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Statistics I

Educator Edition

Contributor
Portland Community College
Course
MTH 243, Statistics I. Introduces displaying data with graphs, numerical descriptions of data, producing data, elementary probability, probability distributions, confidence intervals and significance testing. Investigates applications from science, business, and social science perspectives. Graphing calculator with advanced statistical programs and/or computer software required; see instructor.
TextbookStats Data and Models by DeVaux, Velleman, and Bock, or a textbook of your choice.
PrerequisitesIntended for students who have passed an Intermediate Algebra course.

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Intended Outcomes

Upon completion of the course students should be able to:

  1. Analyze data and graphs in real world scenarios to recognize what probability and statistics are appropriate, formulate problems about the scenarios, creatively model these scenarios (using technology, if appropriate) in order to solve the problems using multiple approaches, then judge if the results are reasonable and clearly interpret the results via written or oral communication.
  2. Recognize probability and statistics concepts that are encountered in the real world, understand and be able to communicate the underlying mathematics involved to help another person gain insight into the situation.
  3. Work with probability and statistics in various situations and use correct mathematical terminology, notation, and symbolic processes in order to be prepared for future coursework and to continue a course of study in their major field that requires the use of and an understanding of the concepts of probability and statistics.
  4. Read a peer reviewed journal article and understand the meaning and logical implications behind the statistical processes of a confidence interval and a significance test.

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Problem Sets

  1. Basics Of Data
  2. One Variable Calculations
  3. Displaying Data
  4. Z Score Basics
  5. Normal Distributions
  6. Empirical Rule
  7. Normal Area For Arbitrary Z
  8. Sampling Issues
  9. Experimental Design
  10. Basic Probability
  11. General Probability
  12. Venn Diagrams And Sample Spaces
  13. Conditional Probability
  14. Expected Value And Variance
  15. Binomial Distribution
  16. Distribution Of Sample Mean
  17. Sampling And Central Limit Theorem
  18. Proportion And Confidence Intervals
  19. Significance Testing
  20. Scatterplots And Linear Regression

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