Chapter 1: Introduction to Statistics Flashcards
(18 cards)
Statistics
science of collecting, analyzing, organizing, and interpreting data in order to make decisions
Why study statistics?
1) To construct meaning out of the data around us
2) To recognize problems with published information
3) To draw conclusions from data
4) To improve processes
5) To obtain reliable forecasts (e.g. weather, stock market)
What do we use statistics for?
Discovering information on a characteristic of the population
Population
the entire collection of individuals or objects about which information is desired; collection of all outcomes, responses, measurements, or counts that are of interest
Why might you not be able to collect data from the entire population?
Depends on what “you” want to know. If you were studying breast cancer in women, you wouldn’t use men. Furthermore, there are too many people. Some might not wish to participate.
- Cannot identify entire population
- Cost too much, too much time
- Pop infinite
Sample
subset of the population
a set can be a subset of itself
Two branches of statistics:
1) Descriptive - describing sets of data; tables, graphs, numerical calculations
2) Inferential - drawing conclusions; use information obtained from a sample to draw a conclusion on a population
Data
information coming from observations, counts, measurements, or responses
Descriptive Statistics
branch of statistics that involves the organization, summarization, and display of data
Inferential Statistics
branch of statistics that involves using a sample to draw conclusions about a population; basic tool used: probability
Qualitative Data
consist of attributes, labels, or nonnumerical entries
Quantitative Data
consist of numerical measurements or counts
Four levels of measurement:
1) Nominal
2) Ordinal
3) Interval
4) Ratio
Nominal level of measurement
Qualitative only; categorized using names, labels, or qualities; NO MATHEMATICAL COMPUTATIONS CAN BE MADE
Ordinal level of measurement
Qualitative or quantitative; can be arranged in order, or ranked, but differences between data entries are not meaningful
Interval level of measurement
Quantitative only; can be ordered; meaningful differences between data entries can be calculated; a zero entry simply represents a position on a scale; the entry is not an inherent zero
Ratio level of measurement
Quantitative; similar to data at the interval level, BUT zero entry is an inherent zero; a ratio of two data entries can be formed so that one data entry can be meaningfully expressed as a multiple of another
Inherent zero
zero implies “none”; ex: money; NOT-ex: temperature
