Essay On GPA

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The study performed on students enrolled in the MBA program at Whatsamattu U will determine the mean of students GPA. The variables in this study include their age, gender, major; GPA, Bachelors GPA, course load, English speaking status, family, and weekly hours spent studying. Although it is common, most schools grades at the MBA level are divided only between A's and B's. For that reason, the graph displays an expected mean GPA of 3.50. In order to examine the unknown data, we will conduct a hypothesis test with significance level of 0.50 (a tolerance level of error we are willing to accept during this study). Furthermore, the one sample hypothesis test for the mean will calculate the unidentified statistics to determine if the …show more content…

Statistic supporters report that if a null rejection transpires, then the null hypothesis must conclude that H1 is true (Mirabella, 2011). Following, the upper-tail test identifies a p-value of 0.9998, which suggest not rejecting the null hypothesis. Research contest the p-value is the possibility of making a mistake if the null is rejected (Farnsworth, 2016). Nevertheless, if a rejection of the null hypothesis occurs, then insufficient evidence proposes that H1 exists as proofs (Mirabella, 2011). Further concluding the lower-tail test identifies a p-value of 0.002, therefore, the decision remains; reject the null hypothesis. According to Mirabella (2011), the confidence interval is another way to acquire the sample mean. To organize this, just utilize the mean added to or minus a margin of error. Furthermore, the margin of error or sampling error is merely the difference between the results and the truth (Mirabella, 2011). Therefore, the sampling error necessity determined is vital in order to develop a sample mean. Early units have taught us, the Z score times the standard deviation divided by the square root of the sample size. Therefore, the Z score remains known as plus/minus of the level of confidence based on the data in the normal distribution. Through reflection, the standard deviation remains characterized as a typical distance of an observation from the distribution center or middle value (Barde & Barde, 2012). Following,

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