Average of x^2 is= 1.67"Calculating Mean & STDev of # of Quarters

Never write 87(0)+8(1)+3(2)+1(4)+1(3)=21/100; in fact, 87(0)+8(1)+3(2)+1(4)+1(3)=21, period. I think what you want to do is note that 0.87(0)+0.08(1) + 0.03(2) + 0.01(4) + 001(3) = 0.21, so that is what you should write. Alternatively, you can say in words that 87(0)+8(1)+3(2)+1(4)+1(3)=21 is 100 times the mean
  • #1
noreturn2
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Homework Statement


Mind mean and STDev of number of quarters someone has on them at one time
0 - 87%
1 - 8%
2 - 3%
3- 1%
4 - 1%

The first time I did this I assumed a population but she said that was wrong and not what she was looking for.

Here was my new attempt:
x^2f(x)=
0(.87)
1(.08)
4(.03)
9(.01)
16(.01)

sum= .45

so: .45-(.2)^2=.6403

I want to do E[x^2]-[E[x]]^2=stdev
 
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  • #2
I guess I am missing something. Where are those multipliers (0, 1, 4, 9, 16) coming from? What formula are you using?

Oh, I guess I see. You have a variable with values (0, 1, 2, 3, 4) with probabilities 0.87, 0.08, 0.03, 0.01, 0.01, respectively. You should have made that clear in your problem statement.

In that case, you should be more careful about your calculations. I get 0.45-(0.21)^2 = 0.4059
 
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  • #3
FactChecker said:
I guess I am missing something. Where are those multipliers (0, 1, 4, 9, 16) coming from? What formula are you using?

I forgot to add in part of the problem statement. I've added that.

x^2f(x)
 
  • #4
noreturn2 said:
so: .45-(.2)^2=.6403
$$0.45-0.2^2 = 0.45-0.04 = 0.41$$ So don't write that it's equal to 0.6403. The equal sign doesn't mean "the next step in my calculation gives me..." Trust me, when you write something like that, it annoys your teacher at best and probably drives her crazy. Instead, you could say ##0.45-0.2^2 = 0.45-0.04 = 0.41## for the first step and then ##\sigma = \sqrt{0.41}=0.6043##.

(As @FactChecker noted, you should recheck your calculations.)

I want to do E[x^2]-[E[x]]^2=stdev
Again, this isn't true. The lefthand side is equal to the variance, not the standard deviation.

It appears you basically know what you're doing, but you need to be more careful in writing stuff down to demonstrate that to others (like the person who is going to grade your test).
 
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  • #5
vela said:
$$0.45-0.2^2 = 0.45-0.04 = 0.41$$ So don't write that it's equal to 0.6403. The equal sign doesn't mean "the next step in my calculation gives me..." Trust me, when you write something like that, it annoys your teacher at best and probably drives her crazy. Instead, you could say ##0.45-0.2^2 = 0.45-0.04 = 0.41## for the first step and then ##\sigma = \sqrt{0.41}=0.6043##.

(As @FactChecker noted, you should recheck your calculations.)Again, this isn't true. The lefthand side is equal to the variance, not the standard deviation.

It appears you basically know what you're doing, but you need to be more careful in writing stuff down to demonstrate that to others (like the person who is going to grade your test).

So my answer of .64043 was correct?
 
  • #6
Close, but as @FactChecker noted, you need to check your calculations.
 
  • #7
vela said:
Close, but as @FactChecker noted, you need to check your calculations.

So what is throwing me off is I think my calculation of the mean is incorrect. Because more people has 0 quarters then say 2 quarters, the the mean should theoretically be less then 2 correct?
 
  • #8
Right. Since the vast majority of people had no quarters, you'd expect the mean to be relatively close to 0.
 
  • #9
vela said:
Right. Since the vast majority of people had no quarters, you'd expect the mean to be relatively close to 0.
So would it be .45/100%= .0045, which seems also wrong but makes sense. Since the .45 is the number of quarters in the "system" sort of say, and then we accounted for 100% of the population.
 
  • #10
noreturn2 said:
So what is throwing me off is I think my calculation of the mean is incorrect. Because more people has 0 quarters then say 2 quarters, the the mean should theoretically be less then 2 correct?
Yes. But your calculated mean of 0.2 (should be more accurate 0.21) is much smaller than 2. Why do you doubt that answer for the mean?
 
  • #11
noreturn2 said:
So would it be .45/100%= .0045, which seems also wrong but makes sense. Since the .45 is the number of quarters in the "system" sort of say, and then we accounted for 100% of the population.
I don't understand where you are getting the 0.45 number. In any case, dividing by 100% makes no sense to me.

I suggest that you stick with the established formulas and be more careful with them. You essentially got the right answer the first time, but you presented it carelessly and it was not possible (for me) to follow what you were doing.
 
  • #12
Ok so here is what I have let me know if this looks better

Mean: .21
87(0)+8(1)+3(2)+1(4)+1(3)=21/100

STDev:
E[x^2]-[E[x]]^2

.45-(.21)^2=.4059
sqrt(.4059)

STDEVA: .637
 
  • #13
Much better. Some improvements could be: Show the calculation of E[x^2] that gave you .45, label the variance, and use the same name STDev (not STDEVA).
 
  • #14
noreturn2 said:
Ok so here is what I have let me know if this looks better

Mean: .21
87(0)+8(1)+3(2)+1(4)+1(3)=21/100

STDev:
E[x^2]-[E[x]]^2

.45-(.21)^2=.4059
sqrt(.4059)

STDEVA: .637

Never write 87(0)+8(1)+3(2)+1(4)+1(3)=21/100; in fact, 87(0)+8(1)+3(2)+1(4)+1(3)=21, period. I think what you want to do is note that 0.87(0)+0.08(1) + 0.03(2) + 0.01(4) + 001(3) = 0.21, so that is what you should write. Alternatively, you can say in words that 87(0)+8(1)+3(2)+1(4)+1(3)=21 is 100 times the mean, so you need to divide the result by 100 to get the mean.
 

1. What does the average of x^2 equal to 1.67 mean?

The average of x^2 equal to 1.67 means that when you square a set of numbers and find their average, the result will be approximately 1.67. This indicates the central tendency of the data set.

2. How do you calculate the average of x^2?

To calculate the average of x^2, you need to first square each number in the data set. Then, add all the squared values together and divide by the total number of values in the data set. The result will be the average of x^2.

3. Why is it important to calculate the average of x^2?

Calculating the average of x^2 is important because it helps to determine the variability or spread of the data. It can also provide information about the symmetry of the data set.

4. How is the average of x^2 related to the standard deviation?

The average of x^2 is directly related to the standard deviation. In fact, the standard deviation is the square root of the average of x^2. This means that the average of x^2 can be used to calculate the standard deviation of a data set.

5. Can the average of x^2 be negative?

No, the average of x^2 cannot be negative. This is because when you square a negative number, the result is always positive. Therefore, the average of x^2 will always be a positive number.

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