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
Which of the following is a statistical procedure used to describe the relationship of the variables of bivariate data?Correlation is a bivariate analysis that measures the strength of association between two variables and the direction of the relationship.
What is the statistical procedure used to describe the relationship between two variables?Correlation is a statistical technique that is used to measure and describe a relationship between two variables. Usually the two variables are simply observed, not manipulated. The correlation requires two scores from the same individuals. These scores are normally identified as X and Y.
What statistical test is used to determine the relationship between two variables?Pearson's correlation coefficient (r) is used to demonstrate whether two variables are correlated or related to each other.
Which of the following graph is used to see the relationship between bivariate data?The most useful graph for displaying the relationship between two quantitative variables is a scatterplot.
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