Introductory Statistics (editable text + online assessment)

Content Overview

Course Materials YES NO
Lumen OHM Questions?  X
Editable Text?  X – access here
Video Support? X – in text
Written Assessments/ Test?  X – problem sets in text with answers to odds
Workbook? X

Text

This text blends Introductory Statistics from OpenStax with other OER to offer a first course in statistics intended for students majoring in fields other than mathematics and engineering. This course assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of the OpenStax text is Collaborative Statistics, by Barbara Illowsky and Susan Dean.  The eText is fully editable and can be delivered as a pdf, or in an LMS (Canvas, Blackboard, D2L, Moodle).

This course package contains online assessments in Lumen OHM, which can be imported into your LMS (Canvas, Blackboard, D2L, Moodle).  This text also contains embedded video examples created by James Sousa (mathispower4u.com).

Topic Overview

This course is delivered in 16 chapters that include the following topics:

Sampling and Data

  • Frequency, frequency tables, levels of measurement
  • Ethics

Descriptive Statistics

  • Stem-and-leaf plots, histograms, frequency polygons, time series graphs, box plots
  • Measures of the center of data, skewness, central tendency

Probability

  • Contingency tables
  • Tree and Venn diagrams

Discrete Random Variables

  • Probability distribution function
  • Mean or expected value, standard deviation
  • Binomial distribution, geometric distribution, poisson distribution

Continuous Random Variables

  • Continuous probability functions
  • Uniform and exponential distribution

Normal Distribution

  • The standard normal distribution

Central Limit Theorem

  • Central limit theorem for sample means, sums

Confidence Intervals

  • A single population mean using normal distribution, student t distribution
  • A population proportion

Hypothesis Testing With One Sample

  • Null and alternative hypothesis
  • Rare events

Hypothesis Testing With Two Samples

  • Comparing two independent population proportions
  • Matched or paired samples

The Chi Square Distribution

  • Linear equations
  • Scatter plots, correlation coefficient
  • Prediction, outliers

Introduction to Linear Regression

  • Line fitting, residuals, least squares
  • Inference, types of outliers

Multiple and Logistic Regression

  • Model selection, assumptions
  • Logistic regression

F-Distribution and One-Way ANOVA

  • One-Way ANOVA, relationships in an ANOVA table
  • F-Distribution and the F-ratio

Length: One semester

Delivery: This course package has been used in online and in face to face courses

Online Content

Each module of text has a set of online practice problems.  Additionally, there are two quizzes, a mid-term and comprehensive final exam.

Online Practice Problems

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Online Assessment Features

Many questions in the Lumen OHM libraries are randomized, algorithmic questions. Students get immediate feedback after they submit an answer. Question types include:

  • Entering an integer, fraction, decimal
  • Graphing
  • Reading information from a graph
  • Multiple choice
  • Free-writing (instructor graded)
Graphing question Immediate feedback
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Because of the open license on the libraries of questions in Lumen OHM, you are also free to edit and create your own questions with the question writing tools.

Course Review Access

Follow the link to review the Introductory Statistics course materials in Lumen OHM.