Use the following set of points to test the null hypothesis H0:β1=0 versus H1:β1≠0. Use the P-value method with the α=0.05 level of significance. The slope of the regression line for this data is computed to be b1=0.96830, and the standard error of b1 is computed as sb=0.317710. Use the TI 84 calculator. x 19 22 8 29 17 16 15 18 y 16 30 5 22 12 12 16 14 Compute the test statistic. Always round the t-score values to three decimal places.
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.
Use the following set of points to test the null hypothesis H0:β1=0 versus H1:β1≠0. Use the P-value method with the α=0.05 level of significance. The slope of the regression line for this data is computed to be b1=0.96830, and the standard error of b1 is computed as sb=0.317710. Use the TI 84 calculator. x 19 22 8 29 17 16 15 18 y 16 30 5 22 12 12 16 14 Compute the test statistic. Always round the t-score values to three decimal places.
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