Summary Week 14

Using the code in section 4.4.1, create a generalized linear regression model. Extract the coefficient estimates into a tidy dataframe. ANSWER THE FOLLOWING QUESTIONS: 1. What does glr represent? 2. What is the standard error of the intercept? Use the code provided to create a coefficient plot. ANSWER THE FOLLOWING QUESTIONS: 3. Which two coefficients have the tightest confidence intervals. 4. Why does the y axis appear on the bottom of the chart while the x axis is on the left side? Use the code provided to fit a neural net model. Use the assessment set to make predictions. ANSWER THE FOLLOWING QUESTIONS: 5. What is a neural net? 6. In the first case, what is the probability that the person profiled is working? 7. In the first case, what is the probability that the person profiled is not working? 8. According to the data, is the person working? 8. What does the AUC tell us about how well the neural net model makes predictions? Submit a Word document with a screenshot of the coefficient plot with a time stamp. Explain what the plot is showing. Include the answers to these questions with the questions and numbers.