4. Biostatistics_2

What is inferential statistics?

The branch of statistics that uses sample data to make inferences or decisions about a population.

What does inferential statistics help measure?

Uncertainty and relationships between variables.

What are the main components of inferential statistics?

Sampling methods, estimation, hypothesis testing, and drawing conclusions about populations.

What is the purpose of sampling?

To select a representative subset of a population for valid inference.

What are the four probability sampling methods?

Simple random, systematic, stratified, and cluster sampling.

What are the four non-probability sampling methods?

Convenience, purposive, snowball, and quota sampling.

What factors determine sample size?

Population size, desired precision, confidence level, expected variability, and available resources.

What is estimation?

Using sample statistics to estimate unknown population parameters.

What is point estimation?

Using a single value to estimate a population parameter.

What is interval estimation?

Using a range of values to estimate a population parameter.

What is a confidence interval?

A range of values within which the population parameter is likely to lie.

What is hypothesis testing?

A statistical process used to test assumptions or claims about a population.

What does hypothesis testing determine?

Whether observed differences are statistically significant or due to chance.

Name three statistical tests commonly used in hypothesis testing.

t-test, ANOVA, and Chi-square test.

What is a random error?

An unpredictable error caused by unknown changes in measurements or environmental conditions.

Give two causes of random error.

Electronic noise and environmental changes.

How are random errors usually distributed?

They often follow a normal (Gaussian) distribution.

What is a systematic error?

An error caused by faulty instruments or incorrect measurement methods.

Give two causes of systematic error.

Faulty instruments and incorrect use of instruments.

What is probability?

The likelihood that an event will occur.

Name three applications of probability in health.

Risk estimation, diagnostic testing, and environmental exposure modelling.

What is the null hypothesis (H₀)?

The hypothesis that assumes no effect, no difference, or no relationship.

What is the alternative hypothesis (H₁ or Ha)?

The hypothesis that suggests an effect or difference exists.

What is the significance level (α)?

The probability of rejecting a true null hypothesis, usually 0.05.

What is a p-value?

The probability of obtaining results as extreme as those observed if the null hypothesis is true.

When should the null hypothesis be rejected?

When the p-value is less than or equal to the significance level (α).

When do you fail to reject the null hypothesis?

When the p-value is greater than α.

What is a Type I error?

Rejecting a true null hypothesis (false positive).

What is another name for a Type I error?

False positive.

Give a medical example of a Type I error.

A test indicates disease when the patient is healthy.

What is a Type II error?

Failing to reject a false null hypothesis (false negative).

What is another name for a Type II error?

False negative.

Give a medical example of a Type II error.

A test shows a patient is healthy when they actually have the disease.

What increases the chance of a Type II error?

Low statistical power, small sample size, or strict significance criteria.

What is a t-test?

A statistical test used to compare the means of two groups.

When should a t-test be used?

When comparing exactly two group means.

What is a Chi-square test?

A statistical test that compares observed and expected frequencies for categorical data.

When should a Chi-square test be used?

When testing associations between categorical variables.

What is ANOVA?

Analysis of Variance, a test that compares the means of three or more groups.

When should ANOVA be used?

When comparing means across three or more independent groups.

What does correlation measure?

The strength and direction of a linear relationship between two variables.

What does regression estimate?

The numerical relationship used to predict one variable from another.

When is correlation used?

When examining whether two continuous variables are related.

When is regression used?

When predicting an outcome using another variable.

Which statistical test compares two group means?

t-test.

Which statistical test compares three or more group means?

ANOVA.

Which statistical test examines associations between categorical variables?

Chi-square test.

Which statistical method measures relationships between continuous variables?

Correlation.

Which statistical method predicts outcomes?

Regression.

What is environmental health?

The branch of public health concerned with environmental factors affecting human health.

What is the main goal of environmental health?

To prevent and control environmental hazards.

What disciplines contribute to environmental health?

Science, policy, and community engagement.

Name eight areas included in the scope of environmental health.

Air, water, waste, housing, occupational health, chemical hazards, biological agents, and the physical environment.

Name six environmental determinants of health.

Pollution, sanitation, climate, built environment, air quality, and water quality.

What are three major sources of air pollution?

Industrial emissions, vehicle exhaust, and indoor cooking fuels.

Name three health effects of air pollution.

Respiratory disease, cardiovascular disease, and cancer.

What does WASH stand for?

Water, Sanitation and Hygiene.

Why is WASH important?

It prevents disease and promotes safe water, sanitation, and hygiene.

Which Sustainable Development Goal is linked to WASH?

SDG 6 – Clean Water and Sanitation.

What are the two main types of waste?

Solid waste and hazardous waste.

Why is proper waste management important?

It reduces health risks and environmental contamination.

What topics are covered under food safety?

Foodborne disease, food contamination, environmental food hazards, and regulatory frameworks.

Name four examples of chemical hazards.

Pesticides, heavy metals, chronic exposure, and industrial chemicals.

Name three biological hazards.

Vector-borne diseases, zoonotic diseases, and environmental reservoirs of pathogens.

What does occupational health focus on?

Preventing workplace hazards and protecting workers' health.

Name three types of workplace hazards.

Physical, chemical, and biological hazards.

What are the major health effects of climate change?

Heat-related illness, extreme weather events, spread of vectors, and food and water insecurity.

What are the four steps of risk assessment?

Hazard identification, exposure assessment, dose-response assessment, and risk characterization.

What is environmental surveillance?

Monitoring environmental exposures and disease trends.

What role does biostatistics play in environmental surveillance?

It supports monitoring, analysis, and decision-making.

What does policy and regulation in environmental health include?

National laws, international regulations, WHO guidelines, and environmental impact assessments.

What is the importance of community participation in environmental health?

It promotes health education, advocacy, and community-based interventions.

What are the main roles of environmental health practitioners?

Inspection, monitoring, policy enforcement, health promotion, and emergency response.

Why are biostatistics and environmental health integrated?

To support evidence-based decisions, programme evaluation, and data-driven interventions.

What are four major challenges in environmental health?

Urbanization, climate change, limited resources, and weak regulation enforcement.

What are four future directions in environmental health?

Sustainable development, green technologies, stronger surveillance systems, and climate-resilient health systems.

What are the key takeaways from the lecture?

Data guides health action, environmental factors affect health, biostatistics improves understanding of risks, and prevention is the cornerstone of environmental health.