| Required readings | |

## How to create an account and enroll in the course? | ||

## Biostatistics Homepage
This introductory course in This course is co-sponsored 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) and sponsored in part by the Annenberg Physician Training Program. Like all NextGenU.org courses, it is competency-based, using competencies from the Association of Schools and Programs of Public Health (ASPPH). This course uses learning resources from world-class 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, to see more research related to NextGenU.org’s educational model, check out NextGenU.org’s publication page. Subscribe to our newsletter to be notified of future updates, new courses, and to be part of our community. There are two components to this course. The first component involves completing the modules and which provide: - An introduction to probability and sampling distributions;
- An overview of confidence intervals, hypothesis testing, regression analysis, confounding, and interactions;
- Skills for the application of biostatistics in the practice and study of public health.
In order to receive a certificate of completion, you will need to also complete the second, skills-based component of the course, which requires you to identify a mentor with professional health care training at least at the bachelor’s level, and with a certificate or other specific training in Public Health, who can provide you with feedback on the assignments you submit. The results of your assessments will be provided to you, and we can report your testing information and share your work with anyone you request (school, employer, etc.). The evaluation you provide at the course’s conclusion will help us improve the training for future students. We hope you find this Biostatistics course a wonderful learning experience!
Before you begin the course, please take a moment to take the short knowledge Pre-course test below. It allows us to assess various aspects of the course itself and is mandatory to receive your certificate upon completion of the course. Then you may start Module 1: The Basics of Biostatistics. The course requires completion of peer and mentored activities. At the end of each lesson, there is a practice quiz. At the end of the course, after you’ve completed each lesson, quiz, and activity, you’ll have access to a final exam, and a chance to assess the training. Once you’ve passed that last test, you will be able to download a certificate of completion from NextGenU.org and our course’s co-sponsoring organizations (listed above). We keep all of your personal information confidential, never sell any of your information, and only use anonymized data for research purposes, and we are also happy to report your testing information and share your work with anyone (your school, employer, etc.) at your request. We hope that you will find this a rewarding learning experience, and we count on your assessment and feedback to help us improve this training for future students. Before you begin the course, please take a moment to take the short knowledge Pre-test below. It allows us to assess various aspects of the course itself and is required to receive your certificate upon completion of the course.
You may browse this course for free to learn for your personal enrichment; there are no requirements.
- Show in the registration fields that you have the appropriate prerequisites to be certified [a high school degree for college courses, a college degree for the master’s level courses, and enrollment in or graduation from a medical doctoral program for our medical doctoral-level courses].
- Take the brief pre-test.
- Complete all the reading requirements.
- Complete all quizzes.
- Complete all 6 peer activity and associated certification quizzes.
- Find a mentor and complete the 3 required mentor activities.
- Successfully complete the final exam with a minimum of 70% and a maximum of 3 attempts.
- Complete the self and course evaluation forms.
- Complete all requirements listed above for the certificate.
- Your learning institution or workplace should approve the partner-university-sponsored NextGenU.org course for educational credit, as they would for their learner taking a course anywhere.
- NextGenU.org is happy to provide your institution with:
- a link to and description of the course training, so they can see all its components, including the cosponsoring universities and other professional organization cosponsors;
- your grade on the final exam;
- your work products (e.g. peer and mentored activities), and any other required or optional shared materials that you produce and authorize to share with them;
- your evaluations -- course, self, and peer assessments;
- a copy of your certificate of completion, with the co-sponsoring universities and other organizations listed.
We hope that you will find this a rewarding learning experience, and we count on your assessment and feedback to help us improve this training for future students.
- Take the short knowledge pre-test below. It allows us to assess various aspects of the course itself.
- Complete the registration form.
- Begin the course with Module 1: The Basics of Biostatistics. In each lesson, read the description, complete all required readings and any required activity, and take the corresponding quizzes.
*This course is sponsored in part by the Annenberg Physician Training Program: Abstinence-based Recovery from Addictive Disease. Click here to see curricular threading related to mental health disorders. Required readings | ||

## Module 1: The Basics of Biostatistics
## 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.
Required readings | ||

## 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 | Required readings- Role of Biostatistics (12 mins)
- Johns Hopkins Bloomberg School of Public Health – Statistics for laboratory scientists I (5 mins)
- Basic statistical tools in research and data analysis (22 mins)
- NHANES descriptive statistics
| |

## 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 | Required readings- Levels of Measurement (15 mins)
- Introductory Statistics (80 mins)
- Chapter 4 – Exploratory Data Analysis (20 mins)
- Chapter 2 – Defining and Classifying Data Variables (20 mins)
| |

## 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 hour | Required readings- Chapter 4 – Exploratory Data Analysis (25 mins)
- One Categorical Variable (13 mins)
- Statistics by Example (35 mins)
- 4.2 – The Normal Curve (10 mins)
| |

## 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): 3 hours. | Required readings- Dr. Elizabeth Newton – 15.075, Applied Statistics (15 mins)
- Importance of using basic statistics adequately in clinical research (26 mins)
- Webinar Using Data to Guide and Evaluate Responses to the Opioid Crisis Rhode Island's Drug Overdose
| |

## 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## 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 | Required readings- Introduction to Probability (30 mins)
- Introductory Statistics (25 mins)
- Basic Probability Rules (40 mins)
- Introductory Statistics (40 mins)
- Johns Hopkins Bloomberg School of Public Health – Probability (15 mins)
- Johns Hopkins Bloomberg School of Public Health – Probability Concepts (35 mins)
| |

## 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 | Required readings- Unit 3B: Random Variables (80 mins)
- 3.2.2 – Binomial Random Variables (15 mins)
- Sampling (30 mins)
- Inferential Statistics (15 mins)
- Chapter 3 - Review of Probability (105 mins)
- Introduction to Sampling Distributions (20 mins)
- Central Limit Theorem (11 mins)
- The Sampling Distribution (10 mins)
- Normal Random Variables (80 mins)
- 1.5.1 – Measures of Central Tendency (30 mins)
| |

## Module 3: Confidence Intervals
| ||

## 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 one-sided and two-sided confidence intervals for mean and proportion.
Approximate time required for the readings in this lesson (at 144 words/minute): 3 hours | Required readings- Introduction to Estimation (30 mins)
- 4.2 – Introduction to Confidence Intervals (7 mins)
- Introductory Statistics (60 mins)
- Module 5: Interval Estimation (9 mins)
- Basic Concepts of Inference (60 mins)
| |

## 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 | Required readingsOptional readings | |

## 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## 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 | Required readings- S.3 Hypothesis Testing (45 mins)
- Significance Testing (15 mins)
- 1.1.2 – Explanatory and Response Variables (3 mins)
- 10.1 – Setting the Hypotheses: Examples (9 mins)
- Significance Testing and Confidence Intervals (7 mins)
- Biostatistics Series Module 2: Overview of Hypothesis Testing (26 mins)
- 7.1.5. What is the relationship between a test and a confidence interval? (2 mins)
| |

## 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 chi-squared 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 p-values.
- 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 | Required readings- Introductory Statistics (60 mins)
- Introductory Statistics (30 mins)
- Introductory Statistics (40 mins)
- 8.1 – The Chi-Squared Test for Independence (26 mins)
- Lesson 10: Introduction to ANOVA (30 mins)
- 6. Statistical Inference and Hypothesis Testing: 6.1 One Sample (45 mins)
- 6. Statistical Inference and Hypothesis Testing: 6.2 Two Samples (28 mins)
- When to use the Bonferroni correction (26 mins)
- P-Value, A True Test of Statistical Significance? A Cautionary Note (33 mins)
- Statistical Notes for Clinical Researchers: Type I and Type II errors in statistical decision (16 mins)
| |

## 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 | Required readingsOptional readings- Biostatistics Series Module 5: Determining Sample Size (43 mins)
- How to Calculate Sample Size for Different Study Designs in Medical Research (35 mins)
- Sample Size Calculations: Basic principles and common pitfalls (43 mins)
| |

## Module 4: Lesson 4: Nonparametric Tests## Learning Objectives- Summarize and describe non-parametric 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 p-values.
Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour | Required readings- Nonparametric Tests (60 mins)
- Statistical Notes for Clinical Researchers: Nonparametric statistical methods: 1. Nonparametric methods for comparing two groups (11 mins)
- Statistical Notes for Clinical Researchers: Nonparametric statistical methods: 2. Nonparametric methods for comparing three or more groups and repeated measures (9 mins)
- Peer Activity 3: Hypothesis Testing Problem 1
- Peer Activity 4: Hypothesis Testing Problem 2
- Peer Activity 5: Hypothesis Testing Problem 3
- Peer Activity 6: Hypothesis Testing Problem 4
| |

## Module 5: Regression Analysis## Competencies covered in this module:
- Apply common statistical methods for inference.
| ||

## 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 | Required readings- Introductory Statistics (55 mins)
- Correlation and linear regression (20 mins)
- 1.1 - What is Simple Linear Regression? (40 mins)
- Statistical Reasoning II: Lecture Notes (40 mins)
- Lesson 2: SLR Model Evaluation (60 mins)
- Inferential Statistics for b and r (2 mins)
- Lesson 3: SLR Estimation & Prediction (30 mins)
- Lesson 4: SLR Model Assumptions (50 mins)
- Common pitfalls in statistical analysis: The use of correlation techniques (12 mins)
- Introductory Statistics (40 mins)
| |

## 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 | Required readingsOptional readings | |

## 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 | Required readings- Statistical Reasoning II: Lecture Notes (60 mins)
- Logistic Regression (15 mins)
- Statistical Reasoning II: Lecture Notes (60 mins)
- 15.1 - Logistic Regression (60 mins)
- Common pitfalls in statistical analysis: Odds versus risk (10 mins)
- Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat (10 mins)
- 8.3 - Risk, Relative Risk and Odds (5 mins)
- Common pitfalls in statistical analysis: Logistic regression (17 mins)
- 15.4 - Poisson Regression (30 mins)
| |

## 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 | Required readingsOptional readingsPeer Activities- Peer-To-Peer Activity: Linear Regression Problem Set #1
- Peer-To-Peer Activity: Logistic Regression Problem Set #2
| |

## Module 6: Confounding and Interactions## Competency 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## 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 | Required readings- 3.5 - Bias, Confounding and Effect Modification (30 mins)
- Statistical Reasoning II: Lecture Notes (75 mins)
- Confounding and Effect Measure Modification - Conditions Necessary for Confounding (60 mins)
- Multivariable Methods - Effect Modification (8 mins)
- 6.4 - Error, Confounding, Effect Modification in Ecological Studies (2 mins)
- Confounding Bias, Part I (60 mins)
- Confounding Bias, Part II and Effect Measure Modification (60 mins)
| |

## 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 | Required readings- Cigarette smoking: an underused tool in high-performance endurance training (9 mins)
- Assessing bias: the importance of considering confounding (15 mins)
| |

## Module 7: Biostatistics in Public Health
## Competency covered in this module:- Describe the roles biostatistics serves in the discipline of public health.
- 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## 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.
Approximate time required for the readings in this lesson (at 144 words/minute): 3 hours | Required readings- Statistical methods used in the public health literature and implications for training of public health professionals (32 mins)
- Helping Doctors and Patients Make Sense of Health Statistics (100 mins)
- Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations (55 mins)
- The misuse and abuse of statistics in biomedical research (22 mins)
| |

## 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 | Required readings- National Health and Nutrition Examination Survey - Data Accomplishments (8 mins)
- Did You Know? Video Series (5 mins)
- Biostatistics: fundamental concepts and practical applications (6 mins)
- CDC’s Alcohol Screening and Brief Intervention Efforts
- Bringing Data Science to Addiction Research #3
- Lessons from Prevention Research DrugFacts
- Finding Evidence-based Programs and Practices
- Biostatistics: fundamental concepts and practical applications (15 mins)
| |

## Final Exam | Required readings | |

## Course and Self Evaluation & CertificateIn this section, you can provide feedback about this course to help us make NextGenU.org better. Once evaluations are completed, you will be able to download your certificate of completion. | Required readings | |

## Course ActivitiesRequired readings |