Data analysis and analytics. Uncover insights and transform your organisation.

Evolve your understanding of statistics and statistical analyses with this practical course focused on using the SPSS package. You will learn the practical steps involved in carrying out research involving statistical analysis. The course covers statistical terminology and concepts, selection and conduct of appropriate statistical tests and their interpretation. Complex mathematical and technical terms are kept to a minimum. Attention will be given to both statistical significance (p-values), as well as practical significance (effect size). This course goes beyond descriptive statistics but doesn’t look at more advanced statistical methods.

This course is for you if you are in a profession that requires rigorous statistical analysis in order to make sound decisions and judgements This workshop is suitable for a range of disciplines, including business and management, education, medicine, health or government or non-government services.

The course focus is on using SPSS but the concepts are transferable to any statistical package.

Aims

This course aims to provide you with many of the essential skills required in analysing, interpreting and reporting data using SPSS.

Outcomes

By the end of this course, you should be able to:

• identify different types of data (nominal, ordinal and continuous)
• define a ‘researchable question’ relevant to your area of research
• report your data using the appropriate descriptive statistics
• identify the difference between descriptive and inferential statistics
• identify the difference between statistical significance and practical significance
• interpret p-values, odds ratios (ORs) and confidence intervals
• select the appropriate statistical test based on your research questions and the type of data
• use SPSS to conduct and interpret correlation, t-tests, General Linear Models (covering ANOVA and linear regression techniques) and logistic regression.

Content

• The different types of data, how to report them using descriptive statistics and how data types inform the appropriate statistical test to use.
• The importance of establishing research questions as a framework for determining the appropriate test(s), and for interpreting and communicating results.
• The difference between statistical significance (p-value, the likelihood the results are ‘due to chance’) and practical significance (effect size, whether the results have any practical value or mean anything to the relevant stakeholders) and how both are necessary in order to draw meaningful conclusions.
• The role of confidence intervals in helping the researcher understand the association between sample and population, the precision of their data, statistical significance and effect size.
• How it all comes together – using SPSS and the inferential statistical tests correlation, t-tests, General Linear Models and logistic regression to answer research questions through interpretation of p-values, effect sizes and confidence intervals.

Intended audience

This course is suitable for you if:

• you are just starting out with statistical analysis
• you want to strengthen your skills in statistical analysis and/or using SPSS.

Prerequisites

Previous experience using SPSS is preferred but not essential. Some participant awareness or knowledge of how research in their particular discipline is conducted or reported, as well as previous exposure to statistical analysis, even if very informal or basic, is preferred but not essential.

Delivery mode

Face-to-face, presenter-taught training in a computer lab

Materials

A link to access and download online course materials is provided. Please bring a USB flash drive to class if you would like to make a copy of your work or any relevant class materials. Alternatively, you can save these to a cloud storage space or email them to your personal email address.