INTRODUCTION TO MEASUREMENT AND STATISTICS

(Summer 2012)

Course:

PSYC/SOCI 2750: Introduction to Measurement and Statistics

Professor:

Dr. Linda M. Woolf

Office Hours:

Text:

McCall, R. B. (2000). Fundamental statistics for behavioral sciences, (8th ed.). New York: Harcourt Brace Jovanovich. ISBN-13: 978-0534577803

Course Description:

Introduction to Measurement and Statistics (PSYC/ANSO 2750) is for the university student who wishes to gain an understanding of basic statistical concepts. Knowledge of these concepts is essential for the reading of technical journals in one's field and basic research design. In other words, no matter whether you are sitting by the fireplace catching up on your reading about depression or working on a new treatment method, knowing when and how to use measurements and statistics is fundamental. The basic concepts to be covered are:

  1. the contrast between descriptive and causal research
  2. types of measurement
  3. the use of descriptive statistics to summarize research results
  4. the use of inferential statistics to draw conclusions based on a sample(s) drawn from a population.

No prior statistical knowledge is required for this class. Classroom techniques that will be used to achieve the course objectives will include lecture, active problem solving sessions, homework, and examinations.

Course Objectives:

  1. To develop a practicing and theoretical understanding of descriptive and inferential statistics.

  2. To develop an understanding of how to choose a statistic or determine if the one used is appropriate based on the type or source of quantitative data.

  3. To develop an appreciation for the use of statistics and an ability to recognize the misuse of statistics. In other words, to make the student an active consumer of statistics (i.e. do people really lie with statistics?).

  4. To further develop your statistical literacy, thinking, and reasoning skills.

Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write - H. G. Wells

Course Outcomes:

  1. The student will have an understanding of basic research methodology and the impact of research design on data interpretation.

  2. The student will develop an understanding of statistics as an integral component of the research process.

  3. The student will be able to differentiate between a descriptive and inferential statistic and will know when each is being interpreted appropriately.

  4. The student will know how to represent and interpret frequency and statistical data using basic graphing techniques.

  5. The student will know how to compute and evaluate measures of central tendency, measures of variability, standard scores, correlation coefficients, linear regression, standard error, confidence intervals, t-tests (independent and correlated), and one/two factor ANOVA.

  6. The student will know when to appropriately use and how to interpret data from each of the above statistical techniques.

  7. The student will understand the underlying assumptions and theory of hypothesis testing.

NOTE:

Statistics can be fun or at least they don't need to be feared. The logical and mathematical concepts required to do well in this class are not prohibitive for any health science or university student. The key to doing well in this class can be summarized by two words, "KEEP UP!". If you don't understand a concept in class, ask. I'm more than willing to re-explain. If you start to fall behind, contact me as soon as possible. We'll make some arrangements. This is important because the material discussed four weeks from today will be based on material discussed today. For more survival tips, see Survival Tips

Incoming Competencies/Prerequisites:

Prerequisite: All students should be capable of basic math, be able to think critically, and have basic writing skills.

Bear in mind that statistics is not a math course! Students and teachers should recognize that quantitative literacy is only a small component of statistical literacy. Statistics is not branch of mathematics but is rather a distinct discipline within the liberal arts (Moore, 1998; Cobb & Moore, 2000). As such, it is most important to focus on the learning of ideas, concepts, and the place of statistical thinking and reasoning in the research process.

Class Meetings:

The class will meet on Mondays from 5:30 - 9:30. Attendance is strongly recommended as this material is conceptually complex. Classroom attendance will greatly enhance your understanding of the information.

Course Requirements:

A midterm exam, a final exam, and five homework assignments.

All grades will be assigned on a scale of 0 - 100 with:

90 - 100A,A-Superior work
80 - 89B+,B,B-Good work
70 - 79C+,C,C- Satisfactory work
60 - 69D+,D Passing, but less than Satisfactory
Less than 60F Unsatisfactory

Percent of Grade:

Midterm Exam 40%
Final Exam 40%
Homework 20%

Examination format will include short answer and problem solving. The midterm will be take-home. The final will be in-class. The final will be open-book and open-note. Each exam will constitute 40% of your final grade. All exams must be taken on the date scheduled except in case of emergency. In case of the above, the instructor must be notified. No make-up exams will be provided if you fail to notify and discuss your situation with the instructor. Please note that no extra credit work will be made available to make-up for a poor test grade.

Homework will be assigned for the material covered during lecture. This will provide you with the opportunity to review and reinforce the material covered in class. It also serves as a diagnostic tool for me to see where people might be having problems. No late assignments will be accepted except in cases of emergency. No homework assignment will be accepted once the answer key has been distributed regardless of reason provided. Homework will constitute 20% of your final grade. Note: Not turning in homework assignments can result in a one to two letter grade drop in your final grade.

Plagiarism (attempting to pass off the work of another as one's own) is not acceptable. Plagiarism includes copying all or part of another's writings (even a single sentence), inappropriate paraphrasing, using another student's paper as your own, submitting a paper for more than one class. All papers will be submitted to the university's plagiarism database for review. Plagiarism, either intentional or unintentional, will result in a grade of 0 for that assignment and will be turned over to the appropriate university source for disciplinary action. In addition, cheating on exams will also result in the same fate.

Here are some Web sites that will help you avoid the problem of plagiarism particularly plagiarism resulting from paraphrasing too closely to the original source. -

Late withdraws from this class will not be approved by the instructor except in cases of emergency discussed with the instructor. No late withdraws will be approved on the basis of poor class performance.

This syllabus is subject to change at the instructor's discretion. All changes concerning course requirements will be provided in writing. Changes concerning exam dates may be made at the instructor's discretion and communicated verbally to the class.

It is understood that remaining in this course (not dropping or withdrawing from this course) constitutes an agreement to abide by the terms outlined in this syllabus and an acceptance of the requirements outlined in this document. No grade of Incomplete will be issued for this course.

During my 18 years I came to bat almost 10,000 times. I struck out about 1,700 times and walked maybe 1,800 times. You figure a ballplayer will average about 500 at bats a season. That means I played seven years without ever hitting the ball. - Mickey Mantle


COURSE OUTLINE


Week


Topic


Reading

June11 Introduction to class
Introduction to statistics
Overview of methodology
Chapter 1
Chapter 12
Introduction to Measurement and Statistics
Research Methods

June18Frequency Distributions and Graphing
Measure of Central Tendancy
Chapter 2
June 25 Characteristics-distributions
Measures of relative standing

Receive Midterm

Chapter 3
Chapter 5
June30
Saturday!
2:00 - 4:00
Webster Campus
WH 221
Sampling distributions

If you cannot attend the class, Email Week 3 Homework to woolflm@webster.edu by Friday evening so that I can get it back to you with an answer key on Saturday

Chapter 8
July2 Hypothesis testing
T-tests
Midterm Due
Chapter 9
Chapters 10 - 11
July9 ANOVA
Correlation
Chapter 14
Chapter 7
Week of July16Practice online via Blackboard!Review your notes!
July22
Sunday!
2:00 - 4:00
Webster Campus
WH 221
Option Study SessionBring your Questions!
July23FINAL EXAM




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