Consider two data sets. Set A: n = 5; x = 7 Set B: n = 50; x = 7 (a) Suppose the number 32 is included as an additional data value in Set A. Compute x for the new data set. Hint: Sx = nx. To compute x for the new data set, add 32 to x of the original data set and divide by 6. (Round your answer to two decimal places.) (b) Suppose the number 32 is included as an additional data value in Set B. Compute x for the new data set. (Round your answer to two decimal places.) (c) Why does the addition of the number 32 to each data set change the mean for Set A more than it does for Set B? O Set B has a larger number of data values than set A, so to find the mean of B we divide the sum of the values by a smaller value than for A. O Set B has a larger number of data values than set A, so to find the mean of B we divide the sum of the values by a larger value than for A. O Set B has a smaller number of data values than set A, so to find the mean of B we divide the sum of the values by a larger value than for A. O Set B has a smaller number of data values than set A, so to find the mean of B we divide the sum of the values by a smaller value than for A.
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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