QUESTION IMAGE
Question
- dr. teodora collects data on the heights and weights of men in a study she is conducting. the data is below.
| height (inches) | 66 | 70 | 78 | 74 | 64 | 67 | 72 | 71 | 69 | 67 |
| weight (pounds) | 120 | 160 | 220 | 165 | 125 | 165 | 180 | 185 | 175 | 145 |
q 1 find a regression model, w(h), that shows the estimated weight of men based on their height, h. round all numbers to the nearest tenth.
Step1: Recall linear - regression formula
The linear - regression equation is of the form $y = ax + b$, where $y$ is the dependent variable (weight $w$), $x$ is the independent variable (height $h$), $a$ is the slope, and $b$ is the y - intercept. The formulas for $a$ and $b$ are:
where $n$ is the number of data points, $\bar{x}=\frac{1}{n}\sum_{i = 1}^{n}x_i$ and $\bar{y}=\frac{1}{n}\sum_{i = 1}^{n}y_i$.
Let $x$ be the height and $y$ be the weight. Here, $n = 10$.
Step2: Calculate $\sum_{i = 1}^{n}x_i$, $\sum_{i = 1}^{n}y_i$, $\sum_{i = 1}^{n}x_i^{2}$, $\sum_{i = 1}^{n}x_iy_i$
\(\sum_{i = 1}^{10}x_i=66 + 70+78+74+64+67+72+71+69+67 = 708\)
\(\sum_{i = 1}^{10}y_i=120 + 160+220+165+125+165+180+185+175+145 = 1640\)
\(\sum_{i = 1}^{10}x_i^{2}=66^{2}+70^{2}+78^{2}+74^{2}+64^{2}+67^{2}+72^{2}+71^{2}+69^{2}+67^{2}\)
\(\sum_{i = 1}^{10}x_iy_i=66\times120 + 70\times160+78\times220+74\times165+64\times125+67\times165+72\times180+71\times185+69\times175+67\times145\)
Step3: Calculate $\bar{x}$ and $\bar{y}$
\(\bar{x}=\frac{\sum_{i = 1}^{10}x_i}{10}=\frac{708}{10}=70.8\)
\(\bar{y}=\frac{\sum_{i = 1}^{10}y_i}{10}=\frac{1640}{10}=164\)
Step4: Calculate the slope $a$
Step5: Calculate the y - intercept $b$
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$w(h)=0.6h + 121.5$