At the 5% level of significance, which variables are statistically significant?  If the price of cement per yard increases by 10, what will happen to the estimated quantity of cement demanded? What happens if it will increase by 20%?

Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 93E
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  1. At the 5% level of significance, which variables are statistically significant? 
  2. If the price of cement per yard increases by 10, what will happen to the estimated quantity of cement demanded? What happens if it will increase by 20%?
Given: The ATV Company produces a specialty cement used in the construction of roads. ATV is a price-setting firm and estimates the demand
for its cement using a demand function in the linear form:
Q = f( P, M, PR)
where Qc = demand for cement/month (in yards) Pc = the price of cement per yard, M = country's tax revenues per capita, and PR = the price
of asphalt per yard. The manager of ATV obtained the following results in her attempt to estimate the demand for cement in the succeeding
months. The results are presented below:
DEPENDENT VARIABLE
Qc
R-
SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS
64
0.8093
84.872
0.0001
PARAMETER
STANDARD ERROR
T-
P-VALUE
VARIABLE
ESTIMATE
RATIO
INTERCEPT
8.20
4.01
2.04
0.0461
PC
-3.54
1.64
-2.16
0.0357
M
0.64287
0.19
3.38
0.0014
PA
0.7854
0.38
2.07
0.0439
Transcribed Image Text:Given: The ATV Company produces a specialty cement used in the construction of roads. ATV is a price-setting firm and estimates the demand for its cement using a demand function in the linear form: Q = f( P, M, PR) where Qc = demand for cement/month (in yards) Pc = the price of cement per yard, M = country's tax revenues per capita, and PR = the price of asphalt per yard. The manager of ATV obtained the following results in her attempt to estimate the demand for cement in the succeeding months. The results are presented below: DEPENDENT VARIABLE Qc R- SQUARE F-RATIO P-VALUE ON F OBSERVATIONS 64 0.8093 84.872 0.0001 PARAMETER STANDARD ERROR T- P-VALUE VARIABLE ESTIMATE RATIO INTERCEPT 8.20 4.01 2.04 0.0461 PC -3.54 1.64 -2.16 0.0357 M 0.64287 0.19 3.38 0.0014 PA 0.7854 0.38 2.07 0.0439
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