About ABIS
All CoursesbalkjeGeneral courses » Introduction to HW & SW » Soft skills » TracksOperating systems » MVS - z/OS » Linux - UNIX » Mac OS X » iPad and iPhone iOSDatabases and middleware » Relational databases & SQL » Db2 for z/OS » Db2 for LUW » Oracle » SQL Server » MySQL & MariaDB » IMS » CICS » IBM MQ » WebSphere » Data Science, Big Data and AnalyticsApplication development » Methods and techniques » TOGAF » PRINCE2 » Agile development and Scrum » Programming languages » Internet development » Object Oriented systems » Java » Development tools » SAS » XML » SOA & web servicesSystems management » ITIL » SecuritybalkjePractical informationRegistration 
Statistics fundamentals

Statistics is about extracting meaning from data. We will focus on the fundamentals of statistics, which may be broadly described as the techniques to collect, clarify, summarize, organize, analyze, and interpret numerical information.

This course will cover visualization, probability, estimation, hypothesis testing, regression and other topics that will help you learn the basic methods of understanding data with statistics.


No public sessions are currently scheduled. We will be pleased to set up an on-site course or to schedule an extra public session (in case of a sufficient number of candidates). Interested? Please contact ABIS.

Intended for

All who want to learn the fundamentals of statistics. Also participants who already got a basic statistics course in the past but who want a refresh. The course is especially useful for students who want to use statistical tools in softwares such as Python, R and SAS.


No previous knowledge of statistics is required. Familiarity with basic algebra is however necessary.

Main topics

scatter plot, bar chart, histogram, box plot

mean, median, quartiles, mode, outliers

variance, standard deviation

standard score

probability of disjoint/non-disjoint events

conditional probability and Bayes' Rule

normal distribution: z-score, probability table

Bernouilli distribution

binomial distribution

point estimates

standard error of the mean

confidence intervals

hypothesis testing

t-distribution (one-sample means, paired data, difference of 2 means)

comparing many means with ANOVA

correlation, covariance

regression of standard scores

Training method

Classroom training with practical exercises.


2 days.

Course leader

Paul Veugelen.