7a. Prerequisite(s): (Course and/or other preparation/experience that is REQUIRED to be completed previous to enrollment in this course.)

Two years of high school algebra or Math. D or equivalent with a grade of "C" or better, or placement by matriculation assessment process

7b. Co-requisite(s):  (Courses and/or other preparation that is REQUIRED to be taken concurrently with this course.)

7c. Advisory: (Minimum preparation RECOMMENDED in order to be successful in this course.  Also known as “Course Advisory”.)

9b. Catalog Description:

Introductory course in probability and statistics, including descriptive statistics, techniques and principles of counting, probability, inferential statistics; and use of statistical computer software or statistical graphics calculator. Specific calculator required for course will be purchased by students. (CAN STAT 2)

10. Student Performance Outcomes: (Outcomes for all credit courses must indicate that students will learn critical thinking and will be able to apply concepts at college level.  Outcomes must be related to items listed in Section 11.)

Through homework assignments, quizzes, exams, projects and classroom
discussions, the student will:
1. summarize data by constructing a frequency table and a histogram;
2. calculate and interpret descriptive statistics, and measures of
central tendency, measures of dispersion, and measures of position;
3. calculate probabilities for simple and compound events;
4. determine whether events are independent or mutually exclusive;
5. calculate conditional probabilities;
6. determine probabilities through simulations;
7. calculate probabilities for discrete random variables with
binomial or Poisson probability distributions;
8. calculate the mean, variance, and standard deviation for the
binomial distribution;
9. calculate areas under the standard normal curve;
10. calculate probabilities for continuous random variables with a
non-standard normal distribution;
11. approximate the binomial distribution with the normal curve when
appropriate;
12. apply the Central Limit Theorem to determine probabilities
concerning the mean of a sample;
13. calculate confidence intervals for a population mean for either
large or small sample sizes;
14. calculate a confidence interval to estimate a binomial
proportion;
15. calculate a confidence interval to estimate a population
variance (time permitting);
16. use an appropriate hypothesis test to test a claim about a
population mean, a population variance (or standard deviation), a
population proportion, a difference of population means (large and
small samples), and a difference of population proportions;
17. draw a scatter diagram for a set of paired data;
18. calculate the correlation coeficient for a set of paired data;
19. use a hypothesis test to determine whether or not a correlation
coefficient is significant (time permitting);
20. calculate the regression equation for a set of paired data;
21. perform chi-square goodness of fit tests for multinomial
experiments (time permitting);
22. utilize statistical software and/or a statistical graphics
calculator to display and calculate; and
23. analize and interpret accurately the results and output of
computer software and or graphics calculator.

11. Course Content Outline: (Provides a comprehensive, sequential outline of the course content, including all major subject matter and the specific body of knowledge covered.)

I. Instruction in the Use of the Computer Software and/or the
Graphics Calculator Will Occur Throughout the Course
II. Descriptive Statistics
A. Graphical Representation
B. Frequency Tables
C. Exploratory Data Analysis
D. Measures of Central Tendency
E. Measures of Dispersion
F. Measures of Position
G. Empirical Rule
H. Chebychev''s Theorem
III. Counting and Probability
A. Principles of Counting Including Combinations and
Permutations
B. Introduction to Probability-Classical and Frequency
Approach
C. Introduction to Stochastic Simulation
D. Discrete Random Variables and Probability Distributions
Including Binomial and Poisson Distributions
1. mean, variance and standard deviation of discrete
probability distributions
IV. Normal Distribution and the Central Limit Theorem
A. Continuous Random Variables Including the Normal
Distribution
B. Central Limit Theorem
C. Normal Approximation to the Binomial Distribution
V. Inferential Statistics
A. Estimation, Large and Small Samples
1. point estimates
2. confidence intervals
3. determination of sample size
B. Hypothesis Testing
1. single mean, large and small samples
2. difference of means, large and small samples
3. single proportion
4. difference of two proportions
5. single variance
6. equality of variances
7. contingency tables and goodness of fit tests
C. Regression and Correlation
1. linear correlation coefficient
2. linear regression model
3. forecasting
4. related hypothesis testing
D. Nonparametric Methods
E. One Way Analysis of Variance

12. Typical Assignments: (Credit courses require two hours of independent work outside of class per unit of credit for each lecture hour. List types of assignments, including library assignments.)

a. Reading Assignments: (Submit at least 2 examples)

b. Writing, Problem Solving or Performance: (Submit at least 2 examples)

c. Other (Terms projects, research papers, portfolios, etc.)

SECTION D

SECTION E

SECTION F

SECTION G