MATH242: ALGEBRA II FOR STATISTICS
Course Description
Math 242 is for students whose educational plan includes ONLY Math 5 (Freshman-level Statistics). If your major is math, science, engineering, computer science, business, etc., and/or your educational plan includes any college-level math class other than Math 5, or you are unsure about your major, you should take Math 240. Math 240 and Math 242 are not equivalent. Math 242 prepares students for Freshman-level Statistics (Math 5) by covering core concepts from Algebra II and statistics that are needed to understand the basics of college level statistics. Topics include functions, inequalities, radicals, exponential and logarithmic functions, exploratory analysis of categorical, quantitative, single variable and bivariate data, and probability. PREREQUISITE: Math 430 with a C or better, or Math 205 with a C or better, or Math 205A and Math 205B with a C or better, or by placement recommendation.
Learning Outcomes
- Solve absolute value equations and inequalities. Analyze and solve linear, radical, exponential, and logarithmic equations. Set up equations in all of the above to solve application problems. Graph linear, logarithmic, and exponential functions and be able to utilize the graphs in problem solving
- Given a graph, equation or list, identify domain, range, points on the graph and whether a graph depicts a function. Given a function, find it's inverse.
- Simplify and perform operations with radical, logarithmic and exponential expressions, and solve radical, logarithmic and exponential equations.
- Demonstrate proficiency for calculation of probabilities, including marginal and conditional probabilities.
- Describe and analyze data using descriptive statistics including histograms, frequency tables, stem-and-leaf diagrams, box plots, mean, median, mode, and standard deviation, with and without technology.
- Formulate questions that can be addressed with data, then organize, display and analyze the relevant data to address these questions and communicate the results.
- Investigate relationships in bivariate quantitative data and determine an appropriate mathematical model for that data. Using technology, compute the appropriate regression model, assess the validity of that model, and communicate findings;