What would you use to determine whether significant differences were observed between all level of your independent variable?
This page shows how to perform a number of statistical tests using SPSS. Each section gives a brief description of the aim of the statistical test, when it is used, an example showing the SPSS commands and SPSS (often abbreviated) output with a brief
interpretation of the output. You can see the page Choosing the Correct Statistical Test for a table that shows an overview of when each test is appropriate to use. In deciding which test is appropriate to use, it is important to consider the type of variables that you have (i.e., whether your variables are categorical, ordinal or interval and whether they are normally distributed), see
What is the difference between categorical, ordinal and interval variables? for more information on this. Most of the examples in this page will use a data file called hsb2, high school and beyond. This data file contains 200 observations from a
sample of high school students with demographic information about the students, such as their gender (female), socio-economic status (ses) and ethnic background (race). It also contains a number of scores on standardized tests, including tests of reading (read), writing (write), mathematics (math) and social studies (socst). You can get the hsb data file by clicking on
hsb2. A one sample t-test allows us to test whether a sample mean (of a normally distributed interval variable) significantly differs from a hypothesized value. For example, using the hsb2 data file, say we wish to test
whether the average writing score (write) differs significantly from 50. We can do this as shown below. The mean of the variable write for this particular sample of students is 52.775, which is statistically significantly different from the test value of 50. We would conclude that this group of students has a significantly higher mean on the writing test than 50. One sample median test
Binomial test
Chi-square goodness of fit
Two independent samples t-test
Wilcoxon-Mann-Whitney test
npar test /m-w = write by female(0 1). Chi-square test
Fisher’s exact test
One-way ANOVA
Kruskal Wallis test
Paired t-test
Wilcoxon signed rank sum test
McNemar test
One-way repeated measures ANOVA
Repeated measures logistic regression
Factorial ANOVA
Friedman test
Ordered logistic regression
Factorial logistic regression
Correlation
Simple linear regression
Non-parametric correlation
Simple logistic regression
Multiple regression
Analysis of covariance
Multiple logistic regression
Discriminant analysis
One-way MANOVA
Multivariate multiple regression
Canonical correlation
Factor analysis
How do you know if there is a significant difference in ANOVA?If the F statistic is higher than the critical value (the value of F that corresponds with your alpha value, usually 0.05), then the difference among groups is deemed statistically significant.
What is an ANOVA test used for?ANOVA stands for Analysis of Variance. It's a statistical test that was developed by Ronald Fisher in 1918 and has been in use ever since. Put simply, ANOVA tells you if there are any statistical differences between the means of three or more independent groups. One-way ANOVA is the most basic form.
What statistical analysis should I use to compare two groups?The two most widely used statistical techniques for comparing two groups, where the measurements of the groups are normally distributed, are the Independent Group t-test and the Paired t-test.
What does a oneOne-Way ANOVA ("analysis of variance") compares the means of two or more independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different. One-Way ANOVA is a parametric test. This test is also known as: One-Factor ANOVA.
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