m • (g4c - 3)
(1):g4 was replaced by g^4.
Pulling out like terms:
2.1:Pull out like factors:
g4cm - 3m = m • (g4c - 3)
Trying to factor as a Difference of Squares :
2.2:Factoring: g4c - 3
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!
Answer: the answer is rational number 0.375
Step-by-step explanation:
:D trust me it’s correct
Lynn mixes 39 pounds of water with 48 pounds of brick dust, so the mixture has a total weight of 39 + 48 = 87 pounds.
13 pounds are spilled during mixing, so she's left with 87 - 13 = 74 pounds to turn into bricks.
7 pounds are needed for 1 brick, so she can make 10 bricks because 7 • 10 = 70 and 7 • 11 = 77, and 70 < 74 < 77.
If she uses the mixture to make 10 bricks, she uses up 70 pounds of it, which leaves 4 pounds to be washed out.