Answer:
0.2514 = 25.14% probability that the diameter of a selected bearing is greater than 85 millimeters.
Step-by-step explanation:
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean 
and standard deviation 
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
In this question, we have that:
Find the probability that the diameter of a selected bearing is greater than 85 millimeters.
This is 1 subtracted by the pvalue of Z when X = 85. Then
has a pvalue of 0.7486.
1 - 0.7486 = 0.2514
0.2514 = 25.14% probability that the diameter of a selected bearing is greater than 85 millimeters.
1- I didn't understand it
2).. (a/b)² (a/b)⁸
= (a/b)²+⁸ = (a/b)¹⁰
3) 3-⁵ = 1/3⁵ = 1/243
4) (x/y)"
d/dx (x/y) = (1/y)
d/dx (1/y) = 0
5) (2m⁴n³)⁵
= 2⁵ × (m⁴)⁵ × (n³)⁵
= 32 × m²⁰ × n¹⁵
= 32m²⁰n¹⁵
Answer:
3.5
Step-by-step explanation:
3.5 is the y-intercept because the point is (0,3.5). This is where it intercepts with the y-axis.
Hope it helps!
Answer:
The function a (t) is a vector function composed of the component functions 
and 
. How 
are infinitely derivable functions in R, so they are regular functions in R.
Now, for
, you have to 
. How the functions are periodic functions with period 
the vector function 
will take the same point 
at 
then the vector function is auto-intercepted
Step-by-step explanation:
Answer:
b.0.02
Step-by-step explanation:
As he defined the significance level in α=0.05, and this is a one-side test (as the claim is that the percentage is <em>higher, </em>not lower), any P-value below the significance level shows a significant effect and gives evidence to reject the null hypothesis.
The P-value represents the probability of having this sample statistic, given that the statement of the null hypothesis is true. Then, the lower the P-value, more evident is that the null hypothesis is not correct. This threshold value to reject (or not) the null hypothesis is the significance level.
a) As the significance level is 0.05, a P-value=0.07 would not be low enough to reject the null hypothesis.
c) The magnitude of a P-value has impact on whether he rejects or fails to reject the null hypothesis, as is the value that is compared to the significance level to reject or not the null hypothesis.
