Week 1 - Theoretical

Basic Statistical Concepts • Measurement and scale types •Descriptive statistics types: Graphs, Central tendency measures, Measures of variability Arithmetic Mean, Median (Median) and Peak (Mode) range, quartile deviation, variance, standard deviation) • Program right. Meeting. • Introduction to SPSS: Introduction of menus, Data View, Variable View, input of variables into SPSS and events

Week 2 - Theoretical

• Editing Data in Spss o Editing Data for Measurements of Different (Independent) Groups o Editing Data for Repeated Measurements of the Same Group o Some Variable and Data Operations in SPSS o Recode Process o Variable Value Calculation (Compute) Process o Assigning a Value to a New Variable as a Result of an Operation o Split File Process o Select Cases by Data Criteria o Conversion to Artificial Ranking Scale (Rank Cases) Process o Frequency distribution, descriptive statistics, hypothesis testing o Probability and Normal Distribution o Skewness and Kurtosis o Standard Error of Measurement and Confidence Interval

Week 3 - Theoretical

• Normality Tests with SPSS o The Importance of Normality o Control of Normality with Measures of Central Tendency o Controlling Normality According to Skewness and Kurtosis Coefficient of Distribution o Checking Normality with SPSS's Data Structure Explore Option o Normality Tests (Kolmogorov-Smirnov and Shapiro-Wilk) o Conversion Options for Non-Normal Situations o Activities to transform data into Normal distribution o Standard score types: Z score, T score o Outlier analysis

Week 4 - Theoretical

• Description with Percentages and Frequencies o Frequency [Frequency] Calculation with SPSS o Presenting Results in Crosstabs o Creating a Frequency Table of Data With Labels Assigned to Values • Giving Descriptive (Descriptive) Statistics (Central Tendency and Measures of Variability) on a Group of Quantitative Data o Calculating Center of Frequency Tendency and Measures of Variability with SPSS o Comparing Mean Means with a Norm, Standard, or Parameter • Chi-square test for two variables

Week 5 - Theoretical

For intergroup patterns (independent groups), • Single-sample t-test (Conditions for Performing, Data Entry, Result Table, Effect Size, Expression of the Result in the Research Report)

Week 6 - Theoretical

For intergroup patterns (independent groups), • Mann Whitney U test; (Conditions of Ability, Data Entry, Result Table, Statement of the Results in the Research Report)

Week 7 - Theoretical

For intergroup patterns (independent groups), • Single-factor analysis of variance (ANOVA) (Conditions of Doing, Data Entry, Result Table, Effect Size, Expression of the Result in the Research Report) • Two-factor ANOVA (Conditions for Performing, Data Entry, Result Table, Effect Size, Expression of the Result in the Research Report)

Week 8 - Theoretical & Practice

For intergroup patterns (independent groups), • Kruskal Wallis test (Performance Conditions, Data Entry, Result Table, Effect Size, Expression of the Result in the Research Report)Midterm

Week 9 - Theoretical

For intergroup patterns (independent groups), • Two-factor ANOVA (Conditions for Performing, Data Entry, Result Table, Effect Size, Expression of the Result in the Research Report)

Week 10 - Theoretical

For patterns within groups (dependent groups), • t-test (Performance Conditions, Data Entry, Result Table, Effect Size, Expression of the Result in the Research Report) • Wilcoxon signed-rank test (Conditions for Performing, Data Entry, Result Table, Effect Size, Expression of the Result in the Research Report)

Week 11 - Theoretical

For patterns within groups (dependent groups), • One-factor ANOVA and Friedman test (Conditions of Performing, Data Entry, Result Table, Effect Size, Expression of the Result in the Research Report)

Week 12 - Theoretical

• Two-factor ANOVA for mixed designs. (Conditions of Ability, Data Entry, Result Table, Expression of the Result in the Research Report) Comparison of the difference score series with the T-Test for Unrelated Samples)

Week 13 - Theoretical

For correlational patterns, - Exploratory correlation pattern, simple (binary) and partial correlation coefficient

Week 14 - Theoretical

For correlational patterns, • Introduction to predictive correlation pattern, simple regression and multiple linear regression analysis Determining the Structural Properties of a Measurement Tool Exploratory Factor (Principal Components) Analysis (Conditions of Conducting, Data Entry, Result Table, Statement of the Result in the Research Report)