AKT Statistics & Evidence-Based Practice
Evidence-based practice accounts for 16 of the 160 AKT items, and in recent sittings it has been the domain in which candidates scored lowest. Eleven pocket-sized units take you from study design to Cates plots, with worked examples, live calculators and exam traps flagged.
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Last editorial review: 28 September 2026 · Next scheduled refresh: March 2027.
AKT Statistics & Evidence-Based Practice
Evidence-based practice accounts for 16 of the 160 AKT items, and in recent sittings it has been the domain in which candidates scored lowest. Eleven pocket-sized units take you from study design to Cates plots, with worked examples, live calculators and exam traps flagged.
How to use this module
Foundations and diagnostic tests
Study design and the hierarchy of evidence
Recognise every major study design from a two-line abstract, know which question each design answers best, and place it in the hierarchy of evidence, GRADE, NICE and ESC.
Open unitBias, confounding and appraising a trial
Name the bias from the scenario, tell confounding from bias, and appraise a randomised trial in five questions — randomisation, concealment, blinding, follow-up and intention-to-treat.
Open unitDiagnostic tests I: sensitivity, specificity, PPV and NPV
Build the 2×2 table in thirty seconds, calculate all four test characteristics, and explain why the same test has a different PPV in general practice and in hospital.
Open unitDiagnostic tests II: likelihood ratios and pre- to post-test probability
Convert sensitivity and specificity into likelihood ratios, move from pre-test to post-test probability with odds, and read ROC curves — the Bayesian reasoning behind every referral decision.
Open unitTreatment effects and inference
Measures of effect: RR, RRR, ARR, NNT, NNH and odds ratios
The highest-yield arithmetic in the AKT. Turn any trial result into absolute terms, calculate NNT and NNH with their time frame, and know when an odds ratio can stand in for a relative risk.
Open unitP-values, confidence intervals, type I and II errors, and power
Read any confidence interval at a glance, know exactly what a p-value does and does not mean, apply the overlapping-intervals rule, and link type I and II errors to power and sample size.
Open unitDescribing data, reading charts and choosing the right statistical test
Types of data, normal and skewed distributions, mean vs median, SD vs SE, box-and-whisker plots, and a one-table method for choosing the statistical test in any study.
Open unitSurvival curves, hazard ratios and non-inferiority trials
Read a Kaplan–Meier curve, interpret a hazard ratio correctly, look critically at composite end-points, and decide whether a non-inferiority trial proves what it claims.
Open unitSynthesis, populations and practice
Systematic reviews and meta-analysis: forest, funnel and L’Abbé plots
Read every part of a forest plot, recognise heterogeneity and publication bias, and interpret the L’Abbé plot — a named item on the RCGP data-interpretation list.
Open unitEpidemiology and screening: incidence, prevalence, standardised mortality and screening biases
Incidence and prevalence, crude and standardised rates, the SMR, the Wilson–Jungner criteria, and the three biases that make screening look better than it is.
Open unitCommunicating risk, Cates plots, decision aids, audit and prescribing data
The applied end of the RCGP data-interpretation list: Cates plots and decision aids for shared decisions, the audit cycle, control charts, and prescribing measures such as ADQ and STAR-PU.
Open unitAKT statistics on one page
Re-derive this from memory each week. Every line is taught with worked examples in the units above.
The 2×2 table
| Disease + | Disease − | Total | |
|---|---|---|---|
| Test + | a (true +) | b (false +) | a+b |
| Test − | c (false −) | d (true −) | c+d |
| Total | a+c | b+d | N |
Treatment effects
Inference
Epidemiology
Choosing a statistical test
| Data | Two independent groups | Two paired groups | Three or more groups | Association |
|---|---|---|---|---|
| Continuous, normal | Unpaired t-test | Paired t-test | ANOVA | Pearson r; linear regression |
| Skewed or ordinal | Mann–Whitney U | Wilcoxon signed-rank | Kruskal–Wallis | Spearman rank |
| Categorical | Chi-squared (Fisher’s exact if small) | McNemar | Chi-squared | Logistic regression |
| Time-to-event | Log-rank; Kaplan–Meier | — | Log-rank | Cox regression (hazard ratio) |
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