StatsJam - Recent changes [en]

Notes on Data Analysis

2010-09-09T17:58:47Z

←Older revision		Revision as of 17:58, 9 September 2010
Line 6:		Line 6:
	* Use an external editor to format your wiki text and queries. They are unwieldy in browser text editors		* Use an external editor to format your wiki text and queries. They are unwieldy in browser text editors
	* Watch your use of "median". Median is supplied by R, not the DB, and can be really, really slow for thousands of data points		* Watch your use of "median". Median is supplied by R, not the DB, and can be really, really slow for thousands of data points
-	* Include an "n" (number of data points) ~~and standard deviation for any analysis that calculates a mean or median~~. ~~These are~~ good form and also good sanity ~~checks~~ to make sure you got the query right	+	* Include an "n" (number of data points). It's good form and also a good sanity check to make sure you got the query right
	* Discussion sections seem to be useful for discussing the implications of the data		* Discussion sections seem to be useful for discussing the implications of the data
	[[User:Mterry\|Mterry]] 23:21, 9 May 2008 (UTC)		[[User:Mterry\|Mterry]] 23:21, 9 May 2008 (UTC)

Activity Tags

2010-09-09T17:57:58Z

←Older revision		Revision as of 17:57, 9 September 2010
Line 59:		Line 59:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_tags_per_user)) AS "Mean",~~
	MEDIAN(num_tags_per_user) AS "Median",		MEDIAN(num_tags_per_user) AS "Median",
-	~~ROUND(STDDEV(num_tags_per_user)) AS "SD",~~
	MIN(num_tags_per_user) AS "Min",		MIN(num_tags_per_user) AS "Min",
	MAX(num_tags_per_user) AS "Max",		MAX(num_tags_per_user) AS "Max",

Describing Images

2010-09-09T17:55:27Z

←Older revision		Revision as of 17:55, 9 September 2010
Line 42:		Line 42:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_images)) AS "Mean",~~
	ROUND(MEDIAN(num_images)) AS "Median",		ROUND(MEDIAN(num_images)) AS "Median",
-	~~ROUND(STDDEV(num_images)) AS "SD",~~
	MIN(num_images) AS "Min",		MIN(num_images) AS "Min",
	MAX(num_images) AS "Max",		MAX(num_images) AS "Max",
Line 147:		Line 145:
	<query>		<query>
	SELECT		SELECT
-	~~mean_width AS "Mean Width",~~
	median_width AS "Median Width",		median_width AS "Median Width",
-	~~sd_width AS "SD Width",~~
	min_width AS "Min Width",		min_width AS "Min Width",
	max_width AS "Max Width",		max_width AS "Max Width",
-	~~mean_height AS "Mean Height",~~
	median_height AS "Median Height",		median_height AS "Median Height",
-	~~sd_height AS "SD Height",~~
	min_height AS "Min Height",		min_height AS "Min Height",
	max_height AS "Max Height",		max_height AS "Max Height",
Line 160:		Line 154:
	FROM		FROM
	(SELECT		(SELECT
-	~~ROUND(AVG(width)) AS mean_width,~~
	ROUND(MEDIAN(width)) AS median_width,		ROUND(MEDIAN(width)) AS median_width,
-	~~ROUND(STDDEV(width)) AS sd_width,~~
	MIN(width) AS min_width,		MIN(width) AS min_width,
	MAX(width) AS max_width,		MAX(width) AS max_width,
Line 172:		Line 164:
	) AS width_summary_table,		) AS width_summary_table,
	(SELECT		(SELECT
-	~~ROUND(AVG(height)) AS mean_height,~~
	ROUND(MEDIAN(height)) AS median_height,		ROUND(MEDIAN(height)) AS median_height,
-	~~ROUND(STDDEV(height)) AS sd_height,~~
	MIN(height) AS min_height,		MIN(height) AS min_height,
	MAX(height) AS max_height,		MAX(height) AS max_height,
Line 191:		Line 181:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(median_width)) AS "Mean Median Width",~~
	ROUND(MEDIAN(median_width)) AS "Median Median Width",		ROUND(MEDIAN(median_width)) AS "Median Median Width",
-	~~ROUND(STDDEV(median_width)) AS "SD Median Width",~~
	ROUND(MIN(median_width)) AS "Min Median Width",		ROUND(MIN(median_width)) AS "Min Median Width",
	ROUND(MAX(median_width)) AS "Max Median Width",		ROUND(MAX(median_width)) AS "Max Median Width",
-	~~ROUND(AVG(median_height)) AS "Mean Median Height",~~
	ROUND(MEDIAN(median_height)) AS "Median Median Height",		ROUND(MEDIAN(median_height)) AS "Median Median Height",
-	~~ROUND(STDDEV(median_height)) AS "SD Median Height",~~
	ROUND(MIN(median_height)) AS "Min Median Height",		ROUND(MIN(median_height)) AS "Min Median Height",
	ROUND(MAX(median_height)) AS "Max Median Height",		ROUND(MAX(median_height)) AS "Max Median Height",
Line 336:		Line 322:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_layers)) AS "Mean",~~
	MEDIAN(num_layers) AS "Median",		MEDIAN(num_layers) AS "Median",
-	~~ROUND(STDDEV(num_layers)) AS "SD",~~
	MIN(num_layers) AS "Min",		MIN(num_layers) AS "Min",
	MAX(num_layers) AS "Max",		MAX(num_layers) AS "Max",
Line 354:		Line 338:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(max_layer_num)) AS "Mean",~~
	MEDIAN(max_layer_num) AS "Median",		MEDIAN(max_layer_num) AS "Median",
-	~~ROUND(STDDEV(max_layer_num)) AS "SD",~~
	MIN(max_layer_num) AS "Min",		MIN(max_layer_num) AS "Min",
	MAX(max_layer_num) AS "Max",		MAX(max_layer_num) AS "Max",
Line 394:		Line 376:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(mean_layers)) AS "Mean Mean Layers Per User",~~	+	ROUND(MEDIAN(median_layers)) AS "Median Median Layers Per User"
-	ROUND(MEDIAN~~(mean_layers)) AS "Median Mean Layers Per User",~~	+
-	~~ROUND(STDDEV(mean_layers)) AS "SD Mean Layers Per User",~~	+
-	~~ROUND(AVG~~(median_layers)) AS "~~Mean~~ Median ~~Layers Per User",~~	+
-	~~ROUND(MEDIAN(median_layers)) AS "Median Median Layers Per User",~~	+
-	~~ROUND(STDDEV(median_layers)) AS "SD~~ Median Layers Per User"	+
	FROM		FROM
	(SELECT		(SELECT
-	~~AVG(num_layers) AS mean_layers,~~
	MEDIAN(num_layers) AS median_layers,		MEDIAN(num_layers) AS median_layers,
	COUNT(num_layers) AS num_images		COUNT(num_layers) AS num_images
Line 419:		Line 395:

	= Image Data Discussion =		= Image Data Discussion =
-	Looking at the data above, we have data for over 11,000 images at the time of this writing. ingimp users have each worked on ~~61 images on average, with the~~ median number of images ~~being 21~~. Amongst these images, they typically have very few layers -- ~~an average of 3,~~ median of 1. Furthermore, they are typically less than 1000 pixels wide and heights less than 900 pixels. So people are not working on overly complex images, nor are they working on very large images (though there are some who do work on fairly large, complex images).	+	Looking at the data above, we have data for over 11,000 images at the time of this writing. ingimp users have each worked on a median number of 21 images. Amongst these images, they typically have very few layers -- a median of 1. Furthermore, they are typically less than 1000 pixels wide and heights less than 900 pixels. So people are not working on overly complex images, nor are they working on very large images (though there are some who do work on fairly large, complex images).

Command Counts in Sessions

2010-09-09T17:47:05Z

←Older revision		Revision as of 17:47, 9 September 2010
Line 68:		Line 68:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_commands)) AS "Mean Number of Commands",~~
	ROUND(MEDIAN(num_commands)) AS "Median Number of Commands",		ROUND(MEDIAN(num_commands)) AS "Median Number of Commands",
-	~~ROUND(STDDEV(num_commands)) AS "SD Number of Commands",~~
	COUNT(num_commands) AS "n"		COUNT(num_commands) AS "n"
	FROM		FROM
Line 92:		Line 90:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(per_user_cmd_mean)) AS "Mean Mean Commands/User",~~
-	~~ROUND(MEDIAN(per_user_cmd_mean)) AS "Mean Median Commands/User",~~
-	~~ROUND(AVG(per_user_cmd_median)) AS "Median Mean Commands/User",~~
	ROUND(MEDIAN(per_user_cmd_median)) AS "Median Median Commands/User",		ROUND(MEDIAN(per_user_cmd_median)) AS "Median Median Commands/User",
	COUNT(per_user_cmd_median) AS "n"		COUNT(per_user_cmd_median) AS "n"
	FROM		FROM
	(SELECT		(SELECT
-	~~AVG(num_commands) AS per_user_cmd_mean,~~
	MEDIAN(num_commands) AS per_user_cmd_median		MEDIAN(num_commands) AS per_user_cmd_median
	FROM		FROM
Line 121:		Line 115:
	<view type="table" caption="Summary Stats for Number of Commands Per User"/>		<view type="table" caption="Summary Stats for Number of Commands Per User"/>
	</statsjam>		</statsjam>
-	At the time of this writing, ~~the average user's average number of commands per session is 118;~~ the median number of median commands by users is 26. So users are typically applying somewhere ~~between~~ 26~~-118~~ operations on images. Note that these numbers include undo/redo. We can filter those commands out:	+	At the time of this writing, the median number of median commands by users is 26. So users are typically applying somewhere around 26 operations on images. Note that these numbers include undo/redo. We can filter those commands out:
	<statsjam>		<statsjam>
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(per_user_cmd_mean)) AS "Mean Mean",~~
-	~~ROUND(MEDIAN(per_user_cmd_mean)) AS "Mean Median",~~
-	~~ROUND(AVG(per_user_cmd_median)) AS "Median Mean",~~
	ROUND(MEDIAN(per_user_cmd_median)) AS "Median Median",		ROUND(MEDIAN(per_user_cmd_median)) AS "Median Median",
-	COUNT(~~per_user_cmd_mean~~) AS "n"	+	COUNT(per_user_cmd_median) AS "n"
	FROM		FROM
	(SELECT		(SELECT
-	~~AVG(num_commands) AS per_user_cmd_mean,~~
	MEDIAN(num_commands) AS per_user_cmd_median		MEDIAN(num_commands) AS per_user_cmd_median
	FROM		FROM
Line 154:		Line 144:
	<view type="table" caption="Summary Stats for Number of Commands Per User"/>		<view type="table" caption="Summary Stats for Number of Commands Per User"/>
	</statsjam>		</statsjam>
-	At the time of this writing, this changes the ~~average number of commands, per user, to 91, with a~~ median median of 14 commands per session. Note that these numbers are not removing the commands that were undone.	+	At the time of this writing, this changes the median median of commands per session to 14. Note that these numbers are not removing the commands that were undone.

	= Session Length Command Count Data Discussion =		= Session Length Command Count Data Discussion =
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	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_unique_cmds)) AS "Mean",~~
	ROUND(MEDIAN(num_unique_cmds)) AS "Median",		ROUND(MEDIAN(num_unique_cmds)) AS "Median",
-	~~ROUND(STDDEV(num_unique_cmds)) AS "SD",~~
-	~~MAX(num_unique_cmds) AS "Max",~~
	MIN(num_unique_cmds) AS "Min",		MIN(num_unique_cmds) AS "Min",
		+	MAX(num_unique_cmds) AS "Max",
	COUNT(num_unique_cmds) AS "n"		COUNT(num_unique_cmds) AS "n"
	FROM		FROM
Line 285:		Line 273:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_unique_cmds)) AS "Mean",~~
	ROUND(MEDIAN(num_unique_cmds)) AS "Median",		ROUND(MEDIAN(num_unique_cmds)) AS "Median",
-	~~ROUND(STDDEV(num_unique_cmds)) AS "SD",~~
-	~~MAX(num_unique_cmds) AS "Max",~~
	MIN(num_unique_cmds) AS "Min",		MIN(num_unique_cmds) AS "Min",
		+	MAX(num_unique_cmds) AS "Max",
	COUNT(num_unique_cmds) AS "n"		COUNT(num_unique_cmds) AS "n"
	FROM		FROM
Line 315:		Line 301:
	<view type="table" caption="Summary Stats for Number of Unique Commands Per User, Over All Sessions for the User"/>		<view type="table" caption="Summary Stats for Number of Unique Commands Per User, Over All Sessions for the User"/>
	</statsjam>		</statsjam>
-	From the above data, users have employed (or tried out) ~~an average of 41 different,~~ unique commands (~~with 32 commands~~ the median) ''over all recorded sessions''. Now let's consider the typical number of unique commands they employ in a ''single'' session.	+	From the above data, users have employed (or tried out) a 32 unique commands (the median) ''over all recorded sessions''. Now let's consider the typical number of unique commands they employ in a ''single'' session.
	<statsjam>		<statsjam>
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(mean_per_user)) AS "Mean Mean Per User",~~
-	~~ROUND(MEDIAN(mean_per_user)) AS "Median Mean Per User",~~
-	~~ROUND(STDDEV(mean_per_user)) AS "SD Mean Per User",~~
-	~~ROUND(AVG(median_per_user)) AS "Mean Median Per User",~~
	ROUND(MEDIAN(median_per_user)) AS "Median Median Per User",		ROUND(MEDIAN(median_per_user)) AS "Median Median Per User",
-	~~ROUND(STDDEV~~(median_per_user~~)) AS "SD Median Per User",~~	+	COUNT(median_per_user) AS "n"
-	~~COUNT(mean_per_user~~) AS "n"	+
	FROM		FROM
	(SELECT		(SELECT
-	~~AVG(num_unique_cmds) AS mean_per_user,~~
	MEDIAN(num_unique_cmds) AS median_per_user		MEDIAN(num_unique_cmds) AS median_per_user
	FROM		FROM

Main Page

2010-09-09T17:39:27Z

Data Analyses:

←Older revision		Revision as of 17:39, 9 September 2010
(One intermediate revision not shown.)
Line 1:		Line 1:
	__NOTOC__		__NOTOC__
	= Data Analyses =		= Data Analyses =
-	<b>Please note: Most of the analyses below are now superseded by our [http://hci.uwaterloo.ca/sites/default/files/gi2010_largescale.pdf Graphics Interface 2010 paper].~~</b>~~ Please refer to that for a more authoritative and complete analysis of the ingimp data.	+	<b>Please note: Most of the analyses below are now superseded by our [http://hci.uwaterloo.ca/sites/default/files/gi2010_largescale.pdf Graphics Interface 2010 paper]. Please refer to that for a more authoritative and complete analysis of the ingimp data.</b>
		+
		+	----

	At present, we have the following data analyses available. Feel free to add to them, comment on them, point out bugs and flaws in reasoning (yes, queries can most definitely have bugs). This is a ''community'' site for everyone to do data analysis (see Introduction below).		At present, we have the following data analyses available. Feel free to add to them, comment on them, point out bugs and flaws in reasoning (yes, queries can most definitely have bugs). This is a ''community'' site for everyone to do data analysis (see Introduction below).

Describing Sessions

2010-09-09T17:35:57Z

←Older revision		Revision as of 17:35, 9 September 2010
Line 38:		Line 38:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_logs)) AS "Mean Number of Logs Per User",~~
	ROUND(MEDIAN(num_logs)) AS "Median Number of Logs Per User",		ROUND(MEDIAN(num_logs)) AS "Median Number of Logs Per User",
-	~~ROUND(STDDEV(num_logs)) AS "SD Number of Logs Per User",~~
	ROUND(MIN(num_logs)) AS "Minimum Number of Logs Per User",		ROUND(MIN(num_logs)) AS "Minimum Number of Logs Per User",
	ROUND(MAX(num_logs)) AS "Maximum Number of Logs Per User",		ROUND(MAX(num_logs)) AS "Maximum Number of Logs Per User",
Line 63:		Line 61:
	<view type="table" caption="Summary Stats for Number of Sessions Per User"/>		<view type="table" caption="Summary Stats for Number of Sessions Per User"/>
	</statsjam>		</statsjam>
-	From the above data, we see that over 50% of the users have used ingimp 10 or more times~~, with the average number of uses being 18~~.	+	From the above data, we see that over 50% of the users have used ingimp 10 or more times.

	= Session Length, In Time =		= Session Length, In Time =
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	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(corrected_time_secs)/60.0) AS "Corrected Mean",~~
	ROUND(MEDIAN(corrected_time_secs)/60.0) AS "Corrected Median",		ROUND(MEDIAN(corrected_time_secs)/60.0) AS "Corrected Median",
-	~~ROUND(STDDEV(corrected_time_secs)/60.0) AS "Corrected SD",~~
	ROUND(MIN(corrected_time_secs)/60.0) AS "Corrected Minimum Time",		ROUND(MIN(corrected_time_secs)/60.0) AS "Corrected Minimum Time",
	ROUND(MAX(corrected_time_secs)/60.0) AS "Corrected Maximum Time",		ROUND(MAX(corrected_time_secs)/60.0) AS "Corrected Maximum Time",
-	~~ROUND(AVG(session_time_secs)/60.0) AS "Uncorrected Mean",~~
	ROUND(MEDIAN(session_time_secs)/60.0) AS "Uncorrected Median",		ROUND(MEDIAN(session_time_secs)/60.0) AS "Uncorrected Median",
-	~~ROUND(STDDEV(session_time_secs)/60.0) AS "Uncorrected SD",~~
	ROUND(MIN(session_time_secs)/60.0) AS "Uncorrected Minimum Time",		ROUND(MIN(session_time_secs)/60.0) AS "Uncorrected Minimum Time",
	ROUND(MAX(session_time_secs)/60.0) AS "Uncorrected Maximum Time",		ROUND(MAX(session_time_secs)/60.0) AS "Uncorrected Maximum Time",
-	~~ROUND(AVG(idle_time_secs)/60.0) AS "Idle Time Mean",~~
	ROUND(MEDIAN(idle_time_secs)/60.0) AS "Idle Time Median",		ROUND(MEDIAN(idle_time_secs)/60.0) AS "Idle Time Median",
-	~~ROUND(STDDEV(idle_time_secs)/60.0) AS "Idle Time SD",~~
	ROUND(MIN(idle_time_secs)/60.0) AS "Minimum Idle Time",		ROUND(MIN(idle_time_secs)/60.0) AS "Minimum Idle Time",
	ROUND(MAX(idle_time_secs)/60.0) AS "Maximum Idle Time",		ROUND(MAX(idle_time_secs)/60.0) AS "Maximum Idle Time",
Line 424:		Line 416:
	For completeness, we include uncorrected session length times and idle times.		For completeness, we include uncorrected session length times and idle times.

-	The results of this query indicate people do not use ingimp for long stretches of time. At the time of this writing, the ~~average~~ session length is ~~14 minutes, with a median of~~ 5 minutes. The uncorrected time ~~average~~ (that is, without idle time taken out) is ~~58 minutes with a median of~~ 9 minutes. So most sessions are rather short, in length. Let's look at these data on a per-user basis.	+	The results of this query indicate people do not use ingimp for long stretches of time. At the time of this writing, the median session length is 5 minutes. The uncorrected median for time (that is, without idle time taken out) is 9 minutes. So most sessions are rather short, in length. Let's look at these data on a per-user basis.
	<statsjam>		<statsjam>
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(corrected_user_mean)) AS "Mean Mean Corrected Time",~~
-	~~ROUND(MEDIAN(corrected_user_mean)) AS "Median Mean Corrected Time",~~
-	~~ROUND(STDDEV(corrected_user_mean)) AS "SD Mean Corrected Time",~~
-	~~ROUND(AVG(corrected_user_median)) AS "Mean Median Corrected Time",~~
	ROUND(MEDIAN(corrected_user_median)) AS "Median Median Corrected Time",		ROUND(MEDIAN(corrected_user_median)) AS "Median Median Corrected Time",
-	~~ROUND(STDDEV~~(corrected_user_median~~)) AS "SD Median Corrected Time",~~	+	COUNT(corrected_user_median) AS "n"
-	~~COUNT(corrected_user_mean~~) AS "n"	+
	FROM		FROM
	(SELECT		(SELECT
-	~~AVG(corrected_time_secs)/60.0 AS corrected_user_mean,~~	+	MEDIAN(corrected_time_secs)/60.0 AS corrected_user_median
-	MEDIAN(corrected_time_secs)/60.0 AS corrected_user_median,	+
-	~~AVG(session_time_secs)/60.0 AS uncorrected_user_mean,~~	+
-	~~MEDIAN(session_time_secs)/60.0 AS uncorrected_user_median,~~	+
-	~~AVG(idle_time_secs)/60.0 AS user_idle_time_mean,~~	+
-	~~MEDIAN(idle_time_secs)/60.0 AS user_idle_time_median~~	+
	FROM		FROM
	interaction_log,		interaction_log,
Line 502:		Line 484:
	<view type="table" caption="Summary Stats for Session Length, in Minutes, Across Users"/>		<view type="table" caption="Summary Stats for Session Length, in Minutes, Across Users"/>
	</statsjam>		</statsjam>
-	In aggregating across all users, we need to first summarize on a ''per-user basis''. The query above performs these summaries on ~~average times per user and~~ median times per user. That is, we'll take the mean and median time of each user's individual mean and median times.	+	In aggregating across all users, we need to first summarize on a ''per-user basis''. The query above performs these summaries on median times per user. That is, we'll take the mean and median time of each user's individual mean and median times.

	These summaries show that the mean mean session length across users is 14 minutes. The median median time is 5 minutes. Again, these data show rather short session lengths across all users.		These summaries show that the mean mean session length across users is 14 minutes. The median median time is 5 minutes. Again, these data show rather short session lengths across all users.

	== Session Length (Time) Data Discussion ==		== Session Length (Time) Data Discussion ==
-	At the time of this writing, ~~average session lengths are less than 15 minutes long across all logs, with~~ median median times across users 5 ~~minutes. These data indicate that a user's typical session lies somewhere between 5 and 15~~ minutes, suggesting ~~inimp~~ is~~, on average,~~ being used for rather small tasks.	+	At the time of this writing, median median times across users is 5 minutes, suggesting ingimp is being used for rather small tasks.

	= Image Summaries =		= Image Summaries =
Line 609:		Line 591:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_images)) AS "Mean Number of Images",~~
	ROUND(MEDIAN(num_images)) AS "Median Number of Images",		ROUND(MEDIAN(num_images)) AS "Median Number of Images",
-	~~ROUND(STDDEV(num_images)) AS "SD Number of Images",~~
	COUNT(num_images) AS "n"		COUNT(num_images) AS "n"
	FROM		FROM
Line 640:		Line 620:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(mean_images_per_user)) AS "Mean Mean Number of Images",~~
-	~~ROUND(MEDIAN(mean_images_per_user)) AS "Median Mean Number of Images",~~
-	~~ROUND(STDDEV(mean_images_per_user)) AS "SD Mean Number of Images",~~
-	~~ROUND(AVG(median_images_per_user)) AS "Mean Median Number of Images",~~
	ROUND(MEDIAN(median_images_per_user)) AS "Median Median Number of Images",		ROUND(MEDIAN(median_images_per_user)) AS "Median Median Number of Images",
-	~~ROUND(STDDEV~~(median_images_per_user~~)) AS "SD Median Number of Images",~~	+	COUNT(median_images_per_user) AS "n"
-	~~COUNT(mean_images_per_user~~) AS "n"	+
	FROM		FROM
	(SELECT		(SELECT
-	~~AVG(num_images) AS mean_images_per_user,~~
	MEDIAN(num_images) AS median_images_per_user		MEDIAN(num_images) AS median_images_per_user
	FROM		FROM

Defining Significant Users

2010-09-09T17:27:11Z

←Older revision		Revision as of 17:27, 9 September 2010
Line 128:		Line 128:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_doc_events)) AS "Mean",~~	+	ROUND(MEDIAN(num_doc_events)) AS "Median"
-	ROUND(MEDIAN(num_doc_events)) AS "Median",	+
-	~~ROUND(STDDEV(num_doc_events)) AS "Std Dev~~"	+
	FROM		FROM
	((SELECT		((SELECT
Line 198:		Line 196:
	<query>		<query>
	SELECT		SELECT
-	~~ROUND(AVG(num_doc_events)) AS "Mean",~~	+	ROUND(MEDIAN(num_doc_events)) AS "Median"
-	ROUND(MEDIAN(num_doc_events)) AS "Median",	+
-	~~ROUND(STDDEV(num_doc_events)) AS "Std Dev~~"	+
	FROM		FROM
	((SELECT		((SELECT
Line 336:		Line 332:
	<view type="table"/>		<view type="table"/>
	</statsjam>		</statsjam>
-	Using this filter, approximately 27% of the ingimp installations meet these criteria.	+	Using this filter, approximately 25% of the ingimp installations meet these criteria.

	Now let's see how many log files these users are responsible for:		Now let's see how many log files these users are responsible for:

Main Page

2010-09-09T17:23:05Z

←Older revision		Revision as of 17:23, 9 September 2010
(One intermediate revision not shown.)
Line 1:		Line 1:
	__NOTOC__		__NOTOC__
	= Data Analyses =		= Data Analyses =
		+	<b>Please note: Most of the analyses below are now superseded by our [http://hci.uwaterloo.ca/sites/default/files/gi2010_largescale.pdf Graphics Interface 2010 paper].</b> Please refer to that for a more authoritative and complete analysis of the ingimp data.
		+
	At present, we have the following data analyses available. Feel free to add to them, comment on them, point out bugs and flaws in reasoning (yes, queries can most definitely have bugs). This is a ''community'' site for everyone to do data analysis (see Introduction below).		At present, we have the following data analyses available. Feel free to add to them, comment on them, point out bugs and flaws in reasoning (yes, queries can most definitely have bugs). This is a ''community'' site for everyone to do data analysis (see Introduction below).