Test concerning difference of two means

In summary, a t-test was conducted to determine if there is a significant difference in the number of sales between a sample of salespeople in California and a sample of salespeople in Oregon. The results showed that there is no significant difference between the two groups.
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toothpaste666
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Homework Statement

The following are the number of sales which a sample of nine salespeople of industrial chemicals in California and a sample of six salespeople of industrial chemicals in Oregon made over a certain fixed period of time.

California: 59, 68, 44, 71, 63, 46, 69, 54, 48
Oregon: 50, 36, 62, 52, 70, 41

Assuming that the populations sampled can be approximated closely with normal distributions having the same variance, Is there a difference in the number of sales between the California salespeople and the Oregon salespeople? Conduct a hypothesis test at the significance level .01.

The Attempt at a Solution


since both have the same variances and they are normal, we use a t test.
t = [X - Y - δ]/[(Sp)sqrt(1/n1 + 1/n2)]

where Sp^2 = [(n1-1)S1^2 + (n2-1)S2^2]/[n1+n2-2]

H0: δ = μ1 - μ2 = 0
H1: δ≠0
it is a two sided test so tα/2 = t.01/2 = t.005 for n1+n2-2 = 9 + 6 - 2 = 13 degrees of freedom = 3.012
so we reject H0 if t > 3.012 or t < 3.012

using Y (oregon) = ∑x/n2 and X (california) = ∑x/n1
I found Y = 51.8 and X = 58
using the formula S^2 = [∑x^2 - (∑x)^2/n]/[n-1]
we find S1^2 = 109 and S2^2 = 161

using the formula above Sp^2 = [8(109) + 5(161)]/[9+6-2] = 129
Sp = sqrt(129) = 11.36

plugging all this into t test stastic:
t = [59 - 51.8 - 0]/[(11.36)sqrt(1/9 + 1/6)] = 6.2/ 5.99 = 1.036
this falls within the range so we accept the null hypothesis. there is no difference in the number of sales.

Am I doing this correctly?
 
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toothpaste666 said:

Homework Statement

The following are the number of sales which a sample of nine salespeople of industrial chemicals in California and a sample of six salespeople of industrial chemicals in Oregon made over a certain fixed period of time.

California: 59, 68, 44, 71, 63, 46, 69, 54, 48
Oregon: 50, 36, 62, 52, 70, 41

Assuming that the populations sampled can be approximated closely with normal distributions having the same variance, Is there a difference in the number of sales between the California salespeople and the Oregon salespeople? Conduct a hypothesis test at the significance level .01.

The Attempt at a Solution


since both have the same variances and they are normal, we use a t test.
t = [X - Y - δ]/[(Sp)sqrt(1/n1 + 1/n2)]

where Sp^2 = [(n1-1)S1^2 + (n2-1)S2^2]/[n1+n2-2]

H0: δ = μ1 - μ2 = 0
H1: δ≠0
it is a two sided test so tα/2 = t.01/2 = t.005 for n1+n2-2 = 9 + 6 - 2 = 13 degrees of freedom = 3.012
so we reject H0 if t > 3.012 or t < 3.012

using Y (oregon) = ∑x/n2 and X (california) = ∑x/n1
I found Y = 51.8 and X = 58
using the formula S^2 = [∑x^2 - (∑x)^2/n]/[n-1]
we find S1^2 = 109 and S2^2 = 161

using the formula above Sp^2 = [8(109) + 5(161)]/[9+6-2] = 129
Sp = sqrt(129) = 11.36

plugging all this into t test stastic:
t = [59 - 51.8 - 0]/[(11.36)sqrt(1/9 + 1/6)] = 6.2/ 5.99 = 1.036
this falls within the range so we accept the null hypothesis. there is no difference in the number of sales.

Am I doing this correctly?

It looks OK, but I have not checked the numbers in detail.
 
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What is a test concerning difference of two means?

A test concerning difference of two means is a statistical test that is used to determine if there is a significant difference between the means of two groups or populations. It is a commonly used test in scientific research to compare the means of two samples and determine if the observed difference is due to chance or if it is a true difference.

What is the purpose of a test concerning difference of two means?

The purpose of a test concerning difference of two means is to determine if there is a significant difference between the means of two groups. This can help researchers understand if there are any meaningful differences between the two groups being compared and if those differences are statistically significant.

What are the assumptions of a test concerning difference of two means?

The assumptions of a test concerning difference of two means include: 1) the data is normally distributed, 2) the variances of the two groups being compared are equal, and 3) the observations in each group are independent. Violation of these assumptions can affect the accuracy and validity of the test results.

How is a test concerning difference of two means performed?

A test concerning difference of two means is typically performed using a t-test. This involves calculating the difference between the means of the two groups and comparing it to the standard error of the difference. The result is then compared to a critical value to determine if the difference is statistically significant.

What are the limitations of a test concerning difference of two means?

Some limitations of a test concerning difference of two means include: 1) it can only be used for continuous data, 2) it assumes that the data is normally distributed, 3) it assumes equal variances between the two groups, and 4) it can only determine if there is a significant difference between the means, not the magnitude of the difference. Additionally, the results of the test may be affected by outliers or small sample sizes.

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