Sampling Methods
a straightforward method for selecting a random sample; give each member of the population a number and use a random number generator to select the sample.
Simple Random Sampling
With the column named for it, it is a set of observations (a set of possible outcomes).
Data
a subset of the population studied.
Sample
a nonrandom method of selecting a sample; this method selects individuals that are easily accessible and may result in biased data.
Convenience Sampling
an attribute whose value is indicated by a label.
Qualitative Data
all individuals, objects, or measurements whose properties are being studied.
Population
a method for selecting a random sample and dividing the population into groups (clusters); use simple random sampling to select a set of clusters; every individual in the chosen clusters is included in the sample.
Cluster Sampling
an attribute whose value is indicated by a number.
Quantitative Data
a numerical characteristic of the sample.
Statistic
the natural variation that results from selecting a sample to represent a larger population; this variation decreases as the sample size increases, so selecting larger samples reduces sampling error.
Sampling Error
a method for selecting a random sample used to ensure that subgroups of the population are represented adequately; divide the population into groups (strata) and use simple random sampling to identify a proportionate number of individuals from each stratum to select your sample.
Stratified Sampling
the result of counting (such as the number of dogs of a given breed in a doggy daycare or the number of books on a shelf).
Quantitative Discrete Data
a characteristic of interest for each person or object in a population.
Variable
an issue that affects the reliability of sampling data other than natural variation; it includes a variety of human errors including poor study design, biased sampling methods, inaccurate information provided by study participants, data entry errors, and poor analysis.
Nonsampling Error
•a method for selecting a random sample; list the members of the population and use simple random sampling to select a starting point in the population. Let k = (number of individuals in the population)/(number of individuals needed in the sample). Choose every kth individual in the list starting with the one that was randomly selected. As necessary, return to the beginning of the population list to complete your sample.
Systemic Sampling
the result of measuring (such as distance traveled or weight of luggage).
Quantitative Continuous Data
a number that is used to represent a population characteristic and that generally cannot be determined easily.
Parameter
not all members of the population are equally likely to be selected.
Sampling Bias