PHPS40190 Biostatistics I

Academic Year 2023/2024

Topics covered in this module include:
- Understanding data, types of variables, levels of measurement, distributions of data;
- Descriptive statistics, measures of central tendency, measures of dispersion;
- Summarising and presenting descriptive data; Graphical representation;
- Concept of sampling variation which underlies confidence interval estimation and significance testing;
- Standard errors of means & proportions. Confidence intervals for means & proportions;
- Application and interpretation of significance and confidence intervals;
- Hypothesis testing, statistical significance, Type 1 and Type II errors;
- Assumptions underlying statistical tests. Parametric and nonparametric techniques;
- Comparisons between groups; Choice of statistical techniques appropriate to the data and assumptions;
- Significance tests for differences in means (z test, t tests); CI's for differences in means;
- Significance testing for differences in proportions (chi sq tests, McNemar test); CI's for differences in proportions;
- Non parametric tests for differences in distributions / medians;
- Correlation, simple linear regression;
- Kaplan-Meier survival analysis;
- Introduction to use of multivariable methods.

Show/hide contentOpenClose All

Curricular information is subject to change

Learning Outcomes:

On completion of this module the student will:
- understand data and the implications of type of data and level of measurement for subsequent analyses;
- compute and interpret descriptive statistics appropriate to the data;
- understand sampling variation, significance testing and confidence intervals;
- compute and interpret confidence intervals for means and proportions;
- generate research hypotheses and know how to test them;
- know the assumptions underlying statistical techniques;
- choose and carry out appropriate statistical techniques for two-group comparisons;
- carry out appropriate statistical techniques for independent and paired comparisons;
- derive, present and interpret p values;
- understand, compute and interpret correlation coefficients and simple linear regression models;
- understand and interpret univariate survival methods;
- be familiar with statistical software to carry out descriptive and comparative analyses;
- have a broad overview of multivariable analysis.

Indicative Module Content:

- Data, types of variables, levels of measurement, distributions of data;
- Descriptive statistics, measures of central tendency, measures of dispersion and position;
- Methods used to summarise and present descriptive data;
- Statistical distributions; Basic probability theory;
- Sampling variation; Confidence interval estimation;
- Standard errors for means and proportions. Confidence intervals for means & proportions;
- Hypothesis testing, statistical significance, Type 1 and Type II errors;
- Assumptions underlying statistical tests. Parametric and nonparametric techniques;
- Comparisons between groups; Statistical techniques appropriate to data and assumptions;
- Significance tests for differences in means (z test, t tests); CI's for differences in means;
- Significance testing for differences in proportions (chi sq tests, McNemar Test); CI's for differences in proportions;
- Non parametric tests for differences in distributions / medians;
- Correlation, simple linear regression;
- Orientation to statistical software;
- Introduction to use of multivariable methods.

Student Effort Hours: 
Student Effort Type Hours
Lectures

24

Tutorial

6

Specified Learning Activities

8

Autonomous Student Learning

80

Total

118

Approaches to Teaching and Learning:
In-person classes; Group work;
Practice exercises; Tutorials;
Orientation to statistical software 
Requirements, Exclusions and Recommendations
Learning Requirements:


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: Multiple choice questions; Computations; Data interpretation Week 9 No Standard conversion grade scale 40% Yes

20

Examination: Statistical scenarios. Computations. Interpretation of data in tables and graphs. Single best answer questions. 2 hour End of Trimester Exam No Standard conversion grade scale 40% Yes

60

Examination: Multiple choice questions; Computations; Data interpretation Week 5 No Standard conversion grade scale 40% Yes

20


Carry forward of passed components
Yes
 
Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

In-trimester examinations: Marked individually. Group feedback. Individual feedback as required Examination: Individual feedback post results release on request.

Name Role
Parnian Jalili Tutor
Mr John Loughrey Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Autumn
     
Lecture Offering 1 Week(s) - Autumn: Even Weeks Tues 16:00 - 16:50
Lecture Offering 1 Week(s) - Autumn: All Weeks Wed 13:00 - 14:50
Autumn