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How To Calculate and Understand Analysis of Variance (ANOVA) F Test.
 
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Visual tutorial on how to calculate analysis of variance (ANOVA) and how to understand it too. The tutorial includes how to interpret the results of an Anova test, f test and how to look up values in the f distribution table. The Anova example is for a one way anova test. I am rounding in the video, so if you are doing your own calculations you will not get the same exact numbers. Like MyBookSucks on Facebook! http://www.facebook.com/PartyMoreStudyLess PlayList on ANOVA http://www.youtube.com/course?list=EC3A0F3CC5D48431B3 PlayList On TWO ANOVA http://www.youtube.com/playlist?list=PLWtoq-EhUJe2TjJYfZUQtuq7a0dQCnOWp Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 763962 statisticsfun
Analysis of Variance (ANOVA)
 
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A description of the concepts behind Analysis of Variance. There is an interactive visualization here: http://demonstrations.wolfram.com/VisualANOVA/ but I have not tried it, and this: http://rpsychologist.com/d3-one-way-anova has another visualization
Views: 489043 J David Eisenberg
One Way ANOVA
 
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Demonstration of how to conduct a One-Way ANOVA by hand.
Views: 775142 ArmstrongPSYC2190
14. Biostatistics lecture - Analysis of variance ANOVA
 
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This biostatistics lecture under bioinformatics tutorial explains what is analysis of variance or ANOVA and how it is calculated. For more information, log on to- http://shomusbiology.weebly.com/ Download the study materials here- http://shomusbiology.weebly.com/bio-materials.html
Views: 63067 Shomu's Biology
Analysis of Variance (ANOVA). Part I
 
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The Analysis of Variance (ANOVA) is a hypothesis test to compare the means of more than two populations. For more free math videos, visit: http://www.professorserna.com Here, I explain the steps of the ANOVA Complete Randomized Design: 1)Setting up the Null hypothesis that all the means are equal and the Alternative hypothesis that at least two mean differ. 2) Calculation of the test statistics (the actual calculations are done in the next video of this series). 3) Finding the rejection region using the F distribution. 4) Making the decision whether to reject or not to reject Ho and 5) Writing the conclusion. If you liked this video, please, write a review about me in Google: http://bit.ly/2hP2S3g Share this video: https://youtu.be/7vLp8MDwgcE To be notified about new videos, subscribe to my channel: https://bit.ly/2gmvtIO contact me here: https://goo.gl/vnShib
Views: 179384 ProfessorSerna
Excel - One-Way ANOVA      Analysis Toolpack
 
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Many more great Excel tutorials linked below: http://www.youtube.com/playlist?list=PL8004DC1D703D348C&feature=plcp Be sure to watch my other Excel tutorial videos on my channel, including more advanced techniques and many useful and practical ones. Be sure to Subscribe and Comment. Technically you should say Fail to Reject Ho because you have determined there is a lack of evidence against Ho. You have not proven Ho in any significant way. With that said, many introductory courses teach students that they can conclude that we Accept Ho. Please be aware of the nuance regardless of how you choose to phrase the conclusion. Reject Ho, however, is a stronger statement that we can justifiably make using the laws of probability and the level of significance of the test. When we Reject Ho we are concluding that there is enough evidence against Ho with the state level of significance used. We are willing to accept the chance of making a Type I Error, but we are very clear about the probability of its occurrence, i.e., it is equal to alpha (at least nominally).
Views: 253095 Jalayer Academy
Variance Analysis
 
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Variance Analysis, in budgeting (or management accounting in general), is a tool of budgetary control by evaluation of performance by means of variances between budgeted amount, planned amount and the actual amount incurred/sold. Variance analysis can be carried out for both costs and revenues. This video explains how.
Views: 69992 James Slocombe
Variance Analysis   Part 1 of 3
 
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In this series of managerial accounting videos we learn to compute: a.) Direct materials price and quantity variances b.) Direct labour rate and efficiency variances c.) Variable overhead spending and efficiency variance This video was prepared for the Khan Academy Talent search. #khanacademytalentsearch
Views: 43060 Tony Bell
Standard Costs and Variance Analysis
 
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This video discusses the use of standard costs in Managerial Accounting. It also provides a comprehensive example to illustrate how standard costs are useful in calculating the price variance and quantity variance. Edspira is your source for business and financial education. To view the entire video library for free, visit http://www.Edspira.com To like us on Facebook, visit https://www.facebook.com/Edspira Edspira is the creation of Michael McLaughlin, who went from teenage homelessness to a PhD. The goal of Michael's life is to increase access to education so all people can achieve their dreams. To learn more about Michael's story, visit http://www.MichaelMcLaughlin.com To follow Michael on Facebook, visit https://facebook.com/Prof.Michael.McLaughlin To follow Michael on Twitter, visit https://twitter.com/Prof_McLaughlin
Views: 212023 Edspira
How to Calculate ANOVA with Excel (Analysis of Variance)
 
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Visual explanation of how to calculate ANOVA using Microsoft Excel. Tutorial provides step by step instructions on how to conduct an ANOVA Test using Excel. Like MyBookSucks on Facebook! http://www.facebook.com/PartyMoreStudyLess PlayList On ANOVA http://www.youtube.com/course?list=EC3A0F3CC5D48431B3 Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 356637 statisticsfun
12-2 ANOVA – Variance Between and Within
 
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When measuring groups with ANOVA, there are two sources of variance: between and within. Variance between groups is due to actual treatment effect plus differences due to chance (or error). Variance within the groups is due only to chance (or error). This is the variance that we are analyzing. Table of Contents: 00:30 - Definitions for Analysis of Variance 01:42 - Step 1: Omnibus Test 02:42 - The F Ratio 03:22 - Logic of Analysis of Variance 04:13 - Distribution of F Ratios 05:41 - Examples of Between and Within 07:56 - Step 2: Post Hoc Test 09:02 - Post Hoc Tests in SPSS 10:39 - Example 11:46 - Example
Views: 12408 Research By Design
One-Way ANOVA
 
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statisticslectures.com - where you can find free lectures, videos, and exercises, as well as get your questions answered on our forums!
Views: 225681 statslectures
How To... Perform a One-Way ANOVA Test (By Hand)
 
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Compare the means of three or more samples using a one-way ANOVA (Analysis of Variance) test to calculate the F statistic. This video shows one method for determining F using sums of squares.
Views: 138308 Eugene O'Loughlin
ANOVA: One-way analysis of variance
 
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ANOVA: Analysis Of Variance Hey guys it looks like the audio might only be coming through the left channel on this one. Apologies for any inconvenience! Downloadable ANOVA spreadsheet: http://zstatistics.files.wordpress.com/2011/07/anova-spreadsheet.xlsx 0:00 Introduction 0:48 Variance and SST 1:40 Exercise 1: Finding SST 3:09 One-way ANOVA 4:48 SSW and SSB 8:10 Exercise 2: Finding SSW and SSB 9:15 F-test 11:45 MS Excel aid
Views: 31866 zedstatistics
Calcuating Budget Variances
 
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In this video, we explain and illustrate with a simple example the concept of budget variances.
Views: 28052 tutor2u
Variance Analysis, Master (Static), Flexible and Actual Budgets (Cost Accounting Tutorial #43)
 
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70% Off the Complete Crash Course on Udemy: http://bit.ly/2Dhip74 Variance analysis is a tricky topic near the end of our Intro to Managerial Accounting course. We'll discuss different types of variances including price variances and usage variances along with how they're derived from the Master (static) budget, flexible budget and actual results. Website: http://www.notepirate.com Follow us on Facebook: https://www.facebook.com/pages/Note-Pirate/514933148520001?ref=hl Follow us on Twitter: http://twitter.com/notepirate We appreciate all of the support you guys have given us. Be apart of the mission to help us reach more students by subscribing, thumbs upping and adding the videos to your favorites!
Views: 45298 Notepirate
CIMA P1 Variance analysis - Analysis of variances
 
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CIMA P1 Variance analysis - Analysis of variances Free lectures for the CIMA P1 Exams Management Accounting
Views: 4008 OpenTuition
Overhead Variances - Lesson 1
 
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“Now let’s talk about the UGLY variances, which are the overhead variances!” In the video, 5.03 - Overhead Variances – Lesson 1, Roger Philipp, CPA, CGMA, reviews the components of manufacturing inventory which includes, direct materials, direct labor and factory overhead. All of these components can be analyzed for spending, efficiency and volume variances. Roger also emphasizes the flexible budget equation, which is the basis for all overhead variance analysis. Going into an example from the course BEC textbook, he describes a situation with an allocation base of 100,000 direct labor hours at budgeted production level, budgeted fixed rent of $400,000 and budgeted variable cost of $1 in electricity for each direct labor hour. Of course Roger plugs these budgeted numbers into the flexible budget equation, then goes into the actuals: fixed rent was not-so-fixed at $390,000 and electricity ended up costing $1.01 an hour. Most importantly, actual direct labor hours is 97,000 but standard direct labor hours at budget for the actual level of production is 96,000. Understanding the last point is important, so Roger writes it up on the whiteboard, and warns us we’ll be using all of these direct labor hour numbers in the upcoming variance analysis! 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: OK, now let's talk about the ugly variances, which are the overhead variances. And this is something that even though you just studied it in school, you probably just prayed that the exam wouldn't be tough, and you hopefully got through the exam. What we're looking at here with overhead... Now remember with overhead we said we've got direct materials, direct labor and factory overhead. With overhead we have spending, efficiency, volume. Something that's important to understand is all of your overhead variance analysis is done using the flexible budget equation. What was the flexible budget equation? Total cost equals fixed plus variable times X. So as we go through and we look at these, we're gonna be looking at fixed plus variable times X, where X is gonna be changing as we go across.
Views: 35503 Roger CPA Review
ANOVA, Multiple Comparisons & Kurskal Wallis in R | R Tutorial 4.6 | MarinStatsLectures
 
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Analysis Of Variance (ANOVA), Multiple Comparisons & Kurskal Wallis in R ; Dataset: https://bit.ly/2RNeR0f ANOVA Explanation: https://goo.gl/QfQv9b More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT How to conduct one way Analysis of Variance (ANOVA) in R, ANOVA Pairwise Comparison in R, (Multiple Comparisons in R), and Kruskal Wallis one-way ANOVA in R: ►►In this Tutorial you will learn to use various commands to : ► Conduct one way analysis of variance ANOVA test in R ►View ANOVA table in R ►Produce a visual display for the pair-wise comparisons of the analysis of variance in R ► Conduct multiple comparisons/ANOVA pair-wise comparisons in R ► Produce Kruskal-Wallis one-way analysis of variance using ranks with R Statistical Software. ▶︎To access and download the dataset visit https://www.statslectures.com/ ■Table of Content 0:00:12 when to use one-way analysis of variance (ANOVA) 0:00:37 how to conduct ANOVA in R using the "aov" command 0:00:42 how to access the help menu in R for ANOVA commands 0:00:52 how to create a boxplot in R 0:01:42 how to view ANOVA table in R using "summary" command 0:02:07 how to ask R to let us know what is stored in an object using the "attributes" command. 0:02:23 how to extract certain attributes from an object in R using the dollar sign ($) 0:02:48 how to conduct multiple comparisons/pair-wise comparisons for the analysis of variance in R using the "TukeyHSD" command 0:03:17 how to produce a visual display for the pair-wise comparisons of the analysis of variance in R using "plot" command 0:03:50 how to produce Kruskal-Wallis one-way analysis of variance using ranks in R using the "kruskal.test" command 0:03:56 when is it appropriate to use Kruskal-Wallis one-way analysis of variance for data This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. ▶︎▶︎ Watch More ▶︎ANOVA Use and Assumptions https://youtu.be/_VFLX7xJuqk ▶︎ Understanding Sum of Squares in ANOVA ,concept of analysis of variance, and ANOVA hypothesis testing https://youtu.be/-AeU4y2vkIs ▶︎ ANOVA Test Statistic and P Value: https://youtu.be/k-xZzEYL8oc ▶︎ ANOVA & Bonferroni Multiple Comparisons Correction https://youtu.be/pscJPuCwUG0 ▶︎ Two Sample t test for independent groups https://youtu.be/mBiVCrW2vSU ▶︎ Paired t test https://youtu.be/Q0V7WpzICI8 Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
How to run Analysis of Variance - ANOVA - using Excel
 
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This video describes how to run an analysis of variance (ANOVA) test using Excel. An ANOVA is a statistical test used to determine if there is a significant difference in mean scores between more than two groups.
Views: 9623 Chris Olson
#1 Standard Costing (Introduction) & Material Variance Analysis ~  [For CA/CS/CMA/M.Com/B.Com]
 
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Explained the concept and logic of Standard Costing. An ICAI exam question used to explained the concept of ascertainment of Direct Material Cost Variances without any formula to remember in a very easy away by simply applying the logic. Connect on Facebook : https://www.facebook.com/ca.naresh.aggarwal Download Assignments: https://drive.google.com/drive/folders/0BzfDYffb228JNW9WdVJyQlQ2eHc?usp=sharing
Views: 64478 CA. Naresh Aggarwal
Analysis of Variance in Excel
 
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How to perform an analysis of variance (ANOVA) and multiple comparison of means (Tukey's HSD) using Excel. References to textbook are to "Elementary Statistics in Social Research", 10e, ISBN: 0-205-45958-7. In the 11th edition, critical values of F can be found on p.521.
Views: 615 mrsethwright
One-way ANOVA and Post Hoc Test Using SPSS
 
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This video describes two methods of performing a one-way ANOVA using SPSS, including how to interpret post hoc test results.
Views: 130130 Dr. Todd Grande
Combined analysis of variance | Tests for homogeneity of variances | Bartlett's test | F test
 
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In this first part of the video, an important technique has been described which is used to do the analysis for series of experiments. However, this part contains information regarding the tests for homogeneity of variances. Two tests are commonly used for testing homogeneity of variances which include: 1. F test 2. Bartlett's test This video contains full description how to use these tests with very easy to use excel tool that can be downloaded by clicking the below link. Download Homogeneity tests excel tool: https://1drv.ms/x/s!As-fQhyw8QbtghvVL3JnDWjwGjp8 Download EMS and EDF excel tool: https://1drv.ms/x/s!As-fQhyw8Qbtgh3GUuVKY_UlCSRC Suggested videos: Simple RCB Design: https://www.youtube.com/watch?v=7oPoTXRFVwE&t=260s Orthogonal Polynomial Contrast: https://www.youtube.com/watch?v=1lituslQYDI&t=1s Increase file size to import large data in MSTAT C: https://www.youtube.com/watch?v=2rS9A2tvP5s&t=94s ______________________________________________________________ Follow on G+: https://plus.google.com/u/1/101269397606526645442 Like Facebook page: https://www.facebook.com/AgronInfoTech/?ref=bookmarks Follow on Twitter: https://twitter.com/AgronInfoTech ___________________________________________________________ If you have any question please comment below. Thanks for watching this video.
Views: 758 AGRON Info-Tech
MANOVA in SPSS (Multivariate Analysis of Variance) - Part 1
 
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How to run and interpret the results of a MANOVA in SPSS is covered in this video (part 1). Video Transcript: So let's go ahead and get started with our problem in SPSS. Now in SPSS you can see here we have three variables, gender, where we have males and females; I can turn those value labels off for a minute. We have males and females given by 1s and 2s, and we have our two dependent variables, empathic concern and cognitive perspective taking. So notice here we have to have at least two variables once again for MANOVA, so you can see those here, and then we have our grouping variable which is gender. So let's go ahead and run the MANOVA. So to do that we want to go to Analyze and then General Linear Model and then Multivariate. And here the Multivariate dialog box opens. We're going to take our two dependent variables, empathic concern and perspective-taking, move those over to the dependent variables box, and I just pressed and held the control key to grab both of those at once, and then move gender to Fixed Factor(s). And then let's go ahead and go to Options, select gender and move that over to the Display Means for box, check on Descriptive statistics, Estimates of effect size, and Homogeneity tests, and then click Continue and then go ahead and click OK. Next we get our results out, and you can see here our first table shows us our Between-Subjects Factors, and here we have gender, 1 and 2, 1 is male 2 is female, and notice we have 15 adolescents in each group. Next is our Descriptive Statistics table. We have empathic concern for males and females, so here's these two means, and notice in the sample, let's just go ahead and go through this and ask yourself, which of the two genders scored higher on empathic concern? Now we don't know if this is significant yet, but just descriptively, just visually inspecting. Notice that females scored higher than males by 8.27 points, approximately, on empathic concern. And then here on perspective-taking, we can see that females scored about almost three points higher on perspective-taking than did males. OK next we have Box's Test for Equality of Covariance Matrices. Now this test tests an assumption of the MANOVA, which is that the variance-covariance matrices, also referred to as the covariance matrices, as you see here, are equal for the two groups. Now we're going to have a separate video on this assumption to look at it in more detail, but basically in a nutshell it's very similar to the equal variance assumption for the ANOVA; this assumption is the multivariate generalization or extension of the assumption of equal variances for the ANOVA, it's testing the corresponding variances and covariances are equal for the two groups. But for now all you really need to know is that we want to look at our p-value here and we hope that this is greater than .05. But in fact this test, Box's test the equality of covariance matrices, is so sensitive to departures from non- normality, that a lot of people will even use a standard of p is greater than .001. So, basically, we want this result to be not significant. So if we use the more lenient standard and use p is greater than .001, then you can clearly see, well at either level (.05 or .001), this is not significant. So that provides us some evidence that the variance-covariance matrices are equal for the two groups. And that's an assumption of MANOVA, we want that to hold. So, unlike our significance tests on means, we want this to be greater than .05 or greater than .001. And in that other video I'll go into more detail, some of the subtleties of that, and the research findings as well, and what we can do if we do have a p-value that's less than say, .001, for Box's test. OK next we'll go to our Multivariate Tests box MANOVA Multivariate analysis of variance MANOVA in SPSS Wilk's Lambda Pillai Trace DFA Hotelling's T-squared For more on inferential Statistics: https://www.udemy.com/inferential-statistics-spss/ Lifetime access to SPSS videos: http://tinyurl.com/m2532td Channel Description: https://www.youtube.com/user/statisticsinstructor For step by step help with statistics, with a focus on SPSS. Subscribe today! YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Sample size calculation for one-way analysis of variance using Stata®
 
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Discover how to do a sample size calculation for a one-way analysis of variance using Stata. Created using Stata 13; new features available in Stata 14. Copyright 2011-2017 StataCorp LLC. All rights reserved.
Views: 3898 StataCorp LLC
SOCIAL SCIENCE RESEARCH METHODS - ANOVA - ANALYSIS OF VARIANCES
 
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CEC/UGC: Social Science - 2, Education,Psychology, Home Science and related subjects managed by CEC,DELHI
One-way ANOVA in Stata®
 
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Discover how to calculate a oneway analysis of variance (ANOVA) using Stata. Created using Stata 12. Copyright 2011-2017 StataCorp LLC. All rights reserved.
Views: 66313 StataCorp LLC
Introduction to experimental design and analysis of variance (ANOVA)
 
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Covers introduction to design of experiments. Includes, - one-way analysis of variance (ANOVA) - two-way ANOVA - Use of Microsoft Excel for developing ANOVA table Design of experiments is considered heart of the six-sigma DMAIC process and heavily used during improvement phase.
Views: 50784 Bharatendra Rai
Managerial Accounting-Variance Analysis-Severson
 
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See the below link for more resources, including as a list of all of my videos, practice exercises, Excel templates, and study notes. https://www.dropbox.com/s/09hdhag3zieyt08/Severson%20YouTube%20Videos.xlsx?dl=0 This lecture discusses the various types of variance analysis calculations. This includes discussions of the flexible budget and statistic budget, as well as the specific price and quantity variances, sometimes referred to as rate and efficiency variances. This covers how to calculate the variances, as well as how to determine if it is favorable or unfavorable. This covers both the sales and cost budgets.
ANOVA - Unequal Variances - Brown-Forsythe and Welch Tests
 
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A test used to determine whether variances are equal among groups compared in an ANOVA. If the variances are not equal and you need to run a post hoc test, the Games-Howell is, in general, a good option. See https://www.youtube.com/watch?v=oagLeAOaevk
Views: 39563 Robin Kay
One way analysis of variance using R
 
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In this tutorial, you will be able to learn how to carry out one-way analysis of variance along with the comparison of mean values by using different mean comparison tests. You will also be able to learn graphical presentation of the means as bar graphs showing standard deviation or standard error. Download data file: https://1drv.ms/x/s!As-fQhyw8QbtgQggis6mpTLX-2of Visit blog for more details: http://agroninfotech.blogspot.com/2018/06/one-way-analysis-of-variance-using-r.html R is a free software and you can download it from the link given below https://www.r-project.org/ Download link for R studio https://www.rstudio.com/products/rstudio/download/ Package suggestions to install: Agricolae (https://cran.r-project.org/src/contrib/agricolae_1.2-8.tar.gz) car (https://cran.r-project.org/src/contrib/car_3.0-0.tar.gz) Description of video 0:37 Importing data into R studio 1:28 Console commands for analysis of variance (ANOVA) 2:07 Getting treatment means Mean comparison tests 2:12 Tukey HSD test 2:23 LSD test 2:46 Scheffe test 3:01 Construction of bar graphs representing standard error (SE) and standard deviation (SD) and assigning main title and labels for x-axis and y-axis. Get connnected with us on ____________________________________________________________ G+: https://plus.google.com/u/1/101269397606526645442 Facebook page: https://www.facebook.com/AgronInfoTech/?ref=bookmarks Twitter: https://twitter.com/AgronInfoTech Linked In: https://www.linkedin.com/in/agron-info-tech-7429a6156/ Instagram: https://www.instagram.com/agroninfo/ ___________________________________________________________ If you have any question please comment below. Thanks for watching this video.
Views: 197 AGRON Info-Tech
MANOVA in SPSS (Multivariate Analysis of Variance) - Part 3
 
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A step-by-step introduction to MANOVA in SPSS is covered in this video (part 3). Video Transcript: now remember that for these two tests here we're using the alpha of .025 per test. We're not using alpha .05 per test, but instead we're using that Bonferroni adjusted level. So our first result, the empathic concern, this is a p of .015, and that is less than .025, so that result is significant. So this indicates that boys and girls differed on empathic concern. Looking at our next result, we see a p of .138, which is not less than .025, so this result is not significant. So, in other words, there was not a significant difference between boys and girls on perspective taking. So we want to summarize these results in just a minute in our written results, but before we do that, empathic concern was significant and recall earlier I had said if there was a significant result for ANOVA that we want to go ahead and look at the means so we can describe the differences. So we can look at our Estimated Marginal Means table if we'd like. We also saw the means earlier in the Descriptive Statistics table, right here. But let's go and look at the other table for practice as well. So down here at Marginal Means, empathic concern was significant, it had that p of .015 recall. So here we see that males and females, there's the two means. So which group had the higher mean? Females, right? So females had significantly higher or demonstrated significantly higher empathic concern than did males. But as far as perspective-taking was concerned, there was not a significant difference between males and females. So next we'll write those results up using APA format. OK now going back up to our Multivariate Test table, remember we're going to use Wilks' Lambda. And here notice first of all that Wilks' Lambda has a value of of .741, an F of 4.73, rounding, degrees of freedom of 2 and 27, a p-value of .017 as we saw before, and then partial eta-squared, rounding to two decimal places, of .26. So I'm going to use all of that information in the written results here. So the first sentence, I say there was a significant difference between males and females when considered jointly on the variables in empathic concern and perspective taking. And then here we have Wilks', and this is the Lambda, this symbol here, is equal to .741, and you saw that right here, and then F 2, 27. From here on out this part looks like a normal ANOVA. F 2 and 27, so here's the degrees of freedom, 2,27 equals 4.73, which you see right here rounded to two decimal places, and then finally p of .017, which is right there, and then partial eta-squared of .26. OK, so that first sentence shows the multivariate result, or the MANOVA. And then next we have a separate ANOVA was conducted for each dependent variable Lifetime access to SPSS videos: http://tinyurl.com/m2532td 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. Videos series coming soon include: multiple regression in spss, factor analysis in spss, nonparametric tests in spss, multiple comparisons in spss, linear contrasts in spss, and many more. Subscribe today! YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Introduction to Material Variances
 
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For face to face classes please contact Bliss Point Studies, at 2453 Hudson lane, 011-45076221.
Views: 68574 Gagan Kapoor
12-3 Assumptions and Hypotheses for One-Way ANOVA
 
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The assumptions for One-Way ANOVA require a scale-level dependent variable and a categorical independent variable, typically with three or more levels. Check for outliers, independence, and normality. The non-parametric alternative is the Kruskal-Wallis One Way ANOVA test. The null hypothesis for ANOVA is that the means are the same. Table of Contents: 00:17 - Requirements for One-Way ANOVA 02:04 - Assumptions 05:05 - NHST Settings 06:59 - Critical Value for One-Way ANOVA 08:23 - Finding the Critical Value 09:04 - Homogeneity of Variance
Views: 14286 Research By Design
Revenue and Spending Variance Analysis (Flexible Budgeting)
 
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This video discusses revenue and spending variances in the context of flexible budgeting. A comprehensive example is provided to demonstrate how revenue and spending variances are calculated and interpreted. Edspira is your source for business and financial education. To view the entire video library for free, visit http://www.Edspira.com To like us on Facebook, visit https://www.facebook.com/Edspira Edspira is the creation of Michael McLaughlin, who went from teenage homelessness to a PhD. The goal of Michael's life is to increase access to education so all people can achieve their dreams. To learn more about Michael's story, visit http://www.MichaelMcLaughlin.com To follow Michael on Facebook, visit https://facebook.com/Prof.Michael.McLaughlin To follow Michael on Twitter, visit https://twitter.com/Prof_McLaughlin
Views: 35281 Edspira
Planning and Operational variances - Variance analysis - ACCA Performance Management (PM)
 
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Planning and Operational variances - Variance analysis - ACCA Performance Management (PM) *** Complete list of free ACCA lectures is available on OpenTuition.com https://opentuition.com/acca/pm/ *** Free lectures for the ACCA Performance Management (PM) Exam To benefit from this lecture, visit opentuition.com/acca to download the notes used in the lecture and access ALL free resources: ACCA lectures, tests and Ask the ACCA Tutor Forums Please go to opentuition to post questions to ACCA Tutor, we do not provide support on youtube.
Views: 1994 OpenTuition
Combined analysis of variance | Experiments repeated over years | RCBD one factor example
 
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This video will show how to carry out the combined analysis of variance for experiments repeated over two years. Very simple steps to carry out the analysis. Step 1 (at 1:14): Get error mean squares or variance and associated degree of freedom for each year. You can download excel tool where you can just enter data and get a variance with an associated degree of freedom. Download data file: https://1drv.ms/x/s!As-fQhyw8QbtgQkl4nET0QbAmBjD Download Homogeneity tests excel tool: https://1drv.ms/x/s!As-fQhyw8QbtgQ3XdOdGdCb_xKlj Download link for excel tool for calculating variance or EMS & Error degree of freedom: https://1drv.ms/x/s!As-fQhyw8Qbtgh3GUuVKY_UlCSRC Step 2 (at 1:28): Apply test for homogeneity of variance using excel tool. You can download this tool from the link given below... Excel tool for the test of homogeneity of variance: https://1drv.ms/x/s!As-fQhyw8QbteO04vMXj1EvfvCI Step 3 (at 2:08): Choose an appropriate design or construct design according to your objectives in MSTAT C There was mistakenly written the third variable as "Time in days from heading to maturity" at 1:03 and correct is "Time in days from emergence to heading". Useful links: Part 1: Combined analysis of variance | Test for homogeneity of variances: https://youtu.be/1xT39b42P4I Importing excel data to MSTAT C and define variables: https://youtu.be/0Uk41RSI0EM How to install MSTAT C and define data path: https://youtu.be/ZReWTtjBRS8 Mean comparison test with RCBD one factor example: https://youtu.be/7oPoTXRFVwE Download link for MSTAT-C: https://msu.edu/~freed/disks.htm ______________________________________________________________ G+: https://plus.google.com/u/1/101269397606526645442 Facebook page: https://www.facebook.com/AgronInfoTech/?ref=bookmarks Twitter: https://twitter.com/AgronInfoTech Linked In: https://www.linkedin.com/in/agron-info-tech-7429a6156/ Instagram: https://www.instagram.com/agroninfo/ ___________________________________________________________ If you have any question please comment below. Thanks for watching this video.
Views: 330 AGRON Info-Tech
Analysis of Variance (ANOVA), Pt. 3
 
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Part 3 of a series of video explaining ANOVA.
Views: 322 Alan Neustadtl
11-3 Levene’s Test of Homogeneity of Variance
 
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One important assumption of the Independent-Samples t Test is that the variances in the sample groups are approximately equal or that the samples have homogeneity of variance. Levene’s Test for Equality of Variances is a test of whether the variances of the two samples/groups are approximately equal. You will learn how to conduct Levene’s test in SPSS both within an independent samples t test and using the Explore command. This video updated Jan. 2018 to correct the video and audio about p values.
Views: 20191 Research By Design
Direct Materials Variance Analysis
 
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This video demonstrates how to conduct a variance analysis for direct materials. A comprehensive example is provided to show how both the price variance and quantity variance are calculated. The example also shows how variance analysis differs when the quantity purchased differs from the quantity used. Edspira is your source for business and financial education. To view the entire video library for free, visit http://www.Edspira.com To like us on Facebook, visit https://www.facebook.com/Edspira Edspira is the creation of Michael McLaughlin, who went from teenage homelessness to a PhD. The goal of Michael's life is to increase access to education so all people can achieve their dreams. To learn more about Michael's story, visit http://www.MichaelMcLaughlin.com To follow Michael on Facebook, visit https://facebook.com/Prof.Michael.McLaughlin To follow Michael on Twitter, visit https://twitter.com/Prof_McLaughlin
Views: 93787 Edspira
Two Way Analysis of Variance With Interaction
 
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Statistics_stat-11-12-stat-model46.mp4
Views: 54 Sabaq. Pk
ANOVA 3: Hypothesis test with F-statistic | Probability and Statistics | Khan Academy
 
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Analysis of Variance 3 -Hypothesis Test with F-Statistic This is the last video in our probability and statistics subject! Now move on to our first video in Precalculus: https://www.khanacademy.org/math/precalculus/vectors-precalc/vector-basic/v/vector-representations-example?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/statistics-inferential/anova/v/anova-2-calculating-ssw-and-ssb-total-sum-of-squares-within-and-between-avi?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it! About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to KhanAcademy’s Probability and Statistics channel: https://www.youtube.com/channel/UCRXuOXLW3LcQLWvxbZiIZ0w?sub_confirmation=1 Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 463753 Khan Academy
One Way Analysis of Variance
 
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Statistics_stat-11-12-stat-model39.mp4
Views: 102 Sabaq. Pk
One-Way ANOVA:  The Formulas
 
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I look at the calculation formulas and the meaning of the terms in the one-way ANOVA table. In other related videos, I have a brief introduction to one-way ANOVA, and work through a real world example.
Views: 65016 jbstatistics
Working with SPSS: One-Way Analysis of Variance (ANOVA)
 
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This tutorial shows how to use the statistics application SPSS (formerly known as PASW) to compare the means of several groups (3 in this case) on a single quantitative outcome using a one-way analysis of variance (ANOVA). It also shows how to perform a post-hoc analysis using the Tukey test (or Tukey HSD test, for Honestly Significant Difference).
Views: 32334 Barton Poulson
BEC Exam Variance Analysis
 
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Roger Philipp, CPA, CGMA, prepares you for the CPA Exam by covering Variance Analysis in the BEC section of the exam. Perhaps the shortest section of all four sections, BEC still shouldn't be overlooked! 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: In order to do overhead variances, here's what we're going to do. As I said, all the variances are done in the flexible budget equation. What was the flexible budget equation we’ve learned in the past? We learned total cost equals fixed plus variable times x. That’s you're flexible budget equation. Fixed plus variable times x, total cost, for fixed, plus variable, times x. You’ve got your fixed overhead plus your variable overhead to...per hour, times x is your activity level. So x is some cost driver, some activity level. So our flexible budget equation is total cost equals fixed plus variable times x. When you're doing flexible budget, when you do the budget, within a budget what costs are normally the same? Fixed or fixed? Remember, within the relevant range, fixed are fixed. Variable are fixed per unit. We're looking at the x, which is the cost driver, the activity level. So that's called our flexible budget equation. We're trying to figure out what total cost will be at different levels of activity, x being your cost driver. So, for doing all of our overhead analysis using, so we’re always going to compare something with the flexible budget equation, and the way we're going to do this is, we're going to look at, on the left side, we're going to start here with our actual overhead. Actual overhead. We're going to compare that with our flexible budget equation at actual. We're going compare that with our flexible budget equation at standard, and then we’re going to compare that with standard of standard. What is standard of standard. That's called applied. That’s your applied overhead. That's the overhead you applied into what? WIP. Whip it good! Remember that? WIP? Work in process. That’s the amount we applied into work in process. So, with overhead, again, don’t lose sight of the big picture...What is overhead? All the other costs in the factory except which? Direct materials, direct labor. We already gave materials and labor. Now we’re looking at overhead.
Views: 47348 Roger CPA Review
ANOVA - Unequal Variances Unequal Sample Sizes - Brown-Forsythe & Welch F tests
 
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How to perform a Brown-Forsythe and Welch F tests in SPSS. These tests are robust to violation of the homogeneity of variance assumption. I also show the degree to which these tests work at keeping alpha close to .05 across various conditions based on published simulation research.
Views: 28789 how2stats
Homogeneity of Variance (part 1)
 
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What is homogeneity of variance and why is it important? I answer these questions. Also, I describe three different types of Levene's tests, two of which are robust to non-normal distributions and unequal sample sizes. Finally, I provide some brief guidelines relevant to how robust the t-test and ANOVA are to violations of the homogeneity of variance assumption. Here's the link to the video where I demonstrate how to perform the three different levene's tests: http://www.youtube.com/watch?v=81Yi0cTuwzw
Views: 93561 how2stats
Xplorerr: One Way Analysis of Variance in R
 
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In this demo, we will show you how to perform the one way anova or one way analysis of variance using the Xplorerr app.
Views: 4 Rsquared Academy

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