STAT 100, Section 004, Fall 2013: Statistical Concepts and Reasoning

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1 STAT 100, Section 004, Fall 2013: Statistical Concepts and Reasoning This online document is the official course syllabus. It is found at You may download a pdf version of this syllabus if you wish. Welcome to STAT 100! As in the official course listing in the University Bulletin, statistics is the art and science of decision making in the presence of uncertainty. The broad goal of this course is to introduce the student to statistical reasoning and interpretation of data analysis. Course organization and learning objectives: Loosely speaking, the course may be divided into sections, which are assessed by in-class midterms 1, 2, and 3, as follows: Section 1: Collecting and describing data effectively. Learning Objectives: -- Understand the question of causation as it relates to statistical studies. -- Use, interpret, and create commonly used graphical displays of data. -- Recognize normal distributions and understand their properties. -- Recognize common sampling techniques and statistical terminology. Section 2a: Analyzing relationships between variables. Learning Objectives: -- Interpret linear correlation and output from simple linear regression and contingency table chi-square tests. -- Correctly define p-value and interpret p-values seen in statistical studies. Section 2b: Applying basic probability ideas. Learning Objectives: -- Apply rules of probability to idealized situations; recognize common pitfalls in this application. Section 3: Understanding basic statistical inference: Confidence intervals and Hypothesis tests Learning Objectives: Some of these objectives will be assessed on the final exam rather than midterm #3. -- State and use the rules of sample means and sample proportions. -- Calculate basic quantities needed for simple confidence intervals and hypothesis tests. -- Construct and interpret simple confidence intervals. -- Construct and interpret simple hypothesis tests. -- Recognize meta-analysis and related ideas. The final exam will be cumulative. Required Textbook: Seeing Through Statistics, Third Edition, by Jessica Utts, published by Duxbury Press. We will cover most of this book; see the tentative calendar below. You will probably not need the CD-ROM that comes with the book, so feel free to buy a used copy. i>clicker also required: You will need an i>clicker, available at the student bookstore. Please note: You should not buy an i>clicker2 or an i>clicker+, only the original i>clicker. If you already have a clicker that you use for another class, you may use the same one for this class. Important: If you have not yet done so, you must register your i>clicker so that you get credit for your work in class. The 1 of 6 8/26/13 11:29 AM

2 easiest way to do this is by visiting the ANGEL site for this class and clicking on Lessons->Register Your Clicker, then following the instructions. Schedule: MWF 3:35-4:25 in 101 Thomas Course Website: stat.psu.edu/~dhunter/100 Instructor: David Hunter ( is the best method of contact: Please do not use ANGEL to contact me unless you check the box that will forward to my regular . Office hours: Prof. Hunter's office hours will be in 326A Thomas Building. Dates and times will be announced later, but please feel free to me with any questions. Shared office hours for all introductory statistics courses will be held 23 hours per week in room 7B Sparks during the following times: Monday through wednesday, 1:00pm to 4:00 and 6:00pm to 9:00 Thursdays, 1:00pm to 3:00 and 6:00pm to 9:00 Required Work: There will be a total of 500 points awarded in the course, consisting of: 1. Three in-class mid-semester examinations, each worth 100 points. (See "Exams" below) 2. Ten randomly timed, in-class quizzes, each worth 5 points. (See "Quizzes" below) 3. A comprehensive final exam, worth 150 points. (See "Exams" below) Final Grades: Final letter grades will be determined as follows: B+: 88-89% C+: 78-79% A : % B : 84-87% C : 70-77% D : 60-69% A-: 90-93% B-: 80-83% Exams: All exams will be in multiple-choice format and will use computer scan-tron (bubble) sheets. To each exam, you should bring: 1. A single 8.5 x 11 inch sheet of formulas or notes (double-sided if you wish), 2. No. 2 pencils to complete your scan-tron sheet, and 3. Your Penn State University student ID card. You may bring calculators but generally you will not need them. See also "Course Rules" below. Quizzes: At least 13 randomly timed, in-class quizzes will be given, and your best 10 scores will count toward the final score. Each quiz is worth 5 points and it will use the clickers. It is to your advantage to attend class regularly throughout the semester. See also "Course Rules" below. Extra credit: There will be occasional chances to earn one point of extra credit for completing small assignments. These opportunities will be announced as they occur. Homework: Homework will be assigned but not collected. Answers to some homework assignments are posted on the course web page. The exams and quizzes will reflect the homework assignments, so it is advantageous to do your homework diligently. Occasional ANGEL-based assignments, based on the homeworks, will enable you to get some practice with the concepts of the course. 2 of 6 8/26/13 11:29 AM

3 Course Rules: No late or make-up exams will be given. If you must miss any exam, you should provide a valid reason IN WRITING to the instructor PRIOR TO THE EXAM. If you have to miss an exam at the last minute for some reason, be sure to notify the instructor prior to the exam time by or by leaving a phone message; in these cases, you should later back up your excuse with written documentation. Once the instructor has approved your written excuse, your final grade will be calculated without the missed exam (e.g., if you miss one of the midterms, then your final grade will be calculated based on 400 total points instead of 500). No make-up quizzes will be given for ANY reason. You will be allowed to drop at least three quiz grades, which should cover any excused absences that may result in a missed quiz. Students are responsible for all announcements and supplements given within any lecture. If you need to leave class early, please sit in the rear and leave as quietly as possible. Please be courteous to your classmates and keep extra noise to a minimum. Please turn off all cell phones and pagers during class. Academic Integrity: All Penn State and Eberly College of Science policies regarding academic integrity apply to this course. See for details. Please understand that the integrity policy also applies to the use of clickers. In particular, use of any clicker by someone other than a person to whom it is registered is a violation of the policy and will result in academic sanctions such as a loss of five or more points from the final course grade, depending on the severity of the violation. Basically, to avoid problems, you should never bring any clicker to class that is not your own. Code of Mutual Respect: The Eberly College of Science Code of Mutual Respect and Cooperation ( Respect%20final.pdf/view embodies the values that we hope our faculty, staff, and students possess and will endorse to make the Eberly College of Science a place where every individual feels respected and valued, as well as challenged and rewarded. Disabilities statement: Penn State welcomes students with disabilities into the University's educational programs. If you have a disability-related need for reasonable academic adjustments in this course, contact the Office for Disability Services (ODS) at (V/TTY). For further information regarding ODS, please visit the Office for Disability Services web site at Campus emergencies: Campus emergencies, including weather delays, are announced on Penn State Live and communicated to cellphones, , the Penn State Facebook page, and Twitter via PSUTXT (to sign up, please see Tentative Course Calendar for STAT Throughout the semester, the calendar below may be adjusted slightly according to the pace of the class or conflicts that arise3. All chapters refer to Seeing Through Statistics, Third Edition, by Jessica Utts, published by Duxbury Press. See below for chapter titles. 3 of 6 8/26/13 11:29 AM

4 Aug Introduction, Chapter 1, Chapter 7 Sept. 2 Sept. 4-6 Chapter 8 No class; Labor Day Sept Chapter 9, Chapter 3 Sept Chapter 3, Chapter 4 Sept Chapter 5 Sept. 27 (Friday) Mid-term Exam 1 on Chapters 1, 3, 4, 5, 7, 8, 9 Sept. 30-Oct. 4 Chapter 10, Chapter 11 Oct Chapter 13, Chapter 12 Oct Chapter 16, Chapter 17 Oct Chapter 17, Chapter 18 Oct. 28 Review Oct. 30 (Wednesday) Mid-term Exam 2 on Chapters 10, 11, 12, 13, 16, 17, 18 Nov. 1 Chapter 19 Nov. 4-8 Chapter 19, Chapter 20 Nov Chapter 20, Chapter 21 Nov. 18 Chapter 21 Nov. 20 Review Nov. 22 (Friday) Mid-term Exam 3 on Chapters 19, 20, 21, 22 Nov No class; Thanksgiving break Dec. 2-6 Chapter 23, Chapter 24 Dec Chapter 25, Review for final Time, date, and location TBA Comprehensive final exam Chapter titles in the textbook These chapters refer to the required textbook, Seeing Through Statistics, Third Edition, by Jessica Utts, published by Duxbury Press: The Benefits and Risks of Using Statistics. Statistics. Detecting Patterns and Relationships. Don't Be Deceived by Improper Use of Statistics. Summary and Conclusions. Reading the News. The Educated Consumer of Data. Origins of News Stories. How to be a Statistics Sleuth: Seven Critical Components. Four Hypothetical Examples of Bad Reports. Planning Your Own Study: Defining the Components in Advance. 4 of 6 8/26/13 11:29 AM

5 Measurements, Mistakes, and Misunderstandings. Simple Measures Don't Exist. It's All in the Wording. Open or Closed Questions: Should Choices Be Given? Defining What is Being Measured. Defining a Common Language. How to Get a Good Sample. Common Research Strategies. Defining a Common Language. The Beauty of Sampling. Simple Random Sampling. Other Sampling Methods. Difficulties and Disasters in Sampling. Experiments and Observational Studies. Defining a Common Language. Designing a Good Experiment. Difficulties and Disasters in Experiments. Designing a Good Observational Experiment. Difficulties and Disasters in Observational Studies. Random Sample versus Random Assignment. Getting the Big Picture. Final Questions. Case Studies. Summarizing and Displaying Measurement Data. Turning Data into Information. Picturing Data: Stemplots and Histograms. Five Useful Numbers: A Summary. Boxplots. Traditional Measures: Mean, Variance, and Standard Deviation. Caution: Being Average Isn't Normal. Bell-Shaped Curves and Other Shapes. Populations, Frequency Curves, and Proportions. The Pervasiveness of Normal Curves. Percentiles and Standardized Scores. z-scores and Familiar Intervals. Plots, Graphs, and Pictures. Well-Designed Statistical Pictures. Pictures of Categorical Data. Pictures of Measurement Variables. Difficulties and Disasters in Plots, Graphs, and Pictures. A Checklist for Statistical Procedures. Relationships Between Measurement Variables. Statistical Relationships. Strength versus Statistical Significance. Measuring Strength Through Correlation. Specifying Linear Relationships through Regression. Relationships Can Be Deceiving. Illegitimate Correlations. Legitimate Correlation Does Not Imply Causation. Some Reasons for Relationships Between Variables. Confirming Causation. Relationships Between Categorical Variables. Displaying Relationships Between Categorical Variables. Relative Risk, Increased Risk, and Odds. Misleading Statistics about Risk. Simpson's Paradox: The Missing Third Variable. Statistical Significance for 2x2 Tables. Measuring the Strength of a Relationship. Steps for Assessing Statistical Significance. The Chi-Square Test. Practical versus Statistical Significance. Reading the Economic News. Cost of Living: The Consumer Price Index. Uses of the Consumer Price Index. Criticisms of the Consumer Price Index. Economic Indicators. Understanding and Reporting Trends over Time. Time Series. Components of Time Series. Seasonal Adjustments: Reporting the Consumer Price Index. Cautions and Checklist. Understanding Probability and Long-Term Expectations. Probability. The Relative-Frequency Interpretation. The Personal-Probability Interpretation. Applying Some Simple Probability Rules. When Will It Happen? Long-Term Gains, Losses, and Expectations. 5 of 6 8/26/13 11:29 AM

6 Psychological Influences on Personal Probability. Revisiting Personal Probability. Equivalent Probabilities: Different Decisions. How Personal Probabilities can Be Distorted. Optimism, Reluctance to Change, and Overconfidence. Calibrating Personal Probabilities of Experts. Tips for Improving Your Personal Probabilities and Judgments. When Intuition Differs from Relative Frequency. Revisiting Relative Frequency. Coincidences. The Gambler's Fallacy. Confusion of the Inverse. Using Expected Values to Make Wise Decisions. The Diversity of Samples from the Same Population. Setting the Stage. What to Expect of Sample Proportions. What to Expect of Sample Means. What to Expect in Other Situations. Estimating Proportions with Confidence. Confidence Intervals. Three Examples of Confidence Intervals from the Media. Constructing a Confidence Interval for a Proportion. The Role of Confidence Intervals in Research. Confidence Intervals for Population Means. Confidence Intervals for the Difference Between Two Means. Revisiting Case Studies: How Journals Present Confidence Intervals. Understanding Any Confidence Interval. Rejecting Chance--Testing Hypotheses in Research. Using Data to Make Decisions. The Basic Steps for Testing Hypotheses. Testing Hypotheses for Proportions. What Can Go Wrong: The Two Types of Errors. Hypothesis Testing--Examples and Case Studies. How Hypothesis Tests are Reported in the News. Testing Hypotheses about Proportions and Means. Revisiting Case Studies: How Journals Present Hypothesis Tests. Significance, Importance, and Undetected Differences. Real Importance versus Statistical Significance. The Role of Sample Size in Statistical Significance. No Difference versus No Statistically Significant Difference. A Summary of Warnings. Meta-Analysis: Resolving Inconsistencies across Studies. The Need for Meta-Analysis. Two Important Decisions for the Analyst. Some Benefits of Meta-Analysis. Criticisms of Meta-Analysis. Ethics in Statistical Studies. Ethical Treatment of Human and Animal Participants. Assurance of Data Quality. Appropriate Statistical Analyses. Fair Reporting of Results. Putting What You Have Learned to the Test. Case Studies. 6 of 6 8/26/13 11:29 AM

Penn State University - University Park MATH 140 Instructor Syllabus, Calculus with Analytic Geometry I Fall 2010

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