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Cyprus International University
TR

STATISTICAL COMPUTER APPLICATIONS FOR SOCIAL SCIENCES

Course
STAT602 - STATISTICAL COMPUTER APPLICATIONS FOR SOCIAL SCIENCES
Department
Institute of Graduate Studies and Research
Course Type
Course
Status
Required
Language
English
Credit
3
ECTS
0
T+P+L
3 + 0 + 0
Course Coordinator(s)
-
Prerequisite
-
Keywords
-

Course Description

Entering the data collected to the computer, organizing and getting data ready for statistical analyses; normal distribution and sampling distribution of the mean; establishing confidence intervals; writing research questions, research hypotheses, null hypotheses; hypothesis testing. Descriptive statistics: Measures of central tendency and position measurements (arithmetic mean, median, peak, percentile and quartile); measures of variability (distribution width, variance, standard deviation); display of data. Inferential statistics: t-test applications (single-sample t-test, independent samples t-test, dependent samples t-test), analysis of variance applications (one-way ANOVA, two-way ANOVA, MANOVA, ANCOVA); correlations (Pearson and Spearman correlation coefficients), partial correlation; multiple linear regression; exploratory and confirmatory factor analyses; reliability; non-parametric tests (Wilcoxon signed rank test, Mann-Whitney U test, Kruskal-Wallis test, Chi-Square tests); interpreting and writing results of analyses.

STATISTICAL COMPUTER APPLICATIONS FOR SOCIAL SCIENCES

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

  1. 01 have a knowledge of basic concepts and terms related to descriptive and inferential statistics; be able to enter data collected to the computer, organize and get data ready for statistical analyses.
  2. 02 comprehend normal distribution and sampling distribution of the mean and be able to establish confidence intervals; be able to write research questions, research hypotheses, null hypotheses; and comprehend hypothesis testing.
  3. 03 be able to compute measures of central tendency and position measurements (arithmetic mean, median, mode, percentile and quartile) and measures of variability (range, variance, standard deviation) by using SPSS; be able to display data and edit graphs and charts by using SPSS.
  4. 04 be able to use t-test applications on SPSS and conduct one-sample t-test, independent samples t-test and paired samples t-test.
  5. 05 be able to use Analysis of Variance applications on SPSS and conduct one-way ANOVA, two-way ANOVA and ANCOVA.
  6. 06 be able to plot scatter dot diagram and compute Pearson and Spearman correlation coefficients; be able to conduct multiple linear regression analysis and build models.
  7. 07 be able to conduct exploratory factor analysis and reliability analyses.
  8. 08 be able to conduct non-parametric tests (Wilcoxon signed rank test, Mann-Whitney U test, Kruskal-Wallis test, Chi-Square tests)
  9. 09 be able to interpret and write results of analyses.
  10. 10 value statistics as a vital component of doing quantitative research.

Course Syllabus

Week Topic
Week 1 Introduction to the course; basic concepts and terms related to basic statistics.
Week 2 Entering data collected to the computer, organizing and getting data ready for statistical analyses.
Week 3 Using select cases and filter menus in SPSS
Week 4 Frequency Distribution and visualization of the data set in SPSS
Week 5 Statistical Graphs, Detecting outliers and extreme values
Week 6 Descriptive statistics: Measures of central tendency and position measurements (arithmetic mean, median, mode, percentile and quartile)
Week 7 Descriptive statistics: measures of variability (range, variance, standard deviation); display of data.
Week 8 Use of the explore menu
Week 9 Parametric tests and the assumptions of parametric tests
Week 10 One Sample t-test and Independent sample t-test
Week 11 Paired sample t-test
Week 12 One-way variance analysis and post-hoc tests
Week 13 Presentation of projects
Week 14 Presentation of projects
Week 15 Presentation of projects

Reference Books & Course Materials

  1. 01 Green, S. B., Salkind, N. J. (2014). Using SPSS For Windows And Macintosh -7TH Edition. Boston: Pearson.
  2. 02 Elzey, F. F. (1985). Elementary Statistical Techniques. California: Brooks/Cole.
  3. 03 Coursepack prepared by the instructor.

Learning Outcomes

No learning outcomes have been defined.

Program Outcomes

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