A gambler rolls a die to determine whether or not it is fair. A fair die is one that does not favor any of the 6 numbers. Test at 10% significance to see if the die is weighted. Round to the fourth as needed. Observed Expected Categories Frequency Frequency 1 76 2 73 3 54 4 67 5 50 6 76 Test Statistic: Degrees of Freedom: p-val: Decision Rule: | Select an answer Did something significant happen? Select an answer There Select an answer enough evidence to conclude ( Select an answer

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### Chi-Square Test for a Fair Die

A gambler rolls a die to determine whether or not it is fair. A fair die is one that does not favor any of the 6 numbers. Test at 10% significance to see if the die is weighted. Round to the fourth as needed.

#### Data Collected

The observed and expected frequencies are shown in the table below:

| Categories | Observed Frequency | Expected Frequency |
|------------|---------------------|---------------------|
| 1          | 76                  |                     |
| 2          | 73                  |                     |
| 3          | 54                  |                     |
| 4          | 67                  |                     |
| 5          | 50                  |                     |
| 6          | 76                  |                     |

#### Analysis

To determine if the die is fair, we need to perform a Chi-Square test. The fields provided for the educational exercise:

1. **Test Statistic**: 
   - Calculate the test statistic \( \chi^2 \) using the formula:
     \[
     \chi^2 = \sum \frac{(O_i - E_i)^2}{E_i}
     \]
     where \( O_i \) is the observed frequency and \( E_i \) is the expected frequency.

2. **Degrees of Freedom**: 
   - Calculate the degrees of freedom \( df \) using the formula:
     \[
     df = n - 1
     \]
     where \( n \) is the number of categories (in this case, 6).

3. **p-val**: 
   - The p-value will be determined based on the Chi-Square distribution table corresponding to the calculated test statistic and degrees of freedom.

4. **Decision Rule**:
   - Select an answer to decide whether or not the null hypothesis is rejected based on the p-value and the significance level.

5. **Did something significant happen?** 
   - Decide if there is enough evidence to conclude whether the die is fair or not.

By filling in the above values, we can determine if the deviation observed in the data is significant enough to conclude that the die is not fair.
Transcribed Image Text:### Chi-Square Test for a Fair Die A gambler rolls a die to determine whether or not it is fair. A fair die is one that does not favor any of the 6 numbers. Test at 10% significance to see if the die is weighted. Round to the fourth as needed. #### Data Collected The observed and expected frequencies are shown in the table below: | Categories | Observed Frequency | Expected Frequency | |------------|---------------------|---------------------| | 1 | 76 | | | 2 | 73 | | | 3 | 54 | | | 4 | 67 | | | 5 | 50 | | | 6 | 76 | | #### Analysis To determine if the die is fair, we need to perform a Chi-Square test. The fields provided for the educational exercise: 1. **Test Statistic**: - Calculate the test statistic \( \chi^2 \) using the formula: \[ \chi^2 = \sum \frac{(O_i - E_i)^2}{E_i} \] where \( O_i \) is the observed frequency and \( E_i \) is the expected frequency. 2. **Degrees of Freedom**: - Calculate the degrees of freedom \( df \) using the formula: \[ df = n - 1 \] where \( n \) is the number of categories (in this case, 6). 3. **p-val**: - The p-value will be determined based on the Chi-Square distribution table corresponding to the calculated test statistic and degrees of freedom. 4. **Decision Rule**: - Select an answer to decide whether or not the null hypothesis is rejected based on the p-value and the significance level. 5. **Did something significant happen?** - Decide if there is enough evidence to conclude whether the die is fair or not. By filling in the above values, we can determine if the deviation observed in the data is significant enough to conclude that the die is not fair.
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