Question

2. Are gender and age associated with each other for emergency room visits? Do a chi-squared test for the following. Please report the expected counts as a matrix. Also, is this a test of independence or not? Make the 4 steps cleared as outlined on page 325 of your textbook. Visits to the Emergency Room The following data repre- sent the gender and age of 489 randomly selected patients who visited the emergency room with an injury-related emergency Onder Tirana Age (years) 25 44 45 64 65-74 Older | 56 | 92 | 37 | 8 | 11 Genderi Male | 66 AE Male Female 44 | 39 | 66 | 34 | 12 | 24

Answer 1

Null Hypothesis: Ho: Gender and age are not associated with each other for emergency room visits. Alternative Hypothesis: H: Gender and age are associated with each other for emergency room visits. Excel add-in (Mega Stat) procedure: Step 1: In EXCEL, Select Add-Ins > Mega Stat > Chi-square/Crosstab > Contingency Table. Step 2: In Input range, select the cell range Al:G3. Step 3: In Output Options, select chi-square, Expected values. Step 4: Click OK Excel add-in (Mega Stat) output:

Chi-square Contingency Table Test for Independence 25-44 45-64 Under 15 66 60.74 Male Observed Expected Female Observed Expected Total Observed Expected 15-24 56 52.45 39 42.55 92 87.24 66 70.76 37 39.20 34 31.80 65-74 8 11.04 12 8.96 20 20.00 75 and Older 11 19.33 24 15.67 35 35.00 Total 270 270.00 219 219.00 489 489.00 49.26 110 110.00 95 158 95.00 158.00 71.00 12.29 chi-square 5 df 0310 p-value Test Statistic: r2 =12.29 P-value = 0.0310. Conclusion: Use a significance level, a = 0.05 Here, p-value is 0.0310, which is less than the value of a = 0.05. That is, p-value (0.0310) sal=0.05). Therefore, by the rejection rule, reject the null hypothesis H. Interpretation: There is sufficient evidence at level of significance a = 0.05. Gender and age are associated with each other for emergency room visits.