| Calendar |
| Faculty |
| Catalogue |
List >
Introductory >
| Intro Course Sequence | | For AP Teachers | | Calculus Review |
| Modeling - Intro |
| Resampling |
| Survey of Stats |
|
Data Mining >
| Cluster Analysis |
| Data Mining - SAS EM Practicum |
| Data Mining 1 - Intro |
| Data Mining 2 - Unsupervised |
| Decision Trees |
| Logistic Regression |
| Logistic Regression - Advanced |
| Microarray Analysis |
| Natural Lang. Processing |
| SVM in R |
| Text Mining |
| Visualization |
|
Life Science >
| Biostatistics - Medical Research |
| Biostatistics 1 |
| Biostatistics 2 |
| Clinical Trials - Adaptive |
| Clinical Trials - Bayes |
| Clinical Trials - Bioavailability |
| Clinical Trials - Introduction |
| Clinical Trials - Monitoring |
| Clinical Trials - PK & Dose |
| Clinical Trials - Selection Bias |
| Epi 1 - Fundamentals |
| Epi 2 - Bias |
| Epi 3 - Analysis |
| Meta Analysis |
| Microarray Analysis |
| Missing Data - Sensitivity |
| Survival |
| Survival - Advanced |
|
Engineering >
| Design of Experiments |
| Design of Experiments - Advanced |
| Engineering |
| Logistic Regression - Advanced |
| Risk Analysis |
| SPC |
| SPC Advanced |
| Survival - Advanced |
|
Environment >
| Environmental - Bayesian |
| Environmental - Sampling |
| Environmental - Statistics |
| Geostatistics |
| Geostats in R |
| Resampling |
|
Social Science >
| Assessment |
| Choice Modeling |
| Factor Analysis |
| GLM |
| Logistic Regression |
| Longitudinal Data |
| Nonparametrics |
| Rasch - Applications |
| Rasch - Core |
| Rasch - Facets |
| Rasch - Further |
| SEM |
| SEM - Advanced |
| Survey - Complex |
| Survey Analysis |
| Survey Design |
|
Business >
| Choice Modeling |
| Data Mining 1 - Intro |
| Data Mining 2 - Unsupervised |
| Financial Risk |
| Forecasting |
| Forecasting - Advanced |
| National Income |
| Natural Lang. Processing |
| Risk Analysis |
| Visualization |
|
Stat Methods >
| Bootstrap |
| Categorical Data |
| Categorical Modeling |
| Cluster Analysis |
| Count Data |
| Design of Experiments |
| Distributions |
| Exact Tests |
| Factor Analysis |
| Forecasting |
| Forecasting - Advanced |
| GLM |
| Logistic Regression |
| Logistic Regression - Advanced |
| MLE |
| Matrix Algebra |
| Missing Data |
| Missing Data - Sensitivity |
| Mixed Models |
| Modeling - Intro |
| Multivariate |
| Nonparametrics |
| Regression |
| Resampling |
| SAS - Basics |
| Sample Size |
| Visualization |
|
Using R >
| Geostats in R |
| Microarray Analysis |
| R Graphics |
| R Intro (data) |
| R Intro (stats) |
| R Modeling |
| R Programming |
| R ggplot2 |
| SVM in R |
|
Bayesian >
| Bayesian Computing |
| Bayesian MCMC |
| Bayesian Statistics |
| Clinical Trials - Bayes |
| Environmental - Bayesian |
|
|
|
| Tour a Course |
| Learning Style |
| Homework |
| Software |
| Time Requirement |
Communications with Instructor |
|
| How to Register |
| Prerequisites |
| Tuition Discounts |
Transfer/ Withdrawal |
|
| Academic Credit |
| CEU Certificates |
| Programs of Study |
|
| Tutoring |
| Consulting |
| Engage an Expert |
|
| Stat Term Glossary |
| Statistical Symbols |
| Discussion Boards |
Software >
| Statistical Software |
| Free Web-Based |
| SQC Calculators |
|
| Jobs |
| Workshops |
| Stats Books
|
| For Teachers |
|
| Company |
| Faculty |
| Management Team |
| What Students Say |
|
statistics.com statistics.com
|
| View previous topic :: View next topic |
| Author |
Message |
Bitekson
Joined: 24 Jun 2010 Posts: 2
|
Posted: Thu Jun 24, 2010 4:40 am Post subject: Sample size |
|
|
How do i arrive at a statistically representative sample size? What is the minimum sample size for just about any situation?, And how do you arrive there without having to shed much sweat?
Cant really see an acceptable short cut to jargonies of complex statistical formulae, yet would want to.
Its a survey i want to do in a logistically very taxing region. And what's more, no reliable institutions from which to seek help.
Inputs will be highly appreciated. _________________ Bitek,
Jimmiebite (skype) |
|
| Back to top |
|
 |
alethephant
Joined: 06 Sep 2006 Posts: 200 Location: Virginia Beach
|
Posted: Thu Jun 24, 2010 11:48 am Post subject: Sample size |
|
|
Use N = 8/E^2, where E = the effect you want to be able to detect, in units of the standard deviation of the population being sampled.
This formula is not complicated, so it should meet your need. |
|
| Back to top |
|
 |
Bitekson
Joined: 24 Jun 2010 Posts: 2
|
Posted: Fri Jun 25, 2010 12:53 am Post subject: |
|
|
Hi,
Thank you for taking your time trying to help. But i cant make much sense from what you have just given me. Especially the 'effect' you said. _________________ Bitek,
Jimmiebite (skype) |
|
| Back to top |
|
 |
|
|
You cannot post new topics in this forum You cannot reply to topics in this forum You cannot edit your posts in this forum You cannot delete your posts in this forum You cannot vote in polls in this forum
|
Powered by phpBB © 2001, 2005 phpBB Group
|