*Introductory Statistics

Lumen’s new Introductory to Statistics course will be delivered in Lumen One, a new platform that brings together the best of Lumen’s teaching & learning solutions including a full suite of professional development resources to support evidence-based teaching. Designed for the Introductory Statistics course, it can also be used in a co-requisite course model, as it includes extensive additional support for those students struggling with prerequisite skills.  

Designed to Support Equity

This Introductory Statistics course is built with support from the Bill & Melinda Gates Foundation to promote equitable outcomes in gateway coursesPutting equity at the center of course design allows us to focus on the research-backed practices and approaches that have a real and measurable positive impact on outcomes for all students, especially Black, Latino/a/x, Indigenous, and low-income students.

The platform and content of the course are built to:

  • Create and foster connections between faculty and students. 
  • Support students’ sense of belonging and engagement.
  • Provide early & timely intervention when students face challenges.
  • Surface student performance and actionable data for faculty to quickly see who’s struggling and help them.
  • Include sample data sets and problems that are relevant and culturally diverse.
  • Provide worked problem videos that make students feel represented and included.

Working closely with both student and faculty groups, Lumen’s principles of co-design and collaboration also extend to the course content, which comes from our partnership with The Dana Center at UT Austin.

Key features include:

  • A simplified, highly-actionable Faculty Engagement Center that enables timely intervention when students are struggling
  • Class-wide performance analytics on pre-requisite skills and learning objectives so you can flex your instruction to better support your students 
  • A suite of support resources, including evidence-based teaching practices to help faculty quickly identify and action student support needs
  • A suite of Statistical Technology Tools designed to help students visualize and manipulate data as they learn new concepts and attempt problems
  • Facilitation of peer-to-peer learning and engagement
  • A design that is built from the ground up to promote equitable outcomes through research-backed instruction

Content 

Thinking Statistically and Collecting Data

  • Thinking Statistically
  • Statistical Questions
  • Statistical Studies
  • Sampling Methods and Bias

Statistical Studies

  • Observational Studies
  • Experimental Design
  • Advanced Experimental Design
  • Analyzing Statistics in Media

Describing Data Graphically

  • Displaying Categorical Data
  • Applications of Bar Graphs
  • Visualizing Quantitative Data
  • Distribution of Quantitative Data
  • Comparing Quantitative Distributions

Describing Data Numerically

  • Measures of Center
  • Interpreting the Mean and Median
  • Boxplot Data and Displays
  • Measures of Variability
  • Z-Score and the Empirical Rule

Modeling and Analysis of Bivariate Data

  • Scatterplots & Correlation Coefficients
  • Line of Best Fit
  • Coefficient of Determination
  • Assessing the Fit of a Line

Probability

  • Probability
  • Probability of Compound Events
  • Conditional Probabilities

The Normal Distribution

  • Probability Distributions
  • Normal Distribution
  • Normal Curves and Percentiles

Introduction to Sampling Distributions

  • Inference Basics
  • Sampling Distribution of a Sample Proportion
  • Sampling Variability

Confidence Intervals for Population Proportions

  • Confidence Intervals for a Population Proportion
  • Confidence Intervals for Proportions (continued)
  • Sample Size for Proportions
  • Confidence Intervals for the Difference in Population Proportions

Hypothesis Testing for Population Proportions

  • Null and Alternative Hypotheses
  • One-sample Hypothesis Test for Proportions
  • Errors in Hypothesis Testing
  • Comparing Two Population Proportions
  • Connecting Tests and Intervals

Confidence Intervals for Population Means

  • Sampling Distribution of a Sample Mean
  • The t-distribution
  • Confidence Intervals for a Population Mean
  • Confidence Intervals for the Difference in Population Means

Hypothesis Testing for Population Means

  • Null and Alternative Hypothesis for Means
  • One Sample Hypothesis Test for Means
  • Comparing Two Population Means (Independent Samples)
  • Comparing Two Population Means (Dependent Samples)

Inferences Concerning Two Population Means

  • Introduction to One-way ANOVA
  • Conditions for ANOVA
  • ANOVA
  • Pairwise Comparisons for ANOVA

Chi-Squared Statistics

  • Introduction to Chi-Square Statistics
  • Chi-Square Test for Goodness of Fit
  • Chi-Square Test of Homogeneity
  • Chi-Square Test of Independence
  • Fisher’s Exact Test

Analysis of Variance

  • Test for Significance of Slope
  • ANOVA for Regression
  • Confidence Interval and Prediction Interval
  • Transforming Data

Multiple Linear Regression

  • Multiple Linear Regression
  • Indicator Variable
  • Interaction Terms

Bootstrap and Simulation-Based Statistics

  • Bootstrap Distribution and Confidence Interval for a Population Mean
  • Bootstrap Confidence Interval
  • Simulation-Based Hypothesis Tests for a Population Proportion
  • Simulation-Based Hypothesis Test for a Difference in Proportions

Probability: Computation Approach*

  • Probability with Venn Diagrams
  • Probability with Tree Diagrams
  • Bayes’ Theorem

Probability Distributions: Additional Distribution Analysis*

  • Discrete Probability Distributions
  • Binomial Distribution
  • Connection Between Binomial and Normal Distributions

*These modules serve as alternative teaching options. They can be used jointly with other modules, used as a replacement, or not be used at all. The instructor has flexibility for how they wish to incorporate these final modules.

 

 

Teaching with Lumen Course Materials

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  • Replace expensive textbooks | Ready-to-adopt open educational resources (OER) include text, videos, simulations, self-checks, and other interactives.
  • Choose affordability | Low cost to students.
  • Use better content | Continuous, data-driven improvements make OER content more effective at supporting learning.
  • Simplify access | Easy access to course materials in your LMS (Blackboard, Canvas, D2L, and Moodle) plus automatic grade return.
  • Improve student outcomes | Research shows Lumen course materials can improve academic performance, passing rates, and course completion.

FOR INSTRUCTORS

  • Connect with students | Instructor and student tools designed to help strengthen communication.
  • Save time | Start with curated, outcome-aligned OER and supplemental instructor resources like quiz banks, assignments, slide decks, etc. 
  • Customize your course | Freedom to tailor course content to fit your learning outcomes and instructional approach.
  • Enjoy awesome support | Faculty-friendly onboarding, training, and support. 
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FOR STUDENTS

  • Learn by doing | Online homework, self-check activities, and other interactive tools strengthen learning.
  • Engage from day one | Avoid falling behind with access to course materials from the first day of class.
  • Retain materials | Download a digital copy of course content to keep forever.
  • Become a better learner | Real-time feedback guides students on where to focus and how to improve.

Are you ready to get started with Lumen Learning digital courseware?

Great! Fill out our Explore a Course form, and our team will contact you promptly.

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