Below are four bivariate data sets and the scatter plot for each. (Note that each scatter plot is displayed on the same scale.) Each data set is made up of sample values drawn from a population. v u 1.0 7.5 11 10- 9+ 8- 1.0 6.7 11r 10- 2.0 | 8.6 2.0 | 9.0 3.0 6.9 3.0 | 4.0 4.0 5.4 4.0 | 9.0 6- 5- 6+ 5. 5.0 | 8.1 5.0 | 4.7 6.0 | 5.0 3. 6.0 1.7 3. 7.0 4.9 7.0 6.0 1- 1- 8.0 6.8 9.0 6.0 Figure 1 8.0 9.7 89 10 11 9.0 | 4.9 Figure 2 10.0 3.8 10.0 7.9 w t m 1.0 8.0 11 10- 2.0 | 7.2 1.0 3.3 10- 2.0 | 3.9 9- 9- 3.0 | 7.7 8+ x 8- 74 3.0 3.1 4.0 6.2 6- 4.0 4.5 5. 5.0 4.5 6.0 | 7.1 5.0 6.9 4. 6.0 4.5 3. 3. 2. 7.0 | 4.9 7.0 | 6.0 1. 1. 8.0 | 3.3 8.0 | 7.7 6 7 89 10 11 8 9 10 11 9.0 6.6 10.0 8.1 9.0 | 4.4 Figure 3 Figure 4 10.0 3.1 Answer the following questions about the relationships between pairs of variables and the values of r, the sample correlation coefficient. The same response may be the correct answer for more than one question. 1. For which data set is the sample correlation Choose one coefficient r closest to 1? 2. For which data set is the sample correlation coefficient r closest to 0? Choose one 3. For which data set is the sample correlation coefficient r equal to -1? Choose one 4. Which data set indicates the strongest negative linear relationship between its two variables? Choose one
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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