LSP 120 Quantitative Reasoning and Technological Literacy Section 202

Winter 2011

Özlem Elgün 

email  oelgun@depaul.edu
 office phone: (773) 325-4516

Office location: 990 W. Fullerton, Room 2217

Office hours: T, 11:00 am- Noon, 1:00- 2:00 pm, & by appointment

 

Course Web Page: http://qrc.depaul.edu

Course Time and Place: MW 9:40-11-10 am, SAC 224

Course Description:

In this course, students will study issues in the sciences, social sciences, and management in which quantitative data plays a significant role. A variety of analytical approaches will be explored, including numerical, graphical, verbal/logical, and algebraic. Extensive use will be made of computer tools such as Word, Excel, PowerPoint, and the Internet.

Course Objectives:

This course is designed to help you to become a more confident, critical, and capable user of quantitative information of all kinds. In particular, it will help you to

Required  Materials:

USB drive

Prerequisites:

ISP 110, Math 100, Math 101 or Placement through the advising process.

You can test out of this class by taking the LSP 120 Proficiency Exam. Take a look at this Study Guide. If you think you can pass the test please see Jennifer Galka in room 268 SAC to arrange it.

Course Format:

The course will be a mixture of lecture, discussion, cooperative group activities, and work on the computer. Classes almost always will take place in SAC 224. One goal of the first two weeks is for you to become comfortable with the Quantitative Reasoning Center's Windows computer environment and the tools to be found there. During the course you will learn to use many computer tools, among them

As with learning any other skill, mastering these will require practice during class time and afterwards. The Quantitative Reasoning Center will be open in the evening and on the weekend; tutors are on call  whenever the lab is open.  Another general purpose computer lab SAC 235,  located right around the corner from the Quantitative Reasoning Center,  has extended hours into evenings and the weekend.

Outline of Course (more details are below):

Week 1 Introduction to Mathematical Models and Linear Models
Week 2 Exponential Models
Week 3 Making and Interpreting Graphs
Week 4 Absolute and Relative Quantities
Week 5 Localized Trendlines; Midterm
Week 6 Percentages
Week 7 Module: The consumer price index and the value of money
Week 8 Financial Mathematics
Week 9 Financial Mathematics
Week 10 Presentations
Week 11 Final Exam

Evaluation:

  Date Weight
Final  March 14th, Monday, 8:45 - 11:00 am. 35%
Midterm To be announced 20%
Written Data Analysis Project Drafts due at various points 15%
Presentation of Project Last meeting of class 10%
Out of Class Assignments Usually due every week 10%
Attendance/Participation   10%

Note: A passing grade (>55%) on the final exam is required to pass the course.

An expanded description of each follows:

Grading:

Letter grades will be determined accordingly:

A (100- 94), A- (93.99-90), B+ (89.99-87), B (86.99-84), B- (83.99-80), C+ (79.99-77), C (76.99-74), C- (73.99-70), D+ (69.99-67), D (66.99-60), F (59.99 and below)

The final grade that you get for this class will not be rounded up under any circumstances. Students taking the course on a Pass/Fail basis must receive a grade of C or higher in order to pass. The final grade that you get for this class will not be rounded up under any circumstances. The grades are non-negotiable.

Incomplete Grades

Grades of Incomplete are given only in cases of medical emergency or other highly unusual emergency situations.   Please note that University guidelines require that you must be earning a passing grade at the time you request an incomplete grade. You should have completed most of the course, with at most one or two major forms of evaluation missing.  Incompletes revert to an F if they are not resolved within one quarter.   If such a situation should occur, please inform me as soon as possible.


Collaboration on out of class Assignments Policy:

I encourage you to work together when you are doing assignments.  However, the point of the out of class assignments is for you to get enough practice with the material and to engage with the ideas of the course in such a way that you will be to do well on the midterm and final exams.  Therefore, the write ups you submit to me should be entirely your own work and in your own words.   Sharing electronic files and cutting and pasting the work of another person and submitting it as your own work is a form of dishonesty (see below, under academic integrity).  

In short: it's ok to work together, but the work you submit should be your own work in your own words.
 

Academic Integrity:

Violations of academic integrity, particularly plagiarism, are not tolerated. Plagiarism is defined by the university as:

  “..a major form of academic dishonesty involving the presentation of the work of another as one's own. Plagiarism includes but is not limited to the following: 

a. The direct copying of any source, such as written and verbal material, computer files, audio disks, video programs or musical scores, whether published or unpublished, in whole or part, without proper acknowledgement that it is someone else's.

b. Copying of any source in whole or part with only minor changes in wording or syntax, even with acknowledgement.

c. Submitting as one's own work a report, examination paper, computer file, lab report or other assignment that has been prepared by someone else. This includes research papers purchased from any other person or agency.

d. The paraphrasing of another's work or ideas without proper acknowledgement.

Plagiarism, like other forms of academic dishonesty, is always a serious matter. If an instructor finds that a student has plagiarized, the appropriate penalty is at the instructor's discretion. Actions taken by the instructor do not preclude the college or the university from taking further punitive action including dismissal from the university” (DePaul Student Handbook).

 University policies on academic integrity will be strictly adhered to. Consult the DePaul University Student Handbook (http://studentaffairs.depaul.edu/handbook/ for further details.

Make-ups and Absences:

Make-up exams and extensions will be given only in extreme circumstances. If you know that you will be absent due to a school-related or religious reason, please inform me in advance. All absences are considered unexcused until you provide written documentation (e.g. note from student health). The documentation should be submitted within a week of the absence. Late assignments and activities will be deducted a full letter grade for each late day. The 24-hour period begins with the class session in which the assignment is due. It is in your best interest to turn your assignments in on time. Whether you are asking for an absence to be excused or requesting a make-up exam, you may submit the necessary documentation for your request directly to me. If you are uncomfortable sharing personal details with me, you can go to the Dean of Students Office (DSO), where you can fill out an absence notification form and ask the DSO to send me an email requesting flexibility in allowing an extension, a make-up exam, or an excused absence. The Dean of Students Office, it provides a variety of services for students dealing with personal, family or health challenges. You can learn more about the absence notification process and the DSO at: http://studentaffairs.depaul.edu

Disabilities:

Students with disabilities are encouraged to contact the instructor for a confidential discussion of their individual needs for academic accommodation. This meeting should take place early in the semester to ensure that you can receive the most appropriate and reasonable accommodation based on your needs. Please also make sure that you have contacted the following university resources for assistance:

            and/or

1677, located at the Student Center, #370 (http://studentaffairs.depaul.edu/studentswithdisabilities/index.html)

 

Classroom etiquette:

In order to create a classroom environment that is conducive to effective learning, and as a courtesy to your fellow students and to me, please make sure that your conduct does not distract others from the learning experience. The following behavior is considered highly distracting and disrespectful to the learning environment we are collectively aspiring to create:

Your participation in the class and your questions about the lecture and materials are the elements that are going to enhance the learning experience in this classroom. In order to optimize this experience, we need to maintain a respectful, thoughtful, and reflective tone in our conversations to ensure that there is space for a diverse group of opinions, questions, and answers. I expect all students to maintain an engaged attitude that is respectful to others.

 Classroom Resources

The class website: http://qrc.depaul.edu

I will be posting course materials on our class website regularly. All class notes, powerpoint presentations, assignments, in-class activities, information, and syllabus will be posted on this website.  

Instructor Contact

Most students attend office hours only immediately before assignments and exams are due or after grades are returned. These are the times when long lines form. I am very happy to answer questions about exams and assignments up until the due dates, but strongly encourage you to use office hours throughout the semester to discuss the course and your progress. It is important to me that this course enriches your educational experience. I hope that you will feel free to visit during my office hours whenever you think discussion on an individual basis would be helpful. Take responsibility for your learning and ask for individual attention when you need it. Scheduled office hours are listed above. You should feel free to make an appointment to meet with me if these times are inconvenient.   

More Detailed Description of Course Contents

Week 1: Introduction to Mathematical Modeling and Linear Models in particular

Mathematical modeling is a collection of mathematical techniques to facilitate predictions for planning or simulation purposes.  The basic approach is to take existing data and fit a mathematical object (an equation, graph, shape, algorithm) to the data.  If the data fits reasonably well, one can make predictions in between existing data points (interpolations) or beyond the existing data (extrapolations).  Confidence in predictions is tempered by the goodness of fit of the model and by how one is away from existing data.  Generally, the farther one is from existing data, the less confidence one has in predictions.  This week introduces the general concept of modeling, reviews linear functions, and covers linear models.  Excel is used to add trendlines, get their equations, and use them to make predictions. You are introduced to the R-squared value as a measure of goodness of fit.

Week 2: Exponential Modeling

You are introduced to exponential functions as functions characterized by having a constant multiplicative growth or decay.  The formula  Y
  = P(1±r)x describes a general exponential function.  They arise most commonly in situations when a quantity is growing by a fixed percentage r over each unit of time.  This week you learn how to model with exponential functions in wide variety of contexts: population growth, radioactive decay, metabolism of drugs. We will also talk about logarithms and their relationship to exponential functions.

Week 3: Making and Interpreting Graphs

Graphs are an extremely powerful and useful way of presenting and analyzing quantitative information.  The week's focus is on learning how to make three types of graphs in Excel: pie charts, bar charts (including multiple bar charts), and XY-graphs.  You learn when each type of graph is appropriate, how to describe and interpret each type of graph, and how to critique misleading graphs from the media. 

Week 4: Absolute and Relative Quantities

Absolute quantities refer generally to raw numbers and counts; relative quantities are usually ratios of absolute quantities that normalize absolute quantities for comparison.  Examples of relative quantities are rates and percentages.  This week focuses on the distinction between these two kinds of quantities, especially the importance of relative quantities. 

Week 5: Localized Trendlines

We will will revisit trendlines and specifically learn how to identify localized trends.  As part of this topic, we will also learn how to animate graphs in PowerPoint.

Week 6: Percentages

We will look at the use of percentages in quantitative work.  You are expected to master five types of percentage problems that arise in everyday quantitative work:  percentage as part of a whole problems, percent change, "percent more than" problems, successive percent change problems, and reverse percentage change problems.

Week 7: Module on the consumer price index and the value of money

This we apply what we learned to an interdisciplinary topic coming from economics, the consumer price index.  You learn the motivation and history of the consumer price index.  You learn how it calculated and how to use it in order to compare prices in different years.  The week concludes with an interesting public policy application of the ideas to the issue of the US minimum wage.

Week 8 and 9: Financial Mathematics

You will use Excel to analyze savings accounts, annuities, ordinary amortized loans, and credit card loans. You will be introduced to the concept of annual percent yield, a quantity that allows you to compare savings accounts and loans with different terms. Often you will be asked to compare different terms and evaluate which might be more advantageous in certain settings.

Week 10: Presentations

Week 10 is dominated by the presentation of your group project analyses.  There will be materials and help available to review for the final exam.

 

 


The instructor reserves the right to change the contents of this syllabus at any time. You will be notified about any changes to the syllabus immediately, and the updated syllabus will be available on the class website.