Reference no: EM1316581
Finding the normal model for the given proportions.
In a large statistics class, the professor has each student toss a coin 50 times and calculated the proportion of his or her tosses that were tails. The students then report their results, and the professor plots a histogram of these several proportions. Should a Normal model be used here?
1. A normal model should be used because the 50 coin tosses can be thought of as a random sample of coin tosses and are fewer than 10% of the population of all coins.
2. The success/failure condition is also satisfied because np = 25 10 and nq = 25 10.
3. A Normal model should not be used because the sample size, 50, is larger than 10% of the population of all coins.
4. A Normal model should not be used because the sample size is not large enough to satisfy the success/failure condition.
5. A Normal model should be used because the samples are random and independent. Also, the sample size, 50, is less than 10% of the population. Most importantly, the original population has a Normal distribution.
6. A Normal model should not be used because the population distribution is not Normal.