Question 14In psychology, aptitude tests are designed to measure the ability to learn. Questions aredesigned to be age appropriate so as not to be biased toward age due to knowledge acquired. Inthis study, an aptitude test is given on the skills necessary to use apps on a smart phone. An aptitude test with amaximum score of 150 is given to measure the ability to learn how to use apps on a smartphone.The regression line for the predicted value of aptitude given age is as follows:Aptitude 110.2 - 1.10* AgeFind the expected aptitude test score for a person whose age is 17 years. Your answer should be rounded to the nearestwhole number.

Given,Aptitude=110.2-1.10×Age and A person age is 17 years .

Answered: In psychology, aptitude tests are…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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a) Write out the regression equation. b) Fill in the missing values *, **, *** and ****. c) Use the p-value approach to determine if ? is significant at the 5% significance level
Carefully read the description of the following two studies (A and B). For each study answer the following questions: Should a correlation analysis or multiple regression be used to analyze the results. Describe the basis for your answer – why did you select this test. Study A Dr. Banner want to determine whether his patients’ age is a factor in compliance with dialysis. He hypothesizes that older patients will be less compliant with dialysis. In other words, he believes the older the patient the more dialysis appointment they miss. Study B Dr. Banner’s intern does not agree. She believes there are other factors, along with age, that influence compliance such as race anxiety and mistrust of health care, side effects of treatment and issues related to culture. She wants to know who much each of these factors contribute to non-compliance.
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technologgy was also given a foot length of 10.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 10.8 cm, what is the single value that is the best predicted height for that person? H Click the icon to view the technology output. The single value that is the best predicted height is cm. Technology Output (Round to the nearest whole number as needed.) The regression equation is Height - 67.5 +5.15 Foot Length Predictor Coef SE Coef Constant 67.52 11.07 6.10 0.000 Foot Length 5.1508 0.4817 10.69 0.000 S-5.50271 R-Sq = 73.18 R-Sq (adj) = 72.44 Predicted Values for New Observations New Obs Fit SE Fit 95 CI 954 PI 123.149 1.605 (119.732, 126.566) (111.996, 134.302) Values of Predictors for New…
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18)The regression equation is intended to be the “best fitting” straight line for a set of data. Whatis the criterion for “best fitting”?
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The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 17.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 17.8 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. The single value that is the best predicted height is (Round to the nearest whole number as needed.) cm. Technology Output The regression equation is Height = 53.3+4.25 Foot Length Predictor Constant Coef SE Coef 53.28 11.44 Foot Length 4.2537 0.4699 S = 5.50739 R-Sq=72.3% R-Sq (adj) = 71.6% T 4.66 9.05 Predicted Values for New Observations New Obs 1 Fit SE Fit 128.996 1.733 (124.309, 133.683) 95% CI Foot New Obs Length 1 17.8 0.000 0.000 Values of Predictors for New…
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