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Data sets shared by StatCrunch members
Showing 16 to 30 of 138 data sets matching DIE
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Salamander Data.xlsx
Data for 31 Yellow-Spotted Salamanders, from the Kanda Lab at Ithaca College, Central for Natural Sciences, who were sedated with a solution possessing a ratio of 1 liter distilled water/1 gram Oragel (active ingredient 20% benzocaine), until they showed no signs of movement in reaction to a toe-pinch. The salamanders were then rinsed with distilled water, and then a PIT-tag was surgically inserted into the ventral abdominal region, in between the dermis and epidermis tissue layers. Mass and lengths (total length and Snout-Vent Length) were then recorded, and following the salamanders were placed into a Tupperware container surrounded by moist paper towels. At that point, the salamanders were then observed for both 'heads-up' movement and complete recovery (body movement and 'normal behavior'), and the time until these took place was recorded. The variables include Gender, Total Length (cm), Snout-Vent Length [The measurement is from the tip of the nose (snout) to the anus (vent), and excludes the tail] (cm), Mass (g), and Recovery Time (minutes). | yes | matthewqbrooks@gmail.com | Apr 30, 2013 | 854B | 11 | | Excelsior Group 2 Statistic Healthy Habits.xlsx | yes | jodieh@riverland.org | Mar 27, 2013 | 389B | 17 | LAWRENCE/CF RESPONSE DATA
this data is a result of response times taken from four years worth of responses and 168 pages of data. The first column shows response times to certain addresses in various zones. The second column shows the distances to the corresponding response times in the first column. The third column depicts which station the response was from. This analysis was done for a presentation to elected officials and audience as a way to statistically prove that one station was in a more central location then the other. | yes | dpodlog | Mar 19, 2013 | 7KB | 14 | | Random 60 Die Rolls | yes | motoman.pettus | Feb 12, 2013 | 125B | 8 | | 300 Die Rolls | yes | mark.stender@my.witcc.edu | Feb 03, 2013 | 615B | 9 | 2012 MLB Batting Statistics
This set of data was supplied by MLB.com, the official website of Major League Baseball. The stats that are shown here depict the top 50 hitters from the 2012 season. The stats that are accounted into strictly the batting portion are; At bats, walks, hits, doubles, triples, home runs, runs batted in (runs that score on your hit), strike outs, batting average (how many times you get on base by getting a hit), on base percentage (how many times you get on base counting walks), OPS which stands for on base plus slugging (add the players average and on base percentage), and wins above replacement (WAR).
RK PLAYER TEAM AB R H 2B 3B HR RBI SB CS BB SO AVG OBP SLG OPS WAR
1 Buster Posey SF 530 78 178 39 1 24 103 1 1 69 96 .336 .408 .549 .957 7.2
2 Miguel Cabrera DET 622 109 205 40 0 44 139 4 1 66 98 .330 .393 .606 .999 6.9
3 Andrew McCutchen PIT 593 107 194 29 6 31 96 20 12 70 132 .327 .400 .553 .953 7.0
4 Mike Trout LAA 559 129 182 27 8 30 83 49 5 67 139 .326 .399 .564 .963 10.7
5 Adrian Beltre TEX 604 95 194 33 2 36 102 1 0 36 82 .321 .359 .561 .921 6.6
6 Ryan Braun MIL 598 108 191 36 3 41 112 30 7 63 128 .319 .391 .595 .987 6.8
7 Joe Mauer MIN 545 81 174 31 4 10 85 8 4 90 88 .319 .416 .446 .861 4.1
8 Derek Jeter NYY 683 99 216 32 0 15 58 9 4 45 90 .316 .362 .429 .791 2.1
9 Yadier Molina STL 505 65 159 28 0 22 76 12 3 45 55 .315 .373 .501 .874 6.7
10 Prince Fielder DET 581 83 182 33 1 30 108 1 0 85 84 .313 .412 .528 .940 4.5
RK PLAYER TEAM AB R H 2B 3B HR RBI SB CS BB SO AVG OBP SLG OPS WAR
11 Torii Hunter LAA 534 81 167 24 1 16 92 9 1 38 133 .313 .365 .451 .817 5.5
12 Billy Butler KC 614 72 192 32 1 29 107 2 1 54 111 .313 .373 .510 .882 2.9
13 Robinson Cano NYY 627 105 196 48 1 33 94 3 2 61 96 .313 .379 .550 .929 8.2
14 Jordan Pacheco COL 475 51 147 32 3 5 54 7 2 22 61 .309 .341 .421 .762 -0.6
15 Allen Craig STL 469 76 144 35 0 22 92 2 1 37 89 .307 .354 .522 .876 2.2
16 Marco Scutaro SF/COL 620 87 190 32 4 7 74 9 4 40 49 .306 .348 .405 .753 2.0
17 David Wright NYM 581 91 178 41 2 21 93 15 10 81 112 .306 .391 .492 .883 6.7
18 David Murphy TEX 457 65 139 29 3 15 61 10 5 54 74 .304 .380 .479 .859 3.2
19 Alex Rios CHW 605 93 184 37 8 25 91 23 6 26 92 .304 .334 .516 .850 4.2
20 Carlos Gonzalez COL 518 89 157 31 5 22 85 20 5 56 115 .303 .371 .510 .881 1.3
RK PLAYER TEAM AB R H 2B 3B HR RBI SB CS BB SO AVG OBP SLG OPS WAR
21 Aaron Hill ARI 609 93 184 44 6 26 85 14 5 52 86 .302 .360 .522 .882 4.6
22 Martin Prado ATL 617 81 186 42 6 10 70 17 4 58 69 .301 .359 .438 .796 5.4
23 Austin Jackson DET 543 103 163 29 10 16 66 12 9 67 134 .300 .377 .479 .856 5.3
24 Aramis Ramirez MIL 570 92 171 50 3 27 105 9 2 44 82 .300 .360 .540 .901 5.4
25 Dexter Fowler COL 454 72 136 18 11 13 53 12 5 68 128 .300 .389 .474 .863 2.6
26 Adrian Gonzalez BOS/LAD 629 75 188 47 1 18 108 2 0 42 110 .299 .344 .463 .806 3.3
27 Paul Konerko CHW 533 66 159 22 0 26 75 0 0 56 83 .298 .371 .486 .857 1.4
28 Matt Holliday STL 599 95 177 36 2 27 102 4 4 75 132 .295 .379 .497 .877 3.8
29 Alex Gordon KC 642 93 189 51 5 14 72 10 5 73 140 .294 .368 .455 .822 6.2
30 Ben Revere MIN 511 70 150 13 6 0 32 40 9 29 54 .294 .333 .342 .675 2.4
RK PLAYER TEAM AB R H 2B 3B HR RBI SB CS BB SO AVG OBP SLG OPS WAR
31 David Freese STL 501 70 147 25 1 20 79 3 3 57 122 .293 .372 .467 .839 3.6
32 Alcides Escobar KC 605 68 177 30 7 5 52 35 5 27 100 .293 .331 .390 .721 3.2
33 Ian Desmond WSH 513 72 150 33 2 25 73 21 6 30 113 .292 .335 .511 .845 3.2
34 Yoenis Cespedes OAK 487 70 142 25 5 23 82 16 4 43 102 .292 .356 .505 .861 3.4
35 Daniel Murphy NYM 571 62 166 40 3 6 65 10 2 36 82 .291 .332 .403 .735 1.2
36 Erick Aybar LAA 517 67 150 31 5 8 45 20 4 22 61 .290 .324 .416 .740 4.0
37 Jose Altuve HOU 576 80 167 34 4 7 37 33 11 40 74 .290 .340 .399 .740 1.3
38 Dustin Pedroia BOS 563 81 163 39 3 15 65 20 6 48 60 .290 .347 .449 .797 4.6
39 Norichika Aoki MIL 520 81 150 37 4 10 50 30 8 43 55 .288 .355 .433 .787 3.3
40 Michael Brantley CLE 552 63 159 37 4 6 60 12 9 53 56 .288 .348 .402 .750 2.9
RK PLAYER TEAM AB R H 2B 3B HR RBI SB CS BB SO AVG OBP SLG OPS WAR
41 Angel Pagan SF 605 95 174 38 15 8 56 29 7 48 97 .288 .338 .440 .778 4.0
42 Howard Kendrick LAA 550 57 158 32 3 8 67 14 6 29 115 .287 .325 .400 .725 2.7
43 Adam Jones BAL 648 103 186 39 3 32 82 16 7 34 126 .287 .334 .505 .839 3.4
44 Jose Reyes MIA 642 86 184 37 12 11 57 40 11 63 56 .287 .347 .433 .780 2.8
45 Chase Headley SD 604 95 173 31 2 31 115 17 6 86 157 .286 .376 .498 .875 6.0
46 Elvis Andrus TEX 629 85 180 31 9 3 62 21 10 57 96 .286 .349 .378 .727 3.4
47 Miguel Montero ARI 486 65 139 25 2 15 88 0 0 73 130 .286 .391 .438 .829 3.7
48 Paul Goldschmidt ARI 514 82 147 43 1 20 82 18 3 60 130 .286 .359 .490 .850 3.1
49 Albert Pujols LAA 607 85 173 50 0 30 105 8 1 52 76 .285 .343 .516 .859 4.6
50 Josh Hamilton TEX 562 103 160 31 2 43 128 7 4 60 162 .285 .354 .577 .930 3.3
| yes | danbonito3@gmail.com | Jan 31, 2013 | 4KB | 14 | A Foodie's Dilemma Lab 2
Ashley, Ashley, Taylor and Michaela's Project | yes | swavelya@email.sc.edu | Jan 31, 2013 | 92B | 16 | | 60 die rolls | yes | mitchellwbegley | Sep 24, 2012 | 125B | 6 | | 60 Die Rolls | yes | bvandegriend | Sep 24, 2012 | 125B | 17 | | 60 Die Rolls | yes | kalebwvis1 | Sep 24, 2012 | 125B | 6 | Weekly Overall Average Gasoline Prices by State
Weekly Retail Gasoline and Diesel Prices
http://www.eia.gov/dnav/pet/pet_pri_gnd_a_epm0_pte_dpgal_w.htm
09:14:16 GMT-0400 (Eastern Daylight Time)
Source: U.S. Energy Information Administration | yes | sbroad@saintmarys.edu | Jun 27, 2012 | 37KB | 11 | Global Health Data for 86 developing countries
CONTR = % contraception prevalence for women (2005-2009 mean data)
GDP = Gross Domestic Product per capita by Purchasing Power Parities (in international dollars, fixed 2005 prices). 2005 data.
AGE = The average age, in years, of first marriage for women. 2005 data.
MORT = Infant mortality. The probability that a child born in a specific year will die before reaching the age of one, if subject to current age-specific mortality rates. Expressed as a rate per 1,000 live births. 2005 data.
SCHOOL = Mean years in school (women 25 and older). 2005 data.
TFR = Children per woman (total fertility): Total fertility rate is the number of children that would be born to each woman with prevailing age-specific fertility rates. 2005 data. | yes | glangkamp | Feb 08, 2012 | 3KB | 18 | | 300 Die Rolls | yes | dmcmillan86 | Jan 26, 2012 | 615B | 7 | Number Studying Foreign Languages
According to the Modern Languages Association, the number or college students studying foreign languages is increasing. The following data represents the foreign language being studied based on a simple random sample of 30 students learning a foreign language. (Sullivan #29, sec 2.1) | yes | smcdaniel04 | Sep 06, 2011 | 241B | 161 | | Preliminaries Data | yes | diehl8307 | Aug 31, 2011 | 27B | 4 |
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