AP Statistics Unit 1: Key Definitions

Statistics

the collection, analysis, and presentation of data

Descriptive statistics

organizing and summarizing data

Inferential statistics

using probability to infer something about data

Population

a collection of people/objects under study 

Sample

a subset of the population used to study the population

Parameter

a numerical characteristic of the whole population (ex: mean age of population)

Statistic

a number from a sample that is used to estimate a parameter (ex: mean age of 3 states)

x̅

notation for sample mean

Sx

notation for sample standard deviation

p̂

notation for sample proportion

Qualitative data

data that has categorical and descriptive attributes (ex: favorite color)

Quanitative Data

data that is numerically measured

Quantiative Discrete

Result of counting (No between data points; whole numbers) (ex: backpacks per student)

Quantitative Continuous

All numerical values in a given range (ex: hours spent per week on reels)

Frequency

tbe number of times a data value occurs

Relative frequency

frequency/total number of data values

cumulative relative frequency

the accumulation of previous relative frequencies

Simple Random sampling

In a population, each individual has the same probability of being selected as part of the sample (ex: randomly selecting 5 students from AP stats via a number generator)

Stratified sampling

divides population into groups and then take a proportion of each group (ex: divide Pacifica by gender, then take 15% of each strata)

Cluster sampling

divides population into groups (clusters) and randomly selects some groups (clusters) (ex: splitting AP Stats students into 4 groups and selecting 2). 

Systematic sampling

put all individuals in order and randomly select a starting point, then collecting every nth piece of data (ex: every 3rd AP stats student in a line gets chosen)

Convenience sampling

using results readily available; not random (sampling every person who walks into a game stop)

Sampling Bias

when a sample is not representative of the population (ex: surveying only French students to determine American thoughts on US Gov)

Explanatory Variable

variable that causes change in the response variable (independent)(ex: sleep before day of SAT)

Response Variable

variable that is affected by the explanatory variable (dependent) (SAT Score)

Treatments

different values of the explanatory variable (5 hours of sleep vs 10)

experimental units

the object/individual being tested (SAT test taker)

Lurking variable

an extra variable that “clouds” a study affecting the response variable unwantedly (ex: caffeine intake before the SAT)

Random assignment

meant to minimize impact of lurking variables; each treatment group has equal lurking variable affect (ex: sat test takers are split into random groups, equalizing lurking variable effects)

Control group

a treatment group given a placebo or tratement that cannot influence the response variable 

blind experiment

individuals don’t know their treatment

double blind experiment

neither individuals nor experimenters treating know the treatment