某食品店为了了解气温对销售量的影响,随机记录了该店\(1\)月份中\(5\)天的日销售量\(y(\)单位:千克\()\) 与该地当日最低气温\(x(\)单位:\({{ }}^{{∘}}C)\) 的数据,如下表:
\(x\) | \(2\) | \(5\) | \(8\) | \(9\) | \(11\) |
\(y\) | \(12\) | \(10\) | \(8\) | \(8\) | \(7\) |
\((1)\) 求出\(y\)与\(x\)的回归方程\(\hat{y}=\hat{b}x+\hat{a}\);
\((2)\) 判断\(y\)与\(x\)之间是正相关还是负相关;若该地\(1\)月份某天的最低气温为\(6^{{∘}}C\),请用所求回归方程预测该店当日的销售量;
\((3)\) 设该地\(1\)月份的日最低气温\(X{~}N(\mu{,}\sigma^{2})\),其中\(\mu\)近似为样本平均数\(\bar{x}\),\(\sigma^{2}\)近似为样本方差\({{s}^{2}}\),求\(P(3{.}8{ < }X{ < }13{.}4)\).
附:\({①}\) 回归方程\(\hat{y}=\hat{b}x+\hat{a}\)中,\(\hat{b}=\dfrac{\sum\limits_{i=1}^{n}{{{x}_{i}}{{y}_{i}}}-n\bar{x}\bar{y}}{\sum\limits_{i=1}^{n}{{{x}_{i}}^{2}}-n{{{\bar{x}}}^{2}}}\),\(\hat{a}=\bar{y}-\hat{b}\bar{x}\).
\({②}\sqrt{10}{≈}3{.}2\),\(\sqrt{3{.}2}{≈}1{.}8{.}\) 若\(X{~}N(\mu{,}\sigma^{2})\),则\(P(\mu{-}\sigma{ < }X{ < }\mu{+}\sigma){=}0{.}6826\),\(P(\mu{-}2\sigma{ < }X{ < }\mu{+}2\sigma){=}0{.}9544\).