The correlation between x and y in each of the following four visualizations is 0.82, yet you can clearly see differences in the relationship betwee Anscombe's Data Sets B 10- 10- 8- 8- 6- 6- 13- 11- 11- 9- 7- 5- 5- 7.5 10.0 12.5 15.0 17.5 Which does this example show? O a. that a large Pearson correlation value means a strong linear relationship between the variables O b. that simple descriptive statistics suffice for understanding the relationship between variables O c. the effect of outliers on statistical properties of datasets O d. the importance of graphing data before analyzing it -12
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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