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Table 3 a - e Relative frequency (as %) of medical graduate responses on competencies in statistics and probability that medical schools need to provide

From: Medical graduate views on statistical learning needs for clinical practice: a comprehensive survey

TopicnrankRequired competency
Includes practicePractice onlyTheory and practiceTheory onlyNeitherDon’t know
a. Data visualization, Data preparation and manipulation and Software used for statistics
Data visualization
  Graphical presentation of data:274184.332.851.614.21.10.4
  Cross tabulating frequencies or percentages:2732337.415.022.328.916.117.6
  Survival analysis:2773920.95.415.565.07.26.9
  Forest plots:2744515.03.611.351.817.515.7
  Receiver operating characteristic (ROC) curves:2754613.62.611.045.418.322.7
  Cluster analysis:277516.11.15.152.726.714.4
  Time series analysis:272525.92.23.736.427.630.1
Data preparation and manipulation
  Arranging data in spreadsheets for statistical analysis:278281.725.556.114.42.21.8
  Working with subsets of the original data - filtering data:2742733.213.919.338.015.313.5
  Merging similar datasets:2734217.96.211.738.827.515.8
  Types of response data:272499.62.96.641.517.331.6
Software used for statistics
  Using Excel for statistics-tips and warnings270764.126.337.823.09.33.7
  Getting to know the fundamentals of a statistical package such as SPSS:2741157.327.030.422.614.65.5
b. Ratios, rates and proportions, Summarising data and Probability theory
Ratios, rates and proportions
  Sensitivity, specificity and positive and negative predictive values:272475.026.148.924.300.7
  Comparing a study cohort with a general population:2742238.313.524.856.64.40.7
  Statistical risk estimates:2723823.05.217.862.66.38.1
Summarising data
  Simple descriptive (or summary) statistics:272569.924.645.221.75.52.9
  Confidence intervals:278665.120.944.234.50.40.0
  Summarising and analysing missing data:2674317.64.912.750.220.611.6
Probability theory
  Laws of probability:2781248.912.236.746.43.21.4
  Concepts and rules of probability:2762534.510.224.461.12.91.5
c. Reporting statistics and Avoiding bad practice in statistics and exploring study design
Reporting statistics
  Presenting the findings and conclusions of statistical hypothesis tests:276863.420.742.028.65.43.3
  Statistical significance, statistical power and some facts about p-values:2751058.518.939.639.60.71.1
  Valid reporting and interpretation of statistical findings:2741446.012.433.548.43.62.2
  Statistical effect sizes:2741544.911.333.651.52.21.5
Avoiding bad practice in statistics and exploring study design
  Principles of good study design:2751642.614.228.45.31.80.4
  Sample size calculations:2721841.214.027.247.18.53.3
  Randomization:2752039.613.126.559.30.70.4
  Misuse of statistics: some statistical blunders and phenomena to look out for in published literature:2742139.410.628.852.95.12.6
  Different types of study design:2752634.29.125.164.70.40.7
  Statistical aspects of clinical trials:2723229.46.323.265.82.91.8
  Retrospective power calculations versus examination of confidence intervals:2754712.72.510.248.721.517.1
  Cross-over trials:2714811.82.69.270.510.37.4
d. Procedures explicitly requiring statistical hypothesis testing and Assessing agreement, consistency and correlation
Procedures explicitly requiring statistical hypothesis testing
  Tests of normality:2741741.711.329.943.88.06.9
  Simple linear regression analysis:2781939.614.425.243.911.25.4
  Hypothesis tests for a single group of continuous data:2692435.310.424.935.413.016.4
  One-tailed versus two-tailed hypotheses tests:2712832.89.623.248.79.29.2
  Hypothesis tests for categorical data:2713032.18.523.635.814.018.1
  Hypothesis tests for comparing two groups of measurement or ordinal data:2703329.35.923.031.517.421.9
  Analysis of variance (ANOVA):2703627.08.518.545.615.212.2
  Multiple linear regression analysis:2784118.36.811.558.316.27.2
  Analysis of covariance (ANCOVA):2694416.75.910.842.423.017.8
  Tests of homoscedasticity (or, ‘equality’ of variance):269506.71.55.230.530.132.7
Assessing agreement, consistency and correlation
  Correlation coefficients –linear and non-linear:2713429.28.121.053.110.07.7
  Statistical indices for measuring levels of agreement and consistency:2743727.07.319.755.19.98.0
  Assessing agreement between two methods of measurement:2684018.75.613.148.916.416.0
e. Allied topics and Critical appraisals and systematic reviews
Allied topics
  Understanding the proper meaning of an audit:275381.529.152.416.41.11.1
  Designing survey questions to support valid statistical analyses:2711348.015.932.136.210.05.9
  Health-related data sources:2722932.79.922.845.27.714.3
  Representing socioeconomic status:2783529.16.522.758.66.16.1
Critical appraisals and systematic reviews
  Conducting critical appraisals:271962.021.040.230.34.14.4
  Systematic reviews:2673131.58.223.265.52.20.7
  1. Note. The column header ‘n’ denotes the number of responses for the given topic, while ‘Practice only’, ‘Theory and practice’ and ‘Theory only’ are abbreviations used for the listed response options ‘carry out the procedure or calculate the statistic(s) using appropriate data’, ‘both of the above’ and ‘understand the theory only’, respectively. Correspondingly, column 4 is formed by combining columns 5 and 6. The entries in this column are included in bold for ease of reference when identifying how the corresponding ranks were obtained in column 3. Percentages are row percentages with the denominator in the calculation pertaining to the number of persons who responded for the listed topic, inclusive of those who responded, ‘Don’t know’. Percentages in the main text of this paper are obtained from combining original frequencies for two response options (e.g. those pertaining to columns 6 and 7). They may therefore differ slightly from those obtained by simply adding the corresponding percentages in the table. This is to avoid rounding errors