Answer:
standard error = 2.11
Step-by-step explanation:
First we stablish the data that we have for each sample:
<u>Population 1</u> <u>Population </u>2
n₁ = 100 n₂ = 90
x¯1= 95 x¯2 = 75
σ₁ = 14 σ₂ = 15
To calculate the standard error of each sample we would use the formulas:
σ = σ₁/√n₁
σx¯2 = σ₂/√n₂
Now, in order to obtain the standard error of the differences between the two sample means we combine those two formulas to obtain this:
σx¯1 - σ x¯2 = √(σ₁²/n₁ + σ₂²/n₂ )
So as you can see, we used the square root to simplify and now we require the variance of each sample (σ²):
σ₁² = (14)² = 196
σ₂² = (15)² = 225
Now we can proceed to calculate the standard error of the distribution of differences in sample means:
σx¯1 - σx¯2 = √(196/100 + 225/90) = 2.11
This gives an estimate about how far is the difference between the sample means from the actual difference between the populations means.
Answer:
40
Step-by-step explanation:
f(4) = 3(4²) - 2(4)
= 3(16) - 8
= 48 - 8
= 40
when x=4, f(x) = 40
Answer:
90.31 is greater than 90.302
Step-by-step explanation:
Answer:
Step-by-step explanation:
if you can pick any numbers you want then:
rational could be: 0.25 or 1/4
irrational could be: 2/7
Answer:
(^6√x^5) (√y)
(The 6 belongs in the left on top of the square root btw)
For x the 6 moves to the front of the square root while the 5 becomes the power of x.
For y, the power to the 1/2 is the same as a square root.
