**Regression Analysis in Marketing**The marketing director at Reeves Wholesale Products is analyzing monthly sales using three independent variables as estimators: regional population, per capita income, and regional unemployment rate. The derived regression equation is:\[\hat{y} = 64,100 + 0.394x_1 + 9.6x_2 - 11,600x_3\]**Note**: In this equation:- $x_1$ represents the regional population.- $x_2$ represents per capita income.- $x_3$ represents the regional unemployment rate.**Questions:**a. **Choose the correct option for the full name of the equation:**- Multiple regression equation- Single linear equation- Single two linear equationb. **Interpret the number 64,100.**- $x_1$ intercept- $x_2$ intercept- $y$-interceptc. **Calculate the estimated monthly sales for a region with:** - Population: 796,000 - Per Capita Income: $6,940 - Unemployment Rate: 6.0%**Estimated monthly sales:***Provide your calculation here.*

It is given that, the number of independent variables is 3.

The director of marketing at Reeves Wholesale Products is studying monthly sales. Three independent variables were selected as estimators of sales: regional population, per capita income, and regional unemployment rate. The regression equation was computed to be (in dollars): ý = 64,100 + 0.394x1 + 9.6x2 – 11,600x3 Note: Here, the variables x1, X2 and x3 refer to regional population, per capita income, and regional unemployment rate respectively. a. Choose the right option for the full name of the eguation: O Multiple regression equation O Single linear equation O Single two linear equation b. Interpret the number 64,100. O x1 intercept O x2 intercept O y-intercept c. What are the estimated monthly sales for a particular region with a population of 796,000, per capita income of $6,940, and an unemployment rate of 6.0%? Estimated monthly sales

The director of marketing at Reeves Wholesale Products is studying monthly sales. Three independent variables were selected as estimators of sales: regional population, per capita income, and regional unemployment rate. The regression equation was computed to be (in dollars): ý = 64,100 + 0.394x1 + 9.6x2 – 11,600x3 Note: Here, the variables x1, X2 and x3 refer to regional population, per capita income, and regional unemployment rate respectively. a. Choose the right option for the full name of the eguation: O Multiple regression equation O Single linear equation O Single two linear equation b. Interpret the number 64,100. O x1 intercept O x2 intercept O y-intercept c. What are the estimated monthly sales for a particular region with a population of 796,000, per capita income of $6,940, and an unemployment rate of 6.0%? Estimated monthly sales

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

**Regression Analysis in Marketing**

The marketing director at Reeves Wholesale Products is analyzing monthly sales using three independent variables as estimators: regional population, per capita income, and regional unemployment rate. The derived regression equation is:

\[
\hat{y} = 64,100 + 0.394x_1 + 9.6x_2 - 11,600x_3
\]

**Note**: In this equation:
- $x_1$ represents the regional population.
- $x_2$ represents per capita income.
- $x_3$ represents the regional unemployment rate.

**Questions:**

a. **Choose the correct option for the full name of the equation:**

- Multiple regression equation
- Single linear equation
- Single two linear equation

b. **Interpret the number 64,100.**

- $x_1$ intercept
- $x_2$ intercept
- $y$-intercept

c. **Calculate the estimated monthly sales for a region with:**
- Population: 796,000
- Per Capita Income: $6,940
- Unemployment Rate: 6.0%

**Estimated monthly sales:**

*Provide your calculation here.*

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