data and normal distributions

variables

• measured quantities in a study

• studies may have one or multiple

quantitative - continuous data

• measures size of quantity

• can take any value within a range

• units are essential

quantitative - discrete data

• counts or numbers

• takes only specific values

• no units

qualtitative - ordinal data

• categorical data with a ranked order

• differences between categories are not equal

• often displayed using bar charts or scales

qualtitative - nominal data

• categorical data with no order or magnitude

• numbers are labels only

• displayed using bar charts or pie charts

mean

measure of central tendency

variance, standard deviation

describes spread of data around mean

variability and uncertainty

• true values can’t be measured exactly

• repeated measurements improve accuracy

• spread around mean important to assess

variance

• measures how bread out the data are from the mean

• sample variance (S²) based on repeated measurements

• population variance (o²) usually impractical to calculate

standard deviation

• quantifies data dispersion

• low SD - values close to the mean

• high SD - values widely spread

• SD is the square root of variance

normal distribution

• describers random measurement data

• symmetrical bell shapes curve

• mean equal median

• defines by mean and standard deviation

probability of event

• normal distribution curve can be used as a probability density curve

• total area under curve = 1