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A study conducted by the research department of a pharmaceutical company claims that the annual spending (per person) for prescription drugs for allergy relief is greater than or equal to the annual spending (per person) for non-prescription allergy relief medicine. A health insurance company conducted an independent study and collected data from a random sample of 275 individuals for prescription allergy relief medicine. The sample mean 17.6 is found to be dollars/year, with a sample standard deviation 5.2 of dollars/year. They have also collected data for non-prescription allergy relief medicine. An independent random sample of 240 individuals yielded a sample mean of 18.4 dollars/year, and a sample standard deviation of 4.0 dollars/year. Since the sample size is quite large, it is assumed that the population standard deviation of the sales (per person) for prescription and non-prescription allergy relief medicine can be estimated by using the sample standard deviation values given above. Is there sufficient evidence to reject the claim made by the research department of the company, at the 0.01 level of significance? Perform a one-tailed test. Then fill in the table below.
State the null hypothesis?
State the alternate hypothesis?
State the type of test statistic?
State the critical value or 0.01 level of significance?
The following sample data shows the quarterly earnings in millions for two US companies. Your research interest is finding if the average earnings for these companies are different.
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Interpret values of b1, b2, b3 and b4 in this estimated regression equation.
Suppose that an automobile manufacturer designed a radically new lightweight engine and wants to recommend the grade of gasoline to use.
Test the given claim using the traditional method of hypothesis testing.
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Perform a proper analysis. Describe your null and alternative hypothesis, report the p-value. What is your conclusion?
Could you explain the Pearson or product-moment correlation? If we were to use a partial correlation, would you want to look at the relationship between two variables while removing the effect of one or two other variables?
We considered Mary's interest in doing a study to see if learning of 6th graders on a math lesson is affected by background noise level. She was planning to use 2 noise conditions and then analyze her outcomes using a t-test for independent groups..
What is the decision regarding the null hypothesis (is there a difference in the mean numbers of cameras sold at the three department store chains)?
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