Video Segment 1: What Is Statistics?
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This video is an introduction to the links between our world and statistics using anecdotes and contemporary applications. It also covers the evolution of the discipline.
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Video Segment 2: Picturing Distributions
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This video will show the key characteristics in the distribution of a histogram. Using stem plots, this program also emphasizes the importance of seeking explanations for gaps and outliers in small data sets.
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Video Segment 3: Describing Distributions
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This video examines the difference between mean and median, explains the use of quartiles to describe a distribution, and uses box plots and the five-number summary for comparing and describing data.
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Video Segment 4: Normal Distributions
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This video introduces smooth curves, normal curves, and a single normal curve for standardized measurement, showing ways to describe the shape of a distribution using progressively simpler methods.
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Video Segment 5: Normal Calculations
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This video teaches how to convert the standard normal and use the standard deviation; how to use a table of areas to compute relative frequencies; how to find any percentile; and how a computer creates a normal quartile.
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Video Segment 6: Time Series
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This video shows ways to present smooth data and recognize whether a particular pattern is meaningful. A time series and the 68-95-99.7 rule are used in some examples.
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Video Segment 7: Models for Growth
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This video covers linear growth, least squares, exponential growth, and straightening an exponential growth curve by logic.
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Video Segment 8: Describing Relationships
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This video describes how to use a scatter plot to display relationships between variables. Patterns in variables (positive, negative, and linear association) and the importance of outliers are also discussed.
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Video Segment 9: Correlation
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This video will explain how to derive and interpret the correlation coefficient. Then it will go into how to use the square of the correlation coefficient to measure the strength and direction of a relationship between two variables.
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Video Segment 10: Multidimensional Data Analysis
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This video will show how the computer can graph multivariate data and its various ways of presenting it. A study on the Chesapeake Bay and its environmental stresses is analyzed on many variables.
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Video Segment 11: The Question of Causation
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This video defines the concepts of common response and confounding, explains the use of two-way tables of percents to calculate marginal distribution, uses a segmented bar to show how to visually compare sets of conditional distributions, and presents a c
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Video Segment 12: Experimental Design
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This video distinguishes between observational studies and experiments and reviews basic principles of design including comparison, randomization, and replication. There is a study on heart disease in the video that demonstrates some of the advantages of
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Video Segment 13: Blocking and Sampling
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This video focuses on random sampling and the census as two ways to obtain reliable information about a population. It covers single- and multi-factor experiments.
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Video Segment 14: Samples and Surveys
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This video shows how to improve the accuracy of a survey by using stratified random sampling and how to avoid sampling errors such as bias. A 1936 Gallup poll provides an illustration of the perils of under-coverage.
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Video Segment 15: What Is Probability?
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This video introduces the concepts of sample space, events, and outcomes, and demonstrates how to use them to create a probability model. The work of statistician Persi Deaconess's is discussed in regards to probability theory.
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Video Segment 16: Random Variables
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This video will demonstrate how to determine the probability of any number of independent events. To show how probability can be used, a statistician, who helped investigate the space shuttle accident, is brought in to explain.
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Video Segment 17: Binomial Distributions
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This video discusses binomial distribution and the criteria for it, and describes a simple way to calculate its mean and standard deviation. A device from the Boston Museum of Science is added to explain the binomial distribution.
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Video Segment 18: The Sample Mean and Control Charts
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This video will explain how to create x-bar charts and the definitions of control limits and out-of-control limits. To demonstrate the central limit theorem, casino owners and the manufactory industry are studied.
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Video Segment 19: Confidence Intervals
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This video explains the parts of the confidence interval and gives an example of how it is used to measure the accuracy of long-term mean blood pressure.
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Video Segment 20: Significance Tests
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This video explains the basic reasoning behind tests of significance and the concept of null hypothesis. It also shows how a z-test is carried out when the hypothesis concerns the mean of a normal population with known standard deviation.
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Video Segment 21: Inference for One Mean
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This video explains an improved technique for statistical problems that involve a population mean: the t statistic for use when _ is not known. Emphasis is on paired samples and the t confidence test and interval.
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Video Segment 22: Comparing Two Means
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This video will show you how to recognize a two-sample problem and how to distinguish such problems from one- and paired-sample situations are
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Video Segment 23: Inference for Proportions
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This video focuses on inference about the mean of a population to exploring inferences about a different kind of parameter, the proportion or percent of a population that has a certain characteristic.
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Video Segment 24: Inference for Two-Way Tables
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This video concerns inference about two-way tables, covering use of the chi-square test and null hypothesis in determining the relationship between two ways of classifying a case.
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Video Segment 25: Inference for Relationships
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With this video, simple linear regression, emphasizing slope, and prediction will be explained.
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Video Segment 26: Case Study
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This video presents a detailed case study of statistics at work. Operating in a real-world setting, the video traces the practice of statistics, planning the data collection, collecting and picturing the data and drawing inferences from the data.
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