Overview:
SPSS offers more more options compares to using MS Excel in terms of speed, types and advanced analysis, and appearance. For those who deal with frequent data analysis in their daily tasks, mastering the use of SPSS will be an advantage. This training programme offers participants with both theoretical and practical experience in data entry and analysis of both descriptive and inferential statistics. This training programme is specifically focused on enhancing hands-on skills in data analysis using SPSS for quantitative research. Using primary data provided by participants and other sources, the participants will be guided to analyse and interpret data. An overview about the types of data and select the types of analyses will also be addressed in the training.
Objectives:
The main objective of the course is to enhance the knowledge and skills of the participants in data analysis and interpretation, especially using SPSS.
Main topics:
(1) Quick Tours of SPSS Menus (Participants will be guided for exploring SPSS menus to familiarise themselves with various features offered by SPSS); (2) Descriptive vs. Inferential statistics (To provide an overview of data analysis, the participants will be introduced to two types of statistical analyses: descriptive and inferential statistics); (3) Scales of measurement (During this session each participant will be briefed on different levels of measurement scales, i.e. nominal, ordinal, interval, and ratio. This understanding is very important in data analysis); (4) Selection of data analysis techniques (Referring to various factors including the objectives of research and characteristics of the data, this session will elaborate the decision making process in selecting appropriate data analyses); (5) Inputting data in SPSS (This session will provide participants with hands-on activities in entering raw data in SPSS. The facilitator will also demonstrate how to use various commonly used features in SPSS, including retrieving data from MS Excel); (6) Data analyses (This session will focus on descriptive statistical analyses such as central tendencies (mean, median, mode), variability (standard deviation, variance), and correlation. In addition, this session will have demonstration on how to analyse data using inferential statistics, such as Chi-square, t-test, Anova, and Regression; (7) Interpretation of findings from data analysis (Based on the findings from data analyses, this session will elaborate interpret the findings for general audiences).
- Manager: Dr Jaya Priah Kasinathan