Answer:
a) The third quartile Q₃ = 56.45
b) The variance = 2633.31
Step-by-step explanation:
a) The coefficient of skewness formula is given as follows;
![SK = \dfrac{Q_{3}+Q_{1}-2Q_{_{2}}}{Q_{3}-Q_{1}}](https://tex.z-dn.net/?f=SK%20%3D%20%5Cdfrac%7BQ_%7B3%7D%2BQ_%7B1%7D-2Q_%7B_%7B2%7D%7D%7D%7BQ_%7B3%7D-Q_%7B1%7D%7D)
Plugging in the values, we have;
![-0.38 = \dfrac{Q_{3}+30.8-2 \times 48.5_{_{}}}{Q_{3}-30.8}](https://tex.z-dn.net/?f=-0.38%20%3D%20%5Cdfrac%7BQ_%7B3%7D%2B30.8-2%20%5Ctimes%2048.5_%7B_%7B%7D%7D%7D%7BQ_%7B3%7D-30.8%7D)
Solving gives Q₃ = 56.45
b) To determine the variance, we use the skewness formula as follows;
![SK_{p} = \dfrac{Mean-\left (3\times Median - 2\times Mean \right )}{\sigma } = \dfrac{3\times\left ( Mean - Median \right )}{\sigma }](https://tex.z-dn.net/?f=SK_%7Bp%7D%20%3D%20%5Cdfrac%7BMean-%5Cleft%20%283%5Ctimes%20Median%20-%202%5Ctimes%20Mean%20%20%5Cright%20%29%7D%7B%5Csigma%20%7D%20%3D%20%20%20%5Cdfrac%7B3%5Ctimes%5Cleft%20%28%20Mean%20-%20Median%20%5Cright%20%29%7D%7B%5Csigma%20%7D)
Plugging in the values, we get;
![-0.38= \dfrac{42-\left (3\times 48.5- 2\times 42\right )}{\sigma } = \dfrac{-19.5}{\sigma}](https://tex.z-dn.net/?f=-0.38%3D%20%5Cdfrac%7B42-%5Cleft%20%283%5Ctimes%2048.5-%202%5Ctimes%2042%5Cright%20%29%7D%7B%5Csigma%20%7D%20%3D%20%5Cdfrac%7B-19.5%7D%7B%5Csigma%7D)
![\therefore \sigma =\dfrac{-19.5}{-0.38} = 51.32](https://tex.z-dn.net/?f=%5Ctherefore%20%5Csigma%20%3D%5Cdfrac%7B-19.5%7D%7B-0.38%7D%20%3D%2051.32)
The variance = σ² = 51.32² = 2633.31.
the answer is 16.5
Step-by-step explanation:
Answer:
Option F ![\frac{r+5}{b}](https://tex.z-dn.net/?f=%5Cfrac%7Br%2B5%7D%7Bb%7D)
Step-by-step explanation:
we know that
The quotient of r+5 and b is equal to divide (r+5) by b
so
The numerator is equal to (r+5) and the denominator is equal to b
substitute
![\frac{r+5}{b}](https://tex.z-dn.net/?f=%5Cfrac%7Br%2B5%7D%7Bb%7D)
Answer:
(2, -4.5)
Step-by-step explanation:
Used midpoint formula
A distribution of probabilities for random outcomes of bivariate or dichotomous random variables is called (A) binomial probability distribution.
<h3>
What is a binomial probability distribution?</h3>
- The binomial distribution with parameters n and p in probability theory and statistics is the discrete probability distribution of the number of successes in a succession of n separate experiments, each asking a yes-no question and each with its own Boolean-valued outcome: success or failure.
- The binomial distribution is widely used to describe the number of successes in a sample of size n selected from a population of size N with replacement.
- If the sampling is done without replacement, the draws are not independent, and the resulting distribution is hypergeometric rather than binomial.
- Binomial probability distribution refers to a distribution of probabilities for random outcomes of bivariate or dichotomous random variables.
As the description itself says, binomial probability distribution refers to a distribution of probabilities for random outcomes of bivariate or dichotomous random variables.
Therefore, a distribution of probabilities for random outcomes of bivariate or dichotomous random variables is called (A) binomial probability distribution.
Know more about binomial probability distribution here:
brainly.com/question/9325204
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Complete question:
A distribution of probabilities for random outcomes of bivariate or dichotomous random variables is called a ______.
Group of answer choices
(A) binomial probability distribution
(B) distribution of expected values
(C) random variable distribution
(D) mathematical expectation