Probability of Difference in Means for Two Independent Paint Experiments

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In summary, two independent experiments were conducted to compare two types of paints. Each experiment involved painting eighteen specimens with type A and measuring the drying time in hours. The same was done with type B. Assuming that the mean drying time is equal for both types, the probability of XA-XB being greater than 0.3 was calculated using the Central Limit Theorem, resulting in a value of 0.171. However, there may be some discrepancy between the calculated value and the provided answer of 0.00135, and this could be due to the assumed normal distribution and independence of the drying times, as well as the use of i.i.d random variables.
  • #1
tzx9633

Homework Statement


Two independent experiments are being run in which two different types of paints are compared. Eighteen specimens are painted using type A and the drying time in hours is recorded on each. The same is done with type B. The population standard deviations are both known to be 1.0.

Assuming that the mean drying time is equal for the two types of paint, find P(XA–XB>0.3), where XA and XB are the average drying times for samples of size nA = nB = 20. XA and XB has the same mean.

Homework Equations

The Attempt at a Solution


σ between 2 means = sqrt ( 2x(1/sqrt(20))^2 ) = 0.316 P(XA–XB>0.3) = P ( z > ( 0.3 - 0) / 0.316) = 0.171 , but the an sprovided is 0.00135 , is my ans wrong ? [/B]
 
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  • #2
XA-XB is a sum of 36 stochastic variables. What is the distribution of XA-XB and how do you reach that conclusion?

Edit: Actually your question is unclear. It states eighteen samples for each paint but then jumps to nA = nB = 20. Which is it?
 
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  • #3
so
Orodruin said:
XA-XB is a sum of 36 stochastic variables. What is the distribution of XA-XB and how do you reach that conclusion?

Edit: Actually your question is unclear. It states eighteen samples for each paint but then jumps to nA = nB = 20. Which is it?
sorry , typo there . n1 = n2 = 20 , so XA-XB = (0, 0.316)
 
  • #4
It is not so important what you call them as much as what they are. What I am asking about is the apparent discrepancy between
tzx9633 said:
Eighteen specimens are painted
and
tzx9633 said:
samples of size nA = nB = 20
 
  • #5
Orodruin said:
It is not so important what you call them as much as what they are. What I am asking about is the apparent discrepancy between

and
ignore the 18 , take n1 = n2 = 20
 
  • #6
tzx9633 said:

Homework Statement


Two independent experiments are being run in which two different types of paints are compared. Eighteen specimens are painted using type A and the drying time in hours is recorded on each. The same is done with type B. The population standard deviations are both known to be 1.0.

Assuming that the mean drying time is equal for the two types of paint, find P(XA–XB>0.3), where XA and XB are the average drying times for samples of size nA = nB = 20. XA and XB has the same mean.

Homework Equations

The Attempt at a Solution


σ between 2 means = sqrt ( 2x(1/sqrt(20))^2 ) = 0.316 P(XA–XB>0.3) = P ( z > ( 0.3 - 0) / 0.316) = 0.171 , but the an sprovided is 0.00135 , is my ans wrong ? [/B]

Your answer is correct.
 
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  • #7
I would suggest, tzx, more a matter of taste, I guess, you mention at least slightly your use of the CLT here.
 
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  • #8
WWGD said:
I would suggest, tzx, more a matter of taste, I guess, you mention at least slightly your use of the CLT here.
I second this. There is no mention of the drying times having a normal distribution so it is an important point.

Edit: Along the same lines, giving the answer with three significant digits is probably quoting a bit more precision than available.
 
  • #9
Orodruin said:
I second this. There is no mention of the drying times having a normal distribution so it is an important point.

.

Together with the assumed independence, to avoid covariance issues, and maybe some reference to adding i.i.d RVs..
 

1. What is the probability of two means being equal?

The probability of two means being equal depends on the specific data being compared. In general, the probability can be calculated using statistical tests such as t-tests or ANOVA.

2. How do I calculate the probability of two means?

The probability of two means can be calculated using statistical tests such as t-tests or ANOVA. These tests take into account the sample size, means, and variances of the data to determine the probability of the means being equal.

3. Why is the probability of two means important?

The probability of two means is important because it allows us to determine the likelihood of the means being equal or different. This information can be useful in making decisions or drawing conclusions from data.

4. Can the probability of two means change?

Yes, the probability of two means can change depending on the data being compared and the statistical tests used. It can also change if the sample size or variances of the data change.

5. How can I interpret the probability of two means?

The probability of two means can be interpreted as the likelihood of the means being equal or different. A higher probability indicates a higher chance of the means being equal, while a lower probability suggests a higher chance of the means being different.

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