= Question Help The table to the right contains observed values and expected values in parentheses for two categorical variables, X and Y, where variable X has three categories and variable Y has wo categories. Use the table to complete parts (a) and (b) below. X, X2 X, P 32 51 (35.39)(44.42)(47.19) 19 20 44 17 (15.61)(19.58)(20.81) Y2 a) Compute the value of the chi-square test statistic. (Round to three decimal places as needed.)

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### Understanding Chi-Square Test

#### Example 12.2.3-T

This example features a table that displays observed values and expected values (in parentheses) for two categorical variables, \( X \) and \( Y \). Variable \( X \) is divided into three categories (\( X_1, X_2, X_3 \)), and variable \( Y \) consists of two categories (\( Y_1, Y_2 \)). 

#### Data Table:

|       | \( X_1 \) | \( X_2 \) | \( X_3 \) |
|-------|--------|--------|--------|
| \( Y_1 \) | 32 (35.39) | 44 (44.42) | 51 (47.19) |
| \( Y_2 \) | 19 (15.61) | 20 (19.58) | 17 (20.81) |

#### Task:

(a) Compute the value of the chi-square test statistic.

\[ \chi^2_0 = \text{[Round to three decimal places as needed.]} \]

In this example, you'll calculate the chi-square test statistic to test the association between the categories of \( X \) and \( Y \).

### Explanation:

Each cell in the table contains two numbers: the observed count and, in parentheses, the expected count under the assumption that there is no association between \( X \) and \( Y \). The chi-square statistic is computed based on the differences between these observed and expected values.
Transcribed Image Text:### Understanding Chi-Square Test #### Example 12.2.3-T This example features a table that displays observed values and expected values (in parentheses) for two categorical variables, \( X \) and \( Y \). Variable \( X \) is divided into three categories (\( X_1, X_2, X_3 \)), and variable \( Y \) consists of two categories (\( Y_1, Y_2 \)). #### Data Table: | | \( X_1 \) | \( X_2 \) | \( X_3 \) | |-------|--------|--------|--------| | \( Y_1 \) | 32 (35.39) | 44 (44.42) | 51 (47.19) | | \( Y_2 \) | 19 (15.61) | 20 (19.58) | 17 (20.81) | #### Task: (a) Compute the value of the chi-square test statistic. \[ \chi^2_0 = \text{[Round to three decimal places as needed.]} \] In this example, you'll calculate the chi-square test statistic to test the association between the categories of \( X \) and \( Y \). ### Explanation: Each cell in the table contains two numbers: the observed count and, in parentheses, the expected count under the assumption that there is no association between \( X \) and \( Y \). The chi-square statistic is computed based on the differences between these observed and expected values.
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