Syllabus: Introduction to Statistics
Course: Math 2400 (3 hours)
Instructor: Robb Sinn
Office: NOC 221
Phone: 706-864-1676
Email: rsinn@ngcsu.edu
Textbook: All students are required to purchase the e-book version of
Prerequisite: Three hours of college mathematics. A student will not be allowed credit for MATH 2400 after completing MATH 3300 with a grade of "C" or above.
Catalog Description: A noncalculus introduction to descriptive and inferential statistics. Topics include graphical and numerical methods of describing data, hypothesis testing, linear regression and correlation, the normal distribution, and estimation.
Course Objectives: After completion of the course the student will be able to:
· Distinguish the use of descriptive statistics from the use of inferential statistics.
· Distinguish qualitative data from quantitative data.
· Construct a frequency distribution and relative frequency distribution for a given set of data.
· Construct a histogram polygon for a given set of data.
· Compute and provide a qualitative interpretation for the mode, median, and mean of a given set of data.
· Compute and provide a qualitative interpretation for the range and standard deviation of a given set of data.
· Find the proportion of data between two given values for a normal distribution.
· Find the value of a given percentile for a normal distribution.
· Compare scores from two different normal distributions using standard scores.
· Construct a scatterplot for a given set of paired data.
· Compute and provide a qualitative interpretation for the correlation coefficient of a given set of paired data.
· Compute the slope and Y-intercept of the least squares prediction line and use the equation for the least squares prediction line to predict the value of one variable from the value of the other.
· Compute and provide a qualitative interpretation for the standard error of prediction of a given set of paired data.
· Provide a strategy for collecting a random sample from a given population.
· Compute and provide a qualitative interpretation for the mean of all sample means and the standard error of the mean for a given population and sample size.
· Perform the six steps of hypothesis testing for a z-test, t-test, t-test for two independent samples, and t-test for two matched samples.
· Distinguish Type I errors from Type II errors and provide a strategy for minimizing the chance of one or the other occurring.
· Find and provide a qualitative interpretation for a confidence interval.
· Perform the six steps of hypothesis testing for a chi-square test.
· Determine the appropriate hypothesis test to use in a given situation.
Grading: There are 4 components of the students’
course average: test average on 2 in-class exams, (35%), two projects (30%),
final exam (20%) and HW/Quiz/Participation (15%). Participation is expected and
includes (among other things) class attendance, completing the online Homework
problems, bringing the required calculator to class
each day, staying awake, attempting the I-Clicker questions and joining class
discussions. No test scores are dropped, but a test score may be replaced
with the exam grade if this improves the students’ overall average.
Grading Scale (No rounding up!):
A 90% -
B 80% - 89%
C 70% - 79%
D 60% - 69%
Best Contact: Email is by far the best way to reach me. I check my email almost hourly, even when away from work. You may call (706-864-1676) during office hours or leave a message with the department secretary any time between 8 am and 5 pm, Monday - Friday. I do give out my home phone and/or cell number, but I don’t post them on the internet (intentionally).
Office Hours. Tues/Thurs 9 - 11 AM, Mon 10 - 11 AM, Wed 2 - 3 PM
Methods of Instruction: The methods of instruction are determined by the instructor; however, the instructor is expected to use a variety of methods. These methods may include, but are not limited to lecture; problem-solving sessions with informal assessment by the student or instructor; discussion; group projects; timely feedback from test, quiz, or project results (formative assessment); question and answer; computer or calculator based explorations; and student presentations. Students will be encouraged to assess and monitor their own problem-solving process to determine when an error has been made or a new strategy should be used.
Metacognitive Model and Teacher Education Program
Competencies:
The NGCSU Secondary Mathematics Education Program prepares teachers to assume within the school community the roles of Decision-Maker, Facilitator, and Leader as identified in the metacognitive model. Twelve Teacher Education Program competencies reflecting the model are aligned to a specific role. Overlap into more than one role and mathematics course may occur. Current research and professional standards identify these competencies as important for effective teaching (NBPTS and ASCD Framework).
|
Decision-Maker |
Facilitator |
Leader |
|
Assessment |
Individual Differences |
Ethical Perspectives |
|
Planning |
Subject Matter Knowledge |
Reflection/Metacognition |
|
Problem Solver |
Communication |
Professional Leadership |
|
Methods, Materials, Resources |
Classroom Management |
Research & Evaluation |
Evaluation Methods: Formative assessment will be in the form of written tests and/or short quizzes and summative assessment will be in the form of a final examination. Special projects and daily grades may be used at the discretion of the instructor.
Course Content:
1. Graphical and numerical methods of describing data.
2. The normal distribution.
3. Correlation and linear regression.
4. Hypothesis testing.
5. Estimation.
Knowledge Base:
1. Required Text: StatsPortal E-book (Moore, David S., The Basic Practice of Statistics, 4th edition, W. H. Freeman, NY, 2006.) Purchase access card at NGCSU bookstore or online. See course instructor for details.
2. Supplemental
Text:
2006.
3. Library Resources:
·
·
G. Kanji, 100 Statistical Tests, Sage,
·
J. Stevens, Intermediate Statistics: A Modern
Approach,
·
J. Stevens, Applied Multivariate Statistics
for the Social Sciences,
·
R. Mason, Statistical
Design and Analysis of Experiments, Wiley,
·
C. Cox, A
Handbook of Introductory Statistical Methods, Wiley,
·
D. Fraser, Probability
and Statistics: Theory and Applications, Duxbury Press,
·
J. Hodges, Jr. and E. Lehmann, Basic Concepts of Probability and Statistics,
Holden-Day,
· She Does Math! (Marla Parker, Ed., The Mathematical Association of America, 1995)
· Women and Science Celebrating Achievements Charting Challenges (National Science Foundation, 1997)
4. World Wide Web Resources:
·
SurfStat
·
HyperStat OnLine Textbook - davidmlane.com/hyperstat/index.html
·
Globally Accessible Statistical Procedures - http://www.stat.sc.edu/rsrch/gasp/
·
Statistics on the Web - http://www.execpc.com/~helberg/statistics.html
·
Association for Women
in Mathematics - www.awm-math.org
·
·
Eric Weisstein’s World
of Mathematics (Encyclopedia of Mathematics) - mathworld.wolfram.com
·
TEAMS Mathematics
Resources - teams.lacoe.edu/documentation/places/math.html
·
Math Nerds – www.mathnerds.com
·
SOS Mathematics – www.sosmath.com
·
Intermath – www.intermath-uga.gatech.edu/
·
Women in Mathematics -
www.agnesscott.edu/lriddle/women/women.htm
5. Technology Resources:
· A graphing calculator such as the TI-84 Plus
· Software: Microsoft Excel
· A graphing calculator such as a TI-83 or TI-84 is a required and essential learning tool for this course. You should purchase or borrow one of these exact models. The book’s calculator-based examples use it, and in-class demonstrations will use a TI-83 Plus with projector screen. Students should also have access to and be familiar with Microsoft Excel. Excel spreadsheets will be a major part of the projects. Students should be able to access the instructor’s web page without difficulty (radar.ngcsu.edu/~rsinn) and the StatsPortal to retrieve online resources.
General Expectations: The student is expected to abide by the university's attendance policy and integrity code. Other general expectations may be given by the instructor.
Make-Up Work. No late assignments are accepted. Make-up tests and quizzes will not be allowed. The lowest quiz grade is dropped, but no additional quizzes will be dropped no matter the circumstances. If a student misses a test and has a valid, properly-documented reason, the exam grade may count in place of that test score.
Attendance
Policy. Attendance each day in class is mandatory. If a student
misses 4 or more class meetings without valid, extreme circumstances
documented, he or she will be withdrawn from the class and assigned a grade of
WF. If you must miss class for any reason, please notify me (rsinn@ngcsu.edu)
before the absence. If an emergency arises, please notify me as
quickly as is reasonably possible. Tardiness is not acceptable.
Students who show up to class several minutes late may be marked absent for the
period. There is a perfect attendance bonus of 2% added to the final
semester average. Students who miss no more than 1 class session will
have a 1% bonus added. Students with
perfect attendance or A’s on all in-class tests may exempt the final exam. The final exam grade of students with perfect
attendance will not lower the overall average, even if they do poorly.
Early Alert/Early Intervention Policy: NGCSU has implemented this new program. I will refer you to other persons/services at the university designed to help you achieve your academic goals. You will be expected to take advantage of the help offered to you.
Class Evaluations: Class evaluations at NGCSU are now conducted on-line through Banner. Evaluation of the class is considered a component of the course and students will not be permitted to access their course grade until the evaluation has been completed. The evaluations will be accessible beginning one week prior to Final Exam week.
Disabilities and Accommodations.