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This Biostatistics course provides an introduction to the field of biostatistics, the branch of statistics responsible for the interpretation and application of scientific data generated in public health, clinical medicine, biology, and other health sciences. Students will develop foundational skills and knowledge in biostatistics (through online didactics) and gain a deeper understanding of its relevance and application to public health, health policy, clinical medicine, and health economics (with globally available peers and mentors). All components of this training (like all NextGenU.org trainings) are free, including registration, learning, testing, and a certificate of completion.
There are 7 modules to complete through online study and peer and mentored activities. These modules provide an introduction to probability and sampling distributions, confidence intervals, hypothesis testing, regression analysis, confounding and interactions, and the application of biostatistics in the practice and study of public health.
Each module contains practice quizzes, and at the end of the course you’ll take a final exam and have a chance to give your assessment of this training. We will give you all the results of your assessments, such as your final exam and peer activities. We can report your testing information and share your work with anyone (your school, employer, etc.) that you request. We hope this is a wonderful learning experience for you and that your assessments will teach us how we can make it even better.
This course is cosponsored by the University of the Incarnate Word, the Association for Prevention Teaching and Research (APTR), and the US Centers for Disease Control and Prevention (CDC). Like all NextGenU.org courses, it is competencybased, using competencies from the Association of Schools and Programs of Public Health (ASPPH). This course uses learning resources from worldclass academic and governmental organizations such as Penn State University, Rice University, and the US Centers for Disease Control and Prevention (CDC).
For a publication on this course’s efficacy, see “Building Public Health Capacity through Online Global Learning,” (2018), Open Praxis, https://openpraxis.org/index.php/OpenPraxis/article/view/746/427; to see more research related to NextGenU.org’s educational model, check out NextGenU.org’s publication page.
Approximate time for the required readings in this course is 47 hours at an average rate of 144 words/minute; in addition, there are required activities.
Begin the course with Module 1: The Basics of Biostatistics.
Before you begin the course, please take a moment to take the short knowledge Pretest below. It allows us to assess various aspects of the course itself and is mandatory to receive your certificate upon completion of the course.

Module 1: The Basics of Biostatistics
Module 1: The Basics of Biostatistics
Before starting this first module, please take a moment to take the short knowledge Pretest above. It allows us to assess various aspects of the course itself and is mandatory to receive your certificate upon completion of the course.
Competencies covered in this module:
 Describe the roles biostatistics serves in the discipline of public health.
 Distinguish among the different measurement scales and the implications for selection of statistical methods to be used based on these distinctions.
 Apply descriptive techniques commonly used to summarize public health data.
 Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

Module 1: Lesson 1: Introduction to Biostatistics
Module 1: Lesson 1: Introduction to Biostatistics
Learning Objectives
 Explore the basic principles of statistics and some of its common uses
 Understand the basic principles of probability, descriptive statistics, and data analysis
 Understand how to generate descriptive statistics from data
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
4 URLs, 1 Quiz 
Module 1: Lesson 2: Types of Variables, Plots, and Graphs
Module 1: Lesson 2: Types of Variables, Plots, and Graphs
Learning Objectives
 Understand the different types of variables, how they are used, and how to summarize the data
 Understand and identify the different types of plots and graphs
Approximate time required for the readings in this lesson (at 144 words/minute): 2 hours
5 URLs, 1 Quiz 
Module 1: Lesson 3: Descriptive Statistics and Distribution
Module 1: Lesson 3: Descriptive Statistics and Distribution
Learning Objectives
 Generate descriptive statistics from data, calculate descriptive statistics and standard deviations, and understand the methods of summarizing a single quantitative variable
 Summarize and describe the distribution of a categorical variable, and understand the uses and implications of the normal distribution
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour5 URLs, 1 Quiz 
Module 1: Lesson 4: Data Analysis and Study Design
Module 1: Lesson 4: Data Analysis and Study Design
Learning Objectives
 Understand the basic types of data, the main ways in which data are used, and important considerations when using data in analysis
 Identify the design of a study and explain how this impacts interpretation
 Apply knowledge and skills in working with different data types in a chosen public health setting
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
4 URLs, 1 Workshop, 1 Assignment, 1 Quiz 
Module 2: Probability and Sampling Distributions
Module 2: Probability and Sampling Distributions
Competencies covered in this module:
 Describe basic concepts of probability, random variation, and commonly used statistical probability distributions.
 Distinguish among the different measurement scales and the implications for selection of statistical methods to be used based on these distinctions.
 Apply descriptive techniques commonly used to summarize public health data.
 Apply common statistical methods for inference.
 Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

Module 2: Lesson 1: Probability, Frequency, and the Concepts of Probability
Module 2: Lesson 1: Probability, Frequency, and the Concepts of Probability
Learning Objectives
 Relate the probability of an event to the likelihood of this event occurring
 Understand how to interpret and generate proportions from data
 Explain how relative frequency can be used to estimate the probability of an event
 Understand the concepts of probability, conditional probability, and independence
Approximate time required for the readings in this lesson (at 144 words/minute): 2 hours
6 URLs, 1 Quiz 
Module 2: Lesson 2: Variables, Sampling, and Distribution
Module 2: Lesson 2: Variables, Sampling, and Distribution
Learning Objectives
 Understand the concept of random variables
 Distinguish between samples and population and identify different types of samples
 Understand sampling distribution, variance, and the central limit theorem
 Understand the implications and uses of normality and skewness
 Be able to calculate and correctly interpret probability data from a sampling distribution
Approximate time required for the readings in this lesson (at 144 words/minute): 7 hours
10 URLs, 1 Workshop, 1 Quiz 
Module 3: Confidence Intervals
Module 3: Confidence Intervals
Competencies covered in this module
 Distinguish among the different measurement scales and the implications for selection of statistical methods to be used based on these distinctions.
 Apply common statistical methods for inference.
 Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

Module 3: Lesson 1: Point and Confidence Interval Estimation
Module 3: Lesson 1: Point and Confidence Interval Estimation
Learning Objectives
 Understand and be able to apply point estimation and confidence interval estimation
 Recognize inference on means versus inference on proportion
 Be able to calculate onesided and twosided confidence intervals for mean and proportion
Approximate time required for the readings in this lesson (at 144 words/minute): 3 hours
6 URLs, 1 Quiz 
Module 3: Lesson 2: Effect of Sample Size on Confidence Interval
Module 3: Lesson 2: Effect of Sample Size on Confidence Interval
Learning Objective
 Understand the effect of sample size and other conditions on estimation as well as understand and be able to calculate the sample size needed to achieve the desired confidence level
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
2 URLs, 1 Quiz 
Module 4: Hypothesis Testing
Module 4: Hypothesis Testing
Competencies covered in this module:
 Describe preferred methodological alternatives to commonly used statistical methods when assumptions are not met.
 Apply common statistical methods for inference.
 Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

Module 4: Lesson 1: Principles of Hypothesis Testing
Module 4: Lesson 1: Principles of Hypothesis Testing
Learning Objectives
 Reinforce understanding of probability distributions in the context of hypothesis testing, especially in drawing conclusions and types of errors
 Distinguish types of explanatory and response variables
 Understand the relationship between confidence interval and hypothesis testing
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
7 URLs, 1 Quiz 
Module 4: Lesson 2: Applications of Hypothesis Testing
Module 4: Lesson 2: Applications of Hypothesis Testing
Learning Objectives
 Understand and apply hypothesis tests for a single mean and a single proportion as well as for two means (independent and paired/matched samples), and understand chisquared test and ANOVA
 Understand inference, estimation, and the basics of hypothesis testing
 Understand implications of multiple testing and Bonferroni correction
 Understand and be able to correctly interpret pvalues
 Understand the importance and implications of Type I and Type II errors
Approximate time required for the readings in this lesson (at 144 words/minute): 5 hours
11 URLs, 1 Quiz 
Module 4: Lesson 3: Power and Sample Size
Module 4: Lesson 3: Power and Sample Size
Learning Objective
 Understand factors that affect study power and sample size requirements, and how they impact study design
Approximate time required for the readings in this lesson (at 144 words/minute): 2 hours
5 URLs, 1 Quiz 
Module 4: Lesson 4: Nonparametric Tests
Module 4: Lesson 4: Nonparametric Tests
Learning Objectives
 Summarize and describe nonparametric tests and understand the conditions under which they are applied
 Be able (1) to apply appropriate hypothesis tests to variable types in order to explore relationships and (2) to draw conclusions based on such hypothesis testing and to interpret pvalues
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
5 URLs, 1 Workshop, 1 Quiz 
Module 5: Regression Analysis
Module 5: Regression Analysis
Competencies covered in this module:
 Apply common statistical methods for inference.
 Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

Module 5: Lesson 1: Simple Linear Regression Analysis
Module 5: Lesson 1: Simple Linear Regression Analysis
Learning Objectives
 Understand linear relationships, outliers, and the basics of correlation
 Understand the difference between correlation and simple linear regression, and when to apply one or the other
 Understand homoscedasticity and its applications to correlation and regression
 Understand linear regression and how it relates to prediction
Approximate time required for the readings in this lesson (at 144 words/minute): 5 hours
10 URLs, 1 Quiz 
Module 5: Lesson 2: Multiple Linear Regression Analysis
Module 5: Lesson 2: Multiple Linear Regression Analysis
Learning Objective
 Understand multiple linear regression and its applications
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
2 URLs, 1 Quiz 
Module 5: Lesson 3: Logistic Regression Analysis
Module 5: Lesson 3: Logistic Regression Analysis
Learning Objectives
 Understand simple logistic regression analysis
 Understand multiple logistic regression analysis and distinguish between adjusted and unadjusted regression coefficients
 Be able (1) to distinguish between risks, e.g., absolute and relative risks, as well as odds and odds ratios, and (2) to differentiate relative risks from odds ratios and know how to conduct both methods
Approximate time required for the readings in this lesson (at 144 words/minute): 4 hours
9 URLs, 1 Quiz 
Module 5: Lesson 4: Overview of Correlation and Regression Analysis
Module 5: Lesson 4: Overview of Correlation and Regression Analysis
Learning Objectives
 Be able (1) to distinguish between correlation, linear and multiple regression, and logistic regression, and (2) to understand the purpose and methods of linear (simple and multiple) and logistic regression, including when to use each of them
 Be able to specify regression models and interpret regression results
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
2 URLs, 2 Peer Activities, 1 Quiz 
Module 6: Confounding and Interactions
Module 6: Confounding and Interactions
Competencies covered in this module:
 Describe the roles biostatistics serves in the discipline of public health.
 Apply common statistical methods for inference.

Module 6: Lesson 1: Confounding and Effect Modification
Module 6: Lesson 1: Confounding and Effect Modification
Learning Objectives
 Know the definition of a confounder and understand the concepts of adjustment and stratification, as well as the concepts of confounding and effect modification
 Identify the statistical techniques for dealing with confounding and effect modification and their strengths and limitations
Approximate time required for the readings in this lesson (at 144 words/minute): 3 hours
7 URLs, 1 Quiz 
Module 6: Lesson 2: Confounders and their Impact on Study Conclusions
Module 6: Lesson 2: Confounders and their Impact on Study Conclusions
Learning Objectives
 Be able to comment on the validity of study conclusions with respect to confounding and alternative explanations and appreciate that association neither means causation nor indicates the directionality of potential cause and effect
 Identify potential confounders in a relationship from a theoretical perspective and understand the consequences of using faulty reasoning and improper methods in studies
 Apply analytical statistics in the context of a research project and be able to think critically about practical application of statistical concepts
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
2 URLs, 1 Assignment, 1 Quiz 
Module 7: Biostatistics in Public Health
Module 7: Biostatistics in Public Health
Competencies covered in this module:
 Describe the roles biostatistics serves in the discipline of public health.
 Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.
 Apply basic informatics techniques with vital statistics and public health records in the description of public health characteristics and in public health research and evaluation.
 Interpret results of statistical analyses found in public health studies.
 Develop written and oral presentations based on statistical analyses for both public health professionals and educated lay audiences.

Module 7: Lesson 1: Limitations and Misinterpretations of Biostatistics
Module 7: Lesson 1: Limitations and Misinterpretations of Biostatistics
Learning Objectives
 Understand and explain the relative strengths and limitations of biostatistics as it applies in various settings in public health
 Be able to detect misleading claims and inappropriate methods in research papers as well as appreciate that a statistically significant result may not be clinically significant
 Appreciate that many interests may influence researchers towards favorable interpretation and presentation of their findings
4 URLs, 1 Quiz 
Module 7: Lesson 2: Biostatistics in Public Health Programs
Module 7: Lesson 2: Biostatistics in Public Health Programs
Learning Objectives
 Understand that public health programs rely on biostatistics principles and methodologies to collect, analyze, use, and present data
 Relate specific public health contributions to biostatistics concepts learned in this course
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour
4 URLs, 1 Workshop, 1 Assignment, 1 Quiz  Final Exam Final Exam