To clarify the context and correctly put the values, let's work on the question step-by-step with the data from the provided frequency table:
```plaintext
Job Status
--------------------------------------------
| Looking for Job | Not Looking for Job | Total
--------------------------------------------
Currently Employed | 12 | 28 | 40
Not Currently Employed | 38 | 72 | 110
--------------------------------------------
Total | 50 | 100 | 150
```
Then the conditional relative frequencies by column are required. Conditional relative frequencies by column are calculated by dividing the count in each cell by the total of the column it belongs to.
Let's do the calculations for each category:
### For the "Looking for Job" Column:
- Currently Employed: [tex]\( \frac{12}{50} = 0.24 \)[/tex]
- Not Currently Employed: [tex]\( \frac{38}{50} = 0.76 \)[/tex]
### For the "Not Looking for Job" Column:
- Currently Employed: [tex]\( \frac{28}{100} = 0.28 \)[/tex]
- Not Currently Employed: [tex]\( \frac{72}{100} = 0.72 \)[/tex]
With these values, we can construct the conditional relative frequency table by columns:
```plaintext
Job Status
------------------------------------------------------------------------------------------------
| Looking for Job | Not Looking for Job | Total
------------------------------------------------------------------------------------------------
Currently Employed | 0.24 | 0.28 |
------------------------------------------------------------------------------------------------
Not Currently Employed | 0.76 | 0.72 |
------------------------------------------------------------------------------------------------
```
To summarize,
- For the "Looking for Job" column:
- Currently Employed: 0.24
- Not Currently Employed: 0.76
- For the "Not Looking for Job" column:
- Currently Employed: 0.28
- Not Currently Employed: 0.72
