MORE ON DISTRIBUTIONS
1. AGENDA:
1. The binomial distribution
1. Bernoulli trials
2. Sampling distributions
3. Reading:
1. Agresti and Finlay, Statistical Methods, Chapter 4, pages
94 to 99; pages 187 to 191.
2. PROBLEM:
1. Here's a hypothetical polic
More on Graphical and Numerical Summaries
1. CLASS 10 AGENDA:
1. Percentiles
2. Frequency distributions and histograms
3. Times Series
1. More on measures of change
4. Reading:
1. Agresti and Finlay, Statistical Methods for the Social
Sciences, pag
Distributions
1. CLASS 9 AGENDA:
1. Populations and samples
2. Distributions
3. Percentiles and Quartiles
4. The summation sign
5. Reading:
1. Agresti and Finlay, Statistical Methods for the Social
Sciences, chapter 3.
2. POPULATIONS AND SAMPLES:
1. P
The Normal Distribution
(Continued)
1. AGENDA:
1. Using the normal distribution to solve problems.
1. Areas under the normal curve
2. Z scores
3. Reading:
1. Agresti and Finlay, Statistical Methods, Chapter 4,
pages 86-99.
2. QUESTION:
1. Based on A
EXPLAINING VARIATION AND ANALYSIS OF VARIANCE
1. AGENDA:
1. Touring the net and obtaining data
2. The idea of "explained" variation
3. Analysis of variance
1. Using box plots to compare measures of central tendency
and dispersion among different po
Time Series and Distributions
1. CLASS 11 AGENDA:
1. Time series
1. Semi-logarithmic plots
2. Intervention analysis and the interpretation of time series.
2. Probability distributions
1. The normal distribution.
3. Reading:
1. Agresti and Finlay, Sta
The Normal Distribution
1. AGENDA:
1. The normal distribution.
1. Interpretation of the normal distribution function.
2. Area under the normal curve
3. The standard normal distribution
2. THE NORMAL PROBABILITY DISTRIBUTION:
1. See the notes from the
Descriptive Statistics and Numerical Summaries
1. CLASS 8 AGENDA:
1. Variance and standard deviation
2. Box-and-whiskers plot.
3. Measuring change
4. Populations and samples
5. Reading:
1. Agresti and Finlay, Statistical Methods, pages 45 to 67 as
n
STATISTICAL COMPUTING: MINITAB
1. AGENDA:
1. Internet and MINITAB demonstration
2. Data types and structures
3. Reading:
1. The Student Edition of MINITAB for Windows, Tutorial
pages 18 to 33.
1. Try second tutorial.
2. Agresti and Finlay, Statistical
Overview of Course and Information Network
1. CLASS 1: AGENDA
1. Why applied statistics?
1. Some policy and social science research issues
2. Drugs, alcohol and violence.
2. Course Procedures
1. Activities
2. The "information network"
2. SUBSTANTIVE PROBL
Data Types and Structures
1. AGENDA FOR CLASS 4:
1. Data types and structures
2. Constructing and interpreting tables
2. DATA STRUCTURES:
1. Raw data matrix
1. Cases X variables as in SPSS or MINITAB data windows.
2. Example:
1. Here are hypothetical
Descriptive Statistics
(Continued)
1. CLASS 5 AGENDA:
1. Additional examples of stem-and-leaf displays
2. Depths
3. Descriptive statistics: the median, hinges, and the mean
4. Reading:
1. Agresti and Finlay, Statistical Methods, pages 40-42, 4552.
1. N
Windows and MINITAB
1. AGENDA:
1. Some further remarks about the course
2. A brief discussion of Windows
3. The importance of saving data
4. MINITAB
1. A simple example: comparative educational statistics
2. Entering and saving data
3. MINITAB statist
Descriptive Statistics
(Continued)
1. CLASS 7 AGENDA:
1. Interpretation of hinges
2. The arithmetic mean
3. The standard deviation and variance, measures of dispersion
1. Summation notation
4. Reading:
1. Agresti and Finlay, Statistical Methods, pages