We have presented a contingency table that gives a cross-classification of a random sample of values for two variables x and y, of a population.

Perform the following tasks

a. Find the expected frequencies Note: You will first need to compute the row totals, column totals, and grand total.

b. Determine the value of the chi-square statistic

c. Decide at the 5% significance level whether the data provide sufficient evidence to conclude that the two variables are associated.

Short Answer

Expert verified

The data do not provide sufficient evidence to conclude that the two variables are associated at the 5% significance level.

Step by step solution

01

Step 1. Given

02

Step 2. Solution a). Find the Expected frequencies using MINITAB

MINITAB procedure:

Step 1: Choose Stat > Tables > Chi-Square test (Two-Way Table in Worksheet).

Step 2: In Columns containing the table, enter the columns of AandB.

Step 3: Click OK.

03

Step 3. MINITAB output

04

Step 4. Row total, column total and grand total

yABTotal
a53540
b2080100
c3585110
Total50200250
05

Step 5. Expected Frequencies

yABTotal
a83240
b2080100
c2288110
Total50200250
06

Step 6. Solution b)

Determine the value of chi-squared statistic

From the MINITAB output, the value of chi-squared statistic is1.918

07

Step 7. Solution c) 

Check whether or not the data provide sufficient evidence to conclude that the two variables are associated at the 5% significance level

The hypotheses are given below

Null hypothesis:

: The two variables are not associated

Alternative hypothesis:

: The two variables are associated

08

Step 8. Conclusion for 5% significance level

From the output, the value of test statistic is 1.918and the p-value is 0.383.

Here, the p-value is lesser than the level of significance

That is, p-value(=0.383)>α(=0.05).

Therefore, the null hypothesis is not rejected at 5% level

Thus, the data do not provide sufficient evidence to conclude that the two variables are associated at the 5% significance level.

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Most popular questions from this chapter

The t-table has entries for areas of 0.10,0.05,0.025,0.01and0.005. In contrast, the χ2-table has entries for those areas and for 0.995,0.99,0.975,0.95and 0.90.Explain why the t-values corresponding to these additional areas can be obtained from the existing t-table but must be provided explicitly in the χ2-table.

Suppose that you have bivariate data for an entire population.

a. How would you decide whether an association exists between the two variables under consideration?

b. Assuming that you make no calculation mistakes, could your conclusion be in error? Explain your answer.

In each of the given Exercises, we have presented a contingency table that gives a cross-classification of a random sample of values for two variables, x, and y, of a population. For each exercise, perform the following tasks.

a. Find the expected frequencies. Note: You will first need to compute the row totals, column totals, and grand total.

b. Determine the value of the chi-square statistic.

c. Decide at the 5% significance level whether the data provide sufficient evidence to conclude that the two variables are associated.

Table 12.4 on page 486 showed the calculated sums of the observed frequencies, the expected frequencies, and their differences. Strictly speaking, those sums are not needed. However, they serve as a check for computational errors.

a) In general, what common value should the sum of the observer frequencies and the sum of the expected frequencies equal? Ex plain your answer.

b) Fill in the blank. The sum of the differences between each observed and expected frequency should equal

c) Suppose that you are conducting a chi-square goodness-of-fit test. If the sum of the expected frequencies does not equal the sample size, what do you conclude?

d) Suppose that you are conducting a chi-square goodness-of-fit test. If the sum of the expected frequencies equals the sample size, can you conclude that you made no error in calculating the expected frequencies? Explain your answer.

Bottled Water. A project exploring the bottled-water phenomenon and preference of water types was conducted by researchers M. Lunsford and A. Fink in the article "Water Taste Test Data" (Journal of Statistics Education, Vol. 18, No. 1). One hundred nine subjects participated in double-blind taste tests of three different bottled water brands (Fiji, Aquafina, and Sam's Choice) and tap water. Twelve people preferred the tap water, 27 Aquafino 44 Fiji, and 26 Sam's Choice. At the 5% significance level, do the data provide sufficient evidence to conclude that the four different water types are not equally likely in preference?

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