Grades A Statistics instructor created a linear regres-sion equation to predict students’ final exam scores from their midterm exam scores. The regression equation wasFin = 10 + 0.9 Mid.a) If Susan scored a 70 on the midterm, what did theinstructor predict for her score on the final?b) Susan got an 80 on the final. How big is her residual?c) If the standard deviation of the final was 12 points andthe standard deviation of the midterm was 10 points,what is the correlation between the two tests?d) How many points would someone need to score on themidterm to have a predicted final score of 100?e) Suppose someone scored 100 on the final. Explainwhy you can’t estimate this student’s midterm scorefrom the information given. f) One of the students in the class scored 100 on the midtermbut got overconfident, slacked off, and scored only 15 onthe final exam. What is the residual for this student? g) No other student in the class “achieved” such a dra-matic turnaround. If the instructor decides not to include this student’s scores when constructing a newregression model, will the R2 value of the regressionincrease, decrease, or remain the same? Explain.h) Will the slope of the new line increase or decrease?

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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.