| IPS 5/e | Ex. 9.10, p. 614 | Majors in business | ||||||
| GENDER | ||||||||
| M | Female | Male | TOTAL | |||||
| A | Accounting | 68 | 56 | 124 | ||||
| J | Administration | 91 | 40 | 131 | ||||
| O | Economics | 5 | 6 | 11 | ||||
| R | Finance | 61 | 59 | 120 | ||||
| TOTAL | 225 | 161 | 386 | |||||
| Conditional distribution of majors for each gender | ||||||||
| GENDER | ||||||||
| M | Female | Male | TOTAL | |||||
| A | Accounting | |||||||
| J | Administration | |||||||
| O | Economics | |||||||
| R | Finance | |||||||
| TOTAL | ||||||||
| Assuming no relationship between gender and major, | ||||||||
| calculate the expected count in each cell: | ||||||||
| row total times column total / table total. | ||||||||
| GENDER | ||||||||
| M | Female | Male | TOTAL | |||||
| A | Accounting | |||||||
| J | Administration | |||||||
| O | Economics | |||||||
| R | Finance | |||||||
| TOTAL | ||||||||
| Calculate each term of the chi-square statistic: | ||||||||
| (observed count - expected count)^2 / expected count | ||||||||
| GENDER | ||||||||
| M | Female | Male | TOTAL | |||||
| A | Accounting | |||||||
| J | Administration | |||||||
| O | Economics | |||||||
| R | Finance | |||||||
| TOTAL | =X^2 | df = ? | P = ? | |||||