Psy 230 Exam 1

Front 1

Population

Back 1

A complete collection of organisms or objects having some common characteristic.

Front 2

Parameter

Back 2

A measurable characteristic of a population.

Front 3

Sample

Back 3

A subset of a population.

Front 4

Statistic

Back 4

A measurable characteristic of a sample.

Front 5

Sampling

Back 5

The process of selecting a sample from a population.

Front 6

Unbiased Sample

Back 6

A sample that shows no systematic tendency relative to the population; a sample that accurately reflects the population from which it was drawn.

Front 7

Biased Sample

Back 7

A sample that is unrepresentative of the population from which it was drawn.

Front 8

Random Sampling

Back 8

Sampling in which each population member theoretically has an equal chance of being selected.

Front 9

Random Assignment

Back 9

Every participant in a study has an equal chance of being assigned to one or another experimental condition or group.

Front 10

Statistics

Back 10

A set of tools concerned with the collection, organization, and analysis of data; technically statistics are summaries (eg., averages, medians) of sample characteristics, like age.

Front 11

Variable

Back 11

Anything that may take on different values or amounts.

Front 12

Independent Variable

Back 12

The independent variable is the variable that is manipulated by the researcher. The independent variable is something that is hypothesized to influence the dependent variable.

Front 13

Dependent Variable

Back 13

The dependent variable is the variable that is simply measured by the researcher. It is the variable that reflects the influence of the independent variable. For example, the dependent variable would be the variable that is influenced by being randomly assigned to either an experimental condition or a control condition.

Front 14

Data

Back 14

Numbers; the rusults of measurement; THE DATA ARE!

Front 15

Operationalize

Back 15

Translating a psychological phenomenon or something abstract into something quantifiable.

Front 16

Score

Back 16

Data point, symbolized by X

Front 17

Frequency Distribution

Back 17

Distribution in which the scores are ranked from highest to lowest, and the number of times each score occurs (its frequency) is listed beside it.

Front 18

Frequency

Back 18

The number of times each scores occurs; symbolized by f.

Front 19

Continuous Variable

Back 19

Variable whose measurement can take an infinite number of values. The scale is continuous and not made up of discrete points. Eg. Time.

Front 20

Discrete Variable

Back 20

Variable capable of assuming only specific values.

Front 21

Apparent Limits

Back 21

Limits of intervals with gaps between them.

Front 22

Real Limits

Back 22

Limits of scores without gaps between them; constructed by subtracting a half unit from the lower apparent limit and adding a half unit to the upper apparent limit.

Front 23

Percentage Frequencies

Back 23

Frequencies of occurrence presented as percentages of the total sample.

Front 24

Cumulative Frequency Distribution

Back 24

Distribution constructed by starting with the distribution's lowest interval and accumulating frequencies as you ascend.

Front 25

Cumulative Percentage

Back 25

Tells the percentage of scores in an interval plus the percentage of scores below the interval.

Front 26

Cumulative Percentage Distribution

Back 26

Frequency distribution in which the percentage frequencies are accumulated from the lowest score to the highest score.

Front 27

Qualitative Variables

Back 27

Express non-numeric attributes. Hair color, eye color….

Front 28

Quantitative Variables

Back 28

Measured in terms of numbers. Height, weight, shoe size….

Front 29

Discrete Variables

Back 29

Actual numbers on a scale. Eg. The number of children in a household.

Front 30

Nominal Scale

Back 30

Names or categories. Eg. Gender, handedness, favorite color. Qualitative dada.

Front 31

Ordinal Scale

Back 31

Ranking persons or objects according to magnitude (in order). Eg. Class rank, race results. Greater than - Less than relationship. Quantitative data.

Front 32

Interval Scale

Back 32

Numbers have relative merit and have equal units of measurement. No real Zero. Eg. Temperature, IQ test.

Front 33

Ratio-level Scale

Back 33

True 0 or a theoretically meaningful 0, 0 means a complete absence of what you are measuring, probably measurement of physical characteristics, probably continuous

Front 34

Descriptive Statistics

Back 34

Statistics used to summarize and describe data. Eg. Your average test scores over a semester.

Front 35

Inferential Statistics

Back 35

Making inferences from data. Statistics which are used to make inferential statements about a population.