The data below show the scores of the math exam and English exam of 20 students. Math Exam English Exam 70 74 45 50 26 30 84 70 23 30 88 80 75 85 99 100 100 100 100 40 20 30 46 65 42 45 74 80 56 60 12 20 65 65 80 80 66 75 87 95 The Math teacher thought of using the English exam marks as well to predict the math exam marks. The least squares regression line to predict the math exam scores was calculated: Math score = 3.45+0.933*English score 1-A student got 45 in his English exam. Knowing that the residual is equal to 4.565, what is his exact math exam score? 2-The typical deviation about (English score = 17.84 + 0.729*Math score) is 14.3, and the typical deviation about (Math score = 3.45+0.933*English score) is 16.22. which equation is more useful to predict the marks? Why. The English teacher believes that she can find out the student's estimated mark in English exam by knowing his Math exam mark. The following information are given: The least squares regression line to predicting the English exam scores is: English score = 17.84 + 0.729*Math score 3Predict the English mark exam for a student who got 9 on his math exam. If possible.
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.
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