NSCA CPSS Data Delivery and Reporting Questions and Complete Solutions Graded A+

NSCA CPSS Data Delivery and Reporting Questions and Complete Solutions Graded A+ What does quality and effective communication require - Answer: coordination and alignment between 1) the characteristics of the recipient 2) capabilities of the messenger 3) clarity and accuracy of the message Pre-attentive attributes - Answer: first things end user will focus on subconsciously processed within 200ms of exposure to the visual gestalt principles - Answer: principles that describe how humans make inferences about how visual info is organized and related to one another principles of universal design for data insights - Answer: Equitable use Flexibility in use Simple and intuitive Perceptible info Tolerance for error Low physical effort Size and space for approach and use Equitable use - Answer: design is useful and marketable to people with diverse abilities Flexibility in use - Answer: design accommodates wide range of individual preferences and abilities Simple and intuitive use - Answer: use of design is easy to understand regardless of user's experience, knowledge, etc. Perceptible info - Answer: design communicates necessary info Tolerance for error - Answer: design minimizes hazards and accidental actions Low physical effort - Answer: design used efficiently with minimal fatigue Size and space for approach and use - Answer: Appropriate size and space is provided for approach, reach, manipulation, and use regardless of user's body size, posture, or mobility. when are bar plots best used - Answer: when data represents an accumulation attributes of pre-attentive processing - Answer: color form spatial positioning movement Gestalt principles of visual perception - Answer: Proximity Similarity Common fate Symmetry and parallelism Continuity Closure violin plot - Answer: demonstrate range and density of a measurement wider spots = more data points in that area one of the most important principles of scientific integrity - Answer: honesty methods of visualizing uncertainty in data displays - Answer: 1) plotting intervals that represent areas of uncertainty 2) plotting all data points instead of summary 3) using point opacity to indicate degree of certainty 4) showing multiple looks of same problem