Finding ∑fx and ∑fx^2 from the standard deviation and mean

In summary, the conversation discusses a question given in class with given answers that the teacher and students have been unable to obtain. The question involves finding the values for ∑f . x and ∑f . x^2, using equations for mean and standard deviation. The conversation also mentions the definitions of mean and standard deviation, and the use of population values instead of sample values. The conversation ends with doubts about the given answers.
  • #1
albertrichardf
165
11

Homework Statement


This is not homework. This is a question given in class with the answers already given. Neither the teacher nor the students have been able to figure out how to obtain the answers though, so my question is how to find them?
Here is a picture of the question.
upload_2016-9-28_19-26-14.png


The standard deviation, mean and variance are all for a population. None of them are for a sample, since it is not in the syllabus.

The answer given is 492 for ∑f . x and 6114.1 for ∑f . x^2

Homework Equations


The definition of the mean is:
u = ∑(f . x)/∑f
The definition of the standard deviation is:
√v
where is the variance, which is equal to:

(∑(f. (x^2))/42 - u^2)

Which is the mean of the square minus the square of the mean.

The Attempt at a Solution



According to the definition of the mean, ∑f .x would be equal to 42u, since ∑f = 42. u = 72.3. This gives about 3036, which is obviously not equal to 492

Then, according to the definition of the variance, it is the square of the mean. Thus the square of 34.1 should be equal to ∑(f . (x^2)) - u^2/42. Thus:

42 * (34.1^2 + u^2) = ∑f . (x^2)

Plugging in u = 72.3 gives 268384.2, which is again a far cry from 6114.1

So my question is, what is it that I'm doing wrong, and how to obtain the given answers?
Thanks for any answers.
 
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  • #2
Albertrichardf said:

Homework Statement


This is not homework. This is a question given in class with the answers already given. Neither the teacher nor the students have been able to figure out how to obtain the answers though, so my question is how to find them?
Here is a picture of the question.
View attachment 106611

The standard deviation, mean and variance are all for a population. None of them are for a sample, since it is not in the syllabus.
Actually, you are given ##\bar{x}## not ##\mu##. ##\bar{x}## is the sample mean, while ##\mu## is the population mean. The problem states that the sample standard deviation, s, is 34.1 which is generally somewhat larger than the population standard deviation, ##\sigma##.
Albertrichardf said:
The answer given is 492 for ∑f . x and 6114.1 for ∑f . x^2

Homework Equations


The definition of the mean is:
u = ∑(f . x)/∑f
The definition of the standard deviation is:
√v
where is the variance, which is equal to:

(∑(f. (x^2))/42 - u^2)

Which is the mean of the square minus the square of the mean.

The Attempt at a Solution



According to the definition of the mean, ∑f .x would be equal to 42u, since ∑f = 42. u = 72.3.

This gives about 3036, which is obviously not equal to 492
I get 3036 as well. Since your teacher is stumped by this problem, too, I begin to have doubts about the answers given for this problem.
Albertrichardf said:
Then, according to the definition of the variance, it is the square of the mean. Thus the square of 34.1 should be equal to ∑(f . (x^2)) - u^2/42. Thus:

42 * (34.1^2 + u^2) = ∑f . (x^2)

Plugging in u = 72.3 gives 268384.2, which is again a far cry from 6114.1

So my question is, what is it that I'm doing wrong, and how to obtain the given answers?
Thanks for any answers.
 
  • #3
Alright. Thanks. Actually, I know that μ is supposed to the population mean, but the syllabus specifically states that xbar is the population mean. In fact, it mentions that there is no need to know about the sample calculations. The formulae given too are only for the population values.
Well, anyway reducing n by one does not make much of a difference. It does look impossible that a set of data such that the average value is 72.3 adds up to 429.
 
  • #4
I agree with your method. As was noted above, you need a slight adjustment to your variance formula for sample data.
I built a data set that has the properties given, with 21 responses of 106, and 21 responses of 38.6. Doing tests on that clearly provide a counterargument to the so-called answers you posted.
 
  • #5
Yeah it does seem weird. Unless the variables aren't what they are assumed to mean, which is improbable. Thanks for the answers
 

1. What is the purpose of finding ∑fx and ∑fx^2 from the standard deviation and mean?

The purpose of finding ∑fx and ∑fx^2 is to calculate the variance and standard deviation for a set of data. These values help measure the spread or variability of the data from the mean.

2. How do you find ∑fx and ∑fx^2 from the standard deviation and mean?

To find ∑fx and ∑fx^2, you first need to calculate the mean of the data set. Then, for each data point, subtract the mean from the data point and square the result. Multiply this value by the frequency of the data point and add it to the sum of squared deviations (∑fx^2). To find ∑fx, simply multiply the frequency of each data point by the data point itself and add all of these values together.

3. Can you find ∑fx and ∑fx^2 if you only have the standard deviation and mean?

No, you need the actual data points or at least the frequencies of each data point in order to find ∑fx and ∑fx^2. The standard deviation and mean alone do not provide enough information to calculate these values.

4. How do you interpret the values of ∑fx and ∑fx^2?

The value of ∑fx represents the sum of all the data points multiplied by their respective frequencies. This value provides an indication of the total magnitude of the data set. The value of ∑fx^2 represents the sum of all the squared deviations from the mean, providing a measure of the variability of the data set.

5. Why is it important to find ∑fx and ∑fx^2 when calculating the standard deviation?

∑fx and ∑fx^2 are necessary components in the formula for calculating the standard deviation. Without these values, it is not possible to accurately measure the spread or variability of the data set from the mean. The standard deviation is an important statistical measure that helps to understand the distribution of the data and identify any outliers or unusual data points.

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