College of Micronesia-FSM
MS 150 Statistics
Course Description: A semester course designed as an introduction to the
basic ideas of data presentation, descriptive statistics, linear regression, and
inferential statistics including confidence intervals and hypothesis testing.
Basic concepts are studied using applications from education, business, social
science, and the natural sciences. The course incorporates the use of a computer
spreadsheet package for both data analysis and presentation. The course is
intended to be taught in a computer laboratory environment.
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.
- Mathematics 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.
- General Objectives
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 t-statistic distributions
including confidence intervals for means and hypothesis testing (define, calculate, solve, interpret)
- Determine and interpret p-values (calculate,
interpret)
- Perform a linear regression and make inferences based on the results
(define, calculate, solve, interpret)
- Specific Objectives
Students will be able to:
Given one variable data and the use of a
calculator or spreadsheet software on a computer
- Calculate basic statistics
- Distinguish between a population and a sample (define)
- Distinguish between a statistic and a parameter (define)
- Identify different levels of measurement when presented with nominal,
ordinal, interval, and ratio data. (define)
- Determine a sample size (calculate)
- Determine a sample minimum (calculate)
- Determine a sample maximum (calculate)
- Calculate a sample range (calculate)
- Determine a sample mode (calculate)
- Determine a sample median (calculate)
- Calculate a sample mean (calculate)
- Calculate a sample standard deviation (calculate)
- Calculate a sample coefficient of variation (calculate)
- Represent data sets using histograms
- Calculate a class width given a number of desired classes (calculate)
- Determine class upper limits based on the sample minimum and class
width (calculate)
- Calculate the frequencies (calculate)
- Calculate the relative frequencies (probabilities) (calculate)
- Create a frequency histogram based on calculated class widths and
frequencies (represent)
- Create a relative frequency histogram based on calculated class widths
and frequencies (represent)
- Identify the shape of a distribution as being symmetrical, uniform,
bimodal, skewed right, skewed left, or normally symmetric. (define)
- 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 t-statistic distributions
including confidence intervals for means and hypothesis testing
- Discover the normal curve through a course-wide effort involving
tossing seven pennies and generating a histogram from the in-class
experiment. (develop)
- Identify by characteristics normal curves from a set of normal and
non-normal graphs of lines. (define)
- Determine a point estimate for the population mean based on the sample
mean (calculate)
- Calculate a z-critical value from a confidence level (calculate)
- Calculate a t-critical value from a confidence level and the sample
size (calculate)
- Calculate an error tolerance from a t-critical, a sample standard
deviation, and a sample size. (calculate)
- Solve for a confidence interval based on a confidence level, the
associated z-critical, a sample standard deviation, and a sample size
where the sample size is equal or greater than 30. (solve)
- Solve for a confidence interval based on a confidence level, the
associated t-critical, a sample standard deviation, and a sample size
where the sample size is less than 30. (solve)
- 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 p-values
- Calculate the two-tailed p-value using a sample mean, sample standard
deviation, sample size, and expected population mean to to generate a
t-statistic. (calculate)
- Infer from a p-value 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
- Identify the sign of a least squares line: positive, negative, or
zero. (Define)
- Calculate the slope of the least squares line. (Calculate)
- Calculate the intercept of the least squares line. (Calculate)
- Solve for a y value given an x value and the slope and intercept of a
least squares line. (Solve)
- Solve for a x value given an y value and the slope and intercept of a
least squares line. (Solve)
- Calculate the correlation coefficient r. (Calculate)
- Use a correlation coefficient r to render a judgment as to whether a
correlation is perfect, high, moderate, low, or none. (Interpret)
- Calculate the coefficient of determination r˛. (Calculate)
Course Intentions
- Use of Microsoft Excel and Microsoft Excel functions (or
spreadsheet software with equivalent statistical 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 post-graduation.
- Use of real-world 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
The above format maps the course outcomes to the program outcomes using a
reference in parentheses at the end of each outcome.
- Textbook: Understanding
Basic Statistics, Second Edition, Brase and Brase, Houghton Mifflin,
2001
- Required course materials: In-class access to a computer with Microsoft
Excel or spreadsheet software with equivalent statistical functions.
- Reference materials
- Microsoft Excel spreadsheet software by Microsoft or OpenOffice.org Calc
software.
- "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 0-13-083024-0),
- "Elementary Statistics." 6th ed. by Johnson, PVVS-KENT Pub., 1992 (ISBN
0-534-92980-X)
- Instructional costs: None anticipated at this time
- Methods of Instruction: The course will be taught by lecture, class
discussion, and the use of spreadsheet software for problem solving and
computer simulations. This course will be taught in a computer laboratory
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.
- 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
http://shark.comfsm.fm/~dleeling/department/ms150goso.html
http://shark.comfsm.fm/~dleeling/department/ms150sidebyside.html