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Course Outline
Preparation of a database for analysis
- management of data collection
- operations on variables
- transforming the variables selected functions (logarithmic, exponential, etc.)
Parametric and nonparametric statistics, or how to fit a model to the data
- measuring scale
- distribution type
- outliers and influential observations (outliers)
- sample size
- central limit theorem
Study the differences between the characteristics of statistical
- tests based on the average and media
Analysis of correlation and similarities
- correlations
- principal component analysis
- cluster analysis
Prediction - single regression analysis and multivariate
- method of the least squares
- Linear Model
- instrumental variable regression models (dummy, effect, orthogonal coding)
Statistical Inference
Requirements
Knowledge of SPSS and the basis of statistics. Course participant should complete the training of SPSS Statistics Predictive Analytics Software.
28 Hours
Testimonials (5)
We were using road accident data for practicals
Maphahamiso Ralienyane - Road Safety Department
Course - Statistical Analysis using SPSS
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
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
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
The flexible and friendly style. Learning exactly what was useful and relevant for me.
