Calculating Standard Deviation for a Sample Mean

In summary, the problem involves calculating the probability that the sample mean of 55 independent normal observations with mean 100 falls between 98 and 103. The first 50 observations have a variance of 76.4 and the last 5 have a variance of 127. The standard deviation of the sample mean is found to be 1.213559.
  • #1
bonfire09
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Homework Statement



There are 55 independent normal observations with mean 100. The first 50 observations have variance 76.4 and last five have variance 127.
Calculate the probability that ##\bar{x}=\frac{1}{55}\sum_{i=1}^{55} X_i## is between 98 and 103.

Homework Equations


The Attempt at a Solution


The trouble I am having is finding the standard deviation of ##\bar{x}##.
What I did so far is Var(##\frac{1}{55}\sum_{i=1}^{55} X_i##)=##\frac{1}{55^2} Var(\sum_{i=1}^{55} X_i)=\frac{1}{55^2}[Var(X_1)+...+Var(X_{55})]= \frac{1}{55^2}*[76.4*50+127*5]=1.47272##. So the standard deviation of ##\bar{x}## is 1.213559.
Not sure if this correct or not?
 
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  • #2
bonfire09 said:

Homework Statement



There are 55 independent normal observations with mean 100. The first 50 observations have variance 76.4 and last five have variance 127.
Calculate the probability that ##\bar{x}=\frac{1}{55}\sum_{i=1}^{55} X_i## is between 98 and 103.

Homework Equations





The Attempt at a Solution


The trouble I am having is finding the standard deviation of ##\bar{x}##.
What I did so far is Var(##\frac{1}{55}\sum_{i=1}^{55} X_i##)=##\frac{1}{55^2} Var(\sum_{i=1}^{55} X_i)=\frac{1}{55^2}[Var(X_1)+...+Var(X_{55})]= \frac{1}{55^2}*[76.4*50+127*5]=1.47272##. So the standard deviation of ##\bar{x}## is 1.213559.
Not sure if this correct or not?

You seem to be asking us if you are sure this is correct (rather than just asking us if it IS correct). Anyway, assuming no arithmetical errors (I have not checked) the answer should be OK.
 
  • #3
Yes, I'm not sure if what I did is correct. Could you please check it for me if I did it correctly? I've been trying to figure this problem out for a while now thanks.
 
Last edited:

1. What is standard deviation?

Standard deviation is a measure of how spread out a set of data is from its mean. In other words, it tells us how much the data points deviate from the average. A large standard deviation indicates that the data is more spread out, while a small standard deviation means the data is closer to the mean.

2. Why is standard deviation important?

Standard deviation is important because it helps us understand the variability and distribution of data. It is commonly used in statistical analysis to determine the significance of results and to compare different sets of data. It also plays a key role in calculating confidence intervals and making predictions.

3. How do you find standard deviation?

To find standard deviation, you first need to calculate the mean (average) of the data set. Then, for each data point, subtract the mean and square the result. Next, find the sum of all the squared differences and divide by the total number of data points. Finally, take the square root of the result to get the standard deviation.

4. What is the formula for standard deviation?

The formula for standard deviation is √(Σ(x-μ)² / n), where x is each individual data point, μ is the mean, and n is the total number of data points. This formula is also known as the population standard deviation. For a sample standard deviation, the formula is slightly different: √(Σ(x-μ)² / (n-1)).

5. Can standard deviation be negative?

No, standard deviation cannot be negative. Since it is a measure of how far data points deviate from the mean, it will always be a positive value. A value of zero indicates that all the data points are the same, while a larger value indicates a greater spread of data.

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