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FoSSA: Fundamentals of Statistical Software & Analysis

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  1. Course Information

    Meet the Teaching Team
  2. Course Dataset 1
  3. Course Dataset 2
  4. MODULE A1: INTRODUCTION TO STATISTICS USING R, STATA, AND SPSS
    A1.1 What is Statistics?
  5. A1.2.1a Introduction to Stata
  6. A1.2.2b: Introduction to R
  7. A1.2.2c: Introduction to SPSS
  8. A1.3: Descriptive Statistics
  9. A1.4: Estimates and Confidence Intervals
  10. A1.5: Hypothesis Testing
  11. A1.6: Transforming Variables
  12. End of Module A1
    1 Quiz
  13. MODULE A2: POWER & SAMPLE SIZE CALCULATIONS
    A2.1 Key Concepts
  14. A2.2 Power calculations for a difference in means
  15. A2.3 Power Calculations for a difference in proportions
  16. A2.4 Sample Size Calculation for RCTs
  17. A2.5 Sample size calculations for cross-sectional studies (or surveys)
  18. A2.6 Sample size calculations for case-control studies
  19. End of Module A2
    1 Quiz
  20. MODULE B1: LINEAR REGRESSION
    B1.1 Correlation and Scatterplots
  21. B1.2 Differences Between Means (ANOVA 1)
  22. B1.3 Univariable Linear Regression
  23. B1.4 Multivariable Linear Regression
  24. B1.5 Model Selection and F-Tests
  25. B1.6 Regression Diagnostics
  26. End of Module B1
    1 Quiz
  27. MODULE B2: MULTIPLE COMPARISONS & REPEATED MEASURES
    B2.1 ANOVA Revisited – Post-Hoc Testing
  28. B2.2 Correcting For Multiple Comparisons
  29. B2.3 Two-way ANOVA
  30. B2.4 Repeated Measures and the Paired T-Test
  31. B2.5 Repeated Measures ANOVA
  32. End of Module B2
    1 Quiz
  33. MODULE B3: NON-PARAMETRIC MEASURES
    B3.1 The Parametric Assumptions
  34. B3.2 Mann-Whitney U Test
  35. B3.3 Kruskal-Wallis Test
  36. B3.4 Wilcoxon Signed Rank Test
  37. B3.5 Friedman Test
  38. B3.6 Spearman’s Rank Order Correlation
  39. End of Module B3
    1 Quiz
  40. MODULE C1: BINARY OUTCOME DATA & LOGISTIC REGRESSION
    C1.1 Introduction to Prevalence, Risk, Odds and Rates
  41. C1.2 The Chi-Square Test and the Test For Trend
  42. C1.3 Univariable Logistic Regression
  43. C1.4 Multivariable Logistic Regression
  44. End of Module C1
    1 Quiz
  45. MODULE C2: SURVIVAL DATA
    C2.1 Introduction to Survival Data
  46. C2.2 Kaplan-Meier Survival Function & the Log Rank Test
  47. C2.3 Cox Proportional Hazards Regression
  48. C2.4 Poisson Regression
  49. End of Module C2
    1 Quiz
  50. A Note about the Fossa Certificate

This course uses three different options for statistical analysis software for the practical exercises. The next lesson (A1.2) is broken up into three subsections. You only need to complete the one for the software you are planning to use throughout the course. These sessions will help you to familiarise yourself with your chosen software, and set up the course datasets. After the initial set up, there will be one lesson for each topic, but then you will have the choice of which statistical software you would like to use for the practical. Each software package is denoted by a specific colour of banner. 

R is shown in RED

Click here to go to the introduction to R

Stata is shown in BLUE

Click here to go to the introduction to Stata

SPSS is shown in GREEN

Click here to go to the introduction to SPSS

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Elizabeth

Great start

Glynn

Nice and simple introduction, thank you!

Osoti

Great introduction.Many thanks

Last edited 2 months ago by Osoti
Moses

kwach aneni

Osoti

Long time, Comrade. Ilal sana

Moses

an kae amanyo knowledge.

Osoti

Definitely the right place to be

Cristina

Great introduction. Thank you!

Diane

understandable introduction

Marwa

Nice introduction

Sheila

Wow…clear introduction

sazzad

The presentation is nice,clear and understandable.

Patrick

This was very clear and detailed, I understood everything.

Mayssoon

Great introduction. Thank you

Oluwadamilare

Great introduction.

Aftab

this is plat form which by i am learn regarding fundamental statistics

john

goodf instructions

Clear introduction to statistics

Amos

Really insightful

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