1. What is pooled variance and why is it important?

Suppose we have two samples from two populations. Also we know that both the populations have the same variance σ2.

Then we will be having two sample variances s12and s12. They are defined by

s12=x1-x12n1-1 and s22=x2-x22n2-1

Both are estimates of the same population varinaceσ2. So we want to combine these two estimates to a pooled estimate. It is defined as

s2=(n1-1)s12+(n2-1)s22n1+n2-2

In hypothesis testing, when the common population variance is unknown, we make use of the pooled sample variance.

2. Explain what interval data is and give an example:

Interval data is continuous data where differences are interpretable, but where there is no "natural" zero. A good example is temperature in Fahrenheit degrees.

Ratios are meaningless for interval data. You cannot say, for example, that one day is twice as hot as another day.

4. Write the formula for pooled variance.

It is defined as

s2=(n1-1)s12+(n2-1)s22n1+n2-2

n1and n2are sizes of the two sampless12and s22are the variances of the two samples.

5. Please analyze the following data using the T-test for Unpaired data: A school district wants to determine if the girls are equal to boys in test scores. They took a random sample of 22 8th grade girls and 24 8th grade boys. The district looked at recent CAT scores and found the mean score for girls to be xbar1 = 25 and the mean score for boys to be xbar2 = 26. The standard deviation for the girls is s1 = 2.2 and for the boys the standard deviation is s2 = 3.4. Is the school district correct in assuming the girls are equal in performance to boys. They are 95% sure their assumption is correct.

n1 =22

n2 = 24

xbar1 = 25

xbar2 = 26

s1 = 2.2

s2 = 3.4

pooled variance = s=(n1-1)s12+(n2-1)s22n1+n2-2=(22-1)(2.22)+(24-1)3.4222+24-2

=101.64+265.8844=8.3527=2.8901

Null hypothesis H0: μ1 = μ2

The mean scores of girls and boys are equal.

Alternative hypothesis H1: μ1≠ μ2

The mean scores of girls and boys are different.

The test statistic is

T=x1-x2s1n1+1n2=25-262.8901122+124=-1.1723

Degrees of freedom = n1+n2-2=22+24-2=44

5% Critical value of t with 44 degrees of freedom = 2.0154

Critical region is T>2.0154

The computed value T is not in the critical region.

So the does not provide sufficient evidence to reject the null hypothesis.

So we conclude that the school district is correct in assuming the girls are equal in performance to boys.

6. Please analyze the following data using the Z-test for Unpaired data A candy company wants to identify whether or not the size of its' candy bars are the same length from one day to another. On day 1 they sample 52 candy bars with an average mean of 5.4 inches and on day 2 they sample 52 bars again with and average mean of 5.6 inches. Both days have sample standard deviations of 3.4. Is the average mean of size different from day 1 to day 2?

x1=5.4, x2=5.6, n1=52, n2=52, σ=3.4

Null hypothesis H0: μ1=μ2

The means of day1 and day 2 are the same.

Alternative hypothesis H1: μ1≠μ2

The means of the two days are different.

The test statistic is

Z=x1-x2σ1n1+1n2=5.4-5.63.4152+152=-1.0198

The critical region is Z>1.96

Decision

The computed value of Z is not significant.

So the sample does not provide sufficient evidence to reject the null hypothesis. So we conclude that the average mean size is the same from day to day.

7. A sample of 40 observations is selected from one population. The sample mean is 102 and the sample standard deviation is 5. A sample of 50 observations is selected from a second population. The sample mean is 99 and the sample standard deviation is 6. Conduct the following test using 95% level of confidence. Z-test for Unpaired data A. Is it a 1 or 2 tail test B. Compute the statistical calculation C. What is your decision regarding H1

n1=40

x1=102

s1=5

n2=50

x2=99

s2=6

H0:μ1=μ2

H1:μ1≠μ2

z=x1-x2(n1-1)s12+(n2-1)s22n1+n2-211n1+1n2=102-993952+496240+50-2140+150

=2.5349 >1.96

It is a two tail test.

Reject
H0:μ1=μ2

So we accept the alternative hypothesis H1. The means are different.

8. A sample of 65 observations is selected from one population. The sample mean is 2.67 and the sample standard deviation is .75. A sample of 50 observations is selected from a second population. The sample mean is 2.59 and the sample standard deviation is .66. Conduct the following test using 95% level of confidence. Z-test for Unpaired data a. Is it a 1 or 2 tail test b. Compute the statistical calculation c. What is your decision regarding H1 d. What is the P-value 9. The Gibbs Baby Food Company wishes to compare the weight gain of infants using their brand versus their competitor's brand. A sample of 40 babies using the Gibbs products revealed a mean weight gain of 7.6 pounds in the first 3 months after birth. The standard deviation of this sample is 2.3 pounds. A sample of 55 babies using the competitors brand revealed a mean increase of 8.8 pounds with a standard deviation of 2.9 pounds. At 95% level of confidence, can we conclude that the babies using the Gibbs product gained LESS weight? Z-test for Unpaired data 10. What key words tell you that the Hypothesis is to be set up as a 1 Tail UPPER?