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# PHPS40190

#### Biostatistics I (PHPS40190)

Subject:
Public Health & Population Sci
College:
Health & Agricultural Sciences
School:
Public Hlth, Phys & Sports Sci
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Assoc Professor Mary Codd
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No

Curricular information is subject to change.

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.

###### 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
Specified Learning Activities

8

Autonomous Student Learning

80

Lectures

24

Tutorial

6

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 In Module Component Repeat Offered
Examination: Multiple choice questions; Computations; Data interpretation Week 5 No Standard conversion grade scale 40% Yes

20

Yes
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

Yes
Examination: Multiple choice questions; Computations; Data interpretation Week 9 No Standard conversion grade scale 40% Yes

20

Yes

Carry forward of passed components
Yes

Resit In Terminal Exam
Spring Yes - 2 Hour