Basic Quantitative Analysis (BQA-3)

Prerequisites

This module introduces students to four of the most commonly used statistical tests in the social sciences: correlation, chi-square tests, t-tests, and analysis of variance (ANOVA). Building upon the univariate techniques introduced in the Foundations in Applied Statistics module, these sessions aim to provide students with a thorough understanding of statistical methods designed to test associations between two variables (bivariate statistics). Students will learn about the assumptions underlying each test, and will receive practical instruction on how to generate and interpret bivariate results using Stata.

Bookings

Before a place can be booked for them, all students wishing to book a place on this module must have either:

• Completed the SSRMC Skill Check

OR

• Have successfully completed Foundations in Applied Statistics (FiAS)

Students that have already completed the SSRMC Skill Check may have had a place booked for them by their Department. Students can check this by typing their CRSid into the search box at the very top right of this page, hitting the enter key then clicking on their name. This will show all module(s) that they are booked onto, as applicable.

Students for whom this module is not compulsory can make a booking via the Basic Statistics Stream Booking Form on the SSRMC website.

In cases where you have a problem or a clash, please contact the SSRMC Administrator who will try to help you.

This module is designed for MPhil and PhD students as part of the Social Science Research Methods Centre (SSRMC) training programme - a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

• Successful completion of Foundations in Applied Statistics or equivalent level of knowledge, verified by the SSRMC Skill Check
• Enrolment on this module's Moodle course page: How to Enrol on Moodle
• To use the Titan Teaching Room computers you must bring your password for the Desktop Services system. Please note, your password for the Desktop Services system is distinct from your Raven/department/email password. If you are uncertain about this you are advised to go to the University Computing Service Helpdesk before the first day of class or find out more on the UCS Newcomers page.

Number of sessions: 4

• Correlation
• Chi-square
• T-tests
• ANOVA
• Multivariate techniques

• The objective is to learn of the assumptions underlying each test
• To receive practical instruction on how to generate and interpret bivariate results using Stata

To study four most commonly used statistical tests in social sciences:

1. Correlations
2. Chi-square tests
3. T-tests
4. One-way ANOVAS

Presentations, demonstrations and practicals

Stata on MCS

• Weekly (optional) online class tests
• One final online assessment [optional, dependent upon department]
• The SSRMC encourages all students to take the assessment

"TBA

All students are expected to give feedback for each module they take...

At the end of each module, students will be sent a link to a very short evaluation form. They will also be able to find this link on the Moodle page for their course. The survey takes a few minutes to fill in, and can even be done on a mobile phone. Students that do not respond to the survey the first time, will receive regular automated reminders until the survey is completed.

Students will not be given certification or proof of attendance for any module for which they have not provided feedback.

• To gain maximum benefits from the course it is important that students do not see this course in isolation from the other MPhil courses or research training they are taking.
• Responsibility lies with each student to consider the potential for their own research using methods common in fields of the social sciences that may seem remote. Ideally this task will be facilitated by integration of the SSRMC with discipline-specific courses in their departments and through reading and discussion.

8 hours over 2 weeks (4 hours lectures; 4 hours lab)

1 morning lecture and 1 afternoon lab session per week, for 2 weeks

• Foundations in Applied Statistics (FiAS-6)
• Basic Quantitative Analysis (BQA-6)
• Doing Multivariate Analysis (DMA 3)
• Further Topics in Multivariate Analysis (FTMA) 2