Introduction To Biostatistics
- Health Sciences
- 200 level
- 3 credit units
- 183 pages
- 28 units
This course introduces fundamental concepts and applications of Biostatistics in public health. It covers data collection methods, data presentation techniques using tables, diagrams, maps and graphs. The course also delves into numerical measures, measures of relationship, probability theories, and population distributions. Students will learn about sampling techniques, inferential biostatistics, parametric and non-parametric tests, and hypothesis testing. The course aims to equip students with the skills for data analysis and interpretation of statistical results.
About this course
- Difficulty
- Intermediate
- Study hours
- 150 hours
- Maths
- Intermediate
- Content
- Theoretical, practical, problem solving
- Practical work
- Yes
- Tutor Marked Assignments
- Final Examination
What you'll read
The real module and unit structure of PHS210, taken from the course material NOUN publishes.
One paragraph, so you can see how it reads
PHS210 · UNIT 1 DEFINITION AND APPLICATION OF BIOSTATISTICS
The examination concludes the assessment for the course. It constitutes 70 per cent of the whole course. You will be informed of the time for the examination.
What you should be able to do
- Define and explain the scope of Biostatistics
- Understand methods of data collection and presentation
- Discuss probability theories and population distribution
- Explain commonly used test statistics
- Acquire skills for data analysis
- Interpret test statistic results
What it prepares you for
- Public Health Officer
- Biostatistician
- Data Analyst
- Research Scientist
- Epidemiologist
- Healthcare
- Pharmaceuticals
- Research Institutions
- Government Agencies
- Public Health Organizations
Where it gets hard
The units students slow down on, and what makes each one heavy.
- Module 8: Inferential Biostatistics
Unit 2: Hypothesis Testing
Understanding the concepts of hypothesis testing requires a solid foundation in statistical inference and probability.
- Module 9: Non-Parametric Tests
Unit 1: Chi-Square Test
Chi-Square test requires understanding of contingency tables and application of Yate's correction.
- Module 10: Parametric Tests
Unit 1: T-Test
T-test requires understanding of sample distributions and assumptions about population variance.
A suggested way through it
13 weeks, about 41 hours in total. Yours will differ.
- Week 1Module 1: Introduction to Biostatistics and Data Management
Unit 1: Definition and Application of Biostatistics · 2 hours
Define Biostatistics. Explain concepts. Discuss applications in public health.
Unit 2: Data, Data Sources · 2 hours
Define data. Identify data sources. Differentiate raw data from statistics.
- Week 2Module 1: Introduction to Biostatistics and Data Management
Unit 3: Methods of Data Collection · 2 hours
Explain methods of data collection. Discuss validity of methods. Ensure data integrity.
Unit 4: Measuring Instruments · 2 hours
Explain types of measuring instruments. Identify appropriate instruments. Ensure instrument validity.
- Week 3Module 2: Screening Tests and Variables
Unit 1: Defining Screening Tests · 3 hours
Define screening tests. Explain validity and reliability. Calculate sensitivity and specificity.
- Week 4Module 2: Screening Tests and Variables
Unit 2: Variables and Classification of Variables · 3 hours
Define variables. Classify variables. Give examples of each class.
- Week 5Module 3: Organization and Presentation of Data
Unit 1: Tabular Presentations · 3 hours
List tables used in data presentation. Describe features of a good table. Construct various tables.
- Week 6Module 3: Organization and Presentation of Data
Unit 2: Diagrammatic Presentation of Data · 3 hours
State types of diagrams. State properties of a good diagram. Identify appropriate diagrams for variables.
- Week 7Module 3: Organization and Presentation of Data
Unit 3: Maps and Graphs · 3 hours
Define map diagrams and graphs. Identify appropriate diagrams. Construct maps and graphs.
- Week 8Module 4: Numerical Measures
Unit 1: Measures of Central Tendency · 3 hours
Define mean, median, and mode. Calculate measures of central tendency. Understand applications and limitations.
- Week 9Module 4: Numerical Measures
Unit 2: Measures of Location · 3 hours
Define quartiles, quintiles, deciles, percentiles. Explain concept and usage. Understand advantages and limitations.
- Week 10Module 4: Numerical Measures
Unit 3: Measures of Dispersion or Variability · 3 hours
Define standard deviation, variance, coefficient of variation. Calculate and interpret values. Explain comparative advantages.
- Week 11Module 5: Measures of Relationship and Probability
Unit 1: Measures of Relationship · 3 hours
Define linear correlation, Spearman's rank, Pearson's coefficient. Calculate and interpret values. Construct scatter grams.
- Week 12Module 5: Measures of Relationship and Probability
Unit 2: Probability · 3 hours
Define probability. State probability theories. Calculate and interpret probabilities.
- Week 13Module 6: Population Distributions
Unit 1: Normal Distribution · 3 hours
Define normal distribution. Mention properties of normal distribution. Discuss importance of Gaussian curve.
Preparing for the exam
- Focus on understanding the core concepts of each module, especially data collection, presentation, and analysis.
- Practice applying different statistical tests (T-test, Chi-Square) to sample datasets.
- Create summary tables for each module, highlighting key formulas and their applications.
- Review all Tutor-Marked Assignments (TMAs) and understand the solutions thoroughly.
- Allocate sufficient time for practicing calculations and interpreting results.
- Pay special attention to the assumptions underlying each statistical test.
- Create concept maps linking Units 3-5 data presentation and numerical measures.
- Practice hypothesis testing steps from Units 7-9 weekly.
- Review all examples and illustrations provided in the course material.
- Focus on understanding the differences between parametric and non-parametric tests.
Questions students ask about this course
What is PHS210 about?
This course introduces fundamental concepts and applications of Biostatistics in public health. It covers data collection methods, data presentation techniques using tables, diagrams, maps and graphs. The course also delves into numerical measures, measures of relationship, probability theories, and population distributions. Students will learn about sampling techniques, inferential biostatistics, parametric and non-parametric tests, and hypothesis testing. The course aims to equip students with the skills for data analysis and interpretation of statistical results.
How many units does PHS210 have?
PHS210, Introduction To Biostatistics, has 28 units across 10 modules, over 183 pages of course material. You can read it one unit at a time.
How many credit units is PHS210?
PHS210 carries 3 credit units, at 200 level in Health Sciences.
Is PHS210 hard?
PHS210 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical, practical and problem solving work, and it has a practical component.
How long does PHS210 take to study?
About 150 hours of study, spread across its 28 units.
How is PHS210 assessed?
PHS210 is assessed by Tutor Marked Assignments and Final Examination.
What can I do with PHS210?
Public Health Officer, Biostatistician, Data Analyst, Research Scientist and Epidemiologist.