Cart
Free US shipping over $10
Proud to be B-Corp

Activity-Based Statistics, 2nd Edition Student Guide Richard L. Scheaffer

Activity-Based Statistics, 2nd Edition Student Guide By Richard L. Scheaffer

Activity-Based Statistics, 2nd Edition Student Guide by Richard L. Scheaffer


$11.65
Condition - Good
Only 1 left

Summary

Activity-Based Statistics helps build real statistical understanding through a set of innovative hands-on activities that can be used each day in conjunction with other texts. The second edition continues to emphasize discovery by motivating readers to apply the skills they have learned to discover the everyday relevance of statistics.

Faster Shipping

Get this product faster from our US warehouse

Activity-Based Statistics, 2nd Edition Student Guide Summary

Activity-Based Statistics, 2nd Edition Student Guide by Richard L. Scheaffer

Activity-Based Statistics helps build real statistical understanding through a set of innovative hands-on activities that can be used each day in conjunction with other texts. The second edition continues to emphasize discovery by motivating readers to apply the skills they have learned to discover the everyday relevance of statistics. There are over 45 activities and five long-term projects that have been updated and extended to encourage readers to experience statistics in context. While the second edition includes updated technology extensions for Fathom, technology is used throughout the book to extend activities and is not required to complete them.

About Richard L. Scheaffer

Dr. Richard L Sceaffer's research and scholarly interests are in statistical education and sampling theory/practice. He is currently a professor in the department of statistics at the University of Florida. B.A. 1962 Lycoming college; M.A. 1964 Bucknell University; Ph.D. 1968 Florida State University.

Table of Contents

Preface. To the Student. Acknowledgments. I. EXPLORING DATA. A Living Histogram. How to build a histogram out of people. Getting to Know the Class. Surveying the class. Exploratory data analysis. Displaying categorical and quantitative data. A Living Box Plot. How to construct a box-and-whisker plot with people. Shape, center, and spread. V Is for Variation: How Far Are You from the Mean? Measuring variability in data. Matching Plots to Variables. Connecting our knowledge of real-life distributions to their graphs. Matching Statistics to Plots. Matching summary statistics to graphs of distributions. How the mean can differ from the median. Variation in Measurement. Collecting measurement data and looking at its distribution. Measurement Bias. Experiencing measurement bias. Let Us Count. Variation due to the process of measurement. Matching Descriptions to Scatter Plots. Making the correspondence between scatter plots and statistics (regression line and r). The Regression Effect. Find out about the regression effect. Leonardo's Model Bodies. Looking at correlation between the sizes of different body parts. Relating to Correlation. How the correlation coefficient from a sample varies about the true population coefficient. Models, Models, Models ... Modeling time series data with lines. Breaking the time series into two pieces. Predictable Pairs. Relationships between categorical variables. Association in two-way tables. Ratings and Ranks. The relationship between ratings and ranks. II. PLANNING A STUDY. Random Rectangles. Sampling bias. The importance of random sampling. The Rating Game. Analyzing ratings that are results from a questionnaire you design. Stringing Students Along. Learning about selection bias. Gummy Bears in Space. Factorial designs and interaction. Controlling variables. Funnel Swirling. Experimental design, particularly factorial design.Variability in an experiment. Jumping Frogs. Experiments in a factorial situation. Estimating the effects of each factor and of the interaction. How to Ask Questions: Designing a Survey How the way a question is worded can affect the outcome of a survey. III. ANTICIPATING PATTERNS. What Is Random Behavior? Gambler's fallacy. It's hard to predict short-term random behavior. The Law of Averages. What is the law of averages? How probability helps us predict in the long term. Streaky Behavior. Runs in Bernoulli trials. Randomness is streakier than we think. Counting Successes. How to create simulations to study problems about the number of successes in repetitions of an event with a known probability. Waiting for Sammy Sosa. The geometric, or waiting-time, distribution. The Lazy Student. What happens to the spread when you add random variables. What's the Chance? Dependent and independent trials. Spinning Pennies. Sampling distributions. Distribution of sample proportions where p 0.5. Cents and the Central Limit Theorem. How the sampling distribution of the mean of a nonnormal distribution looks normal. Sampling Error and Estimation. How an estimate (for example, of a mean) based on a sample differs from the population value. How Accurate Are the Polls? How an estimate of a proportion differs from the population value. How the spread of sampling distributions defines a margin of sampling error. IV. STATISTICAL INFERENCE. How Many Tanks? Estimating a population from serial numbers. Unbiased estimators. Estimating the Total of a Restaurant Bill. Sources of bias in estimation. Compensating for bias. What Is a Confidence Interval Anyway? Explaining the confidence interval as the range of plausible population values. Confidence Intervals for the Proportion of Even Digits. The meaning of the confidence level.What affects whether 95% of the confidence intervals contain the true value. Capture/Recapture. Estimating population size using a capture/recapture technique. How to Ask Sensitive Questions. Randomized response sampling. Using probability techniques to disguise survey answers and preserve confidentiality. Estimating a Total. It is not always clear how to sample to get the best estimate. The Bootstrap. Creating an interval estimate for statistics when the traditional confidence interval may be inappropriate. Statistical Evidence of Discrimination. Using the randomization test to show that variables are associated. How Typical Are Our Households' Ages? The Chi-Square Test Using chi-square to show that (binned) age distributions are different. Coins on Edge. The power of a hypothesis test increases as the sample size increases. V. PROJECTS. Theme: Exploration of Data and Improvement in Quality. Application: Improved Payment Processing in a Utilities Firm. Theme: Sample Survey. Application 1: A Typical Election Poll. Application 2: The Nielsens. Theme: Experiment. Application: Does Aspirin Help Prevent Heart Attacks? The Physicians' Health Study. Theme: Modeling. Application: Body Composition. References. Index.

Additional information

CIN0470412097G
9780470412091
0470412097
Activity-Based Statistics, 2nd Edition Student Guide by Richard L. Scheaffer
Used - Good
Paperback
John Wiley & Sons Inc
2008-07-14
258
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in good condition, but if you are not entirely satisfied please get in touch with us

Customer Reviews - Activity-Based Statistics, 2nd Edition Student Guide