Sped 503A Lesson 5

Front 1

Visual Displays
four categories

Back 1

1) Data maps
2) Time series graphics
3) Narrative graphics of space and time
4) Relational graphics

Front 2

Data map

Back 2

A map that convery statistical information with respect to area and location

Front 3

Time Series Graphics

Back 3

A graphical display that has a "time series scale on the hoirzontal axis and a quantitative sacle on the vertical access. Time progress from left to right.

Front 4

Time Series Graphics- Narrative graphics of space and time

Back 4

Narrative graphics of space and time- a times series display with addition of spatial information (march of Napoleon's army, life cycle of a beetle)

Front 5

Time Series Graphics- Relational graphics

Back 5

A graphic that displays one variable quantity in rleationship to another variable quantity (relating 2 variables- cig consumtion and death- shows correlations)

Front 6

Emphasized the use of statistic graphics in behavior analysis in 1956

Back 6

Skinner

Front 7

Experimental Control

Back 7

A predictable change in an indivdiual's behaviror that can be reliably and repeatedly produced by the systematic maniulation of some aspect of the person's environment

Front 8

Data

Back 8

The quantitative (#s) results of planned, deliberate and usually controlled observation

Front 9

Dependent Variable

Back 9

target behavior of a study (the measurable dimensions of a target behavior)

Front 10

Independent Variable

Back 10

the particular arrangement of environmental events that the experimenter manipulates during a study

Front 11

Benefits of Graphic Display of Behavioral Data

Back 11

1) Ongoing access when plotted immediately
2) Direct and continuous contact-can explore interesting variations
3) use as judgement aides
4) conservative method to determine significante of behavior change
5) indepdent judgments and interpretations of the meaning and significance of behavior change

Front 12

The most commonly use graphic format in the display of data in beahvior analysis

Back 12

Line Graphs (a time series graph)

Front 13

Seven parts of a simple line graph

Back 13

1) Horizontal Axis (x-axis)
2) Vertical Axis (y-axis)
3) Phase/condtiion change lines
4) Phase/condition labels
5) Data points
6) Data path
7) Figure legend

Front 14

Most common type of vertical axis in behavior analysis

Back 14

equal-inteval vertical axis

Front 15

Maximum number of data paths that can be shown effectively on a line graph

Back 15

three

Front 16

4 Other types of graphs

Back 16

1) Bar graph
2) Cumulative record
3) Standard Celeration Charts
4) Charts-logarithmic vertical axes (semi-logarithmic charts)

Front 17

Bar Graph

Back 17

displays quantitative information by means of a series of vertical rectngles (sed to compare the values of multiple entities at a given point in time)

Front 18

Example of a cumulative record

Back 18

A cumulative record of key pecking by a pigeon

Front 19

Semilogarithmic charts

Back 19

Has a logarithmic scale on one axis and a linear scale on th other (sometimes reffered to as a rate-of change or ratio graphic) Looks t how fast something is changing

Front 20

Standard Celeration Chart covered two universal dimensions of all behavior

Back 20

count and time

Front 21

Standard Celeration Chart

Back 21

34 degrees slope, or doubling (x2)

Front 22

Scatterplot

Back 22

shows the relative distribution of indivdiual mesres in a data set

Front 23

Axes proportions recommended by Cooper et. al.

Back 23

2/3 = 66% difference of vetical to horizontal axis

Front 24

Used to represent discontinuity of time on the horizontal axis

Back 24

scale breaks

Front 25

Tick marks

Back 25

Help view decode information on graph rapidly.

Front 26

Vetical lines used to indicatea change in treatment of experiemental procedures

Back 26

condition change lines

Front 27

labels used to indicate a change in treatment of experimental procedures

Back 27

condition change labels

Front 28

Data paths

Back 28

created by drawing astraight line from the center of each data point in a given data set t othe center of the next data point

Front 29

Figure legend

Back 29

A concise but complete description of the figure

Front 30

Visual analysis

Back 30

The primary strategy of applied researchers use for analyzing data collected within the context of single subject research

Front 31

Guidline for minimum number of data points

Back 31

minimum of three data point colleted over a minimum of two days should be plotted if the data are stable (but, the more the better)

Front 32

Variability

Back 32

the bounce inherent in the data path

if high, suggests lack of experimental control. The higher the variability the more data needs to be be collected to determine a predictable pattern of behavior

Front 33

Level

Back 33

the average of the data within a condition and is typically calculated as the mean of median

Front 34

Trend

Back 34

The overall direction of the data path (increasing, decreasing, maintaining or zero trend)

Front 35

Analying graphic data
Stability of baseline

Back 35

when baseline data drift in the directin of the intervention it is difficult to analyze claims of the intervention.
-Stable baselines or baselines in the opposite direction of the intervention shelp determine change is attributed to the intervention

Front 36

Analying graphic data
Variability within Phases

Back 36

allows us to determine the degree to the effect we have or do not have control

Front 37

Analying graphic data
Variability between phases

Back 37

-Variable baseline followed by stabe intervention data + degree of experimental control.
-Variable baseline followed by stabe intervention tht don't exceed baseline level = lesser degree of ec.
-Variable baseline followed by variable intervention data = weak ec

Front 38

Analying graphic data
Overlap between data of adjacent phases

Back 38

degree of overlap between phases indicates how convincing the intervention is. High degree of overlap=little effect

Front 39

Analying graphic data
Number of data points in each phase

Back 39

more data points are neessary if there is a high degree of variability, overlap, or data drift

Front 40

Analying graphic data
Changes in trend within phase

Back 40

becomes more difficult to determine if the change during the intervention was responsibile for the observed change.

Front 41

Analyzing Graphic Data
Changes in tend between adjacnt phases

Back 41

the degree and direction of the trend compared to baseline reflect the intervention effect

Front 42

Analyzing Graphic Data
Changes in level between phases

Back 42

changes in level show the effectivenes, or lack of, of an intervention

Front 43

Analyzing Graphic Data
Analysis of data across similar hases
Changes in trend within phases

Back 43

beyond changes within phases andbetween adjacent phases, examining the consistency of data across similar phases provides information on the overall effectiveness of an intervention

Front 44

Analyzing Graphic Data
Evaluation of the overall pattern of the data

Back 44

evaluate the impact of the whole set of data as a bais to judge the success or failure of an experiment.
Look at within and between conditions