1. E LEMENTARY Chapter 1 Introduction to Bio-Statistics Chapter 1 Introduction to Statistics
2.
3. DATA:::DISCRETE OSERVATIONS OF ATTRIBUTES OR EVENTS THAT CARRY LITTLE MEANING WHEN CONSIDER ALONE REDUCE,SUMMERISE ADJUSTING FOR VARIATION INFORMATION TRANSFORMATION OF INFORMATION THROUGH INTEGRATION AND PROCESSING WITH EXPERIENCE AND PERCEPTION BASED ON SOCIAL AND POLITICAL VALUE INTELLIGENCE
4.
5.
6.
7.
8. Biostatistics is the application of statistical methods to the problems ofbiology, including human biology, medicine and public health Descriptive Biostatistics : It is the study of biostatistical procedures which deal with the collection, representation, calculation and processing. i.e., the summarization of data to make it more informative and comprehensible. It involves graphical and tabular to describe. Includes: Collecting Organizing Summerizing Presenting data Inferential Biostatistics: It constitutes the procedures which serve to make generalizations or drawing conclusions on the basis of the studies of a sample. This is also known as sampling biostatistics. Includes: Making inferences Hypothesis testing Determining relationship Making predictions
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29. Bio - Statistics Descriptive (Summarize & Describe data) Inferential ( draw conclusion) Qualitative Quantitative Estimation Hypothesis Testing Confidence Interval P Value Proportion, Percentage Rate, Ratio Central tendency (mean median, mode) Dispersion Standard deviation standard error mean variance
30.
31.
32.
33.
34. Computerized HMIS Data Collection at Health Facilities Form 6, 7 and 8) District Computer Unit Block Computer Unit Decision Support System State Directorate Health Managers / Program Officers Through Floppy Through FTP, using phone lines
Notes de l'éditeur
page 4 of text
Emphasize that a population is determined by the researcher, and a sample is a subcollection of that pre-determined group. For example, if I collect the ages from a section of elementary statistics students, that data would be a sample if I am interested in studying ages of all elementary statistics students. However, if I am studying only the ages of the specific section of elementary statistics, the data would be a population.
page 5 of text
page 6 of text
Understanding the difference between discrete versus continuous data will be important in Chapters 4 and 5. When measuring data that is continuous, the result will be only as precise as the measuring device being used to measure.
page 7 of text
Understanding the differences between the levels of data will help students later in determining what type of statistical tests to use. Nominal and ordinal data should not be used for calculations (even when assigned ‘numbers’ for computerization) as differences and magnitudes of differences are meaningless.
Students usually have some difficulty understanding the difference between interval and ratio data. Fortunately, interval data occurs in very few instances.