VIDEO TAPES PROGRAMS: Against All Odds

PROGRAM 1: What is Statistics?

An overview of the nature and impact of statistics using historical anecdotes and short views of contemporary applications.

PROGRAM 2: Picturing Distributions

Presenting and interpreting the distribution of a single variable. Techniques taught include stemplots, frequency tables and histograms.

PROGRAM 3: Describing Distributions: Numerical Description of Distributions Numerical measures of specific aspects of a distribution: center (mean, median), spread (percentiles, the five-number summary, boxplots, and the standard deviation). Resistance and its lack.

PROGRAM 4: Normal Distributions

Topics: density curves as smoothed histograms: mean, median, percentiles for density curves; the normal distributions (general shape, locating the mean and standard deviation, the 68-95-99.7 rule).

PROGRAM 5: Normal Calculations

Standardization and calculation of normal relative frequencies from tables; assessing normality by normal quantile plots.

PROGRAM 6: Time Series

From the distribution of a single variable we move to an examination of change over time. Topics: statistical control, inspecting time series for trend, seasonal variation cycles; smoothing by averaging, either over many units per time or over time by running medians.

PROGRAM 7: Models For Growth

Mathematical models for the overall pattern of simple kinds of growth over time. Topics: linear growth, with review of the geometry of straight lines and anintroduction to the least squares idea; exponential growth, and straightening an exponential growth curve by logarithms; prediction and extrapolation.

PROGRAM 8: Describing Relationships

Topics: scatterplots and their variations, smoothing scatterplots of response vs. explanatory variable by median trace; linear relationships, least squares regression lines, and comment on outliers and influential observations.

PROGRAM 9: Correlation

Correlation and its properties; the relationship between correlation and regression.

PROGRAM 10: Multidimensional Data Analysis

The impact of computing technology on statistics, especially graphics for displaying multidimensional data. A case study in data analysis will employ techniques discussed in previous programs.

PROGRAM 11: The Question of Causation

Association between categorical variables displayed in a two-way table; Simpson's paradox; the varied relations among variables that can underlie an observed association; how evidence for causation is obtained.

PROGRAM 12: Experimental Design

Advantages of planned datacollection over anecdotal evidence or available data. The idea of an experiment. Basic principles of design: comparison, randomization, replication.

PROGRAM 13: Blocking and Sampling: Experiments and Samples

Further principles of design: two or more factors and blocking. Introduction to sample surveys: the danger of bias, random sampling.

PROGRAM 14: Samples and Surveys: Sampling and Sampling Distributions More elaborate sample designs: stratified and multistage designs. The practical difficulties of sampling human populations. The idea of a sampling distribution.

PROGRAM 15: What is Probability?

Probability as a model for long term relative frequencies or personal assessment of chance. Sample space, basic rules of assigning probability: , , addition rule for disjoint events.

PROGRAM 16: Random Variables

Independence and the multiplication rule for independent events. Discrete and continuous random variables. Mean and variance of a random variable.

PROGRAM 17: Binomial Distributions

The law of large numbers.Addition rules for means and variances of random variables. The binomial distributions for sample counts. Normal approximation to binomial.

PROGRAM 18: The Sample Mean and Control Charts

The sampling distribution of . The central limit theorem, control charts and statistical process control.

PROGRAM 19: Confidence Intervals

The reasoning behind confidence intervals, Z-intervals for the mean of a normal distribution. Behavior of confidence intervals.

PROGRAM 20: Significance Tests

The reasoning behind significance tests illustrated by the simple case of tests on a normal mean with known standard deviation. Null and alternative hypotheses and p-values, and cautions on the limited information provided by tests.

PROGRAM 21: Inference for One Mean

Inference aboutthe mean of a single distribution, with emphasis on paired samples as the most important practical use of these procedures. The t confidence interval and test.

PROGRAM 22: Comparing Two Means

The two-sample t confidence intervals for comparing means; brief mention of the sensitivity of the corresponding procedures for variances to nonnormality and their consequent impracticality.

PROGRAM 23: Inference for Proportions

Confidence intervals and tests for a single proportion and for comparing proportions based on paired and independent samples.

PROGRAM 24: Inference for Two-Way Tables

Chi-square test for independence/equal distributions in two-way tables.

PROGRAM 25: Inference for Relationships

Inference for simple linear regression, emphasizing slope and prediction.

PROGRAM 26: Case Study

A case study that illustrates the major aspects of statistical thinking: planning data collection, analysis by graphs and informal inference, more data collection in response to partial success.