STT 290 – Data, Probability and Statistics for K-8 Teachers

MW 3:00 - 4:20 C108 Wells Hall

Syllabus - Spring 2009

Instructor: Professor Jennifer Kaplan Office: WH 443

Phone: 432-2354 (office) WWW: http://www.angel.msu.edu

Office Hours: TBD E-Mail: kaplan@stt.msu.edu

Text: Statistics: Concepts and Controversies, Seventh Edition, 2009, David S. Moore and William I. Notz, W.H. Freeman and Co., Publishers

Prerequisite: MTH 103 or designated score on mathematics placement test

Objectives: Students will develop a comfort level with data collection, data analysis, probability and statistics that will allow them to be effective in the classroom and competent in handling the statistical issues that they encounter in their professional and personal lives. Students will have mathematical skills reinforced and will develop an understanding of statistical thinking. Students will learn to use technology as an aid for understanding data, probability and statistics and for instruction.

Relevance: Probability and data analysis are now taught and tested in elementary school in Michigan and most other states. Furthermore, knowledge of statistical methods is essential for teaching science and social studies, where critical analysis of data is crucial. Future teachers need to be prepared to teach this content. In addition, because of the No Child Left Behind legislation and other accountability efforts, teachers need to be able to interpret statistical measures and graphs to assess the instruction in their schools and to communicate with parents.

Topics: There are four major sections of this course: Data Collection, Data Analysis, Probability and Statistical Inference. The emphasis of the course will be on the data collection and analysis with an overview of probability and statistical inference.

Our Approach: Class time will be used to investigate the course topics in a way that will help students to understand the material so that they can teach it and use it in their professional life. Students are expected to read the textbook outside of class to solidify the ideas that have been investigated in the classroom activities. Homework assignments are used to provide a check that the course objectives are being met.

Course Assessments and Grading:

Assessments:

Weekly writing 50 points (5 points each)

Homework 100 points (10 points each)

2 In-class Tests 150 points (75 points each)

Project 50 points

Final exam 100 points

Attendance 50 points

Total 500 points

Weekly writing: Each week of the course you are expected to write a brief entry about statistics that you have found in the “real world.” The “real world” may include the news, whether print, radio, online or television, another course you are taking, or something to do with teaching. You are expected to keep a journal or notebook that includes the sources (or artifacts) and your writing. You are expected to complete 10 writing assignments. Five of the assignments must be about issues in teaching. Examples of sources for these writings are grade level content expectations (GLCE) or sets of GLCEs in data and probability, a textbook lesson on data and probability, data that are available for students and teachers about the results of the MEAP test, or education related research projects. For examples of the types of things you might write about the sources, see the case studies provided in the textbook. At the end of each chapter there is a list of follow up questions that you should be able to answer about the case studies. These are the types of questions your writing should address. (50 points total)

Homework: Twelve homework assignments are listed in the course syllabus below. These will be due at the beginning of class on Wednesday. No late assignments will be accepted, but only the highest ten scores will be counted (100 points total).

Tests: There will be two in-class tests during the semester (75 points each) and a cumulative final exam on Thursday, May 7: 3:00 – 5:00 pm (100 points).

The dates for the tests are below. There will be no make up tests. In an extreme circumstance, with documentation, for example, jury duty or a death in the family, arrangements may be made for a missed exam.

Project: The purpose of the project is for students to become involved in doing statistics and to give an idea of activities that may be done with upper elementary school students. Details about the project will be distributed later in the semester. The project will cover the data collection and data analysis portions of the course material. The project will be due at the beginning of class on Wednesday, April 22 (50 points).

Attendance: This class is designed to be active and interactive. Much of your learning will evolve from in-class activities, experiences and discussions. This means that class attendance is essential. It is assumed that you will not miss class unless you are ill or must attend to a personal emergency. Beyond the first two absences, every absence will result in a 2-point deduction of your semester grade (up to a possible 50 points total deduction). If you have special needs with regards to attendance, please see the instructor about them during the first week of class.

Course grades will be assigned according to the following percentage scale:

4.0 90 - 100 3.5 85 - 89

3.0 80 - 84 2.5 75 - 79

2.0 70 - 74 1.5 65 - 69

1.0 60 - 64 0.0 < 60

Disclaimer: The instructor reserves the right to make any changes she considers academically advisable. Changes will be announced in class and posted on the class website. It is your responsibility to keep up with any changed policies.

Important dates for Spring Semester 2008:

Important

Dates: Jan 12 First day of Classes April 8 Test 2

Jan 16 Close of adds April 22 Project Due

Jan 19 Martin Luther King April 29 Last Day of Classes

Holiday – No Classes May 7 Final Exam

Feb 6 End of 100% refund

Feb 22 Test 1

Mar 4 Middle of the semester

Mar 9 – 13 Spring Break

– No classes

Course Syllabus:

Week	Topic	Reading	Assignment
1: Jan 12 & 14	Collecting Data: Observational studies, surveys and samples	Chapters 1 & 2	None
2: Jan 21	Collecting Data: Sampling Variability	Chapter 3	1.8, 1.10, 1.14, 1.18;
3: Jan 26 & 28	Data Collection: Bias in Surveys and Experiments	Chapters 4, 5 and 6	2.8, 2.12 (using calculator), 2.13, 2.18; 3.6, 3.8, 3.12, 3.14, 3.26;
4: Feb 2 & 4	Data Collection: Ethics and Measurement issues	Chapters 7 & 8	4.4, 4.12, 4.14, 4.16, 4.30; 5.2, 5.4, 5.6, 5.10, 6.12.
5: Feb 9 & 11	Data Collection: Exploring the numbers Data Analysis: Graphing categorical and quantitative data	Chapters 9, 10, 11	Ethics Assignment TBD; 8.6, 8.16, 8.24, 8.26.
6: Feb 16 & 22	Review of Data Collection and Test 1		9.6, 9.8, 9.12, 9.14, 9.18; Test 1: Chapters 1 – 5, 7 – 9;
7: Feb 23 & 25	Data Analysis: Describing distributions with numbers	Chapter 12	10.12, 10.14, 10.18, 10.22, 10.24; 11.4, 11.9 (histogram), 11.14.
8: Mar 2 & 4	Data Analysis: The Normal Distribution	Chapter 13	12.4, 12.14, 12.16, 12.21, 12.22, 12.30, 12.31, 12.32.
Mar 9 - 13	Spring Break
9: Mar 16 & 18	Data Analysis: Two Quantitative Variables	Chapters 14 & 15	13.7, 13.8, 13.9, 13.10, 13.14, 13.20, 13.26.
10: Mar 23 & 25	Probability: Chance, Randomness, Probability and Probability Models	Chapters 17 & 18	14.4, 14.6, 14.8, 14.12, 14.14, 14.18, 14.22; 15.6, 15.8, 15.26, 15.29, 15.31, 15.33
11: Mar 30 & Apr 1	Probability: Simulations	Chapters 19 & 20	17.8, 17.16, 17.20, 17.22; 18.10, 18.14, 18.20,
12: Apr 6 & 8	Review of Data Analysis and Probability and Test 2		Test 2: Chapters 10 – 15, 17, 18
13: Apr 13 & 15	Statistics: Confidence Intervals	Chapter 21	19.14 (use calculator); 20.7, 20.16.
14: Apr 20 & 22	Statistics: Tests of Significance	Chapter 22	Project Due
15: Apr 27 & 29	Statistics: Use and Abuse of Inference	Chapter 23	Assignment TBD