Introduction to Quantitative Research Methods

Lecturer:                         Dr Stephen Jivraj & Dr James Cheshire

Office Hours:                    TBC

Teaching:                         20 hours of lectures, 10 hours of computer tutorials

Credits:                           0.5 Course Units/ 4 US Credits/ 7.5 ECTS Credits

Assessment:                      One 3,000 word essay (100%)

Essay Deadlines:               Essay: Thursday 30 April 2015, 2pm

Attendance:                     Attendance is compulsory at all lectures and seminars for which students are timetabled.  Attendance will be monitored and no student will be entered for assessment unless they have attended and pursued the module to the satisfaction of the department.

USEFUL LINKS

Lecture and Seminar Times:

Online Timetable at www.ucl.ac.uk/timetable

Extenuating Circumstances

http://www.ucl.ac.uk/spp/intranet/ug/assessment/extenuating-circumstances

Penalties for Late Submission and Overlength Essays

http://www.ucl.ac.uk/spp/intranet/ug/assessment/essays

Essay Submission Information

http://www.ucl.ac.uk/spp/intranet/ug/assessment/essays

Essay Writing, Plagiarism and TurnItIn

http://www.ucl.ac.uk/spp/intranet/ug/assessment/essays

http://www.ucl.ac.uk/current-students/guidelines/plagiarism

http://www.ucl.ac.uk/Library/CitationPlagiarism.doc

Content

This module introduces students to quantitative methods in the social sciences. It assumes no knowledge of quantitative methods or statistical software. The course caters for students from diverse disciplinary backgrounds and adopts a practical hands-on approach to learning, with tutor supported computer tutorials. The course covers descriptive statistics (central tendency and variation), data visualisation, data access, probability, sampling, hypothesis testing, inferential statistics and ends with an introduction to simple linear regression. Students will be introduced to the R statistical software and work with real-world data.

By the end of the module, students will be able to:

• identify and understand levels of measurement
• examine and visualise data using descriptive statistics
• use basic commands in R
• understand probability and statistical inference
• conduct basic statistical tests
• run and interpret simple linear regression

Lectures and tutorials

Each week there will be an introductory lecture followed by a computer tutorial. The lecture will last two hours and the tutorial will last one hour. The lectures will introduce students to many of the ideas and issues relating to the various topics. The computer tutorials will provide an opportunity to implement the techniques covered in the lectures. The first four tutorials provide an introduction to R.

Assessment

The course is assessed through the completion of one essay based on the secondary analysis of survey data. It accounts for 100% of the total marks on the course. The essay must be a maximum of 3,000 words, excluding tables and bibliography. Please include the word count at the top of the essay. 

The deadlines for the essay is as follows:

Thursday 30 April 2015, 2pm                                     

You will find useful guidance for writing and presenting essays on the SPP student website. These guidelines are designed to help you, and you should read them carefully and do your best to follow them. Good essays give clear and focused answers to the question asked, they have clear structures, and they will be adequately and appropriately referenced. They do not provide a vague and unstructured discussion of the topic. Plagiarism is taken extremely seriously and can disqualify you from the course (for details of what constitutes plagiarism see http://www.ucl.ac.uk/current-students/guidelines/plagiarism).  If you are in doubt about any of this, ask the tutor.

Other non-assessed work

The computer tutorials will allow students to apply and test their knowledge of the material covered on the course and the weekly exercises should be submitted for feedback from the course tutor.