with) how long a marriage will last from how long the divorcing couple's courtship was prior to marrying. He selects a random sample of 10 of the hundreds of couples for whom he has records and performs a regression analysis. What follows below is the numerical and graphical output from computer software. Question: Do the data provide convincing evidence that there is a linear relationship between length of courtship and length of marriage? Perform the appropriate sig

Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015
1st Edition
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:HOUGHTON MIFFLIN HARCOURT
Chapter4: Writing Linear Equations
Section: Chapter Questions
Problem 14CR
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2.) A psychologist counsels people who are getting divorced. He suspects that it is possible to predict (among the couples he works with) how long a marriage will last from how long the divorcing couple's courtship was prior to marrying. He selects a random sample of 10 of the hundreds of couples for whom he has records and performs a regression analysis. What follows below is the numerical and graphical output from computer software. Question: Do the data provide convincing evidence that there is a linear relationship between length of courtship and length of marriage? Perform the appropriate significance test to support your conclusion
Residual plot
5.0
25.
布
0.0-
25
Cortip
Scatterplot
Marriage Len vs. Courtship Len
175
Len of Courtship in Years
Len of Marriage in Years
erps
Transcribed Image Text:Residual plot 5.0 25. 布 0.0- 25 Cortip Scatterplot Marriage Len vs. Courtship Len 175 Len of Courtship in Years Len of Marriage in Years erps
Namal Probability Rat of Residuals
2-
1.
0.
-1.
-2.
-5.0
-2.5
0.0
2.5
5,0
Residuals
Predictor
Constant
courtship 2.4559
Coef
5.710
SE Coef
1.880
0.6669
3.04 0.016
3.68 0.006
S 2.7498
R-Sq
= 62.9% R-Sq(adj)
58.3%
z-Score
Transcribed Image Text:Namal Probability Rat of Residuals 2- 1. 0. -1. -2. -5.0 -2.5 0.0 2.5 5,0 Residuals Predictor Constant courtship 2.4559 Coef 5.710 SE Coef 1.880 0.6669 3.04 0.016 3.68 0.006 S 2.7498 R-Sq = 62.9% R-Sq(adj) 58.3% z-Score
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