CogWare™ : Advanced Adaptive Courseware from CogBooks
This course provides an introduction to Statistics for learners majoring in fields other than Math and Engineering. One of the primary objectives of this course is to help learners understand statistical concepts and their application to real-world problems.
Because the course is built on CogBooks’ Advanced Adaptive technology, it instantly helps you teach more effectively and provide every student with the individual support they need.
Your students will find the experience miles ahead of a static textbook. And because our smart instructor tools give you deep insights into each individual student, you’ll find you can use your valuable time much more productively.
“CogBooks has helped me to be able to focus on the more interesting part of teaching history.”
Denise Bates Arizona State University
See Statistics in action
Introduction to Statistics has been crafted in close collaboration with OpenStax, and enriched with dozens of interactive elements, assessments and learning activities. Combined with our Advanced Adaptive Learning methods, it provides a state of the art courseware experience.
CogBooks is an OpenStax Ally. We join OpenStax in the mission to improve access to affordable educational materials by providing additional resources for OpenStax books. OpenStax is committed to providing free, peer-reviewed textbook content and offering multiple options for faculty who need additional resources for their course.
This course is handcrafted by a team of expert CogBooks Instructional Designers and Subject Matter Experts – Dr. Amit K Biswas, Derek Stevens, Helene Ambrose, Raghavendra Kulkarni, Robert Rogowski and others.
Explore the topics covered
Data Collection and Summarization
Learners will be introduced to the processes involved in the collection and preliminary scrutiny of the data. The goal of this unit is to help learners effectively summarize large data sets by the application of appropriate graphical or numerical techniques.
Probability and Discrete Distributions
Probability distributions are mathematical functions that associate an outcome of a statistical experiment with its likelihood of occurrence. There are two types of probability distributions – Discrete probability distribution and Continuous probability distribution.
In this unit, learners will be introduced to the topics of probability and discrete probability distribution. The goal of this unit is to enable learners to make informed decisions by reducing the risk of uncertainty through the application of theory of probability.
Continuous and Sampling Distributions
Statistics as a subject deals with variables which vary over time, space and units of study. These variables have a definite pattern which is unique to them. Without a knowledge of this pattern, evaluation of probabilities of events associated with the variable is not feasible. These patterns are known as distributions in statistical parlance. In this unit, learners will study the concepts of Continuous and Sampling distributions.
Point & Interval Estimation and Introduction to Testing of Hypothesis
Statistics deals with variables. Variables exhibit patterns and these patterns are known as distributions. Distributions are functions of the variable and they also involve parameters. Parameters are population characteristics and hence most often are unknown due to the size of the population. Hence, the best method to estimate these unknown parameters is from a small sample data. However, a single value as estimate or a point estimate may not always provide the desired result therefore a small interval of possible values or an interval estimate is considered.
In addition to Point and Interval estimation techniques, learners will be introduced to the concept of Testing of Hypothesis in this unit.
Testing of Hypothesis and Chi-Square Tests
A hypothesis test is a statistical test that is used to determine whether there is sufficient evidence in a sample of data to conclude that a certain hypothesis is true for the entire population. This test examines two opposing hypotheses about a population: the null hypothesis and the alternative hypothesis. This test can also be extended to two populations or samples. These different possibilities are discussed in detail in this unit.
Additionally, learners will also study about Chi-Square test which is a statistical method to evaluate the goodness of fit between a set of observed values and those expected theoretically.
Correlation and Regression
Regression analysis is a statistical analysis technique which can be used to ascertain the relationship between a dependent variable and one or more independent variables. Correlation analysis helps in estimating the strength of a relationship between two variables. Both these techniques aid in understanding and quantifying the relationship between two or more variables.
Advanced Analytical Methods
Analysis of Variance (ANOVA) is a statistical technique used to determine whether there are any differences between two or more population means.
In this unit, learners will study about statistical methods such as ANOVA, non-parametric inference and categorical data analysis.
Adding CogBooks to your LMS and getting your students started couldn’t be easier
CogBooks can be easily integrated with Blackboard, Canvas, Moodle, D2L, Schoology, or other stand-alone Learning Management System (LMS) or website – without troubling your institution’s IT specialists. Just add a URL to your course and we manage the rest.
Whether student access is covered as part of their course fee or they buy direct through your campus bookstore or online from CogBooks, the process is simple and our dedicated support team are standing by if you need any help to get up and running.
Other integration options are available based on the IMS LTI standard, please contact us for more information.
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Access and review the Statistics course
Full access to the Statistics course will be available from May, 2017. If you’d like an early preview to our courseware to review for use in your class, please submit your details here.