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| Teaching Since: | Apr 2017 |
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bachelor in business administration
Polytechnic State University Sanluis
Jan-2006 - Nov-2010
CPA
Polytechnic State University
Jan-2012 - Nov-2016
Professor
Harvard Square Academy (HS2)
Mar-2012 - Present
13.20 ● The article “Root Dentine Transparency: Age De- termination of Human Teeth Using Computerized Densi- tometric Analysis” (American Journal of Physical Anthro- pology [1991]: 25–30) described a study in which the objective was to predict age (y) from percentage of a tooth’s root with transparent dentine. The accompanying data are for anterior teeth.
Mean Response Time
|
Study |
Control |
CHI |
|
|
7 |
880 |
1421 |
|
|
8 |
920 |
1329 |
|
|
9 |
1010 |
1481 |
|
|
10 |
1200 |
1815 |
|
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a. Fit a linear regression model that would allow you to predict the mean response time for those suffering a
|
me on the
Use the accompanying MINITAB output to decide whether the simple linear regression model is useful.
The regression equation is Age = 32.1 + 0.555percent
Predictor Coef Stdev t-ratio p Constant 32.08 13.32 2.41 0.043
percent 0.5549 0.3101 1.79 0.111
s = 14.30 R-sq = 28.6% R-sq(adj) = 19.7%
Analysis of Variance
Source DF SS MS F p
b. Do the sample data support the hypothesis that there is a useful linear relationship between the mean response time for individuals with no head injury and the mean re- sponse time for individuals with CHI? Test the appropriate hypotheses using a = .05.
c. It is also possible to test hypotheses about the y inter- cept in a linear regression model. For these data, the null hypothesis H0: a = 0 cannot be rejected at the .05 signifi- cance level, suggesting that a model with a y intercept of 0 might be an appropriate model. Fitting such a model re- sults in an estimated regression equation of
|
CHI = 1.48(Control)
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