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) Develop a regression equation for predicting monthly revenue based on the amount spent with Ads. What is the y-intercept? B) What is the sample correlation between these two variables? C) What is the slope of your regression equation? Give your answer to two decimal places.
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) Develop a regression equation for predicting monthly revenue based on the amount spent with Ads. What is the y-intercept?
B) What is the sample
C) What is the slope of your regression equation? Give your answer to two decimal places.
D) Using a 0.05 level of significance, does this regression equation appear to have any value for predicting revenue based on Ads?
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