Research, Biostat Flashcards
Refers to the different
methods applied to
summarize and present data
in a form to make them easier
to analyze and interpret
Desciptive Stat
Tabulation
* Graphical representation
* Summary measures
Methods involved in order to
make generalizations and
conclusions about a target
population,
Inferential Stat
Estimation of parameters
* Testing of hypothesis
Criteria for Good sampling Design
PERA
Practical and feasible
Economy and efficiency
Representative
Adequate
Sampling method where we divide the
population into nonoverlapping
subpopulations or strata, and then select
one sample from each stratum
stratified sample
Selection of the first element is at random
and selection of the other elements is
subsequently taking every k
Systemic Sampling Design
measure how far a set of numbers are SPREAD OUT
Variance
ave. of the SQUARED DEVIATION of the Mean
always a positive value
best for symmetric data
Expresses the standard of deviation as a % of a
mean
Coefficient of variation
used to compare relative dispersion in one type of data with relative dispersion in another type of data
Most common and useful measure because it is the
average distance of each score from the mean or how much each data value deviates from the mean
Standard deviation
Square root of variance
Highly affected by outliers
Most important probability distribution in statistics because it fits many natural phenomena
Normal distribution
probability function that describes how the values of a variable are distributed
Error of rejecting the null hypothesis when it is really
TRUE
Type I (A) error
Declaring a difference when none exists.
Similar to false positive test
Error of NOT rejecting the null hypothesis when it is actually false
Type II (B)
Failing to declare a difference that does exist.
Similar to false negative test
Compares three or more sets of observations made on a single sample
One way analysis of variance using total sum of square - ANOVA
non-parametric: Kruskal-Wallis analysis of variance by ranks
Test the influence (and interaction) of two different variables
Two-way analysis of variance (ANOVA)
non-parametric: Two-way analysis of variance by ranks
Tests the null hypothesis that the distribution of a variable is the same in two (or more) independent samples
Chi square test
non-parametric test: Fisher exact test
Describes the numerical relation between two quantitative variables, allowing one value to be predicted from the other
Regression by least squares method
