Bmi计算年龄

欢迎使用唯一能够计算您的BMI（身体质量指数）计算器，它还可以让您查看自己与其他人相比较的情况！

目錄 Show

什么是BMI？
向减重达人们学习啦~
➡您的BMI值符合標準嗎？
➡ BMI超標先別慌「易瘦體質」養成清單
關於BMI的各種Q&A：

BMI分类

1. 在适当的字段中输入您的身高和体重。您可以选择公制或帝国测量系统.
2. 按"计算"按钮.
3. 您的BMI结果将出现在BMI字段中.
4. 要找出您的体重状况,使用BMI分类表检查您的BMI.

15或以下 = 饥饿

15.1-17.4 = 厌食症

17.5 - 18.4 = 过轻

18.5 - 24.9 = 理想

25-29.9 = 超重

30 - 39.9 = 肥胖

40或以上 = 病态肥胖

什么是BMI？

BMI或身体质量指数是找出您的体重是否超重、过轻或理想的快速方法。BMI可通过比较你的身高和体重立刻告诉您。马上就计算您的BMI！

1分钟彻底了解自己的标准体重、健康体重范围、BMI指数（即身体质量指数）、基础代谢率和燃脂运动中低强度运动心率，看看自己是否需要减肥了。

身体质量指数(BMI)：评估体重与身高比例的常用工具，适用范围：18至65岁的人士。儿童、发育中的青少年、孕妇、乳母、老人及身型健硕的运动员除外。

• 与好友分享：http://www.boohee.com/assessment/batchcalc复制链接

向减重达人们学习啦~

为美丽，更为健康用户：Carrie0907年龄：26身高：154CM

-57 斤

享瘦20斤，阿姨变姐姐用户：臭美妖妖年龄：30身高：153CM

-21 斤

减肥，其实并不难嘛！用户：独门房子年龄：29身高：157CM

-28 斤

» 查看更多达人

BMI身體質量指數(Body Mass Index)利用此數值衡量肥胖程度。

BMI體重標準約為18.5-24，BMI標準年齡男女差別不大，每人的理想體重根據個人身高體重呈現等比，並不是越瘦越好！

話不多說，查查看自己的BMI是多少吧！

➡您的BMI值符合標準嗎？

BMI值＜18.5：體重過輕

18.5 ≦ BMI值＜24：體重標準

24 ≦ BMI值＜27：體重過重

27 ≦ BMI值＜30：輕度肥胖

30 ≦ BMI值＜35：中度肥胖

BMI 值≧ 35：重度肥胖

➡ BMI超標先別慌「易瘦體質」養成清單

關於BMI的各種Q&A：

Q:BMI超標或未達標會發生什麼事？

BMI超標會發生的事

研究顯示，BMI計算體重過重或是肥胖（BMI≧24）為糖尿病、心血管疾病、惡性腫瘤等慢性疾病的主要風險因素。

BMI未達標會發生的事

而BMI計算過瘦的健康問題，則會有營養不良、骨質疏鬆、猝死等健康問題。

Q:BMI男女會有差異嗎？

A:BMI主要以身高、體重的數值計算，因此男女計算方式無差別，因此BMI數值並無差異。

男女肥胖差異可以同步參照「理想腰圍」數值，

男性成年腰圍需小於 90 公分，
女性成年腰圍則需小於 80 公分。

Q:BMI年齡有影響嗎？

A:BMI身體質量指數(Body Mass Index)是專為18歲以上的成年男女為計算指標，非成年以16歲為例，男性BMI正常值落在17.4-23.3，女性BMI正常值落在17.1-22.7，未成年男女依照年齡會有些許差異。

Q:BMI可以計算體脂肪嗎？

A:體脂肪大多以體脂計或是到專門的體育館、醫療院所測量較為準確。

擁有BMI值後也可以利用 體脂率 = 1.2 x BMI 值+ 0.23 x 年齡 - 5.4 -10.8 x 性別（男性= 1，女性= 0）公式計算出體脂率。

男性（2-20岁）身体质量指数（BMI）百分位数

结果


身体质量指数		kg/m2
Z 评分
百分位数

小数点精确度

BMI百分位数解释

百分位数 <5:	体重偏轻
百分位数 >=5 以及 <85:	正常体重
百分位数 >=85 以及 <95:	超重
百分位数 >=95:	肥胖

注意

在极端情况下（>97百分位数或<3百分位数），小的百分位数差异表示有临床重要性的差异。在这些极端情况下，Z-评分能更准确地反映测量值偏离平均值的程度，对于追踪变更是一个有用的工具。
此计算器使用的 LMS 数据见以下数据表格.
对于所有 LMS 表，表格中对应患者特定值的行见此表的第一列；检索用于 Z-评分公式中 L（Box-Cox 幂）、M（中位数）和 S（广义变异系数）的数值。
Z-评分可用于对 Z-评分正态表格百分位数表中的对应百分位数进行表格搜索。表格左侧（Y 轴）的数字表示 Z 评分的个位和小数点后一位数，而表格上方（X 轴）的数字表示 Z 评分小数点后两位数。

使用的方程式

身体质量指数 = 体重 / (身高/100)2

年龄月 = 年龄 * 12

Z 评分 = ((身体质量指数/M)L - 1) / (L * S)

百分位数 = Z对应百分位数(Z 评分)

示例

Z 评分～相应百分位数

+ 1.0～84

+ 2.0～97.5

+ 2.5～99.4

+ 3.0～99.7

参考

LMS Parameters for Boys: BMI for Age. National health and nutrition survey (NHANES), CDC/National Center for Health Statistics.

LMS Parameters for Boys: BMI for Age

Age [months]	Power [L]	Median [M]	Variation [S]
24.5	-1.982373595	16.54777487	0.080127429
25.5	-1.924100169	16.49442763	0.079233994
26.5	-1.86549793	16.44259552	0.078389356
27.5	-1.807261899	16.3922434	0.077593501
28.5	-1.750118905	16.34333654	0.076846462
29.5	-1.69481584	16.29584097	0.076148308
30.5	-1.642106779	16.24972371	0.075499126
31.5	-1.592744414	16.20495268	0.074898994
32.5	-1.547442391	16.16149871	0.074347997
33.5	-1.506902601	16.11933258	0.073846139
34.5	-1.471770047	16.07842758	0.07339337
35.5	-1.442628957	16.03875896	0.072989551
36.5	-1.419991255	16.00030401	0.072634432
37.5	-1.404277619	15.96304277	0.072327649
38.5	-1.39586317	15.92695418	0.07206864
39.5	-1.394935252	15.89202582	0.071856805
40.5	-1.401671596	15.85824093	0.071691278
41.5	-1.416100312	15.82558822	0.071571093
42.5	-1.438164899	15.79405728	0.071495113
43.5	-1.467669032	15.76364255	0.071462106
44.5	-1.504376347	15.73433668	0.071470646
45.5	-1.547942838	15.70613566	0.071519218
46.5	-1.597896397	15.67904062	0.071606277
47.5	-1.653732283	15.65305192	0.071730167
48.5	-1.714869347	15.62817269	0.071889214
49.5	-1.780673181	15.604408	0.072081737
50.5	-1.850468473	15.58176458	0.072306081
51.5	-1.923551865	15.56025067	0.072560637
52.5	-1.999220429	15.5398746	0.07284384
53.5	-2.076707178	15.52064993	0.073154324
54.5	-2.155348017	15.50258427	0.073490667
55.5	-2.234438552	15.48568973	0.073851672
56.5	-2.313321723	15.46997718	0.074236235
57.5	-2.391381273	15.45545692	0.074643374
58.5	-2.468032491	15.44213961	0.075072264
59.5	-2.542781541	15.43003207	0.075522104
60.5	-2.61516595	15.41914163	0.07599225
61.5	-2.684789516	15.40947356	0.076482128
62.5	-2.751316949	15.40103139	0.076991232
63.5	-2.81445945	15.39381785	0.077519149
64.5	-2.87402476	15.38783094	0.07806539
65.5	-2.92984048	15.38306945	0.078629592
66.5	-2.981796828	15.37952958	0.079211369
67.5	-3.029831343	15.37720582	0.079810334
68.5	-3.073924224	15.37609107	0.080426086
69.5	-3.114093476	15.37617677	0.081058206
70.5	-3.15039004	15.37745304	0.081706249
71.5	-3.182893018	15.37990886	0.082369741
72.5	-3.21170511	15.38353217	0.083048178
73.5	-3.23694834	15.38831005	0.083741021
74.5	-3.25876011	15.39422883	0.0844477
75.5	-3.277281546	15.40127496	0.085167651
76.5	-3.292683774	15.40943252	0.085900184
77.5	-3.305124073	15.41868691	0.086644667
78.5	-3.314768951	15.42902273	0.087400421
79.5	-3.321785992	15.44042439	0.088166744
80.5	-3.326345795	15.45287581	0.088942897
81.5	-3.328602731	15.46636218	0.089728202
82.5	-3.328725277	15.48086704	0.090521875
83.5	-3.32687018	15.49637465	0.091323162
84.5	-3.323188896	15.51286936	0.092131305
85.5	-3.317827016	15.53033563	0.092945544
86.5	-3.310923871	15.54875807	0.093765118
87.5	-3.302612272	15.56812143	0.09458927
88.5	-3.293018361	15.58841065	0.095417247
89.5	-3.282260813	15.60961101	0.096248301
90.5	-3.270454609	15.63170735	0.097081694
91.5	-3.257703616	15.65468563	0.097916698
92.5	-3.244108214	15.67853139	0.098752593
93.5	-3.229761713	15.70323052	0.099588675
94.5	-3.214751287	15.72876911	0.100424251
95.5	-3.199158184	15.75513347	0.101258643
96.5	-3.18305795	15.78231007	0.102091189
97.5	-3.166520664	15.8102856	0.102921245
98.5	-3.1496103	15.83904708	0.103748189
99.5	-3.132389637	15.86858123	0.104571386
100.5	-3.114911153	15.89887562	0.105390269
101.5	-3.097226399	15.92991765	0.106204258
102.5	-3.079383079	15.96169481	0.107012788
103.5	-3.061423765	15.99419489	0.107815327
104.5	-3.043386071	16.02740607	0.108611374
105.5	-3.025310003	16.0613159	0.109400388
106.5	-3.007225737	16.09591292	0.110181915
107.5	-2.989164598	16.13118532	0.110955478
108.5	-2.971148225	16.16712234	0.111720691
109.5	-2.953208047	16.20371168	0.112477059
110.5	-2.935363951	16.24094239	0.1132242
111.5	-2.917635157	16.27880346	0.113961734
112.5	-2.900039803	16.31728385	0.114689291
113.5	-2.882593796	16.35637267	0.115406523
114.5	-2.865311266	16.39605916	0.116113097
115.5	-2.848204697	16.43633265	0.116808702
116.5	-2.831285052	16.47718256	0.117493042
117.5	-2.81456189	16.51859843	0.11816584
118.5	-2.79804347	16.56056987	0.118826835
119.5	-2.781736856	16.60308661	0.119475785
120.5	-2.765648008	16.64613844	0.120112464
121.5	-2.749782197	16.68971518	0.120736656
122.5	-2.734142443	16.73380695	0.121348181
123.5	-2.718732873	16.77840363	0.121946849
124.5	-2.703555506	16.82349538	0.122532501
125.5	-2.688611957	16.86907238	0.123104991
126.5	-2.673903164	16.91512487	0.123664186
127.5	-2.659429443	16.96164317	0.124209969
128.5	-2.645190534	17.00861766	0.124742239
129.5	-2.631185649	17.05603879	0.125260905
130.5	-2.617413511	17.10389705	0.125765895
131.5	-2.603872392	17.15218302	0.126257147
132.5	-2.590560148	17.20088732	0.126734613
133.5	-2.577474253	17.25000062	0.12719826
134.5	-2.564611831	17.29951367	0.127648067
135.5	-2.551969684	17.34941726	0.128084023
136.5	-2.539539972	17.39970308	0.128506192
137.5	-2.527325681	17.45036072	0.128914497
138.5	-2.515320235	17.50138161	0.129309001
139.5	-2.503519447	17.55275674	0.129689741
140.5	-2.491918934	17.60447714	0.130056765
141.5	-2.480514136	17.6565339	0.130410133
142.5	-2.469300331	17.70891811	0.130749913
143.5	-2.458272656	17.76162094	0.131076187
144.5	-2.447426113	17.81463359	0.131389042
145.5	-2.436755595	17.86794729	0.131688579
146.5	-2.426255887	17.92155332	0.131974905
147.5	-2.415921689	17.97544299	0.132248138
148.5	-2.405747619	18.02960765	0.132508403
149.5	-2.395728233	18.08403868	0.132755834
150.5	-2.385858029	18.1387275	0.132990575
151.5	-2.376131459	18.19366555	0.133212776
152.5	-2.366542942	18.24884431	0.133422595
153.5	-2.357086871	18.3042553	0.133620197
154.5	-2.347757625	18.35989003	0.133805756
155.5	-2.338549576	18.41574009	0.133979452
156.5	-2.3294571	18.47179706	0.13414147
157.5	-2.320474586	18.52805255	0.134292005
158.5	-2.311596446	18.5844982	0.134431256
159.5	-2.302817124	18.64112567	0.134559427
160.5	-2.294131107	18.69792663	0.134676731
161.5	-2.285532933	18.75489278	0.134783385
162.5	-2.277017201	18.81201584	0.134879611
163.5	-2.268578584	18.86928753	0.134965637
164.5	-2.260211837	18.92669959	0.135041695
165.5	-2.251911809	18.98424378	0.135108024
166.5	-2.243673453	19.04191185	0.135164867
167.5	-2.235491842	19.09969557	0.135212469
168.5	-2.227362173	19.15758672	0.135251083
169.5	-2.21927979	19.21557707	0.135280963
170.5	-2.211240187	19.27365839	0.135302371
171.5	-2.203239029	19.33182247	0.135315568
172.5	-2.195272161	19.39006106	0.135320824
173.5	-2.187335625	19.44836594	0.135318407
174.5	-2.179425674	19.50672885	0.135308594
175.5	-2.171538789	19.56514153	0.135291662
176.5	-2.163671689	19.62359571	0.135267891
177.5	-2.155821357	19.6820831	0.135237567
178.5	-2.147985046	19.74059538	0.135200976
179.5	-2.140160305	19.7991242	0.135158409
180.5	-2.132344989	19.85766121	0.135110159
181.5	-2.124537282	19.916198	0.135056522
182.5	-2.116735712	19.97472615	0.134997797
183.5	-2.108939167	20.03323719	0.134934285
184.5	-2.10114692	20.09172262	0.134866291
185.5	-2.093358637	20.15017387	0.134794121
186.5	-2.085574403	20.20858236	0.134718085
187.5	-2.077794735	20.26693944	0.134638494
188.5	-2.070020599	20.32523642	0.134555663
189.5	-2.062253431	20.38346455	0.13446991
190.5	-2.054495145	20.44161501	0.134381553
191.5	-2.046748156	20.49967894	0.134290916
192.5	-2.039015385	20.5576474	0.134198323
193.5	-2.031300282	20.6155114	0.134104101
194.5	-2.023606828	20.67326189	0.134008581
195.5	-2.015942013	20.73088905	0.133912066
196.5	-2.008305745	20.7883851	0.133814954
197.5	-2.000706389	20.84574003	0.133717552
198.5	-1.993150137	20.90294449	0.1336202
199.5	-1.985643741	20.95998909	0.133523244
200.5	-1.97819451	21.01686433	0.133427032
201.5	-1.970810308	21.07356067	0.133331914
202.5	-1.96349954	21.1300685	0.133238245
203.5	-1.956271141	21.18637813	0.133146383
204.5	-1.949134561	21.24247982	0.13305669
205.5	-1.942099744	21.29836376	0.132969531
206.5	-1.935177101	21.35402009	0.132885274
207.5	-1.92837748	21.40943891	0.132804292
208.5	-1.921712136	21.46461026	0.132726962
209.5	-1.915192685	21.51952414	0.132653664
210.5	-1.908831065	21.57417053	0.132584784
211.5	-1.902639482	21.62853937	0.132520711
212.5	-1.896630358	21.68262062	0.132461838
213.5	-1.890816268	21.73640419	0.132408563
214.5	-1.885209876	21.78988003	0.132361289
215.5	-1.879823505	21.84303819	0.132320427
216.5	-1.874670324	21.8958685	0.132286382
217.5	-1.869760299	21.94836168	0.1322596
218.5	-1.865113245	22.00050569	0.132240418
219.5	-1.860734944	22.05229242	0.13222933
220.5	-1.85663384	22.10371305	0.132226801
221.5	-1.852827186	22.15475603	0.132233201
222.5	-1.849323204	22.20541249	0.132248993
223.5	-1.846131607	22.255673	0.132274625
224.5	-1.843261294	22.30552831	0.132310549
225.5	-1.840720248	22.3549693	0.132357221
226.5	-1.83851544	22.40398706	0.132415103
227.5	-1.83665586	22.45257182	0.132484631
228.5	-1.835138046	22.50071778	0.132566359
229.5	-1.833972004	22.54841437	0.132660699
230.5	-1.833157751	22.59565422	0.132768153
231.5	-1.83269562	22.64242956	0.132889211
232.5	-1.832584342	22.68873292	0.133024368
233.5	-1.832820974	22.73455713	0.133174129
234.5	-1.833400825	22.7798953	0.133338999
235.5	-1.834317405	22.82474087	0.133519496
236.5	-1.83555752	22.86908912	0.133716192
237.5	-1.837119466	22.91293151	0.133929525
238.5	-1.838987063	22.95626373	0.134160073
239.5	-1.841146139	22.99908062	0.134408381
240.5	-1.843580575	23.04137734	0.134675001

Z-score to percentile table

Z	0	1	2	3	4	5	6	7	8	9
-3.0	0.13%	0.13%	0.13%	0.12%	0.12%	0.11%	0.11%	0.11%	0.10%	0.10%
-2.9	0.19%	0.18%	0.18%	0.17%	0.16%	0.16%	0.15%	0.15%	0.14%	0.14%
-2.8	0.26%	0.25%	0.24%	0.23%	0.23%	0.22%	0.21%	0.21%	0.20%	0.19%
-2.7	0.35%	0.34%	0.33%	0.32%	0.31%	0.30%	0.29%	0.28%	0.27%	0.26%
-2.6	0.47%	0.45%	0.44%	0.43%	0.41%	0.40%	0.39%	0.38%	0.37%	0.36%
-2.5	0.62%	0.60%	0.59%	0.57%	0.55%	0.54%	0.52%	0.51%	0.49%	0.48%
-2.4	0.82%	0.80%	0.78%	0.75%	0.73%	0.71%	0.70%	0.68%	0.66%	0.64%
-2.3	1.07%	1.04%	1.02%	0.99%	0.96%	0.94%	0.91%	0.89%	0.87%	0.84%
-2.2	1.39%	1.36%	1.32%	1.29%	1.26%	1.22%	1.19%	1.16%	1.13%	1.10%
-2.1	1.79%	1.74%	1.70%	1.66%	1.62%	1.58%	1.54%	1.50%	1.46%	1.43%
-2.0	2.28%	2.22%	2.17%	2.12%	2.07%	2.02%	1.97%	1.92%	1.88%	1.83%
-1.9	2.87%	2.81%	2.74%	2.68%	2.62%	2.56%	2.50%	2.44%	2.39%	2.33%
-1.8	3.59%	3.52%	3.44%	3.36%	3.29%	3.22%	3.14%	3.07%	3.01%	2.94%
-1.7	4.46%	4.36%	4.27%	4.18%	4.09%	4.01%	3.92%	3.84%	3.75%	3.67%
-1.6	5.48%	5.37%	5.26%	5.16%	5.05%	4.95%	4.85%	4.75%	4.65%	4.55%
-1.5	6.68%	6.55%	6.43%	6.30%	6.18%	6.06%	5.94%	5.82%	5.71%	5.59%
-1.4	8.08%	7.93%	7.78%	7.64%	7.49%	7.35%	7.22%	7.08%	6.94%	6.81%
-1.3	9.68%	9.51%	9.34%	9.18%	9.01%	8.85%	8.69%	8.53%	8.38%	8.23%
-1.2	11.51%	11.31%	11.12%	10.94%	10.75%	10.57%	10.38%	10.20%	10.03%	9.85%
-1.1	13.57%	13.35%	13.14%	12.92%	12.71%	12.51%	12.30%	12.10%	11.90%	11.70%
-1.0	15.87%	15.63%	15.39%	15.15%	14.92%	14.69%	14.46%	14.23%	14.01%	13.79%
-0.9	18.41%	18.14%	17.88%	17.62%	17.36%	17.11%	16.85%	16.60%	16.35%	16.11%
-0.8	21.19%	20.90%	20.61%	20.33%	20.05%	19.77%	19.49%	19.22%	18.94%	18.67%
-0.7	24.20%	23.89%	23.58%	23.27%	22.97%	22.66%	22.36%	22.07%	21.77%	21.48%
-0.6	27.43%	27.09%	26.76%	26.44%	26.11%	25.79%	25.46%	25.14%	24.83%	24.51%
-0.5	30.85%	30.50%	30.15%	29.81%	29.46%	29.12%	28.77%	28.43%	28.10%	27.76%
-0.4	34.46%	34.09%	33.72%	33.36%	33.00%	32.64%	32.28%	31.92%	31.56%	31.21%
-0.3	38.21%	37.83%	37.45%	37.07%	36.69%	36.32%	35.94%	35.57%	35.20%	34.83%
-0.2	42.07%	41.68%	41.29%	40.91%	40.52%	40.13%	39.74%	39.36%	38.97%	38.59%
-0.1	46.02%	45.62%	45.22%	44.83%	44.43%	44.04%	43.64%	43.25%	42.86%	42.47%
0.0	50.00%	50.40%	50.80%	51.20%	51.60%	51.99%	52.39%	52.79%	53.19%	53.59%
0.1	53.98%	54.38%	54.78%	55.17%	55.57%	55.96%	56.36%	56.75%	57.14%	57.54%
0.2	57.93%	58.32%	58.71%	59.10%	59.48%	59.87%	60.26%	60.64%	61.03%	61.41%
0.3	61.79%	62.17%	62.55%	62.93%	63.31%	63.68%	64.06%	64.43%	64.80%	65.17%
0.4	65.54%	65.91%	66.28%	66.64%	67.00%	67.36%	67.72%	68.08%	68.44%	68.79%
0.5	69.15%	69.50%	69.85%	70.19%	70.54%	70.88%	71.23%	71.57%	71.90%	72.24%
0.6	72.58%	72.91%	73.24%	73.57%	73.89%	74.22%	74.54%	74.86%	75.18%	75.49%
0.7	75.80%	76.12%	76.42%	76.73%	77.04%	77.34%	77.64%	77.94%	78.23%	78.52%
0.8	78.81%	79.10%	79.39%	79.67%	79.96%	80.23%	80.51%	80.79%	81.06%	81.33%
0.9	81.59%	81.86%	82.12%	82.38%	82.64%	82.89%	83.15%	83.40%	83.65%	83.89%
1.0	84.13%	84.38%	84.61%	84.85%	85.08%	85.31%	85.54%	85.77%	85.99%	86.21%
1.1	86.43%	86.65%	86.86%	87.08%	87.29%	87.49%	87.70%	87.90%	88.10%	88.30%
1.2	88.49%	88.69%	88.88%	89.07%	89.25%	89.44%	89.62%	89.80%	89.97%	90.15%
1.3	90.32%	90.49%	90.66%	90.82%	90.99%	91.15%	91.31%	91.47%	91.62%	91.77%
1.4	91.92%	92.07%	92.22%	92.36%	92.51%	92.65%	92.79%	92.92%	93.06%	93.19%
1.5	93.32%	93.45%	93.57%	93.70%	93.82%	93.94%	94.06%	94.18%	94.30%	94.41%
1.6	94.52%	94.63%	94.74%	94.85%	94.95%	95.05%	95.15%	95.25%	95.35%	95.45%
1.7	95.54%	95.64%	95.73%	95.82%	95.91%	95.99%	96.08%	96.16%	96.25%	96.33%
1.8	96.41%	96.49%	96.56%	96.64%	96.71%	96.78%	96.86%	96.93%	97.00%	97.06%
1.9	97.13%	97.19%	97.26%	97.32%	97.38%	97.44%	97.50%	97.56%	97.62%	97.67%
2.0	97.73%	97.78%	97.83%	97.88%	97.93%	97.98%	98.03%	98.08%	98.12%	98.17%
2.1	98.21%	98.26%	98.30%	98.34%	98.38%	98.42%	98.46%	98.50%	98.54%	98.57%
2.2	98.61%	98.65%	98.68%	98.71%	98.75%	98.78%	98.81%	98.84%	98.87%	98.90%
2.3	98.93%	98.96%	98.98%	99.01%	99.04%	99.06%	99.09%	99.11%	99.13%	99.16%
2.4	99.18%	99.20%	99.22%	99.25%	99.27%	99.29%	99.31%	99.32%	99.34%	99.36%
2.5	99.38%	99.40%	99.41%	99.43%	99.45%	99.46%	99.48%	99.49%	99.51%	99.52%
2.6	99.53%	99.55%	99.56%	99.57%	99.59%	99.60%	99.61%	99.62%	99.63%	99.64%
2.7	99.65%	99.66%	99.67%	99.68%	99.69%	99.70%	99.71%	99.72%	99.73%	99.74%
2.8	99.74%	99.75%	99.76%	99.77%	99.77%	99.78%	99.79%	99.80%	99.80%	99.81%
2.9	99.81%	99.82%	99.83%	99.83%	99.84%	99.84%	99.85%	99.85%	99.86%	99.86%
3.0	99.87%	99.87%	99.87%	99.88%	99.88%	99.89%	99.89%	99.89%	99.90%	99.90%