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Give a two-way table and specify a particular cell for that table. In each case find the expected count for that cell and the contribution to the chi- square statistic for that cell. \((\) Group \(2,\) No \()\) $$ \begin{array}{l|rr} \hline & \text { Yes } & \text { No } \\ \hline \text { Group 1 } & 720 & 280 \\ \text { Group 2 } & 1180 & 320 \\ \hline \end{array} $$

Short Answer

Expert verified
The expected count for the 'No' cell in 'Group 2' is 360 and its contribution to the Chi-square statistic is approximately 4.44.

Step by step solution

01

Figure out Row, Column and Total Totals

Start by calculating the totals for each row, column and the overall total. That is, the total for 'Group 1', 'Group 2', 'Yes', 'No', and the grand total: \\- For Group 1, add up the numbers of 'Yes' and 'No': 720 + 280 = 1000. \\- For Group 2 do the same: 1180 + 320 = 1500. \\- For 'Yes', add up the numbers from Group 1 and Group 2: 720 + 1180 = 1900. \\- Similarly for 'No': 280 + 320 = 600. \\- The grand total is the sum of all four cells: 1000 (Group 1) + 1500 (Group 2) = 2500.
02

Calculate the Expected Count

The expected count for a given cell in a two-way table is calculated by multiplying the row total for that cell by the column total, and then dividing by the grand total. \\- For the cell under 'No' in 'Group 2' (our point of interest), this would be: (1500 * 600) / 2500 = 360.
03

Determine the Chi-Square Statistic

The chi-square statistic for a specific cell is calculated as: \\- \( (observed-expected)^2 / expected \) \\The observed count is the actual count given in the cell, while the expected count is what we calculated in the previous step. So for 'Group 2’ and 'No': \\- \( (320-360)^2 / 360 \approx 4.44 \)

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Most popular questions from this chapter

Age and Frequency of Status Updates on Facebook Exercise 7.48 introduces a study about users of social networking sites such as Facebook. Table 7.35 shows the self-reported frequency of status updates on Facebook by age groups. (a) Based on the totals, if age and frequency of status updates are really unrelated, how many of the 156 users who are 18 to 22 years olds should we expect to update their status every day? (b) Since there are 20 cells in this table, we'll save some time and tell you that the chi-square statistic for this table is \(210.9 .\) What should we conclude about a relationship (if any) between age and frequency of status updates? $$ \begin{array}{l|rrrr|r} \hline \downarrow \text { Status/Age } \rightarrow & 18-22 & 23-35 & 36-49 & 50+ & \text { Total } \\ \hline \text { Every day } & 47 & 59 & 23 & 7 & 136 \\ \text { 3-5 days/week } & 33 & 47 & 30 & 7 & 117 \\ \text { 1-2 days/week } & 32 & 69 & 35 & 25 & 161 \\ \text { Every few weeks } & 23 & 65 & 47 & 34 & 169 \\ \text { Less often } & 21 & 74 & 99 & 170 & 364 \\ \hline \text { Total } & 156 & 314 & 234 & 243 & 947 \\ \hline \end{array} $$

Exercises 7.9 to 7.12 give a null hypothesis for a goodness-of-fit test and a frequency table from a sample. For each table, find: (a) The expected count for the category labeled B. (b) The contribution to the sum of the chi-square statistic for the category labeled \(\mathrm{B}\). (c) The degrees of freedom for the chi-square distribution for that table. $$ \begin{aligned} &H_{0}: p_{a}=0.2, p_{b}=0.80\\\ &H_{a}: \text { Some } p_{i} \text { is wrong }\\\ &\begin{array}{ll} \mathrm{A} & \mathrm{B} \end{array}\\\ &132 \quad 468 \end{aligned} $$

Exercises 7.9 to 7.12 give a null hypothesis for a goodness-of-fit test and a frequency table from a sample. For each table, find: (a) The expected count for the category labeled B. (b) The contribution to the sum of the chi-square statistic for the category labeled \(\mathrm{B}\). (c) The degrees of freedom for the chi-square distribution for that table. $$ \begin{aligned} &H_{0}: p_{a}=p_{b}=p_{c}=p_{d}=0.25\\\ &H_{a}:\\\ &\text { Some } p_{i} \neq 0.25\\\ &\begin{array}{lccc|c} \hline \text { A } & \text { B } & \text { C } & \text { D } & \text { Total } \\\ \text { 40 } & 36 & 49 & 35 & 160 \\ \hline \end{array} \end{aligned} $$

Gender and Frequency of Status Updates on Facebook Exercise 7.48 introduces a study about users of social networking sites such as Facebook. Table 7.36 shows the self-reported frequency of status updates on Facebook by gender. Are frequency of status updates and gender related? Show all details of the test. $$ \begin{array}{l|rr|r} \hline \text { IStatus/Gender } \rightarrow & \text { Male } & \text { Female } & \text { Total } \\ \hline \text { Every day } & 42 & 88 & 130 \\ \text { 3-5 days/week } & 46 & 59 & 105 \\ \text { 1-2 days/week } & 70 & 79 & 149 \\ \text { Every few weeks } & 77 & 79 & 156 \\ \text { Less often } & 151 & 186 & 337 \\ \hline \text { Total } & 386 & 491 & 877 \\ \hline \end{array} $$

Handedness and Occupation Is the career someone chooses associated with being left- or right-handed? In one study \(^{20}\) a sample of Americans from a variety of professions were asked if they consider themselves left-handed, right-handed, or ambidextrous (equally skilled with the left and right hand). The results for five professions are shown in Table \(7.33 .\) (a) In this sample, what profession had the greatest proportion of left-handed people? What profession had the greatest proportion of right-handed people? (b) Test for an association between handedness and career for these five professions. State the null and alternative hypotheses, calculate the test statistic, and find the p-value. (c) What do you conclude at the \(5 \%\) significance level? What do you conclude at the \(1 \%\) significance level? $$ \begin{array}{l|rrr|r} \hline & \text { Right } & \text { Left } & \text { Ambidextrous } & \text { Total } \\ \hline \text { Psychiatrist } & 101 & 10 & 7 & 118 \\ \text { Architect } & 115 & 26 & 7 & 148 \\ \text { Orthopedic surgeon } & 121 & 5 & 6 & 132 \\ \text { Lawyer } & 83 & 16 & 6 & 105 \\ \text { Dentist } & 116 & 10 & 6 & 132 \\ \hline \text { Total } & 536 & 67 & 32 & 635 \\ \hline \end{array} $$

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