Complete question is;
The abc battery company claims that their batteries last 100 hours, on average. You decide to conduct a test to see if the company's claim is true. You believe that the mean life may be different from the 100 hours the company claims. you decide to collect data on the average battery life (in hours) of a random sample of n = 20 batteries. some of the information related to the hypothesis test is presented below:
Test of H0: μ = 100 versus H1: μ ≠ 100
Sample mean: 98.5
Std error of mean: 0.777
Assuming the life length of batteries is normally distributed, what is the p-value associated with this test?
Answer:
p-value = 0.00001
Explanation:
We are given;
Null hypothesis; H0: μ = 100
Alternative Hypothesis; H1: μ ≠ 100
Sample mean: x = 98.5
Standard error of mean; s = 0.777
To find the test statistic, we will use the formula;
t = (x - μ)/(s/√n)
t = (98.5 - 100)/(0.777/√20)
t = -1.5/0.1737
t = -8.64
Now, from online p-value from t-score calculator attached, using t = -8.64; DF = n - 1 = 20 - 1 = 19; two tail distribution;significance level of 0.05; we have;
The p-value = 0.00001
Answer:
its surface temperature = 54.84 ° C
Explanation:
The density of aluminium = 2700 kg/m ³
Heat capacity = 897 J/Kg.K
radius of the sphere (r) = 0.081029 m
= 25 °C
= 124.978 °C
time (t) = 767.276 s
Using the formula :
where.
Replacing our values ;we have:
T ≅ 54.84 ° C
Therefore, its surface temperature = 54.84 ° C
I believe it would be due to the weight and/or friction.
Answer:
a
b
c
Explanation:
From the question we are told that
The Young modulus is
The length is
The area is
Generally the force acting on the tibia is mathematically represented as
derived from young modulus equation
Now this force can also be mathematically represented as
So
substituting values
Since the tibia support half the weight then the force experienced by the tibia is
From the above equation the extension (compression) is mathematically represented as
substituting values
From the above equation the maximum force is
Answer and Explanation:
The computation of the object distance related to two quantities is shown below:
It could find out by using the lens formula which is shown below:
where,
v = image distance
u = object distance
f = focal length
It could be found by applying the above formula i.e considering the image distance, object distance and the focal length