Statistical Assumptions of Independent Samples Test3
Independent and Dependent Variables4
Null and Alternative Hypothesis4
Results & Interpretation4
Hypothesis Assessment Summary6
Conclusion6
Low Income Cannot Afford More Children
Introduction
The study is related to independent samples test, which is being studied in context of a low income level and having more children that also include males and females. As it is known that income level is important for the survival, though, it is necessary to evaluate this statement. Moreover, the data for this study is collected from GSS data disk.
Statistical Assumptions of Independent Samples Test
The t-test is the most common method to assess the differences between the means of two groups. Theoretically, we can use the same t-test on very small sample size (n = 10 for example, some researchers claim that even smaller samples can be used), so that the variables are normally distributed in each group and the dispersion results in the two groups was not significantly different (Green & Salkind, 2011). The statistical assumptions for the independent samples test are mentioned below:
It is necessary that all the observations for the of independent samples test should be treated as an independent of each other;
It is necessary that the dependent variable of the independent samples test should be measured on a ratio or interval level scale;
It is crucial that the dependent variable in the independent samples test should be distributed normally in the population data which shows that assumption of normality;
In context of assumption pertaining to variances homogeneity, the distribution of the dependent variable in the independent sample t-test for one of the groups being compared should have the identical or equal variance as the distribution for the other group being compared (Frankfort-Nachmias & Nachmias, 2008).
Independent and Dependent Variables
The independent variable that is used in the study of ...