Random Sampling Methods and Data Graphing

This set of flashcards covers the key vocabulary and concepts discussed in the lecture on random sampling methods, types of data, and data representation techniques.

Random Sampling

A technique where each member of a population has an equal chance of being selected.

Systematic Sample

A sampling method where you select every nth item from a list or group.

Stratified Sample

A method of sampling where the population is divided into homogeneous groups, and samples are drawn from each group.

Cluster Sample

A sampling method where the population is divided into heterogeneous groups, and entire clusters are randomly selected.

Quantitative Data

Data that can be measured numerically, such as height, weight, or age.

Qualitative Data

Data that describes characteristics or qualities, often categorical, such as colors or names.

Bar Graph

A visual representation using bars to compare different categories of data.

Stem and Leaf Plot

A method of displaying quantitative data where each number is split into a 'stem' (the leading digit) and a 'leaf' (the trailing digit).

Frequency Histogram

A graphical representation showing the frequency of data points within specified ranges.

Observational Study

A study where the researcher observes and measures characteristics without manipulating the environment.

Experiment

A study where researchers manipulate one or more variables to observe effects on a response variable.

Sample Mean (x̄)

The average of a sample, calculated by summing all sample values and dividing by the number of samples.

Sample Standard Deviation (s)

A measure of the amount of variation or dispersion in a set of sample data.

Discrete Variable

A quantitative variable that can take on only a finite number of values.

Continuous Variable

A quantitative variable that can take on an infinite number of values.

Ratio Level of Measurement

A level of measurement that has a true zero point indicating the absence of the quantity measured.