导读：作文标题：Leastsquaresregressionproject.关 键 词：高中高二1000字字 数：1000字作文本文适合：高中高二作文网提示:我...
作文标题： Least squares regression project.
关 键 词： 高中高二 1000字
字 数： 1000字作文
本文适合： 高中高二
STATS. Least squares regression project. 来自：作文大全 来源：作文网 zw.liuxue86.comI think it would make most sense to predict weight from height, because the growth of height means more bones, more flesh. So as height increases, weight would normally increase along. But gaining weight simply means more fat stored to the body, and it has nothing to do with height. I expect the association between height and weight to be roughly linear and positive. According to our scatter plot, there are curves, the association is roughly linear, and the regression line shows a positive relationship between height and weight. This scatter plot confirmed my expectations of the relationship between height and weight. According to the linear model, we expect that for every extra inch increase in height, there will be about 3.711 pounds increase in weight on average. And the predictions say that when height equals to zero inch, the weight will be -127.14 pounds. This is extrapolation and does not have any meaning in this problem. Yes these lines indicate a difference between the two groups. The slope of the regression line for female group of data is 4.7745 and for male group is 3.4, this means for the same number of inches increase in height, girls are likely to gain more weight than boys. According to our linear model, we expect that for every extra inch increase in height, there will be about 3.4 pounds increase in weight for boys, and 4.77 pounds increase in weight for girls, on average. Predictions according to the first equation (with out grouping by sex.) shirley 17 F 67 122 121.515529 roberto 16 M 70 130 132.649594 charmaine 12 F 60 105 95.536045 huy 14 m 66 112 117.804174 Predictions according to the second & third equation (grouping by sex) shirley 17 F67 122 130.122244 roberto 16 M70 130 129.03125 charmaine12 F60 105 96.7004008 huy 14 M 66 112 115.428638 The residuals are generally small and the predictions are pretty accurate. Both ways of predicting result some errors, and I think neither is more accurate than the other. The differences between the groups that the lines convey are probably due to other factors like age, which we did not take into consideration, or by grouping the data by sex, we have weakened the association of weight and height. 《Least squares regression project.》这篇优秀的“高一作文”由作文网收集，来源于互联网和会员投稿，仅供参考和学习，转载请注明出处。
关 键 词： 高中高二 1000字
字 数： 1000字作文
本文适合： 高中高二
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欢迎阅读《作文:Least squares regression project.》，“作文网”每日为您更新更多优秀的“高一作文”，请随时关注！STATS. Least squares regression project. 来自：作文大全 来源：作文网 zw.liuxue86.comI think it would make most sense to predict weight from height, because the growth of height means more bones, more flesh. So as height increases, weight would normally increase along. But gaining weight simply means more fat stored to the body, and it has nothing to do with height. I expect the association between height and weight to be roughly linear and positive. According to our scatter plot, there are curves, the association is roughly linear, and the regression line shows a positive relationship between height and weight. This scatter plot confirmed my expectations of the relationship between height and weight. According to the linear model, we expect that for every extra inch increase in height, there will be about 3.711 pounds increase in weight on average. And the predictions say that when height equals to zero inch, the weight will be -127.14 pounds. This is extrapolation and does not have any meaning in this problem. Yes these lines indicate a difference between the two groups. The slope of the regression line for female group of data is 4.7745 and for male group is 3.4, this means for the same number of inches increase in height, girls are likely to gain more weight than boys. According to our linear model, we expect that for every extra inch increase in height, there will be about 3.4 pounds increase in weight for boys, and 4.77 pounds increase in weight for girls, on average. Predictions according to the first equation (with out grouping by sex.) shirley 17 F 67 122 121.515529 roberto 16 M 70 130 132.649594 charmaine 12 F 60 105 95.536045 huy 14 m 66 112 117.804174 Predictions according to the second & third equation (grouping by sex) shirley 17 F67 122 130.122244 roberto 16 M70 130 129.03125 charmaine12 F60 105 96.7004008 huy 14 M 66 112 115.428638 The residuals are generally small and the predictions are pretty accurate. Both ways of predicting result some errors, and I think neither is more accurate than the other. The differences between the groups that the lines convey are probably due to other factors like age, which we did not take into consideration, or by grouping the data by sex, we have weakened the association of weight and height. 《Least squares regression project.》这篇优秀的“高一作文”由作文网收集，来源于互联网和会员投稿，仅供参考和学习，转载请注明出处。
