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Testing the significance of correlation.
A manufacturer must decide whether to extend credit to a retailer who would like to open an account with the firm. Past experience with new accounts indicates that 45% are high-risk customers, 35% are moderate-risk customers, and 20% re low-risk customers. If credit is extended, the manufacturer can expect to lose $60,000 with a high-risk cutomer, make $50,000 with a moderate-risk customer, and make $100,000 with a low-risk customer. If the manufacturer decides not ot extend credit to a customer, the manufacturer neither make nor loses any money. Prior to making a credit extension decision, the manufacturer can obtain a credit rating agency concedes that its rating procedure is not completely reliable. In particular, the credit rating procedure will rate a low-risk customer as a moderate-risk customer with probability 010 and as ahigh-risk customer with probability 0.05. Furthermore, the given rating procedure will rate a moderate-risk customer as a low-risk customer with probability 0.06 and as a high-risk customer with probability 0.07. Finally, the rating procedure will rate a high-risk customer as a low-risk customer with probability 0.01 and as a moderate-risk customer with probability 0.05.
1. Find the strategy that maximizes the manufacturer's expected net earnings.
2. Should the manufacturer routinely obtain credit rating reports on those retailers who seek credit approval? Why or why not?
The 95% confidence interval for the mean of the sampling distribution of the mean is about:
Calculate probability that the sample would have a mean:
To sketch the 3-sigma X-bar chart and R-chart parameters. A candy bar manufacturer desires to set up a variables control chart for the net weight of its candy bars.
For following two regressions describe and interpret major parts from regression output. write down the difference between two regressions?
To select a _________ sample, an intact group of subjects that represent the population is selected.
Use the following data to write the normal equations of the linear regression between Y and X, and find the least squares regression.
Determine a 95% confidence interval for the population mean.
At the .01 significance level can we conclude the mean age is more than 8.4 years for the cars of university students? State the null hypothesis and the alternate hypothesis.
Describe the given data show a seasonal effect using moving average method. Describe the data which show a seasonal effect.
A check of dorm rooms on a large college campuses revealed that 38% had refrigerators, 52 percent had TVs and 21 percent had both a TV and a refrigerator. What's the probability that a randomly selected dorm room has.
Find a 96% confidence interval for the true percentage of all households that have central air conditioning. Write a sentence that interprets this interval.
Using the p-value approach, test the hypotheses at the 1% level of significance.
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