Ga Improvement Research Paper

The relevant independent variable in his study is hours worked by a student; the relevant dependent variables in his study are credits completed per semester and student GPA. Darolia’s study also considers disparate effects on GPA and credit completion based on student characteristics (e.g., gender, full or part-time status).

Because the p-value of .035 is less than the significance level of .05, I will reject the null hypothesis at 5% level.

Note: the program we used on this worksheet said the results were not significant, but then in statistical notion it had “p < 0.05”. That is confusing because I believe it should be “p >

Schlosser. She carried out the study while on a post-doctoral fellowship at Princeton University, and will study the effects of gender in higher education lecture halls next. This is one of few studies of its kind to use scientific data to address the question of gender effects in school. Boys with more female peers in their classes show higher enrollment rates in both advanced math and science classes, but overall benefits were found in all grades for both sexes. Prof. Schlosser found that primary-school classrooms with a female majority showed increased academic success for both boys and girls, along with a notable improvement in subjects like science and math. In the middle schools, girls were found to have better academic achievement in English, languages and math. And in high school, the classrooms which had the best academic achievements overall were consistently those that had a higher proportion of girls enrolled. A higher percentage of girls lowers the amount of classroom disruption and fosters a better relationship between pupils and their teacher, a study of the data suggests. Teachers are less tired in classrooms with more girls, and pupils overall seem to be more satisfied when a high female-to-male ratio persists. Prof. Schlosser was inspired to the study by a “renewed interest on the effects of classroom gender composition on students’ learning, since a new amendment to America’s Title IX

Gender – whether there was a difference in performance between genders; used for comparison between male and female participants

Since the P-value (0.386) is greater than the significance level (0.05), we fail to reject the null hypothesis. The p-value implies the probability of rejecting a true null hypothesis.

The degree of freedom in this experiment was 3. The chi-square value that was calculated was 1.4481. The p-value was 0.6943.

According to the above results from MINITAB, the p-value of 0.038 is smaller than the significance level of 0.05; consequently, the null hypothesis will be rejected. There is sufficient evidence to support the

* The F-value suggests that there is a significant difference between the results of the control and treatment groups. The P-value of 0.005 is < the alpha of 0.05. This suggest that the groups are significantly different and the null hypothesis should be rejected.

With a P-value of 0.00, we have a strong level of significance. No additional information is needed to ensure that the data given is accurate.

The relationships between the variables “GPA” and “SEX” can give the admissions department a general idea of how and if gender has any effect on students academic performance. “SEX” can be looked at as a control variable when comparing other variables as well.

The results from this study only reflect a very small number of the population, so it is difficult for this experiment to show any significant results. It would have reflected better on the results if the sample size had been meet, however it was not possible due to lack of time and number of eligible volunteers.

Assumption 3 is homogeneity of variance, that the variances of the outcome variable in both groups, the male group and the female group, will be equal. The Levene Test for Equality of Variances has a sig. value of .566. This number is higher than .05 and, therefore, implies that the variability of the two groups is about equal.

In this case, level of significance, α was not provided. Therefore, the analysis will be evaluated based on two α values which are:

Gender differences occur in many aspects of a person’s life whether it is culture, politics, occupation, family and relationships, or the economy (just to name a few). One major difference in gender occurs in learning and education in the elementary and secondary levels. Research has found that males and females learn differently in many aspects of education. First of all, female and male brains are constructed differently affecting the way they learn; this leads to basic differences in learning and also gives an introduction into why the way one learns differs according to gender and how males and females learn subjects and tasks differently. Second, males and females are treated differently, sometimes unconsciously, in educational