# Biostatistics for Credit

Biostatistics for Credit reviews the procedures covered in the introductory courses Biostatistics 1 and Biostatistics 2, and covers in more detail the principal statistical concepts used in medical and health sciences.

## Overview

This is an eight-week, non-mathematical course designed specifically for medical and health professionals who deal with medical data and want to acquire some statistical skills. It is a two-part course that may be taken together for college credit.

Part 1 covers basic statistical concepts of probability, confidence intervals and medical vs. statistical significance.

Part 2 covers clinical trial designs including randomized controlled trials, ROC curves, relative risk and odds ratios, and an introduction to survival analysis.

• Intermediate
• 8 Weeks
• Expert Instructor
• Tuiton-Back Guarantee
• 100% Online
• TA Support

## Learning Outcomes

Students who complete this two-part, eight-week course will be able to explain the role of probability in health and medicine; calculate confidence intervals; describe the differences between statistical and medical significance; select the proper statistical tests for quantitative data; be familiar with designs for clinical trials; plot ROC curves; calculate relative risk (RR) and odds ratio (OR); and understand introductory survival analysis.

• Apply Bayes Rule to diagnostic tests
• Calculate the sensitivity, specificity, and positive/negative predictive value of a medical test
• Calculate large-sample and exact confidence intervals for means, medians and proportions
• Calculate and explain p-values
• Explain the concept of statistical power
• Perform the chi-square test
• Apply Student’s t-test to one- and two-sample situations
• Conduct an ANOVA test
• Apply the Tukey and Bonferroni corrections for multiple comparisons
• Test for bioequivalence
• Specify the design for a basic clinical trial, with randomization, blinding, masking and a control group
• Explain designs for repeated measures and cross-over trials
• Determine and interpret ROC curves
• Calculate relative risk and odds ratios and their confidence intervals
• Conduct inference procedures for relative risk and odds ratios
• Explain and apply basic survival analysis models (censoring, Kaplan-Meier)

## Who Should Take This Course

This non-mathematical course is specially designed for medical and health professionals who deal with medical data and want to acquire some statistical skills. These include nursing, pharmacy, laboratory technology and nutrition professionals beside physicians, surgeons and dentists.

## Course Syllabus

### Week 1

Probability in Health and Medicine

• Medical uncertainties and probability
• Elementary laws of probability
• Bayes’ Rule
• Sensitivity-specificity of a medical test
• Positive and negative predictive value
• Effect of prevalence

### Week 2

Confidence Intervals

• Sampling distributions and SEs
• Large sample CI for one-sample mean and proportion
• Exact CI for proportion and median
• Large sample CI for differences between means and proportions
• Sample size for estimation

### Week 3

Statistical vs. Medical Significance

• P-value and level of significance
• The concept of statistical power
• Medical vs. statistical significance
• Sample size for significance and power analysis
• Chi-square test for simple situations

### Week 4

Some Statistical Tests for Quantitative Data

• Student’s t-test for one-sample and two-sample situations
• ANOVA for one-way and two-way tables
• Tukey test and Bonferroni procedures for multiple comparisons
• Test for medically significant gain and equivalence test

### Week 5

Introduction to Designs for Clinical Trials

• Control group
• Randomization and matching
• One-way, two-way and repeated measures designs
• Cross-over design

### Week 6

ROC Curves

• Review of sensitivity-specificity
• Serial and parallel tests
• ROC curve
• Predictivity-based ROC curve
• Clinical gains from a test

### Week 7

Relative Risk (RR) and Odds Ratio (OR)

• Definitions and applicability of RR and OR
• CI and test of hypothesis for RR
• CI and test of hypothesis for attributable risk
• CI and test of hypothesis for OR

### Week 8

Introductory Survival Analysis

• Censored durations and need of special methods
• Life table method
• Kaplan-Meier method

## Class Dates

### 2024

01/05/2024 to 02/03/2024
Instructors: Dr. Abhaya Indrayan
07/19/2024 to 08/16/2024
Instructors: Dr. Abhaya Indrayan

### 2025

01/03/2025 to 01/31/2025
Instructors: Dr. Abhaya Indrayan
07/18/2025 to 08/15/2025
Instructors: Dr. Abhaya Indrayan

## Prerequisites

There are no prerequisites for this course.

## Register For This Course

Biostatistics For Credit

#### Organization of Course

This course is comprised of two separate courses, taken together for college credit. Note: Parts 1 and 2 can be taken separately.

• Part 1: Biostatistics 1 (4 weeks)
• Part 2: Biostatistics 2 (4 weeks)

#### Course Text

The course text is Medical Biostatistics, fourth ed., by Abhaya Indrayan, and can be ordered directly from the publisher, CRC Press.

#### Software

Course participants should have access to a standard statistical software package for use in course exercises, including obtaining CI’s, performing tests of significance including two-way ANOVA and multiple comparisons tests, and producing ROC curves. Stata, SAS, MedCalc and R have these capabilities and are supported by statistics.com teaching assistants. SPSS and Systat also have these capabilities.

#### Options for Credit and Recognition

ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for the upper-division baccalaureate degree, 3 semester hours in biostatistics. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.

#### Literacy, Accessibility, and Dyslexia

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#### Miscellaneous

There is no additional information for this course.

## Register For This Course

Biostatistics For Credit