Very hard distribution question

In summary, we have a school psychologist who found that the results of a third school closely fit a normal distribution with a mean completion time of 20.68 minutes and a standard deviation of 5.3 minutes. They are looking at a range of observed frequencies falling between 14.5 and 19.5 minutes. With 125 students and a 10% percentage error, the possible range of values for the observed frequencies is between 112.5 and 137.5.
  • #1
Sirsh
267
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The school psychologist was researching the results of a third school and found them to closely fit a normal distribution with a mean completion time of 20.68 minutes and a standard deviation of 5.3 minutes. Unfortuantly, after he had finished calculating the results, he could not read of of the observed values.

Given there are 125students at the school, and a percentage error of ten percent determine the possible range of values for the observed frequencies, falling between 14.5 and the 19.5 minute interval.

Equations:

z(standardised score) = (x-mean/standard dev)
Percentage error = |o-e|/total frequency * 100.


I have no clue.. please help me!
 
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  • #2


Hi there,

I am happy to help you with this problem. Let's break it down step by step.

First, let's define some variables:
- n = total number of students (125)
- m = mean completion time (20.68 minutes)
- s = standard deviation (5.3 minutes)
- p = percentage error (10%)

We know that the range of observed frequencies should fall between the 14.5 and 19.5 minute intervals. Let's convert these values to standardised scores using the formula: z = (x-m)/s

For the lower end of the range (14.5 minutes), we have z = (14.5-20.68)/5.3 = -1.16
For the upper end of the range (19.5 minutes), we have z = (19.5-20.68)/5.3 = -0.22

Next, let's use the formula for percentage error to determine the range of possible values for the observed frequencies. Rearranging the formula, we get:
|o-e| = p/100 * n
where o is the observed frequency and e is the expected frequency.

For the lower end of the range, we have:
|o-125| = 10/100 * 125 = 12.5
This means that the observed frequency could be anywhere between 125-12.5 = 112.5 and 125+12.5 = 137.5.

For the upper end of the range, we have:
|o-125| = 10/100 * 125 = 12.5
This means that the observed frequency could be anywhere between 125-12.5 = 112.5 and 125+12.5 = 137.5.

Therefore, the possible range of values for the observed frequencies falling between the 14.5 and 19.5 minute intervals is 112.5 to 137.5.

I hope this helps you understand the problem better. Let me know if you have any other questions. Good luck with your research!
 

Related to Very hard distribution question

1. What is a very hard distribution question?

A very hard distribution question is a type of statistical problem that involves finding the probability or frequency of an event or outcome in a complex or unusual distribution. These types of questions often require advanced mathematical and statistical techniques to solve.

2. How do you approach a very hard distribution question?

When faced with a very hard distribution question, the first step is to carefully read and understand the problem. Then, you can use your knowledge of statistics and probability to identify the appropriate techniques or formulas to use. It may also be helpful to break the problem down into smaller, more manageable parts.

3. What are some common challenges when solving a very hard distribution question?

One of the main challenges in solving a very hard distribution question is understanding the problem and identifying the appropriate techniques to use. These types of questions can also be time-consuming and require a lot of critical thinking and problem-solving skills.

4. Are there any tips for solving a very hard distribution question?

Some tips for solving a very hard distribution question include breaking the problem down into smaller parts, using diagrams or visual aids to help understand the problem, and double-checking your work to ensure accuracy. It can also be helpful to consult with other experts or resources for guidance.

5. What are some real-life examples of very hard distribution questions?

Real-life examples of very hard distribution questions can include predicting the stock market, determining the likelihood of rare medical conditions, or estimating the probability of winning a lottery. These types of questions often require advanced statistical models and data analysis techniques to solve accurately.

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