Discipline: Mathematics
Originator: Rogelio Ruiz

Riverside Community College District
Integrated Course Outline of Record

Mathematics 37
MAT-37 : Pre-Statistics
College:
Lecture Hours: 72.000
Lab Hours: 54.000
Outside-of-Class Hours: 144.000
Units: 5.00
Grading Methods: Pass/No Pass
Letter Grade
Course Description
Prerequisite: MAT-65 or qualifying placement level
Course Credit Recommendation: Non-Degree Credit

This is an intensive course that prepares students for transfer-level Statistics. Topics include working with numerical information(fractions,decimals, percentages), evaluating expressions related to statistical formulas, graphical and numerical descriptive statistics for quantitative and categorical data. Two-way tables, linear correlation and regression and an introduction to normal distribution. There is a focus on reading, writing, and critical thinking skills needed for college statistics. This course is appropriate for students who do not plan to major in math, science, computer science, business, technology, engineering and calculus intense fields in the social sciences. 72 hours lecture and 54 hours lab. Letter grade or pass/no pass option.
Short Description for Class Schedule
Math 37 prepares the student for college-level Statistics (Math 12). In Math 37 the student will work on projects and collaborative activities that develop math skills, as well as reading, writing and critical thinking skills. This course is for students who DO NOT plan to major in math, science, computer science, business, technology, engineering and calculus intense fields in the social sciences.
Entrance Skills:
Before entering the course, students should be able to demonstrate the following skills:
  1. Apply the four basic operations to integers and rational numbers.
    • MAT-65 - Apply the principles of arithmetic on whole numbers, fractions, mixed numbers, and decimals without the use of any calculating device.
  2. Solve applications using ratios, proportions and percents.
    • MAT-65 - Apply percents to real world problems.
    • MAT-65 - Solve applications using whole numbers, integers, fractions, mixed numbers, ratios and proportions, and decimals.
  3. Apply the fundamental properties of algebra to simplify basic algebraic expressions.
    • MAT-65 - Apply the fundamental laws of algebra to evaluate and/or simplify basic algebraic expressions and perform the four basic operations on polynomial expressions.
  4. Solve basic linear equations.
    • MAT-65 - Solve multi-step linear equations and derive basic linear equations from elementary applications.
  5. Communicate mathematical concepts using the vocabulary of algebra.
    • MAT-65 - Use the symbols and vocabulary of arithmetic and pre-algebra to communicate mathematical concepts.
Student Learning Outcomes:
Upon successful completion of the course, students should be able to demonstrate the following skills:
  1. Produce a coherent and well-reasoned descriptive analysis of data, based on numerical and graphical representations, to answer a research question.
    • Communication Skills: Students will be able to communicate effectively in diverse situations. They will be able to create, express, and interpret meaning in oral, visual, and written forms. They will also be able to demonstrate quantitative literacy and the ability to use graphical, symbolic, and numerical methods to analyze, organize, and interpret data.
  2. Distinguish between observational studies and experiments and identify studies for which a cause-and-affect conclusion is appropriate.
    • Critical Thinking: Students will be able to demonstrate higher-order thinking skills about issues, problems, and explanations for which multiple solutions are possible. Students will be able to explore problems and, where possible, solve them. Students will be able to develop, test, and evaluate rival hypotheses. Students will be able to construct sound arguments and evaluate the arguments of others.
  3. Demonstrate numerical, algebraic, and geometric reasoning skills to support statistical analysis.
    • Communication Skills: Students will be able to communicate effectively in diverse situations. They will be able to create, express, and interpret meaning in oral, visual, and written forms. They will also be able to demonstrate quantitative literacy and the ability to use graphical, symbolic, and numerical methods to analyze, organize, and interpret data.
  4. Construct, use, and interpret mathematical models, specifically linear models to represent relationships in quantitative data and normal probability models to identify unusual events for a quantitative variable.
    • Communication Skills: Students will be able to communicate effectively in diverse situations. They will be able to create, express, and interpret meaning in oral, visual, and written forms. They will also be able to demonstrate quantitative literacy and the ability to use graphical, symbolic, and numerical methods to analyze, organize, and interpret data.
  5. Use effective learning strategies for success in college.
    • Self-Development & Global Awareness: Students will be able to develop goals and devise strategies for personal development and well-being. They will be able to demonstrate an understanding of what it means to be an ethical human being and an effective citizen in their awareness of diversity and various cultural viewpoints.
Course Content:
  1. Performing Operations 
    1. Ratios, Proportions and Percents
    2. Converting Units
    3. Exponents, Square Roots and Order of Operations
    4. Scientific Notation
  2. Designing Observations Studies and Experiments
    1. Simple Random Sampling
    2. Systematic, Stratified and Cluster Sampling     
  3. Graphical Tabular Displays of Data
    1. Types of Data
    2. Frequency Tables, Relative Frequency Tables, Bar Graphs
    3. Pie Charts, Two -Way Tables
    4. Dotplots and Stemplots
    5. Histograms
  4. Measures of Central Tendency
    1. Mean, Median, Mode
    2. Distribution shapes
  5. Measures of Variation
    1. Range
    2. Variance and Standard Deviation
    3. Empirical Rule
  6. Measure of Relative Position
    1. z-Scores 
    2. Percentiles and Quartiles
    3. Boxplots
  7. Computing Probabilities
    1. Introducing Probability
    2. Complement and Addition Rules
    3. Conditional Probability and the Multiplication Rule
  8. The Normal Distribution
    1. Finding Areas Under the Normal Distribution Curve
    2. Interpreting area as probabilities
    3. Application of the Normal Distribution
  9. Graphing Linear Equations and Linear Models
    1. Graphing Equations of Lines
    2. Rate of Change and Slope of a Line
    3. Slope-Intercept Form
    4. Writing Equations of Lines
    5. Linear Models
  10. Solving Linear Equations in One Variable
    1. Solving Formulas
    2. Solving Linear Inequalities in One Variable
    3.  Solving Linear Equations and Inequalities
  11. Correlation and Regression
    1. Scatterplots and Correlation
    2. Correlation Coefficient
    3. The Regression Line
    4. Predictions and Residuals
    5. Linear Regression Models
    6. Exponential Models
Methods of Instruction:
Methods of instruction used to achieve student learning outcomes may include, but are not limited to, the following activities:
  • Class lectures, discussions, and demonstrations to introduce concepts, such as mathematical models and relationships, as well as providing "just in time" instruction on topics such as demonstrating numerical and algebraic reasoning skills to support statistical analysis. 
  • Use of computer-based tools to effectively find sources of data, and to analyze data and construct graphs.
  • Provision and employment of a variety of media (audio, visual, and tactile) to address multiple learning styles and to reinforce material.
  • Collaborative learning methods will be employed to promote statistical exploration and to enhance problem solving skills.
Methods of Evaluation:
Students will be evaluated for progress in and/or mastery of student learning outcomes using methods of evaluation which may include, but are not limited to, the following activities:
  • Evaluation of written homework assignments and/or computerized homework assignments for correct application of statistical concepts as well as the correct useage of graphs and vocabulary.
  • Evaluation of quizzes, tests, and a final exam for conceptual understanding and correct technique in the application of statistical, algebraic, and arithmetic principles (e.g.,  interpretation and construction of charts and graphs; evaluation of algebraic expressions, and use of percents and fractions).
  • Assessment of classroom explorative and collaborative activities for content knowledge and conceptual understanding.
Sample Assignments:
Outside-of-Class Reading Assignments
  • Read and analyze textual material from a variety of sources, including newspapers or journals covering data collection, data analysis, study designs, and interpretations of data.
Outside-of-Class Writing Assignments
  • Students will write summaries that  describe various data sets, show organizations of data, and communicate the results of data analysis.
Other Outside-of-Class Assignments
  • Students will be given homework assignments that address arithmetic/algebraic concepts necessary for statistical computations, e.g., fractions, decimals, percentages, order of operations, and solving equations.  Projects will be assigned that require students to formulate questions that can be addressed with data, and then collect, organize, display, and analyze the data to address their questions.  Projects will show whether students can apply the basic principles of study design and construct, use, and interpret mathematical models to represent relationships in quantitative data.
Course Materials:
All materials used in this course will be periodically reviewed to ensure that they are appropriate for college level instruction. Possible texts include the following:
  • Bennett, Briggs and Triola. Statistics Reasoning For Every Day Life. 4th Pearson Education, Inc., 2014.
  • Lehmann. A Pathway to Introductory Statistics. 1st Pearson Education, Inc., 2016.
  • StatCrunch. Software. 1st. Pearson,
  • Minitab. Software. 18. Minitab, Inc.,
Codes/Dates:
CB03 TOP Code: 1701.00 - Mathematics, General
CB05 MOV Transfer Status: Non-Transferable (C)
CB05 NOR Transfer Status: Non-Transferable (C)
CB05 RIV Transfer Status: Non-Transferable (C)
Board of Trustees Approval Date: 11/13/2018
COR Rev Date: 11/13/2018