MATH 1100X  Everyday Mathematics With Extra Hours Credit Hours: 4.00 Prerequisites: Acceptable course recommendation/placement method
This course explores applications of mathematics used to solve modern problems. Topics include graph theory, introduction to statistics, linear regression, probability, voting systems, fair division and apportionment, identification numbers, encryption, patterns, and finance models. Same content as MATH1100, but class meets additional contact hours per week to allow more time to learn each concept in MATH1100. Credit may be earned in MATH1100 or MATH1100X, but not both. This course satisfies the requirements of the Michigan Transfer Agreement (MTA).
Billable Contact Hours: 5
Search for Sections Transfer Possibilities Michigan Transfer Network (MiTransfer)  Utilize this website to easily search how your credits transfer to colleges and universities. OUTCOMES AND OBJECTIVES Outcome 1: Upon completion of the course, students will be able to demonstrate a working knowledge of graph theory principles.
Objectives:
 Identify and model Euler circuit and Euler path problems.
 Define basic graph terminology.
 Use Euler’s Theorem to classify which graphs have Euler circuits and paths.
 Eulerize graphs when necessary.
 Identify and model Hamiltonian circuit and Hamiltonian path problems.
 Recognize complete graphs and state the number of possible Hamiltonian circuits using counting principles.
 Use brute force, nearestneighbor, and sortededges algorithms to find minimumcost solutions to traveling salesmen problems.
 Find minimumcost spanning trees using Kruskal’s algorithm.
 Resolve scheduling conflicts using the chromatic number and coloring.
Outcome 2: Upon completion of the course, students will be able collect and organize data into a table and construct appropriate charts and plots to display the data.
Objectives:
 Identify sampling methods.
 Identify experimental methods.
 Create and interpret a histogram.
 Create and interpret a stemplot.
 Create and interpret a boxplot.
Outcome 3: Upon completion of the course, students will be able to define, interpret, and calculate measures of central tendency.
Objectives:
 Find and interpret the shape, center, spread, and outliers of a histogram.
 Find and interpret the mean and median of a data set.
 Find and interpret quartiles.
 Find and interpret the standard deviation and variance from a data set.
 Find and interpret the spread of data of a normal distribution using 689599.7 Rule
Outcome 4: Upon completion of the course, students will be able to display and interpret linear relationships between two variables using regression.
Objectives:
 Create a scatterplot.
 Make a prediction using a regression line.
 Find the equation of the leastsquares regression line identifying slope, yintercept, and correlation with a scientific calculator.
 Interpret the correlation between two variables.
Outcome 5: Upon completion of the course, students will be able to compute basic probabilities and interpret probability models.
Objectives:
 Find and interpret the probability of events that are mutually exclusive.
 Find and interpret the probability of events using complements.
 Find and interpret the probability of events using counting methods.
Outcome 6: Upon completion of the course, students will be able to demonstrate a working knowledge of various voting systems.
Objectives:
 Implement the majority rule voting system and identify its advantages in a twocandidate voting system.
 Implement Condorcet’s Method.
 Implement the plurality, Borda count, sequential pairwise voting, contingent, and instant runoff voting systems for three or more candidates.
 Manipulate the plurality, Borda count, sequential pairwise voting, contingent, and instant runoff voting systems.
Outcome 7: Upon completion of the course, students will be able to use methods of division and apportionment to allocate resources fairly.
Objectives:
 Apply the adjusted winner procedure for divisible items.
 Apply the sealed bids method for indivisible items.
 Explain the basic apportionment problem.
 Implement the Hamilton Method.
Outcome 8: Upon completion of the course, students will be able to recognize various types of information located in identification numbers
Objectives:
 Identify the check digit on a traveler’s check, Universal Product Code, bank routing number, and International Standard Book Number and determine if the item is fraudulent.
 Identify the information contained in a UPC bar code.
 Identify personal data in a driver’s license number.
Outcome 9: Upon completion of the course, students will be able to decipher encrypted messages.
Objectives:
 Use Caesar cipher to decipher a message.
 Use Vigenère cipher to decipher a message.
 Solve a cryptogram by recognizing frequent letters and words.
Outcome 10: Upon completion of the course, students will be able to classify patterns.
Objectives:
 Generate the Fibonacci sequence and identify some of its properties.
 Identify relationships between the Fibonacci sequence and the golden ratio.
Outcome 11: Upon completion of the course, students will be able to use finance and population models.
Objectives:
 Apply simple interest formula to finance problems.
 Apply compound interest formula to finance problems.
COMMON DEGREE OUTCOMES (CDO) • Communication: The graduate can communicate effectively for the intended purpose and audience. • Critical Thinking: The graduate can make informed decisions after analyzing information or evidence related to the issue. • Global Literacy: The graduate can analyze human behavior or experiences through cultural, social, political, or economic perspectives. • Information Literacy: The graduate can responsibly use information gathered from a variety of formats in order to complete a task. • Quantitative Reasoning: The graduate can apply quantitative methods or evidence to solve problems or make judgments. • Scientific Literacy: The graduate can produce or interpret scientific information presented in a variety of formats.
CDO marked YES apply to this course: Critical Thinking: YES Information Literacy: YES Quantitative Reasoning: YES COURSE CONTENT OUTLINE
 Graph Theory
 Euler paths and circuits
 Euler’s Theorem
 Eulerize graphs
 Hamiltonian paths and circuits
 Use various algorithms to find minimumcost solutions
 Bruteforce
 Nearestneighbor
 Sortededges
 Kruskal’s algorithm
 Use chromatic number to resolve scheduling conflicts
 Describing and Interpreting Data
 Types of sampling methods
 Graphs
 Histogram
 Stemplot
 Boxplot
 Measures of center
 Measures of variance
 Linear Regression
 Scatterplot
 Correlation
 Predict using regression line
 LeastSquares regression line
 Probability
 Basic probability
 Counting
 Addition Rule
 Multiplication Rule
 Voting Systems
 Majority rule
 Condorcet’s Method
 Systems for 3 or more candidates
 Plurality
 Borda count
 Sequential pairwise voting
 Contingent
 Instant runoff
 Manipulation of voting system
 Division and Apportionment
 Adjusted winner procedure
 Sealed bids method
 Apportionment
 Basic apportionment problem
 Hamilton method
 Identification Numbers
 Check digits
 UPC bar codes
 Driver’s license numbers
 Encryption
 Caesar cipher
 Vigenère cipher
 Cryptograms
 Patterns and Symmetries
 Fibonacci sequence
 Golden ratio
 Finance and Population Models
 Simple interest
 Compound interest
Primary Faculty Miller, Faith Secondary Faculty Lusha, Elonia Associate Dean McMillen, Lisa Dean Pritchett, Marie
Official Course Syllabus  Macomb Community College, 14500 E 12 Mile Road, Warren, MI 48088
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