College of Medicine University of Malawi
By the end of this lesson you should be able Explain importance of Biostatistics Distinguish between types of variables Explain different types of measurement scales
Definition of Statistics
Statistics is the science that studies the collection and interpretation of numerical data. Field of statistics is divided into Mathematical and Applied statistics.
Applied statistics concerns the application of the methods of mathematical statistics to specific areas such as public health, economics etc Biostatistics is the branch of applied statistics that concerns the application of statistical methods to medical and biological problems
Importance of Biostatistics
To better understand reports of research studies in your field To obtain a foundation in statistical issues for designing and conducting your own research. To learn a few techniques for analyzing data
Variables, Measurement Scales and Summarizing data
Definition of a Variable
A variable is a characteristic that can have many different values.
Types of Variables
A categorical variable has values with interruptions or gaps between them (categories) A continuous variable has values that could, theoretically, be measured without gaps
Scales of Measurement
Nominal Ordinal Binary
Consists of a finite set of possible values or categories Always categorical
Qualitative categories which have no particular order. Examples:
Malaria AIDS Accident Other
Chewa Yao Tumbuka
Two qualitative categories Examples: Gender
Qualitative categories that have a natural order. As a result, we can decide that one outcome is "less-than" or "more-than" another.
View of statement that condoms can help prevent spread of AIDS Agree No opinion Disagree
Severity of diarrhea
None Mild Moderate Severe
Numerical measurements or counts May be categorical or continuous
There are a limited number of distinct possible values or group of values Examples: Number of children in a family Number of decayed, missing or filled teeth 2011 16
Numeric scale with infinitely many values between any two observed values. Examples: Weight in kg Age 2011 17
Nominal Ordinal Binary
Understanding the scale of measurement of data is key to knowing the correct methods for summarizing data graphical display of data analysis of data.