EBK STATISTICS FOR THE BEHAVIORAL SCIEN
EBK STATISTICS FOR THE BEHAVIORAL SCIEN
3rd Edition
ISBN: 9781506386249
Author: PRIVITERA
Publisher: VST
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Chapter 17, Problem 23CAP

1.

To determine

Find the Chi-square test for independence at 0.05 significance level.

Check whether to retain or reject the null hypothesis test by using the chi-square test for independence.

1.

Expert Solution
Check Mark

Answer to Problem 23CAP

The value of test statistic is 4.855.

The decision is to retain the null hypothesis.

The noise level and exam grades during an exam are independent.

Explanation of Solution

Calculation:

The given information is that, a study was conducted by the tests of loudness of noise during an exam (low, medium, high) and exam grades (pass, fail). The summarized table is,

Noise levelTotals
LowMediumHigh
ExamPass2018846
Fail861024
Totals282418N=70

Table 1

The formula for total participants is,

N=i=1nfoi

In the formula, fo denotes the observed frequencies for each category.

The formula for expected frequency is,

fe=row total×column totalN

In the formula, N denotes the total participants.

Test statistic:

The formula for chi-square test statistic is,

χobt2=(fofe)2fe

In the formula, fo denotes the observed frequency and fe denotes the expected frequency.

The formula for degrees of freedom for chi-square independence test is,

df=(k11)(k21)

In the formula, k1 denotes the number of levels of first categorical variable and k2 denotes the number of levels of second categorical variable.

Null hypothesis:

H0: The noise level and exam grades during an exam are independent.

Alternative hypothesis:

H1: The noise level and exam grades during an exam are related.

Expected frequency:

Substitute the corresponding values of roe totals, column totals and total frequencies for each level of categorical variable in the expected frequency formula.

Noise levelTotals
LowMediumHigh
ExamPass46×2870=18.446×2470=15.846×1870=11.846
Fail24×2870=9.624×2470=8.224×1870=6.224
Totals282418N=70

Table 2

Substitute, k1=2,k2=3 in degrees of freedom formula for chi-square independence test.

df=(21)(31)=1×2=2

Critical value:

The given significance level is α=0.05 and the degrees of freedom are 2.

From the Appendix C: Table C.7 Critical values for Chi-square:

  • Locate the value 2 in the degrees of freedom (df) column.
  • Locate the 0.05 in level of significance row.
  • The intersecting value that corresponds to the 2 with level of significance 0.05 is 5.99.

The critical value for df=2 at a 0.05 level of significance is 5.99.

Test statistic value:

Substitute the corresponding values of observed and expected frequencies for each level of categorical variable in the test statistic formula.

χobt2=(2018.4)218.4+(1815.8)215.8+(811.8)211.8+(89.6)29.6+(68.2)28.2+(106.2)26.2=2.5618.4+4.8415.8+14.4411.8+2.569.6+4.848.2+14.46.2=0.139+0.306+1.224+0.267+0.590+2.329=4.855

Hence, the value of test statistic is 4.855.

Conclusion:

The test statistic value is 4.855.

The critical value is 5.99.

The test statistic value is less than the critical value.

The null hypothesis is retained.

The noise level and exam grades during an exam are independent.

2.

To determine

Find the effect size using Cramer’s V.

2.

Expert Solution
Check Mark

Answer to Problem 23CAP

The effect size using Cramer’s V is 0.26.

Explanation of Solution

Calculation:

The test statistic is 4.855, and value of N is 70.

The formula for effect size using Cramer’s V is,

V=χ2N×dfSmaller

In the formula, χ2 denotes the calculated test statistic, N denotes the total participants and dfSmaller denotes the smaller value for two sets of degrees of freedom, that is smaller of (k11) and (k21).

For 2×3 chi-square, the degrees of freedom are 1(=21), and 2(=31).

The smaller degrees of freedom are 1.

Substitute, N=70, χ2=4.855, and dfsmaller=1 in effect size formula using Cramer’s V.

V=4.85570×1=4.85570=0.0694=0.26

Hence, effect size using Cramer’s V is 0.26.

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