Research Design: methods and strategies
(Course Code: -)
Semester: | A | Teaching credits: | – | ECTS credits: | 10 | Type: | Compulsory | |
Course: | Postgraduate | Direction: | – | Instructor: |
–
Topics per Week: |
1 Introduction to data Data basics, Overview of data collection principles, Observational studies and sampling strategies, Experiments, Examining numerical data, Considering categorical data, Graphical display of data 2 Foundation for inference Hypothesis testing, Central Limit Theorem, Normal distribution, Applying the normal model, Confidence intervals 3 Inference for categorical data Inference for a single proportion, Difference of two proportions, Testing for goodness of fit using chi-square, Testing for independence in two-way tables 4 Inference for numerical data One-sample means with the t distribution, Paired data, Difference of two means, Comparing many means with ANOVA 5 Introduction to linear regression Line fitting, residuals, and correlation, Fitting a line by least squares regression, Types of outliers in linear regression, Inference for linear regression 6 Multiple and logistic regression Introduction to multiple regression, Model selection, Checking model assumptions using graphs, Logistic regression 7 Matrices and Vectors Miscellaneous Definitions and Matrix Operations 8 Multivariate data Descriptive Statistics, Rows (Subjects) vs. Columns (Variables), Covariances, Correlations and Distances, The Multivariate Normal Distribution, Scatterplots, More than 2 Variable Plots 9 Measures of Central Tendency, Dispersion and Association Measures of Central Tendency, Measures of Dispersion, Measures of Association, Additional Measures of Dispersion 10 Unconstrained ordination Principal Components Analysis, Correspondence analysis, Multi-dimensional scaling 11 Groups Finding groups (Cluster Analysis), Testing groups (ANOSIM), Discriminating among groups (Discriminant analysis) 12 Constrained ordination Canonical correspondence analysis |
Theory – Lectures (hours / week): |
3 |
Exercises – Laboratories (hours / week): |
2 |
Other activities: | – |
Grading: | Final Exam 70%, Labs 30% |
Class notes: | Yes |
Main textbook(s): |
Diez D.M., C.D. Barr, M. Cetinkaya-Rundel. 2015. Open Intro Statistics. 3rd edition |
Βιβλιογραφία: |
Crawley M.J. 2014. Statistics: An Introduction Using R. Wiley |
Διαδικτυακές Πηγές: | http://onlinestatbook.com/ |