sadc course in statistics graphical summaries for quantitative data module i3: sessions 2 and 3

SADC Course in Statistics

Graphical summaries for quantitative data

Module I3: Sessions 2 and 3

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Learning ObjectivesStudents should be able to:

• Present data in a histogram – and interpret data when shown a histogram

• Present data in a boxplot – and interpret data in a boxplot

• Recognise advantages and limitations – of each method of presentation

• Explain what is gained and lost from data summary• Interpret graphical summaries to answer questions

– concerning proportions, – extremes, – medians – and quartiles

• Resolve simple problems with graphical displays– when real data (not text-book examples) are used


Session Overview

Activity 1: Presentation to introduce the sessions

Activity 2: Demonstration on histograms in Excel

Activity 3: Practical covering the same ideas– CAST Chapter 2.1– Histograms– Population pyramids

Activity 4: Practical on boxplots and percentage points– CAST Chapter 2.2– Boxplots in Excel

Activity 5: Presentation continued


Activity 1- Case studies• Case studies used in these sessions are:

– Rice Survey– Zambia Rainfall Data – The Swaziland Crop Cutting Survey

• The were introduced in Modules B1 and B2 – so for many this will be a reminder.

• The rice survey and the Swaziland Crop Cutting– were already used in Session 1 of this Module.


Rice surveyUsed repeatedly

in slightly different forms

In CAST as shown here

In demonstration

And in Excel

Qualitative and quantitative variables to analyse


Zambia Rainfall data

• Farmers are migrating from Southern Zambia– citing climate change as the reason– they can no longer grow the crops as before

• A local NGO – acknowledges climate change in general, – but believes improved farming practices is more

important– wherever farmers locate

• They question the evidence– for climate change in the pattern of rainfall– as it affects farming strategy


Data analysed in these sessions

Total rainfall from 1 Jan to 31 March – called SeasonTot

Number of rain days in the same period - Scount


Original daily values are also available

Not needed for analysis here, but used for checking

Also useful if further questions posed


Zambia rainfall continued:

• Here we use the annual data – on the final worksheet– preparing data for analysis is done in Module I2

• We have access to the raw data – for checking purposes – and in case other variables are needed on a

later occasion


Swaziland Crop Cutting Survey

• Annual survey– Of agricultural holdings– And areas planted– Then yields from a crop-cutting exercise

• Data from 2005 made available


Person-level data

Ages will be analysed in these sessions


Yield data

The dry weights will be analysed

Analysis overall and just for maize

The zero yields cause a slight problem


Activity 2 – demonstration of histograms

• Before the practical (which is activity 3)• Follow the demonstration• On histograms and population pyramids in Excel

• It shows• Use of Excel• But keeping control – you must remain in charge• And not be limited by the software

• So it shows how to resolve problems• As well as how to use Excel


Activity 3 – practical with CAST and Excel

• Using CAST to understand histograms

• Then use Excel to construct them• Being observant – as was shown in the demonstration• And keeping control

• Remember the aims• Are more to understand statistics• Rather than to practice with Excel• Excel is just the tool


An example with CAST

Practice with small data sets – as shown here and also with large data sets


Population pyramid in CAST

How close to this display can you get with Excel?

Interpret this display


Activity 4: Boxplots and data summary

• Now do the demonstration

• And these two practical exercises

• Then return to the remaining slides

• For a discussion of the key points


Topics for the class discussion

• What was interesting?

• What did you discover

• What was difficult?

• What needs further discussion?


Boxplots and histograms – CAST page 2.2.3

Are you clear how boxplots and histograms relate?


Boxplots show outliers – CAST page 2.2.4

And this makes them very useful for data exploration as well as summary


You can calculate percentage points

• The formula

r * (n + 1)/100

• for the r’th % point

• Should now hold no fears

• For example– when there are 11 observations– and you want the median– use 50 * (11+1)/100 = 6– the median is the 6th highest in the sorted data

• If necessary look again at practical 2


Practical problems with real data

• This always happens

• You saw a problem – with the rainfall data– and with the crop yields

• The solution always involves being observant

• You can follow guidelines for a good analysis

• But not always simply obey rules

• Become a data detective instead!


Learning ObjectivesAre you now able to:• Present data in a histogram

– and interpret data when shown a histogram

• Present data in a boxplot – and interpret data in a boxplot

• Recognise advantages and limitations – of each method of presentation

• Explain what is gained and lost from data summary• Interpret graphical summaries to answer questions

– concerning proportions, – extremes, – medians – and quartiles

• Resolve simple problems with graphical displays– when real data (not text-book examples) are used


These sessions were largely on graphical summaries

The next sessions consider numerical summaries of the data

sadc course in statistics graphical summaries for quantitative data module i3: sessions 2 and 3

Documents

view header

excel slide

annual data

data summary

excel excel

available slide

display slide

large data sets slide