Lecture 1-2 Data

Front 1

Independent Variable

Back 1

A variable whose variation does not depend on that of another.

Front 2

Dependent Variable

Back 2

A variable whose variation depends on that of another.

Front 3

Confounding Variable

Back 3

Obscure variables between independent and dependent variables.

Front 4

Mensurative Experiment

Back 4

A measured experiment where no manipulation was preformed on variables

Front 5

Manipulative Experiment

Back 5

Control or manipulate independent and confounding variables.

Front 6

Trial Run

Back 6

A way to determine sample size by taking ambiguous sample size that is reflective.

Front 7

Cumulative Mean (Avg)

Back 7

Calculate mean of one sample size, increase and repeat and recalculate until it tapers off and stops fluctuating, within a 5%.

Front 8

Pseudoreplication

Back 8

Replicates that are NOT independent from each other (i.e- people from same family, plants from same location)

Front 9

Random Sampling

Back 9

Random choice through computer generator. Equal chance to be chosen as independent. (Unbiased)

Front 10

Regular Sampling

Back 10

Variables chosen at even intervals.

Front 11

Nominal Attribute Scale

Back 11

Scale of classifying events or objects into a mutually exclusive category, and characteristics. (i.e - red/white/blue).

Front 12

Ranked Ordinal Scale

Back 12

ranked, mutually exclusive category. The order has objective meaning. (i.e- poor/fair/good , medium/small/large)

Front 13

Interval Measurement Scale

Back 13

Scale that is a ordinal scale with a constant interval between ranks. with objective meaning, where the zero is arbitrary (i.e - time of day, temperature in Celsius or Fahrenheit, compass reading, date)

Front 14

Ratio Measurement Scale

Back 14

Interval scale with a true zero that is not arbitrary ( i.e - mass or weight, distance, temperature in Kelvin, height)

Front 15

Continuous Date

Back 15

Can take any value within the observed range. the interval between observation is not limited. Usually with decimal places (i.e- length, weight, time, temp.)

Front 16

Discrete Date

Back 16

Can take only certain values. Usually counted data.

Front 17

Accuracy

Back 17

The nearness of a measurement to the actually value of the variable being measured.

Front 18

Precision

Back 18

The degree of variability in repeated measurements of the same object

Front 19

Population

Back 19

The set of items or observations about which one wishes to draw a conclusion

Front 20

Sample

Back 20

A subset of observations drawn from a population.

Front 21

Frequency Distributions

Back 21

Tables or grtaphs indicting how often a particular value occurs in the data set

Front 22

Ordered Array

Back 22

Putting the data in order indicating how often each value occurs

Front 23

Range

Back 23

R= largest observation - smallest observation

Front 24

Bar Diagram

Back 24

Used for discrete data, indicates there are no fractions inside data set. Will have spacing between bars.

Front 25

Ogive

Back 25

Graph of cumulative relative frequency vs upper class limits. Used for discrete data

Front 26

Histogram

Back 26

Graph used for continuous data with no spacing between bars.

Front 27

Frequency Polygon

Back 27

Located on histogram graph, a line connecting midpoints.

Front 28

Normal Distribution

Back 28

Will have even ends and top points.

Front 29

Skewed Right Distribution (+)

Back 29

Will have lower limits towards right.

Front 30

Skewed Left Distribution(-)

Back 30

Will have lower limits towards left

Front 31

Platykurtic Distribution

Back 31

Will have a shallow mode distribution.

Front 32

Bimodal Distribution

Back 32

Will have two modes, that will not be located within the mean.

Front 33

Multimodal Distribution

Back 33

Will have more then one mode, more then one peak

Front 34

Uniform Distribution

Back 34

Very little information provided, relative even distribution throughout entire histogram

Front 35

Leptokurtic Distribution

Back 35

Sharp peak with small upper and lower tail.