An appliance store wants to conduct an experiment to determine the effect of advertising on sales revenue. The data table contains the advertising expenditure (in $100s) and sales revenue (in $100s) in the past 5 months. Below the data table, you will see the results of the regression analysis that was performed using Excel. You need to decide what the sales revenue will be with an advertising expenditure of $600, if possible. Would you be able to use the regression equation to predict the sales revenue? If so, what will be the sales revenue rounded to the nearest dollar? Support your answer. Advertising expenditure ($100s) Sales Revenue ($100s) 1 1 2 1 3 2 4 2 5 4 Coefficients Standard Error t Stat P-value Intercept -0.1 0.635085296 -0.157459164 0.88488398 X Variable 1 0.7 0.191485422 3.655630775 0.035352847
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.
An appliance store wants to conduct an experiment to determine the effect of advertising on sales revenue. The data table contains the advertising expenditure (in $100s) and sales revenue (in $100s) in the past 5 months. Below the data table, you will see the results of the
|
Advertising expenditure ($100s) |
Sales Revenue ($100s) |
|
1 |
1 |
|
2 |
1 |
|
3 |
2 |
|
4 |
2 |
|
5 |
4 |
|
|
Coefficients |
Standard Error |
t Stat |
P-value |
|
Intercept |
-0.1 |
0.635085296 |
-0.157459164 |
0.88488398 |
|
X Variable 1 |
0.7 |
0.191485422 |
3.655630775 |
0.035352847 |
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