Chapters 1 & 2

Front 1

statistics

Back 1

science of conducting studies to collect, organize, summarize, analyze and draw conclusions from data

Front 2

a variable

Back 2

characteristic or attribute that can assume different values

Front 3

data values

Back 3

each value in a data set (datum)

Front 4

descriptive statistics

Back 4

consists of the collection, organization, summarization and presentation of data

Front 5

a population

Back 5

consists of all subjects (human or otherwise) that are being studied

Front 6

a sample

Back 6

group of subjects selected from a population

Front 7

hypothesis testing

Back 7

decision making process for evaluating claims about a population based on information obtained from samples

Front 8

inferential statistics

Back 8

generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables and making predictions

Front 9

qualitative variables

Back 9

variables that can be placed into distinct categories, according to some characteristic or attribute

Front 10

quantitative variables

Back 10

variables that are numerical and can be ordered or ranked

Front 11

discrete variables

Back 11

variables that can be counted

Front 12

continuous variables

Back 12

infinite number of values between any 2 specific values.

Obtained by measuring, often include fractions/decimals.

Front 13

nominal measurement

Back 13

(name)

mutually exclusive (non-overlapping), exhausting categories in which no order or ranking can be imposed on the data

Front 14

ordinal measurement

Back 14

(grades, ranking, judging)

categories that can be ranked; however, precise differences between the ranks do not exist

Front 15

interval measurement

Back 15

(score, temperature)

ranks data and precise differences between units of measure do exist. no meaningful zero.

Front 16

ratio measurement

Back 16

(number)

possesses all characteristics of interval measurement and there exists a true zero. True ratios exist when the same variable is measure on 2 different members of the population

Front 17

Random sampling

Back 17

selected by using chance methods or random numbers

Front 18

systematic sampling

Back 18

numbering each subject of the population and then selecting every __th subject

Front 19

stratified sampling

Back 19

dividing the population in to groups (strata) according to some characteristic that is important to the study then sampling from each group

Front 20

cluster sampling

Back 20

divided into groups by some means such as geographic area or schools in a large district, then researcher randomly selects clusters

Front 21

observational studies

Back 21

researchers merely observe what is happening or what has happened int he past and tries to draw conclusions based on these observations

Front 22

experimental studies

Back 22

researcher manipulates one of the variables and tries to determine how the manipulation influences other variables

Front 23

independent variable

Back 23

the variable being manipulated

(explanatory)

Front 24

dependent variable

Back 24

result

(outcome)

Front 25

confounding variable

Back 25

influences dependent variable but cannot be separated from independent variable

Front 26

ambiguous averages

Back 26

person can use one of the measure of averages that leans most towards their advantage

Front 27

change the subject

Back 27

different values are use to represent the same data

(increase of only 3%, but 3% is 6 million dollars)

Front 28

detached statistics

Back 28

a statistic where no comparison is made

(this snack has 1/3 fewer calories! ... fewer than what?)

Front 29

implied connections

Back 29

claim that attempts to imply connections that do not exist

Front 30

misleading graphs

Back 30

graphs drawn inappropriately

Front 31

faulty questions

Back 31

questions in a survey that are influential to sway towards a specific answer