Probability Question - Pls verify my answer

In summary, a binomial probability distribution with p=0.20 and n=100 has a mean of 20 and standard deviation of 4. We can approximate binomial probabilities by using the normal distribution. The probability of more than 24 successes is 0.1292 and the probability of 18 to 22 successes is 0.383. However, this is the probability of P(-.5<=Z<=.5) so we need to double it to get the actual probability of P(18<=X<=22).
  • #1
ORACLE
12
0
hi,
pls comment on my solution.
thanks.


Question

A binomial probability distribution has p= 0.20 and n = 100.
a)What is the mean and standard deviation?
b)Can you approximate these Binomial probabilities by the normal probabilities? Explain.
c)What is the probability of more than 24 successes?
d)What is the probability of 18 to 22 successes?

Answers

a.) The formula to calculate the mean of Binomial Probability Distribution is
μ = n.p
= 100 X .2
= 20

The formula to calculate the Standard Deviation of a Binomial Probability Distribution is
σ = √np.(1-p)
= √100 X .2 X .8
= 4

b.) Since the binomial distribution approaches the normal distribution as the number of trials increases, we can use the normal distribution to approximate binomial probabilities. These values will all be approximations; we could use the binomial probability to obtain the actual answers, but in some cases these probabilities are difficult to calculate by hand.
We can use the standard normal distribution with the following conversion formula: Z = (X - np)/ sqrt(npq)

c.) Probability of more than 24 successes can be phrased as
P(X>24)
Z value of X = (X - μ)/ σ
= (24.5 – 20)/4
= 1.125 ~ 1.13
= 0.3708
.3708 is the probability between the mean (20) and 24.
P(X>24) = 0.5 - .3708 = 0.1292

d.) Probability of 18 to 22 successes can be formulated as
P(18<=X<=22)
Z value= (X - μ)/ σ
= (22 – 20)/4
= .5
P(22) = 0.1915
P(18)= (18 – 20)/4
= -.5
Z Value= 1 – 0.1915
= 0.8085
Therefore P(18<=X<=22) = P(22)+ P(18)
= .1915 + 8085
= 1
 
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  • #2
There's a definite problem with the last answer.
 
  • #3
hi mystic998

can you explain a bit about the problem.

thanks
 
  • #4
The number you have pulled out of a table 0.1915 represents the probability that the variable falls between Z=0 and Z=0.5. So the probability that it falls between Z=-0.5 and Z=0 is also 0.1915, since the normal distribution is symmetric (NOT 1-0.1915). You just need to practice using your table.
 
  • #5
ORACLE said:
hi,
pls comment on my solution.
thanks.


Question

A binomial probability distribution has p= 0.20 and n = 100.
a)What is the mean and standard deviation?
b)Can you approximate these Binomial probabilities by the normal probabilities? Explain.
c)What is the probability of more than 24 successes?
d)What is the probability of 18 to 22 successes?

Answers

a.) The formula to calculate the mean of Binomial Probability Distribution is
μ = n.p
= 100 X .2
= 20

The formula to calculate the Standard Deviation of a Binomial Probability Distribution is
σ = √np.(1-p)
= √100 X .2 X .8
= 4

b.) Since the binomial distribution approaches the normal distribution as the number of trials increases, we can use the normal distribution to approximate binomial probabilities. These values will all be approximations; we could use the binomial probability to obtain the actual answers, but in some cases these probabilities are difficult to calculate by hand.
We can use the standard normal distribution with the following conversion formula: Z = (X - np)/ sqrt(npq)

c.) Probability of more than 24 successes can be phrased as
P(X>24)
Z value of X = (X - μ)/ σ
= (24.5 – 20)/4
= 1.125 ~ 1.13
= 0.3708
.3708 is the probability between the mean (20) and 24.
P(X>24) = 0.5 - .3708 = 0.1292

d.) Probability of 18 to 22 successes can be formulated as
P(18<=X<=22)
Z value= (X - μ)/ σ
= (22 – 20)/4
= .5
P(22) = 0.1915
P(18)= (18 – 20)/4
= -.5
Z Value= 1 – 0.1915
First, it is not P(18) that is (18- 20)/4, it is the z-value. You are looking for P(-.5). Most importantly, that is not "1- P(5)". I assume your table has only Z> 0 so you are using the symmetry of the normal distribution to get P for negative values. Your mistake is that P(0)= 1/2, not 1. P(-.5)= 1/2- P(.5).

= 0.8085
Therefore P(18<=X<=22) = P(22)+ P(18)
= .1915 + 8085
= 1
Yes, if you calculate P(18) as 1- P(22) then their sum is P(22)+ 1- P(22)= 1!:rofl:
Even with the correct calculation, that P(18)= .5- P(22), their sum would be P(22)+ .5- P(22)= .5. P(18<=X<= 22)= P(22)- P(18), not the sum.
 
  • #6
hi prof,

thanks. but now i get a -ve probability. what does it mean?
pls help.

P(18<=X<=22) = P(22) – P(18)
= .1915 - .3085
= -0.117
 
  • #7
Sorry, I should have recognized that if your table is giving you P(.5)= .1915, then it is giving you P(0<= Z<= .5). The probability of P(-infinity<= Z<= 0)= 0.5 itself so P(-infinity<= Z<= .5) is .5+ .1915= .6915. Then P(-infinity<= Z<= -.5) is, as I said, 1/2- .1915= .3085. P(-.5<= Z<= .5)= .6915- .3085= .383. If you look at that closely, you will see that .383= 2(.1915). Remember that the probability is the "area under the normal curve" and the normal curve is symmetric! The area from -.5 to .5 is just twice the area from 0 to .5.
 
  • #8
thank you prof
 

1. What is probability?

Probability is a measure of the likelihood that a certain event will occur. It is expressed as a number between 0 and 1, where 0 represents impossibility and 1 represents certainty.

2. How is probability calculated?

The probability of an event is calculated by dividing the number of favorable outcomes by the total number of possible outcomes. This can be represented as a fraction, decimal, or percentage.

3. What is the difference between theoretical and experimental probability?

Theoretical probability is based on mathematical calculations and assumes that all outcomes are equally likely. Experimental probability is based on actual outcomes from an experiment or real-life situation.

4. What is the difference between independent and dependent events?

Independent events are events that do not affect each other's outcomes. The outcome of one event does not influence the outcome of the other. Dependent events, on the other hand, are events that do affect each other's outcomes. The outcome of one event can impact the outcome of the other.

5. How can probability be used in real life?

Probability is used in many real-life situations, such as predicting the weather, analyzing risk in insurance and finance, and understanding the likelihood of certain outcomes in games or sports. It is also used in scientific research to determine the likelihood of certain outcomes in experiments.

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