sr=8-1&keywords=21+fem+experiments The models that are discussed in the 21 main videos (corresponding to the chapters) can be downloaded for free via this link: https://grabcad.com/library/solidworks-simulation-educational-files-1 The zip-file in this link contains all SolidWorks models from all 21 chapters.
Views: 16430 Jos van Kreij
Understanding descriptive and inferential statistics | lynda.com overview
 
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This statistical analysis overview explains descriptive and inferential statistics. Watch more at http://www.lynda.com/Excel-2007-tutorials/business-statistics/71213-2.html?utm_medium=viral&utm_source=youtube&utm_campaign=videoupload-71213-0101 This specific tutorial is just a single movie from chapter one of the Excel 2007: Business Statistics course presented by lynda.com author Curt Frye. The complete Excel 2007: Business Statistics course has a total duration of 4 hours and 19 minutes and covers formulas and functions for calculating averages and standard deviations, charts and graphs for summarizing data, and the Analysis ToolPak add-in for even greater insights into data Excel 2007: Business Statistics table of contents: Introduction 1. Introducing Statistics 2. Learning Useful Excel Techniques 3. Summarizing Data Using Tables and Graphics 4. Describing Data Using Numerical Methods 5. Using Probability Distributions 6. Sampling Values from a Population 7. Testing Hypotheses 8. Using Linear and Multiple Regression Conclusion
Views: 95615 LinkedIn Learning
Historical Analysis and Interpretation
 
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Historical Analysis and Interpretation HT Standard 3 Difference between facts and interpretations. Fact -- something undeniable. Used as evidence. Interpretation -- an explanation based on information or personal experiences. Hold interpretations as tentative. They can change! Multiple perspectives. Compare differing sets of ideas, values, personalities, behaviors, and institutions. Evaluate debates among historians. Compare competing historical narratives. Cause and effect Challenge arguments of inevitability. Hypothesize the influence of the past.
Views: 7006 David Hunter
GRE Prep:  Analytical Writing  - Analyze an Issue vs Analyze an Argument
 
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To purchase our GRE book please visit: https://amzn.to/2tIeJVS To have an access to our online comprehensive GRE Prep visit: www.argoprep.com/gre
Views: 1448 Argo Brothers
difference between analysis and evaluation essay
 
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Data Collection & Analysis
 
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Impact evaluations need to go beyond assessing the size of the effects (i.e., the average impact) to identify for whom and in what ways a programme or policy has been successful. This video provides an overview of the issues involved in choosing and using data collection and analysis methods for impact evaluations
Views: 51141 UNICEF Innocenti
Using a Balance Sheet to Analyze a Company
 
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Balance sheets are one of the 3 financial statements that we use to measure the value of a company. A balance sheet gives the value of all of the assets and liabilities in a company, and shows the difference between the two as equity. http://bit.ly/1K9srFX To sign-up for my Transformational Investing Webinar, visit the link above. Think you have enough money saved for retirement? Learn more: http://bit.ly/1ONX2I1 Don't forget to subscribe to my channel here: http://ow.ly/RNAnK Looking to master investing? Attend one of my FREE 3-Day Transformational Investing Workshops. Apply here http://bit.ly/r1workshop _____________ For more great Rule #1 content and training: Podcast: http://bit.ly/1S9IyGw Blog: http://bit.ly/1PiELnA Facebook: https://www.facebook.com/rule1investing Twitter: https://twitter.com/Rule1_Investing Google+: +PhilTownRule1Investing Pinterest: https://www.pinterest.com/rule1investing/ analysis of balance sheet, reading balance sheet, how to read a company balance sheet,
Intro to Systematic Reviews & Meta-Analyses
 
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Here's a brief introduction to how to evaluate systematic reviews.
Views: 139332 Rahul Patwari
Univariate Analysis
 
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Let's go on a journey through univariate analysis and learn about descriptive statistics in research!
Views: 42564 ChrisFlipp
How To Analyse A Poem
 
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https://www.tes.com/teaching-resource/how-to-analyse-a-poem-11494512 How to analyse a poem – in six steps. Analysing a poem can be tricky. Before you analyse a poem in detail, it is important to read through the poem several times. Try to read the poem aloud, because poems can often have a range of sound devices that can alter the poem's meaning. Once you've read through the poem, you can start analysing the poem's content. Here are six steps to help you to analyse a poem: Step 1: Subject. What is the poem about and why? Step 2: Theme. What are the recurring ideas and topics? Step 3: Tone. How would you describe the mood of the language? Step 4: Imagery. What literary devices are used and what do they signify? Step 5: Form. Why the poet has chosen this structure? Step 6: Feeling. What are the different emotions being conveyed? How do you analyse a poem? The prompts are a supportive tool, intended to encourage further analysis and interpretation. If you found this helpful, you may wish to check out Poetry Essay app. It provides you with a range of writing frames to help you stich a poetry essay together. Alternatively, please visit poetryessay.co.uk for some other free resources – such as posters, poetry annotations and planning templates – to assist your analysis of poetry. Poetry Essay app unfortunately is no longer supported, since iOS 11. For daily poetry news and essay support, please visit: http://www.poetryessay.co.uk
Views: 87253 Poetry Essay
Event History Analysis: differences with other analyses using time
 
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Part of a course for MSc and PhD students in demography and epidemiology. Explains the difference between Event History Analysis and other types of analyses: panel data analysis, time series analysis, longitudinal data analysis.
Views: 83 Philippe Bocquier
Introduction to Industry Analysis
 
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Hal Kirkwood, from Purdue Libraries, will give a short introduction to industry analysis. This video will discuss the difference between an industry and a market, consumer information and industry classifications.
Views: 32724 PurdueLibraries
How to Analyze a Poem
 
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In this video, I give one method for analyzing poetry, using the poem "The Chimney Sweeper" by William Blake. This was designed to help students moving towards Common Core Standards who need to go beyond identifying poetic devices to actually analyzing the meaning of words and searching for the deeper meaning.
Views: 136011 Nicole Mohr
SPSS for questionnaire analysis:  Correlation analysis
 
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Basic introduction to correlation - how to interpret correlation coefficient, and how to chose the right type of correlation measure for your situation. 0:00 Introduction to bivariate correlation 2:20 Why does SPSS provide more than one measure for correlation? 3:26 Example 1: Pearson correlation 7:54 Example 2: Spearman (rhp), Kendall's tau-b 15:26 Example 3: correlation matrix I could make this video real quick and just show you Pearson's correlation coefficient, which is commonly taught in a introductory stats course. However, the Pearson's correlation IS NOT always applicable as it depends on whether your data satisfies certain conditions. So to do correlation analysis, it's better I bring together all the types of measures of correlation given in SPSS in one presentation. Watch correlation and regression: https://youtu.be/tDxeR6JT6nM ------------------------- Correlation of 2 rodinal variables, non monotonic This question has been asked a few times, so I will make a video on it. But to answer your question, monotonic means in one direction. I suggest you plot the 2 variables and you'll see whether or not there is a monotonic relationship there. If there is a little non-monotonic relationship then Spearman is still fine. Remember we are measuring the TENDENCY for the 2 variables to move up-up/down-down/up-down together. If you have strong non-monotonic shape in the plot ie. a curve then you could abandon correlation and do a chi-square test of association - this is the "correlation" for qualitative variables. And since your 2 variables are ordinal, they are qualitative. Good luck
Views: 486689 Phil Chan
Analysis: Tekken - The Difference Between 2D and 3D
 
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Join the Core-A Gaming Discord: https://discordapp.com/invite/WRkRQF9 Support on Patreon: http://bit.ly/2rfySih A comparison of 2d and 3d fighting games. Thanks to SonicKurosaki, Nathan Palmer, Tyler Oxtoby, Dot Eater, Sandro Limaj, DeimosClay, Koungnak Baek, Frankie Huynh, Flan, Cory Wright, WoodenFence, Jamaal Graves, KILLYIS, Matt Bahr, Sam Not-Sam, and everyone else who pledged on Patreon! Additional thanks to those who helped on this video on the Core-A Gaming discord. Jeondding's Twitter: @jeondding_tk Watch Aris analyze one of his favorite Tekken matches: https://www.youtube.com/watch?v=hmrLtA4i5q0&t= Wired Article on Virtua Fighter: https://www.wired.com/2012/09/how-virtua-fighter-saved-playstations-bacon/ Gamasutra Interview with Harada: https://www.gamasutra.com/view/news/305185/Between_a_rock_and_a_Harada_place_The_massive_Tekken_interview.php Follow me on Twitter: @CoreAGaming Buy a t-shirt: https://shop.spreadshirt.com/coreagaming Facebook: http://www.facebook.com/coreagaming BGM in order: Tekken 6 - Mystical Forest Tekken 5 - Moonlit Wilderness Tekken 4 - Authentic Sky Tekken Tag Tournament 2 - Eternal Paradise Tekken 7 - Metallic Experience 1st
Views: 377900 Core-A Gaming
Analyzing Differences between Percentages with SPSS
 
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This video demonstrates how to analyze the differences between percentages using SPSS. The chi-square test is used to test the null hypothesis that there is no difference between percentages. Also, there is a review on how to change the expected values.
Views: 18447 Todd Grande
IELTS Writing Task 1 - How to Analyze Charts, Maps, and Process Diagrams
 
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In this IELTS Writing Task 1 lesson, you'll learn how to accurately analyze charts, maps, and process diagrams. I explain how you can use a question checklist to practice your Task 1 analysis abilities. I also give an example of each kind of Task 1 data set. Here are the checklist questions from the video: Instructions: To improve your ability to analyze Task 1 data, use the questions below when you see a new graph, chart, map, or process diagram. After you’re comfortable with the checklists, gradually try to use them less and less until you can analyze the data more easily. Graph or Chart: What are the axes (x and y)? What are the units of measurement? (e.g. amount, %, age, etc.) Is there more than one group being compared? (e.g. 3 different countries) Does it show change over time? (this is common for graphs) What are the time periods shown? (past, present, future) What is the general trend? (increase, decrease, etc.) Are there any large differences between groups or charts? Are there any groups or charts that share similarities? How can I break it into two parts? Map: Is there more than one map being compared? What are the time periods shown? (past, present, future) Are they in different maps or the same map? What are the most noticeable differences between the multiple maps or time periods? What parts of the map are the same in both maps/time periods? Can the map(s) be easily broken into two parts? How? Process Diagrams: Where is the start of the process? The end? How many total stages are there? What kind of process is it? Is it a cycle or a linear (start to finish) process? What does each stage do? And what is its connection with the previous stage? What is the end result? Is something produced? Can the process be easily broken into two parts? How? Watch more IELTS Master Writing Task 1 videos: https://www.youtube.com/playlist?list=PLQKm5R-SeKdOeIIbDm3k4-Bwt0PZNDdas Find more IELTS practice content: http://www.ielts-master.com
Views: 159694 IELTS Master
Qualitative analysis of interview data: A step-by-step guide
 
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The content applies to qualitative data analysis in general. Do not forget to share this Youtube link with your friends. The steps are also described in writing below (Click Show more): STEP 1, reading the transcripts 1.1. Browse through all transcripts, as a whole. 1.2. Make notes about your impressions. 1.3. Read the transcripts again, one by one. 1.4. Read very carefully, line by line. STEP 2, labeling relevant pieces 2.1. Label relevant words, phrases, sentences, or sections. 2.2. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant. 2.3. You might decide that something is relevant to code because: *it is repeated in several places; *it surprises you; *the interviewee explicitly states that it is important; *you have read about something similar in reports, e.g. scientific articles; *it reminds you of a theory or a concept; *or for some other reason that you think is relevant. You can use preconceived theories and concepts, be open-minded, aim for a description of things that are superficial, or aim for a conceptualization of underlying patterns. It is all up to you. It is your study and your choice of methodology. You are the interpreter and these phenomena are highlighted because you consider them important. Just make sure that you tell your reader about your methodology, under the heading Method. Be unbiased, stay close to the data, i.e. the transcripts, and do not hesitate to code plenty of phenomena. You can have lots of codes, even hundreds. STEP 3, decide which codes are the most important, and create categories by bringing several codes together 3.1. Go through all the codes created in the previous step. Read them, with a pen in your hand. 3.2. You can create new codes by combining two or more codes. 3.3. You do not have to use all the codes that you created in the previous step. 3.4. In fact, many of these initial codes can now be dropped. 3.5. Keep the codes that you think are important and group them together in the way you want. 3.6. Create categories. (You can call them themes if you want.) 3.7. The categories do not have to be of the same type. They can be about objects, processes, differences, or whatever. 3.8. Be unbiased, creative and open-minded. 3.9. Your work now, compared to the previous steps, is on a more general, abstract level. 3.10. You are conceptualizing your data. STEP 4, label categories and decide which are the most relevant and how they are connected to each other 4.1. Label the categories. Here are some examples: Adaptation (Category) Updating rulebook (sub-category) Changing schedule (sub-category) New routines (sub-category) Seeking information (Category) Talking to colleagues (sub-category) Reading journals (sub-category) Attending meetings (sub-category) Problem solving (Category) Locate and fix problems fast (sub-category) Quick alarm systems (sub-category) 4.2. Describe the connections between them. 4.3. The categories and the connections are the main result of your study. It is new knowledge about the world, from the perspective of the participants in your study. STEP 5, some options 5.1. Decide if there is a hierarchy among the categories. 5.2. Decide if one category is more important than the other. 5.3. Draw a figure to summarize your results. STEP 6, write up your results 6.1. Under the heading Results, describe the categories and how they are connected. Use a neutral voice, and do not interpret your results. 6.2. Under the heading Discussion, write out your interpretations and discuss your results. Interpret the results in light of, for example: *results from similar, previous studies published in relevant scientific journals; *theories or concepts from your field; *other relevant aspects. STEP 7 Ending remark This tutorial showed how to focus on segments in the transcripts and how to put codes together and create categories. However, it is important to remember that it is also OK not to divide the data into segments. Narrative analysis of interview transcripts, for example, does not rely on the fragmentation of the interview data. (Narrative analysis is not discussed in this tutorial.) Further, I have assumed that your task is to make sense of a lot of unstructured data, i.e. that you have qualitative data in the form of interview transcripts. However, remember that most of the things I have said in this tutorial are basic, and also apply to qualitative analysis in general. You can use the steps described in this tutorial to analyze: *notes from participatory observations; *documents; *web pages; *or other types of qualitative data. STEP 8 Suggested reading Alan Bryman's book: 'Social Research Methods' published by Oxford University Press. Steinar Kvale's and Svend Brinkmann's book 'InterViews: Learning the Craft of Qualitative Research Interviewing' published by SAGE. Good luck with your study. Text and video (including audio) © Kent Löfgren, Sweden
Views: 641623 Kent Löfgren
The science of analyzing conversations, second by second | Elizabeth Stokoe | TEDxBermuda
 
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Prof. Elizabeth Stokoe takes a run on what she terms the “conversational racetrack”—the daily race to understand each other when we speak—and explains how to avoid hurdles that trip us up and cause conflict. Elizabeth Stokoe is a British scientist. She studies conversation analysis. She is a professor at Loughborough University. She graduated from the University of Central Lancashire (Preston Poly) in 1993 with a traditional psychology degree. Then Stokoe completed three years PhD research at Nene College (Leicester University) with Dr. Eunice Fisher. Her research included videotaping interaction in university tutorials, and conducting conversation analyses of topic production, topic management, academic identity, and the relevance of gender. She developed these and other interests while working at the Institute of Behavioural Sciences (University of Derby, 1997-2000) and University College Worcester (2000-2002). Stokoe joined the Department of Social Sciences at Loughborough in October 2002 and was promoted to Reader (2007) and Chair (2009). She teaches on the BSc Social Psychology programme, covering modules in relationships, qualitative methods and forensic psychology. Stokoe developed the Conversation Analytic Role-play Method (CARM), an approach based on evidence about what sorts of problems and roadblocks can occur in conversation, as well as the techniques and strategies that best resolve these problems.[2] CARM won Loughborough University's Social Enterprise award (2013). About TEDx, x = independently organized event In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
Views: 611733 TEDx Talks
Data Science vs Big Data vs Data Analytics | Simplilearn
 
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Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. According to IBM, 2.5 billion gigabytes (GB) of data was generated every day in 2012. An article by Forbes states that Data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet. Which makes it extremely important to at least know the basics of the field. After all, here is where our future lies. In this video, we will differentiate between the Data Science, Big Data, and Data Analytics, based on what it is, where it is used, the skills you need to become a professional in the field, and the salary prospects in each field. For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 132748 Simplilearn
How to Summarize & Critically Respond to an Article
 
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This narrated presentation teaches students how to critically read a piece of writing. It focuses on helping students write the summary portion and the analytical response portion of their Essay. You can print a copy of my notes from this video here: http://www.mesacc.edu/~paoih30491/How%20To%20Summarize%20and%20Critically%20Analyze%20PDF.pdf Sources: Crusius and Channell, The Aims of Argument, Mayfield Publishing Co., 1995 The Prentice Hall Guide for College Writers, 8th Ed. by Stephen Ried, 2008. Published by Prentice Hall, Upper Saddle River, NJ Global Issues, Local Arguments: Readings for Writings by June Johnson, 2007. Published by Longman , New York, NY.
Views: 149739 Paola Brown
Cohort, Case-Control, Meta-Analysis, Cross-sectional Study Designs & Definition
 
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http://www.stomponstep1.com/cohort-case-control-meta-analysis-cross-sectional-study-designs/ Based on the types of bias that are inherent in some study designs we can rank different study designs based on their validity. The types of research studies at the top of the list have the highest validity while those at the bottom have lower validity. In most cases if 2 studies on the same topic come to different conclusions, you assume the trial of the more valid type is correct. However, this is not always the case. Any study design can have bias. A very well designed and executed cohort study can yield more valid results than a clinical trial with clear deficiencies. • Meta-analysis of multiple Randomized Trials (Highest Validity) • Randomized Trial • Prospective Cohort Studies • Case Control Studies or Retrospective Cohort • Case Series (Lowest Validity) Meta-analysis is the process of taking results from multiple different studies and combining them to reach a single conclusion. Doing this is sort of like having one huge study with a very large sample size and therefore meta-analysis has higher power than individual studies. Clinical trials are the gold standard of research for therapeutic and preventative interventions. The researchers have a high level of control over most factors. This allows for randomization and blinding which aren't possible in many other study types. Participant's groups are assigned by the researcher in clinical trials while in observational studies "natural conditions" (personal preference, genetics, social determinants, environment, lifestyle ...) assign the group. As we will see later, the incidence in different groups is compared using Relative Risk (RR). Cohort Studies are studies where you first determine whether or not a person has had an exposure and then you monitor the occurrence of health outcomes overtime. It is the observational study design with the highest validity. Cohort is just a fancy name for a group, and this should help you remember this study design. You start with a group of people (some of whom happen to have an exposure and some who don't). Then you follow this group for a certain amount of time and monitor how often certain diseases or health outcomes arise. It is easier to conceptually understand cohort studies that are prospective. However, there are retrospective cohort studies also. In this scenario you identify a group of people in the past. You then first identify whether or not these people had the particular exposure at that point in time and determine whether or not they ended up getting the health outcomes later on. As we will see later, the incidence in different groups in a cohort study is compared using Relative Risk (RR). Case-Control Studies are retrospective and observational. You first identify people who have the health outcome of interest. Then you carefully select a group of controls that are very similar to your diseased population except they don't have that particular disease. Then you try to determine whether or not the participants from each group had a particular exposure in the past. I remember this by thinking that in a case control study you start off knowing whether a person is diseased (a case) or not diseased (a control). There isn't a huge difference between retrospective cohort and case-control. You are basically doing the same steps but in a slightly different order. However, the two study designs are used in different settings. As we will see later, the incidence in different groups in a case-control study is compared using Odds Ratio (OR). A Case-Series is a small collection of individual cases. It is an observational study with a very small sample size and no control group. Basically you are just reviewing the medical records for a few people with a particular exposure or disease. A study like this is good for very rare exposures or diseases. Obviously the small sample size and lack of a control group limits the validity of any conclusions that are made, but in certain situations this is the best evidence that is available. Cross Sectional Studies are different from the others we have discussed. While the other studies measure the incidence of a particular health outcome over time, a cross-sectional study measures Prevalence. In this observational study the prevalence of the exposure and the health outcome are measured at the same time. You are basically trying to figure out how many people in the population have the disease and how many people have the exposure at one point in time. It is hard to determine an association between the exposure and disease just from this information, but you can still learn things from these studies. If the exposure and disease are both common in a particular population it may be worth investing more resources to do a different type of study to determine whether or not there is a causal relationship.
Views: 106732 Stomp On Step 1
Analyzing Quantitative PCR Data
 
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Relative and absolute methods of qPCR analysis. Created for an assignment for BIOC3001: Molecular Biology at the University of Western Australia. ****SCRIPT**** [I know it's a bit fast] qPCR or quantitative real-time PCR… ….is simply classic PCR monitored using fluorescent dyes or probes. qPCR is accurate, reliable and extremely sensitive, it can even detect a SINGLE copy of a specific transcript. qPCR is commonly coupled to reverse transcription to measure gene expression. No wonder it is so important for molecular diagnostics, life sciences, agriculture, and medicine. Firstly, let's go over the NUTS and BOLTS of qPCR. For this you use a fluorescent dye which binds to the DNA. As qPCR progresses, the fluorescent signal increases. Ideally the signal should double with every cycle, which is then plotted. Because there are few template strands to start with, initially there’s a faint signal. Eventually, usually after 15 cycles, the signal rises above the background noise and can be detected. We call this the THRESHOLD CYCLE, Ct, the point from which all quantitative data analysis begins. But how do you analyse qPCR data? You can either use an absolute quantification method, with a standard curve, OR a relative method, using one or more reference genes to standardize and compare the differences in Ct values between two treatments. The absolute standard curve method determines ORIGINAL DNA concentration by comparing the Ct value of the sample of interest with a standard curve. To create the standard curve, you need to make DNA samples of different KNOWN concentrations. After doing PCR on these, you will see different PCR plots for each standard ….. and unsurprisingly they have different Ct values. The GREATER the concentration of the original DNA sample, the SMALLER the Ct value. So if you plot ORIGINAL DNA concentration against the Ct values. You will have a standard curve like this….. Now let’s say the PCR plot of your unknown DNA sample is somewhere here….. ...which corresponds to this Ct value on the standard curve here…. Using the standard curve you can figure out the log concentration of your DNA sample to be x. As this is in log scale, you can simply calculate your sample DNA concentration to be 10 to the power of x. Absolute analysis is suitable when you want to determine the ACTUAL transcript copy number, that is the level of gene expression. On the other hand, Relative quantification is used when you want to COMPARE the difference in gene expression BETWEEN two treatments, for example light or dark treated Arabadopsis thaliana. This is done using one or more reference genes, such as actin, which are expressed at the SAME level for both treatments. You then perform qPCR on both your samples and the reference genes, find out the DIFFERENCE between the two Cts values, delta Ct, in EACH treatment. Now the RATIO of the two delta Cts …[pause a bit] . tells you how much gene expression has changed. For instance, in the dark treatment, the Ct value of your reference gene is at THIS level, the Ct value of your target gene is THIS Level. So you have this delta Ct which is the difference in Cts in the first treatment. in the dark treatment, the Ct value of your reference gene is STILL at THIS level, but the Ct value of your target gene may become only this much. So the ratio of the two Ct values is.. delta Ct(dark treatment) divided by delta Ct(light treament) equals one third ….showing the delta Ct has DECREASED by a factor of 3, which means that gene expression of the target gene is GREATER in the dark treated sample. This is how relative quantification using a reference gene helps detect change in the expression of your target gene. In conclusion, there are two ways to quantify transcripts using qPCR: absolute quantification using a standard curve, and relative quantification using a reference gene. The method used depends on whether you want to determine the ACTUAL number of transcripts or the RELATIVE change in gene expression.
Views: 173245 TARDIStennant
Strategic Planning: SWOT & TOWS Analysis
 
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http://www.driveyoursuccess.com/2011/09/strategic-business-planning-use-tows-to-move-swot-to-an-action-plan.html - Link explains how to use TOWS to move SWOT to an action plan. http://www.driveyoursuccess.com Video explains both the SWOT analysis and TOWS analysis in strategic planning
Views: 171284 Ian Johnson
What is the Difference Between a Job Analysis and Job Description?
 
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Vocational Expert Everett O'Keefe, from JobAnalysis.Biz, shares the many differences between JAs and JDs. You can get more info at http://jobanalysis.biz.
Views: 18421 jobanalysisbiz
Real Time QPCR Data Analysis Tutorial
 
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In this Bio-Rad Laboratories Real Time Quantitative PCR tutorial (part 1 of 2), you will learn how to analyze your data using both absolute and relative quantitative methods. The tutorial also includes a great explanation of the differences between Livak, delta CT and the Pfaffl methods of analyzing your results. For more videos visit http://www.americanbiotechnologist.com
Views: 307957 americanbiotech
Circuit Analysis: Crash Course Physics #30
 
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How does Stranger Things fit in with Physics and, more specifically, circuit analysis? I'm glad you asked! In this episode of Crash Course Physics, Shini walks us through the differences between series and parallel circuits and how that makes Christmas lights work the way they work. Check out this Crash Course Government Poster (just in time for election season): https://store.dftba.com/products/crash-course-us-government-poster Get your own Crash Course Physics mug from DFTBA: http://store.dftba.com/products/crash... The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list... -- Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios -- Want to find Crash Course elsewhere on the internet? Facebook - http://www.facebook.com/YouTubeCrashC... Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support CrashCourse on Patreon: http://www.patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids
Views: 360831 CrashCourse
Implict vs Explicit Analysis | What is the difference between Implicit & Explicit Analysis | GRS
 
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Contact for Projects & online training Mobile/WhatsApp: +91-9481635839 | INDIA Email: [email protected] Skype: engineeringtutorsdesk Demonstration of Implicit & Explicit Analysis in Finite Element Analysis. LS-Dyna & ANSYS can be used for either Implicit or Explicit Analysis. IMPLICIT ANALYSIS: No effect of mass (inertia) or of damping, Static analysis is done using an implicit solver, solution of each step requires iterative solutions to establish equilibrium within a certain tolerance, Time steps are generally larger than explicit time steps, Requires a numerical solver to invert the stiffness matrix once or even several times over the course of a load/time step, which is expensive for large models. EXPLICIT ANALYSIS: Mass/inertia and damping are included, Dynamic analysis can be done via the explicit solver, No iteration is required as the nodal accelerations are solved directly, No inherent limit on the size of the time step, Time step must be less than the Courrant time step, Dose not require matrix inversion, Handles contact and material nonlinearities with relative ease, Once accelerations are known at time n, velocities are calculated at time n+1/2, and displacements at time n+1, from displacements comes strain, from strain comes stress & the cycle is repeated. The intent of this channel is to provide the complete solution for engineering problems related to Structural, Thermal & Fluid flow. You can get trained on FEA applications like ANSYS, Hypermesh, ANSA, LS-Dyna & Design applications like Creo Parametric, Solid works, Auto CADD. We do handle Industrial projects, IEEE Projects, Students Projects. Research projects You can now get trained on the tools and technologies by sitting at your place. We provide both classroom and online training for students and professionals who can not travel can make best use of this online face to face training. The trainer are corporate professionals, and there is no compromise on the quality we deliver. Contact: Email: [email protected], Skype: engineeringtutorsdesk, Mobile: +91-9481635839 | INDIA Webpage: https://sites.google.com/site/feaengineeringdesign/ Channel:
Views: 26974 CAE Worldwide
5 Key Metrics To Analyse Your Power Data
 
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In association with Training Peaks. These are the key numbers you need to focus on when analysing your power data. Subscribe to GCN: http://gcn.eu/SubscribeToGCN Get exclusive GCN gear in the GCN store! http://gcn.eu/BuyGCNKit_ Sign up to the GCN newsletter: http://gcn.eu/gcnnewsletter Programs like TrainingPeaks make it much easier to have all your data in one place and even more importantly be able to measure progress and improvements in your training. These 5 metrics will allow you to see how hard you worked for a given session and manage your training load accordingly. Watch more on GCN... How to find out your Functional Threshold Power ▶︎ http://gcn.eu/1RDHZE8 Test your fitness indoors ▶︎ http://gcn.eu/1Wf7rPP Buy NEW GCN cycling kit, casual wear and accessories in the GCN Shop: http://gcn.eu/TheGCNShop Music: Israel Medina - Hide And Seek About GCN: The Global Cycling Network puts you in the centre of the action: from the iconic climbs of Alpe D’Huez and Mont Ventoux to the cobbles of Flanders, everywhere there is road or pavé, world-class racing and pro riders, we will be there bringing you action, analysis and unparalleled access every week, every month, and every year. We show you how to be a better cyclist with our bike maintenance videos, tips for improving your cycling, cycling top tens, and not forgetting the weekly GCN Show. Join us on YouTube’s biggest and best cycling channel to get closer to the action and improve your riding! Welcome to the Global Cycling Network | Inside cycling Thanks to our sponsors: Santini cycling kit: http://gcn.eu/1SFf8PV KASK helmets: http://gcn.eu/1FrbcHK fi’zi:k shoes and saddles: http://gcn.eu/1tsXI7S and http://gcn.eu/1KxBGd5 Topeak tools: http://gcn.eu/1Lc4HAj Canyon bikes: http://gcn.eu/1Oge4gz Muc-Off: http://gcn.eu/1XlT5Og Science in Sport: http://gcn.eu/1GrXo6n Ass Savers: http://gcn.eu/1XlTmkm Orbea bikes: http://gcn.eu/1oks6GH Trek Bicycles: http://gcn.eu/1RUwyGf Vision wheels: http://gcn.eu/1qHTlMu Zipp wheels: http://gcn.eu/1OcMUv5 Powertap: http://gcn.eu/1XlfT2p power2max: http://gcn.eu/1sdoPva Rotor: http://gcn.eu/1q3vtCo Reynolds: http://gcn.eu/1JjCDVL YouTube Channel - http://gcn.eu/gcnYT Facebook - http://gcn.eu/gcnFb Google+ - http://gcn.eu/gcnGPlus Twitter - http://gcn.eu/gcnTW GCN newsletter - http://gcn.eu/gcnnewsletter Leave us a comment below!
Views: 102198 Global Cycling Network
Panel Data Analysis | Econometrics | Fixed effect|Random effect | Time Series | Data Science
 
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This video is on Panel Data Analysis. Panel data has features of both Time series data and Cross section data. You can use panel data regression to analyse such data, We will use Fixed Effect Panel data regression and Random Effect panel data regression to analyse panel data. We will also compare with Pooled OLS , Between effect & first difference estimation For Analytics study packs visit : https://analyticuniversity.com Time Series Video : https://www.youtube.com/watch?v=Aw77aMLj9uM&t=2386s Logistic Regression using SAS: https://www.youtube.com/watch?v=vkzXa0betZg&t=7s Logistic Regression using R : https://www.youtube.com/watch?v=nubin7hq4-s&t=36s Support us on Patreon : https://www.patreon.com/user?u=2969403
Views: 54495 Analytics University
Frequencies and Descriptive Statistics
 
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How to conduct an analysis of frequencies and descriptive statistics using SPSS/PASW.
Views: 235716 bernstmj
How does word choice affect tone and meaning?
 
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Learn the difference between denotation and connotation, how connotations create the author's tone, and how both create meaning. Closely study a poem by Ernest Hemingway, "All armies are the same..." Hemingway's poem, written about his experiences in World War I, remains a devastating statement about war seen from the soldier's perspective. This video addresses the Common Core standard, CCSS-ELA Literacy RL9-10.4 : "Determine the meaning of words and phrases as they are used in the text, including figurative and connotative meanings; analyze the cumulative impact of specific word choices on meaning and tone (e.g., how the language evokes a sense of time and place; how it sets a formal or informal tone)." For folks with a Common Core aversion: this is stuff that has been taught in English classes for ages, but perhaps not all together. I break up the complex task into two more manageable ones. I appreciate any feedback teachers and students can offer! Leave a comment! (Select 1080p for higher resolution images.) Now on Twitter @mistersato411
Views: 87048 mistersato411
SPSS Questionnaire/Survey Data Entry - Part 1
 
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How to enter and analyze questionnaire (survey) data in SPSS is illustrated in this video. Lots more Questionnaire/Survey & SPSS Videos here: https://www.udemy.com/survey-data/?couponCode=SurveyLikertVideosYT Check out our next text, 'SPSS Cheat Sheet,' here: http://goo.gl/b8sRHa. Prime and ‘Unlimited’ members, get our text for free. (Only 4.99 otherwise, but likely to increase soon.) Survey data Survey data entry Questionnaire data entry Channel Description: https://www.youtube.com/user/statisticsinstructor For step by step help with statistics, with a focus on SPSS. Both descriptive and inferential statistics covered. For descriptive statistics, topics covered include: mean, median, and mode in spss, standard deviation and variance in spss, bar charts in spss, histograms in spss, bivariate scatterplots in spss, stem and leaf plots in spss, frequency distribution tables in spss, creating labels in spss, sorting variables in spss, inserting variables in spss, inserting rows in spss, and modifying default options in spss. For inferential statistics, topics covered include: t tests in spss, anova in spss, correlation in spss, regression in spss, chi square in spss, and MANOVA in spss. New videos regularly posted. Subscribe today! YouTube Channel: https://www.youtube.com/user/statisticsinstructor Video Transcript: In this video we'll take a look at how to enter questionnaire or survey data into SPSS and this is something that a lot of people have questions with so it's important to make sure when you're working with SPSS in particular when you're entering data from a survey that you know how to do. Let's go ahead and take a few moments to look at that. And here you see on the right-hand side of your screen I have a questionnaire, a very short sample questionnaire that I want to enter into SPSS so we're going to create a data file and in this questionnaire here I've made a few modifications. I've underlined some variable names here and I'll talk about that more in a minute and I also put numbers in parentheses to the right of these different names and I'll also explain that as well. Now normally when someone sees this survey we wouldn't have gender underlined for example nor would we have these numbers to the right of male and female. So that's just for us, to help better understand how to enter these data. So let's go ahead and get started here. In SPSS the first thing we need to do is every time we have a possible answer such as male or female we need to create a variable in SPSS that will hold those different answers. So our first variable needs to be gender and that's why that's underlined there just to assist us as we're doing this. So we want to make sure we're in the Variable View tab and then in the first row here under Name we want to type gender and then press ENTER and that creates the variable gender. Now notice here I have two options: male and female. So when people respond or circle or check here that they're male, I need to enter into SPSS some number to indicate that. So we always want to enter numbers whenever possible into SPSS because SPSS for the vast majority of analyses performs statistical analyses on numbers not on words. So I wouldn't want and enter male, female, and so forth. I want to enter one's, two's and so on. So notice here I just arbitrarily decided males get a 1 and females get a 2. It could have been the other way around but since male was the first name listed I went and gave that 1 and then for females I gave a 2. So what we want to do in our data file here is go head and go to Values, this column, click on the None cell, notice these three dots appear they're called an ellipsis, click on that and then our first value notice here 1 is male so Value of 1 and then type Label Male and then click Add. And then our second value of 2 is for females so go ahead and enter 2 for Value and then Female, click Add and then we're done with that you want to see both of them down here and that looks good so click OK. Now those labels are in here and I'll show you how that works when we enter some numbers in a minute. OK next we have ethnicity so I'm going to call this variable ethnicity. So go ahead and type that in press ENTER and then we're going to the same thing we're going to create value labels here so 1 is African-American, 2 is Asian-American, and so on. And I'll just do that very quickly so going to Values column, click on the ellipsis. For 1 we have African American, for 2 Asian American, 3 is Caucasian, and just so you can see that here 3 is Caucasian, 4 is Hispanic, and other is 5, so let's go ahead and finish that. Four is Hispanic, 5 is other, so let's go to do that 5 is other. OK and that's it for that variable. Now we do have it says please state I'll talk about that next that's important when they can enter text we have to handle that differently.
Views: 415797 Quantitative Specialists
Intro to Cost-Benefit Analysis
 
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This video is a part of Conservation Strategy Fund's collection of environmental economic lessons and was made possible thanks to the support of the Gordon and Betty Moore Foundation and the Marcia Brady Tucker Foundation. This series is for individuals who want to learn - or review - the basic economics of conservation. In this video, you will be introduced to the concept of a cost benefit analysis. You will learn the difference between decision making from the perspective of a private firm vs. a larger society and how this applies to environmental conservation. To follow this series, subscribe to our YouTube channel. For more information on these and other trainings from Conservation Strategy Fund, check out: http://www.conservation-strategy.org/ For copyright information on all sound effects, see http://www.conservation-strategy.org/en/page/csf-economic-video-lessons-sound-references
Network Analysis : Differences among Loop,Mesh,Node,Branch,Junction point
 
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My next video will be on Classification of Electrical Network.
Starbucks SWOT Analysis
 
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On Udemy: https://www.udemy.com/user/365careers/ On Facebook: https://www.facebook.com/365careers/ On the web: http://www.365careers.com/ On Twitter: https://twitter.com/365careers Subscribe to our channel: https://www.youtube.com/365careers This lesson on Business strategy introduces the idea behind doing SWOT analyses. Watch more at https://www.udemy.com/mba-in-a-box-business-lessons-from-a-ceo . This video is part of a series of short lessons about Business Strategy. The complete module can be found on Udemy, as a core part of the MBA in a Box course by CEO Valentina Bogdanova and 365 Careers. The course provides a complete Business Education: Business Strategy, Management, Marketing, Accounting, Decision Making & Negotiation in just under 10 hours. -------------------------------------------------- Strategy module table of contents: MBA in a Box: Introduction 1. What does the course cover? Section: 2 Strategy: An Introduction 2. The role of Strategy and what makes a Strategy successful 3. The difference between Corporate and Business Strategy 4. The importance of the Mission, Vision, Goals, and Values statements Section: 3 Strategy: The industry lifecycle model 5. The four stages of the industry lifecycle model - An introduction 6. The strategic importance of the industry lifecycle model 7. The Introduction stage - A new industry is born 8. The Growth stage - An industry in its expansion phase 9. The Maturity stage - An industry at its peak 10. The Decline stage - An obsolete industry Section: 4 Strategy: Porter's Five Forces model - The competitive dynamics in an industry 11. Michael Porter's Five Forces model 12. The threat of new entrants 13. The threat of substitute products 14. The intensity of current competition 15. The bargaining power of suppliers 16. The bargaining power of clients 17. Porter's Five Forces framework applied in practice Section: 5 Strategy: Game Theory - Studying the interaction between multiple parties 18. An introduction to Game Theory 19. Zero-sum games - approaching situations with a win-lose perspective 20. Non-zero-sum games - considering both cooperation and confrontation 21. Tobacco companies - a real-life example of Game Theory application Section: 6 Strategy: Focusing on the inside of a business 22. Focusing on the inside of a business - An Introduction 23. A company's lifecycle model - what should be done at different stages Section: 7 Strategy: Acquiring a competitive advantage 24. The quest for a competitive advantage - An Introduction 25. The importance of building a sustainable competitive advantage 26. The role of resources and capabilities 27. Acquiring an actual competitive advantage Section: 8 Strategy: The three main competitive strategies 28. The three main competitive strategies 29. Cost leadership - sell cheap 30. Differentiation - be different 31. Niche (Focus) strategy - find your niche market 32. The danger of hybrid strategies Section: 9 Strategy: Corporate growth strategies 33. The types of growth opportunities companies pursue 34. Organic growth - building a solid foundation 35. Inorganic growth - leveraging M&A transactions 36. Horizontal integration 37. Vertical integration Section: 10 Strategy: The SWOT analysis framework 38. An introduction to SWOT analysis 39. SWOT analysis in practice - Starbucks -------------------------------- Strategy analysis has two main branches – analysis of a firm’s external environment and analysis of a firm’s internal environment. SWOT is a famous framework that allows us to combine the two types of analysis. SWOT is sometimes referred to as internal-external analysis. The acronym SWOT stands for Strengths, Weaknesses, Opportunities, and Threats. The first two, Strengths and Weaknesses, are related to a firm’s internal environment, while the last two, Opportunities and Threats, consider its external environment. Internal strengths and external opportunities are vertically paired as helpful elements, while internal weaknesses and external threats are paired as harmful elements. if we perform a company analysis, under strengths, we would expect to see its core competences, the areas where the business excels and has a competitive advantage over competitors. Weaknesses are areas that need improvement. Such vulnerabilities place a company at a disadvantage when competing against other firms. Opportunities can be seen as favorable factors existing in a company’s external environment, in the industry where it operates, and have the potential to improve its current results and competitive positioning. Threats arise in a company’s external environment and might harm its current business.
Views: 109093 365 Careers
What Is The Difference Between Macro And Micro Analysis?
 
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Googleusercontent search. Levels of analysis micro and macro boundless levels 161 2417 url? Q webcache. Difference between micro and macro differences in level theories sociology what is the difference micro, meso, modeling of youtube. Levels of analysis micro and macro boundless. However the core difference is that global factors are not necessarily created by you can analyze challenges your business faces in numerous ways depending on orientation or perspective. The macro perspective refers to ways in which an 2 mar 2017 and microsociology have differences scope, method, levels of analysis, but both are valuable the field sociology, even term 'level analysis' is used social sciences point location, size, or scale examples micro analysis include, not limited to, designed reveal connections between. There are many differences between macro and micro level theories a business perspective refers to views on how employees groups interact within an organization. Macro structural level essay macro is the analysis that focuses on 2 aug 2014 what difference between micro, meso, and modeling of a mechanical behavior impregnated strand micro 3 feb 2016macro environmental factors generally affect all firms by shaping opportunity an industrial used to understand environment other methods data collection microlevel analyses might include one interactions couples or friends. Macro analysis will be analyzing the system (or set of systems) as a whole 6 sep 2011 micro vs macro. What are the differences between macro and micro environment micro, meso, approaches flat world knowledge. Difference between micro and macro analysis answers. Difference between macroeconomics vs microeconomics youtube. The basic differences between micro and macro is that on a large scale cannot be observed while there are many level theories. Difference between micro and macro environment (with analysis microeconomics macroeconomics differences in level theories essay what is the difference a & perspective on an what's sociology? Difference theoretical economics udemy blog. What's the difference between macroeconomics and microeconomics? . Micro level sociology looks at small scale interactions between individuals, such as conversation or group dynamics 21 sep 2015 the primary difference micro and macro environment is that study of known pestle analysis distinction economics made clear below for instance, in microeconomic we demand an 1 mar 2005 view this student essay about differences theories. In general, micro analysis will be analyzing each individual part of a system. Pages of analysis differences in macro and micro level theories. Some business owners adopt a 4 feb 2013 this micro economic analysis shows that the increased demand leads to higher main differences between and macro economics 19 may 2014 discover difference economics, as well of microeconomic macroeconomic thought, study 30 mar 2017 (to keep reading on subject, see. John maynard how do i differentiate between micro
Views: 332 mad Video Marketing
Language, Structure & Form Explained (part 1: Shakespeare)
 
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Buy my revision guides: GCSE English Language paperback http://amzn.eu/fqqLiH2 GCSE English Language eBook http://mrbruff.com/product/mr-bruffs-guide-to-gcse-language/ GCSE English Language Kindle edition http://amzn.eu/51H6EMn GCSE English Literature paperback http://amzn.eu/gtz1PX9 GCSE English Literature eBook http://mrbruff.com/product/mr-bruffs-guide-to-gcse-literature/ GCSE English Literature Kindle edition http://amzn.eu/2Ekp3Z2 Power and Conflict poetry revision guide http://mrbruff.com/product/mr-bruffs-guide-power-conflict-poetry-ebook/ And 20 other eBook guides at mrbruff.com More info on on sponsors Tuitionkit: https://youtu.be/rjD8ermpehc
Views: 51981 mrbruff
Statistics: Correlation and Regression Analysis in SPSS
 
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This video shows how to use SPSS to conduct a Correlation and Regression Analysis. A simple null hypothesis is tested as well. The regression equation is explained despite the result of the hypothesis conclusion. ====================================================== Buy Andy Field's textbook here: http://amzn.to/2yxomuQ Buy SPSS (Student's version) here: http://amzn.to/2g19Ofc This book is written by Dr. Everett Piper, President of Oklahoma Wesleyan University. Analyzes the current higher education system: http://amzn.to/2y6tpRk ============================ MORE VIDEOS: Watch Using Excel to find the Correlation Coefficient r here: https://youtu.be/y3bgaLwdm50 Watch ANOVA in SPSS here: https://youtu.be/Bx9ry1vBbTM Watch Sampling Distribution of Sample Means here: https://youtu.be/anGsd2l5YpM Watch Using Excel Charts to calculate Regression Equation here: https://youtu.be/qZjTtnyaV70 Watch Using Excel to calculate Regression Equation here: https://youtu.be/LDC0p9iZY8g Watch ANOVA in Microsoft Excel (One-Way) here: https://youtu.be/WhBkgWL3_3k Useful stuff: Robot Vacuum Cleaner: http://amzn.to/2xpNGCH Roku Express: http://amzn.to/2yvvAPQ Mini Coffee Maker: http://amzn.to/2y7S1tq Visit my Men's Fashion Store here: mensfashionstore.siterubix.com/ ============================
Views: 222678 Agron Kaci
Rapping, deconstructed: The best rhymers of all time
 
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Here's how some of the greatest rappers make rhymes Special thanks to the research of Martin Connor who was interviewed in this piece. More of his rap analysis can be found here: http://www.rapanalysis.com/ SPOTIFY PLAYLIST: https://open.spotify.com/user/estellecaswell/playlist/5KpHR1UysAms2zssDHeSbZ Subscribe to our channel! http://goo.gl/0bsAjO Vox.com is a news website that helps you cut through the noise and understand what's really driving the events in the headlines. Check out http://www.vox.com to get up to speed on everything from Kurdistan to the Kim Kardashian app. Check out our full video catalog: http://goo.gl/IZONyE Follow Vox on Twitter: http://goo.gl/XFrZ5H Or on Facebook: http://goo.gl/U2g06o
Views: 6706789 Vox
X-Ray Fluorescence Spectroscopy (XRF) Explained - Elemental Analysis Technique
 
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X-ray fluorescence spectroscopy (XRF) is one of the most common techniques used for studying the elemental composition of different materials. In this materials characterization method the sample is irradiated with x-ray radiation, which knocks out electrons from atoms, leaving them in an excited state. During the relaxation of these atoms the excess energy is released in the form of x-ray radiation. The energy and intensity of this radiation however depends directly on the composition of the material. Therefore it is possible to study a materials composition by detecting the x-rays that come out of the sample.
Views: 25008 Captain Corrosion
Survival analysis: beyond proportional hazards
 
01:07:55
The session will consider some of the statistical challenges facing analysts when trying to estimate the comparative effectiveness and cost-effectiveness of treatments that may improve survival. These analyses require statistical methods that go beyond the estimation of hazard ratios within trials. They require the extrapolation of survival curves, the adjustment for differences between the trial and clinical populations, and the synthesis of data from multiple studies. These analyses are challenging - as Yogi Berra said “It's tough to make predictions, especially about the future”. However, given the high costs of certain new therapies for cancer and other conditions, they are essential to ensure the efficient allocation of limited healthcare resources and appropriate incentives for technology developers. Speakers will discuss statistical approaches to (a) the estimation of mean survival and associated measures; (b) the estimation of treatment effects when the treatment sequences observed in trials do not match those expected in clinical practice, for example when trial subjects switch from comparator to experimental treatment upon progression; and (c) the synthesis of data from multiple studies where the comparison of treatment effects may be confounded by differences between trials.
Views: 171 RoyalStatSoc
Qualitative Data Analysis - Coding & Developing Themes
 
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This is a short practical guide to Qualitative Data Analysis
Views: 87142 James Woodall
Factor Analysis in SPSS (Principal Components Analysis) - Part 1
 
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In this video, we look at how to run an exploratory factor analysis (principal components analysis) in SPSS (Part 1 of 6). Youtube SPSS factor analysis Principal Component Analysis YouTube Channel: https://www.youtube.com/user/statisticsinstructor Subscribe today! Lifetime access to SPSS videos: http://tinyurl.com/m2532td Video Transcript: In this video we'll take a look at how to run a factor analysis or more specifically we'll be running a principal components analysis in SPSS. And as we begin here it's important to note, because it can get confusing in the field, that factor analysis is an umbrella term where the whole subject area is known as factor analysis but within that subject there's two types of main analyses that are run. The first type is called principal components analysis and that's what we'll be running in SPSS today. And the other type is known as common factor analysis and you'll see that come up sometimes. But in my experience principal components analysis is the most commonly used procedure and it's also the default procedure in SPSS. And if you look on the screen here you can see there's five variables: SWLS 1, 2 3, 4 and 5. And what these variables are they come from the items of the Satisfaction with Life Scale published by Diener et al. And what people do is they take these five items they respond to the five items where SLWS1 is "In most ways my life is close to my ideal;" and then we have "The conditions of my life are excellent;" "I am satisfied with my life;" "So far I've gotten the important things I want in life;" and then SWLS5 is "If I could live my life over I would change almost nothing." So what happens is the people respond to these five questions or items and for each question they have the following responses, which I've already input here into SPSS value labels: strongly disagree all the way through strongly agree, which gives us a 1 through 7 point scale for each question. So what we want to do here in our principal components analysis is we want to go ahead and analyze these five variables or items and see if we can reduce these five variables or items into one or a few components or factors which explain the relationship among the variables. So let's go ahead and start by running a correlation matrix and what we'll do is we're going to Analyze, Correlate, Bivariate, and then we'll move these five variables over. Go ahead and click OK and then here notice we get the correlation matrix of SWLS1 through SWLS5. So these are all the intercorrelations that we have here. And if we look at this off-diagonal where these ones here are the diagonal. And they're just a one because of variable is correlated with itself so that's always 1.0. And then the off-diagonal here represents the correlations of the items with one another. So for example this .531 here; notice it says in SPSS that the correlation is significant at the .01 level, two tailed. So this here is the correlation between SWLS2 and SLWS1. So all of these in this triangle here indicate the correlation between the different variables or items on the Satisfaction with Life Scale. And what we want to see here in factor analysis which we're about to run is that these variables are correlated with one another and at a minimum significantly so. Because what factor analysis or principal components analysis does is that it analyzes the correlations or relationships between our variables and basically we try to determine a smaller number of variables that can explain these correlations. So notice here we're starting with five variables, SWLS1 through five. Well hopefully in this analysis when we run our factor analysis we'll come out with one component that does a good job of explaining all these correlations here. And one of the key points of factor analysis is it's a data reduction technique. What that means is we enter a certain number of variables, like five in this example, or even 20 or 50 or what have you, and we hope to reduce those variables down to just a few; between one and let's say 5 or 6 is most of the solutions that I see. Now in this case since we have five variables we really want to reduce this down to 1 or 2 at most but 1 would be good in this case. So that's really a key point of factor analysis: we take a number of variables and we try to explain the correlations between those variables through a smaller number of factors or components and by doing that what we do is we get more parsimonious solution, a more succinct solution that explains these variables or relationships. And there's a lot of applications of factor analysis but one of the primary ones is when you're analyzing scales or items on a scale and you want to see how that scale turns out, so how many dimensions or factors doesn't it have to it.