Whata re the answers that i can oick from
Answer:
74.86% probability that a component is at least 12 centimeters long.
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 problem, we have that:

Variance is 9.
The standard deviation is the square root of the variance.
So

Calculate the probability that a component is at least 12 centimeters long.
This is 1 subtracted by the pvalue of Z when X = 12. So



has a pvalue of 0.2514.
1-0.2514 = 0.7486
74.86% probability that a component is at least 12 centimeters long.
Answer in fraction form is 1/3
Answer in decimal form is 0.3333
Pick one answer only.
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Explanation:
The sample space is the set of all possible outcomes. In this case, the outcomes consist of values between 1 and 6
S = sample space
S = {1,2,3,4,5,6}
There are 6 items here. Let B = 6.
We want to roll a number greater than 4, so the event space we're after is
E = {5,6}
which consists of 2 items. Let A = 2.
The probability we want is A/B = 2/6 = 1/3 = 0.3333
So if you go with the fraction option, then you'll type in 1/3
If you go with the decimal option, then you'll type in 0.3333
Answer:
x^2+x+1
Step-by-step explanation:
(3x^2+4x−1)+(−2x^2−3x+2)
Combine like terms
3x^2-2x^2+4x-3x-1+2
x^2+x+1
We can plot this data on MS Excel and determine the distribution of these data reflected on the graph. Among these numbers, 50 is the outlier since it is very far from the other numbers ranging from 76 to 83. We can perform interquartile range to determine or verify the outliers in the data set. In this respect, we can see that there is not much distribution seen. The average of all data sets is equal to 96.25. When the outlier (50) is removed, we expect the mean to become higher since a low number was ommitted including high numbers only. Outliers are obtained from special causations such as human errors.