https://classroom.github.com/a/tfkxd1ES

**Due: 2020-05-04 by 11:59pm**

Use the dataset finches, which measures various physical characteristics of Galapagos island finches, all in centimeters, for finches living on various islands.

Pick 1 numeric response variable and 1 numeric explanatory variable, and use them throughout. Your only option for categorical explanatory variable is `island`

, so please use it when appropriate.

Means by island.

Make transparent violins on a plot with your response variable on the y-axis and the categorical variable on the x-axis.

Write a complete English sentence about the plot.

Simple Linear Regression.

Make a scatter plot of your two numerical variables, and put a line through the data using

`geom_smooth(...)`

.Write a complete English sentence about the plot.

Unique intercepts by island.

Fit a multiple linear regression model with unique intercepts by levels of the categorical explanatory variable island.

Interpret the intercept for Santa Cruz in context of the data. If the interpretation does not make sense, explain why.

Interpret the slope in context of the data. Be sure to say explicitly which island(s) the slope applies to.

Choose a value along the x-axis, call it

`xnew`

. Create bootstrap confidence intervals for predictions at`xnew`

for two different islands.Interpret your two confidence intervals in context of the data.

Make an informative conclusion about finches on the two different islands based on your confidence intervals.

Unique slopes by island.

Fit a multiple linear regression model with unique slopes, and only one intercept, by levels of the categorical explanatory variable island.

Which island has the smallest (in absolute value) slope?

Interpret this slope in context of the data.

Unique intercepts and slopes by island.

Fit a multiple linear regression with unique slopes and unique intercepts by levels of the categorical explanatory variable island.

Make an appropriate plot for this model.

Write a complete English sentence about the plot.