For those undertaking research in the social sciences, an ability to handle data is an essential skill. Many researchers in social sciences use SPSS to perform data analysis, but often a formal training in the use of the software and how to interpret the output is severely lacking. SPSS is a highly interactive, easy to use, windows-based statistical tool that is perfectly suitable for accurate data analysis for research, academic and decision purposes.

SPSS is also a widely used program for statistical analysis in social science for data analytics, reporting and modeling. The software is useful for individuals who need to analyze large amounts of quantitative data and to quickly and accurately carry out statistical analysis of sets of data such as market researchers, health researchers, survey companies, government, education researchers, marketing organizations and data miners.

Fundamentals of research: Introduction to research, problem statement, research question, objectives of the research, hypotheses, sampling procedure, sample size determination and data collection.

Introduction to statistics and SPSS: Introduction to levels of measurement of data, techniques involved in SPSS.

Data entry: Data and its types, Creating data and variable view, exporting and importing data.

Selecting type of test: Based on number of population study, nature of comparison and dependent or independent samples. Missing value management and Test of normality.

Descriptive analysis: Descriptive statistics, frequencies, cross tabulation, graphs.

Factor analysis: Types of factor analysis, exploratory factor analysis.

Correlation and regression analysis: Scatter diagram, correlation coefficient, regression values, comparison between correlation and regression.

Multiple regression: Multiple independent variable relationship with one or more dependent variable study. Interpretation of R square values.

Test of means: One population mean value study

T test: Two population means are equal for small samples and when population standard deviation is not known.

ANOVA test: More than two population means are equal study.

Chi square test: categorical data in one population or more than one population study.

Cluster analysis: various types of cluster analysis such as K-means clustering, two steps clustering and hierarchical clustering methods.

Discriminant analysis: use of discriminant analysis, interpretation of discriminant line.

Seri Iskandar, 32610, 31750 Tronoh, Perak.

The objectives of this professional technical course are:

To impart the data analytical capabilities to the young lecturers, project leaders, business analysts, research scholars and post graduate students, who want the enhance the quality of their work by using statistics for business and research.

To familiarize participants with the basic practice of statistics by using SPSS Statistics.

To acquaint participants with the use of advanced SPSS for analyzing project data for reporting purposes focusing on database management tasks, descriptive statistics and graphics, and basic inferential statistics for comparisons and correlations.

The course is suitable for all sectors of industries and services. Professionals and researchers

interested in the knowledge management system

Academicians, Lecturers and Postgraduate Students in Universities, Colleges and Polytechnics from any discipline

Project leaders, business analysts and others who want to enhance their data analysis capability.

RM 1350 (Student)

RM 1460 (UTP Alumni & Group Registration)

RM 1590 (Professionals)

Course fee is inclusive of 6% GST.

Group registration is applicable for 3 pax and

above from the same company.

The fees include refreshments and the course

materials.

A certificate of attendance will be issued upon

successful completion of the course.

Email to CAPE@utp.edu.my for registration by 27th March 2016.

Seats are limited. A seat will be confirmed once the payment / LOU is received.

Confirmed participants will be informed via email.

Course Coordinator: Associate Professor Dr. Dhanapal Tel: +605 - 368 7510 Email: dhanapal_d@utp.edu.my Course Registration: Mrs. Jaspreet Kaur Tel: +603-2276 0425/+6012-6472410 Email: CAPE@utp.edu.my

Associate Professor Dr. Dhanapal Durai Dominic P. is currently working in Computer and Information Sciences department, Universiti Teknologi PETRONAS, Malaysia. He received his PhD in Management at Alagappa University, India. He received his Post-Graduate Diploma in Operations Research from Pondicherry University, India; Masters of Business Administration; Masters of Philosophy in Mathematics and Masters of Science in Mathematics from Bharathidasan University, India. He has been working in the capacity of editorial board member for renowned journals. His research interests include Management Information Systems and Knowledge Management. He has published more than 100 journals with high impact factors and distinguished indices like SCOPUS and ISI.