Stats Chapter 1

Front 1

Process: Descriptive stats

Back 1

Utilizes numerical and graphical methods to look for patterns in a data set (uses graphs) go summaries the information revealed in the data set and to present information in a convenient form

Front 2

Process: Inferential statistics

Back 2

Uses stats to make inferences about the population parameter making estimations, and predictions about the population

Front 3

Experimental unit

Back 3

An object about which we collect data (person, thing, transaction( event)

Front 4

Population

Back 4

A set of all units that we are interested in studying

(Population mean= M)

(Percentage proportion=p)

Front 5

Sample

Back 5

Any subject selected from the sample

(Sample mean= x bar)

(Sample proportion=p hat)

Front 6

Variable

Back 6

A characteristic or property of an individual experimental unit in the population

Front 7

Statistical inference

Back 7

An estimate, prediction, or some other generalization about a population based on information contained in a sample

Front 8

Reliability

Back 8

How good the inference is

Front 9

Measure of reliability

Back 9

A statement(usually quantitative) about the degree of uncertainty associated with a statistical inference

Front 10

4 elements of descriptive statistical problems

Back 10

1. Population or sample of interest

2. One or more variables that are investigated

3. Tables,graphs, or numerical summary tools

4. Identification of patterns in the data

Front 11

5 elements of inferential statistic problems

Back 11

1. Population of interest

2. One or more variables that are to be investigated

3. The sample of population units

4. The inference about the population based on information contained in the sample

5. The measure of the reliability of the inference

Front 12

Quantitative data

Back 12

Measurements that are recorded on a naturally occurring numerical scale

Front 13

Qualitative

Back 13

Measurements that cannot be measured- classified into groups

Front 14

How data can be collected: Published Source

Back 14

Such as in a book, journal or newspaper

Front 15

How data can be collected: Designed Experiment

Back 15

A data collection method where the researcher exerts full control over characteristics of the experimental Units sampled

Front 16

How data can be collected: Observational Study

Back 16

Where experimental units sampled are observed in their natural setting ( surveys,polls)

Front 17

Selection bias

Back 17

Results when a subset of experimental units in the population has little or no chance of being selected for the sample

Front 18

Non response bias

Back 18

A type of selection bias that results when data on all experimental units in a sample are not obtained

Front 19

Measurement error

Back 19

Refers to inaccuracies in the values of the data collected ( misleading questions)

Front 20

Type of random sample: Simple random sample

Back 20

Sample selected from the population

Front 21

Type of random sample: Stratified Random Sampling

Back 21

Used when the experimental units associated with the population can be separated into groups ( ex. Republicans and democrats)

Front 22

Type of random sample: Cluster Sampling

Back 22

Collecting data from all experimental units within a cluster

Front 23

Type of random sampling: systematic sampling

Back 23

This method involves systematically selecting every kth experimental unit from a list of all experimental units

Front 24

Type of random sample: randomized response sampling

Back 24

When the questions of the pollsters are most likely to exclude false answers