Using the normal model: standardising unstandardising standard normal curve using Table Z.Įxploring relationships between variables: scatterplots correlation and regression residuals. However, the mathematical underpinnings of the methods are not covered in detail in this course other statistics courses cover this aspect.Įxploring and understanding data: variables and values types of data introduction to SPSS Describing distributions: quantitative data graphs of distributions summary statistics.
#IBM SPSS STATISTICS STANDARD GRAD PACK 20.0 SOFTWARE#
Core components of the course include the use of a popular statistical software package (SPSS) and the development of problem-solving skills relevant to many disciplines. Emphasis is on the understanding of the concepts and principles associated with statistical methods and skills required for the analysis of real-life for quantitative studies. This course focuses primarily on the graphical and numerical methods of data analysis including descriptive and inferential statistics for post-graduate students. The course is aimed at developing statistical thinking and literacy for students from diverse disciplines, and is a pre-requisite for most high-level statistics courses. This course aims to provide post graduate students with no or limited knowledge of statistics, the fundamental statistical concepts, methods and data analysis skills necessary to undertake quantitative research and interpret subsequent results.
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