<span>Answer:
Multiple R is the correlation between y and y^
in a regression model. It is always non-negative, but has no nice interpretation as a proportion of variance, unlike its square. I can't think of too many uses for it and only know of one stat package that routinely reports it, SPSS.
Bivariate correlation only tells you about two variables at a time (though you can use partial correlation to remove other variables).</span>
The tangent line to <em>y</em> = <em>f(x)</em> at a point (<em>a</em>, <em>f(a)</em> ) has slope d<em>y</em>/d<em>x</em> at <em>x</em> = <em>a</em>. So first compute the derivative:
<em>y</em> = <em>x</em>² - 9<em>x</em> → d<em>y</em>/d<em>x</em> = 2<em>x</em> - 9
When <em>x</em> = 4, the function takes on a value of
<em>y</em> = 4² - 9•4 = -20
and the derivative is
d<em>y</em>/d<em>x</em> (4) = 2•4 - 9 = -1
Then use the point-slope formula to get the equation of the tangent line:
<em>y</em> - (-20) = -1 (<em>x</em> - 4)
<em>y</em> + 20 = -<em>x</em> + 4
<em>y</em> = -<em>x</em> - 24
The normal line is perpendicular to the tangent, so its slope is -1/(-1) = 1. It passes through the same point, so its equation is
<em>y</em> - (-20) = 1 (<em>x</em> - 4)
<em>y</em> + 20 = <em>x</em> - 4
<em>y</em> = <em>x</em> - 24
Every calculation with multiple operations must abide to BODMAS (Brackets, Other, Divide, Multiple, Addition, Subtraction)
Thus we would multiple first, giving us 86138220. Then we would add giving us: 86145009
