Using the partial R output, answer the questions below. (a) Estimate the model. Use two-decimals your estimation of the slope term, no decimals in the estimation of the y-intercept. MonthlySales, = I Percent HSGrads, (b) What percentage of the variation in a store's monthly sales cannot be explained by its linear dependency on the percentage of the customer base that are high school graduates? Enter your answer as a percentage, using two decimal places.

Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 93E
icon
Related questions
Topic Video
Question

R-Studio. Thank you in advance!

(c) Does the data collected indicate that the monthly sales of a store can be expressed as a linear function the percentage of high school graduates in its customer base? Select the correct statisticaly hypotheses.
А. Но : В1
В. Но : В — о На : В >0
C. Ho : B1 20 HẠ : B1 > 0
D. Ho : B1 = 0 HẠ : B1 + 0
E. Ho : B1 2 0 HẠ: B1 < 0
F. Ho : B1 > 0 HẠ : B1
0 HA : B1 < 0
(d) Using the F-test, test the statistical hypotheses determined in (c). Find the value of the test statistic, using two decimals in your answer.
Feale
%3D
(e) Testing the statistical hypotheses in (c) at a = 0.05, you can conclude from this data that the
?
?
v be expressed as a linear function of the
?
(f) Can you infer from this data that an increase of 1% to the percentage of high school graduates in the customer based will lead to an mean/average increase in the store's monthly sales by more than $50,000?
(i) Find the value of the test statistic, use two decimal places in your answer.
Tcalc
...
(ii) Find the P-value of the result, using three decimals.
P-value =
(g) A store located at a local mall has recently discovered that 90% of its customer base has a high school diploma. With 95% confidence, estimate this store's monthly sales for the current month.
38
38
Note: You will need E, Percent HSGrads; = 2935.17 and E, Percent H SGrads
= 228777
i=1
i=1
Lower Bound =
$1000s (use one decimal in your answer)
Upper Bound =
$1000s (use one decimal in your answer)
(h) A residual plot of the regression was consulted.
Residual Plot
(Response is Sales in $1000s)
2000
1500
1000 -
500 -
-500 -
-1000
-1500
500
1000
1500
2000
2500
Fitted Value
O O
Residual
Transcribed Image Text:(c) Does the data collected indicate that the monthly sales of a store can be expressed as a linear function the percentage of high school graduates in its customer base? Select the correct statisticaly hypotheses. А. Но : В1 В. Но : В — о На : В >0 C. Ho : B1 20 HẠ : B1 > 0 D. Ho : B1 = 0 HẠ : B1 + 0 E. Ho : B1 2 0 HẠ: B1 < 0 F. Ho : B1 > 0 HẠ : B1 0 HA : B1 < 0 (d) Using the F-test, test the statistical hypotheses determined in (c). Find the value of the test statistic, using two decimals in your answer. Feale %3D (e) Testing the statistical hypotheses in (c) at a = 0.05, you can conclude from this data that the ? ? v be expressed as a linear function of the ? (f) Can you infer from this data that an increase of 1% to the percentage of high school graduates in the customer based will lead to an mean/average increase in the store's monthly sales by more than $50,000? (i) Find the value of the test statistic, use two decimal places in your answer. Tcalc ... (ii) Find the P-value of the result, using three decimals. P-value = (g) A store located at a local mall has recently discovered that 90% of its customer base has a high school diploma. With 95% confidence, estimate this store's monthly sales for the current month. 38 38 Note: You will need E, Percent HSGrads; = 2935.17 and E, Percent H SGrads = 228777 i=1 i=1 Lower Bound = $1000s (use one decimal in your answer) Upper Bound = $1000s (use one decimal in your answer) (h) A residual plot of the regression was consulted. Residual Plot (Response is Sales in $1000s) 2000 1500 1000 - 500 - -500 - -1000 -1500 500 1000 1500 2000 2500 Fitted Value O O Residual
A national sporting good store wishes to use demographic information to predict its monthly sales, in $1000s. Thrity-eight, n =
38, stores of the chain are randomly chosen across the country. It is known that each store is approximately the same size and carries the same
merchandise.
The geographic area from which a store draws its customers is known as the customer base. One of the variables is the percentage of the customer base who have graduated from high school.
MonthlySales; = Bo + Bị Percent H SGrads; + e;
where
MonthlySales;
- is the total sales in month i, in $1000s
Percent H SGrads; - is percentage of all customers in store i customer base that have graduated from high school
A least-squares regression was ran in R producing the following output:
Scatter Plot: Sales to High School Graduates
4000 -
3500
3000 -
2500 -
2000
1500-
1000 -
500 -
0-
50
55
60
65
70
75
80
85
90
95
Percentage of Customer Base with a HS Diploma
Regression Analysis: MonthlySales versus PercentHSGrads
Predictor
Coef SD Coef TP
Constant
|-2970
1371
PercentHSGrads 59.66 17.67
S = 802.004 R-Sq =
%3D
Analysis of Variance
Source
DF
S
MS FP
Regression
7333350
Residual Error
23155564
Total
37
Using the partial R output, answer the questions below.
(a) Estimate the model. Use two-decimals your estimation of the slope term, no decimals in the estimation of the y-intercept.
MonthlySales; :
Percent H SGrads;
+
(b) What percentage of the variation in a store's monthly sales cannot be explained by its linear dependency on the percentage of the customer base that are high school graduates? Enter your answer as a percentage, using two decimal places.
%
Sales in $1000s
Transcribed Image Text:A national sporting good store wishes to use demographic information to predict its monthly sales, in $1000s. Thrity-eight, n = 38, stores of the chain are randomly chosen across the country. It is known that each store is approximately the same size and carries the same merchandise. The geographic area from which a store draws its customers is known as the customer base. One of the variables is the percentage of the customer base who have graduated from high school. MonthlySales; = Bo + Bị Percent H SGrads; + e; where MonthlySales; - is the total sales in month i, in $1000s Percent H SGrads; - is percentage of all customers in store i customer base that have graduated from high school A least-squares regression was ran in R producing the following output: Scatter Plot: Sales to High School Graduates 4000 - 3500 3000 - 2500 - 2000 1500- 1000 - 500 - 0- 50 55 60 65 70 75 80 85 90 95 Percentage of Customer Base with a HS Diploma Regression Analysis: MonthlySales versus PercentHSGrads Predictor Coef SD Coef TP Constant |-2970 1371 PercentHSGrads 59.66 17.67 S = 802.004 R-Sq = %3D Analysis of Variance Source DF S MS FP Regression 7333350 Residual Error 23155564 Total 37 Using the partial R output, answer the questions below. (a) Estimate the model. Use two-decimals your estimation of the slope term, no decimals in the estimation of the y-intercept. MonthlySales; : Percent H SGrads; + (b) What percentage of the variation in a store's monthly sales cannot be explained by its linear dependency on the percentage of the customer base that are high school graduates? Enter your answer as a percentage, using two decimal places. % Sales in $1000s
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 2 steps

Blurred answer
Knowledge Booster
Discrete Probability Distributions
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.
Similar questions
  • SEE MORE QUESTIONS
Recommended textbooks for you
Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
Algebra
ISBN:
9781133382119
Author:
Swokowski
Publisher:
Cengage