Course Outline
Using the program
- The dialog boxes
- input / downloading data
- the concept of variable and measuring scales
- preparing a database
- Generate tables and graphs
- formatting of the report
- Command language syntax
- automated analysis
- storage and modification procedures
- create their own analytical procedures
Data Analysis
- descriptive statistics
- Key terms: eg variable, hypothesis, statistical significance
- measures of central tendency
- measures of dispersion
- measures of central tendency
- standardization
- Introduction to research the relationships between variables
- correlational and experimental methods
- Summary: This case study and discussion
Requirements
Motivation to learn
Testimonials (8)
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
We were using road accident data for practicals
Maphahamiso Ralienyane - Road Safety Department
Course - Statistical Analysis using SPSS
The flexible and friendly style. Learning exactly what was useful and relevant for me.
Jenny
Course - Advanced R
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
That Haytham started with the basics and gave us enough time to do the examples and ensure that we were at the same page before we moved on to the next topic.
Jaco Dreyer - Africa Health Research Institute
Course - R Fundamentals
I really was benefit from the real life practical examples.
Wioleta
Course - Data and Analytics - from the ground up
the clarity with which he explained the entire course, as well as the willingness to return to the syllabus when necessary
Carlos Eloy - AMERICAN EXPRESS COMPANY MEXICO
Course - Data Analytics With R
Machine Translated
Very tailored to needs.