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Introduction to Statistics
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Terms in this set (22)
Data
Facts, figures, and other evidence gathered through observations.
Statistics
Collection of methods for planning experiments, obtaining data, organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on data.
Population
The complete collection of all measurements or data that are being considered
Sample
A subset of the population
Census
A complete enumeration of a population.
Voluntary response sample
Composed of individuals who choose to respond to a survey because of interest in the subject. Seriously flawed study.
Analyze
Examine methodically and in detail the constitution or structure of (something, especially information), typically for purposes of explanation and interpretation. Looking at graphs and given context provided.
Statistical significance
The condition that exists when the probability that the observed findings are due to chance is very low. Usually around 5% or lower, but it range up to maybe 10-30% depending on whether it happened by chance.
Practical significance
An observed relationship that is large enough to be of value in a practical sense.
Order of Questions
Questions are unintentionally loaded by such factors as the order of the items being considered
Non-response
The failure to obtain data from an individual or individuals selected for a sample
Percentages
Misused percentages in studies... something above 100%
Parameter
Numerical summary of a population describing some characteristic
Statistic
A numerical measurement describing some characteristic of a sample- use statistics to estimate parameters
Quantitative data
Numerical data
Categorical data
Data that consists of names, labels, or other nonnumerical values
Discrete data
Numerical data values that can be COUNTED
Continuous data
Data that can take on any value. There is no space between data values for a given domain. Graphs are represented by solid lines.
Nominal
Categorical data involving names, labels, or categories that cannot be arranged in order [low to high]. Ex. surveys with y/n.
Ordinal
Categorical data that can be arranged in some order, no difference in data really when subtracting them from each other. Ex. course letter grades and what rank are you in college.
Interval data
Numerical data on a scale, but with no meaningful zero point. It is sensible to talk about differences between values, but not ratios (e.g., 40F is not half as hot as 80F, and a person with an IQ of 140 is not "twice as smart" as someone with an IQ of 70).
Ratio data
a type of numerical data in which the difference between numbers is significant, but there is a fixed non-arbitrary zero point associated with the data
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