Scoring - Revision history

Anna: /* Normalization */

2025-07-25T16:22:48Z

Normalization

Anna at 18:26, 25 April 2025

2025-04-25T18:26:03Z

Trent: /* Formula */

2022-06-10T16:09:06Z

Formula

Trent: /* Formula */

2022-06-10T16:07:23Z

Formula

Trent: /* Formula */

2022-06-10T16:05:08Z

Formula

Michael at 15:56, 24 March 2022

2022-03-24T15:56:05Z

Trent: /* Adjusted Score */

2021-01-30T18:47:30Z

Adjusted Score

Michael at 23:08, 6 January 2021

2021-01-06T23:08:45Z

Michael: Created

2021-01-06T23:07:22Z

Created

Michael at 22:12, 6 January 2021

2021-01-06T22:12:43Z

@@ Line 18: / Line 18: @@
 # We then determine the standard deviation of the sample
 # We calculate the z-score for each judge
-# We then adjust each judge's scores by the [-1 * (z-score * standard deviation)]
+# We then adjust each judge's scores by the [raw score - (z-score * standard deviation)]
 # We then calculate the average score of each project
 # The project with the highest average score is the winner

@@ Line 1: / Line 1: @@
-: Scoring each project takes much consideration and deliberation by each judge. Unfortunately making sense of that score afterwards and determining the best Project Scores can also take much consideration and deliberation. On this page we cover that in a little more detail so you have the information needed to make the best decisions possible.
+: Scoring each project takes much consideration and deliberation by each judge. Making sense of that score afterwards, and determining the best project scores can also take much consideration and deliberation. On this page, we cover in detail how zFairs takes the judges scoring and calculates it to give participants the fairest score possible.
 : For each Project and Judging result you will have access to up to 4 different scores. These are the <strong>Average Score</strong> for the Project, the <strong>Adjusted Score</strong>, the <strong>Raw Score</strong> and the <strong>Z-Score</strong>. See below for clarification on each of the individual scoring types.
@@ Line 100: / Line 100: @@
 :* https://www.simplypsychology.org/z-score.html
+[[File:ZFairsIcon.png|thumb|left]]
 <br/><br/><br/><br/>

← Older revision		Revision as of 16:09, 10 June 2022
Line 93:		Line 93:
	\|}		\|}

		+	The z-scores are values shown in the above table are bogus.

	: Some helpful articles for reading on better understanding z-score values:		: Some helpful articles for reading on better understanding z-score values:

@@ Line 67: / Line 67: @@
+#
+|
-+2.59 <br/>
++0.56 <br/>
--6.83 <br/>
+-1.47 <br/>
 +5.49 <br/>
 -0.31 <br/>

@@ Line 54: / Line 54: @@
 ::{| class="wikitable" style="text-align:center;"
 |-
-|  || Avg=83.43<br/> SD=1.38 || Avg=63<br/> SD=1.23 || Avg=41.86<br/> SD=0.96
+|  || Avg=83.43<br/> SD=6.399 || Avg=63<br/> SD=30.333 || Avg=41.86<br/> SD=9.476
 |-
 ! Project !! Judge A !! Judge B !! Judge C

← Older revision		Revision as of 15:56, 24 March 2022
Line 8:		Line 8:

	== Adjusted Score ==		== Adjusted Score ==
−	: This score is similar to a z-score but is calculated ~~differently~~. It ~~does normalize~~ the ~~data~~ so that any one judge doesn't have more sway than other judges.	+	: This score is similar to a z-score but is calculated to output a score out of 100. It is a normalized score, the same as with the z-score, so that any one judge doesn't have more sway than other judges on the end average score for a given project.

← Older revision		Revision as of 18:47, 30 January 2021
Line 10:		Line 10:
	: This score is similar to a z-score but is calculated differently. It does normalize the data so that any one judge doesn't have more sway than other judges.		: This score is similar to a z-score but is calculated differently. It does normalize the data so that any one judge doesn't have more sway than other judges.

		+
		+	=== Normalization ===
		+	* This helps equalize how judges score
		+	# All the scores from the judges that are part of the set of projects(sample) are gathered
		+	# The average score of each judge is found
		+	# We calculate the mean score given by the judges
		+	# We then determine the standard deviation of the sample
		+	# We calculate the z-score for each judge
		+	# We then adjust each judge's scores by the [-1 * (z-score * standard deviation)]
		+	# We then calculate the average score of each project
		+	# The project with the highest average score is the winner
		+
		+	=== How a Judges Score is calculated ===
		+	# Each Category is Weighted
		+	#* We sum the total possible value of a category
		+	#* We sum the total earned value of a category
		+	#* Each category is scored by: (total_earned/possible_value * category_weight)
		+	# Total Score is the Sum of the category score

	== Raw Score ==		== Raw Score ==

← Older revision		Revision as of 23:08, 6 January 2021
Line 8:		Line 8:

	== Adjusted Score ==		== Adjusted Score ==
−	: This score..~~. (Please update me)~~	+	: This score is similar to a z-score but is calculated differently. It does normalize the data so that any one judge doesn't have more sway than other judges.

@@ Line 15: / Line 15: @@
 == z-Score ==
-: This is a normalized score that takes into account all of the scores assigned by a given judge for a single round, normalizes them and returns a score based on the deviation from the standard for the score applied to the project.
+: This is a normalized score that takes into account all of the scores assigned by a given judge for a single round. It does this by taking each raw score it then normalizes them and returns a score based on the average and the standard deviation.
 :{|
@@ Line 24: / Line 24: @@
 : What that translates to for zFairs is:
 :: In a given round a judge assigns scores to projects. Those scores are evaluated and an Avg & SD (Standard Deviation) value are calculated. Those values are plugged in to the formula as seen above and each raw score from that judge is then normalized to a value representing how different from their standard score it is. Values that are negative are below the average score for the judge and values that are positive are above the judge's average score.
-:: The end result and take away is that the z-score adjusts for the fact that some judges score higher in general whereas others score lower for the same effort and quality of project. Teams and Projects are then less affected by luck of the draw in regards to the judges they have assigned to judge them.
+:: The end result is that the z-score adjusts for the fact that some judges score higher in general whereas others score lower for the same effort and quality of project. Teams and Projects are then less affected by luck of the draw in regards to the judges they have assigned to judge them.
 : An Example of this would be:
@@ Line 30: / Line 30: @@
 :: Judge B judges the same 7 projects and assigns the following scores out of 100: 61, 59, 63, 70, 67, 54 and 67
 :: Judge C judges the same 7 projects and assigns the following scores out of 100: 44, 37, 45, 42, 39, 41 and 45
-:: The mean / average for Judge A is 83.43 <small>(rounded up to two decimal places for convenience)</small>
+:: The mean / average for Judge A is 83.43
-:: The mean / average for Judge B is 63 <small>(this was not rounded nor was it planned but it is convenient)</small>
+:: The mean / average for Judge B is 63
-:: The mean / average for Judge C is 41.86 <small>(rounded up to two decimal places for convenience)</small>
+:: The mean / average for Judge C is 41.86
 :: So for Judge A, B and C we calculate the z-scores as follows:
-:::{|
+::{| class="wikitable" style="text-align:center;"
 |-
 ! Project !! Judge A !! Judge B !! Judge C
 |-
+|
@@ Line 49: / Line 49: @@
+#
+|
-(87-83.43)/1.38 = +2.59
++2.59 <br/>
-(74-83.43)/1.38 = -6.83
+-6.83 <br/>
-(91-83.43)/1.38 = +5.49
++5.49 <br/>
-(83-83.43)/1.38 = -0.31
+-0.31 <br/>
-(77-83.43)/1.38 = -4.66
+-4.66 <br/>
-(82-83.43)/1.38 = -1.04
+-1.04 <br/>
-(90-83.43)/1.38 = +4.76
++4.76
+|
- (61-63)/1.23 = -1.63
+-1.63 <br/>
- (59-63)/1.23 = -3.25
+-3.25 <br/>
- (63-63)/1.23 = 0.00
+.00 <br/>
- (70-63)/1.23 = +5.69
++5.69 <br/>
- (67-63)/1.23 = +3.25
++3.25 <br/>
- (54-63)/1.23 = -7.32
+-7.32 <br/>
- (67-63)/1.23 = +3.25
++3.25
+|
-(44-41.86)/0.96 = +2.23
++2.23 <br/>
-(37-41.86)/0.96 = -5.06
+-5.06 <br/>
-(45-41.86)/0.96 = +3.27
++3.27 <br/>
-(42-41.86)/0.96 = +0.15
++0.15 <br/>
-(39-41.86)/0.96 = -2.98
+-2.98 <br/>
-(41-41.86)/0.96 = -0.90
+-0.90 <br/>
-(45-41.86)/0.96 = +3.27
++3.27
 |}
 |}
@@ Line 77: / Line 77: @@
 : Some helpful articles for reading on better understanding z-score values:
-:* [https://en.wikipedia.org/wiki/Standard_score]
+:* https://en.wikipedia.org/wiki/Standard_score
-:* [https://www.statisticshowto.com/probability-and-statistics/z-score/]
+:* https://www.statisticshowto.com/probability-and-statistics/z-score/
-:* [https://www.simplypsychology.org/z-score.html]
+:* https://www.simplypsychology.org/z-score.html