Suppose Ms. Carr is interested in the relationship between her students' 9th grade math final exam scores and the number of hours they spent studying during the year. She collects information for 15 ninth grade students and uses it to obtain the regression equation, where ?x is the number of hours spent studying during the year and ?̂ y^ is the predicted final exam score. ?̂= 1.48+75.64 The scatter plot displays her results. What is the predicted ?̂ y^‑value when a student spends 13 hours studying? Round your answer to one decimal place. y^= ? Select the correct interpretation. The above predicted value of ?̂ y^ is _____ a. the predicted score of 13 out of 15 students. b. the predicted final math test score if a student studies 13 hours during the year. c. the math final test score that 13 students beat. d. what any student will score on the final exam if they study at least 13 hours.
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.
Suppose Ms. Carr is interested in the relationship between her students' 9th grade math final exam scores and the number of hours they spent studying during the year. She collects information for 15 ninth grade students and uses it to obtain the regression equation, where ?x is the number of hours spent studying during the year and ?̂ y^ is the predicted final exam score.
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