# Data sets shared by StatCrunch members
Showing 1 to 12 of 12 data sets matching coefficient
 Data Set/Description Owner Last edited Size Views anscombe.txt Anscombe's 4 data sets for regression. They are very different, yet have the same correlation and regression coefficients. butler May 31, 2011 360B 779 10 highest peaks in Rockies and Appalachians Is there more variation in the heights of the highest peaks in the Rockies (newer) or in the Appalachians (older)? Use coefficient of variation to find out! anderson_instructor Aug 18, 2018 174B 154 Validity Continuous Data---Class Example Validity data for class example. Compute correlation, coefficient of determination, standard error of prediction, regression equation, predicted value for X = 70, and 95% confidence interval for X = 70 mld May 21, 2014 120B 218 Economic Freedom Index (2018) This set contains data from: -The Heritage Foundation's "Economic Freedom Index", measuring total economic freedom, property rights, government integrity, tax burden, business freedom, and investment freedom. -The World Bank Group's GDP per capita, Net National Income per capita, and GDP percentage growth -The UN's Human Development Index, total and inequality adjusted -The Gini coefficient measures for several countries from 2013 to 2017 -Reporters Without Borders' "Press Freedom Index" williamharrison Sep 10, 2018 17KB 135 Inspecting Anscombe's quartet_Scaringelli_A 1) X1 and y1 correlation coefficient: 0.81642052 X2 and y2 correlation coefficient: 0.81623651 X3 and y3 correlation coefficient: 0.81628674 X4 and y4 correlation coefficient: 0.81652144 This means that the strength of each relation is about the same for all four, although x4 & y4 have the highest correlation coefficient and x2 & y2 have the lowest correlation coefficient. 2) The four calculations lead you to conclude that the strength of the linear association between the two quantitative variables of each x and y. With all of the four correlations around 0.816 we can conclude that there is a moderately strong linear association between each x and y variable and this holds throughout all four sets of variables. 3) See posted scatterplots 4) X1 y1 The direction of this association is positive. The form is linear but the strength of the scatter is weak. X2 y2 The direction of this association starts out positive and then switches to negative around an x value of 11. This is because the form of the association is curved; however the strength of the association is strong. X3 y3 The direction of this association is positive. The form is linear and the strength of the association is strong except for one outlier that stands away from the overall pattern of the scatterplot at x=13 and y=12.74. X4 y4 The direction of this association is positive. The form is linear and the strength of the association is a very strong straight vertical line at x=8 except for one outlier that stands away from the overall pattern of the scatterplot at x=19 and y=12.5. ajs5633 Jul 8, 2014 391B 59 McGuire and Sosa Correlation of Coefficient between the home runs of Sosa and McGuire. emprogboy Dec 9, 2013 4KB 32 Anscombe's Data Anscombe's data that illustrates how the correlation coefficient can be similar for very different non-linear associations. sirelfman Feb 29, 2012 348B 27 Turbine Coefficients statmanone Nov 13, 2008 154B 209 Investigating the Coefficient of Determination cassity Sep 25, 2018 279B 74 Critical Values for Correlation Coefficient chenle Oct 9, 2015 307B 65 Problem 4.50 Prediciton Coefficients ds-14483%sc Aug 11, 2008 187B 30 Investigating the Coefficient of Determination activity cthomas8247 Feb 12, 2018 282B 11

Always Learning