{"id":9649972,"date":"2019-06-01T00:20:00","date_gmt":"2019-05-31T21:20:00","guid":{"rendered":"http:\/\/iee.it.teithe.gr\/course\/%ce%b5%ce%b9%cf%83%ce%b1%ce%b3%cf%89%ce%b3%ce%ae-%cf%83%cf%84%ce%b7%ce%bd-%ce%b1%ce%bd%ce%b1%ce%bb%cf%85%cf%84%ce%b9%ce%ba%ce%ae-%cf%84%cf%89%ce%bd-%ce%b4%ce%b5%ce%b4%ce%bf%ce%bc%ce%ad%ce%bd%cf%89\/"},"modified":"2025-02-09T22:09:27","modified_gmt":"2025-02-09T19:09:27","slug":"1741","status":"publish","type":"course","link":"https:\/\/www.iee.ihu.gr\/en\/course\/1741\/","title":{"rendered":"Introduction to Data Analytics"},"content":{"rendered":"

The R\/RStudio Environment
\nThe Comprehensive R Archive Network (CRAN) Repository
\nTh eR Language:
\n— Data Types
\n— Objects
\n— Vectors and Lists
\n— Matrices
\n— DataFrames
\n— Vectorization
\n— The IF-ELSE Clause
\n— FOR, REPEAT, and WHILE Commands
\n— Functions
\n— Data Importing\/Exporting
\n— RDBMS Coupling (MySQL, PostgreSQL)
\nExtract-Transform-Load (ETL) Operations
\n–Data Cleaning and Homogenization
\n— Noise
\n— Missing Values
\n— Data Discretization and Data Standardization
\n— Data Transformation
\nDescriptive Statistics \/ Exploratory Analysis
\n— Mean, Median, Standard Deviation
\n— Quartiles
\n— Interquartile Range (IQR)
\n— Frequency Tables
\n— Bar Charts
\n— Histograms
\n— Pie Charts
\n— Boxplots
\n— Scatter Plots
\n— Contingency Tables
\nSimulation of Data Distributions: Density Plots, Data Sampling
\nThe Pearson Correlation Coefficient<\/p>","protected":false},"author":1,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"class_list":["post-9649972","course","type-course","status-publish","hentry"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t