06 quantitative data processing
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This document provides an overview of key concepts in data collection and analysis. It defines different types of data, such as primary and secondary data, and variables like independent, dependent, and mediating variables. It also discusses important steps in data processing like editing, coding, data entry, and cleaning. The document explains why computers are useful for data processing and analysis. It then covers specific techniques for coding, entering data into spreadsheets, and cleaning data. Finally, it discusses different types of data analysis including descriptive and inferential statistics, and choosing the appropriate analytical techniques based on factors like sampling design and variable types.
06 quantitative data processing
- 1. By Dr. E. Kanagaraj Department of Social Work School of Social Sciences Mizoram University Aizawl -796 009.
- 2. Data What is Data? What are its Types? Primary vs Secondary Quantitative Vs Qualitative
- 3. Types of Data Primary Data and Secondary Data : Crossectional, Time Series and Pooled Data
- 4. Variable What is Variable? Continuous and Discrete Metric and Non-metric Independent, Dependent and Mediating
- 5. Data Processing Editing Coding : Code Book Data Entry: Master Chart Data Cleaning
- 6. Why Computer in Data Processing and Analysis Time Resources Energy Errors Use of Advanced Tools Multivariate Techniques Difficult?
- 7. Coding Assigning numerals and Labeling Structured, Pre-coded Instruments Unstructured Questions Coding according to research objective Numerical coding most appropriate
- 8. Data Entry Master Chart or Table Variables in Column Cases in Rows Data entry in Ms Excel Integration of Code Book and Master Reading Excel Data in SPSS
- 9. Data Cleaning Correcting Errors in Data Entry Maximum, Minimum, Frequency etc Sorting and Correcting
- 10. Data Analysis What is analysis Explaining the one with the other Association Relationship: Linear vs Non linear Comparison: Two or More Groups Hypothesis Testing
- 11. Choice of Techniques Sampling Design : Random Vs Non random Nature of Variable : Nominal, Ordinal, Interval Number of Variables Number of Cases : Sample Size
- 12. Descriptive Statistics Aim to describe the characteristics Measures of Central Tendency Measures of Dispersion
- 13. Inferential Statistics Parameter – Population measure Statistic – Sample measure Univariate Bivariate Multivariate
- 15. THANK YOU