Reference no: EM133744838

Basic Business Statistics Concepts and Applications

A pet food company has the business objective of expanding its product line beyond its current kidney- and shrimp-based cat foods. The company developed two new products-one based on chicken livers and the other based on salmon. The company conducted an experiment to compare the two new products with its two existing ones as well as a generic beef-based product sold in a supermarket chain.

For the experiment, a sample of 50 cats from the population at a local animal shelter was selected. Ten cats were randomly assigned to each of the five products being tested. Each of the cats was then presented with 3 ounces of the selected food in a dish at feeding time. The researchers defined the variable to be measured as the number of ounces of food that the cat consumed within a 10-minute time interval that began when the filled dish was presented. The results for this experiment are summarized in the following table and stored in : CatFood

At the 0.05 level of significance, is there evidence of a significant difference in the median amount of food eaten among the various products?

Compare the results of (a) with those of Problem

At the 0.05 level of significance, is there evidence of a difference in the mean amount of food eaten among the various products?

Which test is more appropriate for these data, the Kruskal-Wallis rank test or the one-way ANOVA F test? Explain.

A hospital conducted a study of the waiting time in its emergency room. The hospital has a main campus, along with three satellite locations. Management had a business objective of reducing waiting time for emergency room cases that did not require immediate attention. To study this, a random sample of 15 emergency room cases at each location were selected on a particular day, and the waiting time (recorded from check-in to when the patient was called into the clinic area) was measured. The results are stored in ERWaiting.
At the 0.05 level of significance, is there evidence of a difference in the median waiting times in the four locations?

A hospital conducted a study of the waiting time in its emergency room. The hospital has a main campus and three satellite locations. Management had a business objective of reducing waiting time for emergency room cases that did not require immediate attention. To study this, a random sample of 15 emergency room cases that did not require immediate attention at each location were selected on a particular day, and the waiting time (measured from check-in to when the patient was called into the clinic area) was measured. The results are stored in ERWaiting.
a. At the 0.05 level of significance, is there evidence of a difference in the mean waiting times in the four locations?

The per-store daily customer count (i.e., the mean number of customers in a store in one day) for a nationwide convenience store chain that operates nearly 10,000 stores has been steady, at 900, for some time. To increase the customer count, the chain is considering cutting prices for coffee beverages. Management needs to determine how much prices can be cut in order to increase the daily customer count without reducing the gross margin on coffee sales too much. You decide to carry out an experiment in a sample of 24 stores where customer counts have been running almost exactly at the national average of 900. In 6 of the stores, a small coffee will be $0.59, in another 6 stores the price will be $0.69, in a third group of 6 stores, the price will be $0.79, and in a fourth group of 6 stores, the price will now be $0.89. After four weeks, the daily customer count in the stores is stored in CoffeeSales.

At the 0.05 level of significance, is there evidence of a difference in the daily customer count based on the price of a small coffee?

Compare the results of (a) with those of Problem 11.11 (a) on page 428.

a. At the 0.05 level of significance, is there evidence of a difference in the daily customer count based on the price of a small coffee?

A large corporation is interested in determining whether a relationship exists between the commuting time of its employees and the level of stress-related problems observed on the job. A study of 116 workers reveals the following:
At the 0.01 level of significance, is there evidence of a significant relationship between commuting time and stress level?

What is your answer to (a) if you use the 0.05 level of significance?