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Owner: mp327343
Created: Apr 22, 2014
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Math Project Phase 1

-Michael Pensivy

This is the data for MLB player's salaries for the year 2013 by (treiland) .The reasoning behind me choosing this data is because I enjoy baseball and was curious about the salaries of the top starting players. The categorical variable information consists of these columns:  the rank of the player, the players themselves, their team, and their position. The quantitative variable information consists of the player’s salaries (\$), the years(yrs.) they were paid in their contract, the total value of their contract(\$), and their average annual salary(\$).

The graphs represented are, categorical variables, rank of top salary for each player and how many people are in each section, then goes the teams and the percentage of each total of players on that specific team, then the positions of all the players. The players are not shown because there are far too many in the data set to get a real good display and analysis.

The graphs shown as the quantative variables which are total values, 2013 salary, and average annual. Each represents a skew that goes to the left. Showing the number of  summary statistics the total value and the average are almost exact, but the 2013 summary shows greater numbers showing the best choice for an overall option.

Phase 3

The first scatter plot represents the salary by the rank of the player. As you go across the the graph you see a decrease in salary as you go down in rank. Since this is mostly about your salary by rank the graph shows a strong negative linear line. In this graph there no outliers.

The second graph represents the total value of a player and what he made in 2013. As you go left to right you will the graph start spreading out as the players who are getting more money will start inching away from the less paid players. This graph shows a positive, but moderately strong linear graph. However, to me there are three outliers that just stick out in the graph. In order to make the graph stronger I took out these outliers and made a new graph showing these data having a positive, strong, linear, progression

Phase 4

Result 1: Rank Frequency Table   [Info]
Frequency table results for RANK:
 RANK Frequency Relative Frequency Percent of Total 0 to 200 199 0.26392573 26.392573 200 to 400 200 0.26525199 26.525199 400 to 600 200 0.26525199 26.525199 600 to 800 155 0.20557029 20.557029

Result 2: Pie Chart With Rank Data   [Info]

Result 3: Team and position Frequency Table   [Info]
Frequency table results for TEAM:
 TEAM Frequency Relative Frequency Percent of Total ARI 27 0.035809019 3.5809019 ATL 23 0.030503979 3.0503979 BAL 25 0.033156499 3.3156499 BOS 29 0.038461538 3.8461538 CHC 27 0.035809019 3.5809019 CIN 25 0.033156499 3.3156499 CLE 26 0.034482759 3.4482759 COL 24 0.031830239 3.1830239 CWS 23 0.030503979 3.0503979 DET 23 0.030503979 3.0503979 HOU 19 0.025198939 2.5198939 KC 24 0.031830239 3.1830239 LAA 27 0.035809019 3.5809019 LAD 27 0.035809019 3.5809019 MIA 27 0.035809019 3.5809019 MIL 25 0.033156499 3.3156499 MIN 22 0.029177719 2.9177719 NYM 26 0.034482759 3.4482759 NYY 28 0.037135279 3.7135279 OAK 23 0.030503979 3.0503979 PHI 28 0.037135279 3.7135279 PIT 26 0.034482759 3.4482759 SD 29 0.038461538 3.8461538 SEA 20 0.026525199 2.6525199 SF 27 0.035809019 3.5809019 STL 24 0.031830239 3.1830239 TB 25 0.033156499 3.3156499 TEX 23 0.030503979 3.0503979 TOR 27 0.035809019 3.5809019 WSH 25 0.033156499 3.3156499

Frequency table results for POS:
 POS Frequency Relative Frequency Percent of Total 1B 38 0.050397878 5.0397878 2B 44 0.058355438 5.8355438 3B 48 0.063660477 6.3660477 C 63 0.083554377 8.3554377 DH 15 0.019893899 1.9893899 OF 142 0.18832891 18.832891 P 352 0.4668435 46.68435 SS 52 0.068965517 6.8965517

Result 4: Pie Chart With team categorical Data   [Info]

Result 5: Bar Plot With Data   [Info]

Result 6: Total Values Boxplot   [Info]

Result 7: Histogram of 2013 salary   [Info]

Result 8: Avg Annual Dotplot   [Info]

Result 9: 2013 Summary Stats of 5 number summary   [Info]
Summary statistics:
 Column n Mean Variance Std. dev. Std. err. Median Range Min Max Q1 Q3 2013 SALARY 754 3972849.8 2.5534374e13 5053154.8 184025.04 1600000 28510000 490000 29000000 509500 5500000

Result 10: Total value 5 number Summary Stats   [Info]
Summary statistics:
 Column n Mean Variance Std. dev. Std. err. Median Range Min Max Q1 Q3 TOTAL VALUE 754 13999500 1.0061247e15 31719468 1155154.9 1835000 2.7451e8 490000 2.75e8 509500 10300000

Result 11: Avg. Annual 5 number Summary Stats   [Info]
Summary statistics:
 Column n Mean Variance Std. dev. Std. err. Median Range Min Max Q1 Q3 AVG ANNUAL 754 4094844.9 2.6946953e13 5191045.4 189046.72 1662500 27010000 490000 27500000 509500 5687500

Result 12: Scatter Plot with Salary of player by rank   [Info]

Result 13: Scatter Plot   [Info]

Result 14: Scatter Plot with value of player and their average salary   [Info]

Result 15: One Sample T For 2013 salary   [Info]
Hypothesis test results:
Group by: 2013 SALARY
μ : Mean of 2013 SALARY
H0 : μ = 0.5
HA : μ ≠ 0.5
 2013 SALARY Sample Mean Std. Err. DF T-Stat P-value 0 to 5000000 1389761.7 51010.502 542 27.244608 <0.0001 5000000 to 10000000 6716366.6 131698.01 109 50.998234 <0.0001 10000000 to 15000000 11836250 182174.49 56 64.972045 <0.0001 15000000 to 20000000 16196607 246959.17 23 65.584145 <0.0001 20000000 to 25000000 21372391 335853.93 17 63.63597 <0.0001 25000000 to 30000000 27000000 2000000 1 13.5 0.0471

Data set 1. 2013 Major League Baseball Salaries   [Info]