Using a statistics packageto analyse survey data

Module 2 Session 8

Objectives of this session

You should be able to: Use a statistics package to produce

tables and graphs of frequencies and proportions

Pproduce tables of summary statistics Explain why weights

are sometimes needed in analysing survey data

Produce weighted tables of counts and other statistics

How to describe data well - review Look for oddities in the data

and be prepared to adapt the summaries that you calculate Study the data as tables and graphs Use frequencies and percentages

to summarize categorical variables Use averages and measures of variability

to summarize numeric variables Identify any structure in the data

and use it in producing your summaries

Look at the data

The 2 types of variable are summarized in different ways

Analysis to meet objectives

Simple objectives

Not so simple

objectives

Meeting simple objectivesSummaries made with Instat – see practical 1

Answering more complicated objectives

AND explaining some of the variability as shown in Module 1

These were also with Instat

Practical 1

Reviews the construction of tables Using a statistics package

Particularly to look at percentages Because percentages have to be understood clearly to analyse multiple response data

This practical also gives more practice In the use of a statistics package

Common complications when analysing survey data

Common complications include: Missing values in survey data Weights are sometimes needed

Because some observations represent more of the population than others

Multiple response questions have to be processed These are all easier

with an appropriate statistics package Here, as an example

we introduce the need for “weights”

Introducing weights

Suppose a sample of 2 farmers Farmer Yield

A 1 t/ha

B 2 t/ha What is the mean? Obviously it is (1 + 2)/2 = 1.5 t/ha! But…

Introducing weights - continued Suppose the same sample of 2 farmers Farmer Area Yield Production

A 5 ha 1 t/ha 5 tons

B 0.5 ha 2 t/ha 1 ton

Now what is the mean? It could still be (1 + 2)/2 = 1.5 t/ha Or it could be (5 + 1)/5.5 = 1.1 t/ha

But which is right? They are both right,

but they answer different questions

Take food security Are you interested in the farmer Or the production Or both

If the farmer is the unit of interest Then there are 2 farmers The mean is 1.5

If the area is the unit of interest Then there are 5.5 ha And Farmer A is 10 times as important as farmer B So a weighted mean is produced

The weighted mean So if the area is of interest – then with Farmer Area Yield

A 5 ha 1 t/ha

B 0.5 ha 2 t/ha Weight each yield by the area it represents mean = (1*5 + 2*0.5)/5.5 = 1.1 Here the areas are the “weights” They are used when different observations

represent different proportions of the “population”

Weights in the Tanzania agriculture survey

The number of people in

the population

represented by each

observation

It was roughly a

1% sample, so the

weights are about 100

The technical guide explains the calculations

Practical 2

Weights using a statistics package First the rice survey

Weighting by the size of field

Then the Tanzania agriculture survey Investigate ownership of radios By type of farming household

Possession of radio by type of farming

Unweighted analysis

Uses the observed numbers and percentages in the sample

Look at livestock – but numbers small

Possession of radio by type of farming

Weighted analysis

The estimated numbers and percentages in the region of Tanzania

Look at livestock now – what do you conclude?

Why such a large change with weighting?

Examine the weights for these

2 groups

Average weight = 60 Average weight = 20

So estimated % with radio =

100*(42*20)/(10*60+42*20) = 59%

And always take care with small numbers

Large sample overall

But still a small sample of livestock-only farmers

Can you now?

Use a statistics package to produce tables and graphs of frequencies and proportions

Produce tables of summary statistics Explain why weights

are sometimes needed in analysing survey data

Produce weighted tables of counts and other statistics