Statistics for Business and Economics (13th Edition)

13th Edition

ISBN: 9780134506593

Author: James T. McClave, P. George Benson, Terry Sincich

Publisher: PEARSON

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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 p…

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Textbook Question

Chapter 12.8, Problem 12.82LM

Consider a multiple regression model for a response y. with one quantitative independent variable x₁ and one qualitative variable at three levels,

a. Write a first-order model that relates the mean response E(y) to the quantitative independent variable,
b. Add the main effect terms for the qualitative independent variable to the model of part a. Specify the coding scheme you use.
c. Add terms to the model of part b to allow for interaction between the quantitative and qualitative independent variables.
d. Under what circumstances will the response lines of the model in part c be parallel?
e. Under what circumstances will the model in part c have only one response line?

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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Chapter 12.7, Problem 12.81ACA

Chapter 12.8, Problem 12.83LM

Chapter 12 Solutions

Statistics for Business and Economics (13th Edition)

Ch. 12.3 - Write a first-order model relating E(y) to a. two...Ch. 12.3 - Minitab was used to fit the model E(y) = (0 + 1x1...Ch. 12.3 - Suppose you fit the multiple regression model y =0...Ch. 12.3 - Suppose you fit the first-order multiple...Ch. 12.3 - Prob. 12.5LM Ch. 12.3 - Prob. 12.6LM Ch. 12.3 - Prob. 12.7LM Ch. 12.3 - If the analysis of variance F-test leads to the...Ch. 12.3 - Ambiance of 5-star hotels. Although invisible and...Ch. 12.3 - Forecasting movie revenues with Twitter. Refer to...

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