# 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 Additional textbook(s): Crawley M.J. 2014. Statistics: An Introduction Using R. Wiley From the web: http://onlinestatbook.com/