An author of a book discusses how statistics can be used to judge both a baseball player's potential and a team's ability to win games. One aspect of this analysis is that a team's on-base percentage is the best predictor of winning percentage. The on-base percentage is the proportion of time a player reaches a base. For example, an on-base percentage of 0.3 would mean the player safely reaches bases 3 times out of 10, on average. For a certain baseball season, winning percentage, y, and on-base percentage, x, are linearly related by the least-squares regression equation y = 2.92x-0.4871. Complete parts (a) through (d). O Yes O No (c) Would it be a good idea to use this model to predict the winning percentage of a team whose on-base percentage was 0.250? O Yes, it would be a good idea. O No, it would be a bad idea.

An author of a book discusses how statistics can be used to judge both a baseball player's potential and a team's ability to win games. One aspect of this analysis is that a team's on-base percentage is the best predictor of winning percentage. The on-base percentage is the proportion of time a player reaches a base. For example, an on-base percentage of 0.3 would mean the player safely reaches bases 3 times out of 10, on average. For a certain baseball season, winning percentage, y, and on-base percentage, x, are linearly related by the least-squares regression equation y = 2.92x-0.4871. Complete parts (a) through (d). O Yes O No (c) Would it be a good idea to use this model to predict the winning percentage of a team whose on-base percentage was 0.250? O Yes, it would be a good idea. O No, it would be a bad idea.

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MATLAB: An Introduction with Applications

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Author:Amos Gilat

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Sequence and Series

A sequence is defined as a collection of things. Series is defined to sum the things one by one in the sequence. It was invented by German mathematician Carl Friedrich Gauss.

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8/15

An author of a book discusses how statistics can be used to judge both a baseball player's potential and a team's ability to win games. One aspect of this analysis is
that a team's on-base percentage is the best predictor of winning percentage. The on-base percentage is the proportion of time a player reaches a base. For example,
an on-base percentage of 0.3 would mean the player safely reaches bases 3 times out of 10, on average. For a certain baseball season, winning percentage, y, and
on-base percentage, x, are linearly related by the least-squares regression equation y = 2.92x - 0.4871. Complete parts (a) through (d).
O Yes
No
(c) Would it be a good idea to use this model to predict the winning percentage of a team whose on-base percentage was 0.250?
Yes, it would be a good idea.
No, it would be a bad idea.
(d) A certain team had an on-base percentage of 0.324 and a winning percentage of 0.546 What is the residual for that team? How would you interpret this
residual?
The residual for the team is | (Round to four decimal places as needed)

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