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How to Run a one sample t test in spss
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How to Run a one sample t test in spss
How to Run a one sample t test in spss

How to Perform a one sample t test in SPSS

In this step-by-step tutorial, you’ll gain a comprehensive understanding of a one sample t test, when to use it and how to run a one sample t test in spss. In other words, the main aim of this tutorial is to help students gain a comprehensive understanding of the how to run a one sample t test in spss.

What is a One sample t test?

A one sample t test is a type of inferential statistic that is used to compare a sample mean to a hypothesized population mean. It is useful when you want to determine whether the sample mean is significantly different from the hypothesized population mean.

Consider a scenario:

A high school biology teacher introduces a new study method designed to improve students’ test scores. The school has historically known that the average test score in biology is 75 out of 100 based on years of data. The teacher wants to determine if this new study method is effective in increasing students’ scores beyond the historical average. So, the teacher randomly selects a sample of 30 students to apply this new study method over a semester. At the end of the semester, a standardized biology test is administered to these 30 students.

Here, the appropriate statistical test is a one sample t test since we want to compare the average test scores with the hypothesized mean of 75.

We will be testing the hypothesis;

H0: μ = 75 Versus

H1: μ > 75


Once you’ve settled on a one sample t test, it is important ensure your data is suitable for performing a one sample t test. This is main done by testing 4 major assumptions. These 4 main assumptions for a one sample t test include:

  • Assumption #1 – The dependent variable should be measured at the interval or ratio level. That is, it should be continuous. A good example of a continuous variable is scores of a students in a test measured out of 100.
  •  Assumption #2 – The observations should be independent. In other words, there should be no relationship between the observations. This assumption is generally assumed if the data was randomly selected from the sample.
  • Assumption #3 – There should be no significant outliers in the data. Generally, outliers are data points that fall far away from the other data points in the data. Suppose that you’ve a data set containing students scores ranging between 0 and 100 and you find a data point with 150. This would be an outlier. Outliers can be detected by creating a box plot of the dependent variable using SPSS.
  • Assumption #4 – The dependent variable should be approximately normally distributed. This is tested using the Shapiro-wilk test in SPSS.

How to Run One Sample T Test in SPSS: Step by Step Procedure

The procedure for running a one sample t test in spss is as simple as ABC. Just follow these 5 simple tests and You’ll have your one sample t test spss outputs.

  1. Click Analyze -> Compare Means -> One-Sample T Test
  2. Drag and drop the variable you want to test against the population mean into the Test Variable(s) box
  3. Specify your population mean in the Test Value box
  4. Click OK
  5. Your result will appear in the SPSS output viewer


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