Linear Regression Line & Correlation Coefficient

Linear Regression Line & Correlation Coefficient (day 2) Key Concept Correlation Coefficient “r” “r” is a value tells whether the correlation is positive, negative, and how closely the equation models the data. r = 1 r = 0 r = -1 Strong No Strong Positive Correlation Negative r = 0.98 Positive r = -0.99 Strong Strong Positive Negative r = 0.50 r = -0.49 Weak Weak Positive Negative How do we find the equation of linear regression using graphing calculator? Stat - edit - 1 - enter all data on L1 and L2 - stat - calc - 4 - enter (5 times) 1. Walking Q Choose the scatter plot which could possibly have the given r-value: r = 0.50 A B C D E F r = -0.89 A B C D E F r = 0.92 A B C D E F r = -0.85 A B C D E F r = -1 A B C D E F r = -0.48 A B C D E F 2. Jogging Q Which value of r represents data with a strong negative linear correlation between two variables? -1.07 -0.89 -0.14 4) 0.92   3. Which value of r represents data with a strong positive linear correlation between two variables? 0.89 0.34 1.04   0.01 4. What could be the approximate value of the correlation coefficient for the accompanying scatter plot? -0.85 -0.16 0.21 0.90   5. The points in the scatter plot below represent the ages of automobiles and their values. Based on this scatter plot, it would be reasonable to conclude: Age and value have a coefficient of correlation that is less than zero. Age and value have a coefficient of correlation that is equal to zero. Age and value have a coefficient of correlation that is between zero and 0.5. Age and value have a coefficient of correlation that is greater than 0.5.   Джерела й пов’язаний контент