Statistics for Clinical Research – A practical Guide

Sensitivity, Specificity, Hazard Ratio, Life Tables, Clinical Statistic, SPSS, SPSS Result Interpretation & Reporting

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Description

You've come to the correct place if you've ever glanced over the results section of a medical study because words like "confidence interval" or "p-value" confuse you. You might be a clinical practitioner who reads research publications to stay current on advancements in your area of expertise or a medical student who is unsure of how to do their own research. Both working professionals and those conducting their own research might gain from having more confidence in their comprehension of statistical analysis and the results.

Any clinical trial's design, conduct, analysis, and reporting all depend heavily on statistics for minimizing and managing biases, confounding variables, and random error measurement. Mastering statistical techniques is essential to comprehending the procedures and outcomes of randomised trials. We covered many important clinical statistical tests like Sensitivity, Specificity, Life Tables, Hypothesis, Probability, Hazard Ratio, Data Types, Distribution and its types and many other basic statistical test.

This course is a good place to start if you want to learn about clinical statistics including SPSS usage, result interpretation and interpretation. Without delving into complicated calculations, it provides a simple introduction to interpreting popular statistical ideas. The greatest method to delve into the world of clinical literature is to be able to interpret and comprehend these ideas. This course fills that need, so let's get started!

What You Will Learn!

  • Fundamentals of Clinical Statistics
  • Hazard Ratio, Sensitivity, Specificity, Life Tables
  • Hypothesis Testing, Sampling, Population, Confidence interval
  • Central Limit Theorem, Probability, Distribution
  • ANOVA, Regression, Correlation, Hierarchical Regression
  • Distributions: Normal, Poission, Chi-square, t-distribution
  • Errors in hypothesis testing: Type-1 error, Type-2 error

Who Should Attend!

  • Medical Students, Nurses, Research Scholars, Students, Policy Makers, Teaching faculty, Academicians
  • Early Career Researchers, Medical Research Groups
  • PhD scholars and Graduate Students
  • Clinical Researchers
  • Doctors, Nurses and Medical Graduate