Chapter 1: Data Collection Flashcards
descriptive statistics
collecting, organizing, and summarizing data
inferential statistics
analyze sample of data to form conclusions about larger population
population
entire group to be studied
individual
person or object of the population being studied
sample
subset of a population being studied
statistic
numerical summary of a sample
parameter
numerical summary of population
variables
particular characteristics of individuals in the population
qualitative (categorical) variable
classification of an individual based on attribute or characteristic
quantitative (numerical) variable
numerical measure of individuals
discrete variable
quantitative variable where values obtained by counting
continuous variable
quantitative variable that can take up infinitely many and uncountable values
level of measurement
way that a set of data is measured
nominal
labeling variables without quantitative value (ex: gender)
ordinal
order is important but difference in measurements won’t make sense (ex: letter grades)
interval
numeric scale with order and exact difference (ex: temerature)
ratio
like interval, but has 0 and ratios can be calculated (ex: number of days studied in a week)
random sampling
using chance to select individuals from a population for a sample
simple random sampling
every sample size n has an eqal chance of being chosen from the population N
with replacement
once an individual is picked, individual goes back into population and can be equally picked again
convenience sampling
sample is picked by availiability
stratified sample
sample taken by seperating population into different groups (strata) and obtaining a simple random sample of each stratum
How does one select a stratified sample?
- define the groups based on similarites
- conduct simple random sample of each group
- use seed that is different for each group
systematic sample
sample obtained by selecting every kth individual from the population, where the first individual p is randomly selected between 0
How does one conduct a systematic sample?
- determine population size N
- determine desired sample size n
- Compute N/n and round down to find p
- randomly select number btwn 1 and k for p
- the sample consists of starting number p, and add k each time to find the next
cluster sample
sample obtained by creating different clusters and randomly selecting the clusters but choosing all individuals in the cluster as the sample
How does one conduct a cluster sample?
- decide hown to difide population into clusters
- randomly select which clusters to survey
- survey all individuals in chosen clusters
bias
when the results of sample not representative of sample
sampling bias
when the techniques used to select individuals favors one part of population over another
nonresponse bias
individuals selected for sample don’t respond and therefore don’t contribute their differing opinions
response bias
answers on survey don’t accurately reflect true feeling of individual
