SSC 302: Data Analysis for the Health Sciences Division of Statistics & Scientific Computation Spring 2013

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1 SSC 302: Data Analysis for the Health Sciences Division of Statistics & Scientific Computation Spring 2013 Instructor Office Office Hours Website: TA: Labs: COURSE DESCRIPTION This course is designed to help you learn the basics of data analysis, including the descriptive and inferential statistical procedures that are commonly used in health science research. You will learn techniques for graphing and describing data; explore common function patterns including linear, logarithmic, exponential and logistic functions; be introduced to correlation and linear regression; learn the basic principles of hypothesis testing and the inferences that can be drawn from them; and develop skills necessary for evaluating the conditional probability of health-related events. This course satisfies the core math requirement at UT and carries a quantitative reasoning flag. COURSE LEARNING OBJECTIVES The lectures, labs and assignments in this course are designed to help you meet three course objectives: 1) learn the basics of data analysis, including the statistical methods commonly used in the health sciences. 2) learn how to apply an analytical framework to data analysis problems and report your findings. 3) learn how to analyze and model real-world data using common software programs. WEEKLY LAB SSC 302 provides students with the unique opportunity to analyze real-world data in a lab setting for one hour of class time each week. The weekly one-hour lab sessions meet in FAC 101B. Attendance is mandatory and you are expected to arrive on time. All lab work is done in pairs. Students that are not in class by the time work has begun (usually within 5 minutes of the start of class) will not be allowed to work with a partner. If your lab partner doesn t arrive on time, you may choose to work with another individual or work alone. The lab computers are PCs. If you are a Mac user, you are welcome to bring your laptop to the lab and use it to complete the lab exercise. PREREQUISITE You must have a score of at least 30 on the ALEKS on-line math assessment by 11:59 pm the first day of class. You will be dropped from the course if you fail to meet this prerequisite. Students that already have credit for pre-calculus or calculus are exempt from this requirement. For more information please refer to 1

2 REQUIRED TEXTBOOK & MATERIALS 1. Textbooks. Purchase the text and course packet at Austin TXbooks Guadalupe Street Text: Introductory Statistics (Gould, et al); ISBN # Course packet: Functions Modeling Change 2. iclicker. Purchase at Austin TXbooks and bring to class each day. 3. Software for Lab. Make sure you have a copy of Excel and Graphmatica on your computer. Excel can be purchased from the Campus Computer Store. The latest version of Excel is preferred. A free trial version of Graphmatica can be downloaded for the semester from COURSE EXPECTATIONS You are responsible for ensuring that you are prepared for class and lab. Here are the daily requirements for class. 1. Arrive on Time. Late arrivals are disruptive to both the class and the instructor so please be on time. 2. Put Away Electronic Devices. Put your cell phone in silent mode and put away any other electronic devices (e.g., computers, ipods, etc.). These may not be in use during lecture or lab. 3. Download the Class Handout: Some lectures will require you to print the handout from Canvas prior to each lecture and bring it with you to class. 4. Bring Your Calculator. You are expected to bring a scientific or graphing calculator to lecture each day. Graphing calculator is preferred. Also print a copy of the syllabus, with formula sheet and tables, and have it with you in class each day. LECTURE ATTENDANCE & PARTICIPATION There are 30 points assigned for lecture attendance and participation. You must be present and participate (via iclicker) on at least 80% of the lecture days to receive 30 points. Otherwise, you get 0 points. 2

3 LEARNING ACTIVITIES This course is divided into three units. Each unit ends with a lecture exam and lab exam that will evaluate your knowledge of the material. All other unit assignments are learning tools designed to help you develop the necessary skills and understanding. Consistent performance on these assignments will help your grade, but your performance on exams will be considered the strongest indicator of your success in meeting the course learning outcomes. Weekly Assignments End-of-Unit RAQ (on-line) Reading Quiz (on-line) Pre-Lab (on-line) Unit Exam Lecture Lab Homework Lab Exam DEADLINES Assignment Location When does it open? When does it close? Reading Quiz/RAQ Canvas 3pm 11:59 pm Pre-Lab Canvas (Lab) 3pm 11:59 pm Homework Canvas 3pm Due at start of Lab ASSIGNMENT DETAILS Reading Quizzes (10 pts). Reading quizzes are done on-line. They are multiple-choice and are designed to help focus your reading of the textbook BEFORE you attend class. You will have an opportunity to retake the quiz for a higher grade. Labs (30 pts). Labs consist of two assignments: pre-lab (worth 10 points) and lab (worth 20 points). Pre-lab is completed on-line and you can re-take it for a higher grade. Lab is completed during your assigned lab time. Homework (30 pts). Weekly homework includes a data analysis problem from the previous week s lab and problems from lecture. Homework must be turned in at the start of lab. Late or unstapled HW will not be accepted. 3

4 RAQ (Readiness Assessment Quiz) (30 pts). Prior to each exam, you will complete a timed 30-minute on-line quiz that reviews material from that unit. Lab Exams (35 pts). Lab exams test your ability to independently perform data analyses, using Excel or Graphmatica. Lab exams will take place at the end of each unit during your scheduled lab session. Exams (125 pts). There will be three in-class exams. These exams are a combination of multiple choice and hand problem-solving. You must show your work for full credit. Final Exam (250 points). Cumulative, mandatory, and multiple-choice. ACADEMIC HONESTY The course is built upon the idea that team-based learning is important and a powerful way to learn. We encourage you to study together often. However, there are times when you need to demonstrate your own ability to work and solve problems. Your homework and your exams are independent assignments. This means these assignments are to be completed on your own, without discussion with your peers. Students who violate this expectation can expect to receive a failing grade on the assignment and be reported to the Dean of Students office for academic dishonesty. These types of violations are reported to professional schools, should you ever decide to apply one day. Don t do it it s not worth the consequences. GRADING UNIT ASSIGNMENTS 3 Reading Quizzes 3 Labs 3 Homework RAQ Lab Exam Exam Total Points TOTAL COURSE UNIT 1 UNIT 2 UNIT 3 Attendance (attend >80% of lectures) Final Exam Grand Total Points HOW AM I DOING? To calculate your unit grade average: To calculate your final grade average: 4

5 FINAL COURSE GRADES Final grades will be assigned according to the grade cutoffs listed below. Please note that grade cutoffs are firm. We do not curve grades in this class. Keep track of your progress so you know if you are meeting your grade goal. More information about the upgrade policy can be found below. Course Grade Points Needed (standard policy) Points Needed (upgrade policy) 93% A % A % B % B % B % C % C % C % D % D % D MISSED ASSIGNMENT POLICY We will offer make-up exams or labs only under the following circumstances. For any other reason, a make-up is not guaranteed and a grade of 0 will be recorded for any missed lab or exam. 1. You are away from UT as part of a UT-sponsored activity including athletics. Check with me if you are uncertain whether your absence qualifies. 2. The quiz, lab or exam is in conflict with a religious observance notify me by the 12 th day of class. 3. You suffer from a chronic, documented illness or an emergency that results in your missing an exam or lab. Under these circumstances, contact me as soon as possible to discuss a course of action. BONUS POINTS Occasionally, there will be items during the semester that I will offer as BONUS points. These bonus points will be added to your overall TOTAL points for the class. These are good options for you to take advantage of, as they will help pad your grade. UPGRADE POLICY Frequently, students want an opportunity at the end of the semester to raise grades that are close to a grade cutoff. This course has a specific policy for awarding final grades: If you wish, you can earn the right to have your final grade determined by a more lenient cutoff. The key point here is that this is done before you find yourself in a tight situation. 5

6 We call this our upgrade policy, and it involves earning upgrade points over the course of the semester. Upgrades are interesting statistical questions or exercises that can be answered with a little bit of effort. Each upgrade is worth 2 points (with a few exceptions). NOTE: Your upgrade points are NOT added to your total points. By earning 10 upgrade points, you make yourself eligible to have your final grade determined using the more lenient cutoffs (shown above). Upgrade opportunities will be posted on Canvas. Visit Canvas to learn more about them. Bottom line: This is a good deal. Don t pass it up. REGRADE POLICY If you think there may be an error in grading, you should bring it to our attention. To request a regrade, send an to the TA that does the following: 1. Include the words Regrade Request for SSC 302 in the subject heading. 2. Include the unique number of the course, your name, EID, the exact assignment (e.g., HW 3), and a clear concise summary of the concern. 3. There will be a two-week window for regrades on any course assignment. Then the grade sticks. STUDENTS WITH DISABILITIES The University of Texas at Austin provides upon request appropriate academic accommodations for qualified students with disabilities. For more information, contact the Office of the Dean of Students at , TTY. 6

7 STRATEGIES FOR EXCELING IN THIS CLASS SSC 302 is designed to help you become a more effective independent learner, an essential skill in college. We have prepared lecture activities, strategic quizzes and hands-on lab exercises to help strengthen your conceptual understanding of the material and prepare you to excel on the exams. We strongly recommend that you adopt good learning strategies that will serve you well in your other courses here at UT. Here are our ideas on how to succeed in this class. THE BIG THREE: 1) Attend class every day. Attending class is your best study aid. You ll learn more each class you attend. You ll also remember more. 2) Before class, review your notes. Download the daily handout and review your notes from the previous class session. Does it all still make sense? 3) After class, work the suggested problems. What exactly did we learn in class? Your daily handout will have suggested problems from the book. Work them all to check your comprehension and become familiar with the different ways that questions can be asked of the material. CHECK YOUR PROGRESS 1) Set a goal for the week. Need to improve attendance? Make it happen this week. 2) Review your assignment grades and see what they are telling you. 3) Give yourself enough time to complete your work. Good thinking takes time. 4) Adopt good organizational strategies. Keep a binder and hole-punch everything. 5) Explore other strategies if what you are doing is not working. See me for ideas. TARGET YOUR PROBLEM AREAS 1) Don t understand something in class? Raise your hand and ask a question! 2) Not sure how to solve a problem? Watch the on-line problem-solving modules. 3) Can t figure out how to do something in Excel? Review the online Excel videos. 4) Don t understand the readings? Come see the TA or the instructor in office hours. 5) Need more practice? Work the suggested problems in the textbook. 6) Need motivation to study? Form a study group and work together weekly. 7

8 SSC 302 Course Outline Spring 2013 UNIT 1: Data & Distributions Week Day Date Topic Reading Quiz Weekly Lab (due midnight) (HW due in Lab) 1 M 1/14 Intro to SSC 302 Pre-test due before 1/16 Intro to Lab W 1/16 Data 2 M 1/21 MLK HOLIDAY RQ 1: Ch 1-3 (due Tues Lab 1 (HW 1 due) W 1/23 Center, Spread & Location night) 3 M 1/28 Scatterplots & Correlation RQ 2: and 5.3 Lab 2 (HW 2 due) W 1/30 2-way Tables 4 M 2/4 Test of Independence RQ 3: 10.1 and 10.3 Lab 3 (HW 3 due) W 2/6 Goodness of Fit 5 M 2/11 Review RAQ 1 Lab Exam 1 W 2/13 Exam 1 UNIT 2: Functions & Modeling Week Day Date Topic Reading Quiz Weekly Lab 6 M 2/18 General and Linear Funct. RQ 4: (course pack), Lab 4 (HW 4 due) W 2/20 Regression (textbook) 7 M 2/25 Exponential Functions RQ 5: (course pack), Lab 5 (HW 5 due) W 2/27 Exponential Functions (course pack) 8 M 3/4 Log transformations RQ 6: 4.4 (course pack), Lab 6 (HW 6 due) W 3/5 Logistic Functions Logistic (course pack) M 3/11 Spring Break W 3/13 9 M 3/18 Review RAQ 2 Lab Exam2 W 3/20 Exam 2 UNIT 3: Statistical Inference Week Day Date Topic Reading Quiz Weekly Lab 10 M 3/25 Normal Model RQ Bonus: Simulation W 3/27 Sampling Distributions 11 M 4/1 Estimating the Mean RQ 7: 9.3 Lab 7 (HW 7 due) W 4/3 One-sample t-test 12 M 4/8 Independent t-test RQ 8: Lab 8 (HW 8 due) W 4/10 Paired t-test & Hyp. 13 M 4/15 ANOVA RQ 9: Lab 9 (HW 9 due) W 4/17 ANOVA 14 M 4/22 ANOVA post-hoc RAQ 3 Lab Exam 3 W 4/24 Review 15 M 4/29 Exam 3 TBD W 5/1 Final Review Mandatory Final Exam: Tuesday, May 14 from 9 am 12 pm. Location: TBD 8

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