Question 2 A research study indicated a negative linear relationship between two variables: the number of hours spent exercising (exercise time) and the number of seconds it takes to run one lap around a track (running time). Computer output from the study is shown below. per week Variable Mean SE Mean StDev Running time 11 74.81 2.21 7.33 Predictor Coef SE Coef Constant 88.01 0.49 Exercise time -2.20 0.07 S = 0.76 R-Sq = 99.0% %3D Assuming that all conditions for inference are met, which of the following is an appropriate test statistic for testing the null hypothesis that the slope of the population regression line equals 0 ? 88.01 0.49 t = 74.81 7.33 74.81 2.21 t = 2.20 t 3= 0.07 2.20 0.07
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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