Because elderly people may have difficulty standing to have their height measured, a study looked at the relationship between overall height and height to the knee. Here are data (in centimeters) for five elderly men: Knee Height x 56.8 46.7 40.6 43.6 52.9 191.1 154.4 144.4|162.5 172.7 Height y For this data, it is known that Ex = 240.6, E y = 825.1, Ex? = 11754.86, Ey = 137441.47 and Exy = 40148.43. What is the equation of the least-squares regression line for predicting height from knee height? ANSWER: ŷ = Compute the linear correlation coefficient of these data, correct to four decimal places. ANSWER: Predict the mean height of an elderly man with a knee height of 58 centimeters. ANSWER: Assume known that s, = 7.47858. Find a 99% confidence interval for the mean height of an elderly man with a knee height of 58 centimeters.
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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