## Chapter 1.3-1.5

Term Definition
Parameter Measure of the whole population describing a characteristic
Statistic Measure of a sample describing some characteristic (not the whole population)
Quantitative data Data expressed by numbers
Categorical data Data that consists of names or labels that are not expressed in numbers
Discrete data Values are finite or countable
Continuous data Infinitely many possible values
Nominal level of measurement characterized by data that consists of names or labels; not ranked
Ordinal level of measurement data can be ordered but differences do not make sense
Interval level of measurement Difference between data is quantitative but there is no natural starting point
Ratio level of measurement data can be ordered, differences make sense, and there is a natural starting point
Voluntary response sample Respondents decide themselves whether to be included
Problems with voluntary response sample Strong opinions pervade, and inherent bias exist
Correlation When two events are somehow connected
Causation When one event causes another event
Reporter bias when respondents aim to please the researcher
Small samples not always indicative of the whole population, even if properly collective
Loaded question When strong wording skews responses
Order of questions structure of sentence can contributes to responses
Non-response when a person either refuses to respond to a survey question or is unavailable
Missing data Data values are missing for many factors
Self-interest study Researcher desires a certain conclusion and skews study methods in favor of that conclusion
Observational study measure specific characteristics but don't attempt to modify the subjects
Experimental study Apply a treatment and proceed to observe its effects
Simple random sample sample of size n is a selection of n subjects is chosen in such a way so that every group of n subjects has an equal chance of being chosen
Random sample members of the population chosen in such a way that every individual is equally likely to be chosen
Probability sample select members from the population in such a way that each member is chosen with a pre-selected probability
Systematic sampling select some starting point and select every kth person
Convenience sampling sampling from a group convenient to the researcher