Probability & Central Limit Theorem

In summary: In the first case you would have (12,749- (12,752/1.2√35)≈ 12,749- 2.0323≈ 12,746. In the second case you would have (12,749- 12,752)/1.2≈ -3/1.2= -2.5. In either case that is not "unusual".
  • #1
rihnavy
3
0
The population mean and standard deviation are given below. Find the required probability and determine whether the given sample mean would be considered unusual.
μx̄ = μ = 12,749
σ = 1.2
n = 35

For the given sample n = 35, the probability of a sample mean being less than 12,749 or greater than 12,752 is ____________

 
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  • #2
Hello rihnavy :D

We ask that our users show their progress (work thus far or thoughts on how to begin) when posting questions. This way our helpers can see where you are stuck or may be going astray and will be able to post the best help possible without potentially making a suggestion which you have already tried, which would waste your time and that of the helper.

Can you post what you have done so far?
 
  • #3
This is what I have so far.
σx = σ/ √n = 1.2/ √35 = 0.2028

z = x̄ - μx̄/σx = x̄ - μx̄/σ/√n = 12,749 - 12,752/ 1.2√35 = -0.4226 = .33724

I stopped right there because I got confused. I'm stuck.
OTE=greg1313;90547]Hello rihnavy :D

We ask that our users show their progress (work thus far or thoughts on how to begin) when posting questions. This way our helpers can see where you are stuck or may be going astray and will be able to post the best help possible without potentially making a suggestion which you have already tried, which would waste your time and that of the helper.

Can you post what you have done so far?[/QUOTE]
 
  • #4
rihnavy said:
This is what I have so far.
σx = σ/ √n = 1.2/ √35 = 0.2028

z = x̄ - μx̄/σx = x̄ - μx̄/σ/√n = 12,749 - 12,752/ 1.2√35 = -0.4226 = .33724

Do you mean 12,749- (12,752/1.2√35) (which is what you wrote means) or do you really mean
(12,749- 12,752)/1.2√35?

I stopped right there because I got confused. I'm stuck.
Could you not at least do that arithmetic? Do you not have a table of the Normal distribution or an app that gives them?
 

FAQ: Probability & Central Limit Theorem

What is probability?

Probability is a measure of the likelihood of an event occurring. It is expressed as a number between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.

What is the Central Limit Theorem?

The Central Limit Theorem is a fundamental concept in statistics that states that the distribution of sample means from a population will approximate a normal distribution as the sample size increases, regardless of the shape of the population's distribution. This allows us to make inferences about a population using sample data.

How is probability related to the Central Limit Theorem?

The Central Limit Theorem relies on the concept of probability, as it uses the probability distribution of a population to make predictions about the distribution of sample means. It also allows us to calculate the probability of obtaining a particular sample mean from a population.

How is the Central Limit Theorem applied in real-world situations?

The Central Limit Theorem has many practical applications in fields such as finance, psychology, and biology. It is used to analyze and draw conclusions from data collected through experiments or surveys, and to make predictions about a population based on a sample. It is also used in quality control processes to ensure that products meet certain standards.

What are the limitations of the Central Limit Theorem?

While the Central Limit Theorem is a powerful tool in statistics, it does have some limitations. It assumes that the sample is randomly selected from a population and that the sample size is large enough to accurately represent the population. Additionally, it may not apply to populations with extremely skewed distributions or to data that is not independent.

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