I will assume the sample is random. In general, the larger the sample, the smaller the percentage error will be (the difference between percentages in the sample, and the percentages in the universe from whence the sample is taken). The percentage error tends to go down as the square root of the size of the sample.
Because then you can assess how valid your results are =D
The answers are usually always valid. What may or may not be valid are your assumptions about the underlying model. Also, the number of times the results should be similar depends on the number of possible outcomes and the variability in the outcomes. For example, if you spin a fair spinner with 12 equal segments, then the probability of similar results is less than likely.
Because without representative sample, your results will not be valid.
validity is whether the results are valid so the data has no mistakes of as such in it whereas reliability is the dependability; when the results you have are accurate and are of enough quality.
If you documented all your results, had a partner, had a witness, completed the experiment many times with the same results, and tested the experiment on the proper things then this would be good validation.
Statistically the results will not be scientifically valid if the sample size is too small.
DNA testing can still be valid on blood samples after 1 year, but the quality and quantity of DNA may degrade over time, potentially affecting the accuracy of the results. It is recommended to use fresh samples for DNA testing to ensure the most reliable results.
a valid investigation is an effective investigation i think. The results turn out to be what you had inferred.
booty
repeated trials
A valid passport is required
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.
The range of a function is the interval (or intervals) over which the independent variable is valid, i.e. results in a valid value of the function.
reliable.
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.
when there are errors in sampling design, such as biases in selecting participants or a non-representative sample, which can lead to inaccurate results.
when results from the experiments repeatedly fail to support the hypothesis.