STATISTICAL METHODS FOR RESEARCH
Notes on implementation
Use this document to make notes on your ideas and plans for implementing the Statistical Methods for Research
program. You may wish to think about:
Ways in which you want to customize the programme (e.g. screens to delete, areas where you want to add
your own institutional content)
Links between the online content and the face-to-face sessions you will be running as part of a blended
learning program (e.g. which screens/units you might set as preparatory study before a particular workshop)
Features which instructors/trainers could incorporate into their face-to-face sessions (e.g. videos or activities
which could form the basis of a group discussion).
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STATISTICAL METHODS FOR RESEARCH
Introduction – Statistics in the context of research
Screen
Notes
Unit 1: Getting started
You as a researcher
Pre-program quiz
What stage are you at
currently?
What will I be able to
do with my research
data by the end of this
course?
Outline of the program
Defining ‘statistics’
Unit 2: Statistical investigation
What is a statistical
investigation?
Stages 1 to 3 of a
statistical investigation
Stage 4: Statistical
modelling
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STATISTICAL METHODS FOR RESEARCH
Thinking statistically – Describing data well
Screen
Notes
Unit 1: Describing data well
What is a statistical
investigation?
Summaries for
categorical variables
Summarizing
quantitative variables
Reflecting the structure
in the data
The standard deviation
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STATISTICAL METHODS FOR RESEARCH
Thinking statistically – Making good generalizations
Screen
Notes
Unit 1: Sampling variability and the precision of a sample estimate
What use is all this stuff
about variability?
Sampling – the big idea
Sampling in practice
Sampling distribution
Unit 2: Using standard errors to build confidence intervals
The Normal
distribution and
confidence intervals
Calculating a
confidence interval
Using software
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STATISTICAL METHODS FOR RESEARCH
Which hypothesis test should I use?
Screen
Notes
Unit 1: Testing the null hypothesis
Accepting versus not
rejecting the null
hypothesis
A decision-making rule
for hypothesis testing:
The p-value
Decision-making: The
5% significance rule
Unit 2: The practice of statistical hypothesis testing
Recap
Comparing two means
A more general
analysis: ANOVA
Which test do I use?
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STATISTICAL METHODS FOR RESEARCH
Statistical modelling
Screen
Notes
Unit 1: Statistical modelling
What is a statistical
model?
The statistical
modelling framework
Linking a one-sample ttest to the null
regression model
Straight line regression
Straight line regression
stage 4: Generalize
your results
The quadratic
regression model
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STATISTICAL METHODS FOR RESEARCH
Analysis of categorical data
Screen
Notes
Unit 1: Analysis of categorical data
Comparing one single group
of categorical binary data
with a hypothesized target
Testing for association with
categorical binary data:
Comparing two groups
Confidence interval for a
true difference between
two proportions
Testing for association with
categorical binary data:
Comparing three or more
groups
Testing for a linear
association between a
categorical binary outcome
and an ordered categorical
explanatory variable
Conclusion: Putting your skills into practice
Screen
Notes
Unit 1: Model reports
Introduction
Complete a model
report
Unit 2: Conclusion
Post-program quiz
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