Question

To conduct tests of significance (such as t-tests and F-tests) several assumptions are made about the distribution of scores: that they are reasonably normal, and that the variances of the groups are homogeneous. Check the distributions for normality (you may wish to include the notion of skewness) and test homogeneity of variances for the two groups for both variables (for the two significance tests in 4.2).

This involves checking the scores for each group to determine if they are reasonably normally distributed: are means and medians similar? are the data skewed? does the distribution look similar to one that is normal?

The second part is to check the homogeneity of variance. This can be done using the Fmax test (see Gravetter & Wallnau, 2014) or the Levene's test which SPSS provides.

Answer 1

Answer:

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Answer 2

Step-by-step explanation:

T-tests are commonly used in statistics and econometrics to establish that the values of two outcomes or variables are different from one another.

The common assumptions made when doing a t-test include those regarding the scale of measurement, random sampling, normality of data distribution, adequacy of sample size and equality of variance in standard deviation.

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