The accompanying data have a correlation coefficient, rounded to three decimal places, of 0.261. Perform a hypothesis test with the data to determine if the population correlation coefficient p is not equal to zero using a = 0.05. E Click the icon to view the sample data. E Click the icon to view an excerpt from a table of Student's t-distribution values. What are the correct null and alternative hypotheses? Sample data DA. Ho: p>0 H:p=0 O B. Ho: p#0 6 7 7 5 1 H:p=0 y 7 10 5 6 OC. Ho: p=0 H,:p#0 O D. Ho: p=0 Print Done H:p>0 Vhat is the test statistic? = (Round three decimal places as needed.) What is the critical value? Select the correct choice below and fill in the answer box within your choice. Round to three decimal places as needed.) DA. t/2=* O B. t= What is the correct conclusion? OA. Reject Ho. There is not enough evidence from the sample to conclude that a relationship exists between the two variables. OB. Do not reject Ho. There is enough evidence from the sample to conclude that a relationship exists between the two variables. OC. Do not reject Ho. There is not enough evidence from the sample to conclude that a relationship exists between the two variables. O D. Reject Ho- There is enough evidence from the sample to conclude that a relationship exists between the two variables.
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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