6. On page 3 of chapter 4 there is a discrete probability histogram. On this graph, what are the exact values that count as the edges for the discrete random variable x = 10? O The bar is from 9.8 to 10.2 O The bar is from 9.5 to 10.5. O The bar is from 10 to 11. O The bar is from 9 to 10.
6. On page 3 of chapter 4 there is a discrete probability histogram. On this graph, what are the exact values that count as the edges for the discrete random variable x = 10? O The bar is from 9.8 to 10.2 O The bar is from 9.5 to 10.5. O The bar is from 10 to 11. O The bar is from 9 to 10.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Hi, I added the imagine that the question is referring to. Thanks
![P(x)
0.16
0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00
6
8
10
12
14
o² = Var(x) = Σ x² · P(x) − µ²
16
The probability histogram above is for successes out of a sample of size n = 20.
The probabilities that n is 0, 1, 2, 18, 19, or 20, are each so low that they do not even show
up as bars on the graph. But there is a measurable probability for each that is just very
small.
Any discrete probability distribution table can be converted to a histogram.
μ = E(x) = [x · P(x)
3
18
We can use these histograms to check for skewdness and bell-curve shapes as in earlier
chapters.
Whenever the distribution is symmetric and bell-curves, then it is possible and useful to
compute the mean, standard deviation, and variance of a random variable. We do this using
the probability distribution.
The mean of the random variable is a population mean since it comes from exact
probabilities, and not from sample data. Thus it is often called an expected value.
DEFINITION:
Mean, Variance, and Standard Deviation of a Discrete Probability Distribution
20
J =
x
√Σx²
x². P(x) - μ²](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F85f92341-048d-46df-8884-f7af099bbb6d%2F45b0aeaa-2448-43b4-9e0b-674cfc8a3dd2%2F5hn5zx_processed.png&w=3840&q=75)
Transcribed Image Text:P(x)
0.16
0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00
6
8
10
12
14
o² = Var(x) = Σ x² · P(x) − µ²
16
The probability histogram above is for successes out of a sample of size n = 20.
The probabilities that n is 0, 1, 2, 18, 19, or 20, are each so low that they do not even show
up as bars on the graph. But there is a measurable probability for each that is just very
small.
Any discrete probability distribution table can be converted to a histogram.
μ = E(x) = [x · P(x)
3
18
We can use these histograms to check for skewdness and bell-curve shapes as in earlier
chapters.
Whenever the distribution is symmetric and bell-curves, then it is possible and useful to
compute the mean, standard deviation, and variance of a random variable. We do this using
the probability distribution.
The mean of the random variable is a population mean since it comes from exact
probabilities, and not from sample data. Thus it is often called an expected value.
DEFINITION:
Mean, Variance, and Standard Deviation of a Discrete Probability Distribution
20
J =
x
√Σx²
x². P(x) - μ²
![6. On page 3 of chapter 4 there is a discrete probability
histogram. On this graph, what are the exact values that count
as the edges for the discrete random variable x = 10?
O The bar is from 9.8 to 10.2
O The bar is from 9.5 to 10.5.
O The bar is from 10 to 11.
The bar is from 9 to 10.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F85f92341-048d-46df-8884-f7af099bbb6d%2F45b0aeaa-2448-43b4-9e0b-674cfc8a3dd2%2Ff4aeuq7_processed.png&w=3840&q=75)
Transcribed Image Text:6. On page 3 of chapter 4 there is a discrete probability
histogram. On this graph, what are the exact values that count
as the edges for the discrete random variable x = 10?
O The bar is from 9.8 to 10.2
O The bar is from 9.5 to 10.5.
O The bar is from 10 to 11.
The bar is from 9 to 10.
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