Answer:
Follows are the solution to this question:
Step-by-step explanation:
- It is true because the square of the standard error of its estimate was its total square error divided only by the degree of freedom.
- It is true because Its coefficient with Standardized Regression, beta, will have the same value as r, the approximate similarity.
- It is false because Its slope b, of its equation of regression, will have the same value as r, the projected correlation.
To find the least common denominator, or lcd, you have to find the least common multiple, or lcm. To do that you find the multiples of each number until they equal each other. I set up a chart like this,
6 -
8 -
and then I start listing multiples so,
6 - 6, 12, 18, 24,
8 - 8, 16, 24,
I stop after I find a number they are both equal to. So to get to that number I would multiply 8 by 3, and 6 by 4. This gives me 24 as the lcd. If you need the lcd to add the fractions together, then whatever you did to the bottom do to the top. So 5/6 would become 20/24 and 3/8 would become 9/24.
Answer: 24
<h3>
Answer: -6</h3>
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Explanation:
Plug in x = 1
f(x) = 17-x^2
f(1) = 17-1^2
f(1) = 17-1
f(1) = 16
Repeat for x = 5 to find that f(5) = -8
Now we'll use the formula below to find the average rate of change from x = a to x = b.
The average rate of change is -6
The formula is basically the slope formula, more or less. So that's why I used 'm' to represent the average rate of change.
The average rate of change on the interval [1,5] is the same as finding the slope through the lines (1, 16) and (5, -8)
Starting from
take the first derivative using the power and chain rules:
Now take the second derivative:
Optionally, you can condense the second derivative a bit by factoring out 
, which gives
