Requirements: 5.0+
Overview: Data science, Machine Learning and Artificial intelligence market is on boom.
Data science is basically converting structured or unstructured data in to insight, understanding and knowledge using scientific methods, processes and algorithms.
R is free open source language used as statistical and visualization software. It can deal with structured (organised) and semi-structured (semi-organised) data.
To learn R for data science we covered all aspects as follows:
Introduction
Data-Types in R
Variables in R
Operators in R
Conditional Statements
Loop statements
Loop Control Statements
R Script
R Functions
Custom Function
Data Structures
Atomic vectors
Matrix
Arrays
Factors
Data Frames
List
Import/Export Data – Assign values to data structure
Data Manipulation/Transformation
Apply function of Base R
dplyr Package
Statistics is crucial part to start learning in in this field.
Terms used in statistics is very strange and hard to understand for beginners, so we tried our best to explain these terms in very easy language for Novice, Intermediate or Advanced level guys in Data Science, Machine Learning, AI field.
Here we covered so many terms used in statistics like –
Hypotheses
Quantitative methods
Qualitative methods
Independent and Dependent variables
Predictor and Outcome variables
Categorical variables
Binary variable
Nominal variable
Ordinal variable
Continuous variable
Interval variable
Ratio variable
Discrete variable
Confounding variables
Measurement error
Validity and Reliability
Two methods of data collection
Types of variation
Unsystematic variation
Systematic variation
Frequency distribution
The Mean
The Median
The Mode
Dispersion in distribution of Data
Range
Interquartile range
Quartiles
Probability
Standard deviation
What’s New:
Hypothesis term explained more with –
Types of Hypothesis :
Null hypothesis
Alternate hypothesis
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Home Page: https://play.google.com/store/apps/details?id=com.androidassist.datascienceusingr.programminglanguage
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