The "Agency Approach" To Locating Government Information on the Internet: a tutorial.
Animated Statistics Demonstrations
Tutorials regarding variance and standard deviation, probability, sampling distributions, standard error, confidence intervals, analysis of variance.
This module is an interactive tutorial which gives a comprehensive view of Probability and Statistics. This interactive module covers basic probability, random variables, moments, distributions, data analysis including regression, moving averages, exponential smoothing, and clustering.
How to Effectively Locate Federal Government Information on the World Wide Web Information from the U. S. Government is appearing with increasing frequency on the Internet. In many cases the Internet is the only place to locate important government information. Virtually all agencies now maintain their own web pages, on which are linked statistical data, news releases and other full-text publications. As time passes, more data will be in online format rather than standard print sources. In the future, searching the Web will become the primary means of locating government data. This “hands-on” workshop is designed to demonstrate how to maximize retrieval of federal government information on the Web.
Tutorials on univariate data, bivariate data, introduction to probability, normal distribution, sampling distributions, point estimation, confidence intervals, logic of hypothesis testing, prediction, Chi Square, etc.
Tutorials on distributions, probability and stochastic processes, statistics, and models.
Introduction to Data Collection and Analysis
Introduction to Descriptive Statistics
A tutorial on the visual display of information and Linear/nonlinear relationships.
Introduction to Statistical Methods in Education
Learning Statistics on the Internet
Meta - Analysis: Methods of Accumulating Results Across Research Domains
Meta-analysis is a set of statistical procedures designed to accumulate experimental and correlational results across independent studies that address a related set of research questions. The paper gives a brief description of meta-analysis methods based on procedures suggested by Hunter, Schmidt, and Jackson (1982) and Hunter and Schmidt (1990). It also presents the formulas and procedures needed for converting study statistics to a common metric, calculating the sample weighted mean r and d, and correcting for range restriction and sampling and measurement error.
I have written these pages for researchers and students in the sport and exercise sciences.
Researching Trends in the Hospitality Industry - A GGU University Library Research Strategy Tutorial
This tutorial is a discussion on sampling in research it is mainly designed to equip beginners with knowledge on the general issues on sampling that is the purpose of sampling in research, dangers of sampling and how to minimize them, types of samplingand guides for deciding the sample size.
Smart: Explorapedia of Statistical and Mathematical Techniques for use in Research and Technology
Statistical Data Analysis: Prove It with Data
- Computers and Statistical Data Analysis
- Questionnaire Design and Surveys Sampling
- Time Series Analysis and Forecasting Techniques
- Popular Distributions and Their Typical
- Topics in Statistical Data Analysis
The Statistical Instruction Internet Palette from the Arizona State MSMS program
Each page is a data entry form that will allow you to type data in and will write a page that walks you through the steps of computing your statistic.
Basic definitions on presenting data, sampling, probability, confidence intervals, hypothesis testing, paired data, correlation and regression, design of experiments and ANOVA, categorical data, time series data.
Discussions regarding normal approximation of binomial distribution, poisson distribution, mean and variance in the normal distribution, binomial distribution, and central limit theorem.
SticiGui©: Statistical Tools for Internet and Classroom Instruction with a Graphical User Interface
This is a web-based course in introductory statistics. It is interactive: students perform numerical experiments, analyze data, and manipulate plots to learn fundamental statistical and probabilistic concepts. The text and the problem sets combine guided exploration with the presentation of new material. The format encourages students to practice exercises in the text while completing online assignments. The practice exercises are graded instantly, and detailed solutions are one click away. It is dynamic: the examples and exercises change every time a page is reloaded, providing a practically unlimited number of practice problems.
How to produce data, summarize and present data, Variation and Probability, Statistical Inference and Control Charts.
Attention CLU students, faculty, and staff: If you didn't find your answer on these pages, ask your Information Specialists; stop by the Reference Desk, call us at 3255 or E-mail the Reference Desk.
Graphics by Brenda Coan and Gary H. Schrickel
Page created by Susan Herzog
Pearson Library
Information Systems and Services
California Lutheran University
Last update: September 25, 2000
Broken links, suggestions or questions, please E-mail Susan.