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Introduction to Biostatistics (2024)
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Video 
[Image: 9eadadf6acf96ecdd2595a7b5ce835b4.jpeg]
Free Download Introduction to Biostatistics (2024)
Published 10/2024
Created by Gabriel cardenas
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 92 Lectures ( 6h 30m ) | Size: 5.45 GB

Introduction to basic Statistics with Probability and T-test and Basic Categorical Analysis with Chi-Squared
What you'll learn
Descriptive Statistics
Hypothesis Testing
Basic continuous dependent variable statistical tests
Categroical dependent variable statistical tests
Analyzing data with proportion and odds ratios
Using the Chi-Squared analysis and the Cochran Mantel Haenszel test
Showing and explaining the different sample size formulas
Requirements
Basic level of mathematics training.
A basic introduction to statistics course.
Basic level understanding of some statistical software.
No programming experience.
Description
Hello, thank you for considering this course Introduction to Biostatistics. I have made this course out of the years of college courses, webinars, and certificates that I have done over the last 22 years. I made the course at a level that a person who has had an Introduction to Statistics course should be able to start at the beginning and finish with a good education on Introductory Biostatistics. Some people say "Why teach the old stuff?" My reply is "You teach the old stuff because people might be looking for enough knowledge to do their analysis at hand and nothing more." I also think that, most of the new methods are built on the old method, and learning the old methods will help you gain a greater understanding of Biostatistical analysis.I begin the course at an introductory level : introductory probability, into intermediate probability with Bayes Formula and test validation study analysis and introduce Sensitivity and Specificity to parameters of validation studies. I cover the uses of probability in methods such as the Kaplan Meier Survival Analysis. I also make sure to cover the sample size calculation for each statistical method in the course because that will be a large part of your professional work. I briefly cover distributional probability and touch on the Empirical Rule and the T-distribution and including calculating Confidence Intervals.Next, I go into introductory research study methods, discussing rates and incidence and prevalence. I beginning to review hypothesis testing using the two-sample t-test; and then i move to the paired t-test which I discuss is a very useful method in health and clinical research. I also have two main tests, a mid-term and a final; to get you familiar with how the course quizzes in college will look. For all tests I also have a statistical software lesson showing how to do the analyses in SPSS and in R. This should make the time you actually work more productive because you won't be struggling through books or notes.From there I move to the categorical methods: Chi Squared and the Cochran Mantel Haenszel test. The Chi-Squared analysis is the workhorse of categorical Biostatistics. I explain it and do several sections on the Risk Ratio and the Odds ratio in order that you will become familiar with these estimators. The Cochran Mantel Haenszel test is the stratified analysis of more than 1 cross-sectional categorical table. It is also a very powerful method. It involves 3 variable, and I discuss the process models that have three variables and the differences and test that may indicate their presence in the data. My hope is that I will become a we, and we will learn as much as is possible about Biostatistics and improve and advance the field. I will be happy to support you after you have taken the course with whatever Biostatistical help you may need. I have continued to learn new methods well after college and I hope you will also. Thank you and good luck with your careers.
Who this course is for
College Level students looking to get degrees and create careers in Public Health or Biostatistics
College Pharmacy students, Medical School students.
Data Scientists that need more statistics training
Managers that want to be able to analyze processes
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