10th Edition

ISBN: 9780135835210

Author: Angel

Publisher: PEARSON

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Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as p…

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Textbook Question

Chapter 12.6, Problem 12E

In Exercises 11-18, assume that a sample of bivariate data yields the correlation coefficient, r, indicated. Use Table 12.9 on page 787 for the specified sample size and level of significance to determine whether a linear correlation exists.

12. r = 0.59 when n = 17 at α = 0.01

Table 12.9 Critical Values* for the Correlation Coefficient, r

n	α = 0.05	α = 0.01
4	0.950	0.990
5	0.878	0.959
6	0.811	0.917
7	0.754	0.875
8	0.707	0.834
9	0.666	0.798
10	0.632	0.765
11	0.602	0.735
12	0.576	0.708
13	0.553	0.684
14	0.532	0.661
15	0.514	0.641
16	0.497	0.623
17	0.482	0.606
18	0.468	0.590
19	0.456	0.575
20	0.444	0.561
22	0.423	0.537
27	0.381	0.487
32	0.349	0.449
37	0.325	0.418
42	0.304	0.393
47	0.288	0.372
52	0.273	0.354
62	0.250	0.325
72	0.232	0.302
82	0.217	0.283
92	0.205	0.267
102	0.195	0.254
The derivation of this table is beyond the scope of this text. It shows the critical values of the Pearson correlation coefficient.

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Chapter 12.6, Problem 11E

Chapter 12.6, Problem 13E

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Chapter 12 Solutions

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Solution Summary: The author explains that the correlation does not occur for the given data.

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