About Statistics:

Statistics is the study of the collection, organization, analysis, interpretation, and presentation of data. 

In this course, statistical thinking is viewed as an investigative process that leads to data-based conclusions. The type of statistical thinking learned and practiced supports student success in future courses, builds workplace skills, and prepares students to become well-informed, engaged citizens.

We live in a data-driven society. As of May 2024, 328.77 million terabytes of data are created every day, and some experts predict that the world will create 147 zettabytes of data by the end of 2024. This is a significant increase from 2020, when users generated 64.2 zettabytes of data  We need to be able to understand and interpret all this data in meaningful and thoughtful ways.

By the end of the term, you will be informed citizens.  You will have engaged in the kinds of day-to-day activities that statisticians do, such as research, thinking, reading, teaching, presenting, and using technology.  Most importantly, I hope that by the end of the term, you will have learned to ask questions about the world and about statistics and data that news media, politics, and other sources cite.  It is the asking of questions that drives statistical inference and good decision-making.

You will be challenged, but challenge and struggle are VITAL to learning. You must struggle with the concepts to be able to learn and understand them.  I will be facilitating this struggle through active learning and group activities in Canvas. Your voice and perspective are vital to the entire class.

GUIDING QUESTIONS:

• How do we gather “good” data?

• Why is data collected and analyzed?

• How do people use data to influence others?

• How can predictions be made based on data?

MAJOR ASSUMPTIONS:

• As human beings, we engage in research and information gathering — asking questions and pursuing strategies to answer those questions — every day.

• If we are thoughtful and careful, we can use statistics to make connections about various systems, social structures, and scientific data in the world.

• We are a data-driven society: most, if not all, decisions are made on analyzing data and drawing conclusions from the analysis. To make good decisions, we need to know how to analyze and properly draw conclusions.

• Education doesn't have to be painful for us to learn. Learning can be fun; in fact, we probably learn best when our minds and bodies are actively engaged in the learning process.

STUDENT LEARNING OUTCOMES

Upon Completion of Math 40, a student should be able to:

• build a frequency distribution for, and make a histogram of, quantitative data. 

• determine whether or not there is significant correlation for a bivariate data set, and if so, fit a linear regression equation and use it for data prediction. 

• perform the steps for a hypothesis test about a single population parameter and interpret the result. 

• solve an application problem using the central limit theorem. 

• use a computer program to make a graph of categorical data. 

Course Outline

Media Credits: 

Course Banner: Computer with Graphs, Photo by Carlos Muza on Unsplash 

Children in Various Poses: Ashley McHale (my two kids at various ages)

Bottom Quote Background: Person holding a handful of Coins with Note "Make a Change", Photo by Kat Yukawa on Unsplash