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  • Administration
  • Teaching Schedule
  • Model Project
  • 1.0 Why study methods?
  • 1.1 Skills for Learning
  • 1.2 Parts of a Study
  • 2.0 Lit. Review
  • 2.1 Research Ethics
  • 3.0 Qualitative Data
  • 4.0 Quantitative Data
  • 4.1 - The Survey
  • 4.2 - Measurement
  • 5. Qualitative Analysis
  • 5.1 - Theory
  • 5.2 - Example
  • 5.3 - In Word
  • 5.4 - In Dedoose
  • 5.5 - Concepts
  • 6. The Experiment
  • 6.1 - Classical Experiments
  • 6.2 - Key Concepts
  • 6.3 - Types of Exp
  • 6.4 - Validity
  • 6.5 - Exercises
  • 7.0 Writing
  • 9.0 Qualtrics & SPSS
  • 9.3 Intro to Stats
  • 10. Bivariate Stats
  • 11. Cleaning Data
  • 12. Regression & Graphs
  • Presentation Preparation (Week 8)
  • Presentation Preparation (Week 13)
  • Practice mid-semester exam
  • Practice final exam
  • Feedback
  • FAQ
  • Projects: Files
  • Projects: Meetings
  • SPSS help: An Introduction
  • SPSS help: Running SPSS
  • SPSS help: How to Link Google Drive to AppStream
  • SPSS help: Import your data
  • SPSS help: Concept sheet
  • SPSS help: Online resources
  • SOCI2000 Workshop 1: Descriptive statistics
  • SOCI2000 Workshop 2: Correlation
  • SOCI2000 Workshop 3: T-test
  • SOCI2000 Workshop 4: Indexes
  • SOCI2000 Workshop 5: Linear Regression
  • SOCI2000 Workshop 6: Logistic Regression
  • SOCI2000 Workshop 7: Visualisation
  • Preparation for the Workshops
  • Workshop 1: Introducing SPSS
  • Workshop 2: Visualising Data
  • Workshop 3: Exploring 2012 AuSSA
  • Workshop 4: Recoding and Computing Variables
  • Workshop 5: Exploring NSW Crime Data
  • Workshop 6: Exploring Crime Rates in NSW
  • Workshop 7: Exploring the 2019 AuSSA Data
  • Workshop 8: Confidence Intervals and Hypothesis Testing
  • Workshop 9: Crosstabs and Chi-square
  • Workshop 10: Correlation
  • Workshop 11: Regression Analysis
  • Lab 1: Introducing R and RStudio
  • Lab 2: Creating Datasets
  • Lab 3: Playing with Variables
  • Lab 4: Recoding Variables
  • Lab 5: Univariate Statistics
  • Lab 6: Univariate Statistics 2
  • Lab 7: Normal Distribution & Confidence Intervals
  • Lab 8: Testing Hypothesis(t-test)
  • Lab 9: Crosstab & Chi-sqaure Test
  • Lab 10: Correlations & Simple Regression
  • Lab 11: Multiple Regression
  • Overview: Lessons
  • Overview Week 1
  • 1.1 Motivating Example
  • 1.2 Intro to SOCI832
  • 1.3 Intro to R
  • 2.0 Overview
  • 2.1 Intro to Research Methods
  • 2.2 Exercise
  • 2.3 Finding Article + Data
  • 3.0 Overview
  • 3.1 Intro to Stats
  • 3.2 Exercise: Concepts
  • 3.3 Univariate R
  • 3.4 Exercise: Code in R
  • 4.0 Overview
  • 4.1 Setup R
  • 4.2 Downloading Datasets
  • 4.3 Import and Codebook
  • 4.4 Plan Cleaning
  • 4.5 Recoding
  • 4.6 Descriptive Stats
  • 5.0 Overview
  • 5.1 Crosstabs
  • 5.2 Compare Means
  • 5.3 Correlation
  • 5.4 Tables + Plots
  • 6.0 Overview
  • 6.1 Factor Analysis
  • 6.2 Example
  • 6.3 Cronbach's Alpha
  • 6.4 Tables and Graphs
  • 8.0 Overview
  • 8.1 Regression
  • 8.2 Examples
  • 10.0 Overview
  • 10.1 Logit
  • 10.2 Odds Ratios
  • 10.3 Path Analysis
  • 11.1 Diagnostics
  • 11.2 Other Regressions
  • 11.3 Multilevel Models
  • 12.1 Visualisation
  • App. 1. Installing R & RStudio
  • App. 2. Tips for R
  • App. 3. Graphics
  • App. 4. Practice Data
  • App. 5. Choosing Correlations
  • 1. Scoping a Topic
  • 2. Qualtrics Sample
  • Acknowledgements
  • Contact

9.0 Introduction to Qualtrics, SPSS, and Statistics

  • Lecture Slides

Lecture Slides

Week 9 Lecture Slides

Last updated on 11 May, 2020 by Dr Nicholas Harrigan (nicholas.harrigan@mq.edu.au)

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