LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE

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1 LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE MAT 119 STATISTICS AND ELEMENTARY ALGEBRA 5 Lecture Hours, 2 Lab Hours, 3 Credits Pre- Requisite: MAT 095 or placement in MAT096 CATALOG DESCRIPTION This is a statistics course with algebra support using the Statway curriculum. The focus is on statistics (data collection, numerical and graphical representation of data, linear correlation and regression, discrete and continuous probability distributions, estimation, and hypothesis testing); relevant algebra topics such as fractions, percent, linear equations in one and two variables and functional relationships are integrated, resulting in a collaborative, problem- based class. PURPOSES AND GOALS This course covers the curriculum of a 3- credit elementary statistics course with sufficient developmental mathematics to insure success. Two lab hours and two additional classroom hours are required for this. The purpose of this course is to reduce into one semester the sequence of courses leading to a credit- bearing Math course. In addition, the students will be exposed to productive persistence to deepen learning and understanding the topics of the course. This learning opportunity is present in each lesson of the semester, where students work in groups and experience this teaching model. INSTRUCTION OBJECTIVES 1. Enable students to create social ties with peers and instructors using the "Productive Persistence" and "Starting Strong" packages, sets of evidence- based activities developed and tested to increase student success and retention. 2. Introduce students to the fundamental questions that arise in a statistical study. 3. Familiarize students with the design of statistical studies, introducing them to the issues of population identification, sample selection and bias. 4. Provide students with qualitative and quantitative descriptions of data distributions in graphical and numerical formats. 5. Provide students with the skills needed to construct graphs from linear and nonlinear equations and, conversely, determine equations from graphs of straight lines. 6. Introduce students to bivariate data to identify correlations, causations and regressions; in order to make predictions. 7. Introduce students to the basic concepts of probability, the law of large numbers, probability rules, and two- way tables. 8. Familiarize students with the binomial, normal, and Student t- distributions, and the Central Limit Theorem. 9. Provide students with the method of estimating a population mean, and enable them to conduct hypothesis testing.

2 PERFORMANCE OBJECTIVES 1. Demonstrate the ability to work effectively in groups, discussions, and class activities. 2. Compare and contrast observational and experimental statistical studies and describe the conclusions that can be drawn from each. 3. Conduct statistical studies, calculate descriptive statistics, and identify hypotheses. 4. Create, compute, and interpret graphical and numerical summaries of data distributions. 5. Appreciate the interplay of algebra and geometry in the graphical representation of linear and non- linear systems. 6. Compute, analyze and describe the results of linear correlation, causation and regression presented in output data from a statistical package. 7. Compute probabilities using relative frequencies, proportions and basic rules. 8. Compute probabilities and confidence intervals in order to estimate population parameters from sample data. 9. Appropriately use normal or Student t- distributions to estimate the population mean; and formulate and conduct hypothesis tests. REQUIRED MATERIALS Each student is required to have the textbook and online platform for the course (available at All reading (most homework assignments) and all testing will take place on this online platform. Additional materials are available to download at the course website. Each student is expected to know his or her login details for the CUNY Portal to be able to access the Blackboard page for the course. WORKBOOK Statway: A Pathway Through College Statistics. Carnegie s NIC. Version 2.9 (2015) EVALUATION The purpose of a grading system is to give you and anyone else reading your transcript an accurate record of your performance in this course. The role of the MEC Department is to provide a fair, valid, and reliable structure for assessing your achievement. MAT119 is an intensive course and all the work you complete in- class group work, at home on paper, and in the online platform counts towards your final grade. In- class group work (Workbook lessons) 1 Collaborative Assignments Computer lab work Take- it- home assignments (on paper) 10% Online (or Out- of- classroom) Online Activities Activity Depository Essay 6 End- of- module Checkpoints 1 Midterm Final Exam TOTAL 20% 2 100% PASSING GRADE POLICY IN ORDER TO PASS THIS COURSE, YOU MUST HAVE AN AVERAGE TOTAL SCORE OF AT LEAST 60% AS FINAL GRADE AND NO MORE THAN 10 HOURS OF UNEXCUSED ABSENCES.

3 Take advantage of the opportunity to earn grade from your work and effort during the term. EXPLANATION OF GRADING CATEGORIES Collaborative Assignments: Class work following the Statway: A Pathway Through College Statistics workbook is collected for review and grading. The student handout is mostly completed in- class by groups. Computer lab work is the use Statistical technology. Online (or Out- of- classroom) Activity: Activities are assigned using the online platform to be completed (in or out- of- class) following step- by- step instructions to help understanding and to support learning of class concepts. Take- it- homes assignments found the end of the workbook lessons. Depository Essay for the course assigned to all sections of MAT End- of- Module Checkpoints: These short online checkpoints assess your learning at the end of each Statway module and are to be completed during computer lab hour. Midterm: Assessment for the first half of the course. Final Exam: Cumulative Exam covering all course topics. ATTENDANCE The nature of the Statway program requires student to work in groups during for a significant amount of the class time. The learning process depends heavily upon you taking the opportunity to discuss and work with others, and find different ways to solve a problem. Students are expected to attend all class meetings, especially because the in- class work is an integral part of the course. Students are responsible for all information, material, and assignments covered in class regardless of class attendance. Students should consult the college catalog to find out the terms and conditions under which a WU, and incomplete, or an F grade may be given by an instructor. ACADEMIC INTEGRITY This class will be conducted in compliance with LaGuardia Community College s academic integrity policy. COURSE OUTLINE The Module title is the main topic of Statistics covered in the Statway workbook. The column labeled Time list the suggested number of hours (60 min) to spend in class to cover the corresponding lesson. The Lesson Title corresponds to the number and title of a lesson in the Statway workbook. The column labeled Basic Skills lists the minimal mathematics basic skills required for you to be successful in this Elementary Statistics course and in subsequent college math courses in addition to basic writing and reading comprehension skills. Your instructor will provide you with additional support, tools, and resources to acquire and deliberately practice these skills.

4 Topic Time (h) Lesson Title Required Math Background Module 2 Module 1 Types of Statistical Data and Producing Data Summarizing Data Graphically and Numerically Week 3 Week 2 Week Setting Course Expectations The Statistical Analysis Process Mindset Activity and Populations and Samples Research Questions and Statistical Studies - Part 1 2 Computer Lab Getting pathways.carnegiehub.org Research Questions and Statistical Studies - Part Random Sampling Dotplots, Histograms, and Distribution Shapes Constructing Histograms for Quantitative Data 1 Review Module 1 - Checkpoint Module 1 Practice 1: Arithmetic Readiness. Number sets. Number line and graphing. Practice 2: Proportions, percent, ratios, and fractions. Coordinate plane Quantifying the Center of a Distribution Practice 3: Order of Quantifying Variability Relative to the Median operations, exponents and Quantifying Variability Relative to the Mean radicals (2nd order), distance. Module 3 Module 12 Mathematical and Statistical Linear Models Examining Relations: Quantitative Data Week 7 Week 6 Week 5 Week Statistical and Exact Mathematical Models Mathematical Linear Models Proportional Models 1 Review Module 2 - Checkpoint Module Answering Questions Algebraically Solving Inequalities Scatterplots and Bivariate Relationships Form, Direction, and Strength of a Relationship Correlation Coefficient and Its Properties Using Lines to Make a Prediction Least Squares Regression Line as Line of Best Fit Slope and Y- intercept of Least Squares Lines Properties of the Least Squares Regression Line Using Residuals to Determine Line Good Fit 1 Review Module 12 & 3 and Midterm 1 Review Midterm 1 Midterm Part 1 Checkpoint Module 12 & 3 Practice 4: Evaluating functions, translating phrases, linear equations. Practice 5: Inequalities, solving linear inequalities. Pattern recognition, graphing linear equations. Practice 6: Slope and intercept, units and rates. Practice 7: Concept of error. Fraction comparison and rates.

5 - Midterm Part An Introduction to Two- Way Tables Module 5 Relationship in Categorical Data, Probability Week Marginal, Joint, and Conditional Probabilities Building Two- Way Tables to Calculate Probability 1 Review Module 5 - Checkpoint Module 5 Practice 8: Venn diagrams, counting, ratios and proportions. Module 6 Module 10 Probability and Probability Distributions Statistical Inference for Means Week 12 Week 11 Week 10 Week Law of Large Numbers Practice 9: Concept Probability Rules of limits, inequalities review. Summation Discrete Probability Distributions notation. Area concept. Exponents Binomial Experiment and Distribution Continuous Probability Distributions Z- Scores and Normal Distributions Find Normal Probabilities and Critical Values Sampling Distribution of Sample Means Central Limit Theorem for Sample Means The T- Distribution and T- Statistics 1 Review Module 6 - Checkpoint Module 6 Practice 10: Concept of curve and area. Function and inverse function. Practice 11: Concept of curve and area. Reading comprehension. Communication quantitative evidence. Notation Confidence Intervals for a Population Mean Practice 12: Reading Hypothesis Tests for Population Means comprehension. 1 Review Module 10 Communication quantitative - Checkpoint Module 10 evidence. Review hypothesis rationale.

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