The previously recorded answer in inaccurate on several levels (see below for quotations of previous repsonse)
Linearity is the correlation of a regression line. Range is typically derived from linearity. Range implies that the method developed corresponds to the "range"between 80-120% (ideally) of the expected sample range (concentration, wt. etc). For content uniformity, range is expected to be 70-130% of the test concentration. These are guidelines governed by ICH Q2 R1 (International Conference for Hamonisation).
In terms of HPLC method development:
LOQ is the smallest amount that will give a S/N ratio of 10 meaning this is the smallest amount you may give a numerical value with confidence. TYPICALLY, THE LOWER RANGE (AND USUALLY LINEARITY) IS LOQ.
LOD is the smallest value that will give an S/N ratio of 3, meaning you can say the specific compound is there qualitatively, but not quantitate the compound.
Previous:
"The range is any value that lies between the limit of detection (LoD) and the limit of quantitation (LoQ). Where the LoD is the lowest concentration that can be accurately measured and the LoQ is the highest concentration that can be accurately measured.
Linearity describes the correlation to a regression line that has been fit to the data that. For some nice pictures to explain this see regression line at:"
The validation parameters for related substances analysis by HPLC typically include specificity, linearity, accuracy, precision, detection limit, quantification limit, and robustness. Specificity ensures the method can differentiate between the analyte and impurities, while linearity confirms a linear relationship between concentration and response. Accuracy and precision assess the closeness of results to the true value and the method's repeatability. Detection and quantification limits determine the lowest concentration that can be reliably detected and quantified. Robustness evaluates the method's ability to remain unaffected by small variations in parameters.
Specificity refers to the ability of an analytical method to accurately measure the analyte of interest in the presence of potential interfering substances. Selectivity, on the other hand, refers to the ability of the method to only detect the analyte of interest while ignoring any other components present in the sample. Both are important parameters in HPLC method validation to ensure accurate and reliable results.
they are both incredibly boring so no there is no difference ;)
Chemistry is my favourite subject.There is definitely a chemistry between us.
Analytical chemistry studies how to determine the types and relative amount of atoms of different kinds and the bonding between such atoms that are present in materials of initially unknown composition.
When a function or given data set differes from a liniar curve fit. the difference between the data and a linear curve fit is your linearity error
one is a validation the other is redundancy clue is in the name
verification: Are we doing the right system? validation : Are we doing the system right?
minimal
SDLC has both verification and validation activities where as STLC has only validation activity. Simply STLC is a part of SDLC
Im gay -Alfonso Bediones IV from Bacolod City, Philippines
Linearity refers to a progression or movement that follows a straight and predictable path, while dialectic involves the process of resolving contradictions or opposing forces through dialogue and reasoning. Linearity implies a direct cause-effect relationship, whereas dialectic involves a more complex interplay of ideas or perspectives leading to synthesis or resolution.
analytical thinking is of a set rules and process of thinking. Creative thinking is outside the box and no set pattern.
The validation parameters for related substances analysis by HPLC typically include specificity, linearity, accuracy, precision, detection limit, quantification limit, and robustness. Specificity ensures the method can differentiate between the analyte and impurities, while linearity confirms a linear relationship between concentration and response. Accuracy and precision assess the closeness of results to the true value and the method's repeatability. Detection and quantification limits determine the lowest concentration that can be reliably detected and quantified. Robustness evaluates the method's ability to remain unaffected by small variations in parameters.
What are the differences between analytic and synthetic cubism?
The defects detection is the validation process. The defects prevention is a verification process.
Data validation makes sure that the data is clean, correct and meaningful, while data verification ensures that all copies of the data are as good as the original.