S-Z
Sample, 样本
7 W3 M, A s% q1 c) X; ~" h& S* _6 iSample regression coefficient, 样本回归系数
+ Q9 f9 X6 [/ D$ lSample size, 样本量
' s; V1 p( O. n VSample standard deviation, 样本标准差
5 o s! w! E! h' R8 A, g" ^7 VSampling error, 抽样误差& A# {8 @- W$ c2 a" s6 U5 a. P
SAS(Statistical analysis system ), SAS统计软件包) x# ]8 m& d7 {) D- Z
Scale, 尺度/量表+ o9 i5 b4 l2 G+ r/ g; H; [4 P- F
Scatter diagram, 散点图
( \9 c( l U! W3 H1 m% a* D4 L$ D1 N; S; iSchematic plot, 示意图/简图
) U0 K: ^2 \" |2 @& eScore test, 计分检验0 F* E U, W% Y# F
Screening, 筛检5 [( ^5 y( \0 x9 w
SEASON, 季节分析 9 R' H/ G1 R# F; c7 }. _' x2 P6 w
Second derivative, 二阶导数
4 T4 T Q, J8 m# G$ q- }+ d) [; QSecond principal component, 第二主成分
* p& Q- ]) `/ W* {2 CSEM (Structural equation modeling), 结构化方程模型 4 T0 @9 y9 n; n8 ~- d8 M3 K" j6 {( P% j
Semi-logarithmic graph, 半对数图
- g, x' B, {0 `/ q7 xSemi-logarithmic paper, 半对数格纸
/ m& u5 T7 ]+ U( g. m) V; U# Y1 ISensitivity curve, 敏感度曲线
' w& O1 g) `- e( ~ x- G& qSequential analysis, 贯序分析' ^6 s, r# k5 c* c3 s$ ]
Sequential data set, 顺序数据集
# a. S/ c7 z: ^, T2 mSequential design, 贯序设计
2 L g! Y6 z4 K- HSequential method, 贯序法, @ U( V' S5 c. S: {4 F
Sequential test, 贯序检验法' w' z; F) r' |4 K" q" E
Serial tests, 系列试验
7 z2 Y5 ]) C( L* e! G4 f2 _: nShort-cut method, 简捷法
5 b6 @5 @' b! H8 J3 q& p- XSigmoid curve, S形曲线
: F' h0 H' [- P: y/ ^! q3 ESign function, 正负号函数0 f$ o6 D+ X; ]3 p, R' Y+ O
Sign test, 符号检验' C3 W8 G y. a6 `$ l7 x& v
Signed rank, 符号秩6 _9 S2 z. a7 s0 @' m
Significance test, 显著性检验
, b9 s+ p; C, HSignificant figure, 有效数字7 B3 Y7 j5 D; z1 ?5 j, @
Simple cluster sampling, 简单整群抽样
2 `5 d6 N, [, M8 u( Z# j8 ESimple correlation, 简单相关
/ r" P+ m& g/ ~% _Simple random sampling, 简单随机抽样9 T; L& z# M/ ]
Simple regression, 简单回归3 ]5 s, b T2 e5 |/ G9 f! |' |, P
simple table, 简单表
# G* E5 D0 b* S$ W4 mSine estimator, 正弦估计量& \5 l9 C' ?; W! J, K6 k) r5 R
Single-valued estimate, 单值估计
" @& I* u5 q, H/ b, _Singular matrix, 奇异矩阵: _, `: T( l8 T9 U
Skewed distribution, 偏斜分布5 F% W' I, p1 s! }( Y
Skewness, 偏度
- ~0 s, r8 I9 ~. H8 WSlash distribution, 斜线分布
# m2 x: c$ E1 O0 ISlope, 斜率5 k0 ? l3 V N6 u+ k. G
Smirnov test, 斯米尔诺夫检验
( z+ v3 V6 S2 Z8 n/ n' S5 e, aSource of variation, 变异来源+ g) J, i8 t' k2 y$ K, g
Spearman rank correlation, 斯皮尔曼等级相关
9 d( P8 |' k/ {- wSpecific factor, 特殊因子
5 [% C( Y2 a* rSpecific factor variance, 特殊因子方差
) {0 ?9 N: \9 j, j/ i9 }7 w) @Spectra , 频谱* {6 t/ o1 Y; i0 J& n: }
Spherical distribution, 球型正态分布2 N* _+ G I% N9 b: x
Spread, 展布$ j- d" I2 u/ b7 n0 R0 T
SPSS(Statistical package for the social science), SPSS统计软件包0 _ Z$ O; l) [/ i! z
Spurious correlation, 假性相关
: y' q) G }+ T# ?5 X' WSquare root transformation, 平方根变换0 K/ p, Q2 P! D3 o; h* [
Stabilizing variance, 稳定方差3 h6 W; q# ^2 H1 w! o' i
Standard deviation, 标准差' K( u) W5 j! |0 |$ @3 t: F4 ]7 I
Standard error, 标准误
0 a) v C' J* D* h6 B! P8 JStandard error of difference, 差别的标准误: k, B( L9 J2 y X- B7 ]8 \0 \
Standard error of estimate, 标准估计误差& |# |* U( n9 t
Standard error of rate, 率的标准误
p/ G& I9 @7 e& C8 h, v/ {Standard normal distribution, 标准正态分布
9 V0 [' R5 R8 Z, B1 j+ M) p5 ~Standardization, 标准化
# |, p; g* \8 Z# ~- jStarting value, 起始值& k2 h. q5 m0 X+ a: ^% s6 D) p
Statistic, 统计量
# m0 Z) ]6 {: A2 J. ^+ aStatistical control, 统计控制
: G5 h& V: \9 q4 s; {Statistical graph, 统计图5 x; L# q4 H3 W W2 Q" i, V
Statistical inference, 统计推断
# W5 z3 E* z, L$ w3 |! \3 RStatistical table, 统计表1 o. O6 ?0 V2 Q; ?2 ]5 c' s
Steepest descent, 最速下降法. T& |* V2 P- `
Stem and leaf display, 茎叶图
1 N- K9 i2 A0 b3 EStep factor, 步长因子
% Q% _8 n1 U2 X3 y" [! ?Stepwise regression, 逐步回归. h/ B6 c% } P7 K
Storage, 存
$ R9 G/ O9 X. _) K* CStrata, 层(复数)
2 |! E6 G2 J8 J% P! IStratified sampling, 分层抽样
8 [0 I9 n; n* M/ jStratified sampling, 分层抽样
* r8 X) F8 \3 {- N5 Y. ^Strength, 强度
* t$ Z/ }, e' ]$ {/ wStringency, 严密性* @0 v) H2 P! q/ F; ?
Structural relationship, 结构关系6 w' D' Z( H( O# c; `6 G
Studentized residual, 学生化残差/t化残差
2 z' K; m% q4 b8 w! mSub-class numbers, 次级组含量
) C. O* K8 q! P4 VSubdividing, 分割
) y$ ]8 R$ T" o/ V4 FSufficient statistic, 充分统计量
% @/ O4 u2 } tSum of products, 积和
. s3 R; Y$ L3 {1 N* RSum of squares, 离差平方和5 @# @0 y, U* I
Sum of squares about regression, 回归平方和
5 |8 z' P; f" p& V. \4 M: m" o eSum of squares between groups, 组间平方和
! e2 g3 p1 X' @0 L0 N: U+ m/ l% x$ ySum of squares of partial regression, 偏回归平方和8 {' j% p% \) C! i
Sure event, 必然事件1 [) r6 W, g! T7 K% g3 ~
Survey, 调查
4 x4 ~% r- L+ a4 ?4 O# HSurvival, 生存分析
% u+ l8 x" ]+ c" v4 O: V6 C/ y: o# bSurvival rate, 生存率
, j1 k$ y, M$ I; W+ L$ TSuspended root gram, 悬吊根图" e& v0 y& i9 S6 Y& s: R
Symmetry, 对称6 ~$ `2 O9 `$ X! F3 N2 D, ]
Systematic error, 系统误差! Q* [4 h( P) v! l0 `8 Q5 i; s' y' S
Systematic sampling, 系统抽样
) m1 a7 g9 I% XTags, 标签/ K. N5 }! u) N1 X( i
Tail area, 尾部面积
6 b# G! { _ O3 p f- l: K: `Tail length, 尾长
+ q% N' B$ M% B8 K; A/ z2 Y- S5 V: NTail weight, 尾重: P8 A, t6 o, K3 R0 `
Tangent line, 切线* X3 u) J/ W4 X& A' Z
Target distribution, 目标分布
2 s+ E6 J5 d# pTaylor series, 泰勒级数
1 B5 v+ t; r! j. T; [9 @8 aTendency of dispersion, 离散趋势
+ z& |+ ^* {% P$ Q9 g4 J8 B1 yTesting of hypotheses, 假设检验, c- Y( v; ^: e. [) p
Theoretical frequency, 理论频数. h7 `8 {+ r4 f5 O m8 d& h# a
Time series, 时间序列
1 P$ Z- F0 X2 G' H- KTolerance interval, 容忍区间: P3 e% O" H& X; y5 a
Tolerance lower limit, 容忍下限
; N" |+ R& O% O+ H; MTolerance upper limit, 容忍上限0 G* e; H& u y( p* `" Q
Torsion, 扰率' A4 K7 Q# I& s3 m8 I. {: a
Total sum of square, 总平方和
" m6 G; |/ a r) CTotal variation, 总变异1 Q* f* F# i/ m. }; g4 _
Transformation, 转换
% t4 V# m- t, }Treatment, 处理
! R; g3 P8 B; N' gTrend, 趋势# t3 D: s$ k) B! u7 y m9 f/ _/ a
Trend of percentage, 百分比趋势0 n7 L) J8 _) n4 U8 l5 I
Trial, 试验) G" ` \% E* k7 \
Trial and error method, 试错法7 x2 R9 t2 l9 [ Z% b8 w0 a! W9 R+ [
Tuning constant, 细调常数
& F# S& [* p; R* ITwo sided test, 双向检验' f5 j8 A( j6 L8 @6 J: Q1 }
Two-stage least squares, 二阶最小平方$ h# ^6 M# E# m6 k
Two-stage sampling, 二阶段抽样
% L+ T& F% W: n8 o2 M8 ~Two-tailed test, 双侧检验) f) I; |0 }! K5 e* \+ X' }
Two-way analysis of variance, 双因素方差分析
& e3 W4 @2 n! t0 i0 J! n& zTwo-way table, 双向表2 f% Y$ |! s. e; Y; G: M8 A
Type I error, 一类错误/α错误9 X0 X# h( U5 p9 K. B
Type II error, 二类错误/β错误 O1 h/ p9 s0 g1 d/ o
UMVU, 方差一致最小无偏估计简称
6 F! i! s* p) {7 K' Q- D; lUnbiased estimate, 无偏估计
! d& q% M3 ~4 P" pUnconstrained nonlinear regression , 无约束非线性回归+ Q& D" D0 y6 @3 J/ o& \) ]
Unequal subclass number, 不等次级组含量$ s4 B+ _7 Q" ~- o/ l) a5 M, v! u
Ungrouped data, 不分组资料
4 b! I; J# w [3 xUniform coordinate, 均匀坐标
e& h2 A! k Z/ `# BUniform distribution, 均匀分布
4 [( t" X: _# T/ gUniformly minimum variance unbiased estimate, 方差一致最小无偏估计8 V& C! n8 c( L9 a1 n9 v4 ?! X& Q
Unit, 单元
! g% O; D0 K& yUnordered categories, 无序分类3 y+ l0 P4 L% D' z i* e/ n
Upper limit, 上限1 J1 O/ ~% [( ]9 [, I4 {
Upward rank, 升秩
9 Z' k6 |0 W' l1 {+ |0 eVague concept, 模糊概念% m" B. a) V1 l6 n# g# G
Validity, 有效性
/ o, M' j8 s/ k qVARCOMP (Variance component estimation), 方差元素估计
& I7 @$ P0 _- {Variability, 变异性
! Y7 {+ V( V# ~: C/ ]; \$ H+ LVariable, 变量) h! N9 r4 _( b# j2 {! c- S! \
Variance, 方差
b+ | G7 V/ p7 wVariation, 变异3 c4 R$ g4 h6 l1 K% I
Varimax orthogonal rotation, 方差最大正交旋转
/ Q5 M; }/ D. A2 E8 s1 m1 s3 A( mVolume of distribution, 容积
3 h) K% o1 c9 I/ r G3 N+ O; F1 WW test, W检验
; Y; b& H# ]. b# \# X7 ?" GWeibull distribution, 威布尔分布2 H6 y/ m9 c* y8 \
Weight, 权数
8 t7 U; b# k1 p$ f4 OWeighted Chi-square test, 加权卡方检验/Cochran检验
3 v% O6 v/ d4 i. fWeighted linear regression method, 加权直线回归, @) V. P7 T4 J0 ^# _* ~7 V8 @9 s
Weighted mean, 加权平均数2 n3 W3 Z8 P* ~& [# g
Weighted mean square, 加权平均方差# ~ g9 v# Q2 M- p2 N( g
Weighted sum of square, 加权平方和
7 `+ f! }# L) H$ H0 ]Weighting coefficient, 权重系数
" v7 ]/ Y8 S: k4 n' ~! o( BWeighting method, 加权法 $ z0 [2 i. O% w6 i" Z; r. A
W-estimation, W估计量
5 A8 t) G3 ^4 ]W-estimation of location, 位置W估计量2 F! Q. Z; }% h/ ]
Width, 宽度
: q4 E6 }2 k1 {Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验- ?" v3 K; `' y q5 s8 P# `& l% x" J
Wild point, 野点/狂点# W) Y8 I1 h( g9 d- n% v# z E
Wild value, 野值/狂值
) p; O4 k' l" N% |Winsorized mean, 缩尾均值' H7 j) {# S% M; I; \. l
Withdraw, 失访
6 ?) y9 E) R0 z% b( J9 tYouden's index, 尤登指数7 f; I5 C$ ^! q2 X: B
Z test, Z检验
% z' @+ e' a+ \, o( d- R. {Zero correlation, 零相关
5 l' n& c8 v# c1 VZ-transformation, Z变换
M-R
Main effect, 主效应
8 I& [1 r0 m0 ?, k" N! jMajor heading, 主辞标目( d" G' i. `4 H! ?7 p" M
Marginal density function, 边缘密度函数
# X: Y3 H* R7 X* E- z) d! iMarginal probability, 边缘概率
. y0 m7 b$ y! q2 iMarginal probability distribution, 边缘概率分布. l! s' Z+ W7 `% x% q2 s7 }( D5 L
Matched data, 配对资料4 J2 [. p/ g1 x
Matched distribution, 匹配过分布1 F$ D4 d. f7 B# i5 f( ]
Matching of distribution, 分布的匹配
; W# z9 D$ e) x) ~: `& V0 j$ I" NMatching of transformation, 变换的匹配
! a! Q. L# z( z# GMathematical expectation, 数学期望
( Z) Y3 W: C- T# Y, f kMathematical model, 数学模型
! w% _: f0 T3 y' v' P5 |% dMaximum L-estimator, 极大极小L 估计量
7 V" X+ w& t8 ~/ l5 c$ V$ T4 CMaximum likelihood method, 最大似然法5 p. d: U% L7 ^# z
Mean, 均数5 S6 B* H/ o, h5 } Z* Z" _: q1 J
Mean squares between groups, 组间均方. W) f4 w" y+ m
Mean squares within group, 组内均方
2 r% u! Y/ E4 ^. [$ ?Means (Compare means), 均值-均值比较
1 c' l3 }5 t3 G& nMedian, 中位数; Z0 v( E3 i/ P9 k5 J
Median effective dose, 半数效量
: `' d7 Y) e6 A ?7 Q2 a3 bMedian lethal dose, 半数致死量+ D+ ?' Q% l4 \" S
Median polish, 中位数平滑
/ u. I8 ]* J8 ?' D9 w0 p# N$ k+ PMedian test, 中位数检验
0 ` p/ Q' `' n8 h# p/ O" }5 VMinimal sufficient statistic, 最小充分统计量5 m/ f/ E& O" r. @9 \/ i+ Z5 h6 l
Minimum distance estimation, 最小距离估计4 j- q1 y4 \7 _4 Y) U: c
Minimum effective dose, 最小有效量
* K9 A& s' G; @6 l* |; jMinimum lethal dose, 最小致死量' W6 v w) {9 x8 N5 g/ ~% f; u
Minimum variance estimator, 最小方差估计量 T0 e+ `. x2 k' m- z7 ~
MINITAB, 统计软件包
3 x9 a0 A0 b% L2 M4 sMinor heading, 宾词标目
% h" n2 P* G z3 E! L+ m9 {Missing data, 缺失值 * F. P/ | y" d- O6 j: z
Model specification, 模型的确定
; a+ }9 p3 e" V) i9 d/ Q/ \Modeling Statistics , 模型统计) a: J7 y& }1 `$ E
Models for outliers, 离群值模型1 v" i* v- s7 H" w6 A" r
Modifying the model, 模型的修正9 S* B% h: V# t1 y. M( y, S0 a1 o& H
Modulus of continuity, 连续性模
- o9 A3 K1 ] G- eMorbidity, 发病率
5 u! E1 J. h0 I+ [Most favorable configuration, 最有利构形
% G5 ] h2 ], s( ?Multidimensional Scaling (ASCAL), 多维尺度/多维标度3 }! T9 [- r) [- S$ b/ t7 c; s
Multinomial Logistic Regression , 多项逻辑斯蒂回归
. O. i* Q6 u/ O( e2 hMultiple comparison, 多重比较4 J, @ e* l" a; H! i
Multiple correlation , 复相关7 ?+ f9 b$ g; u& H4 y. Y8 n) n/ Q& N
Multiple covariance, 多元协方差- T8 D) V: V3 u- ~* R; @
Multiple linear regression, 多元线性回归
4 {7 \. [! _) o1 S0 ^# ^: d7 jMultiple response , 多重选项+ I& @6 l' K- E! v
Multiple solutions, 多解/ Q4 }# d T. g- [2 l0 }+ T
Multiplication theorem, 乘法定理2 q6 W% Q5 ?/ I+ O5 p% g) a' N L
Multiresponse, 多元响应
) t x# Y8 s. N* j# W2 f# `Multi-stage sampling, 多阶段抽样
- f' m: o( g, n3 k1 N B- tMultivariate T distribution, 多元T分布
# f/ ~% A) o t% bMutual exclusive, 互不相容
1 ]" m U" m9 _% lMutual independence, 互相独立& P* y! ^$ w6 B1 n+ E& d1 E$ u
Natural boundary, 自然边界
9 O/ ~& V, P2 cNatural dead, 自然死亡
9 Q/ k* \7 o" b3 |/ P: d3 K* xNatural zero, 自然零
, I' Q% H8 T# g) {Negative correlation, 负相关
( E5 f Z. @6 B- ^7 l1 kNegative linear correlation, 负线性相关. O9 e" k0 h* H; S" r
Negatively skewed, 负偏/ d+ ~1 v0 Z' L; w, `
Newman-Keuls method, q检验% c0 u* P% p6 k$ I0 z) V. ?
NK method, q检验3 J a m( e5 |9 Z* u) [# a
No statistical significance, 无统计意义) O D+ f& E7 j
Nominal variable, 名义变量5 L& c2 `1 i' d! P3 h
Nonconstancy of variability, 变异的非定常性# D8 ^+ d8 q' q# `4 W
Nonlinear regression, 非线性相关
{- R1 e! D1 N7 pNonparametric statistics, 非参数统计
) L9 q% |$ @7 f: `5 lNonparametric test, 非参数检验
0 u0 v( C$ O! l! VNonparametric tests, 非参数检验
. j& P& j8 O) k( Y. uNormal deviate, 正态离差
# U, ~3 i% @, j& b7 yNormal distribution, 正态分布) `$ x/ `8 L z& P$ \8 r
Normal equation, 正规方程组
6 x2 w' s5 E& c O& v; Y: B1 fNormal ranges, 正常范围
! b. t2 |/ ~4 U4 \. E: q5 pNormal value, 正常值; U9 Y0 {9 W# w! `9 V2 M0 `' f; `: y1 j
Nuisance parameter, 多余参数/讨厌参数9 F" l: G% j$ U! a4 E
Null hypothesis, 无效假设
3 e, Q' H6 [6 i$ qNumerical variable, 数值变量
5 T5 H& U' }8 LObjective function, 目标函数" F G4 x3 G G9 V6 _% T! w' w( q
Observation unit, 观察单位* H3 y) @* i6 W9 j( I5 O
Observed value, 观察值
. _3 w. b3 p# V3 `) ^% T/ @4 VOne sided test, 单侧检验
4 l7 x J; j1 l; b# qOne-way analysis of variance, 单因素方差分析
1 F0 F* v$ c% E% i+ eOneway ANOVA , 单因素方差分析3 k2 x7 S* X( K. d+ H- F
Open sequential trial, 开放型序贯设计 _/ c, f g7 Z9 }6 ~2 n
Optrim, 优切尾4 n" }5 o& R8 u$ ^. A5 [% t& }4 G" F
Optrim efficiency, 优切尾效率+ l: c% }/ z* ?6 y$ F
Order statistics, 顺序统计量5 J' Y: \/ j/ A% v1 s5 L
Ordered categories, 有序分类
# X5 R% L1 z3 _2 o% X @Ordinal logistic regression , 序数逻辑斯蒂回归
* R# o3 _3 |% ROrdinal variable, 有序变量+ e* D5 i' I& G6 A; Q$ j$ H
Orthogonal basis, 正交基
! F' _* E8 I# mOrthogonal design, 正交试验设计9 @4 y" j" }9 J' A$ m0 w. s( B
Orthogonality conditions, 正交条件' \& ]" \+ k! Z' Z; c. b
ORTHOPLAN, 正交设计
: ^! v3 r9 p& j/ X% _9 T# IOutlier cutoffs, 离群值截断点1 B+ t% m2 B9 X- C9 [9 I- x
Outliers, 极端值, Q9 [# J; b4 q+ ?/ J5 s0 Y6 a; S# d! m1 k
OVERALS , 多组变量的非线性正规相关 # `9 \/ F- q2 _3 Z" X
Overshoot, 迭代过度, S/ }$ v& T3 T8 _% C# U
Paired design, 配对设计, r9 x. M c/ I* W4 h* @
Paired sample, 配对样本2 f4 r6 }" C3 W$ h8 ]- ~
Pairwise slopes, 成对斜率
+ l2 q6 u0 v$ u* h. V! XParabola, 抛物线
6 i! e: x" C1 }5 e$ N- m/ MParallel tests, 平行试验- R6 F2 w% v$ Q
Parameter, 参数
2 Z" H8 T. z- Q3 o- CParametric statistics, 参数统计% Z- q# x5 g- T/ e) b+ @1 d
Parametric test, 参数检验
" v$ w# C0 ]7 o7 b4 O2 I) PPartial correlation, 偏相关8 l7 r5 g9 `8 T+ j9 z( l4 o' a
Partial regression, 偏回归
7 ?* S% k1 K! l$ O5 T+ \Partial sorting, 偏排序
! W4 X1 Z. ^6 Q+ D9 SPartials residuals, 偏残差5 ]5 F7 k% U$ {$ M6 a
Pattern, 模式) b ~% H j$ {- e: x- S8 X
Pearson curves, 皮尔逊曲线5 `5 h, C% P3 O7 @$ E
Peeling, 退层' i0 S$ y6 u( {9 l+ X) w
Percent bar graph, 百分条形图5 y* U2 \6 [3 u; p
Percentage, 百分比
0 ~( ]% k9 b- d' h* P0 ^Percentile, 百分位数6 `0 }! K) G ]6 R
Percentile curves, 百分位曲线
% L4 \3 B+ E0 f5 c+ i. d8 J) PPeriodicity, 周期性/ }) y3 {- ?% I( O/ D; h3 V
Permutation, 排列* C1 n7 t) C9 A5 {7 F
P-estimator, P估计量1 A" |" N$ v! d% U4 O6 N& H( {" q
Pie graph, 饼图
, I8 i+ w3 H# I& c+ b* `. ^Pitman estimator, 皮特曼估计量4 i" O3 h6 f# W* |# E3 c
Pivot, 枢轴量
2 M0 V, I0 u; YPlanar, 平坦
0 x& h2 P' B: J" c/ h4 pPlanar assumption, 平面的假设
3 K4 r* U5 t: R! y2 F# a/ v( v: h' I3 DPLANCARDS, 生成试验的计划卡
7 D. t% V3 [" a( J: I" }5 uPoint estimation, 点估计
* U P# ?& S4 O) xPoisson distribution, 泊松分布; t" l* f0 {, b7 B+ j0 C+ v
Polishing, 平滑* T/ c0 ]& H9 }; @4 I; `3 m1 z
Polled standard deviation, 合并标准差) `' x2 {- d3 Z& ~% B
Polled variance, 合并方差
3 f1 W+ F' P Q0 E! d% `! [" t, L" SPolygon, 多边图+ ~0 ?! V5 M9 m% o
Polynomial, 多项式0 t' c0 _+ e& ~7 A' O! b, F
Polynomial curve, 多项式曲线$ Q* }/ n @' f! d; `$ b9 C; c
Population, 总体
. c, b( J: Q( k$ i7 X! W8 {Population attributable risk, 人群归因危险度. d5 [7 R" O+ C3 R# u- l
Positive correlation, 正相关
# ]. ^4 [8 j V+ U2 WPositively skewed, 正偏/ f' O7 r% L' S5 s) G& j# G: J
Posterior distribution, 后验分布8 R/ \. W1 j; _( Q2 F2 `
Power of a test, 检验效能- I) d# |1 H1 s! K
Precision, 精密度
, n0 X" d k; R' _Predicted value, 预测值
5 k$ E& p9 e2 F( KPreliminary analysis, 预备性分析
: Y n& \& O( e0 GPrincipal component analysis, 主成分分析
1 `- U8 L' k; O7 hPrior distribution, 先验分布
6 }2 ?8 w' S- o3 m+ V" [4 yPrior probability, 先验概率9 N- x# [# e* d
Probabilistic model, 概率模型
2 R7 P1 L' M9 \/ O/ {% _probability, 概率
* _8 u" E2 W: d tProbability density, 概率密度
8 w; Z) |2 K7 N/ R4 C# e ~Product moment, 乘积矩/协方差
3 L/ I1 U X ^+ s; h1 `; w$ {Profile trace, 截面迹图
7 A- J& ~+ L, e3 M2 MProportion, 比/构成比
' e' v4 |; u( J9 T/ O uProportion allocation in stratified random sampling, 按比例分层随机抽样. G5 K$ l, @# V2 E6 G
Proportionate, 成比例
9 r) w$ n B& i5 X) S- S6 vProportionate sub-class numbers, 成比例次级组含量' M; u4 `" v5 E' h Y5 w! W2 v- V! }
Prospective study, 前瞻性调查2 p# {; p) K) E
Proximities, 亲近性
7 m% b9 d: s1 @- TPseudo F test, 近似F检验5 K, p/ m8 ]' E7 Y: V' T3 g; T+ t9 r
Pseudo model, 近似模型
2 a/ x b$ `; G( b2 p! H1 XPseudosigma, 伪标准差3 p! _( p1 I$ I' y1 R
Purposive sampling, 有目的抽样
; t. F) C( [+ i( m3 I5 l! ^, b% MQR decomposition, QR分解
$ _) ~% Z5 [) J3 x, FQuadratic approximation, 二次近似
7 D; e2 a& ?1 d) |& ]" \Qualitative classification, 属性分类
; G- L: d$ t; Z' B y# d7 G7 u* nQualitative method, 定性方法; ?, m9 b: w3 t6 b
Quantile-quantile plot, 分位数-分位数图/Q-Q图
9 N* V9 ^4 S9 n8 t! ^Quantitative analysis, 定量分析 r: _9 V) r% F) V
Quartile, 四分位数2 K# F; a+ e( T+ d, X
Quick Cluster, 快速聚类6 {9 [- i+ a! S
Radix sort, 基数排序
+ a' Q$ y, g- `8 B RRandom allocation, 随机化分组
) P, a5 n: z0 R( G2 X5 Y* sRandom blocks design, 随机区组设计
2 `+ H0 j: m7 c8 H! v5 HRandom event, 随机事件) Q, w5 R: \ [, R
Randomization, 随机化* E' j4 o9 R. s# r4 v# l! [) E' I# ~
Range, 极差/全距
; x# K+ y1 g5 Q" o+ v/ RRank correlation, 等级相关
- d+ r# v$ k/ D jRank sum test, 秩和检验( [1 h/ F: D4 L6 V# X1 B
Rank test, 秩检验: t% P. A+ A0 c$ t# n) d- ?* q, f
Ranked data, 等级资料) V5 H( T: p6 H' K& ?0 r& J: X
Rate, 比率* v3 x' [4 ]" Q( P) H6 | N N+ M% W
Ratio, 比例0 o4 J* n4 T$ M. o
Raw data, 原始资料
3 z; N$ H! \2 C: H6 uRaw residual, 原始残差
; ~& t1 u# r: vRayleigh's test, 雷氏检验0 `7 Y3 a5 ?0 c- O! s# b6 E+ B
Rayleigh's Z, 雷氏Z值
$ ~1 c" Y9 s( f1 lReciprocal, 倒数% _: A" M+ k) `/ B0 g
Reciprocal transformation, 倒数变换
% y5 G& ^. S' a# X; z3 hRecording, 记录
}* m. L' a2 W- V1 u& N' A) ZRedescending estimators, 回降估计量
9 J6 M. d/ t( z8 y# z/ eReducing dimensions, 降维8 U/ ^' A4 _/ o. f6 ?
Re-expression, 重新表达( j3 G7 M0 k) g! F
Reference set, 标准组- t; v) A* i. W
Region of acceptance, 接受域; X5 J4 f( o9 N B! e V
Regression coefficient, 回归系数
E5 ^+ O9 I- s3 {0 g$ [/ r. xRegression sum of square, 回归平方和
7 f8 S5 x8 N/ Q6 a x1 o( G: CRejection point, 拒绝点
8 K& I" }: Z" H, }9 y% E TRelative dispersion, 相对离散度# |0 u& t- _3 o0 J+ c. A2 l
Relative number, 相对数
5 c* n& c& z+ ^+ K+ L4 t, o P( v- XReliability, 可靠性
5 O. m6 q7 t( K+ t8 VReparametrization, 重新设置参数 p- z6 C$ E2 a- E9 P
Replication, 重复# o; Y) `) A! ^1 I) R
Report Summaries, 报告摘要
) C% W4 a" L! OResidual sum of square, 剩余平方和
7 _, _& e, Q) r' cResistance, 耐抗性( a( d1 J) |2 u
Resistant line, 耐抗线! N; o6 Y0 U/ e! |# T
Resistant technique, 耐抗技术2 o- A1 V7 a- h' d# v
R-estimator of location, 位置R估计量
2 E1 S$ P* x( l) oR-estimator of scale, 尺度R估计量. y# J4 y' [4 Q' R
Retrospective study, 回顾性调查
0 x: J) H$ _4 p2 t7 C! c7 T, CRidge trace, 岭迹& y( w' E) @. v. ~8 G
Ridit analysis, Ridit分析# K+ y) k0 N& }4 Z$ f# ?
Rotation, 旋转% H& [+ y; v6 o- P
Rounding, 舍入
% Z% O! A; W H" Q! O6 x+ gRow, 行
4 \6 f8 \3 k* a# c% Q$ n- R0 d9 mRow effects, 行效应
# x! B3 S- o: w0 g; D; p6 o9 g# CRow factor, 行因素) u% f/ w! O1 B% N0 d$ G) b
RXC table, RXC表
E-L
Effect, 实验效应
. m V: Z0 P; REigenvalue, 特征值
5 ]$ R, F2 _+ o: mEigenvector, 特征向量
2 L/ G E# f$ tEllipse, 椭圆
0 E' }6 Q7 w/ CEmpirical distribution, 经验分布5 w: I9 D- [, L& D' b
Empirical probability, 经验概率单位. B, I$ a$ s9 Z( ?# G
Enumeration data, 计数资料6 S- r; s8 J( F$ z4 r3 X q/ c
Equal sun-class number, 相等次级组含量
+ W$ ]8 n" H* s! y+ S* GEqually likely, 等可能8 y" T/ e% d9 Q4 J( Y5 w: E" w/ a
Equivariance, 同变性: X1 {( H( N- |: N+ E( v
Error, 误差/错误8 {' ~& b2 p9 W0 }7 }0 p
Error of estimate, 估计误差# C: W7 Q7 ]4 h* |' o
Error type I, 第一类错误6 c; z$ ~5 y, D. c1 ]* ?7 N
Error type II, 第二类错误9 m6 a9 C$ {5 Y1 \) X' p8 V9 F
Estimand, 被估量
' Z4 N- y3 |+ l XEstimated error mean squares, 估计误差均方9 m* V4 x. |" u9 o: u) H
Estimated error sum of squares, 估计误差平方和
; s0 Z* O9 _4 `, H, d* G& ^Euclidean distance, 欧式距离
% B2 C$ e3 K, LEvent, 事件
) ~/ U( j% |. m4 A! `Event, 事件/ ]$ v6 \. b' l3 F* y9 x. I' b
Exceptional data point, 异常数据点7 q0 q n! k" u! t' ^4 {% Y( v3 t# k
Expectation plane, 期望平面
' X9 Z/ ^* p- O7 TExpectation surface, 期望曲面
" `- T0 P) }3 d2 `. M: w( ^ SExpected values, 期望值
$ w5 D5 d8 Z$ w$ CExperiment, 实验
3 Y$ r8 g! X# d( v8 z) B8 kExperimental sampling, 试验抽样
! h, ~' a9 {: V) k( rExperimental unit, 试验单位
1 i5 \5 j n1 ^7 s/ _% iExplanatory variable, 说明变量' s4 i$ J, ?+ r; N
Exploratory data analysis, 探索性数据分析
& O! Y+ q9 n% g% eExplore Summarize, 探索-摘要
X9 ]- R; s( U! l% v' H X% m9 \$ J7 C0 wExponential curve, 指数曲线
6 O+ o: z3 X2 m# N- g, k6 N. p9 R! |Exponential growth, 指数式增长4 s9 _* h* C+ x! g% c5 K, l- d5 Y
EXSMOOTH, 指数平滑方法 8 Y# E9 u$ h Z9 y
Extended fit, 扩充拟合
# M! z) B c6 L* D. [, x( JExtra parameter, 附加参数- j- _* z2 `( J* J/ {4 w- v
Extrapolation, 外推法2 V+ u- v7 i p; ?' S0 x( c; P
Extreme observation, 末端观测值 7 x# Z& f m/ S3 m8 n
Extremes, 极端值/极值
* O# }+ d; r/ L( w8 AF distribution, F分布( p" ?/ C) [3 Q$ n9 p
F test, F检验3 S$ _$ P6 \: @ F4 x
Factor, 因素/因子6 o) [6 i3 w' s, b4 R
Factor analysis, 因子分析
r; ?3 V8 Y# W( G' }Factor Analysis, 因子分析: M) v8 X4 }. z' L# c
Factor score, 因子得分+ R9 l# L% Y/ i3 i) Y5 b
Factorial, 阶乘+ ^2 B! J& }# x. d6 r' c3 f
Factorial design, 析因试验设计
2 U4 b7 a+ v, SFalse negative, 假阴性
) ^5 G2 H9 Q0 a1 h. n& a' w7 iFalse negative error, 假阴性错误
, H) j) H& V J1 x( I fFamily of distributions, 分布族
( m( I* R9 v# WFamily of estimators, 估计量族
$ r3 G2 c- A/ S$ KFanning, 扇面
& L' K2 V$ S a4 T1 E7 J% mFatality rate, 病死率6 _% N' x2 U) b7 p$ s2 _& c' B
Field investigation, 现场调查1 n' {! {3 T$ t4 a, K# b# K$ h: k
Field survey, 现场调查4 @4 X& ~% w0 U: ~4 ^
Finite population, 有限总体
$ X" F' d- ^1 P' z) sFinite-sample, 有限样本! x) a2 T1 P1 x$ s ?( e
First derivative, 一阶导数
?! @8 e7 o% x* ?+ kFirst principal component, 第一主成分
" z$ P7 _5 D* w% y% W5 JFirst quartile, 第一四分位数' _1 U' X2 q+ e. x D1 z9 U
Fisher information, 费雪信息量
; Y! |6 i9 P1 T& V3 r4 W, B! O# f: rFitted value, 拟合值/ ^: |( s, B9 F$ c& v) O
Fitting a curve, 曲线拟合
8 w' n3 m( ?- v# e9 M# VFixed base, 定基: ]- e w9 R' |% Z
Fluctuation, 随机起伏
3 Z& {1 @3 U8 F0 c+ |( ]Forecast, 预测2 V4 c' i; u) p- y
Four fold table, 四格表7 x" Q% {9 S7 U
Fourth, 四分点
/ M6 G' K$ v( ^( M, ~, O) q1 ^0 }Fraction blow, 左侧比率
9 E o- d. z0 H) @. BFractional error, 相对误差* p! t8 Q0 l) {* C# B/ d
Frequency, 频率& N; p8 g2 z: t) s% ?
Frequency polygon, 频数多边图
" ]+ z0 W( O, yFrontier point, 界限点
2 v1 ]2 e% z9 ^( D, C$ nFunction relationship, 泛函关系
3 Q7 h% K5 Q5 F% F. yGamma distribution, 伽玛分布
0 d0 {% \: }1 ^2 XGauss increment, 高斯增量3 m. X4 J) l6 U8 B7 Y/ o
Gaussian distribution, 高斯分布/正态分布' D( |7 O' E% ^! A4 p
Gauss-Newton increment, 高斯-牛顿增量; k; q& r/ r9 D8 A& L
General census, 全面普查+ S$ E# d& j, W
GENLOG (Generalized liner models), 广义线性模型
) v! ] V4 R* Y8 N) b2 J5 rGeometric mean, 几何平均数6 \$ A3 `4 Y- L% o
Gini's mean difference, 基尼均差5 P) @9 A* @2 `8 k
GLM (General liner models), 通用线性模型 9 C/ v7 T" B. K0 G4 R
Goodness of fit, 拟和优度/配合度
9 S2 w$ T/ _) W! Q, rGradient of determinant, 行列式的梯度" E# X7 \: p4 |# u: m% p% Q- \
Graeco-Latin square, 希腊拉丁方
* x& p9 p8 V# K" E% W' W4 pGrand mean, 总均值5 A2 ?) ?/ A9 ~, I- n
Gross errors, 重大错误+ f" k% L& X0 A
Gross-error sensitivity, 大错敏感度' P# z" Y) I) A6 p6 Z4 }3 m5 a# _
Group averages, 分组平均
( a# h x' f9 s( {$ o1 z+ N* _) C. vGrouped data, 分组资料7 Z" ^# h: k- ]& h: a. b
Guessed mean, 假定平均数2 p2 g* I& t1 j5 u9 U1 s$ r3 E
Half-life, 半衰期
7 k$ s0 n% ^- g- n& o8 g# qHampel M-estimators, 汉佩尔M估计量9 f( w. F) o" p, R7 J
Happenstance, 偶然事件
g8 ~2 j D. X' d5 fHarmonic mean, 调和均数
0 j, h7 m P$ j4 `. ]- ^Hazard function, 风险均数
' W- K4 @( W* o8 eHazard rate, 风险率' l) x5 o" L7 P- M9 R
Heading, 标目 + k$ ^% p& t- f( j0 Z2 w" W/ I
Heavy-tailed distribution, 重尾分布9 m" X6 p4 g! g+ R9 W0 j& `; T
Hessian array, 海森立体阵+ f* o) t( t( Z, z2 L5 p
Heterogeneity, 不同质% l0 C! s; h+ m* n
Heterogeneity of variance, 方差不齐
k' R7 f B. I8 n [* z2 rHierarchical classification, 组内分组& Q5 d l2 L. a. _8 f
Hierarchical clustering method, 系统聚类法
8 B$ v7 V# I+ ?: r$ Y" f! vHigh-leverage point, 高杠杆率点
% e3 T9 u# S$ ?( B- W, hHILOGLINEAR, 多维列联表的层次对数线性模型; C- I% r/ V2 Z% W
Hinge, 折叶点" S! Y/ s6 q9 C |3 P; y
Histogram, 直方图
5 \* c5 G3 m! cHistorical cohort study, 历史性队列研究 7 F+ t- A# D( o0 l( n
Holes, 空洞+ k& n- [: o9 H9 c! _2 ~
HOMALS, 多重响应分析
6 C6 e3 A. ?3 BHomogeneity of variance, 方差齐性
4 J1 K0 F. x% @6 w U; H. nHomogeneity test, 齐性检验& \6 Z$ ^6 G% t* i- a& _; Q
Huber M-estimators, 休伯M估计量
, \" \6 ?* v, N3 G8 |! Y4 F& s- RHyperbola, 双曲线
$ Y6 M; U% g' bHypothesis testing, 假设检验+ t N6 k$ A. k; i+ d
Hypothetical universe, 假设总体
$ u; l# O' ^$ i+ b2 O7 h" DImpossible event, 不可能事件: F$ {) K- C1 a$ c5 S$ \
Independence, 独立性2 I( T5 \1 ~" {
Independent variable, 自变量" v$ |$ x8 R/ {4 t8 A+ r t
Index, 指标/指数; d! ?3 c: m$ y1 c5 m& R7 k
Indirect standardization, 间接标准化法
9 @$ b! `9 a9 q+ u2 o4 f# ^ \; IIndividual, 个体
+ S }9 y5 Z \2 q7 \Inference band, 推断带
, P8 S' l8 I+ n4 Z QInfinite population, 无限总体
! P/ {6 I& C3 T" N6 kInfinitely great, 无穷大
; S- k' L0 U5 ]" y( qInfinitely small, 无穷小) p: V+ U) _ y6 o
Influence curve, 影响曲线
2 T& Y$ h e* T2 U$ LInformation capacity, 信息容量% W4 B& o5 Q+ l# ]& _& o
Initial condition, 初始条件# A0 z- x1 \: j B) P6 b3 y% g
Initial estimate, 初始估计值
3 D2 d. H: A9 L" o4 Y) z8 D4 yInitial level, 最初水平
5 S2 U# P; f, x& rInteraction, 交互作用& I' c& k- x7 G% ~1 k( g
Interaction terms, 交互作用项7 e: F/ ?0 l8 D4 n
Intercept, 截距0 L2 P; Z( `- {2 c& a
Interpolation, 内插法
6 p; J. V" E. {% g# R' S9 O. B8 cInterquartile range, 四分位距1 R- D! j2 [. W: x
Interval estimation, 区间估计0 M: n3 H% F" E+ V
Intervals of equal probability, 等概率区间! m5 S! d" b, n# r
Intrinsic curvature, 固有曲率' V% X. l3 ?) }: r% l* W
Invariance, 不变性" v6 M& F. j% x: ?" O$ B) u
Inverse matrix, 逆矩阵: c1 Y& X0 g0 r
Inverse probability, 逆概率
- s) E+ b+ L" \3 Q+ p+ K, ]Inverse sine transformation, 反正弦变换
B- ^/ W$ I, }: {2 l& q9 XIteration, 迭代 * M& @$ Y; e4 N! @ G3 g: f6 Z
Jacobian determinant, 雅可比行列式$ S3 F: S/ |# W! g: O
Joint distribution function, 分布函数
: M- ]9 G% f) n* e/ a4 P6 ~( fJoint probability, 联合概率. @ A, f8 X3 @4 P5 @
Joint probability distribution, 联合概率分布: _$ F) R: R( ?$ s. s8 r, J+ a
K means method, 逐步聚类法. K7 ]! B% p1 [4 \7 X% o
Kaplan-Meier, 评估事件的时间长度 ' v9 w: w* k6 i2 A! L d7 E: K
Kaplan-Merier chart, Kaplan-Merier图
7 ~9 |* M B7 @) U0 H# v- w2 `Kendall's rank correlation, Kendall等级相关- ~3 r4 k' ^+ ~3 u* I. @
Kinetic, 动力学
; h) q p# A1 vKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
: L% w: }4 y/ _ kKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
) N8 n4 n4 `5 Z# P/ h; R" `Kurtosis, 峰度
. x0 H6 b( X! \9 vLack of fit, 失拟% X& a E6 |4 [, W# l& @: [7 U
Ladder of powers, 幂阶梯
$ w7 y7 s0 h6 ^7 Y! U0 XLag, 滞后
9 k' x$ h/ |6 W2 X" XLarge sample, 大样本) w8 \& m# c% u
Large sample test, 大样本检验+ V8 J d9 q9 x( y. ?
Latin square, 拉丁方# z4 G8 C) H: W9 o. o! t" \
Latin square design, 拉丁方设计9 s+ D6 E: a6 a: L- J+ C3 `
Leakage, 泄漏( g; r. }7 ^8 U7 Y. u3 N
Least favorable configuration, 最不利构形$ d9 j8 @5 V$ ?/ |0 V' t v. h" M
Least favorable distribution, 最不利分布, J# ~% a) B2 d0 V( g* ^) N. o* j
Least significant difference, 最小显著差法
; J# m1 z$ Q+ c2 ^( }Least square method, 最小二乘法
2 n$ p5 ?1 O$ M. u RLeast-absolute-residuals estimates, 最小绝对残差估计/ B3 b) ?. Z% h' `9 A
Least-absolute-residuals fit, 最小绝对残差拟合
( A. {9 y7 x- A# y# W7 J$ y J7 @Least-absolute-residuals line, 最小绝对残差线# ] `& C4 T5 ~& T! h6 N$ Y
Legend, 图例* s' z9 Y5 c1 e1 f# @
L-estimator, L估计量: f$ P. C9 t% I5 G8 R; R
L-estimator of location, 位置L估计量
, k G7 u2 f6 t- t6 Q9 x4 c/ [, v0 |L-estimator of scale, 尺度L估计量, l* h7 |. J% {! [7 ^
Level, 水平
" |/ u" G+ Y' ^1 V' FLife expectance, 预期期望寿命
( U F+ L! A \Life table, 寿命表
6 _) I- q" J. N* s) K+ @% ?7 uLife table method, 生命表法2 v' M, ]/ ^' `7 A: k: V" y5 N
Light-tailed distribution, 轻尾分布2 t) M+ o! @3 }# L5 }# D- U& T
Likelihood function, 似然函数) l* y [& W6 d) Z
Likelihood ratio, 似然比
* [4 X" I w8 ?line graph, 线图
/ E, F j- r( U1 O! d# v* zLinear correlation, 直线相关
( ^# B- n% ~7 w. a& WLinear equation, 线性方程
* l; s6 i8 H& g E0 ~3 MLinear programming, 线性规划
& y- T8 q0 D: }Linear regression, 直线回归7 c! H" r$ t& R/ r5 S6 \. z4 \
Linear Regression, 线性回归
0 G. B+ P; z; ^7 A+ f4 PLinear trend, 线性趋势
% A7 F2 ~6 l3 K* XLoading, 载荷
% g. @3 f2 c; b0 M* O- f2 NLocation and scale equivariance, 位置尺度同变性$ q! J" X5 c) O- \9 S
Location equivariance, 位置同变性! j9 b5 v) C& C; h9 }% `: ~
Location invariance, 位置不变性
( ~& }" e' G1 E; G2 sLocation scale family, 位置尺度族 J8 r& \ N$ l% [2 |8 ]
Log rank test, 时序检验
) s! Y7 n n9 g5 [Logarithmic curve, 对数曲线
$ L0 k7 l) a) P1 o3 `Logarithmic normal distribution, 对数正态分布
6 Z5 |5 I5 }$ u+ K& p5 ^ t" X& eLogarithmic scale, 对数尺度7 E, c. E( H$ J7 N' g6 ^. L0 E
Logarithmic transformation, 对数变换" y/ R) g" c) b1 o3 L/ v
Logic check, 逻辑检查 z+ W9 D: z7 L6 Q s- Q
Logistic distribution, 逻辑斯特分布
- m+ |* X2 m) l2 [- \Logit transformation, Logit转换
3 I, l1 u7 [' U q5 HLOGLINEAR, 多维列联表通用模型
2 K8 P! @& j9 fLognormal distribution, 对数正态分布
0 e+ f. p( S' x9 P$ LLost function, 损失函数% a; q) K4 P6 P, V$ ]8 P% d' p
Low correlation, 低度相关) {) e' ]( Z- w s/ ^5 v; W
Lower limit, 下限) G: I7 x3 m; x. Y& F% @
Lowest-attained variance, 最小可达方差7 H% I+ |) N, K0 J9 \+ b3 \+ m& N
LSD, 最小显著差法的简称, A* q3 W' T; w
Lurking variable, 潜在变量
A-D
Absolute deviation, 绝对离差: z& N5 I/ y7 Z
Absolute number, 绝对数
# _8 D5 a$ d" m( V# qAbsolute residuals, 绝对残差! V* t3 d# A" d0 E. P: m3 z) h
Acceleration array, 加速度立体阵' o8 C( C9 e& ^- e$ Q6 d: r6 ?
Acceleration in an arbitrary direction, 任意方向上的加速度
1 W1 p* C+ j( W7 cAcceleration normal, 法向加速度" _6 l8 A5 b: Q/ G' m% l
Acceleration space dimension, 加速度空间的维数5 P8 n5 _& i4 |4 S8 B
Acceleration tangential, 切向加速度
$ e+ D* i/ o8 C( {3 ZAcceleration vector, 加速度向量
0 v V4 v; S) V- Q8 P6 @) qAcceptable hypothesis, 可接受假设
; `9 Z8 U. |+ B$ xAccumulation, 累积
4 ]2 Q3 w/ G, f3 XAccuracy, 准确度
' u' d5 I7 x. W4 AActual frequency, 实际频数2 E) C! F! ] n5 ?
Adaptive estimator, 自适应估计量
- T; h0 V, N/ N1 @" ~Addition, 相加
8 t p2 P ~1 L! k- }- J# L9 mAddition theorem, 加法定理0 {( Q. H# ]9 G4 r" i# ?
Additivity, 可加性* S: a( k* t9 o1 p3 j& g8 e
Adjusted rate, 调整率7 @( z4 @" O% t, P' P
Adjusted value, 校正值9 S# \1 Q* y/ @( O% h) B) }
Admissible error, 容许误差4 O8 r6 V* K/ I+ b2 w J5 R; k
Aggregation, 聚集性4 y4 H% Z4 K7 X1 T3 M( E
Alternative hypothesis, 备择假设! p$ S$ ^0 @2 s+ g7 c
Among groups, 组间7 w9 n0 _; P5 L# q9 L7 Q* N
Amounts, 总量
8 f( c2 H) U4 N" SAnalysis of correlation, 相关分析+ T/ Q( ?2 r+ ]6 v/ T$ J6 [! l
Analysis of covariance, 协方差分析
/ Q* {2 t9 k. e6 ~3 b7 TAnalysis of regression, 回归分析
+ @$ N2 f9 `3 @& q0 ` PAnalysis of time series, 时间序列分析
; }, X$ `( ]" | T/ ]8 vAnalysis of variance, 方差分析
! A4 M- W" ]. k1 |( }Angular transformation, 角转换- S8 a' n/ Y. `% ^( s
ANOVA (analysis of variance), 方差分析
$ H2 J; h* h: I8 E# r! _+ VANOVA Models, 方差分析模型+ m# y% H- _8 F
Arcing, 弧/弧旋
) S# l' N5 H: H* B# V* ?Arcsine transformation, 反正弦变换
, L' w! P0 x2 m% U5 c: _" W7 cArea under the curve, 曲线面积( B! l; {" _+ D
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
; p4 F, k9 k _ B/ P) o, |' |ARIMA, 季节和非季节性单变量模型的极大似然估计 1 B7 o K* o! E. t' M6 k! a
Arithmetic grid paper, 算术格纸! i; C* H7 i R- p5 D
Arithmetic mean, 算术平均数 C, d$ w" p% f+ W9 p
Arrhenius relation, 艾恩尼斯关系; |( \- ]/ v0 g# K3 h8 v
Assessing fit, 拟合的评估; Y/ K' M/ b) C1 ?
Associative laws, 结合律
4 D$ ?% d. S1 p! d4 @ q6 R5 DAsymmetric distribution, 非对称分布
" G& E5 t x! t& K* W# YAsymptotic bias, 渐近偏倚
% Y- h3 H G, _0 T6 r* |5 I ?Asymptotic efficiency, 渐近效率# E* M2 p. U5 v2 i: [& {
Asymptotic variance, 渐近方差6 G" j* B2 W7 `7 E) z" A3 H- ~3 [
Attributable risk, 归因危险度
% c+ `6 l7 Z. ] B8 _) |& z! xAttribute data, 属性资料# X; Y+ u4 [! L) L7 R
Attribution, 属性- `3 H5 |8 c5 m! z7 |% i5 l# X) v: l
Autocorrelation, 自相关. s; i! c# h9 {- V1 V8 ^
Autocorrelation of residuals, 残差的自相关
* p/ g% ]2 k7 n0 V$ y/ VAverage, 平均数6 r' m+ c! }! X. b) s; _6 A
Average confidence interval length, 平均置信区间长度+ x, q0 _. _4 x
Average growth rate, 平均增长率
d4 ^* j4 M9 ~/ RBar chart, 条形图
9 n! {) R9 l$ D2 G4 ?# g y1 aBar graph, 条形图- l5 w, T5 T I3 \3 T L' Z
Base period, 基期6 `+ {) L/ t) L' f
Bayes' theorem , Bayes定理8 Q4 ` s* d" i9 b
Bell-shaped curve, 钟形曲线
" y; s+ m# d4 l) S" ?6 n' `Bernoulli distribution, 伯努力分布 g' J1 |1 r Y0 A& c
Best-trim estimator, 最好切尾估计量
9 j) e* e: C5 o9 WBias, 偏性
* b; P. L, @# T7 w2 w) sBinary logistic regression, 二元逻辑斯蒂回归
; {4 {* J% k5 iBinomial distribution, 二项分布- X) j" p& v' J1 d9 b' v. R @4 R
Bisquare, 双平方: r. T' i% ?8 R$ l5 a* D
Bivariate Correlate, 二变量相关
; X- R0 ~. \: y1 p5 X0 c8 YBivariate normal distribution, 双变量正态分布# |4 h$ C( u9 E' U! o
Bivariate normal population, 双变量正态总体
! |, u% B" I+ ZBiweight interval, 双权区间7 h3 b% a1 o6 j5 ?' }
Biweight M-estimator, 双权M估计量9 A6 l# R. V8 p# q' ? ^" ]
Block, 区组/配伍组
1 L- G: V, Y# ~, G; Y; vBMDP(Biomedical computer programs), BMDP统计软件包5 s, G% z# U# a# V
Boxplots, 箱线图/箱尾图
5 e) \7 [. g1 o+ b. r9 GBreakdown bound, 崩溃界/崩溃点9 D9 c8 d4 V" \* ~* E; S6 R
Canonical correlation, 典型相关+ x+ @4 M: Y/ w) v- f' O
Caption, 纵标目
; ]% ~6 T) [3 n) ^; u8 Q6 o5 mCase-control study, 病例对照研究& z# u; n: |0 Y8 Y% S6 x/ q
Categorical variable, 分类变量+ Z% e# c0 t3 B) ~+ l* L; A
Catenary, 悬链线
2 T5 B& h2 g) {+ L% O7 k% g( LCauchy distribution, 柯西分布
k" f' r) |8 W# w8 d3 e" `Cause-and-effect relationship, 因果关系
5 u# i& w- W& m4 C- ]! bCell, 单元
' q$ X5 ?2 h+ U- V; r7 [Censoring, 终检
9 T6 Y0 C$ A" R* }1 g8 yCenter of symmetry, 对称中心1 ?4 C2 K9 S Z6 g' @$ W6 Q
Centering and scaling, 中心化和定标8 v8 J* u) _: |# [% H! ]
Central tendency, 集中趋势9 m7 s; W" ^2 I3 ~: K9 f/ h# A
Central value, 中心值" Z5 z% C* A! F; s" `5 ^ Y1 B
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
5 c4 r6 V( M4 ~8 P! _$ j; CChance, 机遇4 ?5 M% h* X" L @8 g' E4 p
Chance error, 随机误差
1 z' \* R+ K# V& p8 V8 x6 V, _: p$ R, [Chance variable, 随机变量
( S( z4 {0 Z4 q4 n$ T; M6 M! l' jCharacteristic equation, 特征方程; r" l! ]: `" a, V
Characteristic root, 特征根& Q- K0 c5 P& \% ^+ F
Characteristic vector, 特征向量
( o1 i' v3 l( c, L% |9 Y6 cChebshev criterion of fit, 拟合的切比雪夫准则
4 ?% N) g# I' yChernoff faces, 切尔诺夫脸谱图& z B, U+ {' K7 J! I- y
Chi-square test, 卡方检验/χ2检验
8 @7 {! P7 b* p; j0 x( U$ oCholeskey decomposition, 乔洛斯基分解) z2 S$ H/ {3 Q" p6 G
Circle chart, 圆图 # I( m/ z- f" Q8 ~( k
Class interval, 组距" ~( |8 i, t C7 _# d2 I
Class mid-value, 组中值) p8 o9 [$ e. t! k
Class upper limit, 组上限
, X0 W0 G) r7 bClassified variable, 分类变量+ H% d8 D" c- j& ?) t, q
Cluster analysis, 聚类分析" _# Z% \- t' v' u9 z
Cluster sampling, 整群抽样
- U @) a1 F( M$ X- eCode, 代码
/ h7 d; H w4 b# l! F7 YCoded data, 编码数据
# k# y* b" M+ f v7 `Coding, 编码
0 J; \8 L; l* Y+ ACoefficient of contingency, 列联系数+ P5 \* k2 x( w3 c) |! [
Coefficient of determination, 决定系数
2 j' [& A/ O, k# {) L9 R$ V7 zCoefficient of multiple correlation, 多重相关系数# a h2 Z3 d1 o
Coefficient of partial correlation, 偏相关系数
, ]' q. e6 V: ~; V. A! T" L1 fCoefficient of production-moment correlation, 积差相关系数
( T! P5 J: n" n2 E; s2 aCoefficient of rank correlation, 等级相关系数3 \$ N8 D* A. E: o0 N2 ]- O
Coefficient of regression, 回归系数$ q0 w9 m* I$ Y7 J
Coefficient of skewness, 偏度系数0 Q2 c0 L! g' D0 ?0 {, S6 }
Coefficient of variation, 变异系数7 C/ q5 e- L( P4 q( D3 w2 T
Cohort study, 队列研究
( v3 S) P+ E! J% c8 q( RColumn, 列, g# x$ u" \) y9 y# v& e4 r4 U
Column effect, 列效应0 D6 E) k+ M7 T- S4 m
Column factor, 列因素7 T4 b: d9 h" ]
Combination pool, 合并9 L+ }: L; e- I/ P9 n
Combinative table, 组合表$ f8 t& G3 B0 r
Common factor, 共性因子
9 a+ U- {7 y$ l0 v1 P+ iCommon regression coefficient, 公共回归系数( _: ~0 x( q4 J4 I
Common value, 共同值7 c# Y2 c( W9 @. h m
Common variance, 公共方差
7 @- K! I1 ~& f: G+ i" `; FCommon variation, 公共变异% T) u5 p: s( x4 \) \% p/ Z4 [; }' p e
Communality variance, 共性方差
6 Q# ^, d+ r) b/ RComparability, 可比性) y7 a0 E% X+ j, _( c# m E, y/ b
Comparison of bathes, 批比较/ Q3 e. {' V* e$ N$ v1 b6 D
Comparison value, 比较值) B* O) Q% L" ^" V' f
Compartment model, 分部模型. L5 q8 }# {2 o$ Q* n/ B) V. R6 T3 E
Compassion, 伸缩
1 P T. I( h( DComplement of an event, 补事件5 N# }* M1 i5 Z4 {) J
Complete association, 完全正相关0 V7 M& r! D) i. `3 I5 `
Complete dissociation, 完全不相关
5 I- b5 Z0 B1 @* qComplete statistics, 完备统计量; r% S3 t% r& }, O
Completely randomized design, 完全随机化设计5 w2 C! ^0 @3 {5 ?, e9 t, ~ j5 ]
Composite event, 联合事件5 h4 K: P8 k7 [
Composite events, 复合事件0 A/ g' z/ x D/ @: A. }
Concavity, 凹性: o4 s( y$ t7 W" }* D! [
Conditional expectation, 条件期望
9 @& M6 J+ m( T% Y/ {# G, q mConditional likelihood, 条件似然" v# G- d1 D Z4 y/ f' Z1 t
Conditional probability, 条件概率4 |1 t5 K+ S# f
Conditionally linear, 依条件线性" M$ L5 A: J: k* u; e/ K
Confidence interval, 置信区间3 d* T1 I# _8 _; N% G6 Z1 {8 N
Confidence limit, 置信限
: v8 b7 `) \. ?/ u- G7 L, hConfidence lower limit, 置信下限+ S( I$ `7 o8 W
Confidence upper limit, 置信上限
3 p; I- Y6 e- D7 @% j2 DConfirmatory Factor Analysis , 验证性因子分析1 [& V P3 F5 n: ~" O
Confirmatory research, 证实性实验研究
1 V2 M: b* T4 i! t# L3 kConfounding factor, 混杂因素8 Q) [+ Q2 ^: P- n5 o( ]
Conjoint, 联合分析3 x ]6 x0 J6 Q, c5 X% g
Consistency, 相合性
5 Y6 O0 M& V* T- W6 ~Consistency check, 一致性检验
9 }0 w$ l* r8 ?3 vConsistent asymptotically normal estimate, 相合渐近正态估计" Z, z3 k& s: }
Consistent estimate, 相合估计" |& I. F0 r/ }+ G5 {
Constrained nonlinear regression, 受约束非线性回归
! N6 [/ C* i+ F* t7 t$ ~Constraint, 约束* @7 d' z& Q& T2 D
Contaminated distribution, 污染分布5 a7 b8 h3 D7 O' E* y
Contaminated Gausssian, 污染高斯分布
, a& l! |% k! Z7 \- p' bContaminated normal distribution, 污染正态分布( {/ h* R* r& T( u9 O
Contamination, 污染
Z9 a+ m. o6 E3 L0 eContamination model, 污染模型
J' t' k- X; b$ JContingency table, 列联表
W) n! o: ?( G' z( FContour, 边界线
5 u2 K* I+ w2 g3 v3 n, CContribution rate, 贡献率
E, a% @1 D/ v1 bControl, 对照1 e: K* u7 Y' f5 D' N P
Controlled experiments, 对照实验$ n+ ^4 L; ]/ E& C' n
Conventional depth, 常规深度
8 m% X6 F+ G, b ^. U# D) BConvolution, 卷积
# l n1 |' X4 p! ]+ G1 vCorrected factor, 校正因子
' E) E# T ^2 h; QCorrected mean, 校正均值; r9 D( u5 H. z7 U* ~
Correction coefficient, 校正系数
5 Z6 P- n- M$ h5 |Correctness, 正确性
" C3 D. l) P! v, h. D' _: n& {Correlation coefficient, 相关系数
# {6 w9 k8 g* eCorrelation index, 相关指数9 _$ d$ S& X# w8 i
Correspondence, 对应
7 r2 D" X T4 x2 XCounting, 计数
+ t4 `; e$ P+ A' |5 r5 TCounts, 计数/频数
9 Q& w% T8 d" r& \Covariance, 协方差# Z6 `; T7 z2 |$ s+ g/ y# @
Covariant, 共变
5 u0 L. s/ b% n: _Cox Regression, Cox回归
5 @; b! `( J9 H9 t- J5 c% ~Criteria for fitting, 拟合准则4 T9 V, x o- ~! g6 p( y% _
Criteria of least squares, 最小二乘准则
* d" i$ A$ z: u& WCritical ratio, 临界比; U8 e6 e. g, J: Y" Y
Critical region, 拒绝域
' q. J/ q# `4 ]& {- q1 ~Critical value, 临界值% E8 V) I5 H; v7 i7 ?9 h1 S
Cross-over design, 交叉设计$ B1 [/ f* `+ @1 _- ?' ~
Cross-section analysis, 横断面分析) t+ {% f: \4 p6 X k/ D
Cross-section survey, 横断面调查2 x$ t/ k6 A5 D5 E9 o! b
Crosstabs , 交叉表 # D u( k, S$ j( H6 T
Cross-tabulation table, 复合表9 H; l/ ?0 l% D& \# x8 w9 n
Cube root, 立方根. ]4 ]( |3 f9 B1 Z
Cumulative distribution function, 分布函数
5 A, G, j5 `6 q' @Cumulative probability, 累计概率9 P& m9 B0 {) C1 H( i9 h
Curvature, 曲率/弯曲9 L7 K8 A! O$ T3 a1 N
Curvature, 曲率9 e; u, E% ^" F, e4 e
Curve fit , 曲线拟和 $ J9 L* U( N$ w3 R
Curve fitting, 曲线拟合
% ?+ n$ ^( |, y. D' v( s3 _& m. gCurvilinear regression, 曲线回归
1 e' y: d8 ?5 G1 s1 e$ {Curvilinear relation, 曲线关系& S! F% D3 z- {0 f; h- N
Cut-and-try method, 尝试法
. O: I7 c B5 C c. K8 d9 @Cycle, 周期- k& Q2 n& i9 | Q4 p
Cyclist, 周期性5 U9 W1 ~5 G1 y! R/ p* S
D test, D检验
9 Q O% W: \6 t7 X+ r% [Data acquisition, 资料收集
; Y# E! F9 b9 h( _3 ?9 uData bank, 数据库/ ~( |1 t; L" p' a
Data capacity, 数据容量: V0 A- E& D! J8 \$ i) L
Data deficiencies, 数据缺乏
( N9 u5 M6 V& b$ B6 \6 P5 XData handling, 数据处理7 U& k: |1 |$ D1 s0 b" n _
Data manipulation, 数据处理
+ x5 r% N4 Z% T yData processing, 数据处理" k- J$ ]+ x4 N- \: F( k/ u
Data reduction, 数据缩减6 C3 i; O$ C! E7 v) z
Data set, 数据集3 d3 u8 M) U. Z* W# G! x4 P" s! b
Data sources, 数据来源
$ Z" y& C4 i. ~& UData transformation, 数据变换
% D2 d) Y2 m P0 w, {/ GData validity, 数据有效性
0 k3 G; |- t; u: L" z" C: O1 TData-in, 数据输入1 l% ^# [7 c! K" X8 m3 x
Data-out, 数据输出4 J4 Y z* f/ V2 S [
Dead time, 停滞期
* S' q& G5 S6 Y; K4 D+ ADegree of freedom, 自由度; l* a* ?4 H# Z V# o
Degree of precision, 精密度9 F" x; c. |7 j- s( Z
Degree of reliability, 可靠性程度
- d! b! v% q1 n' `1 ?+ z. N4 {Degression, 递减1 K; P/ q8 x2 f7 h3 }! ^( F1 g
Density function, 密度函数
3 v8 r( w3 R: o2 FDensity of data points, 数据点的密度( ^& |4 S( G0 F1 F- S! q0 n: L
Dependent variable, 应变量/依变量/因变量
8 g5 e6 ^4 @* u1 j/ VDependent variable, 因变量
: S& D; @( I! ^0 Z8 p/ R, `; [Depth, 深度: L" P" }; `5 N/ \
Derivative matrix, 导数矩阵7 o5 r1 ` U' S
Derivative-free methods, 无导数方法
/ C' U' v5 c* t7 T9 Q8 GDesign, 设计, R# F1 n/ M# R; e
Determinacy, 确定性
+ F4 _2 e+ H* f S4 ?4 oDeterminant, 行列式+ ]- E1 c4 v7 @0 ~
Determinant, 决定因素& U: D! _- R! l: N% c( S9 T& w2 L9 }! x
Deviation, 离差
% A- i- F; o, k; g7 ]Deviation from average, 离均差
/ n* ]8 p) v# e& }, A$ B VDiagnostic plot, 诊断图$ \6 D2 p% W2 Y# P+ R+ O( T& l
Dichotomous variable, 二分变量$ K- M3 o/ ?; z1 Q- g* w1 B
Differential equation, 微分方程; Z; O! c9 b; x5 l- O
Direct standardization, 直接标准化法& u6 D/ {! g- v# v, c$ f! u
Discrete variable, 离散型变量
5 ^2 `( O/ e' n n! l3 A' n: YDISCRIMINANT, 判断
; d; u/ O7 L5 Z. ~0 |8 ODiscriminant analysis, 判别分析- {' H' K$ y: P7 X# L3 h
Discriminant coefficient, 判别系数' M% i' k4 F" { J) l# ~5 q; Z, _% f
Discriminant function, 判别值) _% {. L' P- `$ ?
Dispersion, 散布/分散度) {8 H# d$ o; q4 P9 `! a- Q
Disproportional, 不成比例的
8 Z* Q! @9 S. Y9 \: Q' {Disproportionate sub-class numbers, 不成比例次级组含量
- P; s% M$ w7 R( D! ^+ BDistribution free, 分布无关性/免分布% _# }2 G1 k4 ~4 s: _. v
Distribution shape, 分布形状
! ~# ?7 k* h. _ [: d2 i" a. c0 D" nDistribution-free method, 任意分布法
, v- S: \; q& N* X jDistributive laws, 分配律( ~: f g h9 P% K' a' g
Disturbance, 随机扰动项
+ e5 ?3 c, b6 C" d5 ADose response curve, 剂量反应曲线
/ g3 X( p- Q% a0 D7 X9 p6 LDouble blind method, 双盲法
- J5 W! u) o$ G- C, J! WDouble blind trial, 双盲试验
3 k, I/ U4 V+ V! z# fDouble exponential distribution, 双指数分布$ r: _& k, B% @
Double logarithmic, 双对数) H0 s' F4 ?/ E) ~) e! x; U+ i
Downward rank, 降秩9 I: a& y6 G, T7 X" p; M2 w
Dual-space plot, 对偶空间图
# E) o8 ]$ U( A# B b! FDUD, 无导数方法2 _1 s: ?$ j& X" j
Duncan's new multiple range method, 新复极差法/Duncan新法