Biostatistics Tutorial 1: Measurement

Introduction to Biostatistics

• Biostatistics is a branch of statistics that deals primarily with the biological sciences and medical/health-related disciplines.
• Public health is primarily concerned with disease prevention in human populations, and epidemiology is the branch of public health that attempts to discover the causes of disease to make disease prevention possible.

Population and Sample

• A population is a collection of persons/things or characteristics in which we have an interest to investigate.
• A sample is a subset of a population.
• A sample should be a representative part of the population.

Variables

• A variable is a characteristic that takes on more than one value.
• Examples of variables include age, gender, business income and expenses, country of birth, capital expenditure, class grades, eye color, and vehicle type.
• If a sample consists of 50 males, then gender is not a variable in this sample but is termed a constant.

Independent and Dependent Variables

• An independent (explanatory) variable is the cause, and its value is independent of other variables in the study.
• A dependent (response) variable is the effect, and its value depends on changes in the independent variable.

Data Types/Measurement Scales

• Nominal data measures values that fall into categories with no natural numerical value.
• Ordinal data falls into categories that can be qualitatively ordered but have no intrinsic numerical value.
• Discrete data is measured quantities that take on specific values, usually integers.
• Continuous data is measured quantities not restricted to specific values.

Statistics

• A parameter is any summarization of the elements of a population.
• A statistic is any summarization of the elements of a sample.

Descriptive Statistics: Exploratory Data Analysis

• Exploratory data analysis (EDA) allows us to visualize distributions and relationships, detect errors, and assess assumptions for confirmatory analysis.
• EDA is the first step of data analysis.

Introduction to Biostatistics

• Biostatistics is a branch of statistics that deals primarily with the biological sciences and medical/health-related disciplines.
• Public health is primarily concerned with disease prevention in human populations, and epidemiology is the branch of public health that attempts to discover the causes of disease to make disease prevention possible.

Population and Sample

• A population is a collection of persons/things or characteristics in which we have an interest to investigate.
• A sample is a subset of a population.
• A sample should be a representative part of the population.

Variables

• A variable is a characteristic that takes on more than one value.
• Examples of variables include age, gender, business income and expenses, country of birth, capital expenditure, class grades, eye color, and vehicle type.
• If a sample consists of 50 males, then gender is not a variable in this sample but is termed a constant.

Independent and Dependent Variables

• An independent (explanatory) variable is the cause, and its value is independent of other variables in the study.
• A dependent (response) variable is the effect, and its value depends on changes in the independent variable.

Data Types/Measurement Scales

• Nominal data measures values that fall into categories with no natural numerical value.
• Ordinal data falls into categories that can be qualitatively ordered but have no intrinsic numerical value.
• Discrete data is measured quantities that take on specific values, usually integers.
• Continuous data is measured quantities not restricted to specific values.

Statistics

• A parameter is any summarization of the elements of a population.
• A statistic is any summarization of the elements of a sample.

Descriptive Statistics: Exploratory Data Analysis

• Exploratory data analysis (EDA) allows us to visualize distributions and relationships, detect errors, and assess assumptions for confirmatory analysis.
• EDA is the first step of data analysis.

This quiz covers the basics of biostatistics, including measurement, in the context of public health and epidemiology. It discusses the importance of quantitative methods in disease prevention and health investigations.