Foothill CollegeApproved Course Outlines

Physical Sciences, Mathematics & Engineering Division | |||||

MATH 10 | ELEMENTARY STATISTICS | Fall 2012 | |||

5 hours lecture. | 5 Units | ||||

Total Quarter Learning Hours: 60
(Total of All Lecture, Lecture/Lab, and Lab hours X 12) | |||||

Lecture Hours: 5 |
Lab Hours: | Lecture/Lab: | |||

Note: If Lab hours are specified, see item 10. Lab Content below. | |||||

Repeatability - | |||||

Statement: | Not Repeatable. | ||||

Status - | |||||

Course Status: Active | Grading: Letter Grade with P/NP option | ||||

Degree Status: Applicable | Credit Status: Credit | ||||

Degree or Certificate Requirement: AA Degree, Foothill GE | |||||

GE Status: Communication & Analytical Thinking | |||||

Articulation Office Information - | |||||

Transferability: Both | Validation: 07/01/2009; 11/22/11 | ||||

1. Description - | ||

An introduction to modern methods of descriptive statistics, including collection and presentation of data; measures of central tendency and dispersion; probability; sampling distributions; hypothesis testing and statistical inference; linear regression and correlation; analysis of variance; use of microcomputers for statistical calculations. Illustrations taken from the fields of business, economics, medicine, engineering, education, psychology, sociology and from culturally diverse situations. | ||

Prerequisite: Satisfactory score on the mathematics placement test or MATH 105 or 108. | ||

Co-requisite: None | ||

Advisory: Demonstrated proficiency in English by placement into ENGL 1A as determined by score on the English placement test or through an equivalent placement process; UC will grant transfer credit for a maximum of one course from the following: PSYC 7, SOC 7 or MATH 10. | ||

2. Course Objectives - | ||

The student will be able to: - distinguish between quantitative and qualitative data; sample and population; descriptive statistics and inferential statistics.
- read a graph and conclude what information the graph is conveying about the data.
- calculate measures of central tendency, dispersion and relative standing and use these measures to solve application problems.
- compute basic probabilities.
- define discrete probability distributions and use such distributions to solve application problems.
- define continuous probability distributions and use such distributions to solve application problems.
- define sampling distributions, state the Central Limit Theorem and use sampling distributions and the Central Limit Theorem to solve application problems.
- use confidence intervals to estimate population parameters, or the difference between two population parameters, using the appropriate formula and then interpret the result.
- determine the sample size required to estimate a population parameter.
- design, set up, and evaluate the results of hypothesis tests.
- compare and contrast the use of confidence intervals and hypothesis tests to make inferences about population parameters.
- solve application problems utilizing techniques of regression and correlation.
- use analysis of variance to make inferences about more than two population means.
- solve application problems using categorical data analysis.
- demonstrate statistical understanding of inference by participating in a cooperative project.
- demonstrate proficiency in the use of the computer as a tool for doing statistics
- apply statistical methods to situations in a culturally diverse society.
- discuss mathematical problems and write solutions in accurate mathematical language and notation.
- interpret mathematical solutions.
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3. Special Facilities and/or Equipment - | ||

- Graphing calculator
- Access to Microsoft Excel software
- When taught on Foothill Global Access: ongoing access to a computer with e-mail software and e-mail address.
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4. Course Content (Body of knowledge) - | ||

- Organization of Data
- Definitions
- population
- sample
- variables
- descriptive statistics
- inferential statistics
- Sampling Methods
- simple random
- stratified
- cluster
- systematic
- convenience
- Frequency and relative frequency distributions
- Graphs and charts
- histograms
- pie-charts
- stem-and-leaf graphs
- bar charts
- Pareto charts
- box plots
- dot plots
- ogives
- time-series
- graph shapes
- Measures of Central Tendency and Dispersion
- Summation notion
- Measures of central tendency
- mean
- median
- mode
- Measures of dispersion
- range
- sample variance
- sample standard deviation
- coefficient of variation
- Chebyshev's Theorem
- Percentiles and Quartiles
- Probability
- Empirical probability
- Sample spaces and events
- addition rule
- mutually exclusive events
- complementary events
- Conditional probability
- independent events
- multiplication rule
- Discrete Probability Distributions
- Definition of random variables
- Discrete random variables
- mean
- variance
- standard deviation
- Properties of a probability distribution function
- The Binomial distribution
- the binomial probability distribution function
- mean
- variance
- standard deviation
- application problems
- Continuous Probability Distributions
- Continuous random variables; equating area under a curve with probability
- Empirical Rule
- The normal distribution
- standardizing normal curves (z-scores)
- finding z-scores from areas under the standard normal curve
- application problems
- The normal approximation to the binomial distribution
- requirements
- adjusting the interval of the variable from discrete to continuous
- Sampling Distributions
- Sampling distribution of the mean
- mean
- standard deviation
- shape
- Central Limit Theorem
- Estimation
- Margin of Error
- Point estimation; biased and unbiased estimator
- Confidence interval for the mean when the variance is known
- maximal margin of error
- sample size for estimating the mean
- Confidence interval for the mean when the population variance is unknown
- maximal margin of error
- students t-distribution
- degrees of freedom
- Confidence interval for the population proportion
- maximal margin of error
- sample size for estimating the proportion
- Confidence interval for the difference between two means when population variances are known
- maximal margin of error
- Confidence interval for the difference between two means when population variances are unknown, but assumed unequal
- maximal margin of error
- Confidence interval for the difference between two means when population variances are unknown, but assumed equal
- maximal margin of error
- Confidence interval for the difference between two means when the samples are dependent
- Confidence interval for the difference between population proportions
- maximal margin of error
- Hypothesis Testing
- Vocabulary
- null hypothesis
- alternate hypothesis
- right-, left-, and two-tailed tests
- Mechanics of hypothesis testing
- type I error
- type II error
- p-value
- test statistic
- decision rule
- rejection and acceptance region
- Single-population hypothesis testing
- for the population mean when the variance is known
- for the population mean when the variance is unknown
- testing population proportion
- Two-population hypothesis testing
- comparing two population means when the population variances are known
- comparing two population means when the population variances are unknown, but assumed equal
- comparing two population means when the population variances are unknown, but assumed unequal
- dependent samples
- testing difference in population proportions
- Comparision of Hypothesis Tests and Confidence Intervals
- connection between hypothesis testing and confidence intervals
- statistical significance in confidence intervals and hypothesis tests
- Linear Regression and Linear Correlation
- Linear relations
- Linear regression
- scatter diagrams
- method of least squares
- regression analysis
- coefficient of determination
- Linear correlation
- One Way Analysis of Variance (ANOVA)
- Methodology
- F-distribution
- Tukey pairwise comparisons
- Chi Square Tests
- Contingency tables
- Chi-square distribution
- Tests for dependence of categorical variables
- Tests for homogeneity
- Goodness of fit
- Testing and Estimating a Population Variance
- Testing the variance
- Confidence intervals
- Cooperative Project
- Hypothesis testing
- Confidence intervals
- Graphs
- Statistical inference
- Sampling methods
- Data analysis
- Computer as a Tool for Doing Statistics
- Computer lab assignments
- Excel
- Examples used will be from different societies and cultures
- Discuss mathematical problems and write solutions in accurate mathematical language and notation.
- Application problems from other disciplines
- Proper notation
- Interpret mathematical solutions.
- Explain the significance of solutions to application problems.
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5. Repeatability - Moved to header area. | ||

6. Methods of Evaluation - | ||

- Homework
- Quizzes, mid-term exams
- Computer lab assignments
- Cooperative project
- Proctored comprehensive final examination: the final exam must be taken in person at the Los Altos Hills campus or at another approved facility administered by a proctor deemed acceptable by the instructor.
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7. Representative Text(s) - | ||

Beoga.net Inc. Elementary Statistics. V2.5. 2006. Brase, H. and C. Brase. Understandable Statistics: Concepts and Methods, 9th ed. Houghton Mifflin, 2009. When taught on Foothill Global Access: lectures, handouts, and assignments are delivered via e-mail and/or the world wide web. | ||

8. Disciplines - | ||

Mathematics | ||

9. Method of Instruction - | ||

Lecture, Discussion, Cooperative learning exercises, Lecture-Laboratory. | ||

10. Lab Content - | ||

Not applicable. | ||

11. Honors Description - No longer used. Integrated into main description section. | ||

12. Types and/or Examples of Required Reading, Writing and Outside of Class Assignments - | ||

- Homework Problems: Homework problems covering subject matter from text and related material ranging from 30 - 60 problems per week.
| ||

13. Need/Justification - | ||

This course is a required core course for the AS degree in General Studies Science and satisfies the Foothill GE Requirement for Area V, Communication & Analytical Thinking. |

Course status: | Active | |

Last updated: | 2014-04-03 15:54:00 |

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