Understanding Clinical Research: Behind the Statistics

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文件名称：Understanding Clinical Research: Behind the Statistics
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更新时间：2021-09-13 05:28:00
统计 Table of Contents: Week 1 : Getting things started by defining different study types Getting to know study types Observational and experimental studies Getting to Know Study Types: Case Series Case-control Studies Cross-sectional studies Cohort studies Retrospective Cohort Studies Prospective Cohort Studies Experimental studies Randomization Blinding Trials with independent concurrent controls Trials with self-controls Trials with external controls Uncontrolled trials Meta-analysis and systematic review Meta-analysis Systematic Review Week 2: Describing your data The spectrum of data types Definitions Descriptive statistics Inferential statistics Population Sample Parameter Statistic Variable Data point Data types Nominal categorical data Ordinal categorical data Numerical data types Ratio Summary Discrete and continuous variables Discrete data: Continuous data: Summarising data through simple descriptive statistics Describing the data: measures of central tendency and dispersion Measures of central tendency Mean Median Mode Measures of dispersion Range Quartiles Percentile The Interquartile Range and Outliers Variance and standard deviation Plots, graphs and figures Box and whisker plots Count plots Histogram Distribution plots Violin plots Scatter plots Pie chart Sampling Introduction Types of sampling Simple random sampling Systematic random sampling Cluster random sampling Stratified random sampling Week 3: Building an intuitive understanding of statistical analysis From area to probability P-values Rolling dice Equating geometrical area to probability Continuous data types The heart of inferential statistics: Central limit theorem Central limit theorem Skewness and kurtosis Skewness Kurtosis Combinations Central limit theorem Distributions: the shape of data Distributions Normal distribution Sampling distribution Z-distribution t-distribution Week 4: The important first steps: Hypothesis testing and confidence levels Hypothesis testing The null hypothesis The alternative hypothesis The alternative hypothesis Two ways of stating the alternative hypothesis The two-tailed test The one-tailed test Hypothesis testing errors Type I and II errors Confidence in your results Introduction to confidence intervals Confidence levels Confidence intervals Week 5: Which test should you use? Introduction to parametric tests Types of parametric tests Student’s t-test :Introduction Types of t-tests ANOVA Linear Regression Nonparametric testing for your non-normal data Nonparametric tests Nonparametric tests Week 6: Categorical data and analyzing accuracy of results Comparing categorical data The chi-squared goodness-of-fit test The chi-squared test for independence Fisher's exact test Sensitivity, specificity, and predictive values Considering medical investigations Sensitivity and specificity Predictive values