Use data on tab “printers data.” --Run a regression with “Cartridges” as the dependent variable and “Printers” as the independent variable. Place the regression output at cell “I2.” --Create a scatter plot with “printers” as the x-axis and “cartridges” as the y-axis. Place the plot in cell “I22.” --In cell C2 type “Forecast.” In column C, create a cartridge forecast for each printer quantity --In cell D2 type “%error”. In column D calculate the percentage error for each forecasted quantity from each actual cartridge value. --In cell E2 type “ABS[A-F]” and in that column calculate the absolute value of each actual (column B) versus each forecast (column C). --In cell F2 type “Sum ABS[A-F]” --In cell F3 sum the values of column E --In Cell G2 type “MAD” --In cell G3 calculate the Mean Absolute deviation Printers Cartridges 19 57 15 60 15 60 15 75 16 80 14 42 10 40 12 36 20 80 19 76 17 85 19 76 18 72 12 48 17 85 13 65 17 68 11 55 19 76 14 42
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.
Use data on tab “printers data.”
--Run a regression with “Cartridges” as the dependent variable and “Printers” as the independent variable. Place the regression output at cell “I2.”
--Create a
Place the plot in cell “I22.”
--In cell C2 type “Forecast.” In column C, create a cartridge forecast for each printer quantity
--In cell D2 type “%error”. In column D calculate the percentage error for each forecasted quantity from each actual cartridge value.
--In cell E2 type “ABS[A-F]” and in that column calculate the absolute value of each actual (column B) versus each forecast (column C).
--In cell F2 type “Sum ABS[A-F]”
--In cell F3 sum the values of column E
--In Cell G2 type “MAD”
--In cell G3 calculate the Mean Absolute deviation
| Printers | Cartridges |
| 19 | 57 |
| 15 | 60 |
| 15 | 60 |
| 15 | 75 |
| 16 | 80 |
| 14 | 42 |
| 10 | 40 |
| 12 | 36 |
| 20 | 80 |
| 19 | 76 |
| 17 | 85 |
| 19 | 76 |
| 18 | 72 |
| 12 | 48 |
| 17 | 85 |
| 13 | 65 |
| 17 | 68 |
| 11 | 55 |
| 19 | 76 |
| 14 | 42 |
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