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A medical school claims that more than 32% of its students plan to go into general practice. It is found that among a random sample of 130 students, 46 of them plan to go into general practice.
a. Formulate the hypotheses to test the medical school's claim.
b. Test these hypotheses and draw a conclusion about the claim. Use an alpha level of 0.05 (show your work and state your conclusion)
c. Find the p-value for the test of the schools claim. Does this p-value support your conclusion ? Why or why not?
Supposing a linear relationship, use the least squares method to find the regression coefficients b 0 and b 1 .
Using random numbers of 0.1562, 0.9821, 0.3409, 0.5594, and 0.7758, compute the time required for each of five simulated maintenance checks of the airplaine's landing gear.
The normal distribution has several characteristics that make it the underlying foundation of much of inferential statistical tools.
A research company stated that 20% of missed school days are due to asthma. If a group of 400 school children are selected at random, what is the probability that fewer than 70 will miss school because of asthma?
Plot the control limits for the mean outside diameter and the range.
You will actually have negative sales using this multiple regression analysis
The manager of a local gymnasium has determined that the length of time patron spend at the gymnasium is normal distributed with mean 80minutes and standard deviation 20 minutes. What is the patrons who spend more than 120 minutes at the gymnasium..
Several questions will be asked but the main outcome measure of interest will be the percentage of customers who were completely satisfied and plan to return and the average amount spent.
Over the past decade, there has been a strong positive correlation between teachers salaries and prescription drug cost.
Suppose we estimate this model with OLS, and there is a correlation between unobserved student traits (in the error term) with attendance. How does this bias the coefficient of attendance?
What is the aim of multiple linear regression? Discriminate analysis? Canonical correlation? Multivariate analysis of variance?
Give an example of a problem (business, political, scientific) in which ANOVA analysis would be appropriate. (Hint: the dependent variable is categorical, such as male vs. female or comparing three different types of fertilizer.)
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