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MAT 117 Elementary Statistics

Moore Text

The Basic Practice of Statistics Edition: 5th Author(s): Moore, David S. ISBN-10: 1-4292-2426-6 ISBN-13: 978-1-4292-2426-0 Copyright: 2009 Publisher(s): W H Freeman & Co

The Basic Practice of Statistics, by David S. Moore, 3rd edition, @2004 ISBN: 0-7167-9623-6 (Hardcover) ISBN: 0-7167-0223-1 (Paperback)

Course Topics

Major Lessons in Statistics. Unit 1. Unit 2. Unit 3. Symmetry. Statistics Lies. Semester Review. Learning Objectives. Notes. Video. Audio. Chapter 1: Picturing Distributions with Graphs. Chapter 2: Describing Distributions with Numbers. Chapter 3: The Normal Distributions. Chapters 1-3 Review. Chapter 4: Scatterplots and Correlation. Chapter 5: Regression. Chapter 6: Two-Way Tables. Chapters 4-6 Review. Chapter 8: Producing Data: Sampling. Chapter 10: Introducing Probability. Chapter 11: Sampling Distributions. Chapter 12: General Rules of Probability. Symmetry Presentation. How Not to Be Lied To. Review Notes. Review Video. Review Audio. Always Study the Context. Data Beat Anecdotes. Beware the Lurking Variable(s). Where the Data Come from is Important. Variation is Everywhere. Conclusions are not Certain. Poll Question. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Data Files. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Data Files. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Data Files. Review Notes. Review Video. Review Audio. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Data Files. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Data Files. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Data Files. Review Notes. Review Video. Review Audio. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Chapter Data Files. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Chapter Data Files. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Data Files. Learning Objectives. Terms. Procedures. Chapter Notes. Chapter Video. Chapter Audio. Chapter Links. Chapter Assignment. Chapter Data Files. Creation. Mathematics. Make Assumptions. Overwhelm Your Audience. Graph Related Lies. Use of 'Average'. Bias Problems. Withhold Important Facts. Keep Doing Studies Until Results are Right. Definition of Terms. Danger in Prediction. Review Summary. Review Notes. Review 1. Review 2. Review 1. Review 2. 1.1 Categorical and Quantitative Variables. 1.2 Interpret and Produce Histograms. 1.3 Interpret and Produce Stemplots. 1.4 Interpret and Produce Timeplots. Center of a Distribution. Spread of a Distribution. Shape of a Distribution. Symmetric Distribution. Skewed Distribution. Stemplot. Individual. Outlier. back-to-back stemplots. splitting stems in stemplot. Variable. Categorical Variable. Quantitative Variable. Recognize if variable is quantititative or categorical, 4. Recognize when a pie chart can and cannot be used, 6. Making Historgrams, 9. Interpreting Histograms, 11. Making a Stemplot, 15. Making a Time Plot, 18. Finding the Mean, 32. Day 1. Day 2. Day 3. Day 1. Day 2. Day 3. Activity: Making a Stem and Leaf Plot. Bin Width Demonstration (Rice University). Bin Width Demo. Percentiles. Tutorial: Data Sets & Definitions (Chapter 1, pp. 3-5). Tutorial: Graphical Summaries (Chapter 1, pp. 6-17). Tutorial: Time Plots (Chapter 1, pp. 18-20). Text Assignment: 1, 6, 8, 11, 32, 33, 35, 37, 40, 45. Help. Chapter 1 Data Sets. 2.1 Find the mean of data. 2.2 Find the median of data. 2.3 Compare the mean and the median. 2.4 Find quartiles. 2.5 Determine the five-number summary and boxplots. 2.6 Determine the standard deviation of data. 2.7 Determine which measures of center and spread to utilize. Center of a distribution. Skewed Distribution. Five-number summary. Interquartile range. Mean. Mean and Median. Quartiles. Median. Outlier. Standard deviation. Finding the Mean, 32. Finding the Median, 34. Finding the Quartiles, 36. Finding the 5 Number Summary, 38. Making a Boxplot, 38. finding the Standard Deviation, 42. Find the Interquartile Range, 53. Day 1. Day 2. Day 1. Day 2. Tutorial: Mean and Median (Chapter 2, pp. 32-36). Tutorial: Five Number Summary and Boxplots (Chapter 2, pp. 37-41). Tutorial: Standard Deviation & IQR (Chapter 2, pp. 42-44). Measures of Central Tendency Activity. Mean and Median applet. Text Assignment : 1, 4, 9, 11, 25, 28, 42, 43. Help. Chapter Data Files. 3.1 Interpret density curves. 3.2 Evaluate the median and the mean of a density curve. 3.3 Understand normal distributions. 3.4 Understand and use the 68-95-99.7 rule. 3.5 Understand and utilize the standard normal distribution. 3.6 Be able to make normal distribution calculations. 3.7 Given a proportion, able to find a value. Density curve. Symmetric Distribution. Skewed Distribution. Standard Normal distribution [N(0,1)]. Histogram. Mean of Normal distribution. Mean and Median. Quartiles. Symmetry, “Symmetry” presentation. The 68—95—99.7 rule, 63—64, 74, 77, 154, 265—266, 322. Standardize Observations, 65. Use Standardized Scores to Compare, 67. Use Table A to find % of smaller #'s, 70. Use Table A to find # given % smaller, 70. Day 1. Day 2. Day 3. Day 1. Day 2. Day 3. Tutorial: Density Curves (Chapter 3, pp. 56-61). Tutorial: Normal Distribution (Chapter 3, pp. 61-64). Tutorial: Standard Normal Distribution (Chapter 3, pp. 65-71). Tutorial: Using Standard Normal Table (Chapter 3, pp. 67-73). Normal Probability Models @ University of Colorado. Sampling Distribution Simulation. Text Chapter 3 Assignment: 1, 7, 11, 13, 29, 33, 38, 41, 43, 53. 4.1 Understand and utilize explanatory and response variables. 4.2 Understand and produce scatterplots. 4.3 Interpret scatterplots. 4.4 Add categorical variables to scatterplots. 4.5 Understand and utilize correlation. Outlier. Scatterplot. Positive Association. Negative Association. Strength of Relationship. Linear Relationship. Standard deviation. Categorical Variable. Explanatory Variable. Dependent Variable. Independent Variable. Response Variable, 79-81, 82-83, 91, 94, 104, 110, 123, 152, 200, 391, 563. Identify explanatory variable, 79. Identify response variable, 79. Make scatterplot for 2 variables, 82. Recognize positive association, 84. Recognize negative association, 84. Recognize a linear pattern, 84. Recognize outliers in a scatterplot, 83. Compute correlation coefficient r, 88. Know what correlation measures, 88. Day 1. Day 2. Day 3. Day 1. Day 2. Day 3. Regression by Eye Demonstration (Rice University). Tutorial: Bivariate Data (Chapter 4, pp. 79-81). Tutorial: Scatterplots (Chapter 4, pp. 82-87). Tutorial: Correlation (Chapter 4, pp. 88-93). Correlation and Regression Applet. Chapter 4 Assignment: 1, 5, 7, 9, 13, 31, 35, 39, 41, 45 (at least 2 manual, 2 in Excel). Help. Chapter Data Files. 5.1 Understanding the least-squares regression line. 5.2 Application of the least-squares regression line. 5.3 Understanding residuals. 5.4 Understanding influential observations in regression. 5.5 Understanding that association does not imply causation. Correlation. Explanatory Variables. Influential observation. Least-Squares Regression. Prediction. Regression Line. Residual. Response Variable. Standard deviation, 42—44, 47, 88, 92, 111, 153. Draw graph of line given its equation, 104. Calculate least-squares regression line, 104. Find slope & y-intercept of regression line, 104. Explain what slope and y intercept mean in y=a+bx, 107. Calculate residuals and plot them, 115. Know limitations of regression, 116. Use regression line to make prediction, 119. Be aware of dangers of extrapolation, 119. Day 1. Day 2. Day 3. Day 1. Day 2. Day 3. Tutorial: Least Squares Line (Chapter 5, pp. 104-109). Tutorial: R-Squared (Chapter 5, pp. 111-112). Tutorial: Residual Plots (Chapter 5, pp. 113-116). Tutorial: Regression Facts (Chapter 5, pp. 110-112). Tutorial: Regression Cautions (Chapter 5, pp. 116-123). Correlation and Regression Applet. Least Squares demonstration. Chapter 5 Assignment: 1, 3, 5, 7, 9, 13, 33, 35, 51, 53. Help. Chapter Data Files. 6.1 Marginal Distributions. 6.2 Relationships between categorical variables. 6.3 Conditional Distributions. 6.4 Simpson's Paradox. Simpson’s paradox. Marginal Distributions, 135. Interpret and analyze two-way tables, 135. Find relationships between categorical variables, 137. Understand and interpret conditional distributions, 138. Recognize Simpson’s Paradox, 141. Day 1. Day 2. Day 1. Day 2. Tutorial: Two-way Tables (Chapter 6, pp. 134-140). Tutorial: Simpson's Paradox (Chapter 6, pp. 141-142). Chapter 6 Assignment : 1, 3, 5, 7, 25, 29. Help. Chapter Data Files. 8.1 Observation versus experiment. 8.2 Sampling. 8.3 Simple random samples. 8.4 Other sampling designs. 8.5 Cautions about sample surveys. 8.6 Inference about the population. Bias. Confounding. Convenience sampling. independence of random digits. Inference, statistical. Nonresponse. Population. Response bias. Sample surveys. sample. Sampling Variability. Undercoverage. Choosing an SRS. Sample inferences about the population, 189. Tutorial: Survey Designs. Summary of Survey Designs Tutorial. Tutorial: Survey Cautions. Summary of Survey Cautions Tutorial (above). Simple Random Sample Applet. Assignment: 2-32 (Evens). 10.1 The idea of probability. 10.2 Thinking about randomness. 10.3 Probability models. 10.4 Probability rules. 10.5 Assigning probabilities. 10.6 Normal probability models. 10.7 Random variables. Density curve. Disjoint events. Distribution as probability distribution. Uniform Distribution. Independence of observations. Probability of equally likely outcomes. idea of Probability. personal Probability. rules of Probability. Sample. Simple Random Sample. Sampling Variability, xxii—xxiii, 37,47, 189, 206, 223, 251, 262—263. Understand how to calculate a probability. Know and use basic probability rules, 230. Day 1. Day 2. Day 3. Day 1. Day 2. Day 3. Probability Applet. Tutorial: What is Probability?. Tutorial: Probability Models and Rules. Tutorial: Discrete vs. Continuous. Chapter 9 Assignment : 2-50 (Evens. 11.1 Parameters and statistics. 11.2 Statistical estimation and the law of large numbers. 11.3 Sampling distributions. 11.4 The sampling distribution of the mean. 10.5 The central limit theorem. Central limit theorem. Center of a distribution. Central limit theorem. Control chart. Control limits. Normal Distribution. Spread of a Distribution. Inference, statistical. Large numbers, law of. Mean of a population. Normal Distribution. Parameter. Population. Sample. Simple Random Sample. Simulation. Sampling distribution. Sampling Distribution of sample mean. Symmetry, “Symmetry” presentation. The 68—95—99.7 rule. Time Plot. Know difference between a parameter and a statistic. Use the law of large numbers. Calculate the test statistic. Find natural tolerances,. Find control limits. Day 1. Day 2. Day 3. Day 1. Day 2. Day 3. Tutorial: Parameters and Statistics. Tutorial: Sampling Distribution of Sample Mean. Tutorial: Center, Spread, Shape (CLT). Tutorial: An Application of Sampling Distribution. Tutorial: Probability on Sample Mean. Tutorial: Statistical Process Control. Sampling Distributions Applet @ Rice University. Chapter 11 Applets. Chapter 11 Assignment: 2-38 (Evens). Help. Chapter Data Files. 12.1 Independence and the multiplication rule. 12.2 Applyging the multiplication rule. 12.3 The general addition rule. 12.4 Conditional probability. 12.5 The general multiplication rule. 12.6 Independence. 11.7 Tree diagrams. Disjoint events. Uniform Distribution. Independence of events. Independence of observations. conditional probability. Symmetry, “Symmetry” presentation. Tree diagram, 294—295, 393. Find probability of one event or the other occurring. Multiplication Rule. Understand conditional probability. Know meaning and utility of tree diagrams, 294. Tutorial: General Probability Rules. Assignment: 2-36 (Evens). Balance. Bilateral. Radial. Basic Operations. Geometry. Algebra. Statistics. With Impressive Data. With the Percent Lie. With Terminology. Don't Pay Attention to Scale. Change Scale on y-axis to your liking. Don't Show Whole Graph. Use Pictograph Representing 3-D Object. Use Perspective to stretch truth. Use Larger Scale for Scatterplots. Many Lies on One Graph. Used Loosely. Doesn't Mean Very Much. Misleading Conclusions. Sample Too Small. Extrapolate from 1 data point. Sample Not Random. Bias Not Eliminated. Scientific Elitism. Incomplete Report. Video. Audio. Poll Question. Poll Question. Video. Audio. Stats Tech. Poll Question. Video. Audio. Poll Question. Video. Audio. Poll Question. eg: example ex: exercise ta: table. Video. Audio. Stats Tech. Poll Question. Video. Audio. Stats Tech. Video. Audio. Video. Audio. Stats Tech. Video. Audio. Stats Tech. Poll Question. Video. Audio. Stats Tech. Poll Question. Video. Audio. Poll Question. eg: example ex: exercise ta: table. Video. Audio. Poll Question. Video. Audio. Poll Question. Video. Audio. Poll Question. Video. Audio. Video. Audio. Stats Tech. Poll Question. Poll Question. Poll Question 1. Poll Question 2. Poll Question. Stats Tech. Poll Question. eg: example ex: exercise ta: table. Stats Tech. Poll Question 1. Poll Question 2. Stats Tech. Poll Question. Poll Question. Poll Question. eg: example ex: exercise ta: table. Poll Question. Poll Question. eg: example ex: exercise ta: table. Poll Question. Poll Question. Poll Question. Poll Question. Poll Question. eg: example ex: exercise fig: figure ta: table. Normal Distributions. Central Limit Theorem. Larger Sample - More Symmetrical.

Elementary Statistics (MAT 117) 3 credits

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MyWLC

Course Syllabus

Course Description

Beginning statistical theory and practice are introduced through topics of data collection, sampling techniques, organization and presentation of data, measurement of central tendency, probability concepts, statistical estimation, hypothesis testing, correlation analysis, linear regression and analysis of variance. There will also be some time devoted to symmetry and examples of mathematical precision and beauty in God's Creation.

Stats Tech

Instructor

Dr. Ronald Buelow. information. email. Phone. Office: 414-443-8553. Away from Office: 262-510-2046.

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