Year Freshman Applications Annual Tuition ($) 6010 3600 2 5560 3600 3 6100 4000 4 5330 4400 5 4980 4500 6 5870 5700 5120 6000 8 4750 6000 9 4615 7500 10 4100 8000
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.
The registrar at State University believes that decreases in the
number of freshman applications that have been experienced
are directly related to tuition increases. They have collected
the following enrollment and tuition data for the past decade:
a. Develop a linear regression model for these data and
forecast the number of applications for State University
if tuition increases to $10,000 per year and if tuition is
lowered to $7000 per year.
b. Determine the strength of the linear relationship between
freshman applications and tuition using
c. Describe the various planning decisions for State Univer-
sity that would be affected by the forecast for freshman
applications.
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