business statistics ch1

Data :: The facts and figures collected, analyzed, and summarized for presentation and interpretation

Element :: The entities on which data are collected

Population :: The set of all elements of interest

Variable :: A characteristic of interest for the elements

Sample :: A subset of the population

Qualitative (categorical) data :: Data that are categories or labels (nominal or ordinal)

Quantitative data :: Data that are numbers (interval or ratio)

Nominal :: Qualitative data with labels that have no order (e.g., bank, credit union, savings and loan)

Ordinal :: Qualitative data with labels that have a meaningful order (e.g., service ratings: excellent, good, poor)

Interval :: Quantitative data where the difference between values is meaningful (e.g., temperature)

Ratio :: Quantitative data where the ratio between values is meaningful (e.g., starting salary)

Cross-sectional data :: Data collected at one point in time (e.g., average rainfall in 50 states in 2022)

Time series data :: Data collected over time (e.g., average rainfall in Arizona from 1988 to 2022)

Panel (pooled) data :: Cross-sectional and time series data combined (e.g., average rainfall in 50 states from 1988 to 2022)

Descriptive statistics :: Tabular, graphical, or numerical summaries of the data

Class :: A set, category, classification, or grouping

Frequency :: The number of items or observations in a set (a count)

Relative frequency :: A proportion (e.g., 0.30) or percentage (e.g., 30%); class frequency divided by the total count

Cumulative relative frequency :: The successive addition of the relative frequencies

What does cumulative relative frequency always end at? :: 1.00, once every class has been added

Statistical inference :: An estimate, prediction, or other generalization about a population based on information in a random sample

Statistical inference in plain terms :: A decision about an unknown population based on what is known about a random sample of it

Inference element 1 :: The population or sample of interest: what or who we want to learn about

Inference element 2 :: One or more variables or characteristics of the population: our concern, the key items of interest

Inference element 3 :: The random sample of population units: the information available to us (the data)

Inference element 4 :: The inference about the population based on the sample: the conclusions reached or knowledge learned

Inference element 5 :: A measure of reliability for the inference: the level of significance (confidence) we have in our process

Cross-sectional vs. time series vs. panel :: Cross-sectional is one time, many units; time series is one unit, many times; panel is both

How do you compute relative frequency? :: Class count ÷ total