This article considers the relationship between two variables in two ways: (1) by using regression analysis and (2) by computing the correlation coefficient. By using the regression model, we can evaluate the magnitude of change in one variable due to a certain change in another variable. For example, an economist can estimate the amount of change in food expenditure due to a certain change in the income of a household by using the regression model. A sociologist may want to estimate the increase in the crime rate due to a particular increase in the unemployment rate. Besides answering these questions, a regression model also helps predict the value of one variable for a given value of another variable. For example, by using the regression line, we can predict the (approximate) food expenditure of a household with a given income. The correlation coefficient, on the other hand, simply tells us how strongly two variables are related. It does not provide any information about the size of the change in one variable as a result of a certain change in the other variable.

Let us return to the example of an economist investigating the relationship between food expenditure and income. What factors or variables does a household consider when deciding how much money it should spend on food every week or every month? Certainly, income of the household is one factor. However, many other variables also affect food expenditure. For instance, the assets owned by the household, the size of the household, the preferences and tastes of household members, and any special dietary needs of household members are some of the variables that influence a household’s decision about food expenditure. These variables are called independent or explanatory variables because they all vary independently, and they explain the variation in food expenditures among different households. In other words, these variables explain why different households spend different amounts of money on food....

...Chapter 4 Simpleregressionmodel Practice problems
Use Chapter 4 Powerpoint question 4.1 to answer the following questions:
1. Report the Eveiw output for regressionmodel .
Please write down your fitted regressionmodel.
2. Are the sign for consistent with your expectation, explain?
3. Hypothesize the sign of the coefficient and test your hypothesis at 5% significance...

...LinearRegression deals with the numerical measures to express the relationship between two variables. Relationships between variables can either be strong or weak or even direct or inverse. A few examples may be the amount McDonald’s spends on advertising per month and the amount of total sales in a month. Additionally the amount of study time one puts toward this statistics in comparison to the grades they receive may be analyzed using the...

...au/webapps/portal/frameset.jsp?tab=courses&url=/bin/common/course.pl?course_id=_111213_1&frame=top
• You assignment must be in a Word doc format – no pdfs!
• When answering questions, wherever required, you should cut and paste the Excel output (eg, plots, regression output etc) to show your working on your assignment.
• You are required to keep a hard copy and an electronic copy of your submitted assignment to re-submit, in case the original submission is lost for...

...
SimpleLinearRegressionModel
1. The following data represent the number of flash drives sold per day at a local computer shop and their prices.
| Price (x) | Units Sold (y) |
| $34 | 3 |
| 36 | 4 |
| 32 | 6 |
| 35 | 5 |
| 30 | 9 |
| 38 | 2 |
| 40 | 1 |
| a. Develop as scatter diagram for these data. b. What does the scatter diagram indicate about the relationship between the two variables? c....

...study retailers behavior towards Aircel in selected region. The data is collected directly by visiting outlets through structured interview scheduled. The statistical tools used to analyze the data are: Co-relation analysis, SimpleLinearRegression and Multiple LinearRegression. The software used to analyze the data is Windostat version 8.6, developed by Indostat services, is an advanced level statistical software for...

...SIMPLE VERSUS MULTIPLE REGRESSION
The difference between simple and multiple regression is similar to the difference between one way and factorial ANOVA. Like one-way ANOVA, simpleregression analysis involves a single independent, or predictor variable and a single dependent, or outcome variable. This is the same number of variables used in a simple correlation analysis. The difference...

...Tiffany Camp
ECO-250
Volker Grzimek
Regression Analysis of Work Hours in Relation to GPA
This research investigated the affects of working extra hours in a labor position on students’ GPAs each semester at Berea College. It was my belief that students who worked more hours were more likely to have lower GPAs due to their studying abilities and opportunities being compromised as a result of working too long (a negative correlation or trend between GPAs and hours...

...between the variables is 0, it means that the two variables aren’t related. – TRUE
2. In a simpleregression analysis the error terms are assumed to be independent and normally distributed with zero mean and constant variance. – TRUE
3. The difference between the actual Y-value and the predicted Y-value found using a regression equation is called the residual (ε) – TRUE
4. In a multiple regression analysis with N...

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