1. SADC Course in Statistics Analysing numeric variables Module B2, Session 15

2. To put your footer here go to View > Header and Footer 2 Learning Objectives students should be able to Group numeric variables So they can be analysed like categorical variables Summarise numeric variables Without grouping Apply the objectives of Session 14 to the analysis of numeric variables Outline a simple table or graph for a numeric variable Complete a simple table or graph given an objective and an outline.

3. To put your footer here go to View > Header and Footer 3 Contents Introduction of the ideas Practical 1 How to process numeric variables Practical 2 Using Rice survey and the Tanzania survey Discussion

4. To put your footer here go to View > Header and Footer 4 Overall objectives – small example Rice survey Two objectives 1.Estimate total rice production in the district 2.Investigate the possible relationships between production and cultural practices These are both objectives that relate to the yields A numeric variable

5. To put your footer here go to View > Header and Footer 5 The district for the rice survey

6. To put your footer here go to View > Header and Footer 6 The data ready for analysis

7. To put your footer here go to View > Header and Footer 7 Objectives and measurements The objectives led to the questions the measurements we took 1st objective – total yield in the district So we measured the yield on sampled plots 2 nd objective – relationships with cultural practice so we asked about size of field, fertilizer, variety See how the objectives lead directly to the questions in the survey The “students” also gave simple objectives Just from looking at the data

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9. 9 For the categorical variables: These tables and graphs were to satisfy the objectives

10. To put your footer here go to View > Header and Footer 10 Practical work The practical benefits from discussion So it is good for students to work in pairs As in the last session First the rice survey data are analysed Then a larger data set is used This time we start with the rice data Then move on to the sunshine data That was organised in Session 10 Now go and do the practical

11. To put your footer here go to View > Header and Footer 11 Key points We review the key points from the practical work Using both the rice data And the sunshine data

12. To put your footer here go to View > Header and Footer 12 For a numeric variable Either they can be grouped The grouped variable is then categorical The categories are in order So it is an ordered categorical variable Or they can be analysed as they stand Both were investigated in the practical work

13. To put your footer here go to View > Header and Footer 13 Grouping a numeric variable The practical illustrates 3 methods A simple method Also gives practice in using logical calculations Two alternatives Make use of IF statements Which also can be used to add labels to the groups They are also described in the Excel guide chapter 4 For which there is also a demonstration

14. To put your footer here go to View > Header and Footer 14 Sunshine data - objectives The solar cooker can only be used when there is sufficient sun Morning sun is needed To cook lunch – 3 hours in period from 9am to 1pm Afternoon sun is needed To cook dinner One hour of sun either time Is sufficient to pasteurise water The hourly sunshine data were organised In Session 10 – given these needs

15. To put your footer here go to View > Header and Footer 15 The data – ready for analysis Total sun (hrs) between 9am and 1pm From these 12 values. What is the chance of cooking?

16. To put your footer here go to View > Header and Footer 16 Objectives and analyses again Simple objectives A single variable More complicated objectives Two variables or more Apply the same idea to the sunshine data

17. To put your footer here go to View > Header and Footer 17 Sunshine data - objectives How often is cooking possible in the morning? How often is cooking possible in relation to the early-morning sunshine Simple objective –one variable More complicated objective –two variables

18. To put your footer here go to View > Header and Footer 18 So: Are you now able to Group numeric variables So they can be analysed like categorical variables Summarise numeric variables Without grouping Apply the objectives of Session 14 to the analysis of numeric variables Outline a simple table or graph for a numeric variable Complete a simple table or graph given an objective and an outline.

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