Please write the entire R program in Rstudios

Data frame in Janka.xlsx files contain two meaningful attributes. Please write the R program that reads file janka.csv and then computes:

1. mean, variance and standard deviation for every attribute

2. covariance between attributes (i.e. covariance matrix),

3. histograms for each attribute assuming samples are drawn from probability distribution

4. Experimental CDF for each attribute and plot it

5. quintiles for each attribute with a step 0.1

6. quantile-to-quintile plot between attributes

Plots should be saved to files named as a plot itself (e.g. histogram-your last name.jpg) Assume that you are reading files from and writing files to Rs working directory. The program should be submitted as saved in the file Janka-Vizual-your last name.R Notes: To read .xlsx file into R you may need to install xlsx package. Then use the following operators: require(xlsx) data = read.xlsx2("janka.xlsx", 1) where data is a variable that will contain imported data as data.frame type. However, if you do it literally as described above then all your attributes will default to being factors while you need numerical values. So read carefully description of read.xlsx2 and use it properly.

Experimental CDF is computed by ecdf built-in function/object. You can use plot method on it to plot eCDFs. Use ? function to learn about ecdf and its methods.

There are 2 methods of saving plots in .jpg files: 1. Saving from R-studio. Click on export in plot pane and save 2. Use jpeg operator, e.g. jpeg("ecdf-density.jpg"). If you do so then after saving the plot you need to turn the device invoked for the plot off by including dev.off() operator.

All other functions are described

- The following is the data in file that is janka in MS excel:

	Density	Hardness
1	24.7	484
2	24.8	427
3	27.3	413
4	28.4	517
5	28.4	549
6	29.0	648
7	30.3	587
8	32.7	704
9	35.6	979
10	38.5	514
11	38.8	1070
12	39.3	1020
13	39.4	1210
14	39.9	989
15	40.3	1160
16	40.36	1010
17	40.7	1100
18	40.7	1130
19	42.9	1270
20	45.8	1180
21	46.9	1400
22	48.2	1760
23	51.5	1710
24	51.5	2010
25	53.4	1880
26	56.0	1980
27	56.5	1820
28	57.3	2020
29	57.6	1980
30	59.2	2310
31	59.8	1940
32	66.0	3260
33	37.4	2700
34	68.8	2890
35	69.1	2740
36	69.1	3140