Principles of Statistics | |||
STATISTICS | |||
CLASS CODE: | MATH 221 | CREDITS: 3 | |
DIVISION: | PHYSICAL SCIENCE & ENGINEERING | ||
DEPARTMENT: | MATHEMATICS | ||
GENERAL EDUCATION: | This course fulfills a General Education - Math requirement. | ||
CATALOG DESCRIPTION: | Frequency distributions; measures of central tendency and dispersion; elementary probability; regression and correlation; sampling, statistical inference and estimation involving the normal, t- and chi- square distributions. | ||
DESCRIPTION: | This is a traditional introductory statistics class. The course will help categorize and analyze different types of data for descriptive and inferential statistics. | ||
TOPICS: | |||
OBJECTIVES: | By the end of this course, students will: 1. apply statistical techniques to real situations. 2. understand various sampling techniques and appropriately apply each. 3. graphically represent data in histograms, frequency distributions, box-and-whisker plots, scatter diagrams, etc. 4. compute and explain uses of the mean, mode, median, standard deviation and variance. 5.understand randomness and compute the probabilities of simple and compound events. 6. use the binomial distribution to compute the probabilities of outcome of various binomial experiments. 7. use the normal distribution to compute probabilities. 8. know the Central Limit Theorem and its applicability to statistics. 9. use the normal distribution to approximate the binomial distribution when appropriate. 10. utilize estimation techniques to find confidence intervals about a mean with large and small samples, a proportion, and the difference of two means or proportions. 11. estimate the sample size required to achieve a particular margin of error. 12. understand the fundamentals of hypothesis testing; identify the correct hypothesis test to be used in a given situation. 13. set up and execute hypothesis tests involving: one mean with large or small samples, one proportion, paired data (dependent samples), and tests involving two means or proportions (independent samples). 14. understand the significance of the p-value and find (or bound) it for any of the hypothesis tests discussed. 15. find the linear regression coefficients, the correlation coefficient, the coefficient of determination and confidence bounds on a predicted value. 16. test the linear correlation coefficient for significance. 17. use the chi-squared tests for independence and goodness of fit. 18. use relevant statistical functions on a calculator and software such as Minitab. |
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REQUIREMENTS: | A copy of the text and a statistical function calculator. | ||
PREREQUISITES: | At least 30 credits and a passing grade on an algebra skills test. | ||
OTHER: | |||
EFFECTIVE DATE: | August 2002 |