COMS215-26S2 (C) Semester Two 2026

Introduction to Social Analysis

15 points

Details:
Start Date: Monday, 13 July 2026
End Date: Sunday, 8 November 2026
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 26 July 2026
  • Without academic penalty (including no fee refund): Sunday, 27 September 2026

Description

Data analysis is a powerful tool to investigate many important and interesting questions about societies and human behaviour. Policy decisions, your Netflix movie recommendations, or targeted advertisements on social media all rely on making sense of data. This course introduces students to basic skills of data analysis, statistical inference, and programming with a focus on applying these skills to questions in social sciences, politics, and media. Anyone can learn statistics. Graduates who can demonstrate skills in data analysis are highly valued by employers. Such skills are in demand in a wide range of sectors - public policy, public health, political campaigns, news media, business, journalism, law, communication, and information technology to name a few. This course aims to provide students with practical experience analysing and interpreting data. We will use powerful R programming language and open-source statistical software RStudio, both are employed routinely across many industries in many countries. The course requires no programming or coding experience.

Anyone can learn statistics. Data analysis and statistics are as important today as never before and this tendency will likely continue to grow. A title from The New York Times highlights these trends: “For Today’s Graduate, Just One Word: Statistics”.
Students will leave this course with fundamental knowledge and skills necessary to acquire more advanced skills in social data analysis. This course fulfils the prerequisite for POLS306 Craft of Social Science Research.

Learning Outcomes

After completing this course students will be able to:
• Examine steps of conducting quantitative research and data analysis in social sciences.
• Describe principles and concepts of inferential statistics, probability, and uncertainty estimation.
• Recognise and apply data ethics principles, including principles of the Māori data governance model, indigenous perspectives and lived realities to quantitative data analysis.
• Discuss features and limitations of different quantitative analytical tools and research methodologies.
• Choose and carry out an appropriate statistical analysis for given hypotheses and data.
• Properly and correctly interpret and communicate data outputs.
• Develop and apply fundamental skills in programming in R statistical language and free open-source statistical software RStudio when working with quantitative data.
• Critique, and evaluate statistical claims made in news media, policy reports, and in academic research.

Prerequisites

Any 15 points at 100-level COMS or POLS, or
any 60 points at 100-level from the Schedule V of the BA.

Restrictions

Equivalent Courses

Timetable 2026

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Tuesday 13:00 - 15:00 E6 Lecture Theatre
13 Jul - 23 Aug
7 Sep - 18 Oct
Computer Lab A
Activity Day Time Location Weeks
01 Wednesday 15:00 - 17:00 Jack Erskine 248 Computer Lab
13 Jul - 23 Aug
7 Sep - 18 Oct
02 Friday 12:00 - 14:00 Jack Erskine 248 Computer Lab
13 Jul - 23 Aug
7 Sep - 18 Oct

Course Coordinator

Joshua Wilson Black

Assessment

Assessment Due Date Percentage  Description
Final exam 30% On-campus in-person on-paper final exam scheduled during the examination period.
Participation 10%
Problem sets 60% You will complete five problem set assignments during the semester. They are equally weighted.

Textbooks / Resources

Required Texts

2. Boyle, M., & Schmierbach, M; Applied Communication Research Methods: Getting Started as a Researcher ; 3rd ed; Routledge, 2023.

Kellstedt, P. M., & Whitten, G. D; The Fundamentals of Political Science Research ; 3rd ed; Cambridge University Press, 2018.

Kukutai, T., Campbell-Kamariera, K., Mead, A., Mikaere, K., Moses, C., Whitehead, J. & Cormack, D; Maori data governance model ; Te Kahui Raraunga, 2023.

As additional optional resources, I will occasionally provide you with selected chapters from the following books (all available through the library):
• Berger, A. A. (2014). Media and Communication Research Methods: An Introduction to Qualitative and Quantitative Approaches. SAGE.
• Jensen, K.B. (Ed.). (2011). A Handbook of Media and Communication Research: Qualitative and Quantitative Methodologies (2nd ed.). Routledge. https://doi.org/10.4324/9780203357255
• Vogt, W. P. (2011). SAGE quantitative research methods. (Vols. 1-0). SAGE Publications, Inc., https://doi.org/10.4135/9780857028228 (Chapter On Quantitizing)

Software

In this course, we will be using the powerful R programming language and open-source statistical software RStudio. RStudio provides a user interface that makes programming in R easier. The University set up an RStudio server instance to support teaching R in UC. RStudio server can be accessed online through a link which will be provided in AKO|LEARN. Students might also consider installing the software on their personal computers (instructions will be provided in AKO|LEARN).

Indicative Fees

Domestic fee $948.00

International fee $4,263.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Language, Social and Political Sciences .

All COMS215 Occurrences

  • COMS215-26S2 (C) Semester Two 2026