Given the value is 0.959, it is greater than 0.05 therefore the variances are almost equal or has no treatment effect The Levene’s Test for Equality determined the variances show there is no treatment effect due to the fact they are almost equal. A value 0.05 or greater would tell that the variances are not considerably diverse. The significant value will need to be 0.05 or less for either variance to be measured as considerably diverse. There is approximate equal variance between the two groups on the dependent variable. In terms of the Levene’s Test for Equality of Variances, it shows if the second assumption is satisfied. Thus, we can conclude for this assignment the normal distribution is slightly departing from a perfect normal shape as the value is indicating a 0.972 for gender 1 and 0.960 for gender 2. Anything less than 1.0 would represent a departure from a perfect normal shape. For this test, to have a normal distribution results would have to indicate a value of 1.0. The Shapiro-Wilk Test is considered a formal statistical test of normality. With these calculations, one can conclude there is a difference of -2.491 between the two samples. Within the 33 observations there is a mean GPA of 101.82 and a standard deviation of 12.677. In looking at Gender 2, there is a sum of 33 observations. Within those 55 observations there is a mean GPA of 99.33 and a standard deviation of 13.192.
As listed, there is a sum of 55 observations for gender 1. The t-test will assess for a significant difference of the two-sample’s means. An unpaired t-test can be conducted since both samples are independent of each other. Since the p-value is > than 0.05, the samples are considered drawn from normal population. This is a lower bound of the true significance.Īfter reviewing the descriptive table output by the SPSS software, it can be determined that both samples are drawn from normal population. This can be checked by using the Levene’s Test. In addition, the two groups have no effect on the dependent variable. The next assumption is that the two groups are considered independent of each other. Some assumptions that can be made are, that the dependent variable can be considered as normally distributed, this can be checked with the Q-Q plot. GPA is the second variable yet this variable is measured on an interval scale rather than a nominal scale. This variable is considered a dichotomous variable that has values of 1 and 2. Gender, which is measured on nominal scale of measurement is the first variable. GPA and Gender are the variables used for this assignment.
For this assignment, descriptive statistics, visual representation of the distribution, test of normality, as well as an independent samples t-test and test of homogeneity will be created and computed. Per Howell (2011), an independent samples t-test compares the mean scores of two groups on a given variable. It is a value between 1-100, and it is an interval measurement.įinal: This is only the final score, also an interval measurement Total: It is the combined scores of quizzes one, two, three, four, five, and the final exam. GPA: It is the cumulative grade point average of students at the start of the course. “ Gender: Categorical variable, having two values 1 for female and 2 for male. Lacharite (2017), previously reported the description of the data as: In terms of a non-directional alternative hypothesis, the research will propose that the population means vary, however, it will not specify which mean is preeminent. When speaking of a directional alternative hypothesis for a t test, the researcher will conclude that the population means vary in a precise track. The null hypothesis predicts no significant difference in population means. In this paper, we will also explore the null and alternative hypothesis for t-tests. Along with the logic of t-tests, all inferential statistics include independent variables of t-tests and all function under assumptions. There is the predictor variable (X) and the outcome variable (Y). There are always two variables when involving t-tests.
Lacharite Capella UniversityĪ rudimentary inferential statistic that is frequently used in psychological study is called the t-test. Data Analysis and Application: T-tests Heather A.
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