Time 0 5 4 4 14 16 7 5 2 Score 42 55 59 59 84 83 59 73 66 d. r2r2 = (Round to two decimal places) f. The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places) g. Use the model to predict the final exam score for a student who spends 10 hours per week studying. Final exam score = (Please round your answer to the nearest whole number.)
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.
What is the relationship between the amount of time statistics students study per week and their final exam scores? The results of the survey are shown below.
| Time | 0 | 5 | 4 | 4 | 14 | 16 | 7 | 5 | 2 |
|---|---|---|---|---|---|---|---|---|---|
| Score | 42 | 55 | 59 | 59 | 84 | 83 | 59 | 73 | 66 |
d. r2r2 = (Round to two decimal places)
f. The equation of the linear regression line is:
ˆyy^ = + xx (Please show your answers to two decimal places)
g. Use the model to predict the final exam score for a student who spends 10 hours per week studying.
Final exam score = (Please round your answer to the nearest whole number.)
| Time(x) | Score(y) | xy | x2 | y2 | |
| 0 | 42 | 0 | 0 | 1764 | |
| 5 | 55 | 275 | 25 | 3025 | |
| 4 | 59 | 236 | 16 | 3481 | |
| 4 | 59 | 236 | 16 | 3481 | |
| 14 | 84 | 1176 | 196 | 7056 | |
| 16 | 83 | 1328 | 256 | 6889 | |
| 7 | 59 | 413 | 49 | 3481 | |
| 5 | 73 | 365 | 25 | 5329 | |
| 2 | 66 | 132 | 4 | 4356 | |
| 57 | 580 | 4161 | 587 | 38862 | Total |
n = 9
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