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Read the following description of a data set.\newlineKenji wants to ensure that the new board game he's designing is accessible to a wide age range. To test this, he had several children of various ages play the board game against each other. Each child played the game the same number of times.For each child, Kenji recorded his or her age, xx, and the number of games that child had won, yy.The least squares regression line of this data set is:y=22.284x116.736y = 22.284x - 116.736\newlineComplete the following sentence:\newlineIf a child were one year older, the least squares regression line predicts he or she would have won _\_ more games.

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Q. Read the following description of a data set.\newlineKenji wants to ensure that the new board game he's designing is accessible to a wide age range. To test this, he had several children of various ages play the board game against each other. Each child played the game the same number of times.For each child, Kenji recorded his or her age, xx, and the number of games that child had won, yy.The least squares regression line of this data set is:y=22.284x116.736y = 22.284x - 116.736\newlineComplete the following sentence:\newlineIf a child were one year older, the least squares regression line predicts he or she would have won _\_ more games.
  1. Identify Slope: Identify the slope of the least squares regression line. The equation given is y=22.284x116.736y = 22.284x - 116.736. The slope of the least squares regression line is the coefficient of xx, which is 22.28422.284. This slope indicates the change in the number of games won for each one year increase in age.
  2. Interpret Slope: Interpret the slope.\newlineSince the slope is 22.28422.284, this means that for each additional year in age, the least squares regression line predicts that a child would win 22.28422.284 more games.

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