C3 Compile and iterpret data.pptx pharmacy

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1. Chapter three Compile, Interpret and Utilize health data

2. Learning Objectives Upon completion of this Learning Guide, you will be able to : Collect necessary health data as per organizational guideline Describe diagrammatic presentation of data Follow steps to maintain information confidentiality according to prescribed procedures. C ontinuously and consistently collect and update vital events timely in accordance with organization procedures and guidelines Prepare and utilize data according to prescribed procedures and guidelines

3. Data Organization Collected data has to be organized in order to be meaningful and understandable. Collected data are entered in to different statistical soft-wares and stored for future/farther use. To store data, we use different internal and external storage mediums .

4. Data analysis It is a process of inspecting, cleaning, transforming, and modelling data. The goals of data analysis are: discovering useful information, suggesting conclusions, and supporting decision making. We use descriptive analysis to summarize the data and describe sample characteristics .

5. Frequency distribution A frequency distribution is a table showing how often each value (or set of values) of the variable in question occurs in a data set . A frequency table is used to summarize categorical or numerical data. Frequencies are also presented as relative frequencies, that is, the percentage of the total number in the sample.

6. Data presentation We use textual, graphical displays & tabular methods to present a given data. Textual Method The data are presented in the form of texts, phrases or paragraphs. It is common among newspaper reports depicting specifically the salient or important findings.

7. b) Tabular method A statistical table is an orderly and systematic presentation of numerical data in rows and columns. The use of tables for organizing data involves grouping the data into mutually exclusive categories of the variables and counting the number of occurrences (frequency) to each category.

8. Construction of Table The following general principles should be addressed in constructing tables . Tables should be as simple as possible. Tables should be self-explanatory. For that purpose Title should be clear and to the point( a good title answers: what? when? where? how classified ?) and it be placed above the table. Each row and column should be labelled.

9. Cont’d… Totals should be shown either in the top row and the first column or in the last row and last column. If data are not original, their source should be given in a footnote.

10. Cont’d… Immunization status Number Frequency Not immunized 75 35.5 Partially immunized 57 27.1 Fully immunized 78 37.2 Total 210 100.0 T able 3: Overall immunization status of children in Adami Tullu Woreda , Feb. 1995 Source: Fikru T et al. EPI Coverage in Adami Tulu. Eth J Health Dev 1997;11(2): 109-113

11. c) Graphic display of health data Appropriately drawn graph allows readers to rapidly obtain an overall grasp of the data presented . Shows the relationship between magnitude of different categories/variables more quickly and easily. As their size and number increase they become confusing and uninteresting

12. Importance of Diagrammatic Representation They have greater attraction than mere figures. They help in deriving the required information in less time and without any mental strain. They facilitate comparison. They may reveal unsuspected patterns in a complex set of data and may suggest directions in which changes are occurring. This warns us to take an immediate action. They have greater memorising value than mere figures.

13. Limitations of Diagrammatic Representation is made use only for purposes of comparison. It is not to be used when comparison is either not possible or is not necessary . Diagrammatic representation is not an alternative to tabulation. It only strengthens the textual exposition of a subject, and cannot serve as a complete substitute for statistical data . It can give only an approximate idea and as such where greater accuracy is needed diagrams will not be suitable. They fail to bring to light small differences

14. Construction of graphs The choice of the particular form among the different possibilities will depend on personal choices and/or the type of the data. Bar charts and pie chart are commonly used for qualitative or quantitative discrete data. Histograms , frequency polygons are used for quantitative continuous data .

15. G eneral rules that are commonly accepted about construction of graphs. Every graph should be self-explanatory and as simple as possible. Titles are usually placed below the graph and it should again question what ? Where? When? How classified? Legends or keys should be used to differentiate variables if more than one is shown. The axes label should be placed to read from the left side and from the bottom. The units in to which the scale is divided should be clearly indicated. The numerical scale representing frequency must start at zero.

16. i) Bar chart Represent and compare the frequency distribution of discrete variables. When we represent data using bar diagram, all the bars must have equal width and the distance between bars must be equal .

17. Bar chart Figure 1: Immunization status of Children in Adami Tulu Woreda , Feb. 1995

18. Histograms (quantitative continuous data) Histograms displays the frequency distribution of continuous variables. It is constructed on the basis of the following principles : The horizontal axis is a continuous scale running from one extreme end of the distribution to the other. It should be labelled with the name of the variable and the units of measurement . There will never be any gap between the histogram rectangles.

19. Example Example: Consider the data on time (in hours) that 80 college students devoted to leisure activities during a typical school week : Figure 2: Histogram for amount of time college students devoted to leisure activities .

20. iii) Pie chart Is used to represent both quantitative and qualitative/categorical data. Steps to construct pie chart: Construct frequency table Change the frequency in to percentage Change the percentage in to degrees, where: degree= percentage x 360 Draw a circle and divide it accordingly

21. Example : See the immunization status of children in ‘X’ Kebele , August, 2009 Figure 3: immunization status of children in ‘X’ Kebele , Augest , 2009

22. Data Interpretation and conclusions The last step in conducting a research study is to interpret the findings in the discussion section, draw conclusions, and make recommendations. The conclusions and recommendations must be directly related to the data that was collected and analysed .