1. SADC Course in Statistics Introduction and Study Objectives (Session 01)

2. To put your footer here go to View > Header and Footer 2 Module Overview Sample to population inferences, e.g. estimating population characteristics Measuring the precision of such estimates Concepts underlying hypotheses about population parameters Introduction to commonly used statistical distributions Basic tests for comparing means, variances, proportions Tests for association

3. To put your footer here go to View > Header and Footer 3 Module aims By the end of this module, you will be able to explain basic concepts for making sample to population inferences calculate and interpret standard errors and confidence intervals for simple problems conduct statistical tests to compare two means or two proportions discuss the use and limitations of tests of significance have an appreciation of what is meant by a non-parametric test

4. To put your footer here go to View > Header and Footer 4 Aims – this session… By the end of this session, you will be able to appreciate the different type of objectives that may arise in real life situations critically assess the type of information needed to address questions of interest recognise that real situations have complex data structures which have to be ignored in this module in order to understand the basic concepts better without distraction

5. To put your footer here go to View > Header and Footer 5 Objectives related to estimation To estimate proportion of rural households that are food insecure (<6 months food for family) in Zimbabwe average amount of land available for cultivation in Swaziland infant mortality rate, i.e. deaths per 1000 live births in Zambia total number of tobacco estates of <20 ha owned by small-holder farmers in Malawi

6. To put your footer here go to View > Header and Footer 6 Objectives related to comparisons Examples of questions of interest are: is distance from school an impediment to school enrolment amongst girls? is there a difference in child-stunting (measured by height-for-age standardised score<-2) between rural & urban areas is there evidence that agro-forestry farmers are more food secure (measured by no. of months food is available for family) than non-agro-forestry farmers?

7. To put your footer here go to View > Header and Footer 7 Objectives related to relationships Is there a relationship between diarrhoea episodes in a household and availability of access to clean water use of contraceptives and educational level of household head farmers’ adoption of soil fertility management methods and gender? use of mosquito nets and occurrence of malaria?

8. To put your footer here go to View > Header and Footer 8 Initial data analysis requirements Need first to identify the ultimate sampling unit on which measurements are to be made actual measurements needed, plus clarity on the calculation of any derived variable(s) It will also be useful to think about the type of data format (say as an Excel spreadsheet) needed for the analysis Some examples follow…

9. To put your footer here go to View > Header and Footer 9 Initial steps – some examples Example 1. Estimating the proportion of rural households that are food insecure in Zimbabwe Unit: Household Measurement: Number of months in past year when food was available for whole family Derived variable: Coded as 0 if above measurement  6, 1 otherwise

10. To put your footer here go to View > Header and Footer 10 An example with a hierarchy Example 2. Estimating the average number of years of formal education in rural Zimbabwean households Units (within HH): Household members Measurements: Years of education for each member in the household, and HH size Derived variable: Average number of years of education = Sum above measurements divided by HH size (needed since objective is at the HH level, measurement at person level)

11. To put your footer here go to View > Header and Footer 11 What else is needed? What is the data format for above examples at the HH level? Below is an illustration (showing fictitious values) Given data in this format, can questions posed in Examples 1 and 2 be answered?

12. To put your footer here go to View > Header and Footer 12 What about the actual data structure? Above approach assumes there is no further structure to the data. But there may be: further information at HH level, e.g. extent to which the HH relies on subsistence farming, number of employed persons in the HH, etc. information on how the HH’s were selected, e.g. purposively choosing predominantly rural districts, then smaller administrative units within districts, and finally HHs – this is a hierarchical structure

13. To put your footer here go to View > Header and Footer 13 Recognising Limitations Correct approaches to data analysis should allow for the data structure and the possible influence of other factors. However, this module is only aimed at covering the basic statistical concepts. So we will ignore the real complications in the remainder of this module in order to understand the basic concepts without distraction.

14. To put your footer here go to View > Header and Footer 14 Practice and Discussion For the first 2 questions below, identify the starting components necessary for an analysis as illustrated in Examples 1 & 2. A joint discussion will follow regarding (c). (a)What is the average amount of land available for cultivation amongst subsistence farmers? (b)Is distance from school an impediment to school enrolment amongst girls? (c)What is the relationship between use of bednets and occurrence of malaria?

15. To put your footer here go to View > Header and Footer 15 Practical work follows to ensure learning objectives are achieved…