Unit 1: MCT and variability

Descriptive Statistics

Organize/summarize variability in a collection of observations or scores. Makes things concise

Inferential Statistics

Allows us to generalize beyond collections of observations. Helps make decisions and test hypotheses

Qualitative data

words, letters, numbers. represents a class or category

Ranked data

numbers that represent relative standing

Quantitative data

Numbers that represent an amount or a count

Nominal level of measurement

With qualitative data, numbers only help to distinguish one from the other (ex: 1=female, 2=male)

Ordinal level of measurement

with ranked data, numbers place things in order, no info on how far apart (ex: 1=first, 2= second, 3=third)

interval/ratio level of measurement

With quantitative data, numbers place objects into order with meaningful differences, ratio: true zero, equal intervals stay consistent across scales

distribution of datsa

how often scores/values occur in data (frequency), distributions have spread (x axis) and differences in frequency (y axis)

Characteristics of distributions

modality= how many peaks

skewness= is graph symmetric

Measures of central tendency

mean, median, mode

Mode advantages

not affected by extreme values, frequency distribution shows peaks —> modes

mode disadvantages

can be misleading, doesn’t take all scores into account, distributions can have same mode but loo very different

median advantages

takes all scores into account, not susceptible to outliers

median disadvantages

need to arrange all data in order, hard to compute with large sample

mean advangates

best estimate of populaiton center, most commonly used, takes all numbers into account

mean disadvantages

susceptible to outliers

Unimodal and symmetric

Positive skew

lare negative skew

measures of variability

measures amount by which scores are dispersed or scattered in a distribution

range advantages

covers whole range of data, not just middle

range disadvantages

only takes into account 2 scores (big and little), neglects middle scores

variance

The degree to which the scores differ on average from the mean

standard deviation

rough measure of the average amount by which scores deviate on either side of the mean

definitional

theoretical/intuitive, shows proof

computational

easy for calculations, but less clear