1st Edition

ISBN: 9781938168208

Author: Barbara Illowsky, Susan Dean

Publisher: OpenStax College

Concept explainers

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 13, Problem 46P

Use the following information to answer the next five exercises. Two coworkers commute from the same building. They are

interested in whether or not there is any variation in the time it takes them to drive to work. They each record their times for

20 commutes. The first worker’s times have a variance of 12.1. The second worker’s times have a variance of 16.9. The first

worker thinks that he is more consistent with his commute times. Test the claim at the 10% level. Assume that commute

times are normally distributed.

What is s1 in this problem?

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Expert Solution & Answer

Chapter 13 Solutions

Introductory Statistics

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