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Data Analysis and Management Using R-Software

By: Cynet East Africa Consultancy

Kenya

20 - 24 May, 2024  5 days

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USD 1,020

Get 15.00% off

Venue: Nairobi

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Other Dates

Venue Date Fee  
Nairobi, Kenya 24 - 28 Jun, 2024 USD1020
Nairobi, Kenya 15 - 19 Jul, 2024 USD1020
Nairobi, Kenya 19 - 23 Aug, 2024 USD1020
Nairobi, Kenya 16 - 20 Sep, 2024 USD1020
Nairobi, Kenya 18 - 22 Nov, 2024 USD1020

Statistical Data Management and Analysis using R course provides an insight into quantitative data management and analysis (exploring, summarizing, statistical analyzing, visualizing). R is an open-source software with many features for quantitative data management and analysis.

The Expedition

Module 1: Basic statistical terms and concepts.

  • Basic data quality checks.
  • Basic exploratory data analysis procedures.
  • Basic Descriptive Statistics.
  • The core functions of inferential statistics.
  • Common inferential statistics.
  • Concepts and Software for Data Processing.
  • Data Processing using Census and Surveys Processing Software (CsPro).
  • Use of Mobile Phones for Data Collection and Processing.

Module 2: Introduction to R.

  • Why use R?
  • Obtaining and installing R.
  • Working with R.
  • Packages.
  • Batch processing.
  • Using output as input—reusing results.
  • Working with large datasets.

Module 3: Data Entry, Management and Manipulation with R

  • Creating a dataset.
  • Understanding datasets.
  • Data structures.
  • Data input.
  • Annotating datasets.
  • Useful functions for working with data objects.
  • Creating new variables.
  • Recoding variables.
  • Renaming variables
  • Missing values.
  • Date values.
  • Type conversions.
  • Sorting data.
  • Merging datasets.
  • Subsetting datasets.
  • Using SQL statements to manipulate data frames.


Module 4: Tabulations and Graphics with R.

  • Graphing Qualitative data.
  • Graphing Quantitative data.
  • Getting Started R Graphics.
  • Working with graphs.
  • A simple example.
  • Graphical parameters.
  • Adding text, customized axes, and legends.
  • Combining graphs.
  • Basic Graphs (Bar plots Pie charts, Histograms, Kernel density plots, Box plots, Dot plots).
  • Intermediate graphs (Scatter plots, Line charts, Correlograms, Mosaic plots).
  • Frequency and contingency tables.

Module 5: Quantitative Analysis using R.

  • Descriptive statistics.
  • Correlations.
  • t-tests.
  • Nonparametric tests of group differences.
  • Visualizing group differences.
  • Regression.
  • Analysis of Variance.
  • Power Analysis.
Nairobi May 20 - 24 May, 2024
Nairobi, Kenya 24 - 28 Jun, 2024
Nairobi, Kenya 15 - 19 Jul, 2024
Nairobi, Kenya 19 - 23 Aug, 2024
Nairobi, Kenya 16 - 20 Sep, 2024
Nairobi, Kenya 18 - 22 Nov, 2024

Registration: 09:00:am - 04:00:am

USD 1,020.00(All Inclusive)
USD 1,020.00(All Inclusive)
USD 1,020.00(All Inclusive)
USD 1,020.00(All Inclusive)
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Janet Cherono/Nancy Kemunto +254792972525/+254204401089

15% discount for a group of 3 and above
Benard Mwai
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