#TTEST SPSS HOW TO#
#TTEST SPSS MANUAL#

#TTEST SPSS MANUAL#

We can conclude that there is a statistically significant relationship between whether the a car has an automatic or manual transmision and the amount of fuel it consumes per 100 kilometers of city driving. In this case, you can see that the F is 8.080 and 'Sig.', which is a p-value, is. The more spread-out the scores are, the larger variance is. Variance is a measure of dispersion, equal to the square of the standard deviation. The t-test and its associated level of significance lead us to reject the null hypothesis that these two means are equal (t = 7.545, df = 402.021, p-value < 0.05). It is a test of one of the assumptions of the t-test, namely that the variances of the two groups are equal. Researchers want to know if a new fuel treatment leads to a change in the average miles per gallon of a certain car.

#TTEST SPSS HOW TO#

This tutorial explains how to conduct a two sample t-test in SPSS. We see the mean difference between the two groups is about 1.66 liters of fuel. A two sample t-test is used to test whether or not the means of two populations are equal. Decide if your test is one-tailored or two-tailored. Before you embark on your SPSS test for independent samples, there are three important things that you should do: Develop a hypothesis statement.

That means we should focus our remaining attention on the results for t-test when equal variances are not assumed (known as WelchвЂ™s t-test). SPSS is one of the conventional technologies used to run the t-test. Ignacio PAIRED-SAMPLES T-TEST A paired-samples t-test (also referred to as repeated measures) is used when you have only one group of people (or companies, or machines etc.) and you collect data from them on two different occasions or under two different conditions. The F-test tells us we should reject the null hypothesis that the variance of fuelusecity is equal across the two groups. It is common to reject a null hypothesis when a reported level of statistical significance for a test is less than 0.05. It also produces the t-test, the degrees of freedom, a significance level, the mean difference, the standard error of that mean difference, and a 95% confidence interval for that mean difference under both the assumption that the variances of the two groups are equal and the assumption that they are not. Under 'Mean Difference', the t-test output adds a calculation of the difference between the means of the two groups: 3.12. This means that it is highly unlikely that the two groups are equal. First it provides an F-test (denoted as LeveneвЂ™s test) of whether or not the variances of fuelusecity for the two groups can be assumed to be equal or not, along with an appropriate estimate of statistical significance. The p-value indicates that a t value more extreme than 6.21 occurs less than 1 out of a thousand times (.001 1/1000) under the null distribution (assuming no difference between the two groups).

SPSS produces a lot of output in this table. Figure 6: Results from using a t-test to test the difference in fuel consumption between automobiles with automatic and manual transmissions, respectively, assuming unequal variance, Fuel Consumption Report, Natural Resources Canada, 2015.

Ttest spss