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Lecturer

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Course Summary This is a three or four day short course, which emphasizes the foundations of statistics; the collection of information, the summarization and presenting of information and the evaluation of sample information to build a model of the real world.

The course has no pre-requisites and is designed to be of help either the statistical novice or researcher requiring help with research design and data analysis.

The course is an applied course which highlights the problem solving steps to understand both the course material and research topics of interest.
   
Day 1 The principles of collecting and summarizing information will be presented, with emphasis being placed upon how to evaluate and correct problems associated with data collection.

The use of summary indices will be discussed with respect to presenting research findings. The interpretation of common indexes such as means and standard deviation will be explored in detail.
   
Day 2 The principles behind summary indexes will be expanded, to include which indexes should be used in summary tables, to present specific research findings.

The use of simple graphs to readily showcase research findings will be explored, with emphasis being placed upon understanding when and how to produce the most frequent and useful graphs in research.

Time will be devoted to fully interpreting research finding presented through tables and graphs.
   
Day 3 The concepts of measuring error within information will be presented and how these measures can be used to evaluate the strength of the information will be discussed.

How to determine real world measurements, based upon imperfect sample data, using error measurements will be thoroughly explored.

The fundamentals behind indexes such as standard error, confidence intervals and hypothesis testing will be discussed, and the applications of these techniques will be emphasized.
   
Day 4 Statistical software (SPSS) will be explored as a tool for simplifying data summarization and interpretation.

The presented course components, which form the foundations of statistics, will be applied to summarizing and interpreting real world data sets, in order to build a model of how real world situations work.