EP BUSINESS STATISTICS:FIRST COURSE-ACC
EP BUSINESS STATISTICS:FIRST COURSE-ACC
8th Edition
ISBN: 9780135179802
Author: Levine
Publisher: PEARSON CO
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The mean hourly wage for employees in goods-producing industries is currently $24.57. Suppose we take a sample of employees from the manufacturing industry to see if the mean hourly wage differs from the reported mean of $24.57 for the goods-producing industries. State the null and alternative hypotheses we should use to test whether the population mean hourly wage in the manufacturing industry differs from the population mean hourly wage in the goods-producing industries. Suppose a sample of 30 employees from the manufacturing industry showed a sample mean of $23.89 per hour. Assume a population standard deviation of $2.40 per hour. With α = .05 as the level of significance, what is your conclusion?
Nature lovers’ association of Australia, launched a campaign to encourage paper less communication and/or recycling of used papers to save the trees to reduce global warming. Hence, many small businesses have scaled up their business such as new forms of online document exchanges and collecting used papers and cardboards from households and companies. Abita Recycling Ltd is one such company which is operates in Melbourne. The financial analysist of the company has estimated that the firm would make a profit if the mean weekly collection of papers and cardboards from each household exceeded 1KG. To examine the feasibility of a recycling plant, a random sample of 100 households was selected and sample mean and standard deviations are 1.1KG and 0.35KG respectively.   find value of test statistics and null and alternate hypothesis.
Import the data from the Hill City Excel file into Minitab.You are trying to predict Price.Note: Mtn View=1 if there is a mountain view, 0 otherwise. The rest of the variables should be self explanatory. 1.Perform an F Test for overall significance of the model 2.Perform a T test for slope for the age variable 3. Find a 95% confidence interval for the slope of the SqFeet variable4. Create a prediction, CI, and PI for 1 new set of x values (any valid numbers you want), and interpret each.5. Run the residual plots and indicate if they show any problems with the model.
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