One example is the "Five Number Summary" consisting of the sample's minimum, lower quartile, median, upper quartile and maximum.AnswerStatistics or data set might apply to the set of numbers that represent some sort of information from a sample population. AnswerDemographics is the statistical characteristics of a sampled population.
The general term statistics might be the set of numbers representing some sort of information from a sample population. The term data set can also be applied.
Statistics or data set
Answerraw datais this the only answer?
One example is the "Five Number Summary" consisting of the sample's minimum, lower quartile, median, upper quartile and maximum.
The sample must have a high probability of representing the population.
yes the size is 4444
You are studying the sample because you want to find out information about the whole population. If the sample you have drawn from the population does not represent the population, you will find out about the sample but will not find out about the population.
Information about the scale, spread or dispersion of the population from which the sample was drawn.
Information obtained from the sample can be extrapolated to the whole population using statistics.
When the sample - whether it is random or systematic - is somehow representative of the population.
Because it would usually be prohibitively expensive and time consuming to collect information from every single member of the population and because the law of large numbers is sufficiently robust to allow most characteristics of a population to be measured with sufficient accuracy from a sample.
For a large enough sample, it will resemble a rectangle whose base will be the range of the variable and the height will be the reciprocal of the number (or width) of the base.
Data is commonly referred to the quantitative attributes of a variable. A data is nothing but a result of something. Through this result, the information is derived. Sometimes we refer to Raw Data which is unprocessed in nature which can mean a collection of numbers or characters that collect information and then convert from quantities to symbols. Sample, in statistics can mean a subset of a population. Population can be huge, so the sample can represent just a manageable size. Sample is first collected and then the statistics are derived from the sample. This process is known as Sampling.
When performing an experiment or gathering data for statistics, it would be very difficult to gather information for every member of the group's population. Instead, one can gather information from a sample large enough to be representative of the population.
Suppose you have a population for which you want to measure some particular attribute. It may not be feasible or sensible to collect the information from each and every member of the population. In that case you can take a subset of members from the population - called a sample - and collect the relevant information for them. Provided that the sample meets certain statistical conditions, the measurements made for the sample will be good approximations for the characteristics of the whole population.
The sample mean helps researchers maintain the scope of their research. If the sample mean is too far from the mean of the population then the numbers may be skewed.
a census is the procedure of systematically acquiring and recording information about all d members of a given population and a sample is a group from d population a census is more thorough and gives accurate information about a population while being more expensive and comsuming time comsuing rather than a sample
A population survey, better known as a census, entails the collection of each unit in the population. In sample survey information is collected from a subset of the population. The subset, or sample, needs to be selected carefully so that it is representative of the whole population and, if that requirement is met, statistics based on the sample are good estimators for the corresponding population parameters.
The bottom line is it would be wasteful and foolish to use the entire population when a sample, drawn scientifically, provides accuracy in representing your population of interest. Assessing all individuals may be impossible, impractical, expensive or even inaccurate.