Math 200 – Probability and Statistics
Spring 2010 Section #41417
Online Format (MyStatLab: http://www.coursecompass.com/)
January 17, 2010 - May 24, 2010
Inessa Kazaryan, Ph D
January 25 in Bldg. 7 - 7310 at 7:10 PM.
MATH-200 Probability and Statistics
MATH 120 or 123 with grade C or better or two years of high school algebra with grades of
C or better with satisfactory placement test score and other measures as appropriate.
4 credits course transferable to University
; register (you need an access code for
which could be purchased at Skyline’s bookstore.) You have an option to either buy the textbook with this
code, or just buy the code and use the online textbook. The course ID which you need to register is
: This course will integrate graphing technology with the following topics:
random variables, hypothesis testing, confidence intervals, correlation, linear regression, small sample
methods and non-parametric statistics. In addition to using graphing technology, students will learn the
concepts through lecture, textbook (chapters 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 and 12), guided discovery, labs, and
Upon the completion of this course, the student should be able to:
Define population and sample.
Describe a set of quantitative data by computing measures of central tendency (mean, median, mode)
and measures of dispersion (range, variance, standard deviation).
Calculate probabilities using the addition law of probability, law of complement, multiplication law,
and conditional probability.
Solve probability problems using counting techniques.
Construct a probability distribution for a discrete random variable and compute the expected value
(mean), variance, and standard deviation of this distribution.
Construct a binomial probability distribution and compute the mean, variance and standard deviation.
Find probabilities using the z-tables (Z is a standard normal variable).
Use the Central Limit Theorem to find the mean and variance of the sampling distribution of the
Compute confidence intervals using the Z and t-distributions.
Use a hypothesis test to determine whether to accept or reject the null hypothesis: a statement,
assertion, or claim about the nature of a population.
Calculate the coefficient of linear regression (correlation coefficient) for bi-variate data.
Fit a least squares regression line to bi-variate data.