Lesson 3 ======================================================== *** ### What to Do First? Notes: *** ### Pseudo-Facebook User Data Notes: ```{r Pseudo-Facebook User Data} ``` *** ### Histogram of Users' Birthdays Notes: ```{r Histogram of Users\' Birthdays} install.packages('ggplot2') library(ggplot2) ``` *** #### What are some things that you notice about this histogram? Response: *** ### Moira's Investigation Notes: *** ### Estimating Your Audience Size Notes: *** #### Think about a time when you posted a specific message or shared a photo on Facebook. What was it? Response: #### How many of your friends do you think saw that post? Response: #### Think about what percent of your friends on Facebook see any posts or comments that you make in a month. What percent do you think that is? Response: *** ### Perceived Audience Size Notes: *** ### Faceting Notes: ```{r Faceting} ``` #### Let’s take another look at our plot. What stands out to you here? Response: *** ### Be Skeptical - Outliers and Anomalies Notes: *** ### Moira's Outlier Notes: #### Which case do you think applies to Moira’s outlier? Response: *** ### Friend Count Notes: #### What code would you enter to create a histogram of friend counts? ```{r Friend Count} ``` #### How is this plot similar to Moira's first plot? Response: *** ### Limiting the Axes Notes: ```{r Limiting the Axes} ``` ### Exploring with Bin Width Notes: *** ### Adjusting the Bin Width Notes: ### Faceting Friend Count ```{r Faceting Friend Count} # What code would you add to create a facet the histogram by gender? # Add it to the code below. qplot(x = friend_count, data = pf, binwidth = 10) + scale_x_continuous(limits = c(0, 1000), breaks = seq(0, 1000, 50)) ``` *** ### Omitting NA Values Notes: ```{r Omitting NA Values} ``` *** ### Statistics 'by' Gender Notes: ```{r Statistics \'by\' Gender} ``` #### Who on average has more friends: men or women? Response: #### What's the difference between the median friend count for women and men? Response: #### Why would the median be a better measure than the mean? Response: *** ### Tenure Notes: ```{r Tenure} ``` *** #### How would you create a histogram of tenure by year? ```{r Tenure Histogram by Year} ``` *** ### Labeling Plots Notes: ```{r Labeling Plots} ``` *** ### User Ages Notes: ```{r User Ages} ``` #### What do you notice? Response: *** ### The Spread of Memes Notes: *** ### Lada's Money Bag Meme Notes: *** ### Transforming Data Notes: *** ### Add a Scaling Layer Notes: ```{r Add a Scaling Layer} ``` *** ### Frequency Polygons ```{r Frequency Polygons} ``` *** ### Likes on the Web Notes: ```{r Likes on the Web} ``` *** ### Box Plots Notes: ```{r Box Plots} ``` #### Adjust the code to focus on users who have friend counts between 0 and 1000. ```{r} ``` *** ### Box Plots, Quartiles, and Friendships Notes: ```{r Box Plots, Quartiles, and Friendships} ``` #### On average, who initiated more friendships in our sample: men or women? Response: #### Write about some ways that you can verify your answer. Response: ```{r Friend Requests by Gender} ``` Response: *** ### Getting Logical Notes: ```{r Getting Logical} ``` Response: *** ### Analyzing One Variable Reflection: *** Click **KnitHTML** to see all of your hard work and to have an html page of this lesson, your answers, and your notes!