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巧用STDEV函数-计算样本标准偏差——学生成绩标准差计算
语法 STDEV(number1,number2,...) Number1,number2,... 为对应于总体样本的 1 到 30 个参数。 说明 • 函数 STDEV 假设其参数是总体中的样本。如果数据代表全部样本总体，则应该使用函数 Stdeva 来计算标准偏差。 • 此处标准偏差的计算使用“无偏差”或“n-1”方法。
50610编辑于 2024-07-08 - 来自专栏指剑的分享
python3 高斯函数
stdev（float）表示分布数据的标准偏差。 从数据文件中提取的浮点列表 """ def __init__(self, mu = 0, sigma = 1): self.mean = mu self.stdev self.data) / len(self.data) self.mean = avg return self.mean def calculate_stdev self.data: sigma += (d - mean) ** 2 sigma = math.sqrt(sigma / n) self.stdev = sigma return self.stdev def read_data_file(self, file_name, sample=True):
93210编辑于 2022-08-26 - 来自专栏分布式存储
ceph分布式存储-集群容量评估
IOPS=89, BW=360MiB/s (377MB/s)(1024MiB/2848msec) slat (usec): min=623, max=54269, avg=10938.52, stdev =8604.56 clat (msec): min=46, max=2750, avg=1238.56, stdev=741.72 lat (msec): min=47, max=2751 =50053.95, samples=3 iops : min= 38, max= 62, avg=51.33, stdev=12.22, samples=3 lat ( =110414.87, samples=4 iops : min= 22, max= 80, avg=61.00, stdev=26.96, samples=4 lat =80181.23, samples=5 iops : min= 12, max= 58, avg=46.80, stdev=19.58, samples=5 lat (
2.5K20发布于 2020-07-20 - 来自专栏CPK
根据CPK 公式 使用java 代码实现
", "20", "30", "40", "50"};//上限 下限 平均值double usl = 50;double lsl = 10;double mean = 30;// 标准差double stdev = calculateStandardDeviation(strArray);System.out.println("stdev : " + stdev);// 平均值 -- 最大值---最小值sumAvgValue (strArray,stdev);//计算 cpkdouble cpk = calculateCpk(usl, lsl, mean, stdev);System.out.println("cpk : " + cpk);// 计算 cp 制程 精密度double cp = calculateCp(usl, lsl, mean, stdev);System.out.println("cp : " + cp );// 计算 CPL 相对于下限规格的工序能力double cpl = calculateCpl(mean, lsl, stdev);System.out.println("cpl : " + cpl
30010编辑于 2024-09-06 - 来自专栏yeedomliu
ChatGPT快速软件工程
= statistics.stdev(numbers) return avg, median, stdevnumbers = [1, 2, 3, 4, 5]avg, median, stdev (self): self.assertAlmostEqual(self.stats.stdev, statistics.stdev(self.data), places=2) def ) # 断言当只有一个元素时，stdev为None else: self.assertEqual(single_stats.stdev, statistics.stdev (scores)) c_range = (avg_score - 0.5 * statistics.stdev(scores), avg_score + 0.5 * statistics.stdev (scores)) d_range = (avg_score - 1.5 * statistics.stdev(scores), avg_score - 0.5 * statistics.stdev
57820编辑于 2023-09-03 - 来自专栏开源部署
使用 Go 对 Nginx 进行性能测试
Max +/- Stdev Latency 116.96ms 17.76ms 173.96ms 85.31% Req/Sec 429.16 49.20 Max +/- Stdev Latency 124.57ms 18.26ms 209.70ms 80.17% Req/Sec 406.29 56.94 Max +/- Stdev Latency 514.57ms 119.80ms 1.21s 71.85% Req/Sec 97.18 22.56 Max +/- Stdev Latency 425.64ms 80.53ms 925.03ms 76.88% Req/Sec 117.03 22.13 Max +/- Stdev Latency 39.25ms 8.49ms 86.45ms 81.39% Req/Sec 1.29k 129.27
1K10编辑于 2022-06-28 - 来自专栏运维民工
virtiofs性能
=358.95 clat (nsec): min=250, max=2553.1k, avg=6280.18, stdev=2220.15 lat (usec): min=5, max =80466.79, samples=33 iops : min=18266, max=141016, avg=127100.12, stdev=20116.72, samples= =2372.65 clat (usec): min=59, max=42472, avg=6040.74, stdev=2574.32 lat (usec): min=61, max= 42474, avg=6044.68, stdev=2574.39 clat percentiles (usec): | 1.00th=[ 161], 5.00th=[ 2089 =32.87, samples=119 iops : min= 148, max= 186, avg=165.34, stdev= 8.22, samples=119 lat
1.6K00编辑于 2023-07-01 - 来自专栏爬虫资料
如何使用Python爬取网站进行性能测试
= statistics.stdev(latency_times) mean_bandwidth = statistics.mean(bandwidths) median_bandwidth = statistics.stdev(bandwidths) # 获取目标网站的域名和IP地址 url = results[0]["url"] domain = url.split ": stdev_status_code, "mean_response_time": mean_response_time, "median_response_time ": stdev_response_time, "mean_latency_time": mean_latency_time, "median_latency_time ": stdev_bandwidth, "domain": domain, "ip_address": ip_address } 亮点 本文的亮点有以下几点：
95820编辑于 2023-08-15 - 来自专栏技术杂记
fio基础24
(usec) Completion latency: min, max, mean, stdev (usec) Completion latency percentiles: 20 fields (see below) Total latency: min, max, mean, stdev (usec) Bw (KB/s): min, max, aggregate percentage latency: min, max, mean, stdev (usec) Completion latency: min, max, mean, stdev(usec) Completion latency percentiles: 20 fields (see below) Total latency: min, max, mean, stdev (usec) Bw (KB/s) : min, max, aggregate percentage of total, mean, stdev CPU usage: user, system, context switches, major
52220编辑于 2022-04-24 - 来自专栏bit哲学院
python实现朴素贝叶斯分类器（连续数据）
mean(self,numbers): return sum(numbers) / float(len(numbers)) # 计算方差，注意是分母是n-1 def stdev 用来提取每类样本下的每一维的特征集合 summaries = [(self.mean(attribute), self.stdev(attribute)) for attribute in ): # x为待分类数据 exponent = math.exp(-(math.pow(x-mean,2)/(2*math.pow(stdev,2)))) return (1 / (math.sqrt(2*math.pi) * stdev)) * exponent # 计算待分类数据的联合概率 def calClassProbabilities len(classSummaries)表示有多少特征维度 for i in range(len(classSummaries)): # mean, stdev
1.2K00发布于 2020-12-31 - 来自专栏GEE数据专栏，GEE学习专栏，GEE错误集等专栏
Google Earth Engine ——2001-2017年非洲土壤在土壤深度 0-20 厘米和 20-50 厘米的可提取锌，预测平均值和标准偏差数据
mean at 0-20 cm depth 1 32 ppm mean_20_50 Zinc, extractable, predicted mean at 20-50 cm depth 0 31 ppm stdev _0_20 Zinc, extractable, standard deviation at 0-20 cm depth 0 11 ppm stdev_20_50 Zinc, extractable, opacity="1" quantity="5"/>' + '</ColorMap>' + '<ContrastEnhancement/>' + '</RasterSymbolizer>'; var stdev }, "Zinc, extractable, mean visualization, 20-50 cm"); Map.addLayer( raw.select(2).sldStyle(stdev (stdev_20_50), {}, "Zinc, extractable, stdev visualization, 20-50 cm"); var converted = raw.divide
22310编辑于 2024-02-02 - 来自专栏开源技术小栈
PHP 协程框架 Hypervel
Max +/- Stdev Latency 15.93ms 16.86ms 155.82ms 87.02% Req/Sec 2.07k 420.46 Max +/- Stdev Latency 15.93ms 16.86ms 155.82ms 87.02% Req/Sec 2.07k 420.46 Max +/- Stdev Latency 1.03s 184.92us 1.03s 87.50% Req/Sec 1.52 1.29 ) Running s test @ http://10.10.4.12:9501/api threads and connections Thread Stats Avg Stdev Max +/- Stdev Latency 1.02s 64.72ms 1.87s 93.62% Req/Sec 1.16k 1.68k
40910编辑于 2025-06-29 - 来自专栏技术杂记
fio基础4
984.98MB, bw=10086KB/s, iops=630, runt=100002msec clat (usec): min=491, max=215739, avg=2990.82, stdev =3717.96 lat (usec): min=492, max=215739, avg=2991.14, stdev=3717.96 clat percentiles (usec) 99.95th=[52480], | 99.99th=[79360] bw (KB /s): min= 1408, max= 4739, per=33.38%, avg=3366.69, stdev : io=433904KB, bw=4338.1KB/s, iops=271, runt=100002msec clat (msec): min=1, max=213, avg= 4.09, stdev = 3.96 lat (msec): min=1, max=213, avg= 4.10, stdev= 3.96 clat percentiles (usec): | 1.00th
48830编辑于 2022-04-24 - 来自专栏机器学习初学者精选文章
【机器学习基础】朴素贝叶斯的算法实现
def init(self): def mean(self, X): # 计算均值 return sum(X) / float(len(X)) def stdev 综上所述，我们可以通过「字典」的形式进行保存： 因此： def summarize(self, train_data): summaries = [(self.mean(column), self.stdev 首先对于类条件概率，根据高斯公式求得， def gaussian_probabality(self, x, mean, stdev): exponent = math.exp(-math.pow (x - mean, 2) / (2 * math.pow(stdev, 2))) return (1 / (math.sqrt(2 * math.pi) * stdev)) * exponent label] = summaries[0][2] / self.total_rows # 先验 for i in range(len(summaries)): mean, stdev
80510发布于 2021-02-08 - 来自专栏分布式存储
ceph分布式存储-块存储BlueStore性能测试
=12150.39 clat (usec): min=806, max=99391, avg=11156.56, stdev=8561.94 lat (msec): min=2, max =31251.51 clat (usec): min=774, max=249806, avg=25251.42, stdev=16090.29 lat (msec): min=1, max=341, avg=101.27, stdev=35.33 clat percentiles (usec): | 1.00th=[ 1544], 5.00th=[ 8256] =890871.23 clat (usec): min=906, max=243958, avg=34464.33, stdev=18648.43 lat (msec): min=2, =907840.86 clat (msec): min=1, max=70, avg=34.83, stdev=15.47 lat (msec): min=2, max=10224,
10.7K20发布于 2020-07-20 - 来自专栏GEE数据专栏，GEE学习专栏，GEE错误集等专栏
Google Earth Engine ——2001-2017年非洲土壤在 0-20 厘米和 20-50 厘米的土壤深度处可提取的PH数据，预测平均值和标准偏差
20 pH, predicted mean at 0-20 cm depth 35 103 mean_20_50 pH, predicted mean at 20-50 cm depth 35 102 stdev _0_20 pH, standard deviation at 0-20 cm depth 0 18 stdev_20_50 pH, standard deviation at 20-50 cm depth (mean_20_50), {}, "ph, mean visualization, 20-50 cm"); Map.addLayer( raw.select(2).sldStyle(stdev _0_20), {}, "ph, stdev visualization, 0-20 cm"); Map.addLayer( raw.select(3).sldStyle(stdev_20 _50), {}, "ph, stdev visualization, 20-50 cm"); var converted = raw.divide(10); var visualization
16010编辑于 2024-02-02 - 来自专栏逸鹏说道
ASP.NET Core 性能对比评测（ASP.NET，Python，Java，NodeJS）
Max +/- Stdev Latency 5.49ms 21.72ms 358.18ms 98.99% Req/Sec 23.28k 1.98k Max +/- Stdev Latency 5.30ms 5.81ms 22.24ms 76.75% Req/Sec 7.61k 455.21 Max +/- Stdev Latency 5.30ms 5.81ms 22.24ms 76.75% Req/Sec 7.61k 455.21 Max +/- Stdev Latency 4.94ms 5.58ms 22.82ms 80.90% Req/Sec 9.10k 444.04 Max +/- Stdev Latency 4.94ms 5.58ms 22.82ms 80.90% Req/Sec 9.10k 444.04
6K70发布于 2018-04-11 - 来自专栏GEE数据专栏，GEE学习专栏，GEE错误集等专栏
Google Earth Engine ——2001-2017年非洲土壤在 0-20 厘米和 20-50 厘米的土壤深度处可提取的石含量数据，预测平均值和标准偏差
-20 cm depth 1 55 ppm mean_20_50 Phosphorus, extractable, predicted mean at 20-50 cm depth 0 52 ppm stdev _0_20 Phosphorus, extractable, standard deviation at 0-20 cm depth 0 19 ppm stdev_20_50 Phosphorus, extractable ), {}, "Stone content, mean visualization, 20-50 cm"); Map.addLayer( raw.select(2).sldStyle(stdev _0_20), {}, "Stone content, stdev visualization, 0-20 cm"); Map.addLayer( raw.select(3).sldStyle (stdev_20_50), {}, "Stone content, stdev visualization, 20-50 cm"); var converted = raw.divide(10
10910编辑于 2024-02-02 - 来自专栏GEE数据专栏，GEE学习专栏，GEE错误集等专栏
Google Earth Engine ——2001-2017年非洲土壤在 0-20 厘米和 20-50 厘米的土壤深度处可提取的含砂量数据，预测平均值和标准偏差
-20 cm depth 1 55 ppm mean_20_50 Phosphorus, extractable, predicted mean at 20-50 cm depth 0 52 ppm stdev _0_20 Phosphorus, extractable, standard deviation at 0-20 cm depth 0 19 ppm stdev_20_50 Phosphorus, extractable 50), {}, "Sand content, mean visualization, 20-50 cm"); Map.addLayer( raw.select(2).sldStyle(stdev _0_20), {}, "Sand content, stdev visualization, 0-20 cm"); Map.addLayer( raw.select(3).sldStyle (stdev_20_50), {}, "Sand content, stdev visualization, 20-50 cm"); var converted = raw.divide(10
24310编辑于 2024-02-02 - 来自专栏技术小屋
go-web 服务端框架性能测试
Running 2m test @ http://localhost:8080/ 8 threads and 1024 connections Thread Stats Avg Stdev Max +/- Stdev Latency 13.03ms 3.80ms 100.73ms 86.97% Req/Sec 9.43k 1.64k Max +/- Stdev Latency 19.72ms 10.57ms 331.94ms 87.67% Req/Sec 6.52k 1.24k Max +/- Stdev Latency 17.32ms 8.19ms 252.60ms 90.70% Req/Sec 7.52k 1.35k Max +/- Stdev Latency 22.03ms 7.99ms 140.47ms 84.58% Req/Sec 5.79k 775.23
2.6K51发布于 2019-10-21
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