Weight Consumption 41 3 148 8 79 5 41 4 85 5 111 6 37 3 111 6 41 3 91 5 109 6 207 10 49 3 113 6 84 5 95 5 57 4 168 9
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.
| Weight | Consumption |
| 41 | 3 |
| 148 | 8 |
| 79 | 5 |
| 41 | 4 |
| 85 | 5 |
| 111 | 6 |
| 37 | 3 |
| 111 | 6 |
| 41 | 3 |
| 91 | 5 |
| 109 | 6 |
| 207 | 10 |
| 49 | 3 |
| 113 | 6 |
| 84 | 5 |
| 95 | 5 |
| 57 | 4 |
| 168 | 9 |
- The
correlation of Weight and Consumption is 0.987. - State the decision rule for 0.05 significance level: H0: ρ ≤ 0; H1: ρ > 0. Reject Ho if t> _____________
- Compute the value of the test statistic: ______________
- Develop a regression equation that predicts a dog's weight based on the cups of food per day, The regression equation is: Weight =__________+ _________Consumption.
- How much does each additional cup change the estimated weight of the dog? Each additional cup increases the estimated weight by _________ pounds.
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