# MA120 Basic Concepts of Statistics

## for F2F 2008

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| MA 120 Basic Concepts of Statistics |

| F2F 2008 HE |

| Ogilvy, Tom |

| Adjunct Faculty |

| BS General Engineering, United States Military Academy |

| Ft Myers Education Center |

| By Appointment |

| 703.614.1228 |

| 703.425.5596 |

| |

| 13 Oct - 14 Dec 2008 |

| ---W--- |

| 5:00 - 10:00 PM |

| 3 |

**Textbook:**

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**Additional Resources:**

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**Course Description:**

A development of certain basic concepts in probability and statistics that is pertinent to most disciplines. Topics include: probability models, parameters, statistics and sampling procedures, hypothesis testing, correlation and regression. 3:0:3

**Educational Philosophy:**

This is an interactive course based on lectures and readings to develop problem solving skills. Students will be evaluated on class participation, midterm and final exam.

**Learning Outcomes:**

**Core Learning Outcomes**

- Compute descriptive statistics for raw data as well as grouped data.
- Determine appropriate features of a frequency distribution.
- Apply Chebyshev's Theorem.
- Distinguish between and provide relevant descriptions of a sample and a population.
- Apply the rules of combinatorics.
- Differentiate between classical and frequency approaches to probability.
- Apply set-theoretic ideas to events.
- Apply basic rules of probability.
- Apply the concepts of specific discrete random variables and probability distributions.
- Compute probabilities of a normal distribution.
- Compute confidence intervals of means and percentages.
- Perform hypothesis tests involving one population.
- Compute regression and correlation of Bi-variate data.

**Core Assessment:**

Description of MA 120 Core Assessment

One problem with multiple parts for each numbered item, except for item #3, which contains four separate problems.

1. Compute the mean, median, mode, and standard deviation for a sample of 8 to 12 data.

2. Compute the mean and standard deviation of a grouped frequency distribution with 4 classes.

3. Compute the probability of four problems from among these kinds or combinations there of:

a. the probability of an event based upon a two-dimensional table;

b. the probability of an event that involves using the addition rule;

c. the probability of an event that involves conditional probability;

d. the probability of an event that involves the use of independence of events;

e. the probability of an event based upon permutations and/or combinations;

f. the probability of an event using the multiplication rule; or

g. the probability of an event found by finding the probability of the complementary event.

6. Compute and interpret a confidence interval for a mean and/ or for a proportion.

Link to Class Rubric**Class Assessment:**

**Grading:**

**Late Submission of Course Materials:**

Each examination must be taken and completed by the scheduled completion date. No late submissions will be accepted.

**Classroom Rules of Conduct:**

Class Participation is expected. Students are expected to attend all classes and be on time. Roll will be checked each class meeting. Classes missed for legitimate reasons such as illness or temporary duty, are excusable; however, the student must notify the instructor (prior to the class to be missed if possible) and make up the missed work as follows: Read and be responsible for assigned readings/course content and work recommended problems as appropriate. As previously stated, the Final Examination must be taken in a proctored environment. If it is impossible to take the exam with the rest of the class during the scheduled class period, it is the student's responsibility to contact the instructor well prior to that date and arrange to take the exam.

**Course Topic/Dates/Assignments:**

In Unit 1, we will learn what the topic of statistics entails. We'll discuss some ways to collect the needed data for a statistical study. By the end the unit we'll have a view of how the two distinct divisions of statistics, descriptive and inferential, are related. We will discover how to convert ungrouped data into grouped data. Then we will examine some of the many ways data can be visually displayed graphically. We will examine ways to describe data by looking at its central tendency, its variation from its center, and how to determine the location of an element within a data set. A method of finding the proportions of variation a data set possesses will also be covered. (Chapters 1 - 3)

In Unit 2, we will continue our learning from Chapter 3. In furtherance of our learning, we'll explore the basic concepts of probabilities, the branch of mathematics that allows us to take a sample and make predictions about the population from which it was derived. We'll strive to gain a fundamental understanding of probability through its addition, multiplication and counting rules. (Chapters 3 and 4)

In Unit 4, the discussion changes from discrete distributions to continuous random variable distributions. We begin looking at the Normal distribution and then quickly moving on the the Standard Normal distribution. We conclude the unit by learing how the Central Limit Theorem can be applied to sample data sets. (Chapter 6)

**Academic Honesty:**

Academic integrity is the foundation of the academic community. Because each student has the primary responsibility for being academically honest, students are advised to read and understand all sections of this policy relating to standards of conduct and academic life. Park University 2008-2009 Undergraduate Catalog Page 87

**Plagiarism:**

Plagiarism involves the use of quotations without quotation marks, the use of quotations without indication of the source, the use of another's idea without acknowledging the source, the submission of a paper, laboratory report, project, or class assignment (any portion of such) prepared by another person, or incorrect paraphrasing. Park University 2008-2009 Undergraduate Catalog Page 87

**Attendance Policy:**

Instructors are required to maintain attendance records and to report absences via the online attendance reporting system.

- The instructor may excuse absences for valid reasons, but missed work must be made up within the semester/term of enrollment.
- Work missed through unexcused absences must also be made up within the semester/term of enrollment, but unexcused absences may carry further penalties.
- In the event of two consecutive weeks of unexcused absences in a semester/term of enrollment, the student will be administratively withdrawn, resulting in a grade of "F".
- A "Contract for Incomplete" will not be issued to a student who has unexcused or excessive absences recorded for a course.
- Students receiving Military Tuition Assistance or Veterans Administration educational benefits must not exceed three unexcused absences in the semester/term of enrollment. Excessive absences will be reported to the appropriate agency and may result in a monetary penalty to the student.
- Report of a "F" grade (attendance or academic) resulting from excessive absence for those students who are receiving financial assistance from agencies not mentioned in item 5 above will be reported to the appropriate agency.

Park University 2008-2009 Undergraduate Catalog Page 89-90

**Disability Guidelines:**

Park University is committed to meeting the needs of all students that meet the criteria for special assistance. These guidelines are designed to supply directions to students concerning the information necessary to accomplish this goal. It is Park University's policy to comply fully with federal and state law, including Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act of 1990, regarding students with disabilities. In the case of any inconsistency between these guidelines and federal and/or state law, the provisions of the law will apply. Additional information concerning Park University's policies and procedures related to disability can be found on the Park University web page: http://www.park.edu/disability .

Competency | Exceeds Expectation (3) | Meets Expectation (2) | Does Not Meet Expectation (1) | No Evidence (0) |

Evaluation Outcomes 10 | Can perform and interpret a hypothesis test with 100% accuracy. | Can perform and interpret a hypothesis test with at least 80% accuracy. | Can perform and interpret a hypothesis test with less than 80% accuracy. | Makes no attempt to perform a test of hypothesis. |

Synthesis Outcomes 10 | Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with 100% accuracy. | Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with at least 80% accuracy. | Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with less than 80% accuracy. | Makes no attempt to compute or interpret a confidence interval. |

Analysis Outcomes 10 | Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with 100% accuracy. | Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with at least 80% accuracy. | Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with less than 80% accuracy. | Makes no attempt to apply the normal distribution, Central Limit Theorem, or binomial distribution. |

Terminology Outcomes 4,5,7 | Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample, and population with 100% accuracy. | Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample, and population with at least 80% accuracy. | Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample, and population with less than 80% accuracy. | Makes no attempt to explain any of the terms listed. |

Concepts Outcomes 1,6 | Can explain mean, median, mode, standard deviation, simple probability, and measures of location with 100% accuracy. | Can explain mean, median, mode, standard deviation, simple probability, and measures of location with at least 80% accuracy. | Can explain mean, median, mode, standard deviation, simple probability, and measures of location with less than 80% accuracy. | Makes no attempt to define any concept. |

Application Outcomes 1,2,3,8,9 | Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All must be done with 100% accuracy. | Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All must be done with at least 80% accuracy. | Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All are done with less than 80% accuracy. | Makes no attempt to compute any of the probabilities or statistics listed. |

Whole Artifact Outcomes 7,8 | Can apply the concepts of probability and statistics to real-world problems in other disciplines with 100 % accuracy. | Can apply the concepts of probability and statistics to real-world problems in other disciplines with at least 80 % accuracy. | Can apply the concepts of probability and statistics to real-world problems in other disciplines with less than 80% accuracy. | Makes no attempt to apply the concepts to real-world problems. |

Components Outcomes 1 | Can use a calculator or other computing device to compute statistics with 100% accuracy. | Can use a calculator or other computing device to compute statistics with at least 80% accuracy. | Can use a calculator or other computing device to compute statistics with less 80% accuracy. | Makes no attempt to use any computing device to compute statistics. |

**Copyright:**

**Last Updated:***9/9/2008 2:58:16 PM*