The accompanying data represent the number of days absent, x, and the final exam score, y, for a sample of college students in a general education course at a state university. Complete parts (a) through (e) below. E Click the icon to view the absence count and final exam score data. Click the icon to view a table of critical values for the correlation coefficient. (a) Find the least-squares regression line treating number of absences as the explanatory variable and the final exam score as the response variable. Round to three decimal places as needed.) Absences and Final Exam Scores No. of absences, x 0 1 2 3 4 5 6. 7 8 Final exam score, y 89.4 85.6 84.2 80.6 77.4 74.3 63.9 71.4 66.1 66.6
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.
11/15
find the least squares regression line treating number of absences as the explanatory variable and the final exam score as the response variable. Round to three decimal places as needed.
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
