Refer to the Baseball data:1) At the 0.05 significance level, can we conclude that there is a difference in the mean salary of teams in the American League versus teams in the National League?2) At the 0.05 significance level, can we conclude that there is a difference in the mean home attendance of teams in the American League versus teams in the National League?3) Compute the mean and the standard deviation of the attendance for the 10 teams with the highest salaries. Do the same for the 10 teams with the lowest salaries. At the .05 significance level, is there a difference in the mean attendance for the two groups? The spreadsheet presents a dataset organized in a tabular format, detailing various statistics for Major League Baseball teams from different leagues (American and National). The columns in the dataset are as follows:- Column A: Team Name- Column B: League (American or National)- Column C: Year Established- Column D: Payroll (in millions)- Column E: Attendance- Column F: Wins- Column G: Earned Run Average (ERA)- Column H: Batting Average- Column I: Home Runs- Column J: Year (repeated for additional data)- Column K: Team ERA for corresponding years- Column L: Runs Scored Per Game for corresponding years (2010-2016)For instance, the LA Dodgers, established in 1962, had a payroll of $223.35 million with an attendance of 3,703,312. They recorded 91 wins, an ERA of 3.70, a batting average of 0.249, and 189 home runs.The dataset provides a comprehensive overview of team performance and financial statistics over multiple years, illustrating trends in team success and expenditures. There are no graphs or diagrams in this dataset; all information is presented in a tabular form. **Baseball Team Performance and Economics Analysis**This spreadsheet provides data on various baseball teams, illustrating both their performance and financial aspects over selected years. The dataset includes columns with the following information:- **Team (Column A):** The name of the baseball team.- **League (Column B):** Indicates whether the team belongs to the National or American League.- **Year Opened (Column C):** The year the team was established.- **Team Salary (Column D):** The total salary of the team, likely in millions of dollars.- **Attendance (Column E):** The total number of attendees reported for the team.- **Wins (Column F):** The number of games the team won.- **ERA (Column G):** Earned Run Average, a measure of a team's pitching effectiveness.- **BA (Column H):** Batting Average, representing the team's hitting effectiveness.- **HR (Column I):** Home Runs hit by the team.Additionally, there is a section tracking average salaries across years:- **Year (Column K):** The year for which average salary data is provided.- **Average Salary (millions) (Column L):** The average salary for players during that year, in millions of dollars.**Highlights:**- **Part I and Part II (Columns M and N):** These labels separate the average salary data section into two parts, covering different time frames from 2000 to 2016.This information helps analyze trends in team performance metrics like wins, ERA, and home runs, alongside financial data like team salaries and average player salaries over time. Such insights could assist in understanding how financial investments in salaries correlate with on-field success and fan engagement measured by attendance. **No graphs or diagrams are present in this spreadsheet.**

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Description: Refer to the Baseball data:1) At the 0.05 significance level, can we conclude that there is a difference in the mean salary of teams in the American League versus teams in the National League?2) At the 0.05 significance level, can we conclude that th

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Refer to the Baseball data:

1) At the 0.05 significance level, can we conclude that there is a difference in the mean salary of teams in the American League versus teams in the National League?

2) At the 0.05 significance level, can we conclude that there is a difference in the mean home attendance of teams in the American League versus teams in the National League?

3) Compute the mean and the standard deviation of the attendance for the 10 teams with the highest salaries. Do the same for the 10 teams with the lowest salaries. At the .05 significance level, is there a difference in the mean attendance for the two groups?

The spreadsheet presents a dataset organized in a tabular format, detailing various statistics for Major League Baseball teams from different leagues (American and National). The columns in the dataset are as follows:

- Column A: Team Name
- Column B: League (American or National)
- Column C: Year Established
- Column D: Payroll (in millions)
- Column E: Attendance
- Column F: Wins
- Column G: Earned Run Average (ERA)
- Column H: Batting Average
- Column I: Home Runs
- Column J: Year (repeated for additional data)
- Column K: Team ERA for corresponding years
- Column L: Runs Scored Per Game for corresponding years (2010-2016)

For instance, the LA Dodgers, established in 1962, had a payroll of $223.35 million with an attendance of 3,703,312. They recorded 91 wins, an ERA of 3.70, a batting average of 0.249, and 189 home runs.

The dataset provides a comprehensive overview of team performance and financial statistics over multiple years, illustrating trends in team success and expenditures. There are no graphs or diagrams in this dataset; all information is presented in a tabular form.

**Baseball Team Performance and Economics Analysis**

This spreadsheet provides data on various baseball teams, illustrating both their performance and financial aspects over selected years. The dataset includes columns with the following information:

- **Team (Column A):** The name of the baseball team.
- **League (Column B):** Indicates whether the team belongs to the National or American League.
- **Year Opened (Column C):** The year the team was established.
- **Team Salary (Column D):** The total salary of the team, likely in millions of dollars.
- **Attendance (Column E):** The total number of attendees reported for the team.
- **Wins (Column F):** The number of games the team won.
- **ERA (Column G):** Earned Run Average, a measure of a team's pitching effectiveness.
- **BA (Column H):** Batting Average, representing the team's hitting effectiveness.
- **HR (Column I):** Home Runs hit by the team.

Additionally, there is a section tracking average salaries across years:

- **Year (Column K):** The year for which average salary data is provided.
- **Average Salary (millions) (Column L):** The average salary for players during that year, in millions of dollars.

**Highlights:**

- **Part I and Part II (Columns M and N):** These labels separate the average salary data section into two parts, covering different time frames from 2000 to 2016.

This information helps analyze trends in team performance metrics like wins, ERA, and home runs, alongside financial data like team salaries and average player salaries over time. Such insights could assist in understanding how financial investments in salaries correlate with on-field success and fan engagement measured by attendance.

**No graphs or diagrams are present in this spreadsheet.**

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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