Introduction to Statistics

Definition: The science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making effective decisions.
Why Study Statistics: Essential for making sense of data, making valid comparisons, predicting outcomes of decisions, and useful across all careers.

Descriptive Statistics: Methods of organizing, summarizing, and presenting data in an informative way; used to make data meaningful and easy to understand.
Inferential Statistics: Methods used to estimate a property of a population on the basis of a sample; used to make decisions based on limited data.
Population: The entire set of individuals or objects of interest or the measurements obtained from them.
Sample: A portion or part of the population of interest.

Qualitative Variable: An individual is observed and recorded as a non-numeric characteristic or attribute (e.g., gender, eye color).
Quantitative Variable: A variable that is reported numerically (e.g., checking account balance, number of employees).
- Discrete Variables: Typically the result of counting; values have "gaps" between them (e.g., # of bedrooms: $1, 2, 3$ , etcetera).
- Continuous Variables: Usually the result of measuring something; can assume any value within a specific range (e.g., duration of flights: $5.25$ hours, grade point average: $3.258$ ).

Nominal Level: Data are represented as labels or names; have no order and can only be classified and counted (e.g., M&M candy colors, gender).
Ordinal Level: Data based on a relative ranking or rating; variables are only ranked and counted (e.g., top ten states for business climate, student professor ratings).
Interval Level: Possesses all characteristics of ordinal data; differences between values are meaningful; there is no natural $0$ point (e.g., Fahrenheit temperature scale, dress sizes).
Ratio Level: Possesses all characteristics of interval data; ratios between numbers are meaningful; the $0$ point represents the absence of the characteristic (e.g., wages, height, changes in stock prices).

Practice statistics with integrity and honesty in all stages of data handling.
Maintain an independent and principled point of view; question reports based on biased, incomplete, or misleading data.

Involves processing and analyzing data and information to support a company's story or narrative.
Computer software is essential for summarizing, organizing, analyzing, and presenting statistical findings.