Complete Question:
The mean life of a large shipment of CFLs is equal to 7,500 hours. The population standard deviation is 1,000 hours. A random sample of 64 CFLs indicate a sample life of 7,250 hours.
1. State the Null and Alternative Hypothesis.
2. At the 0.05 level of significance, is there evidence that mean life is different from 7,500 hours.
3. Construct a 95% confidence interval estimate of the population mean life of the CFLs.
4. Compute the p-value and interpret its meaning.
Answer:
-2, (7005, 7450), 0.045
Explanation:
1).
H₀: mean of life shipment is 7500 hours
the hypothesis are outlined as follows
H₀:
7500
H₁:
7500
where, n = 64, x = 7250,
1000 hours
Test statistics:

Our conclusion from the above result is that there is sufficient evidence to say that the mean life is different from 7500 hours
2). 95% confidence Interval for the population mean
is
![[7250-1.96\times \frac{1000}{\sqrt{64}},7250+1.96\times \frac{1000}{\sqrt{64}} ]\\\\(7005,7495)](https://tex.z-dn.net/?f=%5B7250-1.96%5Ctimes%20%5Cfrac%7B1000%7D%7B%5Csqrt%7B64%7D%7D%2C7250%2B1.96%5Ctimes%20%5Cfrac%7B1000%7D%7B%5Csqrt%7B64%7D%7D%20%5D%5C%5C%5C%5C%287005%2C7495%29)
3).
the p-value is given by

Based on the calculations, a good approximation for x when f(x) = 30 is equal to: B. 20.
<h3>How to write the equation?</h3>
Based on complete information, the equation for the line of best fit for the set of values in the table is given by this function below:
f(x) ≈ 1.8x - 5.4
Thus, a good approximation for x when f(x) = 30 would be determine by substituting the value of f(x) with 30 as follows:
30 = 1.8x - 5.4
30 + 5.4 = 1.8x
35.4 = 1.8x
x = 35.4/1.8
x = 20.
Read more on line of best fit here: brainly.com/question/4674926
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<u>Complete Question:</u>
The equation for the line of best fit is f(x) ≈ 1.8x − 5.4 for the set of values in the table. Using the equation for the line of best fit, what is a good approximation for x when f(x) = 30?
A. 14
B. 20
C. 45
D. 54
The earth spins and rotates on it axis and it will take 2 years to do a full Rotation (I think)