A team averaging 106 points is likely to do very well during the regular season. The coach of your team has hypothesized that your team scored at an average of less than 106 points in the years 2013-2015. Test this claim at a 1% level of significance. For this test, assume that the population standard deviation for relative skill level is unknown.Use the information in the picture to write a block of code. Here is some information that will help you write this code block. Reach out to your instructor if you need help.The dataframe for your team is called your_team_df.The variable 'pts' represents the points scored by your team.Calculate and print the mean points scored by your team during the years you picked.Identify the mean score under the null hypothesis. You only have to identify this value and do not have to print it. (Hint: this is given in the problem statement)Assuming that the population standard deviation is unknown, use Python methods to carry out the hypothesis test.Calculate and print the test statistic rounded to two decimal places.Calculate and print the P-value rounded to four decimal places. Step 3: Hypothesis Test for the Population Mean (1)A relative skill level of 1340 represents a critically low skill level in the league. The management of your team has hypothesized that the average relative skilllevel of your team in the years 2013-2015 is greater than 1340. Test this claim using a 5% level of significance. For this test, assume that the populationstandard 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 thevariable 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.import scipy.stats as st# Mean relative skill Level of your teammean_elo_your_team = your_team_df['elo_n'].mean()print("Mean Relative Skill of your team in the years 2013 to 2015 =, round(mean_elo_your_team, 2))#Hypothesis Test#---- TODO: make your edits heretest_statistic, p_value = st.ttest_1samp(your_team_df['elo_n'], 1348)print("Hypothesis Test for the Population Mean")print("Test Statistic =", round(test_statistic, 2))print("P-value=", round(p_value,4))Mean Relative Skill of your team in the years 2013 to 2015 = 1489.87Hypothesis Test for the Population MeanTest Statistic = 51.95P-value = 0.0

Answer: from scipy.stats import ttest_1sampimport numpy as npmean_pts =…

Answered: A team averaging 106 points is likely…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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A team averaging 106 points is likely to do very well during the regular season. The coach of your team has hypothesized that your team scored at an average of less than 106 points in the years 2013-2015. Test this claim at a 1% level of significance. For this test, assume that the population standard deviation for relative skill level is unknown.

Use the information in the picture to write a block of code. Here is some information that will help you write this code block. Reach out to your instructor if you need help.

The dataframe for your team is called your_team_df.
The variable 'pts' represents the points scored by your team.
Calculate and print the mean points scored by your team during the years you picked.
Identify the mean score under the null hypothesis. You only have to identify this value and do not have to print it. (Hint: this is given in the problem statement)
Assuming that the population standard deviation is unknown, use Python methods to carry out the hypothesis test.
Calculate and print the test statistic rounded to two decimal places.
Calculate and print the P-value rounded to four decimal places.

Step 3: Hypothesis Test for the Population Mean (1)
A relative skill level of 1340 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 1340. 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.
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.
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(mean_elo_your_team, 2))
#Hypothesis Test
#---- TODO: make your edits here
test_statistic, p_value = st.ttest_1samp(your_team_df['elo_n'], 1348)
print("Hypothesis Test for the Population Mean")
print("Test Statistic =", round(test_statistic, 2))
print("P-value=", round(p_value,4))
Mean Relative Skill of your team in the years 2013 to 2015 = 1489.87
Hypothesis Test for the Population Mean
Test Statistic = 51.95
P-value = 0.0

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