11.3.2.1 - Video Example: Dog & Cat Ownership (Raw Data)
This example uses the dataset:
\(H_0:\) There is not a relationship between dog ownership and cat ownership in the population of all World Campus STAT 200 students
\(H_a:\) There is a relationship between dog ownership and cat ownership in the population of all World Campus STAT 200 students
Cell contents grouped by No, Yes, Missing; First row: count, Next row: expected count
No | Yes | All | |
---|---|---|---|
BaNock | 183 | 69 | 252 |
176.02 | 75.98 | ||
Yes | 183 | 89 | 272 |
189.98 | 82.02 | ||
Missing | 1 | 0 | |
All | 366 | 158 | 524 |
Assumption: All expected counts are at least 5. The expected counts here are 176.02, 75.98, 189.98, and 82.02, so this assumption has been met.
Chi-Square | DF | P-Value | |
---|---|---|---|
Pearson | 1.77 | 1 | 0.1833 |
Likelihood Ratio | 1.77 | 1 | 0.1828 |
Since the assumption was met in step 1, we can use the Pearson chi-square test statistic.
\(Pearson\;\chi^2 = 1.77\)
\(p = 0.1833\)
Our p value is greater than the standard 0.05 alpha level, so we fail to reject the null hypothesis.
There is not evidence of a relationship between dog ownership and cat ownership in the population of all World Campus STAT 200 students.