Biostatistics And Applications
- Health Sciences
- 800 level
- 3 credit units
- 238 pages
- 14 units
This course introduces students to biostatistics and its applications in public health, biological, and agricultural sciences. It covers statistical methodologies relevant to medical research, including data collection, presentation, and analysis. Students will learn descriptive techniques, probability, sampling procedures, estimation, hypothesis testing, and bivariate data analysis. The course aims to equip students with the statistical tools necessary for conducting and interpreting research in health-related fields, such as medicine, epidemiology, and public health.
About this course
- Difficulty
- Intermediate
- Study hours
- 200 hours
- Maths
- Intermediate
- Content
- Theoretical, practical, problem solving
- Practical work
- Yes
- Assignments
- Tutor Marked Assignments
- Final Examination
What you'll read
The real module and unit structure of PHS813, taken from the course material NOUN publishes.
One paragraph, so you can see how it reads
PHS813 · UNIT 1 BASIC STATISTICAL TERMS AND DATA COLLECTION METHODS
Biostatistics is a branch of biological science which deals with the study and methods of collection, presentation, analysis and interpretation of data. Biostatistics is also called biological statistics or biometry.
What you should be able to do
- Define and classify statistics
- Describe data collection and presentation methods
- Explain descriptive techniques for summary statistics
- Evaluate event probabilities
- Discuss sampling procedures and distributions
- Apply statistical techniques in medical and non-medical situations
What it prepares you for
- Biostatistician
- Public Health Analyst
- Data Analyst
- Research Scientist
- Epidemiologist
- Healthcare
- Pharmaceuticals
- Public Health
- Research Institutions
- Government Agencies
Where it gets hard
The units students slow down on, and what makes each one heavy.
- Module 3: Sampling Distributions and Estimation
Unit 3: Sampling Distributions of Sample Mean and Proportion
Requires strong understanding of statistical inference and probability distributions, which builds on previous modules.
- Module 4: Test of Hypothesis
Unit 1: Concepts in Testing a Hypothesis
Involves complex decision-making processes based on statistical evidence, requiring careful consideration of Type I and Type II errors.
A suggested way through it
13 weeks, about 78 hours in total. Yours will differ.
- Week 1Module 1: Introduction to Statistics, Study Designs and Data Presentation
Unit 1: Basic Statistical Terms and Data Collection Methods · 6 hours
Read definitions of statistics, biostatistics, and medical statistics.. Identify different types of data and data collection methods.. Complete Tutor-Marked Assignment 1a and 1b..
- Week 2Module 1: Introduction to Statistics, Study Designs and Data Presentation
Unit 2: Clinical Trial, Epidemiology, Study Designs and Sampling Methods · 6 hours
Differentiate between clinical trials and epidemiological studies.. Understand experimental and observational study designs.. Explore sampling methods and their applications.. Complete Tutor-Marked Assignment 2..
- Week 3Module 1: Introduction to Statistics, Study Designs and Data Presentation
Unit 3: Data Presentation: Tabular and Graphical Methods · 6 hours
Learn tabular and graphical methods for data presentation.. Construct frequency distribution tables.. Explore bar charts, pie charts, and histograms.. Complete Tutor-Marked Assignment 3..
- Week 4Module 2: Summary Measures and Probability
Unit 1: Measures of Location, Partition and Spread · 6 hours
Understand measures of location, partition, and spread.. Calculate mean, median, mode, quartiles, and percentiles.. Compute variance, standard deviation, and coefficient of variation.. Complete Tutor-Marked Assignments..
- Week 5Module 2: Summary Measures and Probability
Unit 2: Permutations, Combination and Introduction to Probability · 6 hours
Learn permutations and combinations.. Understand basic probability concepts.. Apply additive and multiplicative laws of probability.. Complete Tutor-Marked Assignments..
- Week 6Module 2: Summary Measures and Probability
Unit 3: Random Variables and Probability Distributions · 6 hours
Define random variables and probability distributions.. Explore discrete and continuous distributions.. Understand the normal distribution.. Complete Tutor-Marked Assignments..
- Week 7Module 3: Sampling Distributions and Estimation
Unit 1: Introduction to Statistical Inference and Sampling Distributions · 6 hours
Understand the concept of sampling distributions.. Differentiate between population and sample.. Explore the central limit theorem.. Complete Tutor-Marked Assignment..
- Week 8Module 3: Sampling Distributions and Estimation
Unit 2: Point Estimation and Confidence Interval · 6 hours
Learn point estimation and confidence intervals.. Understand properties of estimators.. Construct confidence intervals for population parameters.. Complete Tutor-Marked Assignment..
- Week 9Module 3: Sampling Distributions and Estimation
Unit 3: Sampling Distributions of Sample Mean and Proportion · 6 hours
Explore sampling distributions of sample mean and proportion.. Understand standard error.. Apply central limit theorem.. Complete Tutor-Marked Assignment..
- Week 10Module 3: Sampling Distributions and Estimation
Unit 4: Confidence Intervals for Population Mean and Proportion · 6 hours
Construct confidence intervals for population mean and proportion.. Apply t-distribution and z-distribution.. Interpret confidence intervals.. Complete Tutor-Marked Assignment..
- Week 11Module 4: Test of Hypothesis
Unit 1: Concepts in Testing a Hypothesis · 6 hours
Understand concepts in testing a hypothesis.. Formulate null and alternative hypotheses.. Define Type I and Type II errors.. Complete Tutor-Marked Assignment..
- Week 12Module 4: Test of Hypothesis
Unit 2: Test for Mean and Proportion of One and Two Samples · 6 hours
Conduct tests for mean and proportion of one and two samples.. Apply t-tests and z-tests.. Interpret results.. Complete Tutor-Marked Assignment..
- Week 13Module 4: Test of Hypothesis
Unit 3: One Way ANOVA and Chi Square Test · 6 hours
Perform one-way ANOVA and chi-square tests.. Compare means of multiple samples.. Analyze categorical data.. Complete Tutor-Marked Assignment..
Preparing for the exam
- Create flashcards for key statistical terms and formulas from Units 1-3.
- Practice hypothesis testing problems from Units 11-13 weekly.
- Review different sampling methods and their applications from Unit 2.
- Focus on understanding the assumptions and limitations of each statistical test.
- Create concept maps linking Units 3-5 probability concepts to real-world examples.
Questions students ask about this course
What is PHS813 about?
This course introduces students to biostatistics and its applications in public health, biological, and agricultural sciences. It covers statistical methodologies relevant to medical research, including data collection, presentation, and analysis. Students will learn descriptive techniques, probability, sampling procedures, estimation, hypothesis testing, and bivariate data analysis. The course aims to equip students with the statistical tools necessary for conducting and interpreting research in health-related fields, such as medicine, epidemiology, and public health.
How many units does PHS813 have?
PHS813, Biostatistics And Applications, has 14 units across 4 modules, over 238 pages of course material. You can read it one unit at a time.
How many credit units is PHS813?
PHS813 carries 3 credit units, at 800 level in Health Sciences.
Is PHS813 hard?
PHS813 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 PHS813 take to study?
About 200 hours of study, spread across its 14 units.
How is PHS813 assessed?
PHS813 is assessed by Assignments, Tutor Marked Assignments and Final Examination.
What can I do with PHS813?
Biostatistician, Public Health Analyst, Data Analyst, Research Scientist and Epidemiologist.