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: 17776 Shmoop
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: 67445 ZieneMottiar
Please watch: "Why Python ?" https://www.youtube.com/watch?v=a3sdWlAxO24 --~--
Views: 129 Test My ChatBot
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 Instagram: https://instagram.com/ruleoneinvesting 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,
Views: 163581 Phil Town's Rule #1 Investing
Buy my revision guides in paperback on Amazon*: Mr Bruff’s Guide to GCSE English Language https://amzn.to/2GvPrTV Mr Bruff’s Guide to GCSE English Literature https://amzn.to/2POt3V7 AQA English Language Paper 1 Practice Papers https://amzn.to/2XJR4lD Mr Bruff’s Guide to ‘Macbeth’ https://amzn.to/2GxYO5p Mr Bruff’s Guide to ‘An Inspector Calls’ https://amzn.to/2GxXJKT Power and Conflict poetry guide (ebook) https://bit.ly/2PS8bw6 Mr Bruff’s Guide to ‘Romeo and Juliet’ https://amzn.to/2GvL0s5 Mr Bruff’s Guide to Grammar: https://amzn.to/2GJCBSj Mr Bruff’s Guide to ‘Jekyll and Hyde’: https://amzn.to/2SYOFQA Mr Bruff’s Guide to ‘The Sign of Four’: https://amzn.to/2Sbs1EN Mr Bruff’s Guide to ‘Much Ado About Nothing’: https://amzn.to/2T6s98L Mr Bruff’s Guide to ‘Great Expectations’: https://amzn.to/2S6OuCY Mr Bruff’s Guide to A’ Level English Literature: https://amzn.to/2T23cef Mr Bruff’s Guide to A’ Level English Language (ebook): https://bit.ly/2LwTuhO Mr Bruff’s Guide to ‘Animal Farm’: https://amzn.to/2GshZh0 Mr Bruff’s Guide to ‘The Tempest’ https://amzn.to/2ScmQ7t Mr Bruff’s Guide to ‘Othello’: https://amzn.to/2QH9fbK Mr Bruff’s Guide to ‘The Curious Incident of the Dog in the Night Time: https://amzn.to/2ScMzfY Mr Bruff’s Guide to ‘The Great Gatsby’ https://amzn.to/2QEHEaU Mr Bruff’s Guide to ‘Frankenstein’ https://amzn.to/2Gsj7Bg Mr Bruff’s Guide to ‘Jane Eyre’ https://amzn.to/2Sah46d Mr Bruff’s Guide to ‘The History Boys’ https://amzn.to/2RaSIvX Mr Bruff’s Guide to ‘Spies’ https://amzn.to/2R9f4ho Mr Bruff’s Guide to ‘Pride and Prejudice’ (ebook) https://bit.ly/2A9SWdc *Some of these links are affiliate links, which give me a small commission that helps to support this Youtube channel. The cost remains the same to you, but if you don’t want to use the affiliate link you can simply search for the products yourself on Amazon. More info on Tuitionkit: https://youtu.be/7ecjBwV6Ydg
Views: 45207 mrbruff
Science and Engineering Practice 3: Analyzing and Interpreting Data Paul Andersen explains how scientists analyze and interpret data. Data can be organized in a table and displayed using a graph. Students should learn how to present and evaluate data. Intro Music Atribution Title: I4dsong_loop_main.wav Artist: CosmicD Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/ Creative Commons Atribution License
Views: 63275 Bozeman Science
Purchase the spreadsheet (formulas included!) that's used in this tutorial for $5: https://gum.co/satisfactionsurvey ----- Soar beyond the dusty shelf report with my free 7-day course: https://depictdatastudio.teachable.com/p/soar-beyond-the-dusty-shelf-report-in-7-days/ Most "professional" reports are too long, dense, and jargony. Transform your reports with my course. You'll never look at reports the same way again.
Views: 376776 Ann K. Emery
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: 8815 David Hunter
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; *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. 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 Nb: 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. Text and video (including audio) © Kent Löfgren, Sweden
Views: 727356 Kent Löfgren
These videos were created to accompany a university course, Numerical Methods for Engineers, taught Spring 2013. The text used in the course was "Numerical Methods for Engineers, 6th ed." by Steven Chapra and Raymond Canale.
Views: 80434 Jacob Bishop
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: 192645 IELTS Master
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: 114073 Global Cycling Network
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: 72736 Analytics University
This video explains the differences between parametric and nonparametric statistical tests. The assumptions for parametric and nonparametric tests are discussed including the Mann-Whitney Test, Kruskal-Wallis Test, Wilcoxon Signed-Rank Test, and Friedman’s ANOVA.
Views: 157937 Dr. Todd Grande
This tutorial provides an overview of statistical analyses in the social sciences. It distinguishes between descriptive and inferential statistics, discusses factors for choosing an analysis procedure, and identifies the difference between parametric and nonparametric procedures.
Views: 232343 The Doctoral Journey
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: 340910 americanbiotech
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: 59600 UNICEF Innocenti
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: 547548 Core-A Gaming
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: 200686 Ian Johnson
On Udemy: https://www.udemy.com/user/365careers/ On YouTube: https://www.youtube.com/365careers On Facebook: https://www.facebook.com/365careers/ On the web: http://www.365careers.com/ On Twitter: https://twitter.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: 83122 365 Careers
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: 513027 Phil Chan
Data Science is the combination of statistics, mathematics, programming, problem solving, capturing data in ingenious ways, the ability to look at things differently, and the activity of cleansing, preparing, and aligning the data. Complete Video English - https://goo.gl/WJfPeq Complete Video Tamil - https://goo.gl/kaWumR YouTube channel link www.youtube.com/atozknowledgevideos Website http://atozknowledge.com/ Technology in Tamil & English
Views: 17432 atoz knowledge
In this video, 4.04 – Audit Evidence: Analytical Procedures – Lesson 1, learn how analytical procedures help an auditor plan for and review an audit, and also help the auditor check the results of substantive tests of details for reasonableness. Roger Philipp, CPA, CGMA, gives us a good visual when he states to think of tests of details as ‘the trees’ and analytical procedures as ‘the forest.’ An auditor is required to conduct analytical procedures at the beginning of an audit during the audit planning phase and at the end of the audit as part of an overall review. Analytical procedures are optional but recommended during substantive testing. In this section, Roger defines analytical procedures, gives some examples, and introduces the handy mnemonic CRAFT for remembering how an auditor may ‘craft’ analytical procedures: Client vs. Industry, Related Accounts, Actual vs. Budget, Financial vs. Non-Financial, and This year vs. Prior. He ends with the following question: Which financial statement, balance sheet or income statement, is better suited for applying analytical procedures, and why? Hint – consider the statement which has more reliably predictable relationships between accounts. See if you get the answer correct as Roger answers this question and more. Connect with us: Website: https://www.rogercpareview.com Blog: https://www.rogercpareview.com/blog Facebook: https://www.facebook.com/RogerCPAReview Twitter: https://twitter.com/rogercpareview LinkedIn: https://www.linkedin.com/company/roger-cpa-review Are you accounting faculty looking for FREE CPA Exam resources in the classroom? Visit our Professor Resource Center: https://www.rogercpareview.com/professor-resource-center/ Video Transcript Sneak Peek: Okay, let's talk about analytical procedures. Now, with analytical procedures, remember over here we said, audit procedures. Two types of details of accounts transactions, balances and disclosures and analytic procedures, that's what we're looking at now. Now what are analytical procedures? That's part of your ICORRIIA. Analytical procedures are the study of data comparisons and relationships. How information's compare or relate relationships. This is based on the anticipation or expectation theory. This deals with ratios, ratio analysis. So what we're looking at is how does the number compare? How does it relate based on the expectation? What did you get versus what did you expect to get? That tells us that you know what? This account may have changed by more or less than we expected. So we're going to do this at the beginning of the audit. We're going to do this at the end of the audit. Because at the beginning, we're going to look at all the clients transactions. So for example, here's let's say X1, here's X2, dollar change, percentage change and we're going to set up maybe parameters. We're going to say, we're looking at all the changes greater than 10,000 dollars and five percent. Now notice, this is because you may have a change in this account by one million dollars but it's only one percent. Well that's reasonable. You may have another that's a 42 percent change but it's only 27 dollars, who cares? Immaterial. What you’re looking for is a 17,000 dollar change. That's maybe nine percent. You know what? That exceeds both 10,000 and five percent. That's something that maybe we didn't expect. So when planning the audit you sit down and you go, you know what? In looking at the changes, this is current year, prior year, PY. So here's current year, here's PY which means prior year. You know what? This change is bigger than we expected, then we anticipated. So what we need to do is go back and go, you know? It changed by more than we thought. Is that reasonable? Or could there be a mistake? At the end of the audit you do the same thing. Because as I mentioned earlier, this is called test of details. This is when you're looking at the detail and you're looking but the problem is you get lost when you can't see the forest for the trees. Because you're in the detail of the trees. Step back and see the whole forest and go, in the details of the trees, this one transaction, let me ask questions, let me confirm, let me observe, let me recalculate, let me re-perform it, let me look at the document, look at the assets, let me do that on this one transaction but when you step back and the whole account balance you go, does this make sense? Does this change seem reasonable? That's comparing. That is relationships. So the comparison, relationships, anticipation, expectation, ratio analysis. That's an important concept, ratio analysis.
Views: 72170 Roger CPA Review
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: 440952 CrashCourse
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: 195214 TARDIStennant
A Wireshark tutorial for beginners that shows users how to track network activity, view specific frame, tcp, ip and http information, view specific packets being sent and received on the network, view information within those packets and spot malicious or suspicious network behavior. For behind the scenes and exclusive content: https://www.instagram.com/ansonalex.c0m/ Published by Anson Alexander from http://AnsonAlex.com.
Views: 763810 Anson Alexander
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: 562707 Quantitative Specialists
Excel file: https://dl.dropboxusercontent.com/u/561402/TTEST.xls In this video Paul Andersen explains how to run the student's t-test on a set of data. He starts by explaining conceptually how a t-value can be used to determine the statistical difference between two samples. He then shows you how to use a t-test to test the null hypothesis. He finally gives you a separate data set that can be used to practice running the test. Do you speak another language? Help me translate my videos: http://www.bozemanscience.com/translations/ Music Attribution Intro Title: I4dsong_loop_main.wav Artist: CosmicD Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/ Creative Commons Atribution License Outro Title: String Theory Artist: Herman Jolly http://sunsetvalley.bandcamp.com/track/string-theory All of the images are licensed under creative commons and public domain licensing: 18.104.22.168.2. Critical Values of the Student’s-t Distribution. (n.d.). Retrieved April 12, 2016, from http://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm File:Hordeum-barley.jpg - Wikimedia Commons. (n.d.). Retrieved April 11, 2016, from https://commons.wikimedia.org/wiki/File:Hordeum-barley.jpg Keinänen, S. (2005). English: Guinness for strenght. Retrieved from https://commons.wikimedia.org/wiki/File:Guinness.jpg Kirton, L. (2007). English: Footpath through barley field. A well defined and well used footpath through the fields at Nuthall. Retrieved from https://commons.wikimedia.org/wiki/File:Footpath_through_barley_field_-_geograph.org.uk_-_451384.jpg pl.wikipedia, U. W. on. ([object HTMLTableCellElement]). English: William Sealy Gosset, known as “Student”, British statistician. Picture taken in 1908. Retrieved from https://commons.wikimedia.org/wiki/File:William_Sealy_Gosset.jpg The T-Test. (n.d.). Retrieved April 12, 2016, from http://www.socialresearchmethods.net/kb/stat_t.php
Views: 498673 Bozeman Science
I demonstrate how to perform an analysis of covariance (ANCOVA) in SPSS. The first part of the series is relevant to the ANCOVA tested through the conventional approach to doing so by getting SPSS to estimate adjusted means through the GLM univariate utility. In the second part of the series, I demonstrate the exact correspondence between ANCOVA and multiple regression. NB: The results of the analysis in this series found that males appear to have larger cranial capacities than females, even after controlling for the effects of body size. However, it should be important to emphasize that research has found that there are little to no general mean differences in IQ between males and females. Furthermore, there is neuroanatomical research to suggest that female brains appear to have more neurons per cubic cm than male brains. Thus, the difference in cranial capacity/brain size between the sexes may be counteracted by the differences in neuronal density.
Views: 233699 how2stats
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: 114582 LinkedIn Learning
Likert Scale: http://en.wikipedia.org/wiki/Likert_scale R: http://www.r-project.org/
Views: 213693 Alan Cann
When you are trying to figure out what problem to actually be solving before you dive deep into the software requirements, you want to by analyzing the business process and to do that you create both a visual and a textual business process model. A Business Process Model is a commonly used business analysis technique that captures how a business process works and how individuals from different groups work together to achieve a business goal. Let’s look at what a business process model is, how you’d go about creating one, and why it’s important to model your process both visually and textually. And go here to download the Business Process Template (it's free): https://www.bridging-the-gap.com/bptemplate/
Views: 6961 Bridging the Gap
MDS (multi-dimensional scaling) and PCoA (principal coordinate analysis) are very, very similar to PCA (principal component analysis). There really only one small difference, but that difference means you need to know what you're doing if you're going to use MDS effectively. This video make sure you learn what you need to know to use MDS and PCoA. For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/
Views: 21816 StatQuest with Josh Starmer
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: 20584 Jos van Kreij
This is just a few minutes of a complete course. Get full lessons & more subjects at: http://www.MathTutorDVD.com. In this lesson we will cover the difference between descriptive and inferential statistics.
Views: 98517 mathtutordvd
pharmaceutical quality control in the laboratories of pharmaceutical industry, required validated analytical method as per requirement of the drug regulatory affair bodies in their region to fulfill the pharmaceutical regulatory affairs requirements to provide quality pharmaceutical products for general public use.
Views: 27159 Prestige Pharmacy Profession
HELP ME MAKE MORE VIDEOS: http://www.patreon.com/nerdwriter VISIT WISECRACK HERE: http://bit.ly/1xPTaB7 TUMBLR: http://thenerdwriter.tumblr.com TWITTER: https://twitter.com/TheeNerdwriter Email me here: [email protected] SOURCES: Barton Swaim, “How Donald Trump’s language works for him” (via The Washington Post) September 15, 2015 https://www.washingtonpost.com/news/the-fix/wp/2015/09/15/how-trump-speak-has-pushed-the-donald-into-first-place/ Emily Atkin, “What Language Experts Find So Strange About Donald Trump” (via ThinkProgress) 2015 http://thinkprogress.org/politics/2015/09/15/3701215/donald-trump-talks-funny-2/ Matt Viser, “For presidential hopefuls, simpler language resonates” (via The Boston Globe) October 20, 2015 https://www.bostonglobe.com/news/politics/2015/10/20/donald-trump-and-ben-carson-speak-grade-school-level-that-today-voters-can-quickly-grasp/LUCBY6uwQAxiLvvXbVTSUN/story.html Jack Shafer, “Donald Trump Talks Like a Third-Grader” (via Politico) 2015 http://www.politico.com/magazine/story/2015/08/donald-trump-talks-like-a-third-grader-121340 ALL THE MUSIC COMES FROM HERE: https://soundcloud.com/bluewednesday
Views: 8679612 Nerdwriter1
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: 119764 Stomp On Step 1
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: 182208 365 Careers