How to Read Levene's Test Spss for Dummy Variables

I-way ANOVA in SPSS Statistics

Introduction

The one-way analysis of variance (ANOVA) is used to decide whether there are any statistically significant differences between the means of two or more independent (unrelated) groups (although you tend to only see it used when in that location are a minimum of three, rather than two groups). For example, you lot could use a one-fashion ANOVA to sympathise whether test performance differed based on test anxiety levels amongst students, dividing students into iii independent groups (east.g., low, medium and high-stressed students). Also, it is of import to realize that the one-way ANOVA is an omnibus examination statistic and cannot tell you which specific groups were statistically significantly different from each other; it only tells you that at least two groups were different. Since you may accept three, iv, five or more than groups in your study design, determining which of these groups differ from each other is important. You tin do this using a mail service hoc test (Northward.B., nosotros discuss mail hoc tests later in this guide).

Note: If your study design not only involves one dependent variable and one contained variable, but also a third variable (known as a "covariate") that you want to "statistically control", you may need to perform an ANCOVA (assay of covariance), which can be thought of every bit an extension of the one-way ANOVA. To learn more, see our SPSS Statistics guide on ANCOVA. Alternatively, if your dependent variable is the time until an event happens, you might need to run a Kaplan-Meier assay.

This "quick start" guide shows you how to behave out a one-way ANOVA using SPSS Statistics, as well every bit interpret and report the results from this exam. Since the one-way ANOVA is often followed up with a post hoc examination, we besides show you how to carry out a post hoc examination using SPSS Statistics. Withal, before nosotros introduce yous to this procedure, you need to sympathise the dissimilar assumptions that your data must see in order for a one-way ANOVA to give you a valid result. Nosotros talk over these assumptions next.

SPSS Statistics

Assumptions

When yous cull to analyse your data using a one-way ANOVA, part of the process involves checking to make sure that the data you lot want to analyse can actually be analysed using a i-way ANOVA. You need to practise this considering it is only appropriate to employ a one-manner ANOVA if your data "passes" six assumptions that are required for a 1-way ANOVA to requite you a valid result. In practice, checking for these six assumptions just adds a little bit more time to your analysis, requiring you to click a few more buttons in SPSS Statistics when performing your analysis, besides equally recollect a little scrap more nearly your data, but it is non a hard job.

Before we introduce you to these half dozen assumptions, practice non be surprised if, when analysing your own data using SPSS Statistics, 1 or more of these assumptions is violated (i.east., is not met). This is not uncommon when working with existent-world data rather than textbook examples, which often only show y'all how to carry out a one-mode ANOVA when everything goes well! However, don't worry. Even when your data fails certain assumptions, at that place is often a solution to overcome this. Get-go, let'south take a look at these six assumptions:

Assumption #1: Your dependent variable should exist measured at the interval or ratio level (i.eastward., they are continuous). Examples of variables that meet this criterion include revision time (measured in hours), intelligence (measured using IQ score), test functioning (measured from 0 to 100), weight (measured in kg), so forth. You tin learn more virtually interval and ratio variables in our article: Types of Variable.
Supposition #2: Your independent variable should consist of two or more categorical, independent groups. Typically, a one-way ANOVA is used when you have three or more categorical, independent groups, but information technology can be used for just two groups (but an independent-samples t-examination is more usually used for two groups). Instance independent variables that encounter this criterion include ethnicity (e.thousand., 3 groups: Caucasian, African American and Hispanic), physical activity level (eastward.one thousand., 4 groups: sedentary, low, moderate and loftier), profession (e.g., 5 groups: surgeon, md, nurse, dentist, therapist), and and so along.
Assumption #three: You should have independence of observations, which means that there is no relationship between the observations in each grouping or betwixt the groups themselves. For instance, there must be different participants in each group with no participant being in more than one grouping. This is more of a study design issue than something you tin can examination for, but it is an important assumption of the 1-way ANOVA. If your written report fails this assumption, you lot volition need to apply another statistical test instead of the ane-way ANOVA (due east.thou., a repeated measures pattern). If you are unsure whether your study meets this assumption, you can use our Statistical Exam Selector, which is part of our enhanced guides.
Assumption #4: There should be no significant outliers. Outliers are merely single information points within your data that practise not follow the usual pattern (due east.chiliad., in a study of 100 students' IQ scores, where the mean score was 108 with only a small variation between students, ane pupil had a score of 156, which is very unusual, and may even put her in the peak 1% of IQ scores globally). The problem with outliers is that they tin have a negative effect on the one-fashion ANOVA, reducing the validity of your results. Fortunately, when using SPSS Statistics to run a one-mode ANOVA on your data, you can easily detect possible outliers. In our enhanced one-way ANOVA guide, we: (a) prove you how to find outliers using SPSS Statistics; and (b) hash out some of the options you have in order to deal with outliers. You lot tin can learn more about our enhanced one-manner ANOVA guide on our Features: One-way ANOVA page.
Assumption #5: Your dependent variable should be approximately normally distributed for each category of the independent variable. We talk about the one-manner ANOVA just requiring approximately normal data because it is quite "robust" to violations of normality, meaning that assumption tin can exist a picayune violated and still provide valid results. You can test for normality using the Shapiro-Wilk examination of normality, which is hands tested for using SPSS Statistics. In addition to showing you how to practise this in our enhanced 1-way ANOVA guide, we too explain what you tin can practise if your data fails this assumption (i.eastward., if it fails it more than a niggling bit). Once more, y'all tin can learn more on our Features: One-mode ANOVA page.
Assumption #6: At that place needs to exist homogeneity of variances. Y'all tin can exam this assumption in SPSS Statistics using Levene'due south test for homogeneity of variances. If your data fails this assumption, you will need to not only carry out a Welch ANOVA instead of a i-way ANOVA, which yous can do using SPSS Statistics, but also use a unlike post hoc test. In our enhanced one-mode ANOVA guide, we (a) prove you how to perform Levene's test for homogeneity of variances in SPSS Statistics, (b) explain some of the things you will need to consider when interpreting your data, and (c) present possible means to keep with your analysis if your data fails to meet this assumption, including running a Welch ANOVA in SPSS Statistics instead of a one-way ANOVA, and a Games-Howell test instead of a Tukey post hoc test (larn more on our Features: One-fashion ANOVA page).

Yous can check assumptions #iv, #5 and #6 using SPSS Statistics. Before doing this, y'all should make sure that your data meets assumptions #1, #two and #3, although you don't need SPSS Statistics to exercise this. Remember that if yous do not run the statistical tests on these assumptions correctly, the results you get when running a one-manner ANOVA might not be valid. This is why we dedicate a number of sections of our enhanced 1-manner ANOVA guide to assist you get this right. You tin discover out about our enhanced one-way ANOVA guide on our Features: 1-way ANOVA folio, or more mostly, our enhanced content every bit a whole on our Features: Overview page.

In the section, Exam Procedure in SPSS Statistics, nosotros illustrate the SPSS Statistics procedure to perform a one-way ANOVA bold that no assumptions have been violated. Starting time, we set out the example we utilise to explain the one-style ANOVA procedure in SPSS Statistics.

SPSS Statistics

Example

A manager wants to raise the productivity at his company by increasing the speed at which his employees tin apply a detail spreadsheet plan. Equally he does not have the skills in-house, he employs an external agency which provides training in this spreadsheet programme. They offer three courses: a beginner, intermediate and advanced class. He is unsure which course is needed for the type of piece of work they do at his visitor, and then he sends x employees on the beginner course, x on the intermediate and 10 on the advanced course. When they all return from the grooming, he gives them a trouble to solve using the spreadsheet programme, and times how long it takes them to consummate the problem. He then compares the three courses (beginner, intermediate, avant-garde) to run across if at that place are any differences in the boilerplate fourth dimension it took to complete the problem.

SPSS Statistics

Setup in SPSS Statistics

In SPSS Statistics, we separated the groups for assay by creating a grouping variable called Course (i.e., the independent variable), and gave the beginners form a value of "1", the intermediate course a value of "2" and the advanced course a value of "iii". Time to complete the prepare problem was entered under the variable name Time (i.due east., the dependent variable). In our enhanced one-way ANOVA guide, we show you how to correctly enter data in SPSS Statistics to run a one-fashion ANOVA (see on our Features: One-way ANOVA page). You can learn nigh our enhanced data setup content in general on our Features: Data Setup. Alternately, see our generic, "quick get-go" guide: Entering Data in SPSS Statistics.

SPSS Statistics

Test Procedure in SPSS Statistics

The viii steps below show y'all how to analyse your data using a one-mode ANOVA in SPSS Statistics when the six assumptions in the previous department, Assumptions, have not been violated. At the terminate of these eight steps, we show y'all how to interpret the results from this test. If you lot are looking for help to make sure your data meets assumptions #4, #v and #6, which are required when using a one-way ANOVA, and can exist tested using SPSS Statistics, you tin can learn more on our Features: 1-fashion ANOVA folio.

Click Analyze > Cograndskin Means > One-Mode ANOVA... on the top carte, as shown below.

Published with written permission from SPSS Statistics, IBM Corporation.
You will be presented with the One-Way ANOVA dialogue box:

Published with written permission from SPSS Statistics, IBM Corporation.
Transfer the dependent variable, Time, into the Dependent List: box and the independent variable, Grade, into the Factor: box using the appropriate buttons (or elevate-and-drop the variables into the boxes), equally shown below:

Published with written permission from SPSS Statistics, IBM Corporation.
Click on the push. Tick the Tukey checkbox equally shown below:

Published with written permission from SPSS Statistics, IBM Corporation.
Click on the button.
Click on the button. Tick the Descriptive checkbox in the –Statistics– expanse, equally shown below:

Published with written permission from SPSS Statistics, IBM Corporation.

NOTE: When testing for some of the assumptions of the i-way ANOVA, you will need to tick more of these checkboxes. We take you through this, including how to interpret the output, in our enhanced ane-fashion ANOVA guide.
Click on the push.
Click on the button.