Stat Chapter One

Front 1

Statistics

Back 1

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

Front 2

Variable

Back 2

A characteristic of attribute that can assume different values.

Front 3

Data

Back 3

There values that the variables can assume.

Front 4

Random values

Back 4

Variables whose values are determined by chance.

Front 5

Data set

Back 5

A collection of data values.

Front 6

Data value/ datum

Back 6

Each value that forms a data set.

Front 7

Population

Back 7

Consists of all subjects that are being studied.

Front 8

Census

Back 8

When data is collected from every subject in the population.

Front 9

Sample

Back 9

A group of subjects selected from a population.

Front 10

Descriptive statistics

Back 10

Consists of collection, organization, summarization, and presentation of data.

Front 11

Inferential statistics

Back 11

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

Front 12

Probability

Back 12

The chance of an event occurring.

Front 13

Hypothesis testing

Back 13

A decision-making process for evaluating claims about population, based on information obtained. from samples.

Front 14

Qualitative variables

Back 14

Are variables that have distinct categories according to some characteristic or attribute.

Front 15

Quantitative variables

Back 15

Are variables that can be counted or measured.

Front 16

Discrete variables

Back 16

Can be assigned values that are countable.

Front 17

Continuous variables

Back 17

Can assume an infinite number of values between any two specific values. They are obtained by measuring. They often include fractions and decimals.

Front 18

Boundary

Back 18

A class in which a data value would be placed before the data value was rounded.

Front 19

Measurement scales

Back 19

How variables are categorized, counted, or measured.

Front 20

Nominal level of measurement

Back 20

Classifies days into mutually exclusive categories in which no order or ranking can be imposed on data.

Front 21

Ordinal level of measurement

Back 21

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

Front 22

Interval level of measurement

Back 22

Ranks data, and precise differences between units of measure do exist; however, there is no meaningful zero.

Front 23

Ratio level of measurement

Back 23

Just like interval measurement, except there is a true zero. Also true ratios exist when the same variable is measured on two different members of the population.

Front 24

Random sample

Back 24

A sample in which all members of a population have an equal chance of being selected.

Front 25

Systematic sample

Back 25

A sample obtained by selecting every kth member of the population where k is a counting number.

Front 26

Stratified sample

Back 26

A sample obtained by dividing the population into subgroups or strata according to some characteristic relevant to the study. Then subjects are selected at random from subgroup.

Front 27

Cluster sample

Back 27

Is obtained by dividing the population into sections or clusters and then selecting one or more clusters at random and using all members in the cluster as the members of the sample.

Front 28

Sampling error

Back 28

The difference between the results obtained from a sample and the results obtained from the population from which the sample was selected.

Front 29

Nonsampling error

Back 29

When data are obtained erroneously or the sample is biased, i.e. nonrepresentative.