Basic Business Statistics, Student Value Edition (13th Edition)
13th Edition
ISBN: 9780321946393
Author: Mark L. Berenson, David M. Levine, Kathryn A. Szabat
Publisher: PEARSON
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Question
Chapter 1, Problem 43PS
a.
To determine
Mention an example of categorical variable included in the survey.
b.
To determine
Mention an example of numerical variable included in the survey.
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Show work on paper so I can better understand please! Don't type the work I will not understand it
(a) Interpret the estimated coefficients stating if they are statistically significant in explaining
price of houses. Also interpret R squared.
SUMMARY OUTPUT price and pool
Regression Statistics
Multiple R 0.294065
R Square
0.086474
Adjusted F 0.077605
Standard E 0.463742
Observatio
105
ANOVA
df
SS
MS
F
ignificance F
Regression
1 2.09679 2.09679 9.749948 0.002328
Residual
103 22.15083 0.215057
Total
104 24.24762
Intercept
Coefficientstandard Err t Stat P-value Lower 95% Upper 95%.ower 95.0%/pper 95.0%
1.028381 0.218189
X Variable -0.00301 0.000965
4.71326 7.66E-06 0.595655 1.461107 0.595655 1.461107
-3.12249 0.002328 -0.00493 -0.0011 -0.00493 -0.0011
SUMMARY OUTPUT price and bedroom
Regression Statistics
0.467377
Multiple R
R Square 0.218441
Adjusted F 0.210853
Standard E 1.334785
Observatio
105
ANOVA
df
SS
Regression
Residual
Total
103
104
MS
F
1 51.29003 51.29003 28.78794
183.51 1.78165
234.8
ignificance F
5E-07
Coefficientstandard Err t Stat
P-value Lower 95% Upper 95%.ower…
(Q1) I have attached the dataset for Good Year Real estate home sales, with the selling prices in
the first column.
(a) Consider the variables "prices", bedrooms, "pool", size", "garage" and "baths".
(b) Find out the correlation coefficients among all these variables. Do you see some high
correlation between any two variables?
correlation coefficients
0.467377
of prices and bedrooms
correlation coefficients
-0.20059
of pool and size
correlation coefficients
0.221289
of garage and baths
(c) Identify which variables are the dummy variables in your dataset.
Pool and Garage
(d) Next, you do multiple regression analysis. Using Excel, present a regression output
between price as the dependent variable and all the other variables selected in (a) as
independent variables. Include dummy variables from the dataset provided.
2
Price and bedroom
porce and pool
3 price
price and
sze
24) price
and
garage
price
and baths
Chapter 1 Solutions
Basic Business Statistics, Student Value Edition (13th Edition)
Ch. 1 - Four different beverages are sold at a fast-food...Ch. 1 - U. S. businesses are listed by size small medium,...Ch. 1 - The time it takes to download a video from the...Ch. 1 - For each of the following variables, determine...Ch. 1 - The following information is collected from...Ch. 1 - For each of the following variables, determine...Ch. 1 - For each of the following variables, determine...Ch. 1 - Suppose the following information is collected...Ch. 1 - One of the variables most often included in...Ch. 1 - If two students score a 90 on the same...
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- (c) Interpret the estimated coefficients stating if they are statistically significant in explaining price of houses. Also interpret R squared. SUMMARY OUTPUT price and baths Regression Statistics Multiple R 0.382173 R Square 0.146056 Adjusted F 0.137765 Standard E 0.364917 Observatio ANOVA df Regression Residual Total 105 SS MS F ignificance F 1 2.345936 2.345936 17.61679 5.75E-05 103 13.71597 0.133165 104 16.0619 Coefficientstandard Err t Stat P-value Lower 95% Upper 95%.ower 95.0%/pper 95.0% 1.375992 0.171692 8.014289 1.8E-12 1.03548 1.716503 1.03548 1.716503 X Variable 0.003188 0.00076 4.197236 5.75E-05 0.001682 0.004695 0.001682 0.004695 Interceptarrow_forwardNot use ai pleasearrow_forwardPlease show work on paper only please Thank youarrow_forward
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