Basics of Statistics

Statisticsthe science of collecting, analyzing, and drawing conclusions from data

Descriptive statisticsthe methods of organizing & summarizing data

Inferential statisticsinvolves making generalizations from a sample to a population

This will be the 2nd semester

PopulationThe entire collection of individuals or objects about which information is desired

SampleA subset of the population, selected for study in some prescribed manner

Dataobservations on single variable or simultaneously on two or more variables

Context (the W’s)Tells us WHO was measured

WHAT was measured WHEN the study was performed WHERE the data was collectedWHY the study was performed

HOW the data were collected

Variable any characteristic whose value may change from one individual to another

Types of variables

Categorical variablesor qualitativeidentifies basic

differentiating characteristics of the population

Quantitative variablesor numerical observations or measurements

take on numerical valueshave units (dollars, hours, etc)two types - discrete & continuous

Discrete (numerical)

listable set of valuesusually counts of items

Continuous (numerical)

data can take on any values in the domain of the variable

usually measurements of something

Classification by the number of variablesUnivariate - data that describes a single

characteristic of the populationBivariate - data that describes two

characteristics of the populationMultivariate - data that describes more

than two characteristics (beyond the scope of this course

Identify the following:

gender age Right or left handed How you got to school Number of movies number of girls in class Fastest speed driven

categorical numerical categorical categorical numerical numerical numerical

Types of Distributions

4 common types

Symmetricalrefers to data in which both sides are

(more or less) the same when the graph is folded vertically down the middle

bell-shaped is a special type–has a center mound with two sloping

tails

Uniformrefers to data in which every

class has equal or approximately equal frequency

Skewed (left or right)refers to data in which one

side (tail) is longer than the other side

the direction of skewness is on the side of the longer tail

Bimodal (multi-modal)refers to data in which two

(or more) classes have the largest frequency & are separated by at least one other class