代写Advanced Quantitative Research (PO92Q) Syllabus 2023.24代做数据库编程
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Syllabus 2023.24
1. Module overview
This module has two main aims: to introduce to a set of advanced statistical methods that are commonly used in quantitative social research; and, to prepare to make use of statistics in future research works, academic (such as master's or PhD dissertations) or extra-academic. The module is taught over term 2. Seminars are designed as ‘hands-on’ computer workshops, giving you direct experience of exploring and analysing data in the R environment. Applications and exercises will be based on existing, real-world, high-quality survey datasets. By the end of the module you should understand the basic principles of the statistical methods covered, appreciate their context of application, and knowhow to apply them and interpret their results.
PO92Qand PO91Q compare as follows:
- PO92Q builds directly on PO91Q, or on equivalent previous training. If you have not attended PO91Q, please contact me, so as to make sure that PO92Q suits your needs and skills. PO91Q focused on the fundamental principles of data analysis. PO92Q goes more in depth into the same principles, and elaborates further.
- Continuity on how seminars are run: weekly exercises should be practiced before the class. Attendance is required and participation encouraged. Seminar classes are for sharing solutions and Q&A—you should prepare the exercises before the class, not discover them in class.
- Difference in style. insistence is put on intuitive and visual demonstrations of concepts and methods, more than equations as in PO91Q. Visuals and words are capable of expressing statistics, both in the teaching and in your personal projects. However those keen in equations will be free to display them in exercises and assessment.
- Partial difference in data: we will focus on four large survey datasets (see list in section 5 below), some of which were used in PO91Q exercises. Essay titles will only refer to the BSA, the ESS and the WVS, but transposing a title to the BES is an option for those interested.
- Difference in assessment: One report based on pre-approved titles (instead of an examination in PO91Q). PO92Q insists more on the necessity of developing a personal research project, up to writing down the results. To achieve this, some exercises will be replaced by the analysis of the methodological content of published journal articles.
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To succeed in this module, it is not enough to attend, listen and review the exercises’ solutions. You need to engage actively with all the module content: follow lectures and case studies, do relevant readings, take quizzes, solve exercises, and work regularly on your personal projects. |
If you have concerns about your ability to access the module content due to any kind of disability or practical issue, please contact me and will do my best to accommodate. I aim to deliver the module material in a format that is convenient for all participants to use. Live Lecture Capture records of lectures will be available on Moodle shortly after the lectures, with captions. Unfortunately seminar recording is impossible for legal reasons.
2. Weekly timetable
Weeks 1-5 and 7-10 for lecture, seminar and individual advice & feedback hours. Week 6 (14/15 February), a.k.a. “reading week”, is not taught.
Lecture
Wednesdays, 10-11, in Sciences building “Concourse”, B2.02.
Seminars
• Group 1: Wednesday 11-13 in Zeeman A0.01
• Group 2: Thursday 9-11 in Library R0.41
• Group 3: Thursday 11-15 in Library R0.41
Choose your group at the beginning of term and please stick to it. If you have a clash and wish to switch group, please write to [email protected], copying [email protected].
Advice and feedback
Please make use of the Moodle Forum for topics of general interest, as we did in PO91Q. Email me or make appointment for questions and issues that have a personal character, such as illness, learning difficulty and reasonable adjustments, choice of modules or essay title, as well as advice on personal projects during term, and feedback on essays in May-June. A&F hours (seemy personal webpage) will be in weeks 1-5 and 7-10, on Mondays and Tuesday 14-15.
Moodle releases
Slides (pdf), case studies (in R), quiz (on Moodle), and exercises (in R): Friday noon.
Recording of the live lecture through Lecture Capture is released on Wednesday, shortly after the lecture.
Solutions to exercises (in R): Friday at 9am, so that everybody has maximum time to work autonomously on the exercises.
3. Schedule
It will run as follows, with possible minor amendments:
Week 1. Linear regression: revisions and advanced issues I
Week 2. Linear regression: revisions and advanced issues II
Week 3. Logistic regression I
Week 4. Logistic regression II
Week 5. Reading session
Week 7. Factor analysis I
Week 8. Factor analysis II
Week 9. Cluster analysis I
Week 10. Cluster analysis II
The topics above are a only selection among the most standard specific methods used in the social sciences. For further options, I recommend the Qstep Masterclasses, offered in priority to Warwick Social Sciences QM students. All term 2-3 topics are great complements to PO92Q: Quantitative Tet Analysis, Structured Query Language (SQL), Social Network Analysis, Multilevel Modelling, and Web data collection. Multilevel in particular is directly applicable to comparative research on PO92Q surveys.
4. Computers and software
We will be using R and R-Studio, two widespread standards in social science data analysis.
• R and R-Studio are freeware and easy to install: please share between 5 and 20 minutes (depending on your experience) to install them on your own as soon as you can, and in any case before your first seminar class. First install the last version of R from www.r-project.org, then the last, free version of RStudio Desktop on rstudio.com. Excel, a convenient complement for formatting outputs, can be downloaded from the Microsoft Office package on warwick.ac.uk/services/its (often preinstalled).
• Face-to-face seminars take place in a computer room with one post per student, where all softwares are normally pre-installed. You are welcome to use your own laptop as well.
• Outside the seminars, you may use the University Work areas—see the University IT webpage.
• If you need help with IT, such as about your Windows/Macintosh operating system, software installation or connection issues, please visit the University Help Desk. I am unfortunately materially unable to handle these issues, beyond helping you tailor and use the above-mentioned module-specific softwares.
• The University network (such as MyFiles) can be used to store your files and transfer easily between computers.
5. Data
As the focus of the module is on data analysis, and not data collection, we will use secondary data. This year the focus will be on the four datasets below. These are individual-level survey datasets. Skills you will acquire using these data will be easily transferable to other data in your future research. Datasets are available for free for academic purpose, for example from theUK Data Service website.
• TheBritish Social Attitudes (BSA 36, fieldwork 2018)asks over 3,000 people every year what it's like to live in Britain and how they think Britain is run. Since 1983 the survey has been tracking people's changing social, political and moral attitudes. It informs the development of public policy and is an important barometer of public attitudes used by opinion leaders and social commentators.”
• TheEuropean Social Survey (ESS round 9, 2018)is “a large-scale, cross-national, and longitudinal survey research program on basic human values. It provides insights into the ideas, beliefs, preferences, attitudes, values and opinions of citizens all over Europe. It is a unique research project on how Europeans think about life, family, work, religion, politics and society” .
• The World Values Survey (WVS wave 6, 2010-12), “a global research project, explores people's values and beliefs, how they change overtime and what social and political impact they have. Since
1981 a worldwide network of social scientists have conducted representative national surveys as part of WVS in almost 100 countries. The WVS measures, monitors and analyses: support for democracy, tolerance of foreigners and ethnic minorities, support for gender equality, the role of religion and changing levels of religiosity, the impact of globalization, attitudes toward the environment, work, family, politics, national identity, culture, diversity, insecurity, and subjective well-being.” Wave 7 is in progress; you may use these data, but make sure the countries you need are available.
• The British Election Study (BES 2017 Post-election Survey), "one of the longest running election studies world-wide and the longest running social science survey in the UK... Surveys have taken place immediately after every general election since 1964… The British Election Study is a non- partisan, objective independent study providing world-class data and research into British general elections. The British Election Study is committed to providing expertise which advances understanding of the British electorate to any interested party, as part of its broad commitment to public engagement and impact."
All these datasets are long (number of individuals) and wide (number of variables) enough to form. the basis of in-depth analyses on many social and political topics. They differ with respect to their geographical scope and their thematic focus. Some topics are shared by two or three of these datasets, in which case the difference is in the number and formulation of the questions on the topic, as well as in the availability of other, more standard questions.
Note that in your final essay, you may use two or more waves of the same survey for studying historical change or evolutions. Class exercises are limited to the most recent waves, but older waves and cumulative datasets are available. Beware of the size of the files: above 50 Mo, you might have trouble loading and processing the data. To reduce size, consult the documentation and on the web form for data downloading, only request the variables useful to your project.
Whatever the source of the data you use, do not forget to cite their authors as indicated on the documentation or the website.
6. Bibliography and other resources
Detailed weekly references, with pages and links towards resources, will be available on theWarwick Library Reading list from week 1. Most references are available at the University Library, mostly electronically.
In addition to textbooks, you are encouraged to read weekly one article with quantitative analyses in a journal of your discipline. Try and focus, more than on the substance, on the data, methods and tools at play, and how they correspond to the module’s weekly topics. As a matter of routine you could consult the most recent issues of a number of journals as they come into the library and establish for yourselves whether they contain pertinent articles. Search for applications of personal interest, as long as they include similar statistical developments as treated the corresponding week. Some journals tend to reduce quantitative analyses to a race to sophistication, which is sometimes sterile. I rather recommend journals that take a more open-minded approach to methods and publish articles that subordinate methods to research questions.
You could also consult on a regular basis one or more “reference” newspapers (e.g. Financial Times, Independent, Guardian, The Economist), blogs or other websites, where you will find considerable reference to quantitative studies. They provide plenty of examples of good and bad investigation.
You might also consider keeping a close eye on the National Centre for Research Methods materials, which provide introductions to a range of topics:
http://www.ncrm.ac.uk/resources/online/
7. Assessment
The essay is a 4,000-word maximum research report comprising: an explanation of the research question, a succinct literature review, hypotheses, justification of sample and variables, analysis, interpretation, and conclusion. It should make use of at least one of the methods listed in Section 3 above. Using two or more of these methods will be rewarded, as well as combining survey waves and/or countries.
Choose a title from the list on Moodle. I recommend thinking thoroughly about which title suits your purpose best. It should fit your personal interest and knowledge of a topic, possibly of a country or group of countries, as well as your choice of method from the module. There are more titles offered than students,so everybody should have enough time to identify their best fit.
The list of essay titles will be released on Friday 12.01, noon, on Moodle. Choosing a title will be possible between Friday 12.01, noon, and Friday 26.01, noon. Essay should be submitted on Thursday 03.05, noon, on Tabula.
A number of rules are put in place for two reasons: practising social scientific quantitative research in real conditions and ensuring module-level fairness across all students from distinct courses and disciplines.
Please check in the first place the general assessment rules in your departmental course regulations.
The following rules apply for all in PO92Q, even where they contradict the regulations from your department, whether PAIS, CIM or other (ask if you are not sure):
1. Deliver your essay in Word, or equivalent text format. You may deliver in pdf only in case you are using Latex.
2. Use the Essay Submission Cover Sheet available on Moodle, which includes the essay title exactly as you chose it, the word count without illustrations, the total word count, and an abstract of 150 to 200 words.
3. Use Times New Roman, size 11, line spacing 1.5 and justified alignment. No Word styles, no headers, no footers, no fancy formatting.
4. Be focused and precise in referencing. Theorising is not a goal perse in this module, only a means to elaborate a meaningful empirical research design. Do not use more than 15 references per essay. Always indicate pages or chapters, as a proof that you did read the reference. Do not cite what you did not read.
5. Use Harvard style. (many quick guides are available online): references between parentheses, such as ‘(name date: pages)’, together with a complete bibliography at the end of your essay.
6. Do not use notes. Either write a sentence in the main text, or do not write it.
7. Your appendix should contain:
- Up to one page of additional statistical outputs that are relevant to your essay, but not essential to it. Essential outputs should go into the main text.
- A full copy of your code. You may for example copy-paste your R-Studio source pane. The syntax should be structured in sections and subsections and commented using # signs.
8. Essays should not be more than 4,000 words each, without any minimum. Illustrations (graphs and tables) are included (see point 9 below) but title page, summary, bibliography and appendix are excluded.
9. For tables and figures, a page counts as 400 words. For example,a table or figure taking up half of a page counts as 200 words out of your 4,000 total. Illustrations should not count for more than 30% of your whole essay (i.e. equivalent to 1200 words). If you lack space, send a less important illustration into the appendix, or format your illustrations more concisely.
10. Penalties are automatically applied along PAIS rules for the following issues:
- Late delivery: 5 marks per 24 hours late (each 24-hour period is considered to be one working day).
- Excess length: 5 points for each 5% (200 words) in excess, or part thereof, that is: 5 pts between 4,001 and 4,200, 10 pts between 4,201 and 4,400, etc.
- Academic misconduct (plagiarism, contract cheating, etc.): when the marker suspects such a case, the essay is immediately transferred to the PAIS academic conduct committee, which then investigates. Do not take a chance.
11. If you receive any kind of assistance from an artificial intelligence, you have to cite it at the end of your text, before the bibliography. For example: “This essay was written with the assistance of Grammarly AI-powered text editor, version 5, 2024”. AI tools that hamper your ability to achieve the module’s learning outcomes are prohibited. For example, you cannot use AI to write down a literature review. Any suspicion of a breach of these rules will be reported to the PAIS academic conduct committee.