# t test t tests are used when you want to examine differences but you do not know everything about the population

Assignment 2

T-tests are used when you want to examine differences but you do not know everything about the population.There are three types of t-tests that you may choose to do:one-sample t-test, independent sample t-test, or dependent sample t-test.You can calculate these by hand, in SPSS, or in Excel.The instructions below can be used for SPSS and your textbook offers instructions for using Excel.

**Single-sample t-tests**

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**These tests are used when you want to determine the probability that a sample was drawn from a population with a known mean (Î¼) but with a standard deviation estimated from the sample.**

- Click on analyze, compare means, one-sample t-test
- Copy the variables you want to test into the Test Variables box
- Type the population mean into the Test Value box
- Click on options to get:
- Confidence intervals (95% is default)
- Exclude cases analysis by analysis
- If some data is missing, this will drop the data only in analyses where that data is missing.

- Exclude cases listwise
- If you are doing multiple t-tests and have missing data, this will drop participants who have missing data from all t tests

- Click on continue, ok
- The output will display the t-statistic, degrees of freedom (n-1), significance (two-tailed), and the confidence interval

**Independent sample t-test**

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**These tests are used when you want to determine the probability that two samples were drawn from the same population with unknown means and standard deviations; both of which are estimated from the sample.No population parameters are specified.**

- The data should be entered in one column and should be named as your dependent variable.
- You will need another column of data to identify each group according to number.So, it is a good idea to have two columns of data (one for the IV and one for the DV).
- For the IV column, you should use two consecutive numbers (I usually use 1 and 2)
- Also, be sure to use variable view to name your variables (otherwise this can become very confusing)

**Dependent samples t-test**

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**We use this t-test when we have a repeated measures design such as the same sample completes a pre and post-test and we want to know if there is a difference from one test to the other.**

- Go to analyze, compare means, paired sample t-test
- Select two variables and move into box
- Click on OK
- The output will give you means for each trial (or pre-post test measure) as well as the t-statistic and significance level

Letâ€™s try a few using the data below.Be sure to attach your printouts and answer the questions below.

- First, do an independent sample t-test for gender (IV) and pretest scores (DV)

Were there significant gender differences?How do you know? Interpret the results statistically and in words.

- Then do an independent sample t-test for gender (IV) and posttest scores (DV)

Were there significant gender differences?How do you know? Interpret the results statistically and in words.

- Now, do a paired (dependent) sample t-test for pretest and posttest scores.

Were there two scores significantly different?How do you know? Interpret the results statistically and in words.

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**Data Set Homework 2 (*note 1 = males, 2 = females)**

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**GenderPretestPosttest**

**1.0050.0080.00**

**1.0050.0070.00**

**1.0080.0070.00**

**1.0080.0050.00**

**1.0070.0050.00**

**1.0070.0050.00**

**1.0060.0060.00**

**1.0060.0080.00**

**1.0090.0080.00**

**1.0090.0090.00**

**1.0090.0080.00**

**1.0080.0090.00**

**1.0080.0090.00**

**1.0070.0070.00**

**1.0070.0080.00**

**1.0050.0080.00**

**1.0050.0070.00**

**1.0050.0070.00**

**1.0060.0060.00**

**1.0070.0080.00**

**2.0050.0070.00**

**2.0040.0050.00**

**2.0040.0080.00**

**2.0070.0080.00**

**2.0050.0070.00**

**2.0050.0080.00**

**2.0050.0090.00**

**2.0060.0090.00**

**2.0070.0090.00**

**2.0040.0080.00**

**2.0040.0080.00**

**2.0030.0070.00**

**2.0030.0070.00**

**2.0050.0060.00**

**2.0060.0080.00**

**2.0040.0080.00**

**2.0070.0080.00**

**2.0050.0070.00**

**2.0060.0070.00**

**2.0070.0090.00**

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