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Revision Date: 22-May-17

MAT-2021-VR02 - Statistics I


Synonym: 154380
Location: Rutland
Credits: 3 (45 hours)
Day/Times: Thursday, 05:30P - 09:00P
Semester Dates: 05-25-2017 to 08-10-2017
Last day to drop without a grade: 06-12-2017
Last day to withdraw (W grade): 07-10-2017
Faculty: Jay Wilson | View Faculty Credentials

This course has started, please contact the offering academic center about registration

Browse the Moodle Site for this class.

Course Description:

An introduction to the basic ideas and techniques of probability and statistics. Topics may include numerical and graphical descriptive measures, probability, random variables, the normal distribution, sampling theory, estimation, hypothesis testing, correlation and regression. The use of technology may be required. Students must take a math assessment for placement purposes prior to registration.

Essential Objectives:

1. Outline the general development of statistical science, and list a number of common applications of statistical methodology.
2. Distinguish between descriptive and inferential statistics.
3. Create and apply various techniques used to describe data, such as pie charts, bar graphs, frequency tables, and histograms.
4. Define three common measures of central tendency (mean, median, and mode), and demonstrate the ability to calculate each manually from a series of small data sets.
5. Describe common methods of measuring variability, including range, percentiles, variance, and standard deviation, and calculate each from a series of small data sets.
6 Explain the Normal Probability Distribution, techniques of sampling, the Central Limit Theorem, and the concept of standard error, and compute probabilities associated with normally distributed samples.
7. Test hypotheses about the value of the mean assuming the normal distribution and large sample results.
8. Select and perform common statistical tests including one- and two-tailed tests.
9. Define linear regression and correlation and discuss their applications
10. Interpret and evaluate the validity of statistical data and reports.
11. Demonstrate proficiency in understanding, interpreting, evaluating and applying quantitative data and information.

Additional Instructor Pre-Assignments/Notes/Comments:

PRE-ASSIGNMENTS/COMMENTS:

INSTRUCTOR:  JAY WILSON

 

CONTACT:  DAYTIME PHONE:  1-802-345-7462

                      EMAIL:  JXW04220@CCV.VSC.EDU

                                      PJKSCW@HOTMAIL.COM

                      GENERAL PHONE FOR THIS SITE:  1-802-786-6996

 

 

                      ****EXTRA HELP OFFERED…BY APPOINTMENT PLEASE****

 

CLASS EXPECTATIONS:  ATTENDANCE, ATTENTION, ATTITUDE, LUL

 

CELL PHONES:  CELL PHONES ARE A DISTRACTION IN THE CLASSROOM; PLEASE TURN THEM OFF DURING CLASS TIME.

 

3 RING BINDER:  A MUST

 

CALUCULATORS

 

A GRAPHING CALCULATOR IS REQUIRED. THE INSTRUCTOR WILL BE USING A TI-84 PLUS GRAPHING CALCULATOR. A TI - 83 PLUS GRAPHING CALCULATORS OR ANY HIGHER VERSION OF THE TI SERIES IS THE RESPONSIBILITY OF THE STUDENT AND WILL BE USED DURING EVERY CLASS PERIOD.

 

TEXTBOOK...NO TEXTBOOK IS REQUIRED FOR THIS COURSE

 

Evaluation Criteria:

EVALUATION CRITERIA: 

 

                                    ATTENDANCE/PARTICIPATION - 10%

                                    HOMEWORK – 20%

                                    QUIZZES – 25%

                                    EXAMS (2) - 45%

                                   

Grading Criteria:

GRADING CRITERIA:

              A   90 - 100   AVERAGE AND AT LEAST 10 CLASSES ATTENDED

              B   80 - 89     AVERAGE AND AT LEAST 9 CLASSES ATTENDED

              C   70 - 79     AVERAGE AND AT LEAST 8 CLASSES ATTENDED

              D   60 - 69     AVERAGE AND AT LEAST 8 CLASSES ATTENDED

              N   0 – 59      AVERAGE OR FEWER THAN 8 CLASSES ATTENDED

Textbooks:

Summer 2017 textbook data will be available on April 1. On that date a link will be available below that will take you to eCampus, CCV's bookstore. The information provided there will be for this course only. Please see this page for more information regarding the purchase of textbooks.

MAT-2021-VR02 Textbooks.

Texas Instruments® TI-84 Plus Silver Edition Graphing Calculator, ISBN: 8780000100116, Ecampus Depot   $155.18

Attendance Policy:

ATTENDANCE:  BECAUSE PROMPTNESS AND ATTENDANCE ARE KEY    COMPONENTS IN THIS CLASS, BOTH IMPACT THE GRADE YOU RECEIVE.  IF YOU ARE GOING TO BE TARDY OR ABSENT, PLEASE CONTACT ME DIRECTLY OR CALL THE GENERAL PHONE NUMBER FOR THIS SITE.

Contact Faculty:

Email: Jay Wilson
Hiring Coordinator for this course: Virginia Gellman

Syllabus:


SYLLABUS

 

 

WEEK1 

 

INTRODUCTION/EXPECTATIONS

 

CLASS DISCUSSION: 

CHAPTER1

            TOPICS TO INCLUDE:  DESCRIPTIVE/INFERENTIAL STATISTICS, TYPES OF VARIABLES, DATA COLLECTION AND SAMPLING TECHNIQUES, OBSERVATIONAL/EXPERIMENTAL STUDIES, COMPUTERS AND CALCULATORS

            CHAPTER 2

            TOPICS TO INCLUDE:  ORGANIZING DATA, HISTOGRAMS, FREQUENCY POLYGONS, OGIVES, TIME PLOTS, PIE GRAPHS, STEM PLOTS, PAIRED DATA AND SCATTERPLOTS

 

TAKE HOME QUIZ 1  

 

WEEK 2

 

 

CLASS DISCUSSION: 

            CHAPTER 3

            TOPICS TO INCLUDE:  MEASURES OF CENTRAL TENDENCY, MEASURES OF VARIATION, MEASURES OF POSITION, AND EXPLORATORY DATA ANALYSIS

 

TAKE HOME QUIZ 2

 

WEEK 3

 

 

CLASS DISCUSSION:

            CHAPTER 4

            TOPICS TO INCLUDE:  SAMPLE SPACES AND PROBABILITY, THE ADDITION RULES OF PROBABILITY, MULTIPLICATION RULES AND CONDITIONAL PROBABILITY, COUNTING RULES, PROBABILITY AND THE COUNTING RULES

 

TAKE HOME QUIZ 3

 

 

WEEK 4

 

 

CLASS DISCUSSION:

            CHAPTER 5

            TOPICS TO INCLUDE:  PROBABILITY DISTRIBUTIONS, MEAN, VARIANCE, STANDARD DEVIATION, EXPECTATION, BINOMIAL DISTRIBUTION 

 

TAKE HOME QUIZ 5

 

 

WEEK 5

 

CLASS DISCUSSION:  REVIEW FOR MID TERM/WILD CARD CLASS

 

 

WEEK 6  

CLASS DISCUSSION:  LAST MINUTE REVIEW FOR MID TERM

 

MID TERM EXAM (CHAPTERS 1-5)

 

        

 

WEEK 7

 

CLASS DISCUSSION:  MID TERM EXAM RESULTS

            CHAPTER 6:

            TOPICS TO INCLUDE:  PROPERTIES OF A NORMAL DISTRIBUTION, STANDARD NORMAL DISTRIBUTION, APPLICATIONS OF THE NORMAL DISTRIBUTION, CENTRAL LIMIT THEOREM, NORMAL APPROXIMATION TO THE BINOMIAL DISTRIBUTION

 

TAKE HOME QUIZ 6

 

             

WEEK 8 

            

  

CLASS DISCUSSION: 

            CHAPTER 7 

         TOPICS TO INCLUDE:  CONFIDENCE INTERVALS FOR THE MEAN AND SAMPLE SIZE, CONFIDENCE INTERVALS AND SAMPLE SIZE FOR PROPORTIONS, CONFIDENCES INTERVALS FOR VARIANCES AND STANDARD DEVIATIONS

 

TAKE HOME QUIZ 7

             

 

WEEK 9 

 

 

CLASS DISCUSSION: 

            CHAPTER 8

            TOPICS TO INCLUDE:  STEPS IN HYPOTHESIS TESTING-TRADITIONAL METHOD, z TEST FOR A MEAN, t TEST FOR A MEAN, z TEST FOR PROPORTIONS, CHI SQUARE TEST, CONFIDENCE INTERVALS AND HYPOTHESIS TESTING

 

TAKE HOME QUIZ 8

           

WEEK 10 

 

 

CLASS DISCUSSION: 

            CHAPTER 9

            TOPICS TO INCLUDE:  TESTING THE DIFFERENCE BETWEEN TWO MEANS, TESTING THE DIFFERENCE BETWEEN TWO VARIANCES, AND TESTING THE DIFFERENCE BETWEEN TWO PROPORTIONS

 

TAKE HOME QUIZ 9

 

 

 WEEK 11

 

 

CLASS DISCUSSION: 

            CHAPTER 10

            TOPICS TO INCLUDE:  CORRELATION, REGRESSION, COEFFICIENT OF DETERMINATION, AND STANDARD ERROR OF THE MEASUREMENT

 

REVIEW FOR EXAM

 

 

WEEK 12

  

CLASS DISCUSSION:  FINAL EXAM (CHAPTERS 6-10)

           

 

Please note: In order to receive accommodations for disabilities in this course, students must make an appointment to see the Americans with Disabilities Coordinator in their site and bring documentation with them.

Academic Honesty: CCV has a commitment to honesty and excellence in academic work and expects the same from all students. Academic dishonesty, or cheating, can occur whenever you present -as your own work- something that you did not do. You can also be guilty of cheating if you help someone else cheat. Being unaware of what constitutes academic dishonesty (such as knowing what plagiarism is) does not absolve a student of the responsibility to be honest in his/her academic work. Academic dishonesty is taken very seriously and may lead to dismissal from the College.

Course description details subject to change. Please refer to this document frequently.

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