QUESTION IMAGE
Question
the table shows the temperature of an amount of water set on a stove to boil, recorded every half minute. waiting for water to boil
| time (min) | 0 | 0.5 | 1.0 | 1.5 | 2.0 | 2.5 | 3.0 | 3.5 | 4 | 4.5 |
| temp. (°c) | 75 | 79 | 83 | 86 | 89 | 91 | 93 | 94 | 95 | 95.5 |
according to the line of best fit, at what time will the temperature reach 100°c, the boiling point of water?
o 5
o 5.5
o 6
o 6.5
Step1: Assume a linear - regression model
Let the time be $x$ (in minutes) and the temperature be $y$ (in $^{\circ}C$). We can use a linear regression formula $y = mx + b$, where $m$ is the slope and $b$ is the y - intercept. Using a calculator or software for linear regression on the given data points $(x_1,y_1),(x_2,y_2),\cdots,(x_{10},y_{10})$.
Step2: Calculate the slope and y - intercept
If we calculate the linear regression by hand (using the formulas $m=\frac{n\sum_{i = 1}^{n}x_iy_i-\sum_{i = 1}^{n}x_i\sum_{i = 1}^{n}y_i}{n\sum_{i = 1}^{n}x_i^{2}-(\sum_{i = 1}^{n}x_i)^{2}}$ and $b=\overline{y}-m\overline{x}$, where $n = 10$, $\overline{x}=\frac{\sum_{i = 1}^{n}x_i}{n}$, $\overline{y}=\frac{\sum_{i = 1}^{n}y_i}{n}$), or use a graphing utility. For simplicity, if we observe the trend:
The temperature is increasing. The change in temperature $\Delta y$ and change in time $\Delta x$:
From $x = 0,y = 75$ to $x=4.5,y = 95.5$. The average rate of change (approximate slope) $m=\frac{95.5 - 75}{4.5-0}=\frac{20.5}{4.5}\approx4.56$. The y - intercept $b = 75$. So the equation of the line is $y=4.56x + 75$.
Step3: Solve for $x$ when $y = 100$
Set $y = 100$ in the equation $y=4.56x + 75$. Then $100=4.56x + 75$.
Subtract 75 from both sides: $100 - 75=4.56x$, so $25 = 4.56x$.
Solve for $x$: $x=\frac{25}{4.56}\approx5.5$.
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