Use the given data set to complete parts (a) through (c) below. (Use a = 0.05.) 12 8. 6.77 11 7.81 10 13 9. 14 7.46 12.73 7.11 8.85 6.08 5.39 8.16 6.41 5.73 y Click here to view a table of critical values for the correlation coefficient. b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r= (Round to three decimal places as needed.) Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below. O A. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables. O B. There is insufficient evidence to support the claim of a linear correlation between the two variables. O C. There is sufficient evidence to support the claim of a linear correlation between the two variables. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables.

Use the given data set to complete parts (a) through (c) below. (Use a = 0.05.) 12 8. 6.77 11 7.81 10 13 9. 14 7.46 12.73 7.11 8.85 6.08 5.39 8.16 6.41 5.73 y Click here to view a table of critical values for the correlation coefficient. b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r= (Round to three decimal places as needed.) Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below. O A. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables. O B. There is insufficient evidence to support the claim of a linear correlation between the two variables. O C. There is sufficient evidence to support the claim of a linear correlation between the two variables. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables.

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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Concept explainers

Correlation

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 predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

100%

Use table of critical values of correlation coefficient.

Use the given data set to complete parts (a) through (c) below. (Use a = 0.05.)
10
8
13
9
11
14
6
4
12
7
7.46
6.77
12.73
7.11
7.81
8.85
6.08
5.39
8.16
6.41
5.73
y
Click here to view a table of critical values for the correlation coefficient.
b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables.
The linear correlation coefficient is r=.
(Round to three decimal places as needed.)
Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between
the two variables. Choose the correct answer below.
O A. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables.
O B. There is insufficient evidence to support the claim of a linear correlation between the two variables,
O C. There is sufficient evidence to support the claim of a linear correlation between the two variables.
O D. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables.

Use the given data set to complete parts (a) through (c) below. (Use a = 0.05.)
10
8
13
9.
11
14
4
12
y
7.46
6.77
12.73
7.11
7.81
8.85
6.08
5.39
8.16
6.41
5.73
Click here to view a table of critical values for the correlation coefficient.
a. Construct a scatterplot. Choose the correct graph below.
OA.
OB.
OC.
OD.
Ay
16-
Ay
16-
Ay
16-
Ay
16-
12-
12-
12-
12-
8-
8-
8-
8-
.....
. ...
4-
4-
4-
4-
0-
0-
0-
0-
16
4 8 12 16
4
12
12
16
b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables.

Definition Definition Statistical measure used to assess the strength and direction of relationships between two variables. Correlation coefficients range between -1 and 1. A coefficient value of 0 indicates that there is no relationship between the variables, whereas a -1 or 1 indicates that there is a perfect negative or positive correlation.

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