Baseball Data Set

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Research of Baseball Data Set RES/341 July 18, 2011 Research of Baseball Data Set Research Process In baseball, does salary affect performance of the players? This is the question being used in this research process. The data being used to answer this question ranges from team, salary, wins, batting, ERA’s, HR, Errors and SB’s. All of this information is necessary in attempting to gauge the effect salary has on players performances. We must note that salary as a whole is based upon several factors as determined by Gerald Scully in his 1974 article titled “Pay and Performance in Major League Baseball.” Two of these factors are skill level and team standing. Quantifiable Measures * T = Team * L = League * S = Salary in…show more content…
The information is data collected from Major League Baseball season of 2005. The data set shows the team salaries, team statistics, and the average salary of professional players from years 1989 until 2005. It is important to indicate that individual statistics are not given. However, a generalization is made to support the hypothesis. The research is designed to show how salary is used as a motivational factor to affect performance. The importance is to show what motivates the players from several perspectives such as manager’s, team owners and stakeholder’s. Millions of dollars are spent every year to support Major League Baseball, and for 2005 the amount was $2,191,906,898 (Lind, Marchal, & Wathen,…show more content…
Gender, zip codes, area of country, desired color, and belief are illustrations of variables calculated on a nominal scale. The important thing concerning nominal scales is that they have no impact on the data. In the Ordinal Scale style, the figures given to things or occasions stand for the rank order (First, Second, Third, etc.) of the units reviewed that represent a quality measurement and can tell if a case has more or less. An ordinal scale describes a whole preorder of things; the scale importance is to have a total order. Ranked preferences only tell what one preference is over another, not how much more is desired. Quantitative traits are all calculable with interval scales, as some variation with the levels of an trait will be able to be multiplied by a real number to surpass or equivalent some other variation. A very well-known illustration of interval scale capacity is temperature with the Celsius scale. The thermometer signifies equal amounts of mercury between each interval on the scale. The "zero point" lying on an interval scale is subjective; and negative values will be of use. Another example of the interval scales in our everyday life are the SAT

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