3.5- 2.5- 2+ 2.5 3 High School GPA 3.5 University GPA 2.
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. The scatterplot below contains high school and university grades for 105 computer
science majors at Big Ten Universities. We now consider how we could predict a
student’s university GPA if we knew his or her high school GPA.
a. What do you think the
its sign and magnitude.
b. The best fitting line for this data is as follows:
University GPA = 1.097 + 0.675×High School GPA. A student with a high school GPA
of 3 would be predicted to have what university GPA?
c. The r2 for this regression line is 0.61. Interpret this value given the context of the data.
d. Would you feel confident using this regression line to make predictions for all students
at Iowa? Why or why not?
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