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 (7)
Very tailored to needs.
Yashan Wang
Course - Data Mining with R
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
Well thought out and high grade planning materials.
Andrew - Office of Projects Victoria - Department of Treasury & Finance
Course - Forecasting with R
Wasn't boring, the trainer could keep the attention, the topics were covered in depth.
Marta - Ministerstwo Zdrowia
Course - Advanced R Programming
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
At the end of the class, we had a great overview of the language, we were provided tools to continue learning and were provided suggestions on how to continue learning. We covered AI/ML information.