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.
The perimeter of the polygon will be given by:
Perimeter=distance around the figure
Thus the perimeter will be:
P=9.9+(9.9-5.9)+5.9+15.9+(15.9-4.6)+4.6
P=9.9+4+5.9+15.9+11.3+4.6
P=51.6
Answer: 51.6 units
Answer:
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Step-by-step explanation:
