Statistics For Clinical Research – A Practical Guide

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

What you'll 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

Requirements

Understanding of Basic Mathematics

Basic of Clinical Statistics

Basic of Research Methods

Statistical Package for Social Sciences (SPSS)

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!

Overview

Section 1: Introduction to Statistics for Clinical Research

Lecture 1 Introduction of Instructor

Lecture 2 Different Types of Student in Clinical Research

Lecture 3 Difference between Meta-Analysis and Systematic Literature Review

Section 2: Measure of Central Tendency, Key Definition and Data Types

Lecture 4 Population, Sample, Inferential Statistics

Lecture 5 Data Types in Clinical Statistics

Lecture 6 Data Types: Discrete and Continuous variable

Lecture 7 Measure of Central Tendency

Lecture 8 Mean, Mode and Median

Section 3: Probability, Distributions in Clinical Statistics, Central Limit Theorem

Lecture 9 P-value in Clinical Research

Lecture 10 Probability

Lecture 11 Types of Probability

Lecture 12 Central Limit theorem: Heart of Statistics

Lecture 13 Probability Distribution

Lecture 14 Normal Distribution

Lecture 15 Poission Distribution

Lecture 16 Chi-square

Lecture 17 T-distribution

Section 4: Hypothesis Testing in Clinical Research

Lecture 18 Introduction to Hypothesis Testing

Lecture 19 Null and Alternate Hypothesis

Lecture 20 Errors in Hypothesis Testing - Type-1, Type-2 error

Lecture 21 Confidence Interval in Statistics

Section 5: Parametric and Non-parametric Tests

Lecture 22 Introduction to Parametric and Non-parametric Tests

Lecture 23 Student's T- test

Lecture 24 Analysis of Variance - ANOVA

Lecture 25 Chi-Square

Lecture 26 Correlation Analysis

Lecture 27 Regression Analysis

Section 6: Important Clinical Statistical Tests

Lecture 28 Hazard Ratio

Lecture 29 Risk and Odd Ratio's

Lecture 30 Number needed to Treat and Harm

Lecture 31 Life Tables

Lecture 32 Sensitivity, Specificity, Predictive Values

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