SPSS and Applied Techniques

Duration: 7 days Start Date: 16th April, 2018 End Date:  24th April, 2018 Time: 9:00 – 3:00pm   COURSE OBJECTIVE At the end of the course, students should be able to:

1. Distinguish between qualitative and quantitative data analysis and procedures
2. Conceptualize, state, test hypotheses and explain the conclusions
3. Distinguish between parametric and non-parametric analysis
4. Select appropriate statistical techniques for data analysis
5. Produce professional quality reports

  COURSE CONTENT Main Application software will be SPSS, and Excel

1. Data Analysis in the Research Process
   • Types of Qualitative Data
   • Transcription and analysis (summarizing, categorization and thematization; interpretation; constant comparative causal pathways, cross-site analysis, inductive analysis, concept mapping etc.)
   • Presentation (text, matrices, charts, pictures, tables, sound)
   • Quantitative Data management
2. Scale of measurement – measure of central tendency
   • Introduction to SPSS: File creation, Dialogue boxes, Definition of variables and management, Missing Values, Data entry, Saving and retrieving data, backing up files
   • Data screening and cleaning, Reliability, Overview of Open-ended items & Coding Manual,
3. SPSS: Coding and recording, Transformation – computation, merging files (cases or variables). Selecting cases – Conditions; Combining Logical Relationships, versions of files
4. SPSS: Data processing and analysis
   • Linkage to objectives, All instruments, Data summary,
   • Exploration, Stem and leaf, Frequencies, Pivot table editing,
   • Descriptives, Standardization, Percentiles and Quartiles
5. SPSS: Inferential statistics
   • Exploring relationships (correlation (Pearson and Spearman), regression, cross-tabs, chi-square – phi, Cramer’s V), Mann-Whitney U Test, Wilcoxon Signed Rank Test, Kruskal-Wallis Test
   • Comparison between means – Paired, Independent samples, One sample – T, Z, etc tests, ANOVA (1,2 way), Effect size
6. Excel:
   • MegaStats tools
   • Mathematical operations, Data transformation, Analysis tools, Insert functions, Descriptives, Skewness, Kurtosis, Percentiles & Quartiles, Standardization, Fractions, sumproduct
   • Histogram, Other graphs (bar, pie, line, S&D, Lorenz)
   • Inferential statistics – Sampling, T-test, Z-test, F-test, ANOVA (1,2 way), Difference between proportions
   • Pivot table and chart report – One Variable, two variable tally, Grouping categories in charts
   • Excel Logical Functions

MODE OF DELIVERY Through demonstrations