2. Using the data (HERE), to develop a model that establishes a relationship between the sales (dependent variable) and demand of a product. i. Provide the regression equation and interpret the coefficients.
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.
2. Using the data (HERE), to develop a model that establishes a relationship between the sales (dependent variable) and demand of a product.
i. Provide the regression equation and interpret the coefficients.
ii. What does p value indicate about the hypothesis between the dependent-independent variables relationship?
iii. Find the lower and upper bounds for the estimates. iv. What the strength of the straight-line relationship based on the variance explained? v. Would it be appropriate to estimate the sales of the product when the demand is 30 and 5 respectively?
| A | B | C | |
|---|---|---|---|
| 1 | Demand | Sales | |
| 2 | 1 | 36 | 31 |
| 3 | 2 | 28 | 29 |
| 4 | 3 | 35 | 34 |
| 5 | 4 | 39 | 35 |
| 6 | 5 | 30 | 29 |
| 7 | 6 | 30 | 30 |
| 8 | 7 | 31 | 30 |
| 9 | 8 | 38 | 38 |
| 10 | 9 | 36 | 34 |
| 11 | 10 | 38 | 33 |
| 12 | 11 | 29 | 29 |
| 13 | 12 | 26 | 26 |
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