- Offered for Year: 2022/23
- Module Leader(s): Professor John Wildman
- Lecturer: Dr Grega Smrkolj, Dr Saumik Paul
- Owning School: Newcastle University Business School
- Teaching Location: Newcastle City Campus
Semesters
|
Semester 1 Credit Value:
|
10
|
|
Semester 2 Credit Value:
|
10
|
|
ECTS Credits:
|
10.0
|
Aims
To develop an understanding of basic probability theory, so that decision making under uncertainty can be analysed.
To develop an understanding of statistical inference as a foundation for applied economics.
This module is an introduction to statistics and data analysis for economists. The first semester deals with the fundamental issues of statistics, building from basic probability theory, through sampling, distributions, hypothesis testing and interpretation. A wide range of examples is considered. The second semester moves into data analysis. We use a variety of statistical methods to investigate and interpret real world data.
The module will also include an introduction to statistical software.
Outline Of Syllabus
Probability
Discrete and Continuous Random Variables
Probability Distributions
Estimation and Sampling Distributions
Hypothesis Testing
Describing Data
Learning from Data
Graphical and Numerical Analysis of Data
Correlation versus Causation
Introduction to Regression Analysis
Multiple Regression
Statistical inference for Regression: Hypothesis Testing, Confidence Intervals, Prediction
Nonlinear Models
Estimation Problems
An introduction to Stata
Teaching Methods
Teaching Activities
| Category |
Activity |
Number |
Length |
Student Hours |
Comment |
|---|
| Scheduled Learning And Teaching Activities | Lecture | 16 | 2:00 | 32:00 | PiP Lectures |
| Guided Independent Study | Assessment preparation and completion | 1 | 60:00 | 60:00 | N/A |
| Guided Independent Study | Directed research and reading | 1 | 60:00 | 60:00 | N/A |
| Scheduled Learning And Teaching Activities | Small group teaching | 5 | 1:00 | 5:00 | PiP Seminars |
| Scheduled Learning And Teaching Activities | Small group teaching | 5 | 1:00 | 5:00 | PiP PC Labs |
| Guided Independent Study | Independent study | 1 | 38:00 | 38:00 | N/A |
| Total | | | | 200:00 | |
Jointly Taught With
| Code |
Title |
|---|
| ECO1009 | Analysing Economic Data |
Teaching Rationale And Relationship
Lectures deliver the main concepts.
Seminars and PC labs provide students with an opportunity to enhance both theoretical and practical (computer-based) aspects of statistical analysis.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description |
Length |
Semester |
When Set |
Percentage |
Comment |
|---|
| Written Examination | 90 | 1 | A | 50 | When social-distancing measures prevent PiP invigilated examinations, this will be an online, time-limited PC exam. |
| Written Examination | 60 | 2 | A | 25 | When social-distancing measures prevent PiP invigilated examinations, this will be an online, time-limited PC exam |
Exam Pairings
| Module Code |
Module Title |
Semester |
Comment |
|---|
| ECO1009 | Analysing Economic Data | 2 | N/A |
Other Assessment
| Description |
Semester |
When Set |
Percentage |
Comment |
|---|
| Prof skill assessmnt | 2 | M | 25 | Group project - 2000 words (with peer review) |
Formative Assessments
Assessment Rationale And Relationship
Written examination ensures learning of theoretical concepts and is an appropriate way to assess problem solving skills under the time constraint as required in industry.
In the case of alternative assessments for semester 1 (50% of the module mark) and Semester 2 (25% of the module mark) being necessary due to circumstances, the Module Leader will in discussion with the DPD and the University, discuss possible acceptable online alternatives, such as a take home exam delivered online with a set time limit to complete (24 hours or less as deemed appropriate).
Group project demonstrates that students can analyse and interpret real world data.
Reading Lists
Timetable
