A sample size is a group which is sampled in surveys, statistics, and in the scientific method. Increasing a sample size might decrease or increase the margin of error, depending on what was being measured. For instance, a sample of 100 women who were pregnant, might increase or decrease the the margin of error for women who showed morning sickness while pregnant.
No. Only a census can ACCURATELY predict the outcomes: a random sample cannot.
The sample must be large and random.
A parameter describes a population. A statistic describes a sample.
yes
Increasing your sample size might help
Yes. If the sample is a random drawing from the population, then as the size increases, the relative frequency of each interval from the sample should be a better estimate of the relative frequency in the population. Now, in practical terms, increasing a small sample will have a larger effect than increasing a large sample. For example, increasing a sample from 10 to 100 will have a larger effect than increasing a sample from 1000 to 10,000. The one exception to this, that I can think of, is if the focus of the study is on a very rare occurrence.
The margin of error is reduced.
A sample that accurately reflects the characteristics of the population as a whole
No. Only a census can ACCURATELY predict the outcomes: a random sample cannot.
It should reduce the sample error.
Freezing the sample causes the molecules to slow down and come closer together, often leading to a decrease in volume and possibly forming a solid. Boiling the sample provides energy to the molecules, causing them to separate from each other and enter a gaseous state, thereby increasing the volume.
A broad sample would result in peak broadening on the chromatogram. This can be caused by factors such as sample dispersion, slow diffusion rates, or poor column efficiency. Broad peaks can lead to decreased resolution and difficulty in accurately determining peak parameters.
The term used in forensics to describe a sample of unknown origin is "questioned sample."
The sample must be large and random.
A sample that is not fair is often referred to as a "biased sample." This occurs when certain members of the population are overrepresented or underrepresented, leading to skewed results that do not accurately reflect the entire population. Bias can arise from various factors, such as selection methods or the sample size. Recognizing and addressing bias is crucial for ensuring the validity of research findings.
The term is "representative sample." It is a subset of a population that accurately reflects the characteristics of the whole population it is meant to represent.
One can accurately measure hydrogen in a given sample using techniques such as gas chromatography, mass spectrometry, or titration. These methods involve separating and quantifying the amount of hydrogen present in the sample.