*** Use a calculator plz***** The accompanying data are x = advertising share an
ID: 2909178 • Letter: #
Question
*** Use a calculator plz*****
The accompanying data are x = advertising share and y = market share for a particular brand of cigarettes during 10 randomly selected years.
(a) Calculate the equation of the estimated regression line. (Round your answers to six decimal places.)
y =
Obtain the predicted market share when the advertising share is 0.09. (Round your answer to five decimal places.)
(b) Compute r2. (Round your answer to three decimal places.)
(c) Calculate a point estimate of ?. (Round your answer to four decimal places.)
On how many degrees of freedom is your estimate based?
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The accompanying summary quantities resulted from a study in which x was the number of photocopy machines serviced during a routine service call and y was the total service time (min).
(a) What proportion of observed variation in total service time can be explained by a linear probabilistic relationship between total service time and the number of machines serviced? (Give the answer to three decimal places.)
(b) Calculate the value of the estimated standard deviation se. (Give the answer to three decimal places.)
se =
What is the number of degrees of freedom associated with this estimate?
Explanation / Answer
#### By using R command:
> x=c(0.101,0.073,0.072,0.077,0.086,0.047,0.060,0.050,0.070,0.052)
> x
[1] 0.101 0.073 0.072 0.077 0.086 0.047 0.060 0.050 0.070 0.052
> y=c(0.137,0.126,0.123,0.086,0.079,0.076,0.065,0.059,0.051,0.039)
> y
[1] 0.137 0.126 0.123 0.086 0.079 0.076 0.065 0.059 0.051 0.039
> fit=lm(y~x)
> fit
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
-0.007004 1.324190
> summary(fit)
Call:
lm(formula = y ~ x)
Residuals:
Min 1Q Median 3Q Max
-0.034689 -0.019380 -0.003826 0.018141 0.036338
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.007004 0.036864 -0.190 0.8540
x 1.324190 0.521586 2.539 0.0348 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.02669 on 8 degrees of freedom
Multiple R-squared: 0.4462, Adjusted R-squared: 0.377
F-statistic: 6.445 on 1 and 8 DF, p-value: 0.03478
a) The estimated regression line is:
y=-0.007 + 1.3242*x
the predicted market share when the advertising share is 0.09 obtain by:
y=-0.007 + 1.3242*0.09
y=-0.007 + 0.11918
y=0.11218
b) R-squared= 0.4462
c) Point estimate of ?=0.02669
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