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5. Hypothesis Test for the Difference Between Two Population Means You were asked to compare your team 's skill level Girom its years) with the
5. Hypothesis Test for the Difference Between Two Population Means You were asked to compare your team 's skill level Girom its years) with the assigned team 's skill level from the assigned time ame). You tested the claim that the skill level of your team is the same as the skill level of the assigned team, using a 1% level of signicance. See Step 6 in the Python script to address the following items: I In general, how is hypothesis testing used to test claims about the difference between two population means? 0 Summarize all important steps of the hypothesis test. This includes: . Null Hypothesis (statistical notation and its description in words) b. Alternative Hypothesis (statistical notation and its description in words) c. Level of Signicance d. a Report the Test Statistic and the P-value in a formatted table as shown below: Table 5: Hypothesis Test for the Difference Between Two Population Means Test Statistic 17.07 *Round of to 2 decimal places. Pvalue 0.0000l *Round 0 to 4 decimal laces. 6. Conclusion of the hypothesis test and its interpretation based on the P-value 0 What are the implications of your findings from this hypothesis test? What is its practical significance? 3] .0 Step 6: Hypothesis Test for the Difference Between Two Population Means The management of your team wants to compare the team with the assigned team (the Bulls in 19961 998). They claim that the skill level of your team in 2013-2015 is the same as the skill level of the Bulls in 1996 to 1998. In other words, the mean relative skill level of your team in 2013 to 2015 is the same as the mean relative skill level of the Bulls in 1996-1998. Test this claim using a 1% level of significance. Assume that the population standard deviation is unknown. Make the following edits to the code block below: 1. Replace ??DATAFRAME_ASSIGNED_TEAM?? with the name of assigned team's dataframe. See Step 1 for the name of assigned team's dataframe. 2. Replace ??DATAFRAM E_YOUR_TEAM?? with the name of your team's dataframe. See Step 2 for the name of your team's dataframe. 3. Replace ??RELATIVE_SKILL?? with the name of the variable for relative skill. See the table included in 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'. After you are done with your edits, click the block of code below and hit the Run button above. import scipy.stats as at mean_elo_n_project_team = assigned_team_df[ 'elo_n' ] .mean() print("Mean Relative Skill of the assigned team in the years 1996 to 1998 =\
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