5 Nom X M Inbo: X 31 Goor X & Logir X One- X in Notif X Rour X Hom Unit X Powe X Desc X r/index.html?launchld=2d73585e-107c-438c-9742-1497503f9af5#/question/9 Question 10 of 15 -12 5 View Policies Current Attempt in Progress NBA Players: Correlation Matrix The dataset NBAPlayers2019 contains information on many variables for players in the NBA (National Basketball Association) during the 2018-19 season. The dataset includes information for all players who averaged more than 24 minutes per game (7 = 194) and 25 variables, including Age, Points (number of points for the season per game), FTPct (free throw shooting percentage). Rebounds (number of rebounds for the season), and Steals (number of steals for the season). A correlation matrix for these five variables is shown. A correlation matrix allows us to see lots of correlations at once, between many pairs of variables. For any pair of variables (indicated by the row and the column), we are given two values: the correlation as the top number and the p- value for a two-tail test of the correlation right beneath it. Correlations: Age, Points, FTPct, Rebounds. Steals Age Points FTPct Rebounds Points -0.072 0.319 FTPct 0.165 0.310 0.022 0.000-12 Question 10 of 15 (a) Which two variables are most strongly positively correlated? O FTPct Points Rebounds Steals Age e Textbook and Media What is the correlation and p-value between these variables? The correlation is i ! The p-value is i eTextbook and Media (b) Which two variables are most strongly negatively correlated? 3 HotDogs2019.csv(b) Which two variables are most strongly negatively correlated? O Steals O Age O Points O FTPct O Rebounds e Textbook and Media What is the correlation and p-value between these variables? The correlation is i The p-value is i eTextbook and Media (c) At a 5% significance level, for how many pairs of variables is there NOT convincing evidence of a linear association? i pair(s) HotDogs2019.csv earch O B C W