The following data set was collected by Campus Life. They are investigating the possibility of a relationship between students' satisfaction with Penn State (on a scale of 1-10 where higher numbers indicate greater satisfaction) and how many activities they participate in on campus. In this table, each "ID" represents a single student. Imagine that someone in campus life wants to convert the "Satisfaction" scale of 1-10 to a scale of 1-100. Would the covariance get larger, smaller, or stay the same? ____________ Would the correlation coefficient r become larger, smaller, or stay the same? __________ What would be an example of an impossible correlation coefficient? In other words, give a value of r that would lead you to suspect that the researcher made a mistake. Imagine a study where all our data (x, y) falls perfectly on a flat and straight horizontal line. If we calculated the correlation coefficient r for this data, what would it be? What would that mean for our hypotheses?
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 following data set was collected by Campus Life. They are investigating the possibility of a relationship between students' satisfaction with Penn State (on a scale of 1-10 where higher numbers indicate greater satisfaction) and how many activities they participate in on campus. In this table, each "ID" represents a single student.
- Imagine that someone in campus life wants to convert the "Satisfaction" scale of 1-10 to a scale of 1-100.
- Would the
covariance get larger, smaller, or stay the same? ____________ - Would the
correlation coefficient r become larger, smaller, or stay the same? __________ - What would be an example of an impossible correlation coefficient? In other words, give a value of r that would lead you to suspect that the researcher made a mistake.
- Imagine a study where all our data (x, y) falls perfectly on a flat and straight horizontal line. If we calculated the correlation coefficient r for this data, what would it be? What would that mean for our hypotheses?
Step by step
Solved in 3 steps
