The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Com No. of absences, x 0 1 2 3 4 5 6 7 8 9 0 Final grade, y 88.2 85.3 82.3 79.8 76.8 72.4 62.9 67.2 64.3 61.3 (a) Find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as the re y = - 3.150 x + ( 88.224 (Round to three decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. (Round to three decimal places as needed.) O A. For a final score of zero, the number of days absent is predicted to be days. O B. For every unit change in the final grade, the number of days absent falls by days, on averag O C. For zero days absent, the final score is predicted to be O D. For every day absent, the final grade falls by on average. O E. It is not appropriate to interpret the slope.
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.
![Interpret the y-intercept. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.
(Round to three decimal places as needed.)
O A. For zero days absent, the final score is predicted to be
O B. For every day absent, the final grade falls by , on average.
O C. For every unit change in the final grade, the number of days absent falls by
days, on average.
O D. For a final score of zero, the number of days absent is predicted to be
days.
O E. It is not appropriate to interpret the y-intercept.
(c) Predict the final grade for a student who misses five class periods and compute the residual. Is the observed final grade above or below average for this number of absences?
The predicted final grade is. This observation has a residual of
which indicates that the final grade is
average.
(Round to one decimal place as needed.)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc97b645b-272d-44ae-847c-e33fe9b8ea4b%2F28f41eac-00cc-4cd0-bca5-b7ae1deb2e33%2Fifaf86_processed.png&w=3840&q=75)
![The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Comp
0 1 2
7
No. of absences, x
Final grade, y
3 4 5
6
8
88.2 85.3 82.3 79.8 76.8 72.4 62.9 67.2 64.3 61.3
(a) Find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as the res
y = - 3.150 x+ (88.224)
(Round to three decimal places as needed.)
(b) Interpret the slope and y-intercept, if appropriate.
Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.
(Round to three decimal places as needed.)
A. For a final score of zero, the number of days absent is predicted to be
days.
O B. For every unit change in the final grade, the number of days absent falls by
days, on average
O C. For zero days absent, the final score is predicted to be
D. For every day absent, the final grade falls by
on average.
O E. It is not appropriate to interpret the slope.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc97b645b-272d-44ae-847c-e33fe9b8ea4b%2F28f41eac-00cc-4cd0-bca5-b7ae1deb2e33%2F7yt5v9v_processed.jpeg&w=3840&q=75)
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