Weka - Data mining Tool W eka is a tool for big data and data mining. It is used to various classification, experiments, and analysis over large data sets. Installation Guide -weka You can download Weka from here and follow the normal installation procedure. After completion you will get following window, here you can begin your classification or experiment on different data sets with Weka.
Introduction to Applied Statistics
Applied Statistics is a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters. In applying statistics such as a scientific, industrial, or societal problem, it is necessary to begin with a population or process to be studied. Populations can be diverse topics such as "all persons living in a country" or "every atom composing a crystal". It deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.
Software Environment
The S, S plus, Mat lab and R environments are an integrated suite of software facilities for data analysis and graphical display with the feature like an extensive and coherent collection of tools for statistics and data analysis, language for expressing statistical models and tools for using linear and non-linear statistical models, Graphical facilities for data analysis and display either at a workstation or as hard copy and an effective object-oriented programming language that can easily be extended by the user community. Most things done in S are permanent; in particular, data, results and functions are all stored in operating system files and referred to as objects.
Technically S is a function language. Elementary commands consist of either expressions or assignments. If an expression is given as a command, it is evaluated, printed and the value is discarded. An assignment evaluates an expression and passes the value to a variable but the result is not printed automatically. An expression can be as simple as 2 + 3 or a complex function call. Assignments are indicated by the assignment operator.
Example
for S and R Environments:
> 4 + 2
-> 6
>
sqrt(3/4)/(1/3 - 2/pi^2)
-> 6.6265
>
library(MASS)
>
data(chem) # needed in R only
>
mean(chem)
-> 4.2804
> m <-
mean(chem); v <- var(chem)/length(chem)
>
m/sqrt(v)
->3.9585
(Note: R is widely used open source language for applied statistics you can download R from here and start through normal installation procedure and directly use above example)
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