Home-> Multiple Choice Questions
Sets of MCQ's for each chapter below. For those wishing to intergrat them into Electronic Learning Environments (Moodle etc) please contact the author.
chapter | Title | Multiple choice questions |
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1 | How this book works |
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2 | Statistics and R - Setting the scene |
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3 | R - What is it? Two ways to use it |
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4 | Downloading and installing the R software - free! |
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5 | Starting R | |
6 | R Commander the graphical front end to R |
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7 | Packages: the apps | |
8 | A quick tutorial: Analysing data shipped with R | |
9 | A quick introduction to the R language |
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Basic Statistical techniques | ||
11 | Summary statistics | |
12 | Graphing Distributions of single variables: histograms and density plots | |
13 | Densityplots for subgroups defined by factor levels | |
14 | Boxplots | |
15 | Percentages for each category/factor level |
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Samples and Populations | ||
17 | Comparing a sample mean to a population mean - Single sample t test | |
18 | Comparing pre-post test means - Paired samples t test | |
19 | Comparing 2 sample means - independent samples t test | |
20 | Comparing pre-post test median difference - Wilcoxon Matched Pairs Statistic | |
21 | Comparing 2 distributions - Mann Whitney U | |
22 | Comparing an observed proportion to a population value - The Binomial test | |
23 | Several independent proportions compared with the average: two way tables | |
24 | Comparing several independent categories: Contingency tables | |
25 | Measuring the degree to which two variables co-vary: Correlation |
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26 | Measuring the influence of one variable on another: Regression | |
Health Statistics |
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28 | Risk and Odds ratios |
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29 | Number needed to treat/harm | |
30 | Sensitivity, Specificity and predictive values |
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31 | Levels of agreement - Kappa, Krippendorff and the ICC | |
32 | Bland - Altman plots |
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33 | Meta-analysis: the basics |
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34 | Plotting survival over time: KM (Kaplan-Meier) plots | |
35 | Investigating effects upon survival over time: Cox PH regression | |
36 | Graphical summaries of data | |
37 | Paired nominal data: comparing proportions using McNemar's test | |
Managing your data and R |
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39 | Creating datasets and distributions in R Commander and R |
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40 | Importing your data into R |
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41 | Cutting and Pasting from Excel/Word to the R Data editor |
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42 | Saving and exporting your work and data | |
43 | R Script files (.r) | |
44 | Manipulating variables (columns) in R Commander and R | |
45 | Manipulating cases (rows) in R Commander and R | |
46 | Expanding tables of counts into flat files | |
47 | Installing non-CRANS packages | |
48 | Workspaces, objects and history files | |
49 | Developing R Code – Rstudio and NppToR | |
More ways of analysing your data |
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51 | Mosaic and extended association plots |
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52 | Multiway tables and Crosstabs | |
53 | Re-sampling – Permutations, Jackknifes and Bootstrap’s | |
54 | Repeated measures: Mixed models and Gee | |
55 | Sample size requirements |
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56 | Confidence intervals for effect sizes - Noncentral distributions | |
57 | Publication quality graphics | |
More Regression Techniques |
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59 | Multiple Linear Regression: Measuring the influence of several variables on one continuous variable |
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60 | Logistic regression: a binary outcome | |
61 | Poisson (Log linear) Regression | |
62 | Conditional Logistic Regression | |
63 | Factorial ANOVA |
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64 | Factor Analysis | |
65 | Structural Equation Modelling (SEM) | |
66 | Résumé |