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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
14 Hours
Testimonials (5)
The variation with exercise and showing.
Ida Sjoberg - Swedish National Debt Office
Course - Econometrics: Eviews and Risk Simulator
the trainer had patience, and was eager to make sure we all understood the topics, the classes were fun to attend
Mamonyane Taoana - Road Safety Department
Course - Statistical Analysis using SPSS
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
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Tamil was held up helping other people, I could crack on with the next parts.
