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    StatisticsThis 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 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 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). 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 UniversityRice University,  and the  US Centers for Disease Control and Prevention (CDC).

    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 Pre-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.

  • Before starting this first module, please take a moment to take the short knowledge Pre-test 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:
    1. Describe the roles biostatistics serves in the discipline of public health. 
    2. Distinguish among the different measurement scales and the implications for selection of statistical methods to be used based on these distinctions.
    3. Apply descriptive techniques commonly used to summarize public health data.
    4. Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

    Click here for the brief module introduction


  • 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

    Click here to start this module

    4 URLs, 1 Quiz

  • 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

    Click here to start this module

    5 URLs, 1 Quiz

  • 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 

    Click here to start this module

    5 URLs, 1 Quiz

  • 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

    Click here to start this module

    4 URLs, 1 Workshop, 1 Assignment, 1 Quiz

  • Competencies covered in this module:
    1. Describe basic concepts of probability, random variation, and commonly used statistical probability distributions.
    2. Distinguish among the different measurement scales and the implications for selection of statistical methods to be used based on these distinctions.
    3. Apply descriptive techniques commonly used to summarize public health data.
    4. Apply common statistical methods for inference.
    5. Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

    Click here for the brief module introduction


  • 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

    Click here to start this module

    6 URLs, 1 Quiz
  • 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

    Click here to start this module

    10 URLs, 1 Workshop, 1 Quiz

  • Competencies covered in this module
    1. Distinguish among the different measurement scales and the implications for selection of statistical methods to be used based on these distinctions.
    2. Apply common statistical methods for inference.
    3. Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

    Click here for the brief module introduction

  • 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

    Click here to start this module

    6 URLs, 1 Quiz

  • 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

    Click here to start this module

    2 URLs, 1 Quiz

  • Competencies covered in this module:
    1. Describe preferred methodological alternatives to commonly used statistical methods when assumptions are not met.
    2. Apply common statistical methods for inference.
    3. Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

    Click here for the brief module introduction


  • 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

    Click here to start this module

    7 URLs, 1 Quiz

  • 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

    Click here to start this module

    11 URLs, 1 Quiz
  • 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

    Click here to start this module

    5 URLs, 1 Quiz
  • 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

    Click here to start this module

    5 URLs, 1 Workshop, 1 Quiz

  • Competencies covered in this module:

    Linear least squares example2

    1. Apply common statistical methods for inference.
    2. Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.

    Click here for the brief module introduction


  • 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

    Click here to start this module

    10 URLs, 1 Quiz

  • Learning Objective
    • Understand multiple linear regression and its applications

    Approximate time required for the readings in this lesson (at 144 words/minute): 1 hour

    Click here to start this module

    2 URLs, 1 Quiz

  • 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

    Click here to start this module

    9 URLs, 1 Quiz

  • 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

    Click here to start this module

    2 URLs, 2 Peer Activities, 1 Quiz
  • Simple Confounding Case

    Competencies covered in this module:
    1. Describe the roles biostatistics serves in the discipline of public health.
    2. Apply common statistical methods for inference.

    Click here for the brief module introduction


  • 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

    Click here to start this module

    7 URLs, 1 Quiz

  • 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

    Click here to start this module

    2 URLs, 1 Assignment, 1 Quiz
  • US timeline. Number of overdose deaths from all drugs

    Competencies covered in this module:

    1. Describe the roles biostatistics serves in the discipline of public health.
    2. Apply descriptive and inferential methodologies according to the type of study design for answering a particular research question.
    3. 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.
    4. Interpret results of statistical analyses found in public health studies.
    5. Develop written and oral presentations based on statistical analyses for both public health professionals and educated lay audiences.

    Click here for the brief module introduction


  • 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

    Click here to start this module

    4 URLs, 1 Quiz

  • 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

    Click here to start this module

    4 URLs, 1 Workshop, 1 Assignment, 1 Quiz