Question

1. Interpret your results. Guidelines for interpreting dependent t tests can be found in What to Include When Writing Up Dependent t Test Results (PDF).

Answer 1

Interpret your results. Guidelines for interpreting dependent t tests can be found in What to Include When Writing Up Dependent t Test Results (PDF)

Answer:

Guidelines for interpreting independent t tests can be found in : What to Include When Writing Up Independent t Test Results (PDF).

The independent-samples t-test (or independent t-test, or students t-test) compares the means between two independent variables on the same dependent variable.

The null hypothesis for the independent t-test is that population means from the two unrelated groups or the independent variables are equal:

H0: m1 = m2

In the alternative hypothesis the population means are not equal:

H1: m1 ≠ m2

OR

H0: m1 - m2 = 0 (the difference between the two population means is equal to 0)

H1: m1 - m2 ≠ 0 (the difference between the two population means is not 0)

where, m1 is the mean of women’s weight and m2 is the mean of men’s weight

To reject or accept the alternative hypothesis, we have to set a significance level (alpha , P) that allows us to either reject or accept the hypothesis. Usually this value is set at 0.05

Degrees Of Freedom (df):

As we are working with two independent groups, restrict one df to the mean for each group. Therefore, df for an independent-samples t test will be (n1 – 1) + (n2 –1), where n1 and n2 are the sample sizes for each of the independent groups, respectively.

Or N – 2, where N is the total sample size for the study.

Assumption of homogeneity of variance can be tested using Levene's Test of Equality of Variances ; as the independent t-test assumes the variances of the two groups you are measuring are equal in the population.

Reporting:

An independent-samples t-test was conducted to compare the weight women and men.

One-sample t(df) = t-value, p = p-value

Two-sample t(df) = t-value, p = p-value

paired t(df) = t-value, p = p-value