From the course: Machine Learning with Logistic Regression in Excel, R, and Power BI

Unlock the full course today

Join today to access over 24,800 courses taught by industry experts.

Using statistics

Using statistics

From the course: Machine Learning with Logistic Regression in Excel, R, and Power BI

Start my 1-month free trial Buy for my team

Using statistics

“

- [Instructor] As we're building our logistic regression model, we want to pay attention to the model statistics so we know that if the model we set up is a good fit. There are entire courses in the library that focus on statistics, but understanding the outcomes and the statistics that go along with the logistic regression model can help us develop better models in the future because we're able to put our numbers in the proper context. We can use the logit results return when we solve that maximum likelihood estimate or MLE, and our logistic regression models will further analyze the fit and statistical significance of our model. Let's run just the first three lines of code to see what the outcome is. The Deviance Residuals are the difference between our model and the ideal fit for this logistic regression model. We see our numbers seem reasonable and in line with the log likelihood distances we calculated in our Excel…

Contents