PředmětyPředměty(verze: 861)
Předmět, akademický rok 2019/2020
  
Research Methods - JPM031
Anglický název: Research Methods
Zajišťuje: Katedra politologie (23-KP)
Fakulta: Fakulta sociálních věd
Platnost: od 2019
Semestr: letní
Body: 10
E-Kredity: 10
Způsob provedení zkoušky: letní s.:
Rozsah, examinace: letní s.:1/2 Zk [hodiny/týden]
Počet míst: 50 / 50 (50)
Minimální obsazenost: neomezen
Stav předmětu: vyučován
Jazyk výuky: angličtina
Způsob výuky: prezenční
Poznámka: předmět je možno zapsat mimo plán
povolen pro zápis po webu
Garant: RNDr. Jan Kofroň, Ph.D.
Vyučující: RNDr. Jan Kofroň, Ph.D.
Mgr. Jakub Stauber
Anotace - angličtina
Poslední úprava: RNDr. Jan Kofroň, Ph.D. (12.02.2020)
The course covers the most important parts of methodological toolkit for master level students.
The course focuses on (i) concepts and (ii) causation, with respect to specific methods - case selection techniques and OLS regression makes for the cornestone of the course.
Given the high ECTS of the course, students should be prepared for a substantial workload.
Literatura - angličtina
Poslední úprava: RNDr. Jan Kofroň, Ph.D. (12.02.2020)

1) Gerring, J., Christenson, D. (2017): Applied Social Science Methodology: An Introductory Guide, OUP
2) Wickham, H. (2014): Tidy Data, Journal of statistical Software. Volume 59, Issue 10.

3) http://www.cookbook-r.com/ 

Požadavky ke zkoušce - angličtina
Poslední úprava: RNDr. Jan Kofroň, Ph.D. (28.10.2019)

1) Do all the Homeworks 30 % 

2) Midterm 20 %

3) Final test 50 %

Grading is based on A-F scale

Sylabus - angličtina
Poslední úprava: RNDr. Jan Kofroň, Ph.D. (12.02.2020)

While the course provides insight into key elements of research methods, we expect you have
certain amount of knowledge regarding four issues mentioned bellow:
(i) Essentials of correct citing and quoting (academic ethics)
(ii) Essentials of academic writing (style, logic of test structuration etc.)
(iii) Basics of probability
(iv) Descriptive statistics (mean, median, standard deviation etc.)
+ previous exposure to academic text is considered sine qua non

Broadly speaking, we do expect that you have retained at least basics of BA level methodological
know-how (as defined by e.g. JPB 283 and 284).

Software: Excel + R
1) Intro + arguments
a. Organization
b. Types of argument
c. Distinction between a causal theory and a concept


2) Concepts and measures
a. Concepts – key criteria
b. Concepts – strategies for building a concept
c. Operationalization (HW excel)
d. Indicators (HW excel)


3) Analysis + Cross section, time series, panel – building the dataset
a. Precision and validity
b. Internal vs external validity
c. Sample size and representativeness
d. Sampling
e. Building your database (HW – excel + long vs wide format of data/tidy_data)


4) Analytical description + presenting the data
a. Defining dimensions of interest
b. Historical analysis
c. Analyzing a sector or a field (HW)
d. Variation on your variables/among groups etc.
e. Presenting the data – spotting patterns (HW – excel)


5) Causality, counterfactuals and hypotheses
a. Counterfactuals as cornerstone of causal thinking
b. Causal model
c. Deducing a (testable) hypothesis (HW)


6) Introduction to R
a. Installation (R Studio, packages)
b. Data import
c. Data handling (filter, select, summarise, mutate)


7) Descriptive statistics
a. Central tendency

b. Distributions (skewness, kurtosis)

c. Visualization (Boxplot, Histogram)
8) Bivariate Statistics
a. Parametric and non-parametric methods
b. correlation
c. t-test
d. Chi-test

9) Linear models I.
a. Regression
i. Assumptions
ii. Interpretation
iii. Visualization (Scatter plot, Forest plot)

10) Linear models II.
a. Multiple regression
i. Interpretation
ii. Standard coefficients
iii. Model evaluation
iv. Dummy variables

11) Generalized linear models
a. Logistic regression
i. Comparison with OLS
ii. Interpretation
iii. Model evaluation
iv. Visualization

12) Case study design
a. Exploratory vs. diagnostic
b. Cross case
c. Within case
d. Selecting from a regression (HW)
e. Strengths and weaknesses

 
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