Scientifically valid samples are those that accurately represent the population being studied, ensuring that findings can be generalized. They should be selected using appropriate sampling methods, such as random sampling, to minimize bias. Additionally, sample size must be sufficient to provide reliable and statistically significant results. Valid samples also adhere to ethical standards and maintain the integrity of the research process.
When you plot a function with asymptotes, you know that the graph cannot cross the asymptotes, because the function cannot be valid at the asymptote. (Since that is the point of having an asymptotes - it is a "disconnect" where the function is not valid - e.g when dividing by zero or something equally strange would occur). So if you graph is crossing an asymptote at any point, something's gone wrong.
a biased sample is valid determin
Reliably is the adverbial form of reliable.
A valid conclusion is when your conclusion is written using the text you have and get it right.
In my view reliable test is always valid.
Is it possible for an operational definition to be valid but not reliable
A test may be reliable but not valid. A test may not be valid but not reliable. For example, if I use a yard stick that is mislabeled to measure the distance from tee to hole in golf on different length holes, the results will be neither reliable nor valid. If you use the same stick to measure football fields that are the same length the result will reliable (repeatable, consistent) but not valid (wrong numbers of yards). There is no test that is unreliable (repeatable, consistent) and valid (measures what we are looking for).
A reliable measure is consistent and yields consistent results, so it may not be measuring the intended construct accurately (lack validity). On the other hand, a valid measure accurately assesses the intended construct, but it must be consistent and produce stable results (reliable) to ensure that the measurements are dependable and trustworthy.
No, validity is not a prerequisite of reliability. Reliability refers to the consistency or stability of a measure, while validity refers to the accuracy of the measure in assessing what it is intended to assess. A measure can be reliable but not valid, meaning it consistently measures something but not necessarily what it is intended to measure.
observations can be more valid because when you observe things you are kind of making small facts about it and facts are valid unlike opinions which is giving something you think is valid from your point of view but you are not sure for a fact that its real so to make that short opinions are saying what you believe.
Reliable indicates that each time the experiment is conducted, the same results are obtained (accuracy). Valid indicates the experiment (or test) has controlled variables and used an appropriate method/model.
A test may be reliable yet not valid, The results can end up being reliable, in other words certain to have yielded properly based on input. But the results may not be trustworthy.
Social and Medical sciences uses these statistical concepts. ideally, we have to measure the same way each time, but intrasubject, interobserver and intraobserver variance occur, so we have to anticipate and evaluate them. In short, it is the repeatability of a measurement, by you, myself and everybody person or instrument. Validity is how much the mean measure that we got is near of the true answer or value. So, an instrument can be reliable but not valid, valid but not reliable, both valid and reliable, nor valid neither reliable. I suggest that you imagine a target: you can aim and 1) always get the center (both valid and reliable) 2) always get the same distant point (reliable but not valid) 3) err much around the true center (valid but not reliable - the mean and median of your arrow's shot will get the center) 4) err much around the another center, false one (nor valid neither reliable) I did not understood exactly what selection criteria have to do with the rest of question, so, left in blank ;-)
probability!
A reliable experiment is one that can be proven or has been worked out several times giving valid or dependable results.
valid