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Course Outline

  • Introduction
  • Dataset & Resources
  • Conceptual Foundation of Statistics
  • Data Entry: Learning to Enter Data in SPSS
  • Working with Various File Types in SPSS
  • Data Transformation in SPSS: RECODE and Other Transformation Functions
  • Descriptive Statistics using SPSS
  • Advanced Descriptive Statistics in SPSS
  • Independent Sample t-test: Comparing Two Independent Group Means
  • Paired Sample t-test: Comparing Differences between Two Correlated Group Means
  • One-Way ANOVA: Comparing Differences between More than Two Groups
  • Linear Regression: Cause and Effect Analysis of One IV on One DV
  • Multiple Regression: Causal Effect of Many IVs on One DV
  • Hierarchical Regression Analysis
  • Exploratory Factor Analysis
  • Chi-Square Test
  • Reliability Analysis
  • Graphical Presentation & Data Visualization in SPSS
  • Logistic Regression
  • Moderation and Mediation Analysis using PROCESS Macro
  • General Linear Modelling (GLM) & Generalized Linear Modelling (GLIM)
  • One-Way Repeated Measure ANOVA
  • Correlations
  • Measures of Association
  • Bug Fixing in SPSS
  • ANCOVA: One-Way Analysis of Covariance
  • MANOVA (Multivariate Analysis of Variance)
  • Python for SPSS Users
  • Ratio Statistics in SPSS
  • TURF Analysis in SPSS
  • Advanced data Visualization in SPSS
  • Survival Analysis
  • Meta Analysis
  • Assignments

Requirements

  • The course is designed from the ground up, so no prior knowledge of SPSS or Statistics is required. We cover all necessary details in both the theoretical and practical components of the course.
  • Learners must have a copy of SPSS software to practice the steps taught in this course.
 35 Hours

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