Essay about Statistics and Opposite Sex

Submitted By soiekfihe
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Pages: 3

males (M) and females (F).
z = 2.12 p-value = 0.017
z = -0.2 p-value = 0.579

c. Refer to part (b). Compare the results for males and females by writing a summary of the results in words that would be understood by someone who has not studied statistics.
It is easier for women to find male friends then for men to find female friends.

d. Compare your results in parts (a) and (b). Explain how they are similar and how they are different, if at all. Explain any discrepancies you found. Part a and part b can be said to be different where the z values and p values were different. Also however there are no discrepancies particularly found anywhere in my personal opinion.

e. Is there sufficient statistical evidence to conclude that the population proportions of men and women who would answer ”Opposite Sex” differ?
I do think there is a sufficient statistical.

Carry out the five steps of the appropriate hypothesis test.
Step 1:
Ho: - 0.562 0
Ha: - 1.94 0
Step 2: Conditions met?
I do think that the conditions meet.

Step 3: z = 1.196
Null standard error = 1.3 p-value 0.315

Steps 4 and 5: Do you reject the null hypothesis?
Conclusion: There ____I don’t think there were a_____ convincing evidence to support the idea that the proportions of men and women who would answer ”opposite sex” differ in the population.

2. For this exercise, use the dataset UCDavis2. The variable Seat is a response to the question ”Where do you typically sit in a classroom?” Possible responses were F = Front, M = Middle, B = Back. The variable SeatCode is 1 if middle, 0 if not middle (Front or Back).

a. Test the hypothesis that a majority of students prefer to sit in the middle of the room. z = 2.4 p-value = 0.033
Explain your conclusion b. Specify the population of interest, and comment on whether this sample is an appropriate representation of it.
We can prove that this sample was a trust worthy sample which can be sued there for it is a appropriate representation.

3. Refer to Case Study 1.6, comparing heart attack rates for men who had taken aspirin or placebo. Suppose the observed proportions of .017 and .0094 are actually the correct population proportions who would have heart attacks with placebo and with aspirin. The following Minitab output shows the power of a one-sided test for two proportions for this situation for three sample sizes. The samples are the number of participants in each group (aspirin and placebo). Suppose you are the statistician advising a research team about conducting a new study to confirm the results of the old study. The researchers comment that samples of size 500 in each condition should be sufficient, since the effect is obviously so strong, based on the small p-value for the previous study.
What would you advise? Explain.
The larger the