Complete the following steps if the response data is a single column with two distinct values. Optionally, the data can include a column that contains the count of responses that corresponds to the response and predictor values in the row.
- From the drop-down, select Response in binary response/frequency format.
- In Response, enter the column of binary data that you want to explain or predict. Binary variables are categorical variables that have two possible levels, such as pass/fail or true/false. The response is also called the Y variable.
- In Response event, select which event the analysis will describe.
- (Optional) In Frequency, enter the column that contains the counts that correspond to the response and predictor values in the row.
- In Predictor, enter the continuous variable that may explain or predict changes in the response. The predictor is also called the X variable.
In this worksheet, Bought is the response and indicates whether a consumer purchased a new brand of cereal. The response event is Yes. Income is the continuous predictor. The data in row 1 indicate that one consumer with an income of $37,000 bought the new brand of cereal.
| C1 |
C2 |
| Bought |
Income |
| Yes |
$37,000 |
| No |
$47,000 |
| Yes |
$34,000 |
| Yes |
$58,000 |
In this worksheet, the response and predictor variables are the same as the previous example but the data also include a frequency variable. Frequency contains the count of consumers that correspond to the combination of response and predictor values in each row. The first row shows that 2 consumers with an income of $40,000 bought the new brand of cereal.
| C1 |
C2 |
C3 |
| Bought |
Income |
Frequency |
| Yes |
$40,000 |
2 |
| No |
$40,000 |
12 |
| Yes |
$45,000 |
1 |
| No |
$45,000 |
6 |
