<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>
Answer:
Okays so for 100 guests we can make the equation $5000 ÷ 100 = $50.00
For 100 guests at the wedding it would cost <u>$50.00</u> per plate
For 45 guests we can make the equation $2750 ÷ 45 = $61.111111111111, it would be a repeating decimal
For 45 guests at the wedding, it would cost <u>$61.111111111111</u>
I hope that this can help you! ^‿^
The output is -20 to this question
Answer:
See below
Step-by-step explanation:
In the second step there should be (1 - cot x) instead of (1 + cot x)
(1 + tan x) [1 + cot(-x)]
= (1 + tan x) (1 - cot x)
= 1 - cot x + tan x - tan x cot x
= 1 - cot x + tan x - 1
= tan x - cot x
Answer:
n=601
Step-by-step explanation:
A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".
The margin of error is the range of values below and above the sample statistic in a confidence interval.
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The population proportion have the following distribution
In order to find the critical value we need to take in count that we are finding the interval for a proportion, so on this case we need to use the z distribution. Since our interval is at 95% of confidence, our significance level would be given by
and
. And the critical value would be given by:
The confidence interval for the mean is given by the following formula:
The margin of error for the proportion interval is given by this formula:
(a)
And on this case we have that
and we are interested in order to find the value of n, if we solve n from equation (a) we got:
(b)
Since we don't have a prior estimation for the proportion we can use 0.5 as estimation. And replacing into equation (b) the values from part a we got:
And rounded up we have that n=601