Name: how analytical methods are checked
Uploaded: 2024-12-05T18:31:54.000Z
Duration: 1 min 15 s
Channel: JoVE

K12 Standards

Virginia  Standards of Learning

HIgh School

Physics

PH.1

PH.1.d

Data Validation

Die Methodenvalidierung ist der Prozess, der eingesetzt wird, um sicherzustellen, dass eine Methode replizierbare Ergebnisse mit akzeptabler Qualität liefert.
Es ist notwendig, wenn die Methode routinemäßig verwendet wird, um eine andere Probenmatrix oder über ein modifiziertes Verfahren zu analysieren.
Dies erfordert verschiedene Parameter der Methodenvalidierung wie Methodenspezifität, Linearität, Genauigkeit, Präzision, Reichweite, Nachweisgrenze, Quantifizierungsgrenze und Robustheit.
Um diese Parameter abzuschätzen, ist es notwendig, den Beitrag von zufälligen und systematischen Fehlern von der Methode und dem Analysten zu unterscheiden.
Dazu gibt die Standardabweichung der Replikationsmessungen Aufschluss über den Zufallsfehler und die Genauigkeit der Methode.
Die Analyse unter Verwendung von Standardreferenzen, Blindproben und einer größeren oder kleineren Stichprobengröße gibt Aufschluss über den systematischen Fehler und die Genauigkeit der Methode.
Während die unabhängige Analyse einer Probe mit alternativen Methoden Aufschluss über die systematischen Fehler der Methode gibt, gibt die Analyse derselben Probe mit der gleichen Methode in verschiedenen Labors Aufschluss über die systematischen Fehler des Analytikers.

datenvalidierung

Die Methodenvalidierung ist ein entscheidender Prozess in der analytischen Chemie, der bestätigen soll, dass eine bestimmte Methode durchgängig zuverlässige und qualitativ hochwertige Ergebnisse liefert. Dieser Prozess ist unerlässlich, wenn eine Methode auf verschiedene Probenmatrizen angewendet wird oder wenn Verfahrensänderungen vorgenommen werden, um sicherzustellen, dass die Ergebnisse in verschiedenen Anwendungen akzeptablen Standards entsprechen.

Zu den wichtigsten Parametern für die Methodenvalidierung gehören:

<ul style="list-style-type: disc; padding-left: 35px; margin: 0;">
	<li>Spezifität: Die Fähigkeit der Methode, den Zielanalyten ohne Störungen durch andere Substanzen genau zu messen.</li>
	<li>Linearität: Die Fähigkeit der Methode, Ergebnisse zu erzielen, die über einen bestimmten Bereich direkt proportional zur Konzentration des Analyten sind.</li>
	<li>Genauigkeit: Die Nähe der gemessenen Werte zum wahren Wert, die die Richtigkeit der Methode widerspiegelt.</li>
	<li>Präzision: Die Konsistenz wiederholter Messungen unter denselben Bedingungen, oft anhand der Standardabweichung bewertet.</li>
	<li>Bereich: Das Intervall zwischen der oberen und unteren Konzentration des Analyten, für das die Methode eine akzeptable Genauigkeit, Präzision und Linearität nachgewiesen hat.</li>
	<li>Nachweisgrenze (LOD): Die kleinste Analytkonzentration, die mit der Methode nachgewiesen werden kann, obwohl sie möglicherweise nicht quantifiziert werden kann.</li>
	<li>Bestimmungsgrenze (LOQ): Die niedrigste Konzentration des Analyten, die mit akzeptabler Genauigkeit und Präzision quantitativ gemessen werden kann.</li>
	<li>Robustheit: Die Fähigkeit der Methode, von kleinen, absichtlichen Abweichungen der Analysebedingungen unbeeinflusst zu bleiben, weist auf ihre Zuverlässigkeit bei routinemäßiger Verwendung hin.</li>
</ul>

Um diese Parameter zu bewerten, muss zwischen zufälligen und systematischen Fehlern unterschieden werden, die sowohl von der Methode als auch vom Analytiker, der die Analyse durchführt, ausgehen können. Die Präzision einer Methode, die oft mit zufälligen Fehlern zusammenhängt, kann anhand der Standardabweichung wiederholter Messungen bewertet werden, die die Konsistenz unter denselben Bedingungen widerspiegelt.

Systematische Fehler beeinflussen oft die Genauigkeit oder wie nahe die Ergebnisse am wahren Wert liegen. Diese können auf verschiedene Weise bewertet werden, z. B. durch Verwendung von Standardreferenzen, Blindproben oder unterschiedlichen Probengrößen. Darüber hinaus können unabhängige Tests mit alternativen Methoden oder die Durchführung derselben Analyse in verschiedenen Labors systematische Fehler aufdecken, die von der Methode bzw. dem Analytiker herrühren.

Alles in allem bietet die Methodenvalidierung die Gewissheit, dass eine Analysemethode zuverlässige Ergebnisse liefert, unabhängig von Änderungen der Probentypen oder Verfahrensanpassungen.

Datenvalidierung

Die Methodenvalidierung ist ein entscheidender Prozess in der analytischen Chemie, der bestätigen soll, dass eine bestimmte Methode konsistent zuverlässige und qualitativ hochwertige ...

Education

Lehre

JoVE Core

Analytical Chemistry

Analytische Chemie

Unit 1

Einheit 1

Method Development and Sampling Techniques

Methodenentwicklung und Probenahmetechniken

method-development-and-sampling-techniques

KEY TERMS AND CONCEPTS

WICHTIGE BEGRIFFE UND KONZEPTE

how analytical methods are checked

Method validation checks whether an analytical chemistry method gives reliable results. It is especially important when the same method is used with different sample matrices or when the procedure is changed. Validation helps show that the method still meets acceptable standards in each case.

Several key checks are used in method validation. Specificity means the method can measure the target analyte without interference from other substances. Linearity means the result changes in direct proportion to analyte concentration over a set range. Accuracy is how close the measured value is to the true value, and precision is how consistent repeated measurements are under the same conditions.

Other checks describe how well the method works at low or limited concentrations. Range is the interval between the upper and lower concentrations where accuracy, precision, and linearity are acceptable. The limit of detection, or LOD, is the smallest amount that can be detected but not necessarily measured exactly. The limit of quantitation, or LOQ, is the lowest amount that can be measured with acceptable accuracy and precision. Robustness shows whether small, planned changes in analytical conditions affect the method.

Method validation also helps separate random errors from systematic errors. Random errors affect precision, and they are often described using the standard deviation of repeated measurements. Systematic errors affect accuracy and how close the result is to the true value. These errors can be checked with standard references, blanks, different sample sizes, alternative methods, or tests in different laboratories. Validation gives confidence that an analytical method will produce dependable results, even when the sample type or procedure changes.

How Analytical Methods Are Checked

development of analytical methods

Analytical Methods: Technique to Protocol

Analytical methods follow a clear path from technique to protocol. In analytical chemistry, a technique is the scientific principle used to explain a chemical measurement. A method applies that technique to a sample of interest. The next steps are procedure and protocol. A procedure gives the directions for carrying out the analysis with an analytical method. A protocol is the detailed set of guidelines for that procedure, and it should be followed closely to get the desired results. <br...

quality control

Quality Control Charts and Lab Records

Quality control charts, proficiency testing, and lab records are key parts of quality control in a laboratory. These steps help keep a system under statistical control. They also help track data, show trends, and spot variations that may affect the accuracy of an analysis. One common tool is a quality control chart. This chart plots one or more analytical characteristics over time. The measured values are taken at different times during the analysis and compared with the known value of...

quality assurance

Quality Checks in Analytical Testing

Quality assurance in analytical testing brings together the checks that help a system perform properly. It includes quality control, quality assessment, and internal corrective measures. These parts work in a cycle to support reliable results. Quality control happens before and during the analysis. Quality assessment takes place during and after the investigation. Internal corrective measures are then based on the results of post-analysis quality assessment, or they may be applied before a new...

data validation

Method validation checks whether an analytical chemistry method gives reliable results. It is especially important when the same method is used with different sample matrices or when the procedure is changed. Validation helps show that the method still meets acceptable standards in each case. Several key checks are used in method validation. Specificity means the method can measure the target analyte without interference from other substances. Linearity means the result changes in direct...

qualitative analysis

Classical and Instrumental Sample ID

Qualitative analysis identifies the elements, ions, or compounds in an unknown sample. It is the first step in the hierarchy of analytical goals. That makes it the starting point for scientific study before quantitative analysis or other forms of analysis. Two main approaches are used in qualitative analysis: classical methods and instrumental methods. Classical methods depend on the visible or sensory result of a chemical reaction, such as a color change, a precipitate, or even a smell. These...

quantitative analysis

Measuring Analyte Concentration

Quantitative analysis measures the amount of a specific substance, called the analyte, in a sample. If the sample composition is unknown, qualitative analysis comes first. That step identifies the components so the correct substances can be measured during the quantitative phase. This method depends on two key measurements. Scientists measure the sample quantity and also a property that is proportional to the amount of analyte. Together, these measurements help determine the analyte...

instrument calibration

Calibrating Lab Instruments for Accurate Results

Calibration helps lab instruments produce accurate and consistent results. It is important in manufacturing, healthcare, testing laboratories, and scientific research. Each instrument needs a calibration process that matches its design and function. This process improves data accuracy and helps results stay reliable. An analytical balance measures mass and needs regular calibration to stay precise. It is calibrated by comparing its readings with known standard weights. These weights act as...

glassware calibration

Calibrating Lab Glassware for Accurate Volume

Calibrating lab glassware helps students measure liquids accurately in the analytical laboratory. It reduces volume errors and supports consistent results across measurements. This matters when using volumetric flasks, pipettes, burettes, and other tools that depend on precise volume readings. Volumetric flasks are used to prepare aqueous solutions with a precise final volume. They have a calibration line on the neck. To calibrate one, fill it with distilled water until the meniscus, the...

standard solutions

Preparing Standard Solutions in the Lab

Standard solutions are prepared to have a precisely known concentration or composition. In analytical chemistry, this accuracy is important because it supports reliable results. A primary standard is a highly pure, stable substance with a high molar mass. It is fully soluble in water, which is the most commonly used solvent in analytical chemistry. A primary standard solution can be used to standardize a secondary standard. Secondary standards have known concentrations, but they are usually...

blank solutions

Blank Solutions in Analytical Testing

Blank solutions are used in analytical testing to show the background signal before a sample is measured. A blank solution does not contain the analyte, which is the substance of interest being tested or measured. It is usually made with the same reagents and procedure as the sample solution, but without the analyte. The main purpose of a blank solution is to control for background interference and contamination. Reagents, solvents, or lab equipment can sometimes create a detectable signal on...

sampling methods: overview

How Sampling Shapes Lab Results

Sampling shapes lab results by determining how a smaller sample represents a larger population. In analytical chemistry, testing an entire population is often impractical or impossible, so samples are collected to make inferences about the whole group. The sampling method is the process used to choose individuals or items for that sample. Common sampling methods include random, judgemental, systematic, stratified, and cluster sampling. Each method can affect the quality of the data in a...

sampling methods: sample types

Sampling Materials in Solid, Liquid, Gas

Sampling materials are grouped as solid, liquid, or gas. The type of sample helps decide the right collection method. Solid samples can include sediments from water bodies, soil, metals, and biological tissues. Sediment sampling from water bodies can be done in two common ways. Grab sampling uses a device to collect a discrete sample from the bottom with minimal disturbance. These samples may not show the full area because conditions can vary from place to place. Piston coring collects a...

sampling plans

Choosing Samples for Reliable Results

Sampling is a key step in analytical chemistry. It helps researchers collect data that represents a larger population. The main sampling methods in this topic are random, judgmental, systematic, stratified, and cluster sampling. Random sampling gives each member of the population an equal chance of being chosen. Researchers often use a random number generator or a lottery-style method. For example, a polymer sheet can be divided into 1 cm x 1 cm sections, and 10 sections can be selected at...

sample preparation for analysis: overview

Preparing Samples by State and Form

Sample preparation depends on the state and form of the sample before analysis. It helps make the sample ready for accurate measurement. The main goal is to extract the analyte, which is the substance being measured, and remove parts that could interfere with the analysis. Solid samples often need the most handling. Large solids are usually ground, crushed, or milled to make them smaller and increase surface area. The sample is then sieved and mixed so it has a uniform composition. After that,...

sample preparation for analysis: advanced techniques

sample-preparation-for-analysis-advanced-techniques

Preparing Complex Samples for Analysis

Preparing complex samples for analysis often requires special digestion and fusion methods. Samples with inorganic or organic material can be hard to dissolve or break down. Common sample preparation methods include acid digestion, fusion, dry ashing, and wet digestion. These steps help turn difficult samples into forms that can be tested reliably and again with similar results. Acid digestion is often used for inorganic materials that do not dissolve in water. It is useful for soil and...

sample handling

Sample Transport and Storage Basics

Sample transport and storage help keep specimens intact before testing. Moving a sample from the collection point to the laboratory requires careful handling. The sample should be sealed well and clearly labeled. These steps help prevent cross-contamination and support reliable results. Temperature control is also important during transport. Some samples travel in insulated containers, cool packs, or refrigerated vehicles so they stay within the needed temperature range. After the samples...

contaminants and errors

Sampling Errors in Sample Preparation

Sampling errors in sample preparation can affect the accuracy of laboratory results. Two common problems are concentration bias from poor sample splitting and contamination from reducing particle size by grinding or homogenization. Recognizing these errors helps make analysis more reliable. The number of samples also matters when a target population follows a normal distribution. In that case, the sample size ns can be found with a formula that uses the t-value for the chosen confidence level,...

key terms and concepts

Learn how method validation tests specificity, accuracy, precision, LOD, LOQ, and robustness to show an analytical chemistry method gives dependable results.

How Analytical Methods Are Checked | JoVE K12

analytical chemistry

JoVE Core Analytical Chemistry simplifies complex chemical principles by breaking them down into clear, engaging animations, making topics from SI Units to NMR spectroscopy more accessible and straightforward. Additionally, the scientist-in-action videos highlight the application of these concepts in real-world research conducted in laboratories globally.

Florida Department of Education

High School

Nature of Science

SC.912.N.1

SC.912.N.1.4

Scientific Method

The scientific method is used to solve problems and explain phenomena. The development of the scientific method coincided with changes in philosophy ...

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not ...

Unusual Results

Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In ...

Expected Value

The expected value is known as the &#34;long-term&#34; average or mean. This means that over the long term of experimenting over and over, you would ...

What is a Hypothesis?

A hypothesis can be a simple sentence or statement about a property or any phenomenon observed or predicted for a population. It is usually a claim about ...

Null and Alternative Hypotheses

The actual hypothesis testing begins by considering two hypotheses. They are termed&#160; the null hypothesis and the alternative hypothesis. These ...

Types of Hypothesis Testing

There are three types of hypothesis tests: right-tailed, left-tailed, and two-tailed.
When the null and alternative hypotheses are stated, it is observed ...

Introduction to Test of Independence

In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their ...

Hypothesis Test for Test of Independence

The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test ...

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a ...

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using ...

empirical-method-to-interpret-standard-deviation

Empirical Method to Interpret Standard Deviation

The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The ...

Data Collection by Experiments

Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method ...

Solving Problems in Physics

Problem-solving is the ability to apply general physical principles to specific situations, usually expressed by equations. It is an essential skill in ...

The student will demonstrate an understanding of scientific and engineering practices by. asking questions and defining problems
• ask questions that arise from careful observation of phenomena, examination of a model or theory, unexpected results, and/or to seek additional information
• determine which questions can be investigated within the scope of the school laboratory
• make hypotheses that specify what happens to a dependent variable when an independent variable is manipulated
• generate hypotheses based on research and scientific principles
• define design problems that involves the development of a process or system with interacting components and criteria and constraints

PH.1.a

What is an Experiment?

An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two ...

Study Design in Statistics

A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research ...

Experimental Designs

An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are ...

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally ...

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in ...

Controls in Experiments

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more ...

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected ...

Blinding

Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control ...

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and ...

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the ...

Data Collection by Survey

The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data ...

Units and Standards of Measurement

A physical quantity is defined either by specifying its measurement method or by stating how it is calculated from other measurements. For example, ...

Estimation of the Physical Quantities

On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as ...

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Base Quantities and Derived Quantities

In any system of units, the units for some physical quantities must be specified through a measurement process. These measurements are the base quantities ...

Conversion of Units

Sometimes, there is a need to convert from one unit to another one. For instance, reading a cookbook in which quantities are expressed in units of liters ...

The student will demonstrate an understanding of scientific and engineering practices by. planning and carrying out investigations
• individually and collaboratively plan and conduct observational and experimental investigations
• plan and conduct investigations or test design solutions in a safe manner
• select and use appropriate tools and technology to collect, record, analyze, and evaluate data

PH.1.b

Review and Preview

Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative ...

What is a Frequency Distribution

A frequency is the number of times a value of the data occurs. The sum of all the frequency values represents the total number of students included in the ...

Ogive Graph

An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, ...

Histogram

The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data ...

Relative Frequency Histogram

The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. ...

Scatter Plot

The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a ...

Time-Series Graph

A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct ...

Bar Graph

A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show ...

Multiple Bar Graph

As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can ...

Pareto Chart

A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the ...

Pie Chart

A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each ...

What is Central Tendency?

Descriptive statistics describe or summarize relevant characteristics of a sample and aid in the analysis of data of interest. When analyzing large ...

What is Variation?

Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of ...

Range

The range is one of the measures of variation. It can be defined as the difference between a dataset&#39;s highest and lowest values. For example, in the ...

Standard Deviation

The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The ...

Calculating Standard Deviation

The standard deviation is the most common measure of variation. It is a value that tells us how far a data value is from the mean value in a dataset. ...

Variance

&#160;The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative ...

Coefficient of Variation

The coefficient of variation measures the dispersion of the data points or distribution around the mean. Using the coefficient of variation, we can ...

Contingency Table

A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution ...

Statistical Analysis: Overview

An analysis is usually conducted by replicated sampling or repeated measurements on the same sample. This leads to scattered results rather than a single ...

The student will demonstrate an understanding of scientific and engineering practices by. interpreting, analyzing, and evaluating data
• record and present data in an organized format that communicates relationships and quantities in appropriate mathematical or algebraic forms
• use data in building and revising models, supporting an explanation for phenomena, or testing solutions to problems
• analyze data using tools, technologies, and/or models (e.g., computational, mathematical, statistical) in order to make valid and reliable scientific claims or determine an optimal design solution
• analyze data graphically and use graphs to make predictions
• consider limitations of data analysis when analyzing and interpreting data
• evaluate the effects of new data on a working explanation and/or model of a proposed process or system
• analyze data to optimize a design

PH.1.c

Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality ...

Qualitative Analysis

Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of ...

Quantitative Analysis

Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample&#39;s composition is unknown, ...

Models, Theories, and Laws

Scientists frequently use models to help them comprehend a specific collection of phenomena. In physics, a model is a condensed version of a physical ...

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The student will demonstrate an an understanding of scientific and engineering practices by. constructing and critiquing conclusions and explanations
• make quantitative and/or qualitative claims based on data
• construct and revise explanations based on valid and reliable evidence obtained from a variety of sources
• apply scientific ideas, principles, and/or evidence to provide an explanation of phenomena or design solutions
• compare and evaluate competing arguments in light of currently accepted explanations and new scientific evidence
• construct arguments or counterarguments based on data and evidence
• differentiate between scientific hypothesis, theory, and law

The student will demonstrate an understanding of scientific and engineering practices by.

How Analytical Methods Are Checked

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