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Question: A professor used data from last semester's statistics class to create a regression that predicts how students will do on the final exam. The equation is yˆ = 70.2 + 3.2 (X1) - 6(X2), where X1 is the number of hours studied for the exam and X2 is the number of sleep interruptions the night before the exam. What is the predicted score of:
a) a student who studied for 10 hours and had 2 sleep interruptions?
b) a student who studied for 6 hours and had no sleep interruptions?
a national study has determined that people who work full time average 43.4 hours worked per week. assume that the
In a large section of statistics class, the points for the final exams are normally distributed with a mean of 72 and a standard deviation of 9. Grades are to be assigned according to the following rule.
find the z-score for the standard normal distribution wherepzlta
While in Paymor Hospital such exams were given in 110 out of 200 cases. In a left-tailed test for equality of proportions, the p-value is?
What is the probability that none can transact business in a foreign language?
In a sample of 476 adults selected randomly from one town, it is found that 9 of them have been exposed to a particular strain of the flu. Find the Pvalue for a test of the claim that the proportion of all adults in the town that have been exposed..
Describe a simulation to estimate the probability of answering at least four of the ten questions correctly. carry out three repititons. estimate the probability
The flashlight batteries produced by one of the northern manufacturers are known to have an average life of 60 hours with a standard deviation of 4 hours. Use Chebyshev's theorem to answer the following questions.
Whose characteristics can be assume to be independent of each other, were examined. Let X denotes the number of defective computer chips.
The standard deviation is 4. what is the best point estimate of the mean? find the 95% confidence interval of the mean score for golfers.
What are the requirements that must be met for a regression analysis? What happens if these requirements are violated? Why is the analysis of residuals important?
What sample size and acceptable level would result in a probability of .05 that a good batch will be rejected and a probability of .10 that a bad batch will be accepted?
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