Running head: T-TEST DATA ANALYSIS AND APPLICATION
For this assignment, the data file ‘grades.sav’ was utilized to measure the difference
between
... [Show More] two data populations and their corresponding means. The two variables applied are
gender and GPA. The analysis and application of the t-test seek to determine if there is a
significant difference between the means of these two variables: gender and GPA. To effectively
utilize the t-test, this paper will focus on the mean values (or the mean difference) for each data
set, the standard deviation of each group, and the number of data values. Doing so will allow us
to gain an accurate depiction of the mean difference between the two variables: gender and GPA.
Data Analysis Plan
This analysis aims to determine the difference between two means, where each group is
independent of one another. For this assignment, the test variable, also known as the outcome
variable, is GPA. As a continuous variable, GPA is quantitative and represented along the ratio
scale of measurement. The measurement’s scale is due to the GPA scores’ interval level of
measurement properties and a true fixed zero point. The predictor variable is gender, where
Group 1 is Female (1), and Group 2 is Male (2). As a qualitative variable, gender is a nominal or
categorical scale of measurement due to its dichotomous nature. The sample size (N) for the data
is 105, with 64 data points in Group 1 and 41 data points in Group 2. While the alpha (α) level in
use is .05.
The research question quantifies the difference between gender and GPA to understand
whether a significant difference exists. The ultimate goal is to determine if there is a substantial
difference between male and female GPA scores. The null hypothesis states that there is no
significant mean difference between gender and GPA. In contrast, the alternative hypothesis
2
Running head: T-TEST DATA ANALYSIS AND APPLICATION
states that there is a meaningful mean relationship between the two variables. With that in mind,
this assignment’s focus relies on a nondirectional hypothesis to initiate the comparison of two
independent variables, which ultimately renders a continuous outcome. In this case, one of these
variables is dichotomous, an essential factor when running the t-test. The t-test is the best choice
based on the nature of the variables presented in the data. This is due to the independent
variables, the dichotomy of one of those variables, and the continuous outcome.
Testing Assumptions
The assumptions of the Independent Samples t-Test that this assignment will test are the
independence of observations, that data is normally distributed, and that there is a homogeneity
of variance. Regarding the independence of observations, the dichotomous nature of the variable
gender makes it evident that participants were assigned to groups according to one “condition,”
Female or Male. This indicates that the research methodology was sound and allowed for the
independence of observation to be maintained. The normality assumption can be observed
through the application of the Shapiro-Wilk Test, as well as, through the observation of skew and
kurtosis values. [Show Less]