sampling errors + samples + types of data

Sampling Error

occurs when a characteristic of a sample differs from that of the whole population. This error is random, and will occur even for samples which are well-chosen to avoid bias.

Measurement error

refers to inaccuracies in measurement at the data collection stage. For example, when we record a person’s height to the nearest centimeter, the recorded height is slightly different from
the person’s exact height.

Coverage errors

occur when a sample does not truly reflect the population we are trying to find information about.

Non-response errors

occur when a large number of people selected for a survey choose not to respond to it.

Stratified sampling/quota sampling

when the population can be divided into subgroups, and you want to make sure each subgroup is represented fairly in the sample.

convenience samples

they are convenient for the experimenter.

systematic sampling

the sample is created by selecting members of the population at regular intervals.

simple random sampling

Each member of the population has the same chance of being selected in the sample.

categorical variable

The data is divided into categories, and the information collected is called categorical data ( describes a particular quality or characteristic)

quantitative variable

The information collected is called numerical data (has a numerical value)

discrete quantitative variable

takes exact number values. It is usually a result of counting.

continuous quantitative variable

can take any numerical value within a certain range. It is usually a result of measuring.