Write an equation of the line in slope-intercept form.
1 answer:
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Answer:
Step-by-step explanation:
1) The null hypothesis is,
H_0: The mean thickness of teh wafers for the five positions are equal
i.e,
2)
The alternative hypothesis is,
H_1: There is an evidence of a difference in the mean thickness of the wafers for the five positions
3)
Let us consider the level of significance
from the Minitab outout
One-way ANOVA:C1 versus C2
source DF SS MS F P
C2 4 1417.73 354.43 51.00 0.00
Error 145 1007.77 6.95
Total 14 2425.50
S = 2.636 R - S = 58.45% R - Sq(adj) = 57.31%
Individual 95% CIs For Mean Based on Pooled StDev
level N Mean StDev -,----------,----------,----------,----------
1 30 240.53 2.62 (--,--)
2 30 243.73 2.79 (--,--)
3 30 246.07 2.90 (--,--)
4 30 249.10 2.66 (--,--)
5 30 247.07 2.15 (--,--)
-,----------,----------,----------,----------
240.0 243.0 246.0 249.0
Pooled StDev = 2.64
4)
The test statistic is, F = 51
5)
The P-value is approximately 0
6)
Here, the P - value is less than the level of significance
So, we do not accept our null hypothesis H_0
7)
Therefore, we conclude that there is an evidence of a difference in the mean thickness of the wafers for the five positions at level of significance
b)
chek attachment
we observe that,
The mean thickness of the wafer for position 1 is significant with position 2,
position 18, position 19 and position 28.
The mean thickness of the wafer for position 2 is significant with position 18,
position 19 and position 28.
The mean thickness of the wafer for position 18 is significant with the
position 19.
But the mean thickness of the wafer for position18 is not significant with
position 28.
The mean thickness of the wafer for position 19 is significant with position 28.
Answer:
0.6826 = 68.26% probability Z will be within one standard deviation of average.
Step-by-step explanation:
Normal Probability Distribution
Problems of normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation
, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.
What is the probability Z will be within one standard deviation of average?
This is the p-value of Z = 1 subtracted by the p-value of Z = -1.
Z = 1 has a p-value of 0.8413.
Z = -1 has a p-value of 0.1587.
0.8413 - 0.1587 = 0.6826
0.6826 = 68.26% probability Z will be within one standard deviation of average.