MATH 219 Syllabus

Course Introduction Video

 

Below in an outline of the course syllabus.  You can download the complete syllabus using the link below.

Course Syllabus: Math 219 Full PDF Course Syllabus

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Meet Your Instructor: 

Instructor Name: Dr. Marty Romero

Phone: (714) 564-6640

Email: romero_martin@sac.edu

Office Location: H102-3

 

Course Description: 

Beginning course in statistics. Includes descriptive statistics, graphical displays of data, probability, confidence intervals, hypothesis testing, regression, contingency tables, ANOVA, and non-parametric statistics. Includes use of technology.

Textbook Information: 

Statistics, Informed Decisions Using Data, 5th Edition, Michael Sullivan III

Student Edition:   0-13-413353-6

Course Policies: 

Expectations

This is a college level course. College credits are based on the Carnegie Unit, the structure of the US Education system, for a system of “units”. One semester unit represents one lecture hour of required classroom time and two hours of student preparation time. Thus, our four unit course requires, 4 lecture hours and 8 hours student preparation, or a total of approximately 12 hours per week needs to be spent working on this class. Make sure you have to time to be successful.

 

Attendance

I will be taking roll during each course meeting. Attending every class is required and important for your success. Remember there are no make-up assignments, tests and quizzes. If you are absent, you are responsible for getting any class announcements and updates, and turning in any assignments that are due. Remember, any student missing the first day of class will be dropped. Any student absent 4 times during the semester may be dropped.

Tardiness

Any student missing 30 or more minutes of class (start and/or end of class) will be marked absent, unless your missing time is cleared with me prior to class beginning. The best way to do this is via email.

Classroom Behavior

Students are expected to actively participate by following class rules, being on time, having materials, answering and asking appropriate math questions, presenting solutions to the class, and helping others. Students are not expected to distract or disrupt their peers. All cellular phones or other technological devices must be put away and put on silent at the beginning of class. If you need to leave the classroom during class, please do so quietly without disturbing others.

Course Assignments

MyLab Statistics (MLS) Homework

Homework: Section assignments are assigned on the course schedule and due dates are shown in MLS (1-2 Point/Problem). Online help features available to assist, you may redo any problem as many times as you would like to before due date. 25% will be deducted for late homework .

 

Textbook Homework

Selected problems from textbook will be assigned after we complete a lesson. Your solutions to those problems will be due at the beginning of the next class. If you are late or not present when homework is discussed, graded, and collected, it will not be accepted.   Homework grade is determined by three things and worth 100 points: (Full Completion and effort, Correcting your homework before class, Participating in group discussion and reflection in class). Keep in mind that solutions are provided a head of time, 20 points will be deducted if you do not self-correct your homework using the posted solutions and 10 points will be deducted if you do not complete the reflection. PLEASE BE NEAT AND ORGANIZED WITH YOUR WORK, USE STANDARD SIZE PAPER AND MAKER SURE EVERYTHING IS LABLED AND FOLLOWS THE FORMAT BELOW. ILLEGIBLE WORK WILL NOT BE SCORED.

* Three (3) of your lowest written homework assignments will be dropped. NO LATE HOMEWORK IS ACCEPTED

Out of Class Written Assignments/ Collaborative Assignments / Technology (Mini) Projects

During class time I will design learning activities where you engage in the act of doing and learning statistics beyond rote memorization and procedures. It is my belief you understand statistics better and are able remember which procedures to apply when you discover statistical concepts on your own or with others. These assignments may need to be completed at home, but the goal is to have them done in class. You must be present in class to complete assignments. Some of the projects will integrate StatCrunch since when statistics is done in the real world, most statisticians use technology. No Make-ups.

(Points will vary)

Course Quizzes/Exams/Final

Exams

There will be 4 exams throughout the course that is broken up into two parts: Part 1 is completed in class and consists of show-your-work questions, and Part 2 is done online and consist of questions chosen from your online homework. Part 2 is done out of class, but you cannot get assistance or work collaboratively on the Part 2. There are no make-up Tests. Part 1 has a time limit of 1-hour and Part 2 will have a 2-hour time limit.

 

Quizzes

There will be 4 quizzes throughout the course that will be based off Statistical Articles, Podcasts, and Videos. You will find them posted on Canvas.

Final

The final exam will cover Chapters 1-13 and be given during the last class meeting. It will contain both multiple-choice and free-response questions. There are no make-up Final exams. (*Your Final Exam percentage will be averaged with your lowest exam percentage to REPLACE your LOWEST EXAM PERCENTAGE, this is only if your Final Exam score is higher than your lowest exam score and you have 70% or above on your online homework)

Class Materials

Pencil, Paper, Eraser, Binder, Calculator (TI-36, TI-30, TI-83, or TI-84), (No Cell Phone Calculator or Computer on Tests), Ruler

Grading

• Online Homework: 15%
• Textbook Homework / Out of Class Written Assignments / Collaborative Assignments / Technology (Mini) Projects: 10%
• Quizzes (Article / Podcast Responses, Kaggle.com): 15%
• Tests: 40%
• Final: 20%

A: 90% and Above     B: 80%-89.9%               C: 70%-79.9%   D: 60%-69.9%   F: Below 60%

Student Learning Objectives:  

1. By the end of the semester students will correctly interpret a graphical display of data.
2. By the end of the semester students will take a statistical claim about a data set, perform an appropriate procedure, and write a conclusion that addresses that claim.