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PALOMAR COLLEGE
 COURSE OUTLINE FOR CREDIT COURSE
 
  • Courses numbered 1 - 49 are remedial or college preparatory courses which do not apply toward an A. A. Degree and are not intended for transfer.
  • Courses numbered 50-99 apply toward an AA Degree, but are not intended for transfer.
  • Courses numbered 100 and higher apply toward an AA Degree and/or are intended for transfer to a four-year college or university.
 
Course Number and Title: MATH 120 Elementary Statistics
 

Unit Value: 3  

Lecture Hours Per Week: 3  

Lab Hours Per Week:  

Lecture/Lab Hours Per Week:  

 

Grading Basis: Grade/Pass/No Pass
 
Basic Skills Requirements: Appropriate Language and/or Computational Skills.
 
Requisite(s)
To satisfy a prerequisite, the student must have earned a letter grade of A, B, C or P(Pass) in the prerequisite course, unless otherwise stated.
Prerequisite:
A minimum grade of 'C' in MATH 56 or A minimum grade of 'C' in MATH 60 or eligibility determined through the math placement process
Corequisite:
None
Prerequisite: Completion of, or concurrent enrollment in
None
Recommended Preparation:
None
Limitation on Enrollment:
None
Catalog Description:
Selected topics include tabular and graphical representation of data, counting principles, permutations, combinations, discrete and continuous probability distributions, sampling distributions, the Central Limit Theorem, an introduction to inferential statistics, and simple linear regression analysis. Applications from the fields of business, economics, life sciences, social sciences, and the physical sciences.
 
Specific Course Objectives:
Upon successful completion of the course the student will be able to:
  1. Organize and analyze data by using descriptive techniques such as tables, graphs, measures of central tendency, and measures of dispersion
  2. Use probability models to analyze data
  3. Calculate confidence intervals and interpret their meaning.
  4. Perform hypothesis tests and interpret those tests for a variety of data types
  5. Use appropriate technology, such as a calculator, graphing calculator, computer, Internet, etc., for statistical purposes.
 
Methods of Instruction:
Methods of Instruction may include, but are not limited to, the following:
  1. Lecture
 
Content in Terms of Specific Body of Knowledge:
  1. Types of data, frequency distributions, histograms, measures of central tendency, measures of dispersion.
  2. Counting techniques, permutations, combinations, random variables, sample space, event.
  3. Probability, conditional probability, probability distributions (binomial, normal, Student-t, chi-square), expected value of a probability distribution.
  4. Variance and standard deviation of a probability distribution, sampling distributions,confidence intervals, hypothesis testing using p-values and test statistics, type I and type II errors, estimation of parameters (mean, proportion, difference of means, difference of proportions).
  5. Contingency tables, goodness of fit.
  6. Correlation and regression, analyze relationships between two variables, use scatter diagram and linear correlation coefficient, describe linear relationship using the equation and graph of regression line.
  7. Appropriate applications of the above techniques.
  8. Additional topics, such as Bayes Theorem and the hypergeometric distribution, may be included at the instructor's discretion.
Textbooks/Resources:
May Include Textbooks, Manuals, Periodicals, Software, and Other Resources
  1. Triola, Mario F. Elementary Statistics. 9th ed. Boston: Pearson/Addison Wesley, 2004.
  2. Brase, Charles Henry, and Corrine Pelillo Brase. Understandable Statistics. 8th ed. Boston: Houghton Mifflin, 2006.
Required Reading:
Text appropriate for the course such as the following:
Triola, Mario F. Statistics 9th Edition. Boston, MA: Pearson/Addison, 2004

Or Brase, Charles Henry, and Corrine Pellillo Brase. Understandable Statistics. 8th Edition. Boston, MA: Houghton Mifflin, 2006.
 
Suggested Reading:
Triola, Mario F. Student's Solution Manual. 9th Edition. Boston, MA: Pearson/Addison Wesley, 2004.

Farber, Elizabeth. Study and Solutions Guide for Understandable Statistics. 8th Edition. Boston, MA: Houghton Mifflin, 2006.
 
Critical Thinking:
Students will be able to analyze a data set using methods from descriptive statistics or inferential statistics.
 
Required Writing:
Statistical problem-solving exercises on homework assignments and written tests are more appropriate. In addition, students may be required to write reports from one paragraph to several pages interpreting or presenting statistical research.
 
Outside Assignments:
Students are expected to spend a minimum of three hours per unit per week in class and on outside assignments, prorated for short-term classes.

Students are expected to read the text, study lecture notes, and complete daily homework assignments. Homework assignments may include practice solving routine problems, explaining concepts, and solving application or non-routine problems.

Student projects requiring a student to design and implement a statistical experiment may be assigned. Students may also be expected to use a computer or a graphing calculator on some assignments.
 
Methods of Assessment:
Methods of Assessment may include, but are not limited to, the following:
  • Exams/Tests
 
Open Entry/Open Exit:
No, course is not offered as open entry/open exit.
 
Is Course Repeatable for Reason(s) Other Than Deficient Grade? No
 
Contact Person: Cynthia M. Torgison