Statistics Ch 1

What is the difference between a sample and a statistic?

a sample is the portion of the larger populations that is studied to gain information of said population and the statistic is the numerical representation of a property of the sample.

For what type of data does it make sense to have a random variable?

Quantitative Data (both discrete and continuous) as it is numerical

Sampling Techniques (List and describe or give an example)

SRS - equal chance of who/what gets selected

Systematic - random starting point and choosing by every nth number

Stratified - population is divided into subgroups (by characteristic) and an SRS is chosen from subgroup to ensure representation of subgroup

Cluster - population is divided into clusters, then when clusters are randomly selected, all individuals from that group are sampled

Levels of Measurement (List and give an example of each)

Nominal - data that can be organized w/no inherent order or rank (gender, hair color)

Ordinal - data that can recategorized or ranked, but intervals between ranks aren’t necessarily equal (satisfaction surveys)

Interval - data that have an order, and equal space between values, but no true zero point (IQ scores, temperature)

Ratio - The most precise level, featuring categories, order, equal spacing, and a true zero point (height, weight)

Describe the difference between Sampling Error vs. Nonsampling Error

Sampling error arises from taking the sample itself and non sampling error arises from outside sources (lurking variables)

List the types of data

Qualitative data - categorical data

Quantitative data - numerical data

Quantitative Discrete data - counted numerical data (number of ___)

Quantitative Continuous data - measured numerical data (fractional, decimal, like weight, height, etc.)