Statistics for healthcare professionals

Learn how to create and name spss variables in variable view, assign numeric types and widths, code gender with 0/1, and prepare data from Excel.

Use jamovi exercise 2 to describe data with gender frequency. Split by gender to describe height with mean and standard deviation, and other variable with median and quartiles.

Explore how a two by two contingency table links smoking history and ischemia incidence, reading margins and joint probabilities to assess their relationship.

Learn how relative risk and odds ratio quantify associations between exposure and disease, interpret their values, and choose appropriate measures for cohort vs case-control studies in healthcare.

Learn jamovi exercise 3: analyze relationships between variables using frequency tables, chi-square tests, and relative risk with gender and disease data.

Analyze the effect of corticosteroid on infection and mortality in ICU patients using SPSS, comparing 26 treated and 24 untreated individuals, and interpreting confidence intervals.

Explore using Jamovi to estimate confidence intervals for odds ratio and relative risk in assessing corticosteroid effects on infection and mortality in ICU patients, and test gender associations.

Link study design and research question to statistical analysis, classify questions by objective, and choose appropriate tests—parametric or nonparametric—based on group differences, prediction, and diagnostic goals.

Learn how to apply the paired t-test to a within-group before-and-after study, using blood pressure changes after joining residency to test significance with 95% CI and p-values.

Examine the effect of residency on blood pressure by creating a difference score (after minus before) and checking normality, then apply the Turkey test for a significant mean difference.

Explore residency’s effect on blood pressure with a paired t-test in jamovi exercise 5, creating a difference variable and assessing normality with histogram and QQ plots.

Explore the Wilcoxon signed-rank test in SPSS to compare pre and post training scores for ten residents, using related samples and legacy dialogues methods, and interpret p-values to assess significance.

Assess a new educational technique by comparing test scores of ten residents before and after a day of training in Jamovi, using a t-test, p = 0.016 indicating significance.

Compare weight changes in low carbohydrate vs low fat diets and cholesterol changes in drug vs placebo using SPSS, with normality, outlier, and variance checks, finding significant differences.

Jamovi exercise 9 compares traditional training and peer to peer training using an independent samples t-test, showing median scores for peer to peer training and a significant p-value around 0.03.

Compare three or more groups with one-, two-, and three-way anova, covering between, within, and mixed designs and guarding against type i error.

Jamovi exercise 10 analyzes LDL levels across control, drug E, and drug B groups with a one-way ANOVA, checks normality and equal variances, and uses Tukey post hoc tests for significance.

Apply the Kruskal-Wallis test to compare three training groups—traditional, peer-to-peer, and hands-on—on ordinal test scores using ranks and mean ranks, testing equal ranks versus differences.

Learn the logic of chi-square tests for two categorical variables, compute expected counts, and compare relative risk and odds ratios to choose between chi-square and Fisher exact.