COURSE
SYLLABUS
Elements of Statistics
MAT 206
Marcos de Niza
Room
Number: 328
Instructor:
Author/Editor: Yates, Moore, and McCabe
Title: The
Practice of Statistics
Edition/Copyright: 3rd Edition, 1999
Publisher/Source: W.H. Freeman
ISBN #: 0-7167-3370-6
Prerequisites: Grade of "C" or better in Honors Pre
Calculus or equivalent.
Attendance: Regular attendance is important. Students are allowed 6 absences and may be
dropped from the course.
Grades: Cumulative Point
System – Standard Grading Scale
Grade
will be comprised approximately from:
Tests............................... 55%
Quizzes........................... 15%
Notebook....................... 15%
Computer Labs .............. 15%
Policy: 1. Expect a daily assignment.
2. Maintain a Class Notebook
a) Classroom examples – new concepts
b) Homework assignments
c) Computer Labs and quizzes
3. The due date for the notebooks is the
day of the chapter test.
4. A calculator is required.
5. You are responsible for any material
missed due to absences.
6. Do not be late.
7. Extra help – Daily before or after
school.
Disability Statement: The
College will make reasonable accommodations for persons with documented
disabilities. Students should notify
Student Services and their instructors of any special needs.
DISCLAIMER
Course content may vary from the
outline to meet the needs of this group.
COURSE DESCRIPTION – ELEMENTS of
STATISTICS
Basic
concepts and applications of statistics, including data description,
estimation, and hypothesis tests
COURSE OBJECTIVES/COMPETENCIES
STATISTICS
On
completion of this course, the student will be able to:
1. Identify the difference between descriptive and inferential statistics.
2. Distinguish between a population and a sample.
3. Group a set of data and present the grouping in graphical form.
4. Determine the mean, median, mode and standard deviation of data set and find the z-score for a data piece.
5. Define random variable and the probability distribution of a random variable.
6. Find probabilities for normal random variables by using the standard normal distribution.
7. Construct random samples.
8. Graph the sampling distribution of the mean for all sample sizes and all populations.
9. Find point and interval estimates of population means.
10. Describe the logic of hypothesis testing emphasizing the role of probability distributions and types of error.
11. Perform inferences about one mean in the case of normal populations or large sample size.
12. Perform inferences about two means in the case of normal populations or large sample size.
13. Use the Chi-square goodness-of-fit test to determine if two populations have the same shape.
14. Use the Chi-square independence test to determine whether two characteristics of a population are associated (dependent).
15. Identify the best-fitting regression line for a set of data points.
16. Partition the total sum of squares for a set of data points to find measures of regression line fit and linear relationship.
17. Use one-way analysis of variance to partition the total sum of squares in order to test for a difference among means.
18. Identify the difference between parametric and nonparametric statistics.
19. Demonstrate proper use of nonparametric procedures.