janelle tracks the number of miles she drives and the number of gallons of gas she has left. what is the…

janelle tracks the number of miles she drives and the number of gallons of gas she has left. what is the linear regression model for this scenario? what is the correlation coefficient? what is the strength of the model?\nmiles driven\tgallons in tank\n27\t13\n65\t12\n83\t11\n109\t10\n142\t9\n175\t8
Answer
Explanation:
Step1: Denote variables
Let $x$ be the miles - driven and $y$ be the gallons - in - tank. Calculate the necessary sums: Let $n = 6$. $\sum_{i = 1}^{n}x_{i}=27 + 65+83 + 109+142+175=591$ $\sum_{i = 1}^{n}y_{i}=13 + 12+11 + 10+9+8=63$ $\sum_{i = 1}^{n}x_{i}^{2}=27^{2}+65^{2}+83^{2}+109^{2}+142^{2}+175^{2}=27^{2}+4225+6889+11881+20164+30625=74663$ $\sum_{i = 1}^{n}y_{i}^{2}=13^{2}+12^{2}+11^{2}+10^{2}+9^{2}+8^{2}=169+144+121+100+81+64=679$ $\sum_{i = 1}^{n}x_{i}y_{i}=27\times13+65\times12+83\times11+109\times10+142\times9+175\times8=351+780+913+1090+1278+1400=5812$
Step2: Calculate the slope $m$
The formula for the slope $m$ of the regression line is $m=\frac{n\sum_{i = 1}^{n}x_{i}y_{i}-\sum_{i = 1}^{n}x_{i}\sum_{i = 1}^{n}y_{i}}{n\sum_{i = 1}^{n}x_{i}^{2}-(\sum_{i = 1}^{n}x_{i})^{2}}$ $m=\frac{6\times5812 - 591\times63}{6\times74663-591^{2}}$ $=\frac{34872-37233}{447978 - 349281}=\frac{- 2361}{98697}\approx - 0.024$
Step3: Calculate the y - intercept $b$
The formula for the y - intercept $b$ is $b=\overline{y}-m\overline{x}$, where $\overline{x}=\frac{\sum_{i = 1}^{n}x_{i}}{n}=\frac{591}{6}=98.5$ and $\overline{y}=\frac{\sum_{i = 1}^{n}y_{i}}{n}=\frac{63}{6}=10.5$ $b = 10.5-(-0.024)\times98.5=10.5 + 2.364=12.864$ The linear regression model is $y=-0.024x + 12.864$
Step4: Calculate the correlation coefficient $r$
The formula for the correlation coefficient $r$ is $r=\frac{n\sum_{i = 1}^{n}x_{i}y_{i}-\sum_{i = 1}^{n}x_{i}\sum_{i = 1}^{n}y_{i}}{\sqrt{(n\sum_{i = 1}^{n}x_{i}^{2}-(\sum_{i = 1}^{n}x_{i})^{2})(n\sum_{i = 1}^{n}y_{i}^{2}-(\sum_{i = 1}^{n}y_{i})^{2})}}$ $r=\frac{6\times5812-591\times63}{\sqrt{(6\times74663 - 591^{2})(6\times679-63^{2})}}$ $=\frac{-2361}{\sqrt{98697\times105}}\approx - 0.73$
Step5: Determine the strength of the model
Since $|r| = 0.73$, and $0.7\leq|r|\lt0.9$, the strength of the model is moderate.
Answer:
Linear regression model: $y=-0.024x + 12.864$ Correlation coefficient: $-0.73$ Strength of the model: Moderate