Analysis of the Salaries of 100 Baseball Players
Analysis of the Salaries of 100 Baseball Players

Analysis of the Salaries of 100 Baseball Players

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  • Pages: 4 (2044 words)
  • Published: October 22, 2017
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Undertaking 1

Question # 1: Obtain a set of 100 natural informations refering to some concern units.

Answer 1: The information I selected for this undertaking is the wages of 100 participants. This natural information including name of participants, their salary, their place and the last column is for ciphering the frequence distribution in the 2nd inquiry, I have arranged the information in falling order, from highest to lowest.

Player

Salary

Position

Largest to smallest

Acevedo, Juan

900,000

Pitcher

20,000,000

Anderson, Jason

300,000

Pitcher

15,600,000

Mark twains, Roger

10,100,000

Pitcher

15,500,000

Contreras, Jose

5,500,000

Pitcher

13,000,000

Flaherty, John

750,000

Catcher

12,357,143

Giambi, Jason

11,428,571

First Baseman

12,000,000

Hammond, Chris

2,200,000

Pitcher

11,500,000

Hitchcock, Sterling

6,000,000

Pitcher

11,500,000

Jeter, Derek

15,600,000

Shortstop

11,428,571

Johnson, Nick

364,100

First Baseman

11,000,000

Karsay, Steve

5,000,000

Pitcher

10,500,000

Latham, Chris

400,000

Outfielder

10,100,000

Liever, Jon

550,000

Pitcher

9,900,000

Matsui, Hideki

6,000,000

Outfielder

8,166,667

Mondesi, Raul

13,000,000

Outfielder

8,000,000

Mussina, Mike

12,000,000

Pitcher

7,833,333

Osuna, Antonio

2,400,000

Pitcher

7,500,000

Pettitte, Andy

11,500,000

Pitcher

7,250,000

Posada, Jorge

8,000,000

Catcher

7,250,000

Rivera, Mariano

10,500,000

Pitcher

7,166,667

Soriano, Alfonso

800,000

Second Baseman

6,750,000

Trammell, Bubba

2,500,000

Outfielder

6,750,000

Ventura, Robin

5,000,000

Third Baseman

6,000,000

Weaver, Jeff

4,150,000

Pitcher

6,000,000

Wells, David

3,250,000

Pitcher

5,500,000

Williams, Bernie

12,357,143

Outfielder

5,500,000

Wilson, Enrique

700,000

Shortstop

5,350,000

""""""

Zeile, Todd

1,500,000

Third Baseman

5,125,000

Anderson, Garret

5,350,000

Outfielder

5,000,000

Appier, Kevin

11,500,000

Pitcher

5,000,000

Callaway, Mickey

302,500

Pitcher

4,700,000

Donnelly, Brendan

325,000

Pitcher

4,250,000

Eckstein, David

425,000

Shortstop

4,150,000

Erstad, Darin

7,250,000

Outfielder

4,000,000

Fullmer, Brad

1,000,000

First Baseman

4,000,000

Gil, Benji

725,000

Shortstop

3,916,667

Glaus, Troy

7,250,000

Third Baseman

3,875,000

Kennedy, Adam

2,270,000

Second Baseman

3,625,000

Lackey, John

315,000

Pitcher

3,450,000

Molina, Benjie

1,425,000

Catcher

3,250,000

Molina, Jose

320,000

Catcher

3,000,000

Ortiz, Ramon

2,266,667

Pitcher

2,900,000

Owens, Eric

925,000

Outfielder

2,500,000

Percival, Troy

7,833,333

Pitcher

2,400,000

Ramirez, Julio

300,000

Outfielder

2,270,000

Rodriquez, Francisco

312,500

Pitcher

2,266,667

Salmon, Tim

9,900,000

Outfielder

2,200,000

Schoeneweis, Scott

1,425,000

Pitcher

2,100,000

Sele, Aaron

8,166,667

Pitcher

2,000,000

Shields, Scot

305,000

Pitcher

2,000,000

Spiezio, Scott

4,250,000

First Baseman

1,850,000

Washburn, Jarrod

3,875,000

Pitcher

1,700,000

Weber, Ben

375,000

Pitcher

1,500,000

Wise, Matt

302,500

Pitcher

1,500,000

Wooten, Shawn

337,500

Catcher

1,425,000

Burkett, John

5,500,000

Pitcher

1,425,000

Damon, Johnny

7,500,000

Outfielder

1,250,000

Embree, Alan

3,000,000

Pitcher

1,000,000

Fossum, Casey

324,500

Pitcher

1,000,000

Fox,

...

Chad

500,000

Pitcher

925,000

Garciaparra, Nomar

11,000,000

Shortstop

900,000

Giambi, Jeremy

2,000,000

Outfielder

900,000

Gonzalez, Dicky

300,000

Pitcher

805,000

Hillenbrand, Shea

407,500

Third Baseman

800,000

Howry, Bobby

1,700,000

Pitcher

750,000

Jackson, Damian

625,000

Shortstop

725,000

Lowe, Derek

3,625,000

Pitcher

700,000

Lyon, Brandon

309,500

Pitcher

625,000

Martinez, Pedro

15,500,000

Pitcher

550,000

Mendoza, Ramiro

2,900,000

Pitcher

500,000

Millar, Kevin

2,000,000

First Baseman

500,000

Mirabelli, Doug

805,000

Catcher

425,000

Mueller, Bill

2,100,000

Third Baseman

407,500

Nixon, Trot

4,000,000

Outfielder

400,000

Ortiz, David

1,250,000

First Baseman

400,000

Person, Robert

300,000

Pitcher

375,000

Ramirez, Manny

20,000,000

Outfielder

364,100

Timlin, Mike

1,850,000

Pitcher

337,500

Varitek, Jason

4,700,000

Catcher

330,000

Wakefield, Tim

4,000,000

Pitcher

325,000

Walker, Todd

3,450,000

Second Baseman

324,500

White, Matt

300,000

Pitcher

320,000

""""Anderson, Brian

1,500,000

Pitcher

315,000

Baez, Danys

5,125,000

Pitcher

314,400

Bard, Josh

302,100

Catcher

314,300

Bere, Jason

1,000,000

Pitcher

312,500

Blake, Casey

330,000

Third Baseman

309,500

Bradley, Milton

314,300

Outfielder

307,500

Broussard, Benjamin

303,000

First Baseman

305,000

Martha jane burks, Ellis

7,166,667

Outfielder

303,000

Davis, Jason

301,100

Pitcher

302,500

Garcia, Karim

900,000

Outfielder

302,500

Gutierrez, Ricky

3,916,667

Shortstop

302,200

Hafner, Travis

302,200

First Baseman

302,100

Laker, Tim

400,000

Catcher

301,100

Lawton, Matt

6,750,000

Outfielder

300,900

Cleveland Indians

6,750,000

Outfielder

300,900

Cleveland Indians

300,900

Pitcher

300,000

Cleveland Indians

314,400

Shortstop

300,000

Cleveland Indians

500,000

Pitcher

300,000

Cleveland Indians

307,500

Pitcher

300,000

Cleveland Indians

300,900

Shortstop

300,000

Question # 2: Concept a frequence distribution and histogram for the informations utilizing 7 or 8 categories.

Answer 2: Frequency Distribution: the distribution of frequence in a interval is the figure of observations. The interval size used depends on the information. If the information is big so the interval is big and if the information is little so the interval is little. An of import point that must be kept in head while doing intervals is that they must non overlap one another and it must incorporate all the possible observation nowadays.

For the intent of happening frequence distribution, I found out lowest wage and highest wage from the sample, which is as follows:

Lowest salary = 300,000 and highest salary = 20,000,000

This lower and highest wage can besides be referred as lower category boundary which is little figure that can be represented in different categories, whereas, upper category boundary is the highest figure that can belong to the different categories.

I had an option of choosing either 7 or 8 categories so:

Number of categories = 8

The Range of my informations = 20,000,000 – 300,000 = 19,700,000

Class breadth which is besides known as the size of interval =""

For ciphering the category bounds, I have added 2,462,500 in 300,000 which is the lowest wage to acquire 2,762,500. For the 2nd bound I have once more repeated this process and added 2,462,500 to acquire 5,225,001. I have repeated this for all category limits computation. To avoid informations from over lapping I have increased 1 figure at the terminal of each category bound.

Class bounds

Frequency

Upper bound

300,000 – 2,762,500

5

300,000

2,762,501 – 5,225,001

55

2762501

5,225,002 – 7,687,502

15

5,225,002

7,687,503 – 10,150,003

11

7,687,503

10,150,004 – 12,612,503

5

10,150,004

12,612,504 – 15,075,004

7

12,612,504

15,075,005 – 17,537,505

1

15,075,005

17,537,506 – 20,000,005

2

17,537,506

Histogram:

It is fundamentally a graph that shows the information with the aid of bars of assorted highs. In a histogram Numberss are grouped in intervals and frequences. The tallness of a peculiar saloon depends on scope of interval. It varies from one scope

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to another. For doing histogram, I used informations analysis in excel. Bin is the upper category bound that I calculated for the intent of doing category bounds. For doing histogram, bin and frequence are required ; I used them both as shown:

Bin

Frequency

300,000

5

2,762,501

55

5,225,002

15

7,687,503

11

10,150,004

5

12,612,504

7

15,075,005

1

17,537,506

2

More

1

The histogram formed from this tabular array is:

""

Question # 3: What can you detect from the histogram about informations?

Answer 3: In the histogram shown above, Frequency is plotted at the perpendicular axis ( y-axis ) and Bin is plotted at the horizontal axis ( x-axis ) . To understand and construe a histogram, it’s of import to understand frequence foremost. Frequency is the figure of times a peculiar character or figure is found in a given sample.

In my sample, I have calculated the frequence of the figure of times a peculiar sum of wage is found in the sample. For illustration, the wage of 300,000 if found 5 times in the sample and so hold the frequence of 5.

This histogram tells that the wage of $ 2,762,501 has the highest frequence of 55 which means that this is the salary most common amongst the participants. Similarly, the lowest frequence in our sample is 1 with the sum of salary $ 15,075,005 which is the most uncommon amongst participants.

Other observations of histogram are as follows, the wage of 300,000 has a frequence of 5 which means that there are 5 participants who have the wage of 300,000. Another observation shows that 15 participants have the wage of 5,225,002, 11 participants have the wage of 7,687,503, 5 participants have the wage of 10,150,004 and 7 participants have the wage of 12,612,504.

Question # 4: Find mean, average and manner.

Answer # 4: mean is the mean figure, it represents a sample and if in a sample norm is used for computations, consequences will be the same if original values are used, whereas, median is the in-between figure in a set of informations. And manner is the figure that occurs most often in a set of informations.

I calculated the mean, average and manner for the informations utilizing excel and computation is shown in the affiliated excel file above is:

Mean

3,615,811

Median

1,775,000

Manner

300000

The norm of our sample is 3,615,811 which represents our set of informations, median is 1,775,000 which is the center or in-between figure of our sample and manner is 3000,000 which is the most perennial figure of our sample.

Question # 5: Find the sample standard divergence and discrepancy.

Answer # 5: standard divergence of a sample measures that in a peculiar distribution, how much are Numberss spread out, it shows that in a peculiar sample, how much divergence is at that place between the value and mean of the sample. A simple expression for mean is variance’s square root. Variance besides measures the discrepancy of values from the mean.

Both standard divergence and discrepancy are used for ciphering discrepancy in the information. Both measures the scattering of informations and are really of import steps of statistics. The computation for mensurating discrepancy is non every bit simple as that of standard divergence.

Similarly, I calculated the standard divergence and fluctuation utilizing excel:

Standard divergence

4240353.494

Variation

1.79806E+13

This standard divergence shows that

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