Student Absent Average 80 66 85 Hours 14 2 3 3 2 86 73 97 2 18 3 17 88 76 62 10 94 92 11 12 88 6. 13 14 87 78 90 2 12 10 15 2 15
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.
1. A professor is interested in how attendance is related to grades her class. She goes through her records and determines each student’s final average and the number of days absent. The scores for her sample are given in the table below.
a. Construct a scatter plot of the relationship between final averages and the number of days absent.
b. Is there a significant relationship between final averages and the number of days absent? Calculate and interpret the
c. Compute r2 for the data. What percent of the variability in final averages is accounted for by the number days absent?
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