The question asks for the slope ($m$) of the linear regression plot of $Y$ on $X$ given three data points: $(2, 60)$, $(4, 70)$, and $(6, 90)$.
The formula for the slope ($m$) in linear regression of $Y$ on $X$ is: $m = \frac{n(\sum XY) - (\sum X)(\sum Y)}{n(\sum X^2) - (\sum X)^2}$ where $n$ is the number of data points.
First, let's list the data points and calculate the necessary sums:
| X | Y | $X^2$ | XY | |
|---|---|---|---|---|
| 2 | 60 | 4 | 120 | |
| 4 | 70 | 16 | 280 | |
| 6 | 90 | 36 | 540 | |
| Sum | $\sum X = 12$ | $\sum Y = 220$ | $\sum X^2 = 56$ | $\sum XY = 940$ |
Now, substitute the calculated sums into the slope formula:
$m = \frac{3(940) - (12)(220)}{3(56) - (12)^2}$ $m = \frac{2820 - 2640}{168 - 144}$ $m = \frac{180}{24}$ $m = 7.5$The slope ($m$) of the linear regression plot is $7.5$.
| $x$ | 2 | 3 | 4 | 5 |
| $y$ | 8 | 9 | 7 | 16 |
| $x$ | 1 | 2 | 3 | 4 |
| $y$ | 2 | 6 | 7 | 10 |
The graph below shows a plot of annual rainfall on the X axis and number of plant species on the Y axis. Based on the pattern in the graph, which one of the following statistical methods would be most appropriate to model the relationship between annual rainfall and the number of plant species?
