(a) Find the equation of the least squares line would allow you to predict the percentage of alumni who would strongly agree that their education was worth the cost, using ranking as the independent variable. (Round your answers to four decimal places.) ý - 51.3 + 0.1633x (b) Predict the percentage of alumni who would strongly agree that their education was worth the cost for a university with a ranking of 50. (Round your answer to three decimal places.) 59.357 X % (c) Explain why it would not be a good idea to use the least squares line to predict the percentage of alumni who would strongly agree that their education was worth the cost for a university that had a ranking of 10. The prediction is reliable for within the range of the independent variable since it is very uncertain if the model is followed outside the range or not. Since, 10 is outside the range of x', the prediction might not be very reliable meaning it is not a good idea.

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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.