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Collecting data for informed

decision-making

Module 3

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Introduction

WelcomeHousekeeping etc.

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Overview

So far in this training programme we have only studied the handling of data, and report writing.

Key concepts of statistics, e.g. Good tables and graphs – using Excel

Data management e.g. Data entry and validation – using Epi-info

Some analysis methods e.g. Instat

It is now time to study aspects of collecting data

(see next slide).

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Design survey

Design questionnaire

Enumerators collect data in the field

Data entered onto computer

Manual checking, editing etc.

Data analysis

Reporting of results

Computer data management

Data management cycle

Conception

Have covered some data analysis- more to come in

Module 4

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Design survey

Design questionnaire

Enumerators collect data in the field

Data entered onto computer

Manual checking, editing etc.

Data analysis

Reporting of results

Computer data management

Data management cycle

Conception

Module 3

Module 4

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Module content

Types of study Types of data Tables to address objectives Questionnaire design Practical aspect of sampling surveys Sampling techniques

simple random sampling, stratified sampling, etc. Integrating qualitative and quantitative

approaches

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Duration and timetable

Morning Afternoon

Day 1Data collection and the research process

Table design

Day 2 Questionnaire designIntroduction to sampling techniques:

Day 3 Simple random sampling Stratified sampling

Day 4 Systematic sampling Cluster sampling

Day 5 Multistage samplingIntegrating qualitative research into quantitative research

Day 6Integrating qualitative research into quantitative research

Wrap up

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Module Learning Objectives

At the end of the module, participants will be able to: Design questionnaires to address survey

objectives effectively; and identify questionnaires that fail to address survey objectives

Explain to others the benefits of random sampling. Describe stratified, cluster and multistage

sampling. Select random samples using different sampling

schemes, and advise others on how to do so.

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Module Learning Objectives (cont.)

More experienced members of the class may also be able to:

explain the benefits of stratified sampling compared to simple random sampling

explain the difference between stratified sampling and cluster sampling

explain what multistage sampling is, and how it relates to other sampling methods

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Prerequisites

None (except possibly Module 1).

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Resources

CAST The Green Book (Chapter 4).

To the Woods Paddy Rice Survey

A case study of objectives for investigation by observation - provided by UBOS.

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Data collection methods

Module 3

Session 1

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Overview (of Session)

This session sets the scene for the module as a whole, and for the next three sessions in particular.

It reviews types of studies, and types of data and data collection.

It is laying the foundations for ensuring good data collection that will address the objectives of a research study.

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Session Learning Objectives

At the end of the session participants will be able to:

Describe a range of different data collection activities.

Explain the difference between primary and secondary data and their roles in the research process.

Recount the methods and tools that are used in collecting different types of data.

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Introduction

Within statistical offices and other departments, research studies are carried out to answer questions and inform policy.

Most of these studies are observational studies.observational studies.(i.e. researcher does not change the environment that is being studied, but observes and measures characteristics of interest with the aim of understanding the phenomenon under study.)

Sometimes they are desk studies using secondary data to draw conclusions.

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Types of study

Examples of observational studies are: Census, sample survey, monitoring

These are all formally designed with structured questionnaires.

Sample surveysSample surveys are commonly carried out observational studies.

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Types of study

Less structured examples are: Qualitative interviewing, focus groups, etc.

Instruments for collecting data include: semi-structured questionnaires to ad-hoc

conversations diagrams ranking methods mapping techniques etc.

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Data sources

Primary data are data that you, or your team, collect to meet specific objectives Data collected in a sample survey is primary data. Sometimes called raw data or micro-data You know its qualityquality (checking, entering, managing,

etc. all done by you.)

Secondary data are collected by others for other purposes. Sometimes only available in summary form.

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Getting it right!

Important that the study conveys correct message to the policy makers.

This means that for surveys, for example, the study needs to be well designed: needs well designed instruments asking the

right questions and collecting all the relevant data.

needs to ensure that the sample studied is representative of the population of interest.

(more of this later in the module).

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Types of surveys

Cross-sectional studies involve observation of some subset of a population

of items all at the same time. Cross-sectional studies are used in most branches

of science, social sciences and elsewhere.

Longitudinal studies involves repeated observations of the same items

over long periods of time, often many decades. They allow researchers to distinguish short from

long-term phenomena, such as poverty.

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Types of surveys (cont.)

Panel studies is a longitudinal study where a cross-sectional

sample of units is selected and surveyed at usually regular intervals. The observation units may be individuals, households, organisations, etc.

Cohort studies is a form of longitudinal study. They sample a

cohort, defined as a group experiencing some event (typically birth) in a selected time period, and studying them at intervals through time.

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Uganda Examples:Sample Survey

The 2002/2003 UNHS2 survey: approx.50,000 individuals 9700 households 970 communities

is an example of a cross-sectional surveycross-sectional survey.

UBOS designed sampling scheme, designed questionnaire etc.

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Part of UNHS2 questionnaire

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Uganda Examples:Focus Group

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Types of data

QuantitativeQuantitative Yield per hectare

(numeric)

Time to travel to primary school (numeric)

Number of bundles of straw (0,1,2,….) Traditional cash crops

(1=coffee, 2=cotton, 3=tea,….) (categorical)

Ownership of car (yes / no) (binary)

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Types of data

Qualitative Qualitative results of focus group discussion additional comments reasons … etc.

Can still be classified (coded) into categories.

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Activity - Primary and secondary data

Read Chapter 4.1 (Using Secondary Data) of the Green Book.

In groups, discuss what secondary data is, where it can be used in the research process, and advantages and disadvantages.

Report back.

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Discussion – studies and methods and instruments

Working in small groups. Find out what types of study others have

been involved in, and what methods and instruments they have used - with examples.

Discuss pros and cons of different studies and different methods and instruments.

Report back and group discussion.