Tables and graphs for frequencies and summary statistics Module I3 Sessions 10 to 12

Learning objectives Students should be able to: Produce multi-way tables of counts and tables with the appropriate percentages Explain the criteria that dictate how complex a table needs to be Produce tables for continuous variables that include the appropriate summary statistics. Explain what the margins of a table are and know when to include the margins in a table. “Drill-down” to examine the data that have given rise to the elements of a table. Produce the charts that correspond to a given table

Contents This presentation initially Review Uses full demonstration “Describe data well” Practicals 1, 2 and 3:Counts and percentages Practical 1 – on demonstration Practical 2 – uses rice survey Practical 3 – Survey on Principles of Official Statistics Presentation continued Practical 4: Summarising variates in tables Practical 5: Tables and graphs together Using the Tanzania case study

Objectives from the rice survey Simple objectives Not so simple objectives

Objectives for different types of variable Factor, or category, or qualitative variable Numeric or quantitative variable Two factors One numeric and one factor Two numeric

Review and practicals 1 and 2 Look at the demonstration As a class or in pairs Do practical 1 at the same time Then practical 2 Same ideas Practice using Excel Introduces a more complicated objectives (next slide) To understand different percentages Then review these ideas Or continue with practical 3 first

Review of ideas Practical 1 Practical 2 Practical 3 Reminder of the steps in an analysis Practical 2 One-way and two-way tables Which percentage is appropriate? Practical 3 Frequency tables in general Tables with and without margins (“totals” in Excel)

How to describe data well 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

The 2 types of variable are summarized in different ways Look at the data The 2 types of variable are summarized in different ways

Simple summaries to meet simple objectives

Contents of these summaries

Does this summary satisfy any of the objectives? Summary of the yields Does this summary satisfy any of the objectives?

In summary – for the simple objectives

What other suggestions were made for coping with outliers? Checking for oddities What other suggestions were made for coping with outliers?

Answering more complicated objectives AND explaining some of the variability

One-way and two-way tables One way table – with 2 summary statistics Two-way table Margins of the table The margins of a 2-way table are one-way tables

Percentages in tables Consider carefully which percentage(s) are appropriate Here “row” percentages compare types of country Column percentages would compare where implemented

Sort of 2-way table? Or one-way table with 9 summary statistics This margin is meaningless – and should be hidden

Tables can be 3-way or higher Excel gives all the totals But is more limited in giving percentages

Practicals 4 and 5 Practical 4 Practical 5 Rice survey again Tables for numeric variables As well as frequencies for factors Practical 5 Apply the ideas To the data from Tanzania Look at power used for lighting (factor) At size of land holdings (numeric variate) And at keeping indigenous chickens – both!

Tables that summarise variates as well Objective: How do the yields relate to the variety grown?

More one-way tables: summary statistics Also Lower s.d. for Variety than Village. Why might that be important?

Summary statistics in 2-way tables How do the yields relate to fertilizer and variety? i.e. extends to objectives from those stated

Tanzania agriculture survey A huge survey of agriculture in Tanzania Involving about 1800 enumerators And a main questionnaire of 22 pages Given to 3223 households In the district provided for analysis A technical report Describes the process of data entry And checking Then there is the analysis And reporting

Data for lighting

How large a table do you need? Are these differences sufficiently large that you need this 2-way table? If no, then the one-way presentation is simpler If yes, then perhaps a one-way table/graph hides important information

One way table/graph

Objectives and many questions To help the extension service Improve their service to households keeping chickens What proportion of households keeps indigenous chickens? When they do, how many do they keep? Are these values roughly the same, or do they differ by district? Do they differ by other factors, in particular the sex of the household head or the type of agriculture household (Q021).

Recap Now have the tools to process Factors (categorical data) Using frequencies and percentages Variates (quantitative data) Using means and medians And quartiles, extremes, standard deviations And proportions (risks), percentiles (return periods) You also know to use other measurements to reduce the unexplained variation And the statistics can be presented in tables and graphs

Good tables for Excel users – a guide A guide is provided That summarises how to use tables in Excel And can be used for reference It also introduces some additional topics where we need more than Excel Other summaries in a table (e.g. medians) Weights in tables Multiple responses That are considered in the next sessions

Learning objectives Are you now able to?: Produce multi-way tables of counts and tables with the appropriate percentages Explain the criteria that dictate how complex a table needs to be Produce tables for continuous variables that include the appropriate summary statistics. Explain what the margins of a table are and know when to include the margins in a table. “Drill-down” to examine the data that have given rise to the elements of a table. Produce the charts that correspond to a given table

In the next sessions we extend these analyses To handle common problems that occur with many surveys