# MATH 123: Mathematics for Elementary Statistics

This class is for students who wish to fulfill the Area B4 requirement by taking MATH 124, ISED 160 or PSY 171. Concurrent enrollment in MATH 124, ISED 160 or PSY 171 is required.

## Course Objectives/Content

This course is designed to support development of quantitative reasoning at the college level.  The contexts for quantitative reasoning that will be strengthened in this course are data visualization, data analysis, probability theory, and statistics. The mathematics topics in the course include development of sense-making skills and computational understanding that support and draw upon three units:

• Descriptive analysis of one-variable data, including graphical representations such as histograms and box-plots, as well as measures of central tendency and variation; correlation and linear modeling of two-variable numerical data;
• foundational theory of experimental and theoretical probability;
• normal distribution and its properties, basics of confidence intervals, and hypothesis testing.

The course will focus on developing mathematical practices (e.g., problem-solving, making and testing conjectures, critiquing and building on the reasoning of others; representing and communicating mathematical ideas). Approaches include reflective and collaborative learning to enhance the knowledge needed to succeed in college-level mathematics.

## Student Learning Outcomes

Upon completion of this course, students will have competence to:

• organize numerical data (e.g., as histograms, bar charts, boxplots), and summarize data using mean, median, mode, standard deviation, quartile, and percentile;
• recognize a linear correlation between two variables, and measure and interpret the direction and strength of the linear correlation;
• use elementary probability theory of discrete random variables to express probabilities of complex events;
• understand properties of the normal distribution, recognize when it is suitable to use a normal distribution to describe data;
• improve and practice numerical and computational fluency in the context of the three broad topics (descriptive analysis of one- and two-variable data, elementary probability theory and normal distribution, and basics of confidence intervals and hypothesis testing) chosen from data analysis, probability theory, and statistics.

## Course Evaluation and Expectations

Grade will be based on participation in class activities and completion of outside-of-class assignments. Class participation includes working on activities with other students and presenting problem solutions to others in the class both formally and informally. You are expected to be fully engaged during class. Homework assignments are to be completed PRIOR to class. Do your best to complete assignments.

Submitted by Eric Hsu, May 16 2024