Refer to the accompanying scatterplot. a. Examine the pattern of all 10 points and subjectively determine whether there appears to be a strong correlation between x and y. b. Find the value of the correlation coefficient r and determine whether there is a linear correlation. c. Remove the point with coordinates (2,10) and find the corelation coefficient r and determine whether there is a linear correlation. d. What do you conclude about the possible 10. effect from a single pair of values? Click here to view a table of critical values for the correlation coefficient. a. Do the data points appear to have a strong linear correlation? O Yes O No What is the value of the correlation coefficient for all 10 data points? r (Simplify your answer. Round to three decimal places as needed.) c. What is the correlation coefficient when the point (2,10) is excluded? ra(Round to three decimal places as needed.)
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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