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SCI1020

Statistics

TermDefinition
Simple Random Sampling 1. All units in population have the same chance of being in the sample. 2. Every conceivable group of units required size has the same chance of being the selected sample
homogeneous population relatively the same, not too much variability
heterogeneous population there is variability between groups in the question of interest
stratified random sampling Population divided into subgroups (strata) and random samples taken from each strata
table B (SRS) small population
excel (SRS) large population
Why use stratified sampling? better representation when there are subgroups
cluster sampling Divide the population area into sections (or clusters). Then randomly select some of those clusters. Now choose all members from selected clusters.
systematic sampling The process of selecting a sample of subjects for a study by drawing every nth unit on a list
multistage sampling a probability sampling technique involving at least two stages
selection bias when some part of the population is not included in the sampling process
non-response bias when a representative sample is chosen but a subset cannot be contacted or doesn't respond
response bias when participant response differently from how they truly feel
what is measured unit - a single individual or object bein measured. if an experiment, then called an experimental unit. when units are people, called subjects or participants.
explanatory variable a variable that we think explains or causes changes in the response variable
response variable a variable that measures an outcome of a study.
confounding variable a variable that affects the response variable and also related to the explanatory variable. - known
lurking variable potential cofounding variable but it is not really known or anticipated beforehand
observational study researches observe or question participants about opinions, behaviors, or outcomes. the outcome (response) is associated with other features observed (explanatory)
experiment researchers deliberately manipulate at least one explanatory variable (factor) and measure at least one response variable.
a type of observational study case control study
experimental design steps 1. control 2. randomisation 3. replication
types of control treated identically in all aspects. placebo controlled placebo
single-blind control : participants do not know which treatment they have received
double-blind control: neither participant nor researcher making measurements knows who has which treatment
mathematical model mathematical representation of the relationship between simply 2 different quantitative physical phenomena
categorical data represents characteristics or qualities of people or things
distribution statistics of a variable: shows how many times it shows
histogram a graph of the distribution, bars are placed closer together
parameter when describing the population
statistic number taken from a sample
parameter mean symbol mu (microgram)
statistic mean symbol x bar
parameter standard deviation symbol sigma
statistic standard deviation symbol s
confidence interval a probability that a parameter will fall between a set of values
level of confidence the probability with which the estimation of the location of a statistical parameter in a sample population is also true for the population
degrees of freedom maximum number of logically independent values, which are values that have the freedom to vary, in the data sample
matched pair where subjects with same characteristics get paired up
Created by: redshre
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