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{{venn3 |caption=Breakdown of British and<br>American [[traffic collision]] causes |unit=% |labelA=Driver factors |labelB=Roadway<br>factors |labelC=Vehicle factors |countA=57 |countB=3 |countC=2 |countAB=27 |countAC=6 |countBC=1 |countABC=3 }}
Element | Percent by mass | Atomic percent (calc.) | ||
---|---|---|---|---|
Oxygen | 65% | 25.6% | ||
Carbon | 18% | 9.5% | ||
Hydrogen | 10% | 63% | ||
Nitrogen | 3% | 1.3% | ||
Calcium | 1.5% | 0.24% | ||
Phosphorus | 1.2% | 0.24% | ||
Potassium | 0.2% | 0.03% | ||
Sulfur | 0.2% | 0.04% | ||
Chlorine | 0.2% | 0.04% | ||
Sodium | 0.1% | 0.03% | ||
Magnesium | 0.05% | 0.01% | ||
Iron | 3 g in men, 2.3 g in women | |||
Cobalt, Copper, Zinc, Iodine | < 0.05% each | |||
Selenium, Fluorine | < 0.01% each |
Knock-out without trapping | Knock-out with trapping | Overprinting |
---|
☎ ∈ The following chart shows the range of distances of the planets, dwarf planets and Halley's Comet from the Sun.
☎ ∈
☎ ∈ Timeline of recent buildings that have held the title Tallest building in the world. Heights of buildings are to scale. Note the early buildings that lost the title as their spires collapsed.
Condition (as determined by "Gold standard") | ||||
Condition Positive | Condition Negative | |||
Test Outcome |
Test Outcome Positive |
True Positive | False Positive (Type I error) |
Positive predictive value = Σ True Positive Σ Test Outcome Positive |
Test Outcome Negative |
False Negative (Type II error) |
True Negative | Negative predictive value = Σ True Negative Σ Test Outcome Negative | |
Sensitivity = Σ True Positive Σ Condition Positive |
Specificity = Σ True Negative Σ Condition Negative |
LEGEND | No food restrictions | Food sale/trade restrictions / ran | tests
---|---|---|
No cases | ||
Suspected | cases||
Known cases | ||
Deaths |
Country | Deaths | Confirmed cases | Suspected cases |
---|---|---|---|
Germany | 17[14] | 450 | 1 200 |
United Kingdom | 0 | 3 | - |
Sweden | 1 | 41 | - |
Denmark | 0 | 14 | 26 |
Netherlands | 0 | 2 | - |
France | 0 | 0 | 3[15] |
Spain | 0 | 1[16] | - |
Austria | 0 | - | - |
Norway | 0 | - | - |
Switzerland | 0 | 2 | - |
Finland | 0 | - | 1 |
Poland | 0 | 1 | - |
United States | 0 | 3 | - |
|v| r |
1 m/s 3.6 km/h 2.2 mph |
2 m/s 7.2 km/h 4.5 mph |
5 m/s 18 km/h 11 mph |
10 m/s 36 km/h 22 mph |
20 m/s 72 km/h 45 mph |
50 m/s 180 km/h 110 mph |
100 m/s 360 km/h 220 mph | |
---|---|---|---|---|---|---|---|---|
Slow walk | Bicycle | City car | Aerobatics | |||||
10 cm 3.9 in |
Laboratory centrifuge |
10 m/s² 1.0 g |
40 m/s² 4.1 g |
250 m/s² 25 g |
1.0 km/s² 100 g |
4.0 km/s² 410 g |
25 km/s² 2500 g |
100 km/s² 10000 g |
20 cm 7.9 in |
5.0 m/s² 0.51 g |
20 m/s² 2.0 g |
130 m/s² 13 g |
500 m/s² 51 g |
2.0 km/s² 200 g |
13 km/s² 1300 g |
50 km/s² 5100 g | |
50 cm 1.6 ft |
2.0 m/s² 0.20 g |
8.0 m/s² 0.82 g |
50 m/s² 5.1 g |
200 m/s² 20 g |
800 m/s² 82 g |
5.0 km/s² 510 g |
20 km/s² 2000 g | |
1 m 3.3 ft |
Playground carousel |
1.0 m/s² 0.10 g |
4.0 m/s² 0.41 g |
25 m/s² 2.5 g |
100 m/s² 10 g |
400 m/s² 41 g |
2.5 km/s² 250 g |
10 km/s² 1000 g |
2 m 6.6 ft |
500 mm/s² 0.051 g |
2.0 m/s² 0.20 g |
13 m/s² 1.3 g |
50 m/s² 5.1 g |
200 m/s² 20 g |
1.3 km/s² 130 g |
5.0 km/s² 510 g | |
5 m 16 ft |
200 mm/s² 0.020 g |
800 mm/s² 0.082 g |
5.0 m/s² 0.51 g |
20 m/s² 2.0 g |
80 m/s² 8.2 g |
500 m/s² 51 g |
2.0 km/s² 200 g | |
10 m 33 ft |
Roller-coaster vertical loop |
100 mm/s² 0.010 g |
400 mm/s² 0.041 g |
2.5 m/s² 0.25 g |
10 m/s² 1.0 g |
40 m/s² 4.1 g |
250 m/s² 25 g |
1.0 km/s² 100 g |
20 m 66 ft |
50 mm/s² 0.0051 g |
200 mm/s² 0.020 g |
1.3 m/s² 0.13 g |
5.0 m/s² 0.51 g |
20 m/s² 2 g |
130 m/s² 13 g |
500 m/s² 51 g | |
50 m 160 ft |
20 mm/s² 0.0020 g |
80 mm/s² 0.0082 g |
500 mm/s² 0.051 g |
2.0 m/s² 0.20 g |
8.0 m/s² 0.82 g |
50 m/s² 5.1 g |
200 m/s² 20 g | |
100 m 330 ft |
Freeway on-ramp |
10 mm/s² 0.0010 g |
40 mm/s² 0.0041 g |
250 mm/s² 0.025 g |
1.0 m/s² 0.10 g |
4.0 m/s² 0.41 g |
25 m/s² 2.5 g |
100 m/s² 10 g |
200 m 660 ft |
5.0 mm/s² 0.00051 g |
20 mm/s² 0.0020 g |
130 m/s² 0.013 g |
500 mm/s² 0.051 g |
2.0 m/s² 0.20 g |
13 m/s² 1.3 g |
50 m/s² 5.1 g | |
500 m 1600 ft |
2.0 mm/s² 0.00020 g |
8.0 mm/s² 0.00082 g |
50 mm/s² 0.0051 g |
200 mm/s² 0.020 g |
800 mm/s² 0.082 g |
5.0 m/s² 0.51 g |
20 m/s² 2.0 g | |
1 km 3300 ft |
High-speed railway |
1.0 mm/s² 0.00010 g |
4.0 mm/s² 0.00041 g |
25 mm/s² 0.0025 g |
100 mm/s² 0.010 g |
400 mm/s² 0.041 g |
2.5 m/s² 0.25 g |
10 m/s² 1.0 g |
Narrator — Wife | |
Father — Stepdaughter | |
Narrator |
Family tree showing how
the narrator of the song
is his own grandfather.
When X has standard deviation σ = 0.25, the distribution of Y is weakly skewed. Using formulas for the log-normal distribution, we find:
Indeed, the median is about one third on the way from mean to mode.
When X has a larger standard deviation, σ = 1, the distribution of Y is strongly skewed. Now
Here, Pearson's rule of thumb fails.
The following example uses the bar notation to calculate 0.012 × 0.85 = 0.0102:
* This step makes the mantissa between 0 and 1, so that its antilog (10mantissa) can be looked up.
Ending | Percentage | |
---|---|---|
0 | 7.5 | |
1 | 0.3 | |
2 | 0.3 | |
3 | 0.8 | |
4 | 0.3 | |
5 | 28.6 | |
6 | 0.3 | |
7 | 0.4 | |
8 | 1.0 | |
9 | 60.7 |
The above formulas can be used to show that the volumes of a cone, sphere and cylinder of the same radius and height are in the ratio 1 : 2 : 3, as follows.
Let the radius be r and the height be h (which is 2r for the sphere).
The discovery of the 2 : 3 ratio of the volumes of the sphere and cylinder is credited to Archimedes.[17]
The above formulas can be used to show that the volumes of a sphere and cylinder of the same radius and height are in the ratio 2 : 3, as follows.
Let the radius be r and the height be h (which is 2r for the sphere).
The discovery of this ratio is credited to Archimedes.[18]
Moon | Sun | |||
---|---|---|---|---|
At perigee (nearest) | At apogee (farthest) |
At perihelion (nearest) | At aphelion (farthest) | |
Mean radius, r | 1,737.10 kilometres (1,079.38 miles) |
696,000 kilometres (432,000 miles) | ||
Distance, d | 363,104 km (225,622 mi) | 405,696 km (252,088 mi) |
147,098,070 km (91,402,500 mi) | 152,097,700 km (94,509,100 mi) |
Angular diameter, 2×arctan(r / d) |
32' 54" (0.5482°) | 29' 26" (0.4907°) |
32' 32" (0.5422°) | 31' 28" (0.5244°) |
Apparent size to scale |
||||
Rank in descending order |
1st | 4th | 2nd | 3rd |
Celestial body | Angular diameter | Relative size (10 pixels per arcsecond) |
---|---|---|
Sun | 31.6′ – 32.7′ | 28.7 – 29.7 times the maximum value for Venus (orange bar below) |
Moon | 29.3′ – 34.1′ | 26.6 – 31.0 times the maximum value for Venus (orange bar below) |
Venus | 9.565″ – 66.012″ | |
Jupiter | 29.800″ – 50.115″ | |
Saturn | 14.991″ – 20.790″ | |
Mars | 3.492″ – 25.113″ | |
Mercury | 4.535″ – 13.019″ | |
Uranus | 3.340″ – 4.084″ | |
Neptune | 2.179″ – 2.373″ | |
Ceres | 0.330″ – 0.840″ | |
Vesta | 0.20" – 0.64" | |
Pluto | 0.063″ – 0.115″ | |
R Doradus | 0.052″ – 0.062″ | |
Betelgeuse | 0.049″ – 0.060″ | |
Eris | 0.034" – 0.089″ | |
Alphard | 0.00909″ | |
Alpha Centauri A | 0.007″ | |
Canopus | 0.006″ | |
Sirius | 0.005936″ | |
Altair | 0.003″ | |
Deneb | 0.002″ | |
Proxima Centauri | 0.001″ |
Apparent magnitude | Brightness relative to magnitude 0 | Example | Apparent magnitude | Brightness relative to magnitude 0 | Example | Apparent magnitude | Brightness relative to magnitude 0 | Example | ||
---|---|---|---|---|---|---|---|---|---|---|
-27 | 6.3×1010 | Sun | -7 | 630 | SN 1006 supernova | 13 | 6.3×10-6 | 3C 273 quasar | ||
-26 | 2.5×1010 | -6 | 250 | International Space Station (max) | 14 | 2.5×10-6 | Pluto (max) | |||
-25 | 1.0×1010 | -5 | 100 | Venus (max) | 15 | 1.0×10-6 | ||||
-24 | 4.0×109 | -4 | 40 | 16 | 4.0×10-7 | Charon (max) | ||||
-23 | 1.6×109 | -3 | 16 | Jupiter (max) | 17 | 1.6×10-7 | ||||
-22 | 6.3×108 | -2 | 6.3 | Mercury (max) | 18 | 6.3×10-8 | ||||
-21 | 2.5×108 | -1 | 2.5 | Sirius | 19 | 2.5×10-8 | ||||
-20 | 1.0×108 | 0 | 1.0 | Vega | 20 | 1.0×10-8 | ||||
-19 | 4.0×107 | 1 | 0.40 | Antares | 21 | 4.0×10-9 | Callirrhoe (small satellite of Jupiter) | |||
-18 | 1.6×107 | 2 | 0.16 | Polaris | 22 | 1.6×10-9 | ||||
-17 | 6.3×106 | 3 | 0.063 | Andromeda galaxy | 23 | 6.3×10-10 | ||||
-16 | 2.5×106 | 4 | 0.025 | Acubens | 24 | 2.5×10-10 | ||||
-15 | 1.0×106 | 5 | 0.010 | Vesta asteroid (max) | 25 | 1.0×10-10 | Fenrir (small satellite of Saturn) | |||
-14 | 4.0×105 | 6 | 4.0×10-3 | typical limit of naked eye | 26 | 4.0×10-11 | ||||
-13 | 1.6×105 | Full moon | 7 | 1.6×10-3 | Ceres (max) | 27 | 1.6×10-11 | visible light limit of 8m ground-based telescopes | ||
-12 | 6.3×104 | 8 | 6.3×10-4 | Neptune (max) | 28 | 6.3×10-12 | ||||
-11 | 2.5×104 | 9 | 2.5×10-4 | 29 | 2.5×10-12 | |||||
-10 | 1.0×104 | 10 | 1.0×10-4 | typical limit of 7x50 binoculars | 30 | 1.0×10-12 | ||||
-9 | 4.0×103 | Iridium flare | 11 | 4.0×10-5 | 31 | 4.0×10-13 | ||||
-8 | 1.6×103 | 12 | 1.6×10-5 | 32 | 1.6×10-13 | visible light limit of Hubble Space Telescope |
4:1:1 | 4:2:0 | 4:2:2 | 4:4:4 | ||||||||||||||||||||
Y'CrCb | |||||||||||||||||||||||
= | = | = | = | ||||||||||||||||||||
Y' | |||||||||||||||||||||||
+ | + | + | + | ||||||||||||||||||||
1 | 2 | 3 | 4 | J = 4 | 1 | 2 | 3 | 4 | J = 4 | 1 | 2 | 3 | 4 | J = 4 | 1 | 2 | 3 | 4 | J = 4 | ||||
(Cr, Cb) | 1 | a = 1 | 1 | 2 | a = 2 | 1 | 2 | a = 2 | 1 | 2 | 3 | 4 | a = 4 | ||||||||||
1 | b = 1 | b = 0 | 1 | 2 | b = 2 | 1 | 2 | 3 | 4 | b = 4 | |||||||||||||
¼ horizontal resolution, full vertical resolution | ½ horizontal resolution, ½ vertical resolution | ½ horizontal resolution, full vertical resolution | full horizontal resolution, full vertical resolution |
This Wikipedia page has been superseded by template:diagnostic_testing_diagram and is retained primarily for historical reference. |
True condition | |||||||
Total population | Condition positive | Condition negative | Prevalence = Σ Condition positive/Σ Total population | Accuracy (ACC) = Σ True positive + Σ True negative/Σ Total population | |||
Predicted condition |
Predicted condition positive |
True positive | False positive, Type I error |
Positive predictive value (PPV), Precision = Σ True positive/Σ Predicted condition positive | False discovery rate (FDR) = Σ False positive/Σ Predicted condition positive | ||
Predicted condition negative |
False negative, Type II error |
True negative | False omission rate (FOR) = Σ False negative/Σ Predicted condition negative | Negative predictive value (NPV) = Σ True negative/Σ Predicted condition negative | |||
True positive rate (TPR), Recall, Sensitivity (SEN), probability of detection, Power = Σ True positive/Σ Condition positive | False positive rate (FPR), Fall-out, probability of false alarm = Σ False positive/Σ Condition negative | Positive likelihood ratio (LR+) = TPR/FPR | Diagnostic odds ratio (DOR) = LR+/LR− | Matthews correlation coefficient (MCC) = √TPR·TNR·PPV·NPV − √FNR·FPR·FOR·FDR |
F1 score = 2 · PPV · TPR/PPV + TPR = 2 · Precision · Recall/Precision + Recall | ||
False negative rate (FNR), Miss rate = Σ False negative/Σ Condition positive | Specificity (SPC), Selectivity, True negative rate (TNR) = Σ True negative/Σ Condition negative | Negative likelihood ratio (LR−) = FNR/TNR |
This Wikipedia page has been superseded by template:diagnostic_testing_example and is retained primarily for historical reference. |
Patients with bowel cancer (as confirmed on endoscopy) | ||||||
Total population (pop.) = 2030 |
Condition positive | Condition negative | Prevalence = (TP + FN) / pop. = (20 + 10) / 2030 ≈ 1.48% |
Accuracy (ACC) = (TP + TN) / pop. = (20 + 1820) / 2030 ≈ 90.64% | ||
Fecal occult blood screen test outcome |
Test outcome positive |
True positive (TP) = 20 (2030 × 1.48% × 67%) |
False positive (FP) = 180 (2030 × (100% − 1.48%) × (100% − 91%)) |
Positive predictive value (PPV), precision = TP / (TP + FP) = 20 / (20 + 180) = 10% |
False discovery rate (FDR) = FP / (TP + FP) = 180 / (20 + 180) = 90.0% | |
Test outcome negative |
False negative (FN) = 10 (2030 × 1.48% × (100% − 67%)) |
True negative (TN) = 1820 (2030 × (100% − 1.48%) × 91%) |
False omission rate (FOR) = FN / (FN + TN) = 10 / (10 + 1820) ≈ 0.55% |
Negative predictive value (NPV) = TN / (FN + TN) = 1820 / (10 + 1820) ≈ 99.45% | ||
True positive rate (TPR), recall, sensitivity = TP / (TP + FN) = 20 / (20 + 10) ≈ 66.7% |
False positive rate (FPR), fall-out, probability of false alarm = FP / (FP + TN) = 180 / (180 + 1820) = 9.0% |
Positive likelihood ratio (LR+) = TPR/FPR = (20 / 30) / (180 / 2000) ≈ 7.41 |
Diagnostic odds ratio (DOR) = LR+/LR− ≈ 20.2 |
F1 score = 2 × precision × recall/precision + recall ≈ 0.174 | ||
False negative rate (FNR), miss rate = FN / (TP + FN) = 10 / (20 + 10) ≈ 33.3% |
Specificity, selectivity, true negative rate (TNR) = TN / (FP + TN) = 1820 / (180 + 1820) = 91% |
Negative likelihood ratio (LR−) = FNR/TNR = (10 / 30) / (1820 / 2000) ≈ 0.366 |
Status | Configuration | Name | Year built | Deadweight tonnage | IMO ship identification number | Photograph |
---|---|---|---|---|---|---|
Retired | Passenger (upper deck) Vehicle (lower deck)[20] | Pulau Labuan | 1971 | 139 | 7038408 | |
In service | Passenger (upper deck) Vehicle (lower deck) | Pulau Rawa | 1975 | 262 | 7343736 | |
In service | Passenger (upper deck) Vehicle (lower deck) | Pulau Talang Talang | 1975 | 262 | 7343748 | |
In service | Passenger (upper deck) Vehicle (lower deck) | Pulau Undan | 1975 | 262 | 7343724 | |
In service | Vehicle (both decks) | Pulau Rimau | 1980 | 100 | 7911076 | |
In service | Passenger (upper deck) Vehicle (lower deck) | Pulau Angsa | 1981 | 100 | 8010491 | |
In service | Vehicle (both decks) | Pulau Kapas | 1981 | 280 | 8101082 | |
In service | Vehicle (both decks) | Pulau Payar | 2002 | 440 | 9254393 | |
In service | Vehicle (both decks) | Pulau Pinang | 2002 | 440 | 9275244 |
Age group |
Estimated July 2010 population in millions[21] | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Africa | Asia | Europe | Latin America and the Caribbean |
Northern America |
Oceania | |||||||
0–4 | 155.3 | 360.4 | 39.67 | 53.83 | 23.54 | 3.079 | ||||||
5–9 | 136.2 | 354.5 | 37.01 | 55.52 | 22.66 | 2.875 | ||||||
10–14 | 120.2 | 364.8 | 37.32 | 55.12 | 21.72 | 2.844 | ||||||
15–19 | 108.1 | 374.6 | 42.54 | 54.11 | 23.93 | 2.829 | ||||||
20–24 | 97.21 | 379.4 | 51.28 | 52.08 | 24.00 | 2.838 | ||||||
25–29 | 83.89 | 343.8 | 53.33 | 49.47 | 24.42 | 2.721 | ||||||
30–34 | 69.28 | 310.5 | 52.96 | 45.52 | 22.17 | 2.497 | ||||||
35–39 | 55.60 | 315.4 | 52.88 | 41.34 | 22.71 | 2.594 | ||||||
40–44 | 45.15 | 297.5 | 53.46 | 37.64 | 23.03 | 2.382 | ||||||
45–49 | 37.82 | 248.4 | 55.15 | 34.33 | 25.74 | 2.362 | ||||||
50–54 | 31.68 | 212.2 | 53.08 | 28.68 | 24.91 | 2.128 | ||||||
55–59 | 25.68 | 188.5 | 48.30 | 23.72 | 21.72 | 1.862 | ||||||
60–64 | 20.11 | 135.1 | 41.80 | 18.07 | 18.62 | 1.676 | ||||||
65–69 | 14.78 | 100.0 | 31.57 | 13.88 | 13.72 | 1.227 | ||||||
70–74 | 10.43 | 78.13 | 32.85 | 10.66 | 10.25 | 0.939 | ||||||
75–79 | 6.367 | 53.71 | 24.09 | 7.564 | 8.223 | 0.702 | ||||||
80–84 | 3.100 | 29.75 | 17.89 | 4.870 | 6.755 | 0.564 | ||||||
85–89 | 1.036 | 12.70 | 9.446 | 2.460 | 4.201 | 0.318 | ||||||
90–94 | 0.229 | 3.882 | 2.689 | 0.921 | 1.714 | 0.120 | ||||||
95–99 | 0.030 | 0.775 | 0.795 | 0.253 | 0.425 | 0.031 | ||||||
100+ | 0.003 | 0.090 | 0.089 | 0.044 | 0.063 | 0.004 |
For example, consider an RGB Stripe Panel:
RGBRGBRGBRGBRGBRGB WWWWWWWWWWWWWWWWWW R = red RGBRGBRGBRGBRGBRGB is WWWWWWWWWWWWWWWWWW G = green RGBRGBRGBRGBRGBRGB perceived WWWWWWWWWWWWWWWWWW where B = blue RGBRGBRGBRGBRGBRGB as WWWWWWWWWWWWWWWWWW W = white RGBRGBRGBRGBRGBRGB WWWWWWWWWWWWWWWWWW
Shown below is an example of black and white lines at the Nyquist limit, but at a slanting angle, taking advantage of Subpixel rendering to use a different phase each row:
RGB___RGB___RGB___ WWW___WWW___WWW___ R = red _GBR___GBR___GBR__ is _WWW___WWW___WWW__ G = green __BRG___BRG___BRG_ perceived __WWW___WWW___WWW_ where B = blue ___RGB___RGB___RGB as ___WWW___WWW___WWW _ = black ____GBR___GBR___GB ____WWW___WWW___WW W = white
Shown below is an example of chromatic aliasing when the traditional whole pixel Nyquist limit is exceeded:
RG__GB__BR__RG__GB YY__CC__MM__YY__CC R = red Y = yellow RG__GB__BR__RG__GB is YY__CC__MM__YY__CC G = green C = cyan RG__GB__BR__RG__GB perceived YY__CC__MM__YY__CC where B = blue M = magenta RG__GB__BR__RG__GB as YY__CC__MM__YY__CC _ = black RG__GB__BR__RG__GB YY__CC__MM__YY__CC
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