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

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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