Data on Advertising Expenditures and Revenue (each measured in thousands of dollars) was collected and Excel was used to run a Regression Analysis on the data. The Excel-generated output is provided below: ANOVA df SS MS F Signficance F Regression 1 571.4127907 571.4127907 38.03889695 0.003508906 Residual 4 60.0872093 15.02180233 Total 5 631.5 Coefficients Standard Error t Stat P-value Intercept 32.76744186 2.865238148 11.43620187 0.000333583 Expend 1.578488372 0.255933673
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.
Data on Advertising Expenditures and Revenue (each measured in thousands of dollars) was collected and Excel was used to run a
ANOVA
| df | SS | MS | F | Signficance F | |
| Regression | 1 | 571.4127907 | 571.4127907 | 38.03889695 | 0.003508906 |
| Residual | 4 | 60.0872093 | 15.02180233 | ||
| Total | 5 | 631.5 |
| Coefficients | Standard Error | t Stat | P-value | |
| Intercept | 32.76744186 | 2.865238148 | 11.43620187 | 0.000333583 |
| Expend | 1.578488372 | 0.255933673 | 6.167568155 | 0.003508906 |
For a month where the advertising expenditure amount was 7, what is the predicted (monthly) Revenue? Round off your answer to the closest penny. To answer this question you'll need to construct the estimated regression equation from the Excel regression output.
The predicted (monthly) Revenue, given that advertising Expenditures is 7, rounded off to the closest penny,
is:
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