Answer:
6.5
Step-by-step explanation:
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Answer: I=sqrt(P/R)
Step-by-step explanation:
R=p/I^2
Multiple l squared on both sides...
(I^2) R=p/l^2 (l^2)
R(I^2)=p
Separate I by dividing both sides by R...
I^2=p/R
Square root both sides...
I=sqrt(P/R)
The answer to your question is 4/5
Answer:
3
Step-by-step explanation:
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Answer:
Step-by-step explanation:
Hello!
Given the linear regression of Y: "Annual salary" as a function of X: "Mean score on teaching evaluation" of a population of university professors. It is desired to study whether student evaluations are related to salaries.
The population equation line is
E(Y)= β₀ + β₁X
Using the information of a n= 100 sample, the following data was calculated:
R²= 0.23
Coefficient Standard Error
Intercept 25675.5 11393
x 5321 2119
The estimated equation is
^Y= 25675.5 + 5321X
Now if the interest is to test if the teaching evaluation affects the proffesor's annual salary, the hypotheses are:
H₀: β = 0
H₁: β ≠ 0
There are two statistic you can use to make this test, a Student's t or an ANOVA F.
Since you have information about the estimation of β you can calculate the two tailed t test using the formula:
~
= 25.1109
The p-value is two-tailed, and is the probability of getting a value as extreme as the calculated
under the distribution 
p-value < 0.00001
I hope it helps!