suppose to use the information in step two for the variables in step three but not sure what to use for relative skill and how to input it and the null hypothesis

File Not Trusted Python 3 O Edit % View B Insert + Cell Run Kernel C Widgets Help Markdown + Step 2: Pick Your Team In this step, you will pick your team. The range of years that you will study for your team is 2013-2015. Make the following edits to the code block below: 1. Replace ??TEAM?? with your choice of team from one of the following team names. Bucks, Bulls, Cavaliers, Celtics, Clippers, Grizzlies, Hawks, Heat, Jazz, Kings, Knicks, Lakers, Magic, Mavericks, Nets, Nuggets, Pacers, Pelicans, Pistons, Raptors, Rockets, Sixers, Spurs, Suns, Thunder, Timberwolves, Trailblazers, Warriors, Wizards Remember to enter the team name within single quotes. For example, if you picked the Suns, then ??TEAM?? should be replaced with 'Suns' After you are done with your edits, click the block of code below and hit the Run button above. In [2]: # Range of years: 2013 2015 (Note: The line below selects al teams within the three-year period 2013-2015. This is not your_years_leagues df = nba orig det (nba_orig_df['year id'l between (2013, 2015)) 1 # The dataframe for your team is called your team d. ---- TODO: make your edits here your team df = your years leagues df[(your years leagues de tran id'='Heat')] your team df = your team_df.reset_index (drop=True) display (HTML (your team_df.head().to_html())) print("printed only the first five observations...") print("Number of rows in the dataset -"len (your team df)) game_id year_id fran_id pts opp_pts elo_n opp_elo n game_location game_result O 201210300MIA 2013 Heat 120 107 1666.3193 1586.1121 1 201211020NYK 2013 Heat 84 104 1647.6675 1548.2699 2 201211030MIA 2013 Heat 119 116 1650.0934 1554.4674 3 201211050MIA 2013 Heat 124 99 1656.56521504.0280 4 20121107OMIA 2013 Heat 103 73 1659.7239 1361.5804 I III printed only the first five observations ... Number of rows in the dataset - 246 Step 3: Hypothesis Test for the Population Mean (0) yu + x + Run C Markdown printed only the first five observations... Number of rows in the dataset - 246 Step 3: Hypothesis Test for the Population Mean (1) 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 standan 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. 2. 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 'var2'. 3. Replace ??NULL HYPOTHESIS_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 1 1: import scipy.stats as st # Mean relative skill level of your team mean_elo_your team = your team_df['olon'].mean() print("Mean Relative Skill of your team in the years 2013 to 2015 -", round (mean olo your team, 2)) # Hypothesis Test # ------ TODO: make your edits here -- test statistic, p value = st.ttest 13amp (?? DATAFRAME YOUR TEAM????RELATIVE SKILL??). ??NULL HYPOTHESIS VALUE??) print("Hypothesis Test for the Population Mean") print("Test Statistic", round (test statistic,2)) print("P-value=", round(p_value, 4)) Step 4: Hypothesis Test for the Population Mean (II)