Flashcards in CH 1 Deck (39):
Numerical summary of a sample
Organizing and summarizing data
Methods that take a result form a sample, extend it to the population, and measure the reliability of the result.
Numerical summary of a population
Entire group in study
Subset of the population being studied
Can be classified based on attribute or characteristic
Numerical measure of an individual
Discrete quantitative variable
Countable, finite number of possible values
Continuous quantitative variable
Infinite number of possible values. Can take on every possible value between any two values.
Names, labels, or categorizes
Nominal + must have level of ranking or specific orders
Ordinal + differences in values of variables
Interval + clear definition of zero (none of something)
Measures the value of the response variable without attempting to influence the value of either the response or explanatory variables.
Intentionally change the value of the explanatory variable to record the responses of each group.
Collect information at a specific point in time, or over a very short period of time.
Retrospective. Look back in time or look at existing records. Individuals with certain characteristics are matched with those who do not have it.
the cohort = the group to be studied. They are observed over a long period of time = Prospective study.
What is being studied
What is affecting the response variable
when the effects of two or more explanatory variables are not separated. Could lead to different conclusions about the results.
An explanatory variable that was not considered in a study, but that affects the value of the response variable in the study. Typical related to explanatory variables.
Process of using chance to select individuals form a population to be included in the sample
Sample without replacement
Individual who is selected is removed from the population and cannot be chosen again.
Sample with replacement
Selected individual is placed back into the population and could be chosen a second time.
Simple Random Sampling
A sample of size n from a population of size N is obtained through simple random sampling if every possible sample of size n has an equally likely chance of occurring.
Obtained by separating the population into non overlapping groups and then obtaining a simple random sample from each group
Obtained by selecting every "k"th individual from the population (first individual is selected randomly from 1 to k)
Obtained by selecting individuals within a randomly selected group of individuals.
Sample in which the individuals are easily obtained
Systematic formula when k is known
p + (n-1)k
p = first client
n = sample size
k = every "k"th individual
How to find "k"th individual in systematic sample when N/n is known.
N = total population
n = desired sample size
When the technique used to sample favors one part of the population over another.
proportion of one segment of the population is lower in a sample than the population
When answers on a survey do not reflect the true feelings of the respondent.
Inability to measure accurately and directly what one would wish to measure.
Matched-pair design (experiment)
Experimental units are paired up. Where one individual will receive one treatment and the other receives a different one. aka Pre and post experiment