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MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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
Transcribed Image Text:The test statistic is
(Type integers or decimals.)
The P-value is.
(Round to three decimal places as needed.)
Draw a conclusion. Choose the correct answer below.
OA Reject the nul hypothesis. The coefficient is significantly different from
OB. Fal to reject the nul hypothesia. The coeficient in significanty diferent
from zero.
zero.
OC. Reject the null hypothesis. The coeficient is not significantly different from OD. Fal to rejoct the null hypothesis. The coeficient is not significantly differen
2ero
from zero
d) How might this model be improved?
OA Remove x and from the regression
OB. Remove x, and x from the regression
OC. Remove x from the regression equation.
equation
equation.
OE. Remove Xy, . and Xg from the regression
equation
OF Remove x, and K trom the regression
equation
OD. Remove trom the regression equation.

Transcribed Image Text:Variable
Coef
9.853
Std. Error
t-value
A study of 30 secretaries' yearly salaries (in thousands of dollars) was done. The researchers Intercept
want to predict salaries from several other variables. The variables considered to be potential X1
predictors of salary are months of service (x,). years of education (x2), score on a
standardized test (x3), words per minute (wpm) typing speed (X4). and ability to take dictation x,
in words per minute (Xs). A multiple regression model with all five variables was run.
0.373
26.416
0.112
0.013
8.615
0.066
0.029
2.276
0.093
0.031
3.000
0.008
0.306
0.026
0.063
0.022
2.864
Assume that the residual plots show no violations of the conditions for using a linear regression model.
a) What is the regression equation?
(Use integers or decimals for any numbers in the expression. Do not round.)
) From this model what is the predicted salary y (in thousands of dollars) of a secretary with 11 years (132 months) of experience, 12h grade education (12 yeurs of
education), a 46 on the standardized test, 63 wpm typing speed, and the ability to take 32 wpm dictation?
The predicted salary is houand dollars.
(Round to one decimal place a needed)
e) Test whether the coefficient of words per minute of typing speed () is significiney different from zero at a0.05.
Fist state the nu and altemative hypotheses. Choose the corect hypotheses below.
OAMAOO
OB HO
OC. H: 0
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