Merge pull request #1 from fivethirtyeight/master

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thecloudist · Oct 25, 2016 · 559833b · 559833b
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diff --git a/README.md b/README.md
@@ -4,6 +4,9 @@ We hope you'll use it to check our work and to create stories and visualizations
 
 Article Date(s) | Headline(s) | Folder
 ---|---------|-------------
+Oct. 6, 2016 | [A Handful Of Cities Are Driving 2016’s Rise In Murders](http://fivethirtyeight.com/features/a-handful-of-cities-are-driving-2016s-rise-in-murders/) | `murder_2016`
+Sept. 16, 2016 | [When Does Praying In Public Make Others Uncomfortable?](http://fivethirtyeight.com/features/when-does-praying-in-public-make-others-uncomfortable/) | `religion-survey`
+Sept. 8, 2016 | [The Rams Are Dead To Me, So I Answered 3,352 Questions To Find A New NFL Team](http://fivethirtyeight.com/features/the-rams-are-dead-to-me-so-i-answered-3352-questions-to-find-a-new-team/) | `nfl-favorite-team`
 July 14, 2016 | [Hip-Hop Is Turning On Donald Trump](http://projects.fivethirtyeight.com/clinton-trump-hip-hop-lyrics/) | `hip-hop-candidate-lyrics`
 June 2, 2016 | [FiveThirtyEight's Pollster Ratings](http://projects.fivethirtyeight.com/pollster-ratings/) | `pollster-ratings`
 May 13, 2016 | [Some People Are Too Superstitious To Have A Baby On Friday The 13th](http://fivethirtyeight.com/features/some-people-are-too-superstitious-to-have-a-baby-on-friday-the-13th/) | `births`

diff --git a/murder_2016/README.md b/murder_2016/README.md
@@ -0,0 +1,9 @@
+### 2016 murder data
+
+The raw data behind the story [A Handful Of Cities Are Driving 2016's Rise In Murder](http://fivethirtyeight.com/features/a-handful-of-cities-are-driving-2016s-rise-in-murders/)
+
+There are two files:
+
+`murder_2016_prelim.csv` contains preliminary 2016 murder counts for 79 large U.S. cities. 2015 figures are counts through the same data a year ago. Sources are listed in the file.
+
+`murder_2015_final.csv` contains full-year 2014 and 2015 murder counts for all U.S. cities with at least 250,000 residents. Source is FBI Uniform Crime Reports.
diff --git a/murder_2016/murder_2015_final.csv b/murder_2016/murder_2015_final.csv
@@ -0,0 +1,84 @@
+city,state,2014_murders,2015_murders,change
+Baltimore,Maryland,211,344,133
+Chicago,Illinois,411,478,67
+Houston,Texas,242,303,61
+Cleveland,Ohio,63,120,57
+Washington,D.C.,105,162,57
+Milwaukee,Wisconsin,90,145,55
+Philadelphia,Pennsylvania,248,280,32
+Kansas City,Missouri,78,109,31
+Nashville,Tennessee,41,72,31
+St. Louis,Missouri,159,188,29
+Oklahoma City,Oklahoma,45,73,28
+Louisville,Kentucky,56,81,25
+Denver,Colorado,31,53,22
+Los Angeles,California,260,282,22
+Dallas,Texas,116,136,20
+New York,New York,333,352,19
+Orlando,Florida,15,32,17
+Minneapolis,Minnesota,31,47,16
+Omaha,Nebraska,32,48,16
+Sacramento,California,28,43,15
+Anchorage,Alaska,12,26,14
+Charlotte-Mecklenburg,North Carolina,47,61,14
+New Orleans,Louisiana,150,164,14
+Albuquerque,New Mexico,30,43,13
+Aurora,Colorado,11,24,13
+Fort Wayne,Indiana,12,25,13
+Long Beach,California,23,36,13
+Durham,North Carolina,21,34,13
+Indianapolis,Indiana,136,148,12
+Newark,New Jersey,93,104,11
+Tulsa,Oklahoma,46,55,9
+Portland,Oregon,26,34,8
+San Francisco,California,45,53,8
+Cincinnati,Ohio,60,66,6
+Tampa,Florida,28,34,6
+Bakersfield,California,17,22,5
+Colorado Springs,Colorado,20,25,5
+Las Vegas,Nevada,122,127,5
+Oakland,California,80,85,5
+San Diego,California,32,37,5
+St. Paul,Minnesota,11,16,5
+Anaheim,California,14,18,4
+Greensboro,North Carolina,23,26,3
+Jersey City,New Jersey,24,27,3
+Mesa,Arizona,13,16,3
+Fort Worth,Texas,54,56,2
+Virginia Beach,Virginia,17,19,2
+Irvine,California,0,2,2
+Atlanta,Georgia,93,94,1
+Henderson,Nevada,3,4,1
+Jacksonville,Florida,96,97,1
+Raleigh,North Carolina,16,17,1
+Wichita,Kansas,26,27,1
+Chandler,Arizona,1,1,0
+Plano,Texas,4,4,0
+Stockton,California,49,49,0
+Toledo,Ohio,24,24,0
+Chula Vista,California,7,6,-1
+Phoenix,Arizona,114,112,-2
+Riverside,California,12,10,-2
+San Jose,California,32,30,-2
+Detroit,Michigan,298,295,-3
+Seattle,Washington,26,23,-3
+El Paso,Texas,21,17,-4
+Tucson,Arizona,35,31,-4
+Arlington,Texas,13,8,-5
+Lexington,Kentucky,20,15,-5
+Memphis,Tennessee,140,135,-5
+St. Petersburg,Florida,19,14,-5
+Columbus,Ohio,83,77,-6
+Honolulu,Hawaii,21,15,-6
+Laredo,Texas,14,8,-6
+Lincoln,Nebraska,7,1,-6
+Miami,Florida,81,75,-6
+Santa Ana,California,18,12,-6
+Mobile,Alabama,31,24,-7
+Fresno,California,47,39,-8
+Austin,Texas,32,23,-9
+San Antonio,Texas,103,94,-9
+Corpus Christi,Texas,27,17,-10
+Pittsburgh,Pennsylvania,69,57,-12
+Boston,Massachusetts,53,38,-15
+Buffalo,New York,60,41,-19
diff --git a/murder_2016/murder_2016_prelim.csv b/murder_2016/murder_2016_prelim.csv
@@ -0,0 +1,80 @@
+city,state,2015_murders,2016_murders,change,source,as_of
+Chicago,Illinois,378,536,158,https://portal.chicagopolice.org/portal/page/portal/ClearPath/News/Crime%20Statistics,10/2/2016
+Orlando,Florida,19,73,54,OPD ,9/22/2016
+Memphis,Tennessee,114,158,44,MPD,9/11/2016
+Phoenix,Arizona,72,111,39,PPD ,8/31/2016
+Las Vegas,Nevada,90,125,35,http://www.lvmpd.com/Sections/Homicide/HomicideLog/tabid/454/Default.aspx,9/28/2016
+San Antonio,Texas,78,111,33,SAPD ,9/26/2016
+Louisville,Kentucky,52,79,27,https://louisvilleky.gov/government/police/lmpd-transparency,8/31/2016
+Dallas,Texas,95,118,23,DPD,8/31/2016
+Houston,Texas,191,212,21,http://www.houstontx.gov/police/cs/index-2.htm,8/31/2016
+Fort Wayne,Indiana,17,34,17,FWPD ,9/26/2016
+Atlanta,Georgia,68,85,17,http://www.atlantapd.org/crimedatadownloads.aspx,9/24/2016
+Indianapolis,Indiana,102,117,15,IPD ,10/2/2016
+Austin,Texas,13,28,15,http://www.austintexas.gov/page/chiefs-monthly-reports,8/31/2016
+Kansas City,Missouri,77,90,13,http://kcmo.gov/police/homicide-3/crime-stats/,10/4/2016
+Arlington,Texas,4,17,13,http://www.arlington-tx.gov/police/wp-content/uploads/sites/9/2016/08/UCR-Crime-Summary.pdf,8/31/2016
+San Jose,California,22,35,13,http://www.sjpd.org/CrimeStats/updates/Part_One_Crimes_Reported_YTD.pdf?cacheID=20160921,8/31/2016
+Albuquerque,New Mexico,35,46,11,APD ,9/21/2016
+Jacksonville,Florida,67,78,11,JPSO ,9/21/2016
+Santa Ana,California,10,20,10,SAPD ,9/21/2016
+Tulsa,Oklahoma,43,52,9,TPD ,9/27/2016
+Lincoln,Nebraska,0,9,9,http://www.lincoln.ne.gov/city/police/stats/stats.htm,8/31/2016
+Stockton,California,30,38,8,SPD ,9/21/2016
+Anchorage,Alaska,19,26,7,APD ,9/27/2016
+Buffalo,New York,31,38,7,http://www.bpdny.org/Home/Statistics,9/24/2016
+San Diego,California,23,30,7,http://crimestats.arjis.org/default.aspx,8/31/2016
+Mobile,Alabama,6,12,6,https://www.mobilepd.org/precinct/pdf/UCR_April_Public.pdf,4/30/2016
+Greensboro,North Carolina,15,20,5,http://www.greensboro-nc.gov/modules/showdocument.aspx?documentid=29678,10/2/2016
+Durham,North Carolina,25,30,5,https://durhamnc.gov/ArchiveCenter/ViewFile/Item/2419,10/1/2016
+Detroit,Michigan,216,221,5,DPD ,9/25/2016
+St. Petersburg,Florida,9,14,5,SPPD ,8/31/2016
+Philadelphia,Pennsylvania,209,213,4,https://www.phillypolice.com/crime-maps-stats/,10/4/2016
+Long Beach,California,25,29,4,http://homicide.latimes.com/neighborhood/long-beach/year/2016,9/20/2016
+Lexington,Kentucky,13,16,3,LPD ,9/28/2016
+Aurora,Colorado,13,16,3,APD ,9/21/2016
+Jersey City,New Jersey,11,14,3,http://www.njjcpd.org/node/5,8/31/2016
+Plano,Texas,2,5,3,http://www.plano.gov/DocumentCenter/View/119,8/31/2016
+Colorado Springs,Colorado,12,15,3,http://www.krdo.com/news/local-news/springs-womans-shooting-death-ruled-homicide-/73436432,8/2/2016
+Toledo,Ohio,5,8,3,TPD ,6/24/2016
+El Paso,Texas,12,14,2,ELPD ,9/21/2016
+Laredo,Texas,7,9,2,LPD ,9/21/2016
+Nashville,Tennessee,47,49,2,NPD ,9/21/2016
+Oklahoma City,Oklahoma,28,30,2,OKCPD ,6/30/2016
+Henderson,Nevada,1,3,2,HPD ,4/30/2016
+Chandler,Arizona,2,3,1,CPD ,9/21/2016
+Denver,Colorado,32,33,1,https://www.denvergov.org/content/dam/denvergov/Portals/720/documents/statistics/2016/UCR_Citywide_Reported_Offenses_2016.pdf,8/31/2016
+Riverside,California,6,7,1,http://www.riversideca.gov/rpd/crstats/cstats.asp,8/31/2016
+Bakersfield,California,21,22,1,BPD ,6/23/2016
+Boston,Massachusetts,28,28,0,BPD ,9/27/2016
+Cincinnati,Ohio,50,50,0,http://www.cincinnati-oh.gov/police/crime-statistics/city-wide-stars-report/,9/24/2016
+Pittsburgh,Pennsylvania,46,46,0,PPD ,9/21/2016
+Columbus,Ohio,71,70,-1,CPD ,9/24/2016
+Raleigh,North Carolina,8,7,-1,RPD ,7/17/2016
+Corpus Christi,Texas,10,9,-1,CCPD ,6/24/2016
+Charlotte-Mecklenburg,North Carolina,27,25,-2,http://charlottenc.gov/CMPD/Safety/Pages/CrimeStats.aspx,6/30/2016
+New Orleans,Louisiana,130,127,-3,NOPD ,9/27/2016
+San Francisco,California,35,32,-3,SFPD ,9/27/2016
+Seattle,Washington,17,14,-3,http://www.seattle.gov/seattle-police-department/crime-data/crime-dashboard,8/31/2016
+St. Louis,Missouri,136,133,-3,http://www.slmpd.org/crime_stats.shtml,8/31/2016
+Honolulu,Hawaii,12,9,-3,HPD ,6/30/2016
+Wichita,Kansas,13,10,-3,MCCA,6/30/2016
+Virginia Beach,Virginia,17,13,-4,https://eprodmz.vbgov.com/MainUI/Crimes/CrimeSearch.aspx,9/30/2016
+Newark,New Jersey,76,72,-4,http://npd.newarkpublicsafety.org/comstat,9/25/2016
+Los Angeles,California,209,205,-4,http://assets.lapdonline.org/assets/pdf/cityprof.pdf,9/17/2016
+Chula Vista,California,5,1,-4,http://crimestats.arjis.org/default.aspx,8/31/2016
+Portland,Oregon,19,14,-5,PPD ,9/21/2016
+Tucson,Arizona,23,18,-5,TPD ,9/21/2016
+Anaheim,California,10,4,-6,APD ,6/27/2016
+Cleveland,Ohio,96,89,-7,CPD ,9/26/2016
+Minneapolis,Minnesota,34,26,-8,http://www.minneapolismn.gov/police/statistics/crime-statistics_codefor_arrests,10/3/2016
+Sacramento,California,31,21,-10,SPD ,9/22/2016
+Fresno,California,30,19,-11,http://www.fresno.gov/CityOfFresno/Templates/StandardTemplate.aspx?NRMODE=Published&NRNODEGUID=%7bA9D853FB-EBA4-4900-8435-B880D98AE480%7d&NRORIGINALURL=%2fGovernment%2fDepartmentDirectory%2fPolice%2fAboutFresnoPD%2fCrimeReportsandStatistics%2fMonthlyCrimeStatistics%2ehtm&NRCACHEHINT=Guest,7/31/2016
+Fort Worth,Texas,61,49,-12,FWPD ,9/27/2016
+Oakland,California,65,52,-13,http://www2.oaklandnet.com/government/o/OPD/s/Statistics/index.htm,10/2/2016
+Washington,D.C.,119,105,-14,http://mpdc.dc.gov/page/district-crime-data-glance,9/30/2016
+New York,New York,266,252,-14,https://compstat.nypdonline.org/,9/25/2016
+Omaha,Nebraska,34,20,-14,http://dataomaha.com/homicides,9/5/2016
+Miami,Florida,62,45,-17,MPD ,9/21/2016
+Baltimore,Maryland,249,230,-19,https://data.baltimorecity.gov/Public-Safety/Summarized-Crime-Data-By-District-Week-26/4nh3-w6zf,10/1/2016
+Milwaukee,Wisconsin,105,84,-21,http://itmdapps.milwaukee.gov/publicApplication_SR/policeDistrict/policeDistrictfm.faces,9/28/2016
diff --git a/nfl-favorite-team/README.md b/nfl-favorite-team/README.md
@@ -0,0 +1,29 @@
+
+The data behind the story [The Rams Are Dead To Me, So I Answered 3,352 Questions To Find A New NFL Team](http://fivethirtyeight.com/features/the-rams-are-dead-to-me-so-i-answered-3352-questions-to-find-a-new-team/).
+
+Contains grades for each NFL franchise in 16 categories, to be used to pick a new favorite team.
+
+Key for categories:
+
+| abbrev |                                                           category                                                            |
+|--------|-------------------------------------------------------------------------------------------------------------------------------|
+| FRL    | Fan relations - Courtesy by players, coaches and front offices toward fans, and how well a team uses technology to reach them |
+| OWN    | Ownership - Honesty; loyalty to core players and the community                                                                |
+| PLA    | Players - Effort on the field, likability off it                                                                              |
+| FUT    | Future wins - Projected wins over next 5 seasons                                                                              |
+| BWG    | Bandwagon Factor - Are the team's next 5 years likely to be better than their previous 5?                                     |
+| TRD    | Tradition - Championships/division titles/wins in team's entire history                                                       |
+| BNG    | Bang for the buck - Wins per fan dollars spent                                                                                |
+| BEH    | Behavior - Suspensions by players on team since 2007, with extra weight to transgressions vs. women                           |
+| NYP    | Proximity to New York City                                                                                                    |
+| SLP    | Proximity to St. Louis                                                                                                        |
+| AFF    | Affordability - Price of tickets, parking and concessions                                                                     |
+| SMK    | Small Market - Size of market in terms of population, where smaller is better                                                 |
+| STX    | Stadium experience - Quality of venue; fan-friendliness of environment; frequency of game-day promotions                      |
+| CCH    | Coaching - Strength of on-field leadership                                                                                    |
+| UNI    | Uniform - Stylishness of uniform design, according to Uni Watch's Paul Lukas                                                  |
+| BMK    | Big Market - Size of market in terms of population, where bigger is better                                                    |
+
+
+
+Should be used in conjunction with weights derived from a survey structured like this: http://www.allourideas.org/nflteampickingsample.
diff --git a/nfl-favorite-team/team-picking-categories.csv b/nfl-favorite-team/team-picking-categories.csv
@@ -0,0 +1,33 @@
+TEAM,BMK,UNI,CCH,STX,SMK,AFF,SLP,NYP,FRL,BNG,TRD,BWG,FUT,PLA,OWN,BEH
+Green Bay Packers,0,94,81,100,100,94,84,52,100,81,100,6,77,97,100,69
+Pittsburgh Steelers,32,100,65,58,68,74,68,77,84,42,90,29,81,84,97,69
+Kansas City Chiefs,26,71,84,84,74,71,97,35,71,48,45,77,94,71,87,44
+New England Patriots,68,68,100,68,32,26,23,90,90,84,81,0,87,94,65,77
+Buffalo Bills,3,81,58,32,97,97,55,81,55,61,48,74,68,58,77,69
+Carolina Panthers,35,16,52,61,65,84,61,68,74,90,6,52,90,77,74,44
+Seattle Seahawks,58,35,95,90,42,23,6,13,97,100,35,26,100,100,94,29
+Indianapolis Colts,19,74,68,97,81,77,100,61,94,94,71,23,26,87,48,16
+Arizona Cardinals,65,6,95,87,35,90,16,16,77,68,29,42,84,81,71,56
+Baltimore Ravens,39,29,90,81,61,81,45,87,68,74,26,19,42,90,90,6
+Houston Texans,87,32,55,71,13,48,52,23,81,35,0,39,61,74,68,95
+New Orleans Saints,6,45,87,74,94,87,58,29,87,45,16,16,23,65,61,84
+Philadelphia Eagles,81,77,71,52,19,29,35,94,52,26,55,55,45,55,39,95
+Denver Broncos,42,23,45,65,58,45,39,19,61,97,68,10,97,68,81,0
+Detroit Lions,61,19,35,45,39,39,81,71,32,58,42,61,58,35,42,84
+Minnesota Vikings,55,52,74,35,45,52,77,39,39,29,52,81,74,52,45,44
+New York Giants,100,65,77,42,0,13,29,100,48,23,97,58,39,48,84,10
+Atlanta Falcons,74,13,48,48,26,61,74,55,58,55,10,35,48,42,58,56
+Dallas Cowboys,90,84,42,77,10,16,65,26,45,77,87,32,29,61,52,29
+Jacksonville Jaguars,13,0,61,94,87,100,42,45,65,3,3,100,6,45,55,29
+Miami Dolphins,77,48,6,29,23,35,19,32,29,71,58,65,32,16,32,95
+Cincinnati Bengals,29,3,13,19,71,58,87,65,26,87,23,13,71,32,29,29
+Oakland Raiders,10,97,32,3,90,65,0,0,42,0,65,94,35,19,19,69
+Tampa Bay Buccaneers,45,10,29,55,55,68,32,42,35,13,13,97,13,23,35,44
+Los Angeles Rams,97,42,39,6,3,55,10,6,6,39,61,90,65,29,0,56
+Chicago Bears,94,90,26,16,6,6,90,58,13,19,94,48,19,0,26,56
+Cleveland Browns,23,39,16,26,77,42,71,74,10,32,77,87,3,10,10,16
+San Diego Chargers,52,87,19,0,48,19,13,10,23,52,39,45,16,39,3,84
+San Francisco 49ers,48,61,0,39,52,10,3,3,3,65,84,3,10,26,6,95
+New York Jets,71,58,23,23,29,3,29,100,16,10,19,68,52,13,23,16
+Washington Redskins,84,26,3,10,16,0,48,84,0,6,74,84,55,3,16,3
+Tennessee Titans,16,55,10,13,84,32,94,48,19,16,32,71,0,6,13,29
diff --git a/poll-of-pollsters/README.md b/poll-of-pollsters/README.md
@@ -1,6 +1,6 @@
 ### Poll of Pollsters data
 
-This repo contains the responses from pollsters to FiveThirtyEight's six polls of professional political pollsters, as described in these articles:
+This repo contains the responses from pollsters to FiveThirtyEight's seven polls of professional political pollsters, as described in these articles:
 
 [Pollsters Predict Greater Polling Error In Midterm Elections](http://fivethirtyeight.com/features/pollsters-predict-greater-polling-error-in-midterm-elections/)
 
@@ -14,7 +14,9 @@ This repo contains the responses from pollsters to FiveThirtyEight's six polls o
 
 [Iowa Teaches Pollsters To Poll Until The End](http://fivethirtyeight.com/features/iowa-teaches-pollsters-to-poll-until-the-end/)
 
-We sent out the first poll starting Wed. Sept. 24, 2014, and 26 pollsters responded by deadline. We sent out the second poll starting Sunday, Oct. 12, and 24 pollsters responded by deadline. We sent out the third poll starting Friday, Oct. 24, and 26 pollsters responded by deadline. We sent out the fourth poll starting Wednesday, Nov. 5, and 17 pollsters responded by deadline. We sent out the fifth poll starting Friday, Dec. 11, 2015, and 26 pollsters responded by deadline. We sent out the sixth poll starting Tuesday, Feb. 2, 2016, and eight pollsters responded by deadline.
+[Top Pollsters Expect Clinton To Win](http://fivethirtyeight.com/features/top-pollsters-expect-clinton-to-win/)
+
+We sent out the first poll starting Wed. Sept. 24, 2014, and 26 pollsters responded by deadline. We sent out the second poll starting Sunday, Oct. 12, and 24 pollsters responded by deadline. We sent out the third poll starting Friday, Oct. 24, and 26 pollsters responded by deadline. We sent out the fourth poll starting Wednesday, Nov. 5, and 17 pollsters responded by deadline. We sent out the fifth poll starting Friday, Dec. 11, 2015, and 26 pollsters responded by deadline. We sent out the sixth poll starting Tuesday, Feb. 2, 2016, and eight pollsters responded by deadline. We sent out the seventh poll starting Saturday, Oct. 8, 2016, and 33 pollsters responded by deadline.
 
 Respondents include commercial and academic pollsters who identify their polling organizations as liberal, nonpartisan or conservative. Some poll online, some by phone, some both. Some answers have been edited, primarily for spelling, grammar, style and to protect anonymity, when requested.
 
@@ -26,4 +28,4 @@ This tab-separated file contains the names of the respondents, their polling org
 
 The second file has a name like `poll-of-pollsters-anonymous-answers.tsv`:
 
-This tab-separated file contains those responses that pollsters didn't want attributed to them. The heading of each column contains a question, and below it, the responses to that question, in alphabetical order. That means that each row doesn’t correspond to any one respondent. For example, the answer in the fourth row, in the third column, wasn't necessarily given by the same respondent as the rest of the answers in the fourth row. This sorting step was taken to better protect anonymity, by making it harder to figure out who gave which answer.
+This tab-separated file contains those responses that pollsters didn't want attributed to them. The heading of each column contains a question, and below it, the responses to that question, in alphabetical order. That means that each row doesn’t correspond to any one respondent. For example, the answer in the fourth row, in the third column, wasn't necessarily given by the same respondent as the rest of the answers in the fourth row. This sorting step was taken to better protect anonymity, by making it harder to figure out who gave which answer.
diff --git a/poll-of-pollsters/poll-of-pollsters-7.tsv b/poll-of-pollsters/poll-of-pollsters-7.tsv
diff --git a/poll-of-pollsters/poll-of-pollsters-anonymous-answers-7.tsv b/poll-of-pollsters/poll-of-pollsters-anonymous-answers-7.tsv
diff --git a/religion-survey/README.md b/religion-survey/README.md
@@ -0,0 +1,5 @@
+### Religion Survey
+
+This directory contains the data behind the story [When Does Praying In Public Make Others Uncomfortable?](http://fivethirtyeight.com/features/when-does-praying-in-public-make-others-uncomfortable)
+
+Using a SurveyMonkey poll, conducted between July 29 and August 1, 2016, we asked 661 respondents [questions about public displays of religion](https://espnfivethirtyeight.files.wordpress.com/2016/09/surveymonkey_82631483.pdf).