MS 150 Statistics Calendar and Syllabus • College of Micronesia-FSM • Instructor: Dana Lee Ling
Wk Day Name Date Topic Assessment
0 Friday01/11/08 Prequiz
1 Monday01/14/08 Syllabus, text book. • 1.1 Population and samples, types of measurement1.2 Simple random samples with introduction to OpenOffice
Wednesday01/16/08 Barefoot day: Determining your body fat • End add course [Tues]
Friday01/18/08 1.3 Experimental design Quiz 1
2 Monday01/21/08 2.1 Circle and column chartsClass lists due
Wednesday01/23/08 2.2 Histograms and Frequency Distributions
3 Monday01/28/08 Shapes of Distributions3.1 Measures of center
Wednesday01/30/08 3.2 Measures of variation3.3 Continous and Discrete variables3.4 Measures of relative standing: z only
4 Monday02/04/08 4.1 Best fit lines Drop a ball, graph the bounce height. [homework] Terminology including least squares, linear regression, trend line.
Wednesday02/06/08 4.2 Slope & Intercept • Predicting values
Friday02/08/08 Quiz 3 • Early warning
5 Monday02/11/08 4.3 Relationship
Wednesday02/13/08 4.4 Correlation
Friday02/15/08 Quiz 4
6 Monday02/18/08 5.1 Fundamentals of probability
Wednesday02/20/08 5.3 Probability as relative frequency
Friday02/22/08 Staff development day: no class
7 Monday02/25/08 Review of q05 5.3 and pedometer distribution
Wednesday02/27/08 [Probable term project work day]
Friday02/29/08 Midtermansods
MS 150 Statistics Calendar and Syllabus • College of Micronesia-FSM • Instructor: Dana Lee Ling
Wk Day Name Date Topic Assessment
8 Monday03/03/08 Review midterm
Wednesday03/05/08 [These will not happen here - this material has yet to be distributed down the calendar.]
7.1 Distribution shape
7.2 Pennies: The shape of randomness
Friday03/07/08 Quiz 6ods Middefs due
9 Monday03/10/08 7.3 The normal curve
Wednesday03/12/08 7.4 x to area 7.5 Area to x
Friday03/14/08 Quiz 7ods LDTWWW
10 Monday03/17/08 8.1 Distribution of Statistics8.2 Central Limit TheoremStandard error
Wednesday03/19/08 Easter break begins 2008
Friday03/21/08 Good friday
11 Monday03/24/08 9.1 Inference and point estimates
[Skip the material on confidence intervals for n ≥ 30; σ known; NORMINV function material]
Wednesday 03/26/08 9.2 Inferences and confidence intervals for 5 ≤ n ≤ 30; σ unknown. Also used for n ≥ 30.
Friday03/28/08 Quiz 08 (for reference only)ansods Test Twot2at2.ods
12 Monday03/31/08 Rahn en Tiahk
Wednesday04/02/08 9.3 Confidence intervals for a proportion 9.4 Sample Size
Friday04/04/08 Quiz 9 10.1q09a
13 Monday04/07/08 10.1 Hypothesis testing using confidence intervals Course selection
Wednesday04/09/08 10.2 Hypothesis testing
Friday04/11/08 q10 fish.ods
14 Monday04/14/08 10.3 p-value
Wednesday04/16/08 11.1 Paired differences t-test: Barefoot day II
Friday04/18/08 q11.ods
15 Monday04/21/08 11.2 Independent samples t-test
Wednesday04/23/08
Friday04/25/08 q12 Calibrians
16 Monday04/28/08
Wednesday04/30/08
Friday05/02/08 Probable review quiz
17 Monday05/05/08 Last day of instruction. Question & Answer session
TBATBA M08 Final at TBA (possibly 8:00) • fxdata.odsods
TBATBA M09 Final at TBA (possibly 8:00) • fxods

Do not alter the desktop settings, the screensaver, change color schemes, nor add nor delete panels to the computer desktop!

• Textbook: Introduction to Statistics Using OpenOffice.org Calc
• Recommended materials: Scientific calculator.
• Statistics office hours:TBA.
Instructor: Dana Lee Ling.
Email: dleeling@comfsm.fm cc: dana@mail.fm
Web site: http://www.comfsm.fm/~dleeling/statistics/statistics.html
Work: 320-2480 extension 228 / Home phone: 320-2962.
• Attendance: Seven absences results in withdrawal from the course. A late is one third of an absence. Thus any combination of absences and lates that adds to seven will result in withdrawal. For example, twenty-one lates would result in withdrawal.
• No betelnut in class nor on campus except in the cultural huts.
No spitting over the balcony!
• Quizzes are given every Friday that there is not a test. Quizzes and tests can and do occur on a Wednesday wherein Friday is a holiday.
Homework is worth 2 points and is checked at the start of the next class.
Quizzes are worth on the order of 7 to 19 points each, with an average of around 12 points.
Two tests are each worth 15 to 25 points.
The midterm fall 2007 was worth 34 points.
The final fall 2007 was worth 53 points.
Fall 2007 generated 343 total points.
No one quiz, test, midterm, nor even the final will have a large impact on your final grade. 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.
Points map to student learning outcomes via questions on publicly published quizzes, tests, and examinations wherein each question can be linked back to a course or program learning outcome.
• Statistics project: We all walk in an almost invisible sea of data. I walk into a school fair and notice a jump rope contest. The number of jumps for each jumper until they foul out is being recorded on the wall. Numbers. With a mode, median, mean, and standard deviation. Then I notice that faster jumpers attain higher jump counts than slower jumpers. I can begin to predict jump counts based on the starting rhythm of the jumper. I use my stopwatch to record the time and total jump count. I later find that a linear correlation does exist, and I am able to show by a t-test that the faster jumpers have statistically significantly higher jump counts. I later incorporate this data in the fall 2007 final.

I walked into a store back in 2003 and noticed that Yamasa soy saunce appeared to cost more than Kikkoman soy sauce. I recorded prices and volumes, working out the cost per milliliter. I eventually showed that the mean price per milliliter for Yamasa is higher than Kikkoman. I also ran a survey of students and determined that students prefer Kikkoman to Yamasa.

My son likes articulated mining dump trucks. I find pictures of Terex dump trucks on the Internet. I write to Terex in Scotland and ask them about how the prices vary for the dump trucks, explaining that I teach statistics. "Funny you should ask," a Terex sales representative replied in writing. "The dump trucks are basically priced by a linear relationship between horsepower and price." The representative included a complete list of horsepower and price.

One term I learned that a new Cascading Style Sheets level 3 color specification for hue, luminosity, and luminance was available for HyperText Markup Language web pages. The hue was based on a color wheel with cyan at the 180° middle of the wheel. I knew that Newton had put green in the middle of the red-orange-yellow-green-blue-indigo-violet rainbow, but green is at 120° in the rainbow. And there is no cyan in Newton's rainbow. Could the middle of the rainbow actually be at 180° cyan, or is it truly at 120° green? I used a hue analysis tool to analyze the image of an actual rainbow taken by a digital camera here on Pohnpei. This allowed an analysis of the true center of the rainbow.

While researching sakau consumption in markets here on Pohnpei I found differences in means between markets, and I found a variation with distance from Kolonia. I asked some of the markets to share their cup tally sheets with me, and a number of them obliged. The data proved interesting.

The point is that data is all around us all the time. You might not go into statistics professionally, yet you will always live in a world filled with numbers and data. For one sixteen week term period in your life I want you to walk with an awareness of the data around you. At midterm you will turn in a proposed ratio level data set with basic statistics. You pick the data - you decide on the sample. At term's end you will add a 95% confidence interval for your data set and turn in a final, completed project. The project will be marked on sample size (optimally n ≥ 30, minimally n ≥ 10), whether the sample is random or not, and on analysis factors. Other marking metrics may be announced as the term progresses. Details will be explained as the term unfolds.

For now, simply watch for numbers around you. See the matrix.

• Course outline: http://www.comfsm.fm/~dleeling/statistics/ms150_2007.html
• Academic Honesty Policy: Cheating on an assignment, quiz, test, midterm, or final will result in a score of zero for that assignment, quiz, or examination. 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...
1. Program Learning Outcomes:
Define mathematical concepts, calculate quantities, estimate solutions, solve problems, represent and interpret mathematical information graphically, and communicate mathematical thoughts and ideas.
2. Course Learning Outcomes:
1. Identify levels of measurement and appropriate statistical measures for a given level
2. Determine frequencies, relative frequencies, creating histograms and identifying their shape visually
3. Calculate basic statistical measures of the middle, spread, and relative standing
4. Perform linear regressions finding the slope, intercept, and correlation; generate predicted values based on the regression
5. Calculate simple probabilities for equally likely outcomes
6. Determine the mean of a distribution
7. Calculate probabilities using the normal distribution
8. Calculate the standard error of the mean
9. Find confidence intervals for the mean
10. Perform hypothesis tests against a known population mean using both confidence intervals and formal hypothesis testing
11. Perform t-tests for paired and independent samples using both confidence intervals and p-values