Understanding Variables, Mean, Median, and Sampling Methods

Qualitative Variables

Nominal Variables

Nominal variables are qualitative variables that cannot be ordered in an ascending or descending manner; that is, they cannot be ranked. For example, blood group.

Ordinal Variables

Ordinal variables are variables that can be ordered in an ascending or descending manner; that is, they can be ranked.

Quantitative Variables

Discrete Variables

Discrete variables are variables whose values are obtained by counting.

Continuous Variables

Continuous variables are variables whose values are obtained by measurement using a scale.

Mean

Advantages

• Has many good theoretical properties
• Used as the basis of many statistical tests
• Good summary statistic for symmetrical distribution
• Easy to calculate
• Possible for further algebraic treatment

Disadvantages

• Less useful for an asymmetric distribution
• Most affected by outliers

Median

Advantages

• There is a unique median for each data set
• Not affected by extreme values - therefore a valuable measure of central tendency when such values occur
• It can be computed for ratio-level, interval-level, and ordinal-level data
• It can be computed for an open-ended frequency distribution if the median does not lie in an open-ended class

Disadvantages

• The median does not contain information on the other values of the distribution
• The median is less amenable to statistical tests

Quota Sampling

Quota sampling is a type of convenience sampling where the population is first segmented into mutually exclusive sub-groups, as in stratified sampling.

1. Judgment is used to select the subjects from each segment.
2. The selection of the sample is made by the interviewer, who has been given quotas to fill from specific sub-groups.
3. When the quota for a given demographic group is filled, the researcher will stop recruiting subjects from that particular group.
4. There are similarities with stratified sampling, but in quota sampling, the selection of the sample is non-random.
5. The advantage of this method is that it is quick and cheap.

Snowball Sampling

Snowball sampling is a non-probability sampling technique where existing study subjects recruit future subjects from among their acquaintances. Thus the sample group is said to grow like a rolling snowball.

1. It is often used in hidden populations, such as drug users or sex workers, which are difficult for researchers to access.
2. As sample members are not selected from a sampling frame, snowball samples are subject to numerous biases.
3. Researchers may be able to make inferences about the population being studied.
4. The choice of the initial subject strongly influences the overall sample.
5. The advantage of this method is that it can reach difficult-to-access populations.