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Population
entire group of individuals about which the researcher wants information
Parameter
characteristics of a population that the researcher wants to measure, GREEK LETTERS, proportion, average, mean
Sample
a subset of the population that is contacted and examined for research
Statistic
descriptive measure computed from data in a sample that can be expressed or evaluated numerically
Inference
statement about a population based on data collected in a sample
Distribution
listing of values that a characteristic can take and the number or percentage of times each value occurs
Descriptive statistics
branch of stat which use data and statistics computed from a sample
Replication/repetition
Repeated measurements
Constant
measurements that do NOT change in repeated trials over time
Variable
measurements vary and change in trials over time
Discrete quantitative variables
Things you can count
Continuous quantitative variable
anything that is measured or calculated, averages, rates, percentages
Selection bias
one or more types of subjects are systematically excluded from the sample Ex: Raising fees to expand the Siegal center and only asking students at the game (creates a bias)
Non response bias
individual from the sample can not be contacted or refuses to respond
Response bias
responders give inaccurate information or if they interviewer influences the subject to respond in a certain way.
Haphazard sample
selecting a sample by using some kind of convenient mechanism/technique that does not involve randomization. Ex: Standing outside Cabell at 3:00 to ask about classes beginning at 2:30
Volunteer response samples
subject volunteers to be part of the study. Call in survey, internet, etc. Bias because most responders are going to feel either very strongly on their opinion either pos or neg
Simple random sampling
list of all possible individuals in a population and randomly choose "n" subjects. Every person has an equal chance at winning. Refer to the table of random digits after assigning every subject a number. +Easy, random -Sample may contain too large of a percentage of a subject (M or F)
Stratified random sampling
population is naturally divided in to two or more groups of similar subjects called strata. EVERY GROUP HAS AT LEAST 1 SELECTED.
Multistage random sampling
population- all American college students population naturally divided in to 2 groups, randomly select several of these groups, each chosed group is further divided in to smaller subgroups, simple random sampling is used to pick from subgroups