MATH 1000 Reasoning Using Mathematics
Instructor:
Office:
Phone:
Office hours:
Email:
Course Credit: 3 hours
Prerequisite: MATH 0101 or Placement
Textbook: To be determined by instructor but as an example:
“Using &Understanding Mathematics: A Quantitative Reasoning Approach”, sixth edition by Jeffrey Bennet and William Briggs.
On-line Software: To be determined by instructor but as an example:
Students will need to get a mymathlab account in order to access on-line homework assignments.
Graphing calculator: Students are required to have and be able to use a graphing calculator; a version of the TI-83 or the TI-84 is what the instructor will use.
Catalog Description: This course is designed to increase students’ quantitative and logical reasoning abilities and improve students’ ability to communicated mathematics. The course covers numeracy, statistics and probability, and modelling using mathematics.
Course Goals
Students who complete this course will be able to:
- Solve real world problems using percentages and ratios;
- Solve real world problems including units of measurements;
- Be proficient with scientific notation;
- Solve real world problems using rates of change
- Solve real world problems involving absolute change;
- Computing and using index numbers
- Understanding reliability of testing and interpreting the likely of certain occurrences based on test results
- Understand and solve financial problems involving compounding interests
- Solve mathematical problems related to income tax
- Evaluating basic statistical studies
- Recognizing statistical sampling techniques
- Understanding the difference between an experiment and an observation
- Understand different displays for data
- Understanding correlation and causality
- Understand and compute measures of center for data
- Measuring spread for data
- Computing five number summaries
- Formulating the null and alternative hypothesis for a statistical study
- Model real world problems using linear functions
- Model real world problems using exponential functions
Disability Statement: Any student who believes s/he may need an accommodation based on the impact of a documented disability should first contact a Coordinator in the Office of Disability Services, Student Success Center, Massie Hall, 740-351-3276 to schedule a meeting to identify potential reasonable accommodation(s). Students are strongly encouraged to initiate the accommodation process in the early part of the semester or as soon as the need is recognized. After meeting with the Coordinator, students are then required to meet with their instructors to discuss the student’s specific needs related to their disability. If a student does not make a timely request for disability accommodations and/or fails to meet with the Coordinator of Disability Services and the instructor, a reasonable accommodation might not be able to be provided.
Evaluation: To be determined by instructor, but as an example:
Test 1 19%
Test 2 19%
Homework 23%
Final Exam 39%
Final course grades will be based on the following scale:
92% to 100%....................... A
90% to 91%......................... A-
88% to 89%......................... B+
82% to 87%......................... B
80% to 81%......................... B-
78% to 79%......................... C+
72% to 77%......................... C
70% to 71%......................... C-
68% to 69%......................... D+
62% to 67%......................... D
60% to 61%......................... D-
Below 60%.......................... F
Attendance policy: Left to the instructor, but as an example:
Students are expected to attend class. You will be allowed to make up work with a valid university excuse.
Cell Phone and Other Electronic Devices Policy: Left to the instructor, but as an example:
Cell phones and personal computers are NOT permitted during class.
Course Outline
- Numeracy in terms of percentages, absolute change, relative change, and finances.
- Statistics in terms of understanding the basic components and pitfalls of a statistical study, familiarity with reading different displays for data, computing mean, median, mode, five number summaries, standard deviation, and formulating null and alternative hypothesis.
- Modeling in terms of using linear and exponential modelling with an understanding of slope, doubling time, half-life and predictions from models.