Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Stratified Sampling Method01:16

Stratified Sampling Method

11.7K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
11.7K
Sampling Plans01:23

Sampling Plans

1.5K
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
1.5K
Statistical Significance01:37

Statistical Significance

21.1K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
21.1K
Comparing Experimental Results: Student's t-Test01:09

Comparing Experimental Results: Student's t-Test

5.8K
The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
5.8K
Significance Testing: Overview01:04

Significance Testing: Overview

10.2K
Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
10.2K
Sampling Distribution01:12

Sampling Distribution

17.6K
Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
17.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Delirium: Medical Students' Knowledge and Effectiveness of Different Teaching Methods.

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry·2019
Same author

Automation of the standard DNA differential extraction on the Hamilton AutoLys STAR system: A proof-of-concept study.

Forensic science international. Genetics·2019
Same author

Improving the efficacy of the standard DNA differential extraction method for sexual assault evidence.

Forensic science international. Genetics·2018
Same author

Evaluating the efficacy of DNA differential extraction methods for sexual assault evidence.

Forensic science international. Genetics·2017
Same author

Evaluation of the RapidHIT™ 200 and RapidHIT GlobalFiler(®) Express kit for fully automated STR genotyping.

Forensic science international. Genetics·2016
Same author

Material modifications for the alkaline differential extraction method for sexual assault evidence.

Forensic science international. Genetics·2013

Related Experiment Video

Updated: Apr 30, 2026

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.3K

Stochastic sampling effects in STR typing: Implications for analysis and interpretation.

Mark D Timken1, Sonja B Klein1, Martin R Buoncristiani1

  • 1State of California, Department of Justice, Jan Bashinski DNA Laboratory, 1001 W. Cutting Blvd., Richmond, CA 94804, USA.

Forensic Science International. Genetics
|May 7, 2014
PubMed
Summary
This summary is machine-generated.

Stochastic effects in forensic DNA analysis, such as peak imbalance and allelic dropout, stem from pre-PCR sampling. Modeling these effects aids in standardizing STR typing results across different kits and platforms.

Keywords:
Heterozygous balanceLogistic regressionLow-template DNAPoissonShort tandem repeatStochastic

More Related Videos

Exploring Life History Choices: Using Temperature and Substrate Type as Interacting Factors for Blowfly Larval and Female Preferences
12:14

Exploring Life History Choices: Using Temperature and Substrate Type as Interacting Factors for Blowfly Larval and Female Preferences

Published on: November 17, 2023

2.2K
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

1.2K

Related Experiment Videos

Last Updated: Apr 30, 2026

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.3K
Exploring Life History Choices: Using Temperature and Substrate Type as Interacting Factors for Blowfly Larval and Female Preferences
12:14

Exploring Life History Choices: Using Temperature and Substrate Type as Interacting Factors for Blowfly Larval and Female Preferences

Published on: November 17, 2023

2.2K
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

1.2K

Area of Science:

  • Forensic Science
  • Genetics
  • Molecular Biology

Background:

  • Forensic STR typing is complicated by stochastic effects at low DNA template levels.
  • These effects include reduced heterozygous peak balance and increased allelic dropout.

Purpose of the Study:

  • To investigate the origins of stochastic effects in forensic STR typing.
  • To model peak-height imbalance and allelic dropout in low-template DNA samples.

Main Methods:

  • Used AmpFlSTR Identifiler Plus and MiniFiler kits with a DNA dilution series.
  • Analyzed amplicons on Applied Biosystems 3130xL and 3500 genetic analyzers.
  • Applied Poisson distribution and logistic regression for statistical modeling.

Main Results:

  • STR/genetic analyzer combinations showed similar normalized peak-height ratio statistics.
  • Poisson modeling confirmed pre-PCR sampling as the source of peak-height imbalance.
  • Pre-PCR sampling simulations accurately predicted allelic dropout frequencies.

Conclusions:

  • Pre-PCR stochastic sampling is the primary driver of peak-height imbalance and allelic dropout.
  • Accurate DNA quantification could standardize STR typing results across platforms.
  • This approach can aid in validation studies and comparing results from different STR/CE combinations.