Search results “Analysis of variances in”

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.
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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
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Views: 735351
statisticsfun

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: 454197
J David Eisenberg

Demonstration of how to conduct a One-Way ANOVA by hand.

Views: 720184
ArmstrongPSYC2190

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.
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Views: 177727
ProfessorSerna

CIMA P1 Variance analysis - Analysis of variances
Free lectures for the CIMA P1 Exams Management Accounting

Views: 3767
OpenTuition

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: 68020
James Slocombe

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: 46591
Bharatendra Rai

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: 42314
Tony Bell

Variance analysis can be summarized as an analysis of the difference between planned and actual numbers.
Click here to learn more about this topic: https://corporatefinanceinstitute.com/resources/knowledge/accounting/variance-analysis/
Further information on variance: https://corporatefinanceinstitute.com/resources/knowledge/finance/variance-formula/
Click here to learn more about Revenue Variance: https://corporatefinanceinstitute.com/resources/knowledge/accounting/revenue-variance-analysis/

Views: 5321
Corporate Finance Institute

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.
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Views: 44046
Notepirate

In this video, we explain and illustrate with a simple example the concept of budget variances.

Views: 25299
tutor2u

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.
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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: 349215
statisticsfun

statisticslectures.com - where you can find free lectures, videos, and exercises, as well as get your questions answered on our forums!

Views: 210677
statslectures

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: 8981
Chris Olson

An introduction to Two Way ANOVA (Factorial) also known as Factorial Analysis. Step by step visual instructions organize data to conduct a two way ANOVA. Includes a comparison with One Way ANOVA. Instructions on how to build a mean table.
Playlist on Two Way ANOVA
http://www.youtube.com/playlist?list=PLWtoq-EhUJe2TjJYfZUQtuq7a0dQCnOWp
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David Longstreet Professor of the Universe
Professor of the Universe: David Longstreet http://www.linkedin.com/in/davidlongstreet/
MyBookSucks.Com

Views: 263114
statisticsfun

This video explains how to conduct variance analysis of direct labor. A comprehensive example is provided to demonstrate how the rate variance and quantity variance are calculated, and similarities between the computation of direct materials variances and direct labor variances are highlighted.
Edspira is your source for business and financial education. To view the entire video library for free, visit http://www.Edspira.com
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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
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Views: 60888
Edspira

“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!
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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: 33907
Roger CPA Review

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
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Views: 197829
Edspira

http://thedoctoraljourney.com/ This tutorial demonstrates how to conduct a One Way ANOVA in SPSS.
For more statistics, research and SPSS tools, visit http://thedoctoraljourney.com/.

Views: 409078
The Doctoral Journey

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
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Views: 87234
Edspira

CEC/UGC: Social Science - 2, Education,Psychology, Home Science and related subjects managed by CEC,DELHI

Views: 46
Ch 04 Social Science-II

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: 91357
how2stats

In this video for the open, online course "Statistics in Education for Mere Mortals," Lloyd Rieber explains how to use Excel spreadsheet to compute a one-way analysis of variance (ANOVA).
At the start of the tutorial, you will be asked to copy and paste the following steps into your Excel spreadsheet:
PART 1: CALCULATE THE SUM OF SQUARES
Step 1: Enter Participant IDs, Group IDs, and Raw Scores
Step 2: Calculate N total, Grand Mean, Group Ns, and Group Means
Step 3: Calculate Squared Deviation Scores For Raw Scores Using Group Means and Grand Mean
Step 4: Calculate the Total Sum of Squares (SStotal)
Step 5: Compute Error Sum of Squares (SSerror)
Step 6: Calculate Squared Deviation Scores For Group Means Using Grand Mean
Step 7: Calculate Between-Treatments Sum of Squares (SStreat)
Step 8: Check to be sure that SStot = SStreat + SSerror
PART 2: COMPUTE THE MEAN SQUARES
Step 1: Determine df
Note: Use df total as a check (df total=df treat+df error)
Step 2: Calculate the Mean Square Treatment (MStreat): F Numerator
Step 3: Calculate the Mean Square Error (MSerror): F Denominator
PART 3: COMPUTE F VALUE
PART 4: INTERPRET F VALUE
1. Are the means of the treatment groups the same?
2. If no (i.e. reject the null hypothesis), then which of the treatment means are different from each other?

Views: 859
Lloyd Rieber

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: 9716
Research By Design

**VIEW IN HD**This mini video lecture relates to chapter 12 in our textbook. There is a "pre-lecture" document as well, also covering the one-way ANOVA. Other people - This video is public and you are free to view it. Note that I do not respond to messages asking for help with statistics, and also that I do rotate videos and sometimes remove them.

Views: 912
E.Sanborne

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: 610
mrsethwright

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-fQhyw8QbteO04vMXj1EvfvCI
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
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Views: 572
AGRON Info-Tech

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: 33515
Edspira

In this video for the open, online course "Statistics in Education for Mere Mortals," Lloyd Rieber explains how to use Excel spreadsheet to compute a one-way analysis of variance (ANOVA).

Views: 2255
Lloyd Rieber

This video demonstrates how to interpret t test and ANOVA output in SPSS when the assumption of homogeneity of variance has been violated. Homogeneity of variance (homoscedasticity) is tested with the Levene’s test. The null hypothesis for the Levene’s test is that the group variances are equal.

Views: 6875
Dr. Todd Grande

Statistics for Educational Researchers by Chan Yuen Fook PhD and Suthagar Narasuman PhD.

Views: 9
Suthagar Narasuman

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
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Our Team:
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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!

Views: 118946
MarinStatsLectures-R Programming & Statistics

This short video will demonstrate how to run a simple Analysis of Variance (ANOVA) in SPSS to see if there are significant differences based on one main effect.

Views: 628
Gerard Babo

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/
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Views: 63460
Quantitative Specialists

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: 11736
Research By Design

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: 30986
zedstatistics

One Way ANOVA in SPSS - Part 3 (one way analysis of variance - ANOVA). ANOVA Post Hoc Tests are covered in this video on SPSS. Learn how to conduct post hoc tests for the one-way analysis of variance procedure.
Video Transcript: In this video we'll continue with our discussion of the analysis of the one-way ANOVA, and now we're going to focus on post-hoc tests. Recall in our prior video that our test was significant, with a p-value .019, which indicated that there was a significant difference somewhere between these three groups. But we didn't know exactly where the difference existed at this point. So we were going to do post-hoc tests to flush out those differences and see where in fact they are. Now post-hoc tests are conducted after the fact. They are typically only conducted or interpreted after a significant ANOVA. So we so We have a significant result, recall, .019, so that effectively gives us the green light to go and dive in and try and find out where the differences lie between the groups. So post-hoc tests are used to, as I just said, dive in and look for the differences between the groups and, importantly, they test each possible pair of groups. So they test two at a time. So, for example, a post-hoc test will test none versus low volume, and there will be another test that tests none vs high volume, and then there will be a final test that tests low volume versus high volume. So it does all possible pairs, two at a time. The total alpha used for the set of tests is .05, and that's important to keep in mind. It's not .05 per test, but it's .05 in total. And we're using a test which we selected in the previous video under the Post-Hoc button which was called Tukey. We're going to use Tukey's test, and Tukey's test does a good job at keeping the whole set of tests at .05. So the post-hoc tests for Tukey's test there's actually two tables that come out; there's a Post Hoc Tests table, which is labeled Multiple Comparisons, and then there's the Homogeneous Subsets table, which is labeled exam scores. We'll take a look at each of these in turn. So let's start with our Multiple Comparisons result. Now here the way this is organized is that we have our pairs organized from left to right. So, for example, this first test is none versus low volume, and if we scroll over, we can zero in on this column, these are the p-values. So here the p-value is .963. And we use the same decision rule as always, if p is less than equal to .05, there's a significant difference between the groups. If p is greater than .05, there's no significant difference. So here we can see that no music and low volume is not significantly different, since this is greater than .05. OK our next result we read here, diagonally, so we move down diagonally, and this compares the no volume versus high volume. And as we read over we can see that this test is in fact significant at .027. So there's a significant difference between no volume and high volume. Our next result, low volume versus none, if you look at this low volume versus none with the p of .963, you know we've already done this. If you notice it up here, none versus low volume, low volume versus none, these two have the exact same p-values, this is the same test. And this is one of the drawbacks of the multiple comparisons table; it produces actually the same test twice, for each test, and we've seen this one right here, so we're going to ignore this because it tells us the same thing. Next we have low volume versus high volume, and notice that p-value is .049. So that's very close, but it in fact also is significant. So there's a significant difference between the low volume and the high-volume groups. As I move down here, high volume versus none, that test has already been done here, notice the same p value .027. And then high volume low volume, we just read that one right here, with a p of .049. So, in summary, the results we have here are
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Views: 5478
Quantitative Specialists

For face to face classes please contact Bliss Point Studies, at 2453 Hudson lane, 011-45076221.

Views: 58875
Gagan Kapoor

Equality of variances is an assumption for statistical methods such as Analysis of Variance (ANOVA)—a parametric method—and the Kruskal-Wallis one-way analysis—a non-parametric method. We must be able to test for equality of variances in both normally distributed data and non-normally distributed data. There are two separate tests for equality of variances: 1) If you have normally distributed data, you should perform the parametric Levene's test. 2) If you have non-normally distributed data, you should perform the non-parametric Levene's test. In this video tutorial, I show you how to perform both, using SPSS, and I also show the necessary references, and how to write out your results.
PARAMETRIC LEVENE'S TEST
-Analyze, Compare Means, One Way ANOVA.
-Put your data variable in the Dependent List.
-Put your groups in the Factor Field.
-Click on Options and check, Homogeneity of Variance Test, and then click Continue and OK.
-Scrutinize the Test of Homogeneity of Variances.
The null hypothesis for the parametric Levene's test is that there is an equality of variance. If the p-value is below 0.05, we reject the null hypothesis and assume that we do not have equality of variance. If it is above 0.05, we keep the null hypothesis.
NONPARAMETRIC LEVENE'S TEST
In SPSS, it is not yet possible to execute Levene's test for non-normally distributed data in one step. We need to prepare the data by taking some initial steps:
Step 1) Create the ranked data and put them into a new variable. This is how I do it with my example data:
-In the SPSS menu, select Transform, and then Rank Cases.
-Put your data into the field Variable (in this example, it is "Score") and then click OK.
SPSS will automatically create and label a new variable, "RScore," where the letter "R" stands for "ranked." In this new variable, each student has been given an individual rank based on their exam scores. Students with low exam scores are given lower rankings than students who performed better.
Step 2) Based on these individual rankings, determine the mean ranks for each group. So, yet another variable has to be created in SPSS. This is how I do it:
-In the menu, select Data, then Aggregate.
-Put the variable previously created, "RScore," into the field Summaries of Variable.
-Click on Function and select Mean. This will collect the numbers in the variable "RScore" and aggregate them in the form of mean values.
-Put your groups in the field Break Variable, in our example "Town," and then click OK.
SPSS will automatically create and label a new variable, this time entitled "RScore_mean_1". In this new variable, each student has been given a value based on their group. All members of the same group, or "Town" in my example, will have the same value. It is the group's mean rank.
Step 3) Create a third variable, containing a measure of each individual's deviation from his or her group's mean rank.
-Transform, Compute Variable.
-Then, under Target Variable, provide a label for this third, new variable.
-In the field Numeric Expression, enter the formula.
-Before we click OK and execute this computation, we must instruct SPSS that we only want positive values. In the field Function group, click once on All. Then select the entire expression and double-click on Abs, in the field Functions and Special Variables. You have now instructed SPSS to transform all results to absolute values.
-Click OK.
The third variable is created and it contains individual measures of spread, i.e. how far each individual is to his or her group's mean.
Next, you will perform an ANOVA on these individual differences. The null hypothesis is that there is an equality of variance. If the p-value is above 0.05, we keep the null hypothesis and assume equality of variance. If the p-value is below 0.05, we reject the null hypothesis and assume that the differences in variance or spread between the groups are statistically significantly.
Suggested reading
Nordstokke, D. W., & Zumbo, B. D. (2010). A new nonparametric Levene test for equal variances. Psicológica, 31(2), 401-430.
Nordstokke, D. W., Zumbo, B. D., Cairns, S.L., & Saklofske, D.H. (2011). The operating characteristics of the nonparametric Levene test for equal variances with assessment and evaluation data. Practical Assessment, Research & Evaluation, 1(5). (Page numbers not available.)
Martin, W. E., & Bridgmon, K. D. (2012). Quantitative and Statistical Research Methods: From Hypothesis to Results. Somerset, NJ: Wiley.
In the video tutorial, I show examples of how to write out the results, for both the parametric Levene's test and the nonparametric Levene's test.
Good luck with testing your data in SPSS for equality of variances, either through a parametric or a non-parametric Levene's test.
Text and video (including audio) © Kent Löfgren, Sweden

Views: 81962
Kent Löfgren

Hi all. I am sharing the fourth part of my video on standard costing. The videos provide you a simple way to remember all formulae of standard costing.
You can refer part one (material variances) in this link - https://www.youtube.com/watch?v=i9NXE...
You can refer to part two (labour variances) of the video on
https://www.youtube.com/watch?v=_xT9FWyPRs8&t=39s
You can refer to part three(overhead variances) of the video on https://youtu.be/AW6w6NI7OnI
#CAINTER #CAFINAL #CAIPCC #standardcosting #salesvariances #profitvariances

Views: 3454
Dinesh Jain

Calculation of variable overhead variances and an example.
Variable overhead spending variance
Variable overhead efficiency variance
Variable overhead flexible budget variance
Example of how to calculate variable overhead variances

Views: 2518
Brian Routh TheAccountingDr

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: 15567
Research By Design

The links to the problems are no longer working.
If you want updated videos (with working links) try this playlist:
https://youtu.be/2eG_UVdoJrA
In this series of 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 and the attached worksheet were prepared by Tony Bell of Thompson Rivers University (TRU) - I encourage educators to freely use, edit and modify these videos and the attached worksheet - they are available under Creative Commons Licenses.

Views: 39745
Tony Bell

Second part in demonstrating how to undertake one-way analysis of variance using R. For more on statistical analysis using R visit http://www.wekaleamstudios.co.uk and browse.

Views: 1232
ramstatvid

This video demonstrates how to conduct and interpret a Levene’s Test of Homogeneity of Variances (Homoscedasticity) in SPSS using the Univariate option under the General Linear Model. Also, a demonstration of how to calculate the Levene’s Test in SPSS without selecting the “Homogeneity test” option in ANOVA is provided.

Views: 8833
Dr. Todd Grande

This video describes how to test the assumptions for two-way ANOVA using SPSS.

Views: 26941
Dr. Todd Grande

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: 63366
StataCorp LLC

This video will show you how to verify if there is a difference in the variances of two samples. Basically, we are wondering if one sample is more varied than the other.

Views: 111667
ProfS Taylor

Activity Based Costing 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.

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OpenTuition

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Selling in special circumstances. shares you bought at different times and prices in one company shares through an investment club shares after a company merger or takeover employee share scheme shares. Jointly owned shares and investments. If you sell shares or investments that you own jointly with other people, work out the gain for the portion that you own, instead of the whole value. There are different rules for investment clubs. What to do next. Deduct costs. Apply reliefs.