Introduction to data analysis: Case studies with iSIKHNAS data

Day 1

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Introduction to course

• Relevance of data analysis to policy• Objectives of course• Pre-requisites

Learning approach

Steps in data analysis

• Objective• Data management• Descriptive analysis• Hypothesis testing

Key concepts for sampling (1)

• Sampling verse census• Bias • Sampling variability

Key concepts for sampling (2)

• Datasets and variables

Key concepts for sampling (3)

• Distributions

Case study 1: Introduction

Case study 1: Objectives

• Objectives – Exercise 1– Exercise 2

Case study 1: Data management

• Download iSIKHNAS data• Preserve data

Key concepts on errors

• Missing data– Blank cells in data– Missing observations

• Incorrect data– Random errors– Systematic errors

Case study 1: Data management

• Exercises 3: Missing data• Exercise 5: Create new data

Key concepts on descriptive statistics

• Variable types• Continuous variables– Measures of central tendency – Measures of dispersion

Case study 1: Description of data

• Exercise 6: Descriptive statistics• Exercise 6b: Descriptive statistics without

analysis ToolPak• Exercise 7: Plotting (histograms)

Summary of case study 1

The end of day 1