Spensin has asked me to explain more clearly my "threetier outline format." In a nutshell it is our current format plus the program level outcomes and mapping references. I lay out the MS 150 outline in both formats, sidebyside, below as an illustration.
Robert has an important point, it might not be necessary for every outline to carry the program level outcomes. I put them in because I intend to measure those from the "bottom up." I will later assert I have accomplished my program outcomes by accomplishing the course and specific objectives below. Hence I need the mapping to be explicitly visible. Other divisions may choose to independently measure their program level outcomes. They would not need to put their program level outcomes on every outline.
I should also note that the PE outline is not in a threetier format and will not be moved to one. The course is simply not that complex. The PE outline consists of program level outcomes and specific outcomes only.
Note that the head and tail ends of two outlines are identical, only the differing parts are sidebysided below.
College of MicronesiaFSM
MS 150 Statistics
Course Description: A semester course designed as an introduction to the basic ideas of data presentation, descriptive statistics, and inferential statistics including confidence intervals and hypothesis testing. The course incorporates the use of a computer spreadsheet package, Microsoft Excel, for both data analysis and presentation. Basic concepts are studied using applications from business, social science, health science, and the natural sciences.
Hours per week: 3
Number of weeks: 16
Semester credits: 3
Prerequisite course: MS 100 College Algebra
The order of the sections is not intended to reflect the chronological order of topics.
Three Tier 
Current format 
 Program Outcomes
Students will be able to:
 define arithmetic, algebraic, geometric, spatial, and statistical concepts
 calculate arithmetic, algebraic, geometric, spatial, and statistical quantities using appropriate technology.
 estimate arithmetic, algebraic, geometric, spatial, and statistical solutions
 solve arithmetic, algebraic, geometric, spatial, and statistical expressions, equations, functions, and problems using appropriate technology.
 represent mathematical information numerically, symbolically, graphically, verbally, and visually using appropriate technology.
 develop mathematical and statistical models such as formulas, functions, graphs, tables, and schematics using appropriate technology.
 interpret mathematical and statistical models such as formulas, functions, graphs, tables, and schematics, drawing conclusions and making inferences based on those models.
 explore mathematical systems utilizing rich experiences that encourage independent, nontrivial, constructive exploration in mathematics.
 communicate mathematical thoughts and ideas clearly and concisely to others in the oral and written form.

Not in current format 
 Course Outcomes
Students will be able to:
 Calculate basic statistics (define, calculate)
 Represent data sets using histograms (define, calculate, estimate, represent)
 Solve problems using normal curve and tstatistic distributions including confidence intervals for means and hypothesis testing (define, calculate, solve, interpret)
 Determine and interpret pvalues (calculate, interpret)
 Perform a linear regression and make inferences based on the results (define, calculate, solve, interpret)

 General Objectives
Students will be able to:
 Calculate basic statistics
 Represent data sets using histograms
 Solve problems using normal curve and tstatistic distributions including confidence intervals for means and hypothesis testing
 Determine and interpret pvalues
 Perform a linear regression and make inferences based on the results

 Specific outcomes
Students will be able to:
Given one variable data and the use of a calculator or spreadsheet software on a computer
 Calculate basic statistics
 [Peri] Distinguish between a population and a sample (define)
 [Peri] Distinguish between a statistic and a parameter (define)
 [Peri] Identify different levels of measurement when presented with nominal, ordinal, interval, and ratio data. (define)
 [Core] Determine a sample size (calculate)
 [Core] Determine a sample minimum (calculate)
 [Core] Determine a sample maximum (calculate)
 [Core] Calculate a sample range (calculate)
 [Core] Determine a sample mode (calculate)
 [Core] Determine a sample median (calculate)
 [Core] Calculate a sample mean (calculate)
 [Core] Calculate a sample standard deviation (calculate)
 [Core] Calculate a sample coefficient of variation (calculate)
 Represent data sets using histograms
 [Core] Calculate a class width given a number of desired classes (calculate)
 [Core] Determine class upper limits based on the sample minimum and class width (calculate)
 [Core] Calculate the frequencies (calculate)
 [Core] Calculate the relative frequencies (probabilities) (calculate)
 [Peri] Create a frequency histogram based on calculated class widths and frequencies (represent)
 [Core] Create a relative frequency histogram based on calculated class widths and frequencies (represent)
 [Core] Identify the shape of a distribution as being symmetrical, uniform, bimodal, skewed right, skewed left, or normally symmetric. (define)
 [Peri] Estimate a mean from class upper limits and relative frequencies using the formula Sx*P(x) here the probability P(x) is the relative frequency. (estimate)
 Solve problems using normal curve and tstatistic distributions including confidence intervals for means and hypothesis testing
 [Peri] Discover the normal curve through a coursewide effort involving tossing seven pennies and generating a histogram from the inclass experiment. (develop)
 [Peri] Identify by characteristics normal curves from a set of normal and nonnormal graphs of lines. (define)
 [Core] Determine a point estimate for the population mean based on the sample mean (calculate)
 [Peri] Calculate a zcritical value from a confidence level (calculate)
 [Core] Calculate a tcritical value from a confidence level and the sample size (calculate)
 [Core] Calculate an error tolerance from a tcritical, a sample standard deviation, and a sample size. (calculate)
 [Peri] Solve for a confidence interval based on a confidence level, the associated zcritical, a sample standard deviation, and a sample size where the sample size is equal or greater than 30. (solve)
 [Core] Solve for a confidence interval based on a confidence level, the associated tcritical, a sample standard deviation, and a sample size where the sample size is less than 30. (solve)
 [Core] Use a confidence interval to determine if the mean of a new sample places the new data within the confidence interval or is statistically significantly different. (interpret)
 Determine and interpret pvalues
 [Core] Calculate the twotailed pvalue using a sample mean, sample standard deviation, sample size, and expected population mean to to generate a tstatistic. (calculate)
 [Peri] Infer from a pvalue the largest confidence interval for which a change is not significant. (interpret)
Given two variable data and the use of spreadsheet software on a computer
 Perform a linear regression and make inferences based on the results
 [Core] Identify the sign of a least squares line: positive, negative, or zero. (Define)
 [Core] Calculate the slope of the least squares line. (Calculate)
 [Core] Calculate the intercept of the least squares line. (Calculate)
 [Core] Solve for a y value given an x value and the slope and intercept of a least squares line. (Solve)
 [Core] Solve for a x value given an y value and the slope and intercept of a least squares line. (Solve)
 [Core] Calculate the correlation coefficient r. (Calculate)
 [Core] Use a correlation coefficient r to render a judgment as to whether a correlation is perfect, high, moderate, low, or none. (Interpret)
 [Core] Calculate the coefficient of determination r². (Calculate)

 Specific objectives
Students will be able to:
 Calculate basic statistics
 Distinguish between a population and a sample
 Distinguish between a statistic and a parameter
 Identify different levels of measurement when presented with nominal, ordinal, interval, and ratio data.
 Determine a sample size
 Determine a sample minimum
 Determine a sample maximum
 Calculate a sample range
 Determine a sample mode
 Determine a sample median
 Calculate a sample mean
 Calculate a sample standard deviation
 Calculate a sample coefficient of variation
 Represent data sets using histograms
 Calculate a class width given a number of desired classes
 Determine class upper limits based on the sample minimum and class width
 Calculate the frequencies
 Calculate the relative frequencies (probabilities)
 Create a frequency histogram based on calculated class widths and frequencies
 Create a relative frequency histogram based on calculated class widths and frequencies
 Identify the shape of a distribution as being symmetrical, uniform, bimodal, skewed right, skewed left, or normally symmetric.
 Estimate a mean from class upper limits and relative frequencies using the formula Sx*P(x) here the probability P(x) is the relative frequency.
 Solve problems using normal curve and tstatistic distributions including confidence intervals for means and hypothesis testing
 Discover the normal curve through a coursewide effort involving tossing seven pennies and generating a histogram from the inclass experiment.
 Identify by characteristics normal curves from a set of normal and nonnormal graphs of lines.
 Determine a point estimate for the population mean based on the sample mean
 Calculate a zcritical value from a confidence level
 Calculate a tcritical value from a confidence level and the sample size
 Calculate an error tolerance from a tcritical, a sample standard deviation, and a sample size.
 Solve for a confidence interval based on a confidence level, the associated zcritical, a sample standard deviation, and a sample size where the sample size is equal or greater than 30.
 Solve for a confidence interval based on a confidence level, the associated tcritical, a sample standard deviation, and a sample size where the sample size is less than 30.
 Use a confidence interval to determine if the mean of a new sample places the new data within the confidence interval or is statistically significantly different.
 Determine and interpret pvalues
 Calculate the twotailed pvalue using a sample mean, sample standard deviation, sample size, and expected population mean to to generate a tstatistic.
 Infer from a pvalue the largest confidence interval for which a change is not significant.
 Perform a linear regression and make inferences based on the results
 Identify the sign of a least squares line: positive, negative, or zero.
 Calculate the slope of the least squares line.
 Calculate the intercept of the least squares line.
 Solve for a y value given an x value and the slope and intercept of a least squares line.
 Solve for a x value given an y value and the slope and intercept of a least squares line.
 Calculate the correlation coefficient r.
 Use a correlation coefficient r to render a judgment as to whether a correlation is perfect, high, moderate, low, or none.
 Calculate the coefficient of determination r².

Course Intentions
 Use of Microsoft Excel and Microsoft Excel functions throughout the course as opposed to using dedicated statistics software package. Excel and other spreadsheets will be the desktop software most widely available to MS 150 students both while taking the course and, more importantly, in the workplace postgraduation.
 Use of realworld data, examples, and problems to the extent appropriate and possible.
Assessment
Assessment will be via quizzes, tests, midterm examinations and a final examination. All core outcomes will appear on the final examination.
Notes
[Core] outcomes are tested on the cumulative final examination and preceding quizzes, tests, and midterm examinations. Students must successfully achieve core outcomes at some point in the term in order to pass the class.
[Peri] outcomes are tested during the course and may appear on the final. Their achievement is used to distinguish levels of skill above a minimal pass.
The above format maps the course outcomes to the program outcomes using a reference in parentheses at the end of each outcome.
The student learning outcomes can also be used, at the instructor's option, chronologically, although it need not necessarily be used in the order given.
 Textbook: Understanding Basic Statistics, Second Edition, Brase and Brase, Houghton Mifflin, 2001
 Required course materials: Inclass access to a computer with Microsoft Excel.
 Reference materials
 Microsoft Excel spreadsheet mathematical software by Microsoft.
 "Data Analysis with Microsoft Excel", Berk and Carey, Duxbury Press, 1998
 "Statistics: A First Course", 6th ed. by Freund and Simon, Prentice Hall, Inc. 1995 (ISBN 0130830240),
 "Elementary Statistics." 6th ed. by Johnson, PVVSKENT Pub., 1992 (ISBN 053492980X)
 Instructional costs: None anticipated at this time
 Methods of Instruction: The course will be taught by lecture, class discussion, and the use of Microsoft Excel for problem solving and computer simulations. This course will be taught in the Math/Science computer classroom. Also, students will be encouraged to utilize the computer labs outside of class for homework assignments.
 Evaluation: Homework, tests, quizzes, a midterm, and a final exam will be given. A standard 90%=A, 80%=B, 70%=C, 60%=D Below 60%=F grading scale is recommended pending the outcome of futher discussion on the overall meaning of grading in a student learning outcome centered environment.
 Credit by examination: None
 Attendance policy: As per the current college catalog
Appendix A
Further reading and background on the structure of this outline:
http://shark.comfsm.fm/~dleeling/department/slorevolution.html
http://shark.comfsm.fm/~dleeling/department/slorevolution_ii.html
http://shark.comfsm.fm/~dleeling/department/slorevolution_iii.html
http://shark.comfsm.fm/~dleeling/department/dnsm_program_outcomes.html
http://shark.comfsm.fm/~dleeling/department/slorevolution_v.html
http://shark.comfsm.fm/~dleeling/department/slorevolution_vi.html
http://shark.comfsm.fm/~dleeling/department/systemwidecompetencies.html