9) We have a sample of 6 observations on exam scores and hours of study and would like to estimate the following relationship using the least-squares method: Score Bo+ B, hours + e. We expect the score to increase with hours of study. Score Hours 80 90 85 65 50 80 12 14 11 10 8 11 Escore = 450, E hours = 66, E hours.score = 5085, Escore? = 34850, hours² = 746 %3D a. Estimate the unknown parameters using the method of OLS and find the least-squares prediction equation. b. Calculate SSE, R, standard error of the residuals (s), and standard error of slope coefficient (s Construct and interpret a 90% confidence interval for B. Predict the score of a student who studies 9 hours for the exam, and construct and interpret a 90% confidence interval using the predicted value (prediction interval). c.
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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