# Group-Based Assignment in Quantitative Methods

\$200.00

Group-based assignment in quantitative methods
An independent group-based assignment is part of the examination for this course. As explained in
the syllabus (and in the course plan), the student must receive a pass on this assignment to receive a
The group is free to base its assignment on the data from either the World Value Study (WVS) or the
QoG-institute. That is, the assignment can either be based on analyses of data where countries are
the units of analysis (the QoG) or data where the units of analysis are individuals nested in different
countries (WVS). Building on either of these two databases, the group should select one dependent
variable and present hypotheses about independent variables that may explain variations in the
dependent variable.
The assignment should consist of no less than 4000 words (excluding Tables and Figures), but may
not exceed 4500 words. Moreover, statistical results must not be “copied and pasted” from the
output in the statistical software. Instead of using unedited output, students should present tables
and figures that could be published.
The group assignment is due on Wednesday the 8th of January at 14.00.
The assignment should consist of the following steps:
1. Introduction
a. Present a brief research problem where you highlight why it is theoretically
important to review variations in the phenomena (dependent variable) you have
chosen for your assignment. Your arguments should be based on relevant literature,
that you cite properly to support your claims. Moreover, given the global reach of
both datasets, your research problem should have a comparative perspective – that
is, the outcome you study should most likely differ between countries. Here, you
need to motivate why.
b. Present a clear and unambiguous aim of your assignment.
2. Theory and hypotheses
a. Present a brief, but theoretically grounded, discussion about the factors
(independent variables) that may affect variations in the dependent variable. Here it
is required that your arguments are based on relevant literature, that you cite
properly to back up your claims.
b. Based on this, present one or more hypotheses that you will test in your assignment.
Present these hypotheses properly.
c. Motivate a set of control variables that you use in your subsequent regression
analyses. Moreover, given the global nature of both datasets, countries are evident
control variables that should be included and motivated.
3. Descriptive statistics
2
a. Review the central tendency of your variables and discuss their variation in
substantive terms.
b. Explore the distribution of your dependent variable. Is it normally distributed? If not,
how may this affect your results? In case of highly shewed dependent variable, what
have you done to minimize this problem?
4. Correlation and bivariate regression analyses
a. Present correlations between all of the variables in your analyses. Interpret your
results in substantive terms. What do the correlations say about the suitability of
including all your variables in a multivariate regression analysis? Should some of the
variables be removed and/or replaced?
b. Present bivariate regression analyses to test the separate effect of each of your
independent variables. Comment substantially upon the strengths of the regression
coefficients as well as measures of ‘goodness-of-fit’ (R-squared and the standard
error of the estimate). Also, comment upon the statistical significance of the
relationships.
5. Multivariate regression analyses
a. Set up a model where all of your variables are regressed against the dependent
variable. Compare the results with the bivariate regressions and comment in great
detail upon regression coefficients as well as measures of ‘goodness-of-fit.’ Also,
comment substantially upon how the estimates differ between the bivariate and
multivariate analyses.
b. Add new models where you control the results from the previous model (5a) for (at
least 10 well argued) country dummies. Do these controls affect the results? What
do differences between coefficients for the country-dummies mean?
c. Add a new model with interactions between county-dummies and the one or more of
the central variables in the analyses. Comment substantially on the results in relation
to previous models.
6. Conclusions
the analyses. Why/why not?

Category: Tags: ,

## Description

Group-based assignment in quantitative methods
An independent group-based assignment is part of the examination for this course. As explained in
the syllabus (and in the course plan), the student must receive a pass on this assignment to receive a
The group is free to base its assignment on the data from either the World Value Study (WVS) or the
QoG-institute. That is, the assignment can either be based on analyses of data where countries are
the units of analysis (the QoG) or data where the units of analysis are individuals nested in different
countries (WVS). Building on either of these two databases, the group should select one dependent
variable and present hypotheses about independent variables that may explain variations in the
dependent variable.
The assignment should consist of no less than 4000 words (excluding Tables and Figures), but may
not exceed 4500 words. Moreover, statistical results must not be “copied and pasted” from the
output in the statistical software. Instead of using unedited output, students should present tables
and figures that could be published.
The group assignment is due on Wednesday the 8th of January at 14.00.
The assignment should consist of the following steps:
1. Introduction
a. Present a brief research problem where you highlight why it is theoretically
important to review variations in the phenomena (dependent variable) you have
chosen for your assignment. Your arguments should be based on relevant literature,
that you cite properly to support your claims. Moreover, given the global reach of
both datasets, your research problem should have a comparative perspective – that
is, the outcome you study should most likely differ between countries. Here, you
need to motivate why.
b. Present a clear and unambiguous aim of your assignment.
2. Theory and hypotheses
a. Present a brief, but theoretically grounded, discussion about the factors
(independent variables) that may affect variations in the dependent variable. Here it
is required that your arguments are based on relevant literature, that you cite
properly to back up your claims.
b. Based on this, present one or more hypotheses that you will test in your assignment.
Present these hypotheses properly.
c. Motivate a set of control variables that you use in your subsequent regression
analyses. Moreover, given the global nature of both datasets, countries are evident
control variables that should be included and motivated.
3. Descriptive statistics
2
a. Review the central tendency of your variables and discuss their variation in
substantive terms.
b. Explore the distribution of your dependent variable. Is it normally distributed? If not,
how may this affect your results? In case of highly shewed dependent variable, what
have you done to minimize this problem?
4. Correlation and bivariate regression analyses
a. Present correlations between all of the variables in your analyses. Interpret your
results in substantive terms. What do the correlations say about the suitability of
including all your variables in a multivariate regression analysis? Should some of the
variables be removed and/or replaced?
b. Present bivariate regression analyses to test the separate effect of each of your
independent variables. Comment substantially upon the strengths of the regression
coefficients as well as measures of ‘goodness-of-fit’ (R-squared and the standard
error of the estimate). Also, comment upon the statistical significance of the
relationships.
5. Multivariate regression analyses
a. Set up a model where all of your variables are regressed against the dependent
variable. Compare the results with the bivariate regressions and comment in great
detail upon regression coefficients as well as measures of ‘goodness-of-fit.’ Also,
comment substantially upon how the estimates differ between the bivariate and
multivariate analyses.
b. Add new models where you control the results from the previous model (5a) for (at
least 10 well argued) country dummies. Do these controls affect the results? What
do differences between coefficients for the country-dummies mean?
c. Add a new model with interactions between county-dummies and the one or more of
the central variables in the analyses. Comment substantially on the results in relation
to previous models.
6. Conclusions