This Question: 4 pts 3 of 25 (16 complete) This Test: 100 pts possible The distr

Question

This Question: 4 pts 3 of 25 (16 complete) This Test: 100 pts possible The distribution of scores on a test for a particular class is skewed to the left The professor wants to predict the maximum score and understand the distribution of the sample maximum. She simulates the distribution of the maximum of the test for 36 different tests with n = 5). The histogram to the ri ht shows a simulated samplin distribution ofthe sample ma m um rom these tests Complete pats a and b) below. 35 40 45 50 Max Score a) Would a Normal model be a useful model for this sampling distribution? Explain OA. No. The sampling distribution of the maximum is skewed to the left, so a Normal model would not be useful for this sampling distribution O B. No. The sampling distribution of the maximum is symmetric and unimodal, so a Normal model would not be useful for this sampling distribution O C. Yes. The sampling distribution of the maximum is symmetric and unimodal, so a Normal model would be useful for this sampling distribution. O D. Yes. The sampling distribution of the maximum is skewed to the left, so a Normal model would be useful for this sampling distribution. b) The mean of this distribution is 461 and the SD is 3 5 would you expect about 68% ofthe samples to have her maximums within 35 of 46 12 Why or why not? OA. No. The 68 95 99.7 Rule is based on the Normal distribution. OB. Yes. The 68-95-99.7 Rule is based on the Normal distribution C. Yas The valuas shnw too little variation to annlu the 68 95 99 7 Ridla Click to select your answer

Explanation / Answer

Solution:-

a) No, The sampling distribution of the maximum load is skewed to the left, so a Normal model would not be useful for this sampling distribution.

b) No, The 68-95-99.7 rule is based on the normal distribution.

Related Questions

Navigate

• Browse (All)
• Browse T
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.