![]() We can see that the mean of the sample was 2.9250. The first box gives us the descriptive statistics of our sample of 20 students. In the resulting dialog box place the grade into the test variable box and set the test value to 3. To run the one-sample t-test on these data go to Analyze->Compare Means->One-Sample T test. Open the GradePoint.sav file in SPSS (or enter the data from the example yourself). Our p-value from the test will need to be less than 0.05 to be significant at the 5% level. For significance we often use a p-value of 0.05 (5%) and for the test to be highly significant we use a p-value of 0.01 (1%). If the probability is sufficiently small we can reject the null hypothesis. The test looks at the probability that this sample could have come from a population where the mean value is 3.0 (assuming the population is normally distributed). We are testing from this sample whether the cohort's mean is equal to 3.0 or is less than 3.0. This is called a 2-tailed test.īelow are the grade point averages of 20 randomly selected students from a large biosciences cohort. If we are testing whether a mean value is different from a known value then we test the null hypothesis that the mean is equal to that value against the alternative hypothesis that the mean is not equal to that value. The null hypothesis (written H 0) is that the mean value has not changed and we test this against the alternative hypothesis (written H 1 or H A) that the mean is lower/higher. If we want to test whether a mean value is lower or higher than a particular value (or a mean value has decreased or increased) we are looking at a 1-tailed test. From this we can test hypotheses that the sample comes from a population with a different mean value. We collect a sample and compute the mean value of the sample. ![]() Suppose we know from experience that a population has a mean value of M. We have collected a sample of scale data and want to test whether this sample shows a significant difference from a known mean value.
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