Frequency table and line plot

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Vocabulary ,[object Object],[object Object]

Frequency Table Example ,[object Object]

Frequency Table ,[object Object],[object Object],[object Object]

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Background: This course is all about data visualization. However, we must first have some understanding about the data that we are using to create the visualizations. For this assignment, each group will be given its unique dataset to work with. That same dataset will be used for both part 1 and part 2 of this assignment. Your Assignment : Part 1 - Data Analysis with RStudio Provide screen shots that show analysis of your dataset. For each screen shot, please show comment lines that describes what the next line(s) of code is to achieve, the code in proper syntax for R , and the computed results that R produces. Analyzing your data:Watch the video included in this week's Residency material to learn the simple commands to conduct basic data analysis with RStudio.Use RStudio to generate results - create screen shots and then paste to a MS word document with the basic data analysis of your dataset. Remember to use a comment line (#) that explains each R instruction . Example: (#sets the working directory). Commands ( setwd , dim , head , tail , structure , summary, cor, transform, subset). First, set your working directory (command - setwd OR use drop down from RStudio Session tab. Load your dataset into RStudio and examine its structure - read.csv OR select your object file from RStudio Files pane. Other commands to use: dim , head , tail , structure , and summary (provide comment lines; the R code; and results as screen shot #1) View your original dataset - examine each field/grouping in the data - decide whether each field is: "categorical" or "continuous" data (add this also to screen shot #1) Create a correlation of stats for the dataset. R requires categorical fields to be 0/1 instead of no/yes; also, fields must be numeric instead of string - Hint: might be necessary to Transform some fields. If so, create a new version of your dataset with these transformations then do correlation on transformed data - commands: transform and cor (provide as screen shot #2) What is the Min, Max, Median, and Mean of a continuous value field in your data? (provide also as screen shot #2) What is the correlation values between all fields in your dataset? (provide as screen shot #3) Create a subset of the dataset with only at least two field in your dataset - commands: subset , cor (provide also as screen shot #3) These three (3) screen shots containing the required data details should be placed in a MS Word document and labeled as Part 1 - Dataset Analysis . Part 2 - Data Visualizing with RStudio Background: As we have learned, a lot of thought goes into the design of a visualization. In this examination of your data and its visualization, we review how data types influence the choice of graphing - see "Selecting a Graph" hand-out (in this folder).Provide screen shots that shows graphs and charts of your dataset (Do NOT use ggplot2 or other R package features - we will learn and use these advance.

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