What are some key R Programming terms?

1.) c( )

2.) matrix ( )

3.) str ( ) colnames/type/levels if factor

4.) class ( )

5.) factor ( )

6.) levels ( )

7.) setwd ( )

8.) glass [glass$Type = = 1, ]

9.) length ( )

sample size

10.) Indexing using [ ]

11.) data

col1

col2

col3

12.) data[data$col1 1,]

13.) dbinom P(X=x)

14.) pbinom P(X <= x)

15.) qbinom P(X < k) = #

16.) rbinom

17.) bnom

18.) norm

19.) gamma

20.) t

21.) qqnorm ( )

22.) abline ( )

23.) hist ( )

24.) boxplot ( )

a. ex. Group by things boxplot (number values ~ glass$Type)

25.) par(mfrow = c( ,))

26.) is.na ( ) *important*

27.) for ( ) *Important one*

28.) print ( )

29.) ?? log

30.) ?? histogram

31.) Read.csv *important one*

WEVE SEEN ALL THESE QUESTIONS BEFORE

Question 1: 2 Parts (Worksheet 3)

Question 2: 1 Part (Bonus)

Question 3: 1 Part

***Question 4: Work with dataset (Parts a f) (Big one) (If you dont know the parts before, then you cant do the parts later on) (part e = bonus)

Permutations:

4P6: factorial(6) / factorial(6-4) = 360

Combinations: use choose function

13C4: 4 hearts 1 club

choose(13,4) * choose(13,1) / choose(52,5) = 0.003576431

or

combn(52,5)

ncol(x)

[1] 2598960

BINOMIAL FUNCTION:

sum(pbinom(X VALUE 3,SAMPLE 100,PROB 1/100))

Probability for greater(1-pbinom):

P(X >x1)

1 - pbinom(x1, sample, prob)

Probability for less than:

P(X 3).

pbinom(3, sample100, prob 0.05) = 0.2578387

continuous uniform distribution from 1 to 5. Determine the conditional

probability P(X > x1 | X x2)

(punif(x2,1,5) - punif(x1,1,5)) / punif(x2,1,5) = 0.5

Area under curve:

pnorm(x,mean,sd) always gives the area TO THE LEFT of x

to get area to right do 1- pnorm func

z = 1.43.

pnorm(1.43, mean = 0, sd = 1, lower.tail = TRUE) = 0.9236415

between z = x1 and z = x2

pnorm(x2, mean = 0, sd = 1) - pnorm(x1, mean = 0, sd = 1)

value of k such that P(Z < k) = x1.

qnorm(x1, mean = 0, sd = 1, lower.tail = TRUE)

P(x1 < X < x2)

pnorm(x2, mean, sd) - pnorm(x1, mean,sd)

Percentiles:

95th percentile from a Standard Normal Distribution.

qnorm(0.95)

Percentiles with t-distrib:

99th percentile from a t-distribution with n degrees of freedom.

qt(0.99, n)

from x1 to x2 (inclusive)

P(x1 X x2) = P(X x2) P(X < x2-1)

Pbinom

Pt function

lower.tail

logical; if TRUE (default), probabilities are P[X x], otherwise, P[X > x].*

quantile(file name,0.95)

95%

Bla bla

Summary function gives

Min. :

1st Qu.:

Median :

Mean :

3rd Qu.:

Max. :

QQPLOTS:

Turn it into data frame first

df<-data.frame(LatexPaint)

qqnorm(df$CloumnNAme)

qqline(df$Column name,col='red')

BOXPLOT

Boxplot(df, horizontal=T)

Pick specific columns and get their data:

tapply(pollutants$CO, pollutants$NOX, summary)