Statistical Data Analysis Methods (Basic)

Statistical Data Analysis Methods (Basic)

  • Course level: Beginner  
There are no active Semester Schedule for this course   Pre-registar

Description

This course covers fundamental statistical tools, including Descriptive Statistics, Hypothesis Testing, T-Tests, ANOVA, Non-Parametric Tests, Correlation Analyses, and Regression, providing participants with a robust foundation for data-driven decision-making.

COURSE OBJECTIVES

  1. Learn essential statistical principles like Descriptive Statistics and Hypothesis Testing for interpreting and analyzing data.
  2. Use statistical methods like ANOVA, correlation, and Chi-Square to compare groups and relationships, gaining insights for informed decision-making.
  3. Develop skills in Simple and Multiple Linear Regression for predictive analysis and generating forecasts with data.

COURSE SYLLABUS

  1. Descriptive Statistics
  2. Hypothesis Testing
  3. P-values and Significance Levels
  4. One sample t test
  5. Two (independent/paired ) sample t-test.
  6. One Way Anova
  7. Pearson correlation       
  8. Simple and multiple linear regression analysis
  9. Wilcoxon Signed-Rank Test
  10. Mann-Whitney U Test
  11. Kruskal-Wallis Test
  12. Friedman Test
  13. Chi-Square
  14. Spearman's Rank-Order Correlation
Registration fee :
€ 850

Target audience

  • Academicians
  • University Lecturers
  • Researchers
  • University Students
  • Statisticians

Requirements

  • Basic math and data knowledge are prerequisites for this course.
  • Understanding mathematics, basic statistics, and data interpretation will enhance the learning experience.
  • Knowledge of statistical software is helpful but not required.