It is pretty common across most schools to find the grades at the MBA level divided between A’s and B’s. As such, you expect the mean GPA to be around 3.50. Using the sample of 200 MBA students, conduct a one-sample hypothesis test to determine if the mean graduate GPA is different from 3.50. Use a .05 significance level. Report on your findings (100+ words, 3 or more sentences). In your report, be sure to include the results of the hypothesis test and indicate whether you are using a two-tail, upper-tail, or lower-tail test. Also include a chart (a bar chart or column chart will probably work best) comparing the calculated mean with the hypothesized mean.

We have no access to your data, but this might help.

Z = (mean1 - mean2)/standard error (SE) of difference between means

SEdiff = √(SEmean1^2 + SEmean2^2)

SEm = SD/√n

If only one SD is provided, you can use just that to determine SEdiff.

Find table in the back of your statistics text labeled something like "areas under normal distribution" to find the proportion related to the Z score.

It would be a two-tailed test, since you are not predicting the direction of the difference.

To conduct the one-sample hypothesis test, we can use the t-test as we are comparing the mean graduate GPA of 200 MBA students to a specific value (3.50).

First, we set up the null and alternative hypotheses:
- Null hypothesis (H0): The mean graduate GPA is equal to 3.50
- Alternative hypothesis (Ha): The mean graduate GPA is different from 3.50

Next, we need to determine the significance level (α) which is given as 0.05, meaning we are willing to accept a 5% chance of making a Type I error (rejecting the null hypothesis when it is true).

Now, we can calculate the t-statistic and p-value. Assuming we have the sample mean and standard deviation, we can plug these values into the formula: t = (sample mean - hypothesized mean) / (sample standard deviation / sqrt(sample size)).

Once we have the t-statistic, we can find the p-value associated with it using a t-table or a statistical software. If the p-value is less than the significance level (α), we reject the null hypothesis. Otherwise, we fail to reject the null hypothesis.

After performing the calculation and obtaining the results, we can conclude whether the mean graduate GPA is different from 3.50 or not. It is important to mention the type of test used (two-tail in this case) and present a chart comparing the calculated mean with the hypothesized mean (3.50) to provide a visual representation.