# BSc Global Development with International Study

Year of entry: 2024

## Course unit details:Skills for Global Development Studies 2 (Quantitative Methods)

Unit code MGDI10032 20 Level 1 Semester 2 No

### Overview

This course unit introduces students to basic concepts in statistics and to practical statistical data analysis using Stata. The course unit assumes that students are familiar with material in GCSE maths, but there is revision of the key material in week 1. It is likely that the course will be delivered to a mixed-ability class: some students (but probably a minority) will have studied maths and/or statistics beyond the level of GCSE. The aims and learning outcomes relate to specific concepts in statistics (listed in weeks 2-10 of the lecture schedule). The learning outcomes are common to all students, regardless of their background, but students with A-Level maths and/or statistics will be given the option of alternative reading and assessment that allows them to demonstrate the learning outcomes while extending their understanding of the subject.

### Aims

This unit aims to:

• Introduce students to key concepts in statistics
• Equip students to apply the concepts to global development data using statistical software
• Develop students' ability to evaluate statistical methods and results in a critical manner

### Syllabus

Indicative weekly lecture and class schedule

1. Studying statistics; overcoming math anxiety; mathematical concepts
2. Frequency distributions
3. Descriptive statistics
4. The Normal curve
5. Percentiles and standard scores
6. Correlation coefficients
7. Linear regression
8. Inferential statistics
9. The t test
10. Analysis of variance

### Teaching and learning methods

Teaching and learning will be based on lectures and a problem-solving class (once per week). Lectures will combine presentation of the learning material with short small-group activities. Lecture slides and problem sets will be posted on Blackboard. The problem-solving classes will provide students with the opportunity to reinforce their learning through hands-on work with real-world data using Stata. Advice on how to prepare for each class – and for the assessments - will be posted on Blackboard.

Students will be provided with a range of resources to support their learning, including PowerPoint slides for lectures which will be posted to Blackboard for all sessions, links to relevant web resources, and comments on the relevant textbook chapter for each week.

To further support students’ skill development, students will also be signposted to optional sessions offered across the university to improve their research and academic skills, such as training and skills workshops offered by the University of Manchester Library.

### Knowledge and understanding

• Explain specific concepts in statistics
• Explain the assumptions on which these concepts rest
• Describe some of the applications

### Intellectual skills

• Evaluate the applicability of a statistical concept to a practical problem
• Interpret the results of statistical data analysis in terms of evidence (or the absence of evidence) for specific hypotheses about global development

### Practical skills

• Construct datasets using Excel and Stata
• Apply specific statistical concepts to data using Stata

### Transferable skills and personal qualities

• Apply the intellectual and practical skills above to data that is new to them

### Assessment methods

Method Weight
Project output (not diss/n) 100%

### Feedback methods

Verbal feedback on group activities will act as formative assessment for the three project-based assignments (weighted 30%, 30% and 40%).

Grade and comments on Blackboard. The content and timing of feedback will be consistent with University policy.

Students will be encouraged to further clarify any errors in their work during lecturer office hours.

This course unit is based on a single textbook:

Kranzler, J. H. and Anthony, C. J. (2022). Statistics for the Terrified (7th Edition). Rowman & Littlefield.

Additional reading will be provided to students with A-Level maths and/or statistics on a case-by-case basis. The assessment will be based on the textbook material, but students who already have a background in statistics will have the opportunity to develop their understanding and choose optional versions of the assessment activities that will draw on their additional reading.

### Study hours

Scheduled activity hours
Lectures 20
Tutorials 10
Independent study hours
Independent study 170

### Teaching staff

Staff member Role
Upasak Das Unit coordinator