Please enable JavaScript.
Coggle requires JavaScript to display documents.
Business Statistics (BUSI.2305) - Coggle Diagram
Business Statistics (BUSI.2305)
Data Collection
Chapter 1:
Data
- the facts and figures collected, presented, analyzed, and interpreted
Elements
- entity on which data are collected
Variables
- characteristic of interest for the elements
Scales of Data Measurement
Ordinal
- data exhibits properties of nominal data and in addition, the order or rank is meaningful
Interval
- when the data have the properties of ordinal data and the interval between data is expressed in terms of a fixed unit of measure
Nominal
- data for a variable that consists of names, labels to identify an attribute of the element
Ratio
- when the data have all of the properties of interval data and the ratio of two values is meaningful
Data Classifications
Qualitative
(Categorical) - data that can be grouped by categories, even when coded with numbers, arithmetic operations are not meaningful
Quantitative
(Numerical)- data that use numeric values to indicate how much
Data Sources
Primary Data
- data collected by the user
Observational Study
Experiment
Survey
Mail
Internet
Phone
Secondary Data
- data from someones else's files, data, information
Population Data
- the set of all elements of interest in a study
Sample Data
- data that is a subset of a population
Big Data
- large, complex sets of data
Ethical Use of Statistics Guidelines from the American Statistical Association
Responsibility to Research Subjects
Responsibilities to Research Team Colleagues
Responsibilities in Publications and Testimony
Responsibilities to Other Statisticians or Statistical Practitioners
Responsibility to Funders, Clients, and Employers
Responsibilities Regarding Allegations of Misconduct
Professionalism
Responsibilities of Employers including Organizations, Individuals, Attorneys, or Other Clients Employing Statistical Practitioners
Statistics
- is the art and science of collecting, representing, analyzing, and interpreting data
Data Representation
Data Analysis
Data Interpretation