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For excel xlsReadWrite package is USED and for sas,SPSS ,STATA FOREIGN package is implemented.

For excel xlsReadWrite package is used and for sas,spss ,stata foreign package is implemented.

There are many WAYS to EXPORT the DATA into another formats like SPSS, SAS , STATA , EXCEL Spreadsheet.

There are many ways to export the data into another formats like SPSS, SAS , Stata , Excel Spreadsheet.

Pwr PACKAGE is USED for power analysis in R.

Pwr package is used for power analysis in R.

It is USED for experimental design .It is used to DETERMINE the EFFECT of given SAMPLE size.

It is used for experimental design .It is used to determine the effect of given sample size.

rbind() function is USED to merge two DATA frames VERTICALLY.

Eg.

Sum<- rbind(data frame1,data frame 2)

rbind() function is used to merge two data frames vertically.

Eg.

Sum<- rbind(data frame1,data frame 2)

Merge()function is used to merge two data FRAMES

Eg: SUM&LT;-merge(data frame1,data FRAME 2,by=’ID’)

Merge()function is used to merge two data frames

Eg: Sum<-merge(data frame1,data frame 2,by=’ID’)

Workspace is the CURRENT R working ENVIRONMENT which includes any user defined objects like vector, LISTS etc.

Workspace is the current R working environment which includes any user defined objects like vector, lists etc.

Packages are the collections of data, R functions and compiled CODE in a well-defined FORMAT and these packages are STORED in library.

Packages are the collections of data, R functions and compiled code in a well-defined format and these packages are stored in library.

For creating new VARIABLE assignment OPERATOR ‘<-’ is used For e.g. mydata$sum <- mydata$X1 + mydata$x2.

For creating new variable assignment operator ‘<-’ is used For e.g. mydata$sum <- mydata$x1 + mydata$x2.

There are 5 TYPES of SORTING algorithms are used which are:-

1. Bubble SORT
2. SELECTION Sort
3. Merge Sort
4. Quick Sort
5. Bucket Sort

There are 5 types of sorting algorithms are used which are:-

There are TWO METHODS that is collapsing DATA by using one or more BY VARIABLE and other is aggregate() function in which BY variable should be in list.

There are two methods that is collapsing data by using one or more BY variable and other is aggregate() function in which BY variable should be in list.

There are 5 data structure in R i.e. VECTOR, MATRIX, array which are of homogenous TYPE and other TWO are list and data frame which are heterogeneous.

There are 5 data structure in R i.e. vector, matrix, array which are of homogenous type and other two are list and data frame which are heterogeneous.

In 32 BIT system memory limit is 3GB but most VERSIONS limited to 2GB and in 64 bit system memory limit is 8Tb.

In 32 bit system memory limit is 3Gb but most versions limited to 2Gb and in 64 bit system memory limit is 8Tb.

rcmdr COMMAND is USED to start the R commander GUI.

rcmdr command is used to start the R commander GUI.

Seq(4) means VECTOR from 1 to 4 (c(1,2,3,4)) whereas seq_along(4) means a vector of the length(4) or 1(c(1)).

Seq(4) means vector from 1 to 4 (c(1,2,3,4)) whereas seq_along(4) means a vector of the length(4) or 1(c(1)).

LAPPLY is used to show the output in the FORM of list whereas SAPPLY is used to show the output in the form of VECTOR or data frame.

lapply is used to show the output in the form of list whereas sapply is used to show the output in the form of vector or data frame.

DATAFRAME can contain DIFFERENT type of DATA but matrix can contain only SIMILAR type of data.

Dataframe can contain different type of data but matrix can contain only similar type of data.

COR-relations is PRODUCED by cor() and COVARIANCES is produced by COV() FUNCTION.

Cor-relations is produced by cor() and covariances is produced by cov() function.

For adding two DATASETS rbind() function is used but the COLUMN of two datasets must be same.

Syntax: rbind(x1,x2……) where x1,x2: VECTOR, matrix, data frames.

For adding two datasets rbind() function is used but the column of two datasets must be same.

Syntax: rbind(x1,x2……) where x1,x2: vector, matrix, data frames.

The advantages are:-

1. It is used for managing and manipulating of DATA.
2. No license restrictions
3. Free and open source software.
4. Graphical capabilities of R are GOOD.
5. Runs on many OPERATING SYSTEM and different hardware and also run on 32 & 64 bit processors etc.

The advantages are:-

Transpose is USED for RESHAPING of the data which is used for analysis. Transpose is PERFORMED by t() FUNCTION.

Transpose is used for reshaping of the data which is used for analysis. Transpose is performed by t() function.

Subset() is used to SELECT the variables and observations and SAMPLE() function is used to GENERATE a RANDOM sample of the size N from a dataset.

Subset() is used to select the variables and observations and sample() function is used to generate a random sample of the size n from a dataset.

In R missing values are represented by NA which should be in CAPITAL LETTERS.

In R missing values are represented by NA which should be in capital letters.

with() FUNCTION applies an EXPRESSION to a dataset.

#with(DATA,expression)

By() function applies a function t each LEVEL of a FACTORS.

#by(data,factorlist,function)

with() function applies an expression to a dataset.

#with(data,expression)

By() function applies a function t each level of a factors.

#by(data,factorlist,function)

The disadvantages are:-

1. Lack of STANDARD GUI
2. Not good for big data.
3. Does not PROVIDE SPREADSHEET view of data.

The disadvantages are:-

It is used to determine that the means of TWO GROUPS are equal or not by USING t.test() FUNCTION.

It is used to determine that the means of two groups are equal or not by using t.test() function.

By using # at the STARTING of the LINE of code like #DIVISION commands are WRITTEN.

By using # at the starting of the line of code like #division commands are written.

R is a programming LANGUAGE which is USED for developing STATISTICAL SOFTWARE and data analysis.

R is a programming language which is used for developing statistical software and data analysis.

Combine the DATA, code and analysis results in a SINGLE document using knitr for Reproducible research DONE. Helps to verify the findings, add to them and ENGAGE in conversations. Reproducible research makes it easy to redo the experiments by INSERTING new data values and applying it to different various problems.

Combine the data, code and analysis results in a single document using knitr for Reproducible research done. Helps to verify the findings, add to them and engage in conversations. Reproducible research makes it easy to redo the experiments by inserting new data values and applying it to different various problems.

R provides to import data in R language. To BEGIN with the R commander GUI, user should type the commands in the command Rcmdr into the console.

Data can be imported in R language in 3 ways such as:

1. Select the data set in the dialog box or ENTER the name of the data set as required.
2. Data is entered directly using the editor of R Commander via Data->New Data Set. This works good only when the data set is not too large.
3. Data can also be imported from a URL or from PLAIN text file (ASCII), or from any statistical PACKAGE or from the CLIPBOARD.

R provides to import data in R language. To begin with the R commander GUI, user should type the commands in the command Rcmdr into the console.

Data can be imported in R language in 3 ways such as: