# Statistical Analyses Using SPSS

**Topics:**Statistics, Statistical tests, Regression analysis

**Pages:**37 (6692 words)

**Published:**January 20, 2013

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http://www.ats.ucla.edu/stat/spss/whatstat/whatstat.htm

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Statistical analyses using SPSS

Introduction

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. About the hsb data file

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.

One sample t-test

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.

t-test

/testval = 50

/variable = write.

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

A one sample median test allows us to test whether a sample median differs significantly from a hypothesized value. We will use the same variable, write, as we did in the one sample t-test example above, but we do not need to assume that it is interval and normally distributed (we only need to assume that write is an ordinal variable). nptests

/onesample test (write) wilcoxon(testvalue = 50).

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Statistical Tests in SPSS

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http://www.ats.ucla.edu/stat/spss/whatstat/whatstat.htm

Binomial test

A one sample binomial test allows us to test whether the proportion of successes on a two-level categorical dependent variable significantly differs from a hypothesized value. For example, using the hsb2 data file, say we wish to test whether the proportion of females (female) differs significantly from 50%, i.e., from .5. We can do this as shown below. npar tests

/binomial (.5) = female.

The results indicate that there is no statistically significant difference (p = .229). In other words, the proportion of females in this sample does not significantly differ from the hypothesized value of 50%. Chi-square goodness of fit

A chi-square goodness of fit test allows us to test whether the observed proportions for a categorical variable differ from hypothesized proportions. For example, let's suppose that we believe that the general population consists of 10% Hispanic, 10%

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Statistical Tests in SPSS

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http://www.ats.ucla.edu/stat/spss/whatstat/whatstat.htm

Asian, 10% African American and 70% White folks. We want to test whether the observed proportions from our sample differ significantly from these hypothesized proportions.

npar test

/chisquare = race...

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