A number to the 12th power divided by the same number to the 9th power equals 125 what is the number
1 answer:
You might be interested in
Answer:
Option C
Step-by-step explanation:
Given that for a random sample of 20 houses selected from a city showed that the mean size of these houses is 1880 square feet with a standard deviation of 320 square feet.
X, the sizes of houses is Normal
Hence sample mean will be normal with
Mean = 1880
and std dev =
For 90% confidence interval critical value for t with degree of freedom 19 is
1.328
Confidence interval upper bound
= mean + margin of error
=
Option C is right
Answer:
The standard deviation is of 8.586.
Step-by-step explanation:
For each person, there are only two possible outcomes. Either they have a genetic mutation, or they do not. The probability of a person having the mutation is independent of any other person, which means that the binomial probability distribution is used to solve this question.
Binomial probability distribution
Probability of exactly x successes on n repeated trials, with p probability.
The standard deviation of the binomial distribution is:
About 9% of the population has a particular genetic mutation.
This means that
900 people are randomly selected.
This means that
Find the standard deviation for the number of people with the genetic mutation in such groups of 900.
The standard deviation is of 8.586.
Mean of the distribution = u = 222
Standard Deviation = s = 16
We have to find the probability that a value lies between 190 and 230.
First we need to convert these data values to z score.
For x = 190,
For x = 230
So, we have to find the percentage of values lying between z score of -2 and 0.5
P( -2 < z < 0.5) = P(0.5) - P(-2)
From standard z table, we can find and use these values.
P(-2 < x < 0.5 ) = 0.6915 - 0.0228 = 0.6687
Thus, there is 0.6887 probability that the data value will lie between 190 and 230 for the given distribution.
Standard Deviation = s = 16
We have to find the probability that a value lies between 190 and 230.
First we need to convert these data values to z score.
For x = 190,
For x = 230
So, we have to find the percentage of values lying between z score of -2 and 0.5
P( -2 < z < 0.5) = P(0.5) - P(-2)
From standard z table, we can find and use these values.
P(-2 < x < 0.5 ) = 0.6915 - 0.0228 = 0.6687
Thus, there is 0.6887 probability that the data value will lie between 190 and 230 for the given distribution.