讲解R编程语言、csv讲解留学生、解析R语言程序、R设计解析

Submission:

R script file with R commands/comments showing how you got what was requested and a Word File that shows output and answers questions.

All graphs should have labels for x-axis (xlab), y-axis (ylab), main title (main)

All requested R output must be transferred to WORD.

Data Sets required:

1.boston_corrected_f2013.csv

2.mpgdata.csv

3.lakeveg.csv

4.dodata.csv

Working Directory: Lab3 (all files should be in working directory called Lab3)

Script File Format – all code should be described:

#Lab 3

#Your name

# description of step code

Part A: Dataset 1: boston_corrected_f2013.csv, please load as boston

Examine the two variables RM and AGE.

AGE variable:

1. Create 2 stripcharts of variable with data shown as stacked not overlapped.

Stripchart No.1 should be all values in one line.

Stripchart No. 2 should use the CHAS variable to split data.

Q1. What do the plots show? – ie any clumps, even distribution.

Q2. Did adding CHAS variable reveal any patterns in the data? (compare two lines within plot).

2. Create 2 histograms of variable.

Histogram 1: standard using Scott method for bin calculation

Histogram 2: Relative Frequency (also use Scott for starting point)

3. Create a Quantile plot (method 2 or method 3, make sure to annotate R)

4. Calculate Five number summary

5. Create a Box and Whisker Plot with Whiskers to Adjacent points (1.5 setting)

6. Calculate: Mean, Median, Estimated Mode – please summarize in a table

Q3. How would you describe the distribution of this variable based on what you have plotted and calculated?

Q4. Look at the Quantile-Quantile plot for this variable in lab on bottom of page 17, how do the two distributions compare?

RM variable (basically same as above)

7. Create 2 stripcharts of variable with data shown as stacked not overlapped.

Stripcharts No.1 should be all values in one line.

Stripcharts No. 2 should use the CHAS variable to split data.

Q5. What do the plots show? – ie any clumps, even distribution.

Q6. Did adding CHAS variable reveal any patterns in the data? (compare two lines within plot).

8. Create 2 histograms of variable.

Histogram 1: standard using Scott method for bin calculation

Histogram 2: Relative Frequency (also use Scott for starting point)

9. Create a Quantile plot (method 2 or method 3, make sure to annotate R)

10. Calculate Five number summary

11. Create a Box and Whisker Plot with Whiskers to Adjacent points (1.5 setting)

12. Calculate: Mean, Median, Estimated Mode – please summarize in a table

Q7. How would you describe the distribution of this variable based on what you have plotted and calculated?

13. Plot a Quantile-Quantile plot of AGE on X and RM on Y.

Q8. What does this plot show?

Part B:  Dataset 2: mpgdata.csv, please load as mpgdata

MPG variable (check case)

14. Create 2 stripchart of variable with data shown as stacked not overlapped.

Stripchart No.1 should be all values in one line.

Stripchart No. 2 should use the Origin a variable to split data.

15. Create a standard histogram, document method used for bins.

16. Do a Box and Whiskers Plot, show min/max values ( 0 setting )

Q9. Which of the above provides you with the best idea of data distribution.

Q10. How would you describe the data?

Part C:  Dataset 3: vegdata.csv, please load as vegdata

17. Calculate: Frequency, Percent Frequency and Cumulative Percent Frequency and summarize in a table in Word.

Part D:  Dataset 4: dodata.csv, please load as dodata

18. Create histogram but put into a variable so you can examine counts.

Q11. What happens when you set right=FALSE?