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NOTE: The following information was taken from the Spring 2000 Math 114 course syllabus. It is intended to serve as a reference only. This material may change from semester to semester.
Text:
Understanding Basic Statistics
by Brase
Houghton Mifflin, Second Edition
ISBN: 0-618-054707

College Algebra Concepts & Models
by Larson, Hostetler, Hodgkins
Houghton Mifflin, 3rd Edition
ISBN: 0-395-976219

Note: A TI-82 or TI-83 graphing calculator is required in this course.

Course Content:
This course is designed for liberal arts majors who do not expect to take additional math courses. For approximately the first five weeks we will discuss statistical topics such as mean, median and mode, the bell-shaped curve and confidence intervals. The purpose of this unit is to help you view statistics that you come in contact with, in newspapers or television, with understanding and a more critical eye.

The second part of this course will include an algebra review. The emphasis will be on mathematical modeling of data and on applications. Some of the applications to be covered are profit, supply and demand, and linear programming. For a strong visual image, graphing of functions and reading and interpreting graphs will be stressed throughout the course.

Grades:
Grades will be based on 550 points:
300 points for the exams (3 exams each for 100 points)
150 points for the final exam
100 points for other work and activities
Sample Exams:
Sample exams require the free Acrobat Reader software installed
  Exam 1 Solutions Exam 1
  Exam 2 Solutions Exam 2
  Exam 3 Solutions Exam 3
  Final Exam Solutions Final Exam
Topics Covered: During Spring 2000 (Old Textbook)
Topic
What is Statistics
Basic Terms
Variability
Data Collection
Circle and Bar Graphs
Stem and Leaf Displays
Frequency Distribution and Histograms
Measures of Central Tendency
Measures of Dispersion
Mean and Standard Deviation of
Frequency Distributions
Interpretation and Understanding Standard
Deviation (not Chebyshev's Theorem)
The Art of Statistical Deception
The Standard Normal Distribution
Applications of Normal Distribution
The Central Limit Theorem
Applications of the Central Limit Theorem
The Nature of Estimation
Estimation of Mean
Bivariate Data - Two Quantitative Variables Only
Linear Correlation
Linear Regression
Linear Equations
Graphing
Equations of Lines
Profit/Revenue, Supply/Demand and Cost Applications
Systems of Equations
Functions
Inequalities in One Variable
Inequalities in Two Variables
Linear Programming
Quadratic Equations
Quadratic Functions
Business Applications of Quadratic Functions
Quadratic Modeling
Exponential Functions
Logarithmic Functions
Applications of Exponential and Logarithmic Functions
Exponential Modeling
Compound Interest

©2004, Department of Mathematical Sciences
Last Modified: October 13, 2004
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