When we look at this thing for the first time, it looks like it's going to be a dog of a bear to solve, because 'q' is buried inside a squared term and a cubed term.
But this is why it's so important to learn that in math, you DON't immediately ignite your hair and go running around in circles as soon as you see the problem. The first thing you have to do <u>every</u> time is sit still, look at the problem, breathe air, and switch your brain into the 'ON' position.
Look at that big ugly fraction in the equation. Can it be simplified ? You betcha it can ! The quantity (q+r) is a factor of the numerator and denominator, so we can do some canceling.
Divide the top and the bottom of the fraction by (q+r)², and then the problem says . . .
<em>p = (q+r)/12 + 4r</em>
which is MUCH easier to unravel and solve for 'q' . Let's do this !
p = (q+r)/12 + 4r
Subtract (q+r)/12 from each side . . . p - (q+r)/12 = 4r
Subtract 'p' from each side . . . -(q+r)/12 = 4r - p
Multiply each side by -1 . . . (q+r)/12 = p - 4r
Multiply each side by 12 . . . (q+r) = 12p - 48r
Subtract 'r' from each side . . . <em>q = 12p - 49r</em>
Answer: The letter R is at the coordinate position (-2, 3).
Step-by-step explanation:
The answer is A! Hoped I was able to help you out !bjjucyuvvhhhhhhhhhuuu
We have the sample size, sample mean and the sample standard deviation. Since the population standard deviation is not know, we will use t-distribution to find the confidence interval.
The critical t value for 95% confidence interval and 63 degrees of freedom is 1.998.
The 95% confidence for the population mean will be:
Thus, the 95% confidence interval for the population mean will be (115,123)
So, option A is the correct answer
Answer:
a) strong negative linear correlation.
b) Weak or no linear correlation.
c) strong positive linear correlation.
Step-by-step explanation:
The correlation coefficient r measures the strength and direction (positive or negative) of two variables. The correlation coefficient r is always between -1 and 1. When the coefficient r is negative then the direction of the correlation is downhill (negative) and when it's positive then it's an uphill correlation (positive). Similarly, as the coefficient is closer to -1 or 1 the correlation is stronger, with zero being a non linear relationship.
Now back to the question:
a) Near -1: as we said before, this means an strong negative (-1) linear correlation.
b) Near 0: weak or no linear correlation (we cannot say if its positive or negative because we don't know it it's near zero from the right (positive numbers) or the left (negative numbers)
c) Near 1: strong positive (close to +1) linear correlation
