Curriculum :
The course consists of an introduction to the basic concepts of inferential statistics and the quantitative research method.
The main aim of this lesson is to familiarize the students with the various tests of inferential statistics for analyzing quantitative and qualitative data that is collected during the investigation of social phenomena.
By the end of this course the students will be able to:
- Describe the main phases of a quantitative research
- Select the suitable sampling method to construct a representative sample
- Formulate a suitable research hypothesis depending on the research problem
- Recognize and apply basic hypothesis testing process
- Perform basic data analysis procedures in a statistical package
- Present the conclusions of data analysis, connecting them with the research questions
- Approach modern issues of educational research critically
- Plan and implement quantitative surveys about various educational issues, selecting suitable research instruments.
Outline :
The course includes:
- Random variable, probability function, cumulative distribution function. Bernoulli, Binomial, Poisson and Normal Distribution.
- Sampling distribution, population, sample, Statistical inference, central limit theorem, and t-distribution.
- Point and interval estimation and one and two-sided confidence intervals.
- Test hypotheses, null hypothesis, one and two-sided alternative hypotheses, significance level and type I and II errors. Parametric and non-parametric tests and data screening.
- One sample t-test for the mean, Test for a difference between two means (paired and unpaired).
- F-distribution, one-way analysis of variance (ANOVA) distribution, repeated measures, and two-way ANOVA.
- Power analysis of a test, effect size and sample size determination, non-parametric tests for independent (Mann-Whitney or Kruskal – Wallis test) and dependent (Wilcoxon test) samples.
- Chi-square distribution, Chi-square test for goodness of fit, for homogeneity of proportions, and Chi-square for independence.
- Linear correlation between quantitative variables (zero order) and partial correlation (higher-order). Simple and multiple linear Regression, coefficient of determination (R squared).
Teaching method:
Lectures and laboratory, face-to-face, and group work.
The lecture content of the course for each chapter is uploaded on Moodle, in the form of a series of ppt files and other teaching materials, which the students can freely download them using a password that is provided to them at the beginning of the course.
Use PowerPoint and Prezi. During the laboratory will use specific software environments such as SPSS, R, PSPP, and LibreOffice Calc.