Define And Describe The Three Stages Of Design Psychology Case Study
1) The first stage, low-level property extraction. This stage consists of detection of shape, spatial attributes, orientation, color, texture, movement and often called “preattentive” processing.
Important characteristics of Stage 1 processing include:
• Rapid parallel processing
• Extraction of features, orientation, color, texture, and movement patterns
• Transitory nature of information, which is briefly held in an iconic store
• Bottom-up, data-driven model of processing
2) The second stage, pattern perception. In this stage, visual field is divided in simple patterns such as continuous contours, regions of the same color or texture. This stage is influenced and guided by the …show more content…
In this stage, it uses the information from stage two to respond to visual "queries" from our conscious attention and information is further reduced to a few objects held in visual working memory and used to answer and construct visual queries.
2. Define the OODA Loop steps and describe in your own words why it’s important to business.
1) Observe. Observe is the stage that focus on or gathering or collecting current information from as many sources as practically as possible. All the decisions are based on observations, therefore, the key challenge to effective observation, especially in the era of ‘big data,’ is knowing which elements of information to monitor and how to apply the right filters to each.
2) Orient. Orient is the stage of analyzing the information and use it to update the current reality. Orientation is the most important part of OODA loop because it shapes the way we observe, the way we decide and the way we act.
3) Decide. Decide is the stage of determining a course of action. Having excellent data and analysis and orientation, allows the organization to make a better and more repeatable …show more content…
Interactivity makes comparing data in a visualization particularly engaging. This can be done by, i.e., placing charts or illustrations side-by-side and provide the controls, letting the viewer uncover things on their own.
7) Reveal the data at various level of detail. Visualization or presentation should be able to reveal the data from a broad overview to the fine structure.
8) Show the data with a clear purpose: Visualization should be able to determine the purpose of the data presentation whether it is for description, exploration, tabulation, or decoration.
9) Integrate closely with statistical and verbal descriptions of the data. Visualization should include a link off to the raw data, and some explanation of the how and why. Visualization rarely works in isolation: rather, it is used to complement a written account and benefits from being complemented with statistical measurements.
5. Define and describe the considerations to Formulate Good Analysis Questions.
1) Clear. When asking question, clarity is essential. A good analysis question should be sharply defined and will be clearly stated with as little ambiguity as possible. If there are assumptions implicit in the business question, state them explicitly in the analysis