Question

I NEED ANSWER OF A, B, C, D

You are probably familiar with (and may have used) back belts, which are widely used by workers to protect their lower backs from injuries caused by lifting. A study was conducted to determine the usefulness of this protective gear. Here is a partial description of the study, published in the Journal of the American Medical Association and reported by the Associated Press (December 5, 2000):

New research suggests that back belts, which are widely used in industry to prevent lifting injuries, do not work. The findings by the National Institute for Occupational Safety and Health stem from a study of 160 Wal-Mart stores in 30 states. Researchers [based their findings on] workers’ compensation data from 1996 to 1998.

    Although you do not know the study’s particulars, think about how you would go about investigating the effect of back belt usage on back injuries. Assume that you have data on each of the 160 retail stores in your study. For each store, you know whether back belt usage was low, moderate, or high. You classify 50 stores as having low belt usage by employees, 50 stores as having moderate usage, and 60 stores as having high usage. You also know the number of back-injury workers’ compensation claims from each store. This information permits you to calculate the mean number of claims for low-usage, moderate-usage, and high-usage stores.

A.   The following hypothesis suggests that back belt usage helps prevent injury: In a comparison of stores, stores with low back belt usage by employees will have more worker injuries than will stores with high back belt usage. What is the independent variable? What is the dependent variable? Does this hypothesis suggest a positive or negative relationship between the independent and dependent variables? Explain.

B.   Fabricate a mean comparison table showing a linear pattern that is consistent with the hypothesis. Sketch a line chart from the data you have fabricated. (Because you do not have sufficient information to fabricate a plausible mean for all the cases, you do not need to include a “Total” row in your mean comparison table.)

C.   Use your imagination. Suppose the data showed little difference in the worker injury claims for low-usage and moderate-usage stores, but a large effect in the hypothesized direction for high-usage stores. What would this relationship look like? Sketch a line chart for this relationship.

There us no data, you have to hypothesis it.

Answer 1

Answer:

Ok , no data given to us , so lets simulate this in excel

Lets simulate some data in excel for the 50 stores falling under the low , moderate and high categories

after having done this , we shall formulate the hypothesis as

H0 : There is no difference in the worker injuries for low and high categories

H1 : There is a signifcant difference in the worker injuries for low and high categories

Lets now perform the test in excel and see whether the results are significant or not

Dependent variable : Worker injuries

Independent variable : Categories , Low or High , we shall also consider the alpha as 0.05 for our test , Please see the set up in excel as shown below , we must goto the data> data analysis tool pack

The results are

As the p value is less than 0.05 , we can reject the null hypothesis in favor of alternate hypothesis and conclude that There is a signifcant difference in the worker injuries for low and high categories

we calculate the mean of all the 3 columns as shown above and then plot a line chart

Mean Comparison table
Low	Moderate	High
34.84	29.62	14.3

If the data showed little difference between low and moderate categories but high towards High catergories , the line chart would look something like this ,

Please note we just need to make sure that the data points for low and moderate are close to each other while the data points for high category is considerably low for high usage stores . As can be seen from the simulated data , the mean values of low and moderate usage stores are alomost similar while it is considerably low for the high usage stores.