Discover how this complex discipline is relied upon to get to the  heart the of great quantities of information.  Historical anecdotes and  brief profiles of contemporary applications provide an overview of statistics.  (28:51 minutes)

Are patterns perfect predictors?  Construct stemplots, frequency tables and histograms, and understand the importance of pattern deviations, including gaps and outliers, in examples drawn from meteorology, traffic control and television programming. (28:46 minutes)

A few good numbers can be worth a thousand words. Examines the difference between mean and median and learn of quartiles, boxplots, interquartile range, and standard deviation.  Also discussed is the advantage of  back-to-back stemplots.   An example of pay inequity illustrates the principles.  (28:49 minutes)

How do studies on batting averages in baseball and age changes in population find expression in density curves?  A series of simplifications shows the progression from histogram to a single normal curve for standardized measurement.  Included are mean, median and percentiles for density curves, and the 68-95-99.7 rule.  (28:46 minutes)

Vehicle emission standards and medical studies of cholesterol give practical examples of normal calculations at work.  Covered are the standardization and calculation of normal relative frequencies from tables, assessing normality by normal quintile plots.  (28:42 minutes)

Discover how statistics can help identify patterns over time, answering questions about stability and change.  Trends in the stock market and studies of sleep cycles illustrate these concepts.  Topics include statistical control; inspecting time series for trend, seasonal variation, cycles; and smoothing by averaging.  (28:54 minutes)

Topics include linear growth, with review of the geometry of straight lines; an introduction to the least squares idea; exponential growth, and straightening an exponential growth curve by logarithms; prediction and extrapolation.  Studies of children's growth problems and of world oil production provide examples.  (28:57 minute)

Scatterplots and their variations are discussed in examples drawn from weight-loss programs to manatee protection.  Also covered are smoothing scatterplots of response versus explanatory variables by median trace; linear relationships, least squares regression lines, and comment on outliers.  (28:42 minutes)

Find out how to derive the correlation coefficient and to interpret it, using the relationship between a baseball player's salary and his home-run statistics as one example.  A study of identical twins further illustrate correlation concepts.   (28:52 minutes)

The program recaps the presentation of data analysis by showing the use of computing technology and a case study at Bell Communications Research.  A study on environmental stresses in the Chesapeake Bay demonstrates the value of statistical principles.    (28:46 minutes)

Observed association may or may not represent causation.  The relationship between smoking and lung cancer is examined.  A study of admissions data illustrates Simpson's paradox.  (28:52 minutes)

Distinguish between observational studies and experiments and learn the basic principles of design including comparison, randomization, and replication.  Case material for heart disease study shows the advantages of a double-blind experiment.  (28:46 minutes)

Understand random sampling and the difference between single-factor and multi-factor experiments and the kinds of questions each can answer.  A study of agriculturalists' efforts to find improved varieties of strawberries demonstrates randomized block design.  (28:37 minutes) 

Can small samples give accurate information?  Stratified random sampling is explained.  A 1936 Gallup election yields important information about the concept of undercoverage and the importance of careful use of sampling.  See how a survey is designed to ensure randomness and avoid bias.  (28:51 minutes) 

Distinguish between deterministic and random phenomena, and understand sample space, events, outcomes and probability models.  Examples include the work of statistician Persi Diaconis on probability and randomness and a computer that models traffic scenarios.  (28:49 minutes)

How does a statistician calculate the probability of a space shuttle accident?  How do geologists use statistics to predict earthquakes?  Learn about the idea of independence; the multiplication rule for independent events; and discrete and continuous random variables.  (28:47 minutes)

Find out how to calculate the mean and standard deviation of binomial distributions, and see how the quincunx, a randomizing device at the Boston Museum of Science, illustrates concepts.  Addition rules for the means and variance of random variables are defined in an example predicting sick cell anemia.  (28:46 minutes)

 

Roulette and the manufacturing industry offer real-life demonstrations of the use of the central limit theorem, control chart monitoring of random variation, creation of x-bar charts and definitions of control limits and out-of-control monitoring.  (28:42 minutes)

Understand the two aspects of confidence intervals--the interval and the confidence level--and see how they are used in blood pressure studies, political and population surveys, and primate research. Included are z intervals for the mean of a normal distribution and behavior of confidence intervals.   (28:53 minutes)

A hiring discrimination case and a study of Shakespearean authorship illustrate the basic reasoning behind tests of significance. The strengths and weaknesses of significance tests are assessed.  Defined are null and alternative hypotheses and p-values. (28:44 minutes)

Discover an improved technique for statistical problems that involve a population mean: the t-statistic for use when s is not known.  Paired samples are emphasized as the most important practical use of these procedures.  The t-confidence interval and t-test and "robustness of t-procedures" are defined.   (28:52 minutes)

Learn how to recognize a two-sample problem and to distinguish such samples from one-sample and paired-sample situations.  Give a confidence interval for the difference between two means.  Demonstrate the two-sample t-test with conservative degrees of freedom.   (28:50 minutes)

How do federal government statisticians estimate how many people are unemployed?  What size sample can give accurate results?  Discover confidence intervals and tests for single proportion and for comparing proportions based on paired and independent samples.   (28:51 minutes)

A two-way table can show the relationship between two categorical variables in a single population or compare the distributions of a single categorical variable in several populations.  The chi-square test for independence/equal distributions in two-way tables is covered.  (28:52 minutes)

See how statistical principles come together in a case study that illustrates planning the data collection, collecting and picturing the data, drawing inferences from the data, and deciding how confident to be about the conclusions.  (28:54 minutes) 

See how statistical principles come together in a case study the illustrates planning the data collection, collecting and picturing the data, drawing inferences from the data, and deciding how confident to be about the conclusions.   (28:51 minutes)