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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
Choosing Between z and t Distribution01:25

Choosing Between z and t Distribution

The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...

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Related Experiment Video

Updated: Jun 27, 2026

Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

Sample size determination for categorical responses.

Dimitris Mavridis1, Colin G G Aitken

  • 1School of Mathematics and The Joseph Bell Centre for Forensic Statistics and Legal Reasoning, The King's Buildings, The University of Edinburgh, Mayfield Road, Edinburgh EH9 3JZ, U.K.

Journal of Forensic Sciences
|December 2, 2008
PubMed
Summary
This summary is machine-generated.

This study reviews sampling procedures for estimating population characteristics, offering recommendations for both binary and multinomial responses. It details sequential methods to optimize sample size and decision-making in forensic science applications.

Related Experiment Videos

Last Updated: Jun 27, 2026

Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

Area of Science:

  • Statistical methodology
  • Forensic science applications
  • Sampling theory

Background:

  • Estimating population characteristics requires appropriate sampling procedures.
  • Forensic science often deals with discrete data categorized into distinct groups.
  • Existing methods may not fully address the complexities of sequential sampling for various response types.

Purpose of the Study:

  • To review and recommend optimal sample sizes for estimating population parameters.
  • To describe and evaluate sampling procedures for binary and multinomial responses.
  • To provide guidance for forensic science data analysis.

Main Methods:

  • Description of four sampling procedures for binary responses, including a sequential probability ratio test and Bayesian-informed priors.
  • Development of a sequential procedure for multinomial responses based on probability intervals.
  • Illustration of the multinomial procedure using ternary diagrams for trinomial data.

Main Results:

  • The study details sequential sampling rules that control error probabilities and decision thresholds.
  • A generalized sequential procedure is presented for multinomial populations with more than two categories.
  • Recommendations are provided for selecting appropriate sampling procedures based on context.

Conclusions:

  • Sequential sampling methods offer efficient ways to estimate population characteristics in forensic contexts.
  • The proposed procedures are adaptable for both binary and multinomial data.
  • The choice of sampling procedure should be guided by the specific characteristics of the data and research objectives.