Systems and methods for categorizing and presenting performance assessment data
a performance assessment and data technology, applied in the field of systems and methods, can solve the problems of difficult bulk number crunching, unfavorable data processing and analysis, and inability to meet the needs of users, and achieve the effect of facilitating human understanding
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example 1
[0077]Using weight loss / physical fitness, category prioritization (action block 2030) may apply the standard classification scheme to physical fitness assessment data. Granularity places priority on notes according level of detail: high granularity (e.g., routine workouts to generate “Susan has burned an average of 200 calories while bike riding on Sundays in the past 10 weeks.”); medium granularity (e.g., time-frame split diet to generate “Susan had 8 servings of vegetables since last Tuesday.”); and low granularity (e.g., single performances to generate “Susan ran 2 miles today.”).
[0078]Sample size significance classifies notes as follows: highly significant sample size (e.g., with a sample size of one year, “Susan has lost 30 pounds (25 percent of her starting weight) in the last 365 days.”); medium sample size significance (e.g., with a sample size of a month, “Susan's weight has decreased from 140 pounds to 135 pounds this month.”); and low sample size significance (e.g., singl...
example 2
[0081]Using interactive gaming (e.g., online video poker), category prioritization (action block 2030) may apply the standard classification scheme to gaming assessment data. Granularity places priority on notes according level of detail: high granularity (e.g., specific event to generate “You have averaged +20 credits when being dealt a pair of sevens or lower this month. The average player is even.” or “User has hit the green 18 of 20 times with his drive on the par-three 18th hole at Sawgrass in Tiger Woods Golf.”); medium granularity (e.g., less detailed event to generate “You have been dealt a pair 30 percent of the time this week. The average player is dealt a pair 20 percent of the time.” or “You have won the last 4 times you played John Smith and used Roy Halladay as your starting pitched in MLB The Show.”); and low granularity (e.g., general detail to generate “You averaged −25 credits this week.” or “You have won the last 4 times you played John Smith in Modern Warfare II....
example 3
[0085]Using finance, category prioritization (action block 2030) may apply the standard classification scheme to stock market assessment data. Granularity places priority on notes according level of detail: high granularity (e.g., specific stock event “The most volatile stock in the S&P 500 in the past 60 days has been Netflix (NFLX), with a high of 242 and a low of 129 in that timeframe.”); medium granularity (e.g., smaller time split “Citigroup (C) stock has risen 2.9% in the last 30 days; the rest of the banking sector is down −12.3%.”); and low granularity (e.g., general stock trend “Shares of Verizon (VZ) are down 9 percent since May 1.”).
[0086]Sample size significance classifies notes as follows: highly significant sample size (e.g., “Southwest Airlines (LUV) stock has been positive 210 days and negative 103 days in the last calendar year.”); medium sample size significance (e.g., “The biggest large-cap gainer in tech stocks in the past 120 days has been Cypress Semiconductor ...
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