Chapter 11 - Understanding Statistics in Research Flashcards
used to explain the extent of a relationship, such as the likelihood that an event will occur in a given situation or that an event can be accurately predicted
probability theory
theory that assumes that all of the groups in a study used to test a hypothesis are components of the same population relative to the variables under study
traditionally expressed as a null hypothesis
decision theory
conclusion or judgment based on evidence
inference
application of information that has been acquired from a specific instance to a general situation
generalization
the cutoff point or the probability level at which the results of statistical analysis are judged to indicate a statistically significant difference between the groups
in nursing studies, usually 0.05
signified by alpha
level of statistical significance
theoretical frequency distribution of all possible values in a population
the normal curve (aka the bell curve)
when the null hypothesis is rejected but is actually true
e.g., when the results indicate that there is a significant difference when in reality there is not
more serious errors
Type 1 error (false negative)
when the null hypothesis is regarded as true but it is in fact false
ex: statistical analysis indicate no significant relationship between relationship but in reality there is a significant relationship
less serious errors
Type II error (false positive)
the probability that a statistical test will detect a significant difference that exists
power
determination of the risk of a Type II error
power analysis
the degree to which the phenomenon is present in the population, or the degree to which the null hypothesis is false
effect size
the occurrance of scores or categories in a study - just counting
frequency distribution
the midpoint of the data or the average of the data
measures of central tendency
measures of individual differences of the members of the sample; variability
measures of dispersion
range
