Create the following matrix “mat” in R 1.0 0.5 0.1 0.1 0.1 1.0 0.1 0.1 0.1 0.1 1

Question

Create the following matrix “mat” in R

1.0

0.5

0.1

0.1

0.1

1.0

0.1

0.1

0.1

0.1

1.0

0.1

0.1

0.1

0.1

1.0

Rename rows to R1, R2, R3, and R4.

Change the element at row 2 and column 4 to missing value.

Read in worms.txt as a R data set.

What object is it?

Write code to find out what the variable names are.

How many rows and columns in “Worms”?

What is the mean of “Area”?

How many “Meadow” in “Vegetation”?

Toss a six-sided die twice. The sample space consists of all ordered pairs (i; j)

of the numbers 1; 2; … ; 6, that is, S = f(1; 1); (1; 2); … ; (6; 6)g. We know the size of sample space is 36. Let A = outcomes matching and B = sum of outcomes at least 8. Using R to find P(A|B) and P(B|A).

1.0

0.5

0.1

0.1

0.1

1.0

0.1

0.1

0.1

0.1

1.0

0.1

0.1

0.1

0.1

1.0

Explanation / Answer

For cleating the matrix use thia comand:

mat <- matrix( c(1.0,0.5,.1,0.1,0.1,1.0,0.1,0.1,0.1,0.1,1.0,0.1,0.1,0.1,0.1,1.0), nrow = 4, byrow=TRUE)

Rename rows to R1, R2, R3, and R4. as follow

rownames = c("R1", "R2", "R3", "R4")
mat <- matrix( c(1.0,0.5,.1,0.1,0.1,1.0,0.1,0.1,0.1,0.1,1.0,0.1,0.1,0.1,0.1,1.0), nrow = 4, byrow=TRUE,dimnames = list(rownames))

Change the element at row 2 and column 4 to missing value.:

mat["R2",4]=NA

Read in worms.txt as a R data set.

Suppose you want to read in variable "M" the give the comand

where sep=" " specify how the data was separted in file "worms.txt"

For your problem use the above said comand to read data from "worms.txt" in variable "M"

What object is it?

In R everything is an object. It totaly depend how you have read the file "worms.txt" in R. In abovle solution it is a "data frames" is a "tabular data object"

Write code to find out what the variable names are.:

M[1,]

output:

V1 V2 V3 V4 V5 V6 V7
1 Field.Name Area Slope Vegetation Soil.pH Damp Worm.density

How many rows and columns in “Worms”?:

For number of columns

ncol(M)

output:7 for above example

For number of rows:

nrow(m)

output:21

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