Statistics 101 Syllabus Resource & Lesson Plans
 Course type: Selfpaced
 Available Lessons: 104
 Average Lesson Length: 8 min

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chapter 1 / lesson 1Descriptive & Inferential Statistics: Definition, Differences & Examples
Course Summary
This Statistics 101 Syllabus Resource & Lesson Plans course is a fully developed resource to help you teach introductory statistics. You can easily adapt the video lessons, transcripts, and quizzes to take full advantage of the comprehensive and engaging material we offer. Make planning your course easier by using our syllabus as a guide.to start this course today
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8 chapters in Statistics 101 Syllabus Resource & Lesson Plans
Course Practice Test
Check your knowledge of this course with a 50question practice test. Comprehensive test covering all topics
 Detailed video explanations for wrong answers
How It Works
You can use this statistics course as a template for designing and implementing your course. Here are the key components of the course and how you can use them:
 Chapters  Each chapter covers a unit of introductory statistics, from tables and plots to statistical estimation and hypothesis testing. Use these chapters as mile markers as you map out your course. We recommend planning to spend a week on each chapter, but you can always allocate the chapters according to the length of your specific statistics course.
 Lessons  Within each chapter are video lessons that further break down topics into bitesized chunks. These lessons cover single topics like standard deviation or mathematical sets. Each one is often appropriate for a single class.
 Key Terms  Within each lesson are key terms. These are emphasized on screen and in the transcript. As you develop your syllabus, these key terms help you focus on the most important learning objectives. For example, the lesson on quantitative data includes key terms like discrete data and continuous data.
Video Lessons
As you work on your statistics lesson plans, save time by incorporating video lessons from this resource. Here's how:
 Introduce Topics  Your students will be in the right mindset for understanding topics like probability if you begin class with a short video. It can be a jumpingoff point for a lecture, group activity, or class discussion.
 Break Up Lectures  The video format, which often includes animation, helps students visualize topics like zscores and tdistributions.
 Assign For Homework  Each lesson in the course, from descriptive and inferential statistics to the coefficient of determination, can be assigned to your students as homework.
Transcripts
Each video lesson includes a complete transcript. You can utilize these transcripts in several ways:
 Lecture Notes  Do you need a guide as you plan a lecture, such as one on sampling or statistical estimation? The transcripts cover each topic in depth, with key terms highlighted for quick reference.
 Student Reading  Perhaps you'd like your students to learn about stem and leaf displays, but you don't have class time available. Assign the transcript as extra reading.
 Study Tools  When it's time for a unit exam on hypothesis testing, you can point your students to the transcripts on effect size, type I and type II errors, and related topics to help them study.
Quizzes
Each video lesson has a corresponding quiz. Here's how to use the quizzes:
 Homework  Assign a quiz to your students as homework. You'll receive an email with the results, which enables you to verify they've completed the assignment and that they've understood the material. Questions cover everything from methods for finding expected values in games of chance to techniques for interpreting graphical representations of data, such as histograms and frequency polygons.
 Tests  You can meld the material in the quizzes into your own student assessments, saving you valuable time. Need a few questions on regression and correlation? There are plenty!
 Discussions  Jumpstart a discussion with questions like: What differentiates stratified random samples from other sampling techniques?
Sample Syllabus
Below is a sketch of the statistics syllabus modeled on a 10week course. This sample can be adapted based on your course schedule. Navigate the chapters and lessons for more detail.
Week  Unit  Sample of Topics Covered 

Week 1  Overview of Statistics  Descriptive and inferential statistics, quantitative and categorical data, discrete and continuous data, convenience sampling, random selection and allocation, confounding and bias 
Week 2  Summarizing Data  Data sets, measures of central tendency, unimodal and bimodal distribution, spread, the interquartile range, standard deviation, population and sample variance 
Week 3  Tables and Plots  Relative and cumulative frequency tables, stem and leaf displays, histograms, dot and box plots, bar graphs, pie charts, univariate and bivariate data 
Week 4  Probability  Probabilities of simple, compound, and complimentary events; probabilities of independent and dependent events; simple conditional probabilities; the addition and multiplication rules of probability; permutations 
Week 5  Discrete Probability Distributions  Discrete random variables, expected values in games of chance, game strategies, binomial probabilities, standard deviation of a binomial random variable 
Week 6  Continuous Probability Distributions  Expected values of continuous random variables, the normal distribution, zscores 
Week 7  Sampling  Simple and stratified random samples, cluster random samples, systematic random samples, sampling distributions, the law of large numbers, the central limit theorem 
Week 8  Statistical Estimation  Point and interval estimations, confidence intervals for sample means and proportions, tdistributions, biased and unbiased estimators 
Week 9  Hypothesis Testing  Effect size, type I and type II errors, hypothesis tests for matched pairs and proportions 
Week 10  Regression & Correlation  Scatterplots, simple linear regression, the correlation coefficient, causation, the coefficient of determination 
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