PR2000 – Assignment 1
2020-2021
Research Report using quantitative methods
Examining relationships between two variables is often at the hart of answering research questions. But to move beyond a simple correlation we also need to consider the causal mechanisms that underlie the relationship, the possible direction of causation, and what other variables need to be taken into account or controlled for. In your first PR2000 assignment you will address these issues with regards to a relationship of your own choosing, using the Quality of Governance (QOG) dataset introduced during the course.
You will also statistically examine this relationship using regression analysis and present your findings with the aid of appropriate charts and tables. The maximum length for this assignment will be 2,000 words, not including bibliography or appendix.
For the assignment, you can choose to examine any political science or IR-related relationship that interests you, as long as it is based on variables found in the QOG- dataset. You will have to motivate the relevance of the relationship that you examine, describe a credible causal mechanism underlying it, as well as discuss the direction of causality and important control variables that need to be taken into account. Specifically, in your assignment you will identify three variables in the QOG-dataset.
One outcome variable (y), one explanatory variable (x), and one control variable (z). You need to discuss how each is operationalised using the QOG codebook and other recourses, and provide descriptive statistics from the QOG dataset. You will use regression analysis to examine the relationship between x and y, taking into account the type of variables that are possible to examine using this method .
You will also use multivariate regression 1analysis to control for one possible confounding variable (z) that might make the relationship spurious. The final paper must include two tables (see templates below) and one figure that help you describe the variables and report the findings of your analysis. You will carry out the analysis using R and you must include your R script at the end of the assignment.
Assessment
We will use the step marking scheme consistent with your other modules. For more info on the margin schemes, see the UG handbook. Also refer to the UG handbook for departmental policy on essay submission, rules for word count, late penalties and plagiarism.
Note that the outcome variable in a regression analysis needs to be continuous. We will go 1 through this in detail during the course, especially in Weeks 4 and 5.
Research Report
This is not a normal essay. The quantitative report will include five distinct sections. These
sections are: 1) Introduction, 2) Theory and Hypothesis, 3) Data and Method, 4) Analysis
and Results, and 5) Conclusion. Below you will find additional information about each of
these five sections. For each section, you will be given examples of the information to
include in your answers. Ideally, your answers would very concisely and directly address
as much of this information as possible. Please note that the suggested word counts
provided below are only general guidelines.
The research report must include the following:
Cover Sheet (not included in word count)
The title page should include the following information:
– The title of your assignment
– The module code and name
– The seminar tutor’s name
– Your candidate number (not your student number)
– The word count (excluding the bibliography, and the title page, and R script)
1. Introduction (300 words)
Briefly introduce the relationship that you are examining in the research report. Describe the relationship, clearly mentioning which variables you have selected as outcome variable, explanatory variable, and control variable. Provide a motivation for why it is relevant to examine this relationship. This motivation may focus on the academic or political importance of the relationship, or both of these.
2. Theory and Hypothesis (400 words)
Describe the causal mechanisms that connects your outcome (y) and explanatory variable (x). You need to draw on existing literature to provide some support for your theoretical argument (two or three sources is sufficient). Discuss also whether you can rule out that y is not causing x. Formulate a concrete hypothesis for the main relationship you intend to examine. A hypothesis is presented as an empirical statement.
Discuss also the possibility that the relationship between the two variables could be spurious and present one important variable (z) that should be controlled for in the analysis.
3. Data and Methods (400 words)
Describe the operationalisation of each of the three variables that you have identified and report their level of measurement. Also present relevant descriptive statistics for each variable, including the number of observations, mean, standard deviation, and minimum and maximum values. You can copy the template table below to present these statistics.
You will however need to also describe the statistics in the text. Briefly also describe the main method – regression analysis – that will be used to analyse these variables, and how this will allow you to test the set out hypothesis..
4. Analysis and Results. (500 words)
Present one appropriate chart (e.g. scatterplot, bar-plot comparing means) to describe
the relationship between your outcome variable and explanatory variable. Make sure to
describe your interpretation of the chart in the text.
Present the findings of your regression analysis. You can copy the template below for this.
In Model 1 present only the analysis including the outcome and explanatory variables,
while in Model 2 add to these also the control-variable. Report relevant figures for the
regression coefficient of the main explanatory variable as well as model fit for each
model. Interpret your results and comment on whether the main hypothesis is supported or
rejected by your analysis.
5. Conclusion (400 words)
Briefly reflect on the findings of the analysis. To which extent do they overlay with your
reading of the literature? Also discuss the limitations in this study.
Bibliography (not included in word count)
R Script (not included in word count)
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