How to do logistic regression on data file?

How do you do logistic regression on with this data? I am having trouble finding a correct model as I am relatively new to Matlab and programming.

|0.8046|0.2928|0.8752|0.5727|1|0.8235|1|1|0.8646|0.3871|0.7975|0.4194

|0.8029|0.387 |0.8383|0.5861|0|0.4824|1|1|0.6563|0.4032|0.5823|0.4194

|0.8184|0.2936|0.8903|0.5823|1|0.1765|1|1|0.6875|0.5161|0.6456|0.5323

|0.8849|0.325 |0.9574|0.8383|0|0.8118|1|1|0.7813|0.5323|0.7342|0.6613

|0.7305|0.1746|0.8406|0.4295|1|0.1412|1|1|0.7292|0.4516|0.7215|0.4516

[Star Strider]

What are your predictor and response variables?

[Humblespud]

I'm working on doing a logistic regression using MATLAB for a simple classification problem. I have 9 continuous variables ranging between 0 and 1, while my categorical response is a binary variable of 0 (incorrect) or 1 (correct).

I'm looking to run a logistic regression to establish a predictor that would output the probability of some input observation (e.g. the continuous variable as described above) being correct or incorrect.

Answer 1

[the cyclist]

You don't give us much detail, so we can't give you a detailed answer.

If you have the Statistics and Machine Learning Toolbox, there is a good chance that you can use the fitglm function to do the regression. That documentation link has examples.

[Humblespud]

I'm working on doing a logistic regression using MATLAB for a simple classification problem. I have 9 continuous variables ranging between 0 and 1, while my categorical response is a binary variable of 0 (incorrect) or 1 (correct).

I'm looking to run a logistic regression to establish a predictor that would output the probability of some input observation (e.g. the continuous variable as described above) being correct or incorrect.

Answer 2

[Star Strider]

A classifier might be a more appropriate approach than a regression. My first choice would be the classify function to do a discriminant analysis.