We are interested in exploring the relationship between the weight of a vehicle and its fuel efficiency (gasoline mileage). The data in the table show the weights, in pounds, and fuel efficiency, measured in miles per gallon, for a sample of 12 vehicles. Please help solve F and I subparts with explanations please Weight Fuel Efficiency 2690 25 2580 26 2630 29 2790 38 3000 25 3410 23 3640 21 3700 26 3880 21 3900 21 4060 19 4710 16 Part (f) Graph the best fit line on your scatterplot. (Upload your file below.) Part (i) The outlier is a hybrid car that runs on gasoline and electric technology, but all other vehicles in the sample have engines that use gasoline only. Explain why it would be appropriate to remove the outlier from the data in this situation. The outlier is creating a curved least squares regression line.The outlier lies directly on the line, so the error residual (y − ŷ) is zero. The outlier represents a different population of vehicles compared to the rest.The outlier does not lie directly on the line, but it is close. correlation coefficient coefficient of determination Find the new best fit line. (Round your answers to four decimal places.) ŷ = x +
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.
We are interested in exploring the relationship between the weight of a vehicle and its fuel efficiency (gasoline mileage). The data in the table show the weights, in pounds, and fuel efficiency, measured in miles per gallon, for a sample of 12 vehicles. Please help solve F and I subparts with explanations please
| Weight | Fuel Efficiency |
|---|---|
| 2690 | 25 |
| 2580 | 26 |
| 2630 | 29 |
| 2790 | 38 |
| 3000 | 25 |
| 3410 | 23 |
| 3640 | 21 |
| 3700 | 26 |
| 3880 | 21 |
| 3900 | 21 |
| 4060 | 19 |
| 4710 | 16 |
Part (f)
Part (i)
| coefficient of determination |
Find the new best fit line. (Round your answers to four decimal places.)
ŷ = x +
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