In a chi-square contingency table test for independence, there are six rows and five columns. The computed chi-square value is 46. The p-value is:

_ ,pval = chi2_contingency(contingency_table)

In a contingency table, the number in each cell of the table isQuestion 3Answera.the total number of individuals in the sample.b.the number of individuals who would be expected to belong to a particular category by chance.c.the number of individuals in the sample who are classified in a particular category.d.the number of categories used to classify the participants.

Consider a set of 20 samples from a standard normal distribution. We square each sample and sum all the squares. The number of degrees of freedom for a Chi Square distribution will be?(1 Point)402010None of these

Which statement is not true about both the chi-square and McNemar test?Question 12Answera.Both tests are used on frequency data (or counts)b.The data in separate cells of the contingency table must come from different participants (independent sample)c.The test statistic is based on comparing the observed frequency of an event, with the expected frequency of the event if the null hypothesis is trued.They are non-parametric tests

To calculate the chi-squared statistic, we need to follow these steps: ### Step-by-Step Calculation: #### iii) Calculate the Expected FrequenciesThe expected frequency for each cell in a contingency table is calculated using the formula: \[ E_{ij} = \frac{( \text{Row Total}_i \times \text{Column Total}_j )}{\text{Grand Total}} \] Let's calculate the expected frequencies for each cell: 1. **Facebook:** - Female: \( E_{11} = \frac{(117 \times 64)}{249} \approx 30.07 \) - Male: \( E_{12} = \frac{(132 \times 64)}{249} \approx 33.93 \) 2. **Instagram:** - Female: \( E_{21} = \frac{(117 \times 64)}{249} \approx 30.07 \) - Male: \( E_{22} = \frac{(132 \times 64)}{249} \approx 33.93 \) 3. **Snapchat:** - Female: \( E_{31} = \frac{(117 \times 58)}{249} \approx 27.25 \) - Male: \( E_{32} = \frac{(132 \times 58)}{249} \approx 30.75 \) 4. **Twitter:** - Female: \( E_{41} = \frac{(117 \times 63)}{249} \approx 29.6 \) - Male: \( E_{42} = \frac{(132 \times 63)}{249} \approx 33.4 \) The expected frequencies are: | | Facebook | Instagram | Snapchat | Twitter | Row Total | |------------|----------|-----------|----------|---------|-----------| | **Female** | 30.07 | 30.07 | 27.25 | 29.6 | 117 | | **Male** | 33.93 | 33.93 | 30.75 | 33.4 | 132 | | **Column Total** | 64 | 64 | 58 | 63 | 249 | #### iv) Calculate the Chi-Squared StatisticThe chi-squared statistic is calculated using the formula: \[ \chi^2 = \sum \frac{(O_{ij} - E_{ij})^2}{E_{ij}} \] Where \( O_{ij} \) is the observed frequency and \( E_{ij} \) is the expected frequency. Let's calculate the chi-squared statistic step by step: 1. **Facebook:** - Female: \( \frac{(33 - 30.07)^2}{30.07} \approx 0.29 \) - Male: \( \frac{(31 - 33.93)^2}{33.93} \approx 0.25 \) 2. **Instagram:** - Female: \( \frac{(30 - 30.07)^2}{30.07} \approx 0.00 \) - Male: \( \frac{(34 - 33.93)^2}{33.93} \approx 0.00 \) 3. **Snapchat:** - Female: \( \frac{(26 - 27.25)^2}{27.25} \approx 0.06 \) - Male: \( \frac{(32 - 30.75)^2}{30.75} \approx 0.05 \) 4. **Twitter:** - Female: \( \frac{(28 - 29.6)^2}{29.6} \approx 0.09 \) - Male: \( \frac{(35 - 33.4)^2}{33.4} \approx 0.08 \) Summing these values: \[ \chi^2 = 0.29 + 0.25 + 0.00 + 0.00 + 0.06 + 0.05 + 0.09 + 0.08 = 0.82 \] So, the chi-squared statistic is: \[ \chi^2 \approx 0.82 \] This value should be entered in the box for the chi-squared statistic.