1- Introduction to Biostatistics
Page 1: Introduction to Biostatistics
Biostatistics: The application of statistical methods to the field of biological sciences and medicine.
Page 2: Overview of Statistics and Biostatistics
Statistics: Art and science of data that involves:
Planning research
Collecting data
Describing data
Summarizing and presenting data
Analyzing data
Interpreting results
Making decisions or discovering new knowledge
Page 3: Application of Biostatistics
Biostatistics employs statistical tools across various fields including:
Business
Education
Psychology
Agriculture
Economics
It specifically refers to the application of statistical methods to biological and medical data.
Page 4: Goals of Biostatistics
Enhance the intellectual content of data.
Organize data into comprehensible formats.
Base validity on the test of experience.
Page 5: The Cycle of Statistical Investigation
Identify real problems and foster curiosity.
Pose a specific question.
Design methods for data collection.
Collect data and interpret the results:
Analysis and summary of data to address the original question.
Page 6: Understanding Data
Data: Raw material for statistics; defined as figures obtained by:
Counting (e.g., patient numbers)
Measurement (e.g., temperature, weight, blood pressure).
Page 7: Sources of Data
1. Routinely Kept Records:
Hospital medical records are rich sources of patient data.
Page 8: External Data Sources
2. External Sources:
Published reports, data banks, and research literature may contain pre-existing data relevant to research questions.
Page 9: Surveys as Data Sources
3. Surveys:
Can be used to gather specific information (e.g., transportation modes for clinic visits).
Page 10: Experimental Data Collection
4. Experiments:
Data is collected as a result of experiments (e.g., testing strategies for patient compliance).
Page 11: Variables in Measurement
Variable: A characteristic that can take on different values across subjects, such as:
Heart rate
Heights of adult males
Weights of preschool children
Patient ages.
Page 12: Constants in Observation
Constant: An observation that does not vary (e.g., number of fingers, number of eyes).
Page 13: Types of Data Classification
Different classifications for variables:
Categorical Measurements: Unordered categories.
Ordinal Measurements: Ranked categories.
Quantitative Measurements: Ordered intervals with equal spacing.
Page 14: Quantitative versus Qualitative Variables
Quantitative Variables: Numeric scales (e.g., height, weight).
Qualitative Variables: Characteristics that may not be measured but can be ranked (e.g., sex, blood group).
Page 15: Discrete and Continuous Variables
Discrete Variable: Has gaps in possible values (e.g., daily hospital admissions).
Continuous Variable: Can take any value within a given interval (e.g., height).
Page 16: Qualitative Variables
Qualitative Variables (Categorical or Nominal): Often explored in categories.
Page 17: Binary Qualitative Variables
Binary Variables (Two Categories): Attributes with a yes/no or presence/absence classification (e.g., male/female, disease/no disease).
Page 18: Qualitative Variables with Multiple Categories
1. Nominal: Variables without a rank (e.g., blood group).
2. Ordinal: Variables that can be ordered (e.g., stages of cancer).
Page 19: Conversion of Variables
Quantitative variables can be converted into categorical variables for analysis.
Page 20: Examples of Quantitative Variable Categorization
Systolic Blood Pressure Categorization:
140 mm Hg: Hypertensive
90-140 mm Hg: Normal
<90 mm Hg: Hypotensive
Blood Glucose Categorization:
120: Hyperglycemia
80-120: Normal
<80: Hypoglycemia
Page 21: Avoiding Inaccuracies
Address two main types of inaccuracies:
Imprecision: Random variability in results.
Bias: Systematic deviation from the truth.
Page 22: Understanding Population
Population: The total collection of values of a variable that is of interest (e.g., weights of all children in a school).
Populations can be finite or infinite.
Page 23: Understanding Samples
Sample: A subset taken from a population (e.g., weights of a fraction of children).