---
title: "HW 9"
author: "Name here"
date: "Due March 29, 2018"
output: html_document
---

### Q1. (5 points) 
Continuing the example in the lecture notes, create a model to predict the number of bikes rented using the capital bikeshare dataset. Consider extracting information from the datetime variable to inform you model.

Summarize your model by describing the predictive ability and discussing which variables you included.

### Q2. (5 points) 
Continuing the example in the lecture notes, create a model to predict whether a passenger will survive on the titanic.

Summarize your model by describing the predictive ability and discussing which variables you included.