A cafe company wants to determine how the money they spend on Google ads impacts their monthly revenue. Over 6 consecutive months, they vary the amount they spend on their Ads (in $) and record the associated revenue (in $) for each month. The data is shown below: l Revenue 50 427 75 472 100 467 125 529 150 518 175 543 A) Using a 0.05 level of significance, does this regression equation appear to have any value for predicting revenue based on Ads? a. Yes because there is a significant linear relationship between the two quantities. b. No because there is not a significant linear relationship between the two quantities. c. Yes because there is not a significant linear relationship between the two quantities. d. No because there is a significant linear relationship between the two quantities.
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.
A cafe company wants to determine how the money they spend on Google ads impacts their monthly revenue. Over 6 consecutive months, they vary the amount they spend on their Ads (in $) and record the associated revenue (in $) for each month. The data is shown below:
| l | Revenue |
| 50 | 427 |
| 75 | 472 |
| 100 | 467 |
| 125 | 529 |
| 150 | 518 |
| 175 | 543 |
A) Using a 0.05 level of significance, does this regression equation appear to have any value for predicting revenue based on Ads?
a. Yes because there is a significant linear relationship between the two quantities.
b. No because there is not a significant linear relationship between the two quantities.
c. Yes because there is not a significant linear relationship between the two quantities.
d. No because there is a significant linear relationship between the two quantities.
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