• Textbook: Introduction to Statistics Using Google Sheets
• Recommended materials: mobile smartphone., or scientific calculator
• Office hours: Monday & Friday 1:00 to 3:00 or by appointment. See also further contact information below.
• Instructor: Dana Lee Ling
• Email: dleeling@comfsm.fm Email address recommendations
• Course web site: http://www.comfsm.fm/~dleeling/statistics/
• Statistics blog: http://danaleeling.blogspot.com/search/label/statistics
• Phones: Work: 320-2480 extension 228 | Cell: 926-2868
• Attendance: Seven absences can result in withdrawal from the course. Absences can be excused from the seven absence limit for medical or official education-related travel. Appropriate documentation is required such as a note from the physician (doctor) or, in the case of education-related travel, some form of written communication from official sponsors of the travel.
• Health:No betelnut in class. No spitting over the balcony!
• Gradebook: http://www.schoology.com Apps: Android iOS
• Grading policy: Points are earned for correct answers on homework, quizzes, and tests. You have do consistently well across all quizzes and tests to succeed in this course. Grading is based on the standard college policy: Obtain 90% of the points or more to obtain an A, 80% to 89% for a B, and so forth.
• Course outline: http://www.comfsm.fm/~dleeling/statistics/se3/ms150-statistics-outline-20140908.docx (proposed)
• Academic Honesty Policy: Cheating on an assignment, quiz, test, midterm, or final will result in a score of zero for that assignment, quiz, or test. Due to our cramped quarters, the course operates by necessity on a system of personal integrity and honor.
• Course student learning outcomes assessment: Based on item analysis of final examination aligned to the outline. During term student assessment occurs at the end of each week, see above.
• Learning outcomes in brief: Students will be able to...
Institutional Learning Outcomes:
4. Problem solving: capacity to design, evaluate, and implement a strategy to answer an open-ended question or achieve a desired goal.
8. Quantitative Reasoning: ability to reason and solve quantitative problems from a wide array of authentic contexts and everyday life situations; comprehends and can create sophisticated arguments supported by quantitative evidence and can clearly communicate those arguments in a variety of formats.
Program Learning Outcomes:
3.1 Demonstrate understanding and apply mathematical concepts in problem solving and in day to day activities
3.2 Present and interpret numeric information in graphic forms
Course Learning Outcomes (proposed):
1. Perform basic statistical calculations for a single variable up to and including graphical analysis, confidence intervals, hypothesis testing against an expected value, and testing two samples for a difference of means.
1.1 Identify levels of measurement, variables, and appropriate statistical measures for a given level of measurement
1.2 Calculate basic statistical measures for the middle, spread, quartiles, and relative standing
1.3 Determine frequencies and relative frequencies, create histograms and identify their shape visually
1.4 Calculate confidence intervals for the mean
1.5 Calculate the standard error of the mean
1.6 Calculate the margin of error for the mean using tcritical
1.7 Generate the confidence interval for the mean of a sample using the t-distribution
1.8 Perform hypothesis tests against a known population mean using both confidence intervals and formal hypothesis testing
1.9 Perform t-tests for paired and independent samples using both confidence intervals and p-values
2. Perform basic statistical calculations for paired correlated variables.
2.1 Calculate the linear slope and intercept for a set of data
2.2 Calculate the correlation coefficient r
2.3 Generate predicted values based on the regression
3. Engage in data exploration and analysis using appropriate statistical techniques including numeric calculations, graphical approaches, and tests.
3.1 Explore statistically and graphically represent data sets using appropriate statistics and graphics for that data set
3.2 Make inferences supported by appropriate statistical operations

Body fat, obesity, diabetes, health links
Body comp handout
How Lean Should You Be? - Chart
Forbes most obese nations
Global post most obese
Body Mass Index BBC
How the diabetes-linked thrifty gene triumphed with prejudice over proof
Intentional injury reported by young people in Pohnpei
Number two in marijuana usage
Most inactive nations
Diabetes chart image from conference

Alternatives to USB flash drives