Dairy sales Peninsula Creameries sells both cottage cheese and ice cream. The CEO recently noticed that in months when the company sells more cottage cheese, it seems to sell more ice cream as well. Two of his aides were assigned to test whether this is true or not. The first aide’s plot and analysis of sales data for the past 12 months (in millions of pounds for cottage cheese and for ice cream) appear below. Dependent variable is Ice cream R-squared = 36.9% s = 8.320 with 12 - 2 = 10 degrees of freedom The other aide looked at the differences in sales of ice cream and cottage cheese for each month and created the following output: Cottage Cheese Ice Cream Count 12 Mean 11.8000 Median 15.3500 StdDev 7.99386 IntQRange 14.3000 25th %tile 3.20000 75th %tile 17.5000 Test H 0 : μ (CC - IC) = 0 vs H a : μ (CC – IC) ≠ 0 Sample Mean = 11.800000 t-Statistic = 5.113 w>11 df Prob = 0.0003 Lower 95% bound = 6.7209429 Upper 95% bound = 16.879057 a) Which analysis would you use to answer the CEO’s question? Why? b) What would you tell the CEO? c) Which analysis would you use to test whether the company sells more cottage cheese or ice cream in a typical year? Why? d) What would you tell the CEO about this other result? e) What assumptions are you making in the analysis you chose in part a? What assumptions are you making in the analysis in part c? f) Next month’s cottage cheese sales are 82 million pounds. Ice cream sales are not yet available. How much ice cream do you predict Peninsula Creameries will sell? g) Give a 95% confidence interval for the true slope of the regression equation of ice cream sales by cottage cheese sales. h) Explain what your interval means.
Dairy sales Peninsula Creameries sells both cottage cheese and ice cream. The CEO recently noticed that in months when the company sells more cottage cheese, it seems to sell more ice cream as well. Two of his aides were assigned to test whether this is true or not. The first aide’s plot and analysis of sales data for the past 12 months (in millions of pounds for cottage cheese and for ice cream) appear below. Dependent variable is Ice cream R-squared = 36.9% s = 8.320 with 12 - 2 = 10 degrees of freedom The other aide looked at the differences in sales of ice cream and cottage cheese for each month and created the following output: Cottage Cheese Ice Cream Count 12 Mean 11.8000 Median 15.3500 StdDev 7.99386 IntQRange 14.3000 25th %tile 3.20000 75th %tile 17.5000 Test H 0 : μ (CC - IC) = 0 vs H a : μ (CC – IC) ≠ 0 Sample Mean = 11.800000 t-Statistic = 5.113 w>11 df Prob = 0.0003 Lower 95% bound = 6.7209429 Upper 95% bound = 16.879057 a) Which analysis would you use to answer the CEO’s question? Why? b) What would you tell the CEO? c) Which analysis would you use to test whether the company sells more cottage cheese or ice cream in a typical year? Why? d) What would you tell the CEO about this other result? e) What assumptions are you making in the analysis you chose in part a? What assumptions are you making in the analysis in part c? f) Next month’s cottage cheese sales are 82 million pounds. Ice cream sales are not yet available. How much ice cream do you predict Peninsula Creameries will sell? g) Give a 95% confidence interval for the true slope of the regression equation of ice cream sales by cottage cheese sales. h) Explain what your interval means.
Solution Summary: The author explains the appropriate analysis for the CEO's question. The scatter plot, regression analysis output, histogram of difference, and descriptive statistics are given.
Dairy sales Peninsula Creameries sells both cottage cheese and ice cream. The CEO recently noticed that in months when the company sells more cottage cheese, it seems to sell more ice cream as well. Two of his aides were assigned to test whether this is true or not. The first aide’s plot and analysis of sales data for the past 12 months (in millions of pounds for cottage cheese and for ice cream) appear below.
Dependent variable is Ice cream
R-squared = 36.9%
s = 8.320 with 12 - 2 = 10 degrees of freedom
The other aide looked at the differences in sales of ice cream and cottage cheese for each month and created the following output:
Cottage Cheese
Ice Cream
Count
12
Mean
11.8000
Median
15.3500
StdDev
7.99386
IntQRange
14.3000
25th %tile
3.20000
75th %tile
17.5000
Test H0: μ(CC - IC) = 0 vs Ha: μ(CC – IC) ≠ 0
Sample Mean = 11.800000 t-Statistic = 5.113 w>11 df
Prob = 0.0003
Lower 95% bound = 6.7209429
Upper 95% bound = 16.879057
a) Which analysis would you use to answer the CEO’s question? Why?
b) What would you tell the CEO?
c) Which analysis would you use to test whether the company sells more cottage cheese or ice cream in a typical year? Why?
d) What would you tell the CEO about this other result?
e) What assumptions are you making in the analysis you chose in part a? What assumptions are you making in the analysis in part c?
f) Next month’s cottage cheese sales are 82 million pounds. Ice cream sales are not yet available. How much ice cream do you predict Peninsula Creameries will sell?
g) Give a 95% confidence interval for the true slope of the regression equation of ice cream sales by cottage cheese sales.
h) Explain what your interval means.
Statistics that help describe, summarize, and present information extracted from data. Descriptive statistics include concepts related to measures of central tendency, measures of variability, measures of frequency, shape of distribution, and some data visualization techniques/tools such as pivot tables, charts, and graphs.
During busy political seasons, many opinion polls are conducted. In apresidential race, how do you think the participants in polls are generally selected?Discuss any issues regarding simple random, stratified, systematic, cluster, andconvenience sampling in these polls. What about other types of polls, besides political?
Please could you explain why 0.5 was added to each upper limpit of the intervals.Thanks
28. (a) Under what conditions do we say that two random variables X and Y are
independent?
(b) Demonstrate that if X and Y are independent, then it follows that E(XY) =
E(X)E(Y);
(e) Show by a counter example that the converse of (ii) is not necessarily true.
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