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I don’t know how to handle this Computer Science question and need guidance.

/0x4*

**ITS836 Assignment 1: Data Analysis in R**

**Read** the income dataset, “zipIncomeAssignment.csv”, into R. (You can find the csv file in iLearn under the Content -> Week 2 folder.)
- Change the column
**names** of your data frame so that *zcta* becomes *zipCode* and *meanhouseholdincome* becomes *income*.
- Analyze the
**summary** of your data.What are the mean and median average incomes?
**Plot** a scatter plot of the data.Although this graph is not too informative, do you see any outlier values?If so, what are they?
- In order to omit outliers, create a
**subset** of the data so that:
- What’s your new mean?
- Create a simple
**box plot** of your data.Be sure to add a title and label the axes.
- Make a
*ggplot* that consists of just a scatter plot using the function *geom_point()* with position = “*jitter” * so that the data points are grouped by zip code.Be sure to use *ggplot*’s function for taking the log_{10} of the y-axis data.(Hint: for *geom_point*, have *alpha*=0.2).
- Create a new
*ggplot* by adding a box plot layer to your previous graph.To do this, add the* ggplot *function *geom_boxplot()*.Also, add color to the scatter plot so that data points between different zip codes are different colors.Be sure to label the axes and add a title to the graph.(Hint: for *geom_boxplot*, have *alpha*=0.1 and *outlier.size*=0).
- What can you conclude from this data analysis/visualization?

$7,000 < income < $200,000 (or in R syntax , income > 7000 & income < 200000)

HINT: Take a look at: https://www.tutorialspoint.com/r/r_boxplots.htm (specifically, Creating the Boxplot.) Instead of “mpg ~ cyl”, you want to use “income ~ zipCode”.

In the box plot you created, notice that all of the income data is pushed towards the bottom of the graph because most average incomes tend to be low.Create a new box plot where the y-axis uses a log scale.Be sure to add a title and label the axes. For the next 2 questions, use the *ggplot* library in R, which enables you to create graphs with several different types of plots layered over each other.

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