Math M15: Introduction to Statistics - Open For Antiracism (OFAR)
Overview
The Open for Antiracism (OFAR) Program – co-led by CCCOER and College of the Canyons – emerged as a response to the growing awareness of structural racism in our educational systems and the realization that adoption of open educational resources (OER) and open pedagogy could be transformative at institutions seeking to improve. The program is designed to give participants a workshop experience where they can better understand anti-racist teaching and how the use of OER and open pedagogy can empower them to involve students in the co-creation of an anti-racist classroom. The capstone project involves developing an action plan for incorporating OER and open pedagogy into a course being taught in the spring semester. OFAR participants are invited to remix this template to design and share their projects and plans for moving this work forward.
Action Plan
The use of open pedagogy allow your students to have a say in their eductaion. This project is one slected by students and brings in a wonderful discussion about how racism played a role in forming neighborhoods. Enjoy.
Course Description
Math M15 - Introduction to Statistics
Course Objectives
Summarize data graphically by displaying data using methods from descriptive statistics, interpreting data in tables graphically by using histograms, frequency distributions, box-and whisker (five-number summary); find measures of central tendency for data sets: mean, median, and mode; find measures of variation for data sets: standard deviation, variance, and range; relative positions of data and distinguish among scales of measurements and their implications; distinguish between populations and samples; and identify the standard method of obtaining data and the ad- vantages and disadvantages of each. Interpreting data is 90% of the battle! These skills will prevent you from being fooled by misleading statistics.
Find simple probabilities and probabilities of compound events and compute probabilities using the complement, discrete probability distributions, apply concepts of sample space, the binomial probability distribution. Like to gamble? I can teach you.
Standardize a normally distributed random variable, use normal distribution tables to find probabilities for normally distributed random variables and the t-distribution, and use the Central Limit Theorem to find probabilities for sampling distributions. The most important probability model of all time. This will be fun for me to explain to you.
Construct and interpret confidence intervals for proportions and means. This will allow you to become an efficient decision-making machine. You will be able to interpret so well your grandma will understand.
Identify the basics of hypothesis testing and perform hypothesis testing for means, proportions and standard deviations from one population, and difference of means and proportions from two populations, including finding and interpreting p-value and examining Type I and Type II error.
Find linear least-squares regression equations for appropriate data sets, graph least- square regression equations on the scatter plot for the data sets, and find and apply the coefficient of correlation.
Use the chi-square distribution to test independence and to test goodness of fit.
Conduct a one-way Analysis of Variance (ANOVA) hypothesis test.
Select an appropriate hypothesis test and interpret the result using p-value; use ap- propriate statistical technique to analyze and interpret applications based on data related to business, social sciences, psychology, life sciences, health sciences or education, and interpret results using technology-based statistical analysis.
Course Learning Outcomes
- MATHM15 - Introductory Statistics
- • construct a single-sample confidence interval, and draw an appropriate conclusion. This can be done by hand, with a graphing calculator, or with statistical software.
- • construct a single-sample hypothesis test based on a given claim, and draw an appropriate conclusion. This can be done by hand, with a graphing calculator, or with statistical software.
Antiracist Assignment / Module
This module contains the course syllabus and class project. The project has students examine home prices within two different cities in Los Angeles, CA. Using statistics, they will collect data and run the appropriate hypothesis test. There will be a significant difference in average home prices. The students will further investigate the reason behind this and will learn that a root cause has to with race. They will learn about the history or redlining in the US and how it shaped Los Angeles today.