Introduction to Statistics
| Module title | Introduction to Statistics |
|---|---|
| Module code | BEE1022 |
| Academic year | 2025/6 |
| Credits | 15 |
| Module staff | Dr Ellen Greaves (Convenor) Dr Eva Poen (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 280 |
|---|
Module description
This module aims to equip you with the knowledge, skills and understanding of statistics and probability that are required for the study of modern economics at undergraduate level.
As well as covering probability theory, descriptive statistics and inference, the module will introduce you to working with spreadsheets in MS Excel for the purpose of data organisation, descriptive statistics and probability related tasks.
Additional Information:
Internationalisation
The content of this module is universal and applicable around the world. It includes international examples with real statistical data from countries such as China, India, Europe and the UK.
Employability
Knowledge of statistics is essential for any business or economics student, so this module provides students with a valuable theoretical and practical understanding of the subject, as well as weekly assignments that enable them to work consistently with continuity and discipline. Students will acquire transferable software skills that are valuable in the workplace.
Sustainability
All of the lecture notes and tutorial sets are available on the ELE (Exeter Learning Environment).
Module aims - intentions of the module
- Descriptive statistics
- Probability
- Discrete and continuous random variables
- Bivariate distributions, conditional probabilities and conditional means
- Covariance, correlation, independence
- The expectation operator
- Moments of random variables
- Sampling distributions of the sample mean and the sample proportion
- Confidence intervals for the population mean and population proportion
- Hypothesis tests about the population mean and population proportion
- Introduction to basic concepts in the analysis of time series data
- Confidence intervals for the population variance
- Variance ratio test
- Test for independence and goodness-of-fit test
Throughout the course: The use of MS Excel for descriptive statistics, probability, time series and inference.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Construct charts and calculate appropriate descriptive statistics to summarise a data set
- 2. Demonstrate understanding of discrete and continuous random variables, their marginal and joint probability distributions and their moments
- 3. Solve a range of problems involving probability
- 4. Conduct hypothesis tests and interpret their results
- 5. Demonstrate understanding of the basic properties of time series data
- 6. Use MS Excel competently to organise data, calculate descriptive statistics and work with probabilities
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 7. Demonstrate awareness of the role of numerical evidence in economics
- 8. Demonstrate understanding of the advantages, disadvantages, and limitations of different quantitative methods
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 9. Demonstrate quantitative, computational and computer literacy skills
Syllabus plan
Syllabus:
- Descriptive statistics
- Probability
- Discrete and continuous random variables
- Bivariate distributions, conditional probabilities and conditional means
- Covariance, correlation, independence
- The expectation operator
- Moments of random variables
- Sampling distributions of the sample mean and the sample proportion
- Confidence intervals for the population mean and population proportion
- Hypothesis tests about the population mean and population proportion
- Introduction to basic concepts in the analysis of time series data
- Confidence intervals for the population variance
- Variance ratio test
- Test for independence and goodness-of-fit test
Throughout the course: The use of MS Excel for descriptive statistics, probability, time series and inference.
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 32 | 118 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled learning and teaching activity | 22 | Lectures |
| Scheduled learning and teaching activity | 10 | Tutorials or classes |
| Guided independent study | 118 | Reading, question practice, class and assessment preparation |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Weekly exercises | 50 minutes | 1-9 | In class |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 10 | 70 | 20 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Five online homework quizzes | 10 | ca. 30 minutes each | 1-6 | ELE |
| Excel-based exam | 20 | Up to 15 questions/1500 words | 1-4, 6, 9 | ELE |
| Final examination | 70 | 1.5 hous | 1-9 | Final grade; feedback will be posted on ELE |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Five online homework quizzes (10%) | Single online homework quiz (10%) | 1-6 | Referral/deferral period |
| Excel-based exam (20%) | Excel-based exam (up to 15 questions / 1500 words) | 1-4, 6, 9 | Referral/deferral period |
| Final examination (70%) | Examination (1.5 hours, 70%) | 1-9 | Referral/deferral period |
Re-assessment notes
Referrals and deferrals will normally take place in the August/September Reassessment Period.
If you pass the module overall, you will not be referred in any component – even if you have not passed one or more individual components.
Indicative learning resources - Basic reading
Indicative reading list: selected chapters of some or all of the following textbooks:
- Utts, Jessica M and Heckard, Robert F. (2015), Mind on Statistics, 5th edition, Cengage Learning. ISBN: 978-1-285-46318-6
- Barrow, M. (2017) Statistics for Economics, Accounting & Business Studies, 7th edition, Harlow: Pearson Education
- Cortinhas, C. and Black, K. (2012), Statistics for Business and Economic, 1st European Edition, Chichester: John Wiley and Sons, Ltd. ISBN: 978-1-119-99366-7
- Peck, R., Short, T. and Olsen, C. (2020), Introduction to Statistics and Data Analysis, 6th edition, Cengage Learning. ISBN: 978-1-337-79361-2
- Anderson, D., Sweeney, D., Williams, T., Camm, J., Cochran, J., Fry, M. and Ohlmann, (2020) ‘Essentials of Statistics for Business and Economics’, Cengage Learning, ISBN: 978-0-357-04543-5
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | Grade B or higher in A-Level Mathematics (or equivalent) |
| Module co-requisites | None. Non-requisites: Cannot be taken with BEE1025, BEM1024, BEA1012 or BEA1014. Cannot be taken by students who are taking/have taken MTH1004. |
| NQF level (module) | 4 |
| Available as distance learning? | No |
| Origin date | 01/09/2006 |
| Last revision date | 11/02/2025 |
