1 R. Ching, Ph.D. MIS Area California State University, Sacramento Week 9 March 29 GraphicsGraphics Graphics BuilderGraphics Builder

2 R. Ching, Ph.D. MIS Area California State University, Sacramento Sales Revenue

3 R. Ching, Ph.D. MIS Area California State University, Sacramento Bar Chart

4 R. Ching, Ph.D. MIS Area California State University, Sacramento Pie Chart Note. Slices are ordered large to small, counterclockwise

5 R. Ching, Ph.D. MIS Area California State University, Sacramento Man-Machine Interface Studies Color improvesColor improves –Performance in recall –Performance in a search and locate task –Performance in a retention task –Comprehension of instructional materials –Performance in a decision judgment –Ability to extract information (very quickly)

6 R. Ching, Ph.D. MIS Area California State University, Sacramento Man-Machine Interface Studies Display Format: Graphic versus tabularDisplay Format: Graphic versus tabular –Graphical display is more conducive to information recall than tabular display when the task required memory for temporal and set-integrative patterns –Recall of simple facts (e.g., point values, simple comparisons) was indifferent to variations in presentation format

7 R. Ching, Ph.D. MIS Area California State University, Sacramento Color and Decision-Maker Productivity “If the subject’s task is to identify some feature of a target, colors can be identified more accurately than sizes, brightness, familiar geometric shapes, and other shape or form parameters, but colors are identified with less accuracy than alphanumeric symbols.” Christ, 1975“If the subject’s task is to identify some feature of a target, colors can be identified more accurately than sizes, brightness, familiar geometric shapes, and other shape or form parameters, but colors are identified with less accuracy than alphanumeric symbols.” Christ, 1975

8 R. Ching, Ph.D. MIS Area California State University, Sacramento Color and Decision-Maker Productivity “...the relative effectiveness of color is dependent upon the task of the subject. Color coding appears to be most effective when the position of the target(s) is unknown. This is particularly evident in tasks involving search over cluttered display fields. Other tasks such as target identification tend not be beneficially influenced by color coding.” Barker and Krebs, 1977“...the relative effectiveness of color is dependent upon the task of the subject. Color coding appears to be most effective when the position of the target(s) is unknown. This is particularly evident in tasks involving search over cluttered display fields. Other tasks such as target identification tend not be beneficially influenced by color coding.” Barker and Krebs, 1977

9 R. Ching, Ph.D. MIS Area California State University, Sacramento Color and Decision-Maker Productivity “If graphics and color are to produce positive results they must be used with considerable care. There are apparently important interactions between the use of graphic/color and attributes of both the decision maker and decision task. Effective use will require more than just converting our old tabular presentations to graphics.” Ives, 1982“If graphics and color are to produce positive results they must be used with considerable care. There are apparently important interactions between the use of graphic/color and attributes of both the decision maker and decision task. Effective use will require more than just converting our old tabular presentations to graphics.” Ives, 1982

10 R. Ching, Ph.D. MIS Area California State University, Sacramento Human Information Processing “...the human information processing system can handle considerably more inputs if those inputs are received on multiple channels.” Ives, 1982 Ives, 1982 ColorColor Relative PositionRelative Position BrightnessBrightness MovementMovement ShapeShape Information capacity of a single channel is approximately seven, the number of distinguishable levels (differences) Five Visual Input Channels

11 R. Ching, Ph.D. MIS Area California State University, Sacramento Boeing 777 “Glass Flight Deck”

12 R. Ching, Ph.D. MIS Area California State University, Sacramento Boeing “Steam Gauges,” circa 1970

13 R. Ching, Ph.D. MIS Area California State University, Sacramento Boeing 777 Glass Flight Deck LCD displays Analog images Fuel system Engines The different images can be displayed on each display

14 R. Ching, Ph.D. MIS Area California State University, Sacramento Boeing 777 Glass Flight Deck Fuel system Engines Tanks

15 R. Ching, Ph.D. MIS Area California State University, Sacramento Tokyo (NRT) San Francisco (SFO) 5,117 miles (9-10 hours) Flight path transmitted and programmed into aircraft’s computer from San Francisco before the aircraft leaves TokyoFlight path transmitted and programmed into aircraft’s computer from San Francisco before the aircraft leaves Tokyo San Francisco maintenance base continuously monitors the aircraft’s computer while in flightSan Francisco maintenance base continuously monitors the aircraft’s computer while in flight The aircraft’s computer is capable of flying the aircraft (during its cruise) from origin to destination with human assistanceThe aircraft’s computer is capable of flying the aircraft (during its cruise) from origin to destination with human assistance The aircraft’s computer is capable of landing the aircraftThe aircraft’s computer is capable of landing the aircraft Factoid Factoid

16 R. Ching, Ph.D. MIS Area California State University, Sacramento Graphs Convey information about summarized data, particularly to identify trend and proportionConvey information about summarized data, particularly to identify trend and proportion TypesTypes –Pie chart Proportion of a relative frequency to the wholeProportion of a relative frequency to the whole –Bar graph (vertical and horizontal) Frequency or relative frequencyFrequency or relative frequency –Line graph TrendTrend

17 R. Ching, Ph.D. MIS Area California State University, Sacramento Independent and Dependent Variables Pie charts and bar graphsPie charts and bar graphs –Categorical variable assigned to the independent variable –Quantitative units assigned to the dependent variable Line graphsLine graphs –Independent variable assigned to the horizontal or x axis Must of at least ordinal scaleMust of at least ordinal scale –Dependent variable is a measurement of at least interval scale

18 R. Ching, Ph.D. MIS Area California State University, Sacramento Independent and dependent variables?

19 R. Ching, Ph.D. MIS Area California State University, Sacramento Independent and dependent variables?

20 R. Ching, Ph.D. MIS Area California State University, Sacramento A Few Simple Steps for Creating a Graph Build the initial SQL command in SQL*PlusBuild the initial SQL command in SQL*Plus In Graphics BuilderIn Graphics Builder –Build the data model –Build the graph Select the graph typeSelect the graph type Assign the independent and dependent to the categories and values, respectivelyAssign the independent and dependent to the categories and values, respectively Format the various components of graph as neededFormat the various components of graph as needed Save and run the graphSave and run the graph

21 R. Ching, Ph.D. MIS Area California State University, Sacramento Create the Data Model

22 R. Ching, Ph.D. MIS Area California State University, Sacramento Select the Graph Type and Subtype

23 R. Ching, Ph.D. MIS Area California State University, Sacramento Assign the Independent Variable

24 R. Ching, Ph.D. MIS Area California State University, Sacramento Assign the Dependent Variable

25 R. Ching, Ph.D. MIS Area California State University, Sacramento Initial Graph Field size too small