Course Details

1. Understand the basic methods for collecting data (quantitative and qualitative methods).
2. Construct, present and interpret frequency tables, cumulative distributions and graphs. Understand and explain the shape of various distributions.
3. Calculate indicators of descriptive statistics.
4. Calculate indicators of inductive statistics.
5. Describe and explain the idea of probability, experiments, events, outcomes and sample space and construct the sample space given an experiment.
6. Recognize the chi-square distribution and make use of its table.
7. Discriminate the basic characteristics of the validity and reliability of a research instrument.
8. Analyze data by using SPSS and interpret the results.
9. Propose a schedule for the development of a quantitative research.

• The use of quantitative and qualitative methods. Strengths and limitations in social sciences. 

• Statistics in practice: Kinds of data (discrete and continuous, ordinal and nominal). Different kinds of variables. Frequency tables, cumulative distribution tables and graphs (histograms, bar charts, pie charts). Shape of various data distributions (skewed, and symmetric). Applications in the social sciences.

• Summarizing quantitative data: Measures of location (mean, mode, and median) and measures of dispersion (variance, standard deviation, range) for group data and raw data. Difference between measures of location and measures of dispersion and their significance. Extreme values, outliers and their importance. Applications in the social sciences.

• The idea of probability: Experiments, events, outcomes and sample space. Relative frequencies. Calculation of probabilities and basic relationships of probability (union of events, complement of event, intersection of events).

•The chi square distribution and the two tests: Goodness of fit test and test of independence. The table of the chi-square distribution. 

• The comparison of means: t-test, anova, ancova

• The exploratory factor analysis. Understanding the logic of the confirmatory factor analysis. 

• Validity and reliability test, Correlation analysis. 

• The IBM Statistical Package of the Social Sciences: Data entry, and analysis of data. 

• Greek textbook by: Roussos, P.L., Tsaousis G., 2002 Statistics applied in the Social Sciences
• Makrakes, Β. (2005). Data analysis in scientific research using the SPSS, Athens: Gutenberg. (In Greek)

• Beins, B. (2012). APA style simplified: Writing in psychology, education, nursing, and sociology. Oxford: Wiley-Blackwell.
• Creswell, J. W. (2011). Research in Education: Design, implementation and evaluation of quantitative and qualitative research (ed. Ch. Tzormpatzoudes). Athens: ION. (In Greek)
• Goos, P. & Meintrup, D. (2015). Statistics with JMP: Graphs, Descriptive statistics and probability. Wiley.