Essentials Of Epidemiology And Biostatistics In Medicine | Ikaze Inc

This course provides medical professionals with foundational knowledge and practical skills in epidemiology and biostatistics essential for understanding and conducting medical research, interpreting healthcare data, and making evidence-based clinical decisions. In which participants will gain proficiency in key concepts, methods, and tools used in epidemiology and biostatistics within the context of medical practice.

Course Content

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Introduction to Epidemiology 4 Topics Sample Lesson

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Definition and scope of epidemiology

Historical developments in epidemiology

Importance of epidemiology in medicine

Key concepts: population, incidence, prevalence, risk, and causality

Types of Epidemiological Study design 3 Topics

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Descriptive studies: cross-sectional and case reports, etc

Analytical studies: cohort, case-control, and experimental studies

Strengths and limitations of each study design

Study Measures and Measures of Association 3 Topics

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Types of data: categorical, continuous, and time-to-event

Measures of disease frequency: prevalence, incidence, and mortality rates

Measures of association: relative risk, odds ratio, and hazard ratio

Bias and Confounding in Epidemiology 3 Topics

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Sources of bias in epidemiological studies

Methods to minimize bias in study design and analysis

Types of confounding and strategies to control for confounding

Screening and Diagnostic Tests 3 Topics

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Principles of screening for disease

Characteristics of a good screening test

Diagnostic accuracy measures: sensitivity, specificity, positive and negative predictive value, and odds ratio

Introduction to Biostatistics 4 Topics

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Types of data and their distribution

Population parameters and sample statistics

Hypothesis testing: null and alternative hypotheses, type I and type II errors

Confidence intervals and p-values

Statistical analysis of data 5 Topics

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Sampling techniques and sampling distributions

Measures of central tendency, outliers and dispersion

Estimation of population parameters: point and interval estimation

Hypothesis testing with t-test, ANOVA, and chi-square test

Variables Distribution and graphical representation of data

Study Design and Sample Size Calculation 3 Topics

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Principles of good study design

Calculating sample size for different study designs

Power and effect size in sample size estimation

Survival Analysis 3 Topics

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Types of censoring: right, left, and interval

Kaplan-Meier method for survival analysis

Log-rank test and Cox proportional hazards model

Data Management and Analysis 4 Topics

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Data collection methods: questionnaire, experiment, and biomarkers

Data storage and quality control

Data cleaning and preparation for statistical analysis

Introduction to statistical software (e.g. SPSS, R, SAS)

Biostatistical Applications in Medicine 4 Topics

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Clinical trials and randomized controlled trials

Interpreting diagnostic and screening test results

Meta-analysis and systematic review

Epidemiological studies and public health interventions

Ethical Considerations in Epidemiological Research 4 Topics

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Ethical principles in conducting research and using human subjects

Data confidentiality and protection

Reproducibility and transparency in research

Plagiarism and authorship guidelines

Practical Applications and Questions 4 Topics

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Analysis and interpretation of epidemiological and biostatistical data

Presentation and discussion of case studies illustrating key concepts

Hands-on exercises with real-world datasets

Multiple Choice Questions with Explanation

References 3 Topics

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