<h2>Explanation:</h2><h2></h2>
The diagram is missing but I'll assume that the arc BDC is:
And another arc, let's call it FGH. measures:
If those arc are equal, then this equation is true:
Substituting k into the first equation:
Billy’s employer pays for 65% of his annual health insurance premium. Billy has the rest deducted in equal amounts from his payc
2 answers:
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Answer:
3
Step-by-step explanation:
Given:
Team heights (inches):
61, 57, 63, 62, 60, 64, 60, 62, 63
To find: IQRs (interquartile ranges) of the heights for the team
Solution:
A quartile divides the number of terms in the data into four more or less equal parts that is quarters.
For a set of data, a number for which 25% of the data is less than that number is known as the first quartile
For a set of data, a number for which 75% of the data is less than that number is known as the third quartile
Terms in arranged in ascending order:
Number of terms = 9
As number of terms is odd, exclude the middle term that is 62.
is median of terms
Number of terms (n) = 4
Median =
So,
So, 25% of the heights of a team is less than 60 inches
is the median of terms
Median =
So,
So, 75% of the heights of a team is less than 63 inches
Interquartile range =
The interquartile range is a measure of variability on dividing a data set into quartiles.
The interquartile range is the range of the middle 50% of the terms in the data.
So, 3 is the range of the middle 50% of the heights of the students.
Answer:
a)From the central limit theorem we know that the distribution for the sample mean is given by:
And the standard error for the mean would be:
b) We want this probability:
And we can use the z score formula given by:
And replacing we got:
And we can find this probability with the complement rule and the normal standard deviation or excel and we got:
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
Solution to the problem
Part a
From the central limit theorem we know that the distribution for the sample mean is given by:
And the standard error for the mean would be:
Part b
We want this probability:
And we can use the z score formula given by:
And replacing we got:
And we can find this probability with the complement rule and the normal standard deviation or excel and we got:
Answer: The answer is ounces.
Step-by-step explanation: Given in the question the weight of Jarrett's puppy at birth, one week old and 2 weeks old are as follows:
We can see that
So, the weight of the baby will make an arithmetic progression with first term 'a' and common difference 'd' as follows:
Thus, the weight of the puupy after 3 weeks will be