Mat243

,a...._... \"any... ......_... r... -,.,._,....|-.-_.. Ic,r_-.-_.. ,......._.........-.. ,.....-_......... 0 201210310DET 2013 Pistons 96 105 |1420.1541|1512.0774 H L 1 201211020PHO 2013 Pistons 89 92 |1417.8512|1523.5597 A L 2 20121104OLAL 2013 Pistons 79 108 |1409.0566|1527.5927 A L 3 201211060DEN 2013 Pistons 97 109 |1405.2476|1558.2765 A L 4 20121107OSAC 2013 Pistons 103 105 |1402.0664|1411.2153 A L printed only the first five observations. . . Number of rows in the dataset = 246 Step 3: Hypothesis Test for the Population Mean (I) A relative skill level of 1420 represents a critically low skill level in the league. The management of your team has hypothesized that the average relative skill level of your team in the years 2013-2015 is greater than 1420. Test this claim using a 5% level of significance. For this test. assume that the population standard deviation for relative skill level is unknown. Make the following edits to the code block below: 1. Replace ??DATAFRAME,YOUR,TEAM?? with the name of your team's dataframe. See Step 2 for the name of your team's dataframe. 1. Replace ??RELATIVE_SKILL?? with the name of the variable for relative skill. See the table included in the Project Two instructions above to pick the variable name. Enclose this variable in single quotes. For example, if the variable name is var2 then replace ??RELATIVE_SKILL?? with 'vai2'. 1. Replace ??NULL,HYPOTHES|S,VALUE?? with the mean value of the relative skill under the null hypothesis. After you are done with your edits, click the block of code below and hit the Run button above. In [5]: import scipy.stats as st # Mean relative skill level of your team mean_elo_your_team = your_team_df[ 'elo_n' ] .mean( ) print("Mean Relative Skill of your team in the years 2013 to 2015 =", round(meaneloyourteam,2)) # Hypothesis Test # - TODD: make your edits here - test_statistic, p_value = st.ttest_lsamp(your_team_df[ 'elo_n'], 1420)