Normal Distribution Homework: Expectation and Variance for Sample of 25 Students

In summary, the students of a US university have an average SAT score of 600 and a standard deviation of 75. The expectation and variance of the mean score, Y, of n randomly selected students can be derived by multiplying the mean and standard deviation of the population by n. For a sample of n=25 students, the probability of Y exceeding 610 can be calculated by finding the z score of 610 and using standard tables or a calculator to find the probability of a z score between .67 and infinity.
  • #1
Maybe_Memorie
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Homework Statement



Students of a US university have an average SAT score of 600 and a standard deviation of 75. Assume the scores are distributed as a normal distribution.

If X is the score of a randomly selected student, derive the expectation and variance of the mean score, Y, of n randomly selected students.

If the sample is of n=25 students, what is the probability Y exceeds 610?

Homework Equations





The Attempt at a Solution



For a normal distribution, the expectation is the mean, and the variance is the standard deviation squared, so am I correct in saying for n students it would be n times this value?

As for the second part, I'm lost
 
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  • #2
excuse lack of latex code here.

from my general statistics book:

1. Yes, the mean of x(bar) is the population mean.
2. The standard deviation of the sample is sigma/sqrt(n).

You need to calculate the z score of 610. Then use this with standard tables, or calculator to find P(.67<Z<Infinity).
 

1. What is normal distribution?

Normal distribution is a statistical concept that represents the distribution of a data set in a bell-shaped curve. It is also known as Gaussian distribution and is commonly used in various fields, including science, engineering, and social sciences.

2. What is the purpose of calculating expectation and variance for a sample of 25 students?

The purpose of calculating expectation and variance for a sample of 25 students is to analyze the data and understand the central tendency and variability of the sample. Expectation, also known as mean, represents the average value of the sample, while variance measures the spread of the data points around the mean.

3. How do you calculate expectation and variance for a sample of 25 students?

To calculate the expectation and variance for a sample of 25 students, you need to first find the mean by adding all the values in the sample and dividing it by 25. Then, subtract the mean from each value in the sample and square the differences. Finally, add all the squared differences and divide it by 25 to find the variance.

4. What is the significance of normal distribution in data analysis?

Normal distribution is significant in data analysis because it allows us to make predictions and draw conclusions based on the properties of the bell-shaped curve. It also helps in identifying any outliers or unusual data points in the sample, which can affect the accuracy of the analysis.

5. Is normal distribution applicable to all types of data?

No, normal distribution is not applicable to all types of data. It is only suitable for continuous data that follows a symmetric and bell-shaped pattern. If the data is not normally distributed, other statistical tests and methods may need to be used for analysis.

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