S-Z
Sample, 样本0 _0 r1 T: k& g8 E/ m
Sample regression coefficient, 样本回归系数8 s/ O$ S( n) t" a d
Sample size, 样本量, A0 p) M* i" {) ?' u
Sample standard deviation, 样本标准差. d' G5 O1 P, i/ I1 c* X
Sampling error, 抽样误差
* `; ?+ v* X8 g/ g O- gSAS(Statistical analysis system ), SAS统计软件包9 j% z) k, y: _; e1 j
Scale, 尺度/量表2 m( M9 E/ J8 U2 K4 e+ { }
Scatter diagram, 散点图4 _. R9 d7 K6 R; [* P; x0 p
Schematic plot, 示意图/简图
5 x) v3 [* L, f' zScore test, 计分检验
6 K! G5 v9 B5 H$ [4 e6 z2 }$ tScreening, 筛检5 i+ s- D; U3 H V
SEASON, 季节分析
. U' J3 d2 L$ ~' f. GSecond derivative, 二阶导数
& e7 t5 I' \# y: iSecond principal component, 第二主成分
0 {9 C, H$ E) [& ]7 t9 q4 G7 fSEM (Structural equation modeling), 结构化方程模型
+ b* v9 t7 |5 U1 ]5 |7 ]6 [Semi-logarithmic graph, 半对数图8 ~$ \) K5 _: u: R$ [+ _" d2 p7 Y3 @
Semi-logarithmic paper, 半对数格纸: ^* } v O& z/ g) T6 e4 O: F; ~
Sensitivity curve, 敏感度曲线
f* ?4 u% U; y" V3 n8 P6 r) a$ H/ ^Sequential analysis, 贯序分析
& l0 k7 K+ l7 M, D% G' K1 c3 W7 kSequential data set, 顺序数据集
0 z' ~' O4 h; TSequential design, 贯序设计
& C5 p, J8 }8 ]Sequential method, 贯序法" J( n/ P% |. M, ~7 T1 N
Sequential test, 贯序检验法
& O) m. i: v* R& uSerial tests, 系列试验# t- c: X- e: z4 U/ N5 v% E; V
Short-cut method, 简捷法 % n+ D/ M2 R) W. j3 S- I `( G5 @
Sigmoid curve, S形曲线
1 F6 @5 z) }+ E# ]$ o) ^Sign function, 正负号函数
+ R- f/ m% F' W0 W( n- D- lSign test, 符号检验
/ g* N# B9 B7 Z0 D& pSigned rank, 符号秩2 d' u* O3 y! v# K+ ^
Significance test, 显著性检验" k. W1 ~& }9 ?2 D
Significant figure, 有效数字" y# f) x4 R0 v) \8 m& D% v
Simple cluster sampling, 简单整群抽样' f& t9 _, J0 Y. r% S: Q* C
Simple correlation, 简单相关4 x" m1 o- H; \& Y1 d
Simple random sampling, 简单随机抽样# Q0 S' @. S; v
Simple regression, 简单回归
! E$ u/ w7 I! F Isimple table, 简单表2 Y; C9 H/ W5 H& V
Sine estimator, 正弦估计量
' @4 M2 ~, ~% F0 [% j3 r$ D/ ASingle-valued estimate, 单值估计, j6 e' S& v. x w3 j* e
Singular matrix, 奇异矩阵
; l* F/ W: b8 P' V' dSkewed distribution, 偏斜分布
7 x) H; V# e# D9 _# }Skewness, 偏度# `5 e( {& W, a. P
Slash distribution, 斜线分布
* C1 s# t, U0 zSlope, 斜率. S8 e. F& H8 Y+ A* f' H8 I t
Smirnov test, 斯米尔诺夫检验
4 J% }9 V+ [ n$ O# t5 D8 {Source of variation, 变异来源1 D6 X2 N( c4 F7 S" [
Spearman rank correlation, 斯皮尔曼等级相关- R) K! y5 d2 d3 O% `
Specific factor, 特殊因子2 ~. S7 q; D) m9 S
Specific factor variance, 特殊因子方差, s; h2 d# Z" {2 {4 K5 b
Spectra , 频谱) a, R/ ?! l3 f1 t8 m% F5 V) b2 u
Spherical distribution, 球型正态分布
O# D0 q" ~5 m4 w! C/ U) K* G( NSpread, 展布* a( g4 j+ b+ K( e- o
SPSS(Statistical package for the social science), SPSS统计软件包
, j: D! j6 B0 ?; y5 {5 [: FSpurious correlation, 假性相关( F; c2 N5 ~ Z6 t/ T, ]/ V$ P
Square root transformation, 平方根变换
' \' S9 c: n7 p1 B/ t: NStabilizing variance, 稳定方差- x+ \& s- p. i% D$ v
Standard deviation, 标准差% q8 i% S' v! m f& k3 m
Standard error, 标准误3 Q" t. x3 ~( |; C! ?- v$ h( o
Standard error of difference, 差别的标准误
8 c6 E" z7 k" A0 ^Standard error of estimate, 标准估计误差- }; f F+ t$ \( y. {
Standard error of rate, 率的标准误+ r! C$ c1 o& m8 |
Standard normal distribution, 标准正态分布
0 @) e( P2 [5 c: pStandardization, 标准化. q- L* Q. s( a! b- ^9 P3 G
Starting value, 起始值
6 Q4 F, K! Y x& LStatistic, 统计量 P* D7 u0 J: J; O5 z
Statistical control, 统计控制
/ s; s j7 B6 ^Statistical graph, 统计图- @# F6 n6 ?6 e- ]' H. }* U
Statistical inference, 统计推断% S9 C# j. o% k: k5 }$ [* ?
Statistical table, 统计表
5 l$ R: Q( _1 [8 e+ B0 zSteepest descent, 最速下降法: s2 t6 I( N4 y/ k
Stem and leaf display, 茎叶图
0 }$ e" R4 G, `6 k* gStep factor, 步长因子0 G( S. |: |4 v/ `
Stepwise regression, 逐步回归
' @1 }7 `/ q! \, I( V& [Storage, 存. Q- |( ~, k, c0 F5 Q
Strata, 层(复数)
# M7 x s5 o! B/ S* y$ Z# M( rStratified sampling, 分层抽样8 k& n& M; ]- w8 I( y; y& e( x
Stratified sampling, 分层抽样& ? i' Y( o8 j& o# b
Strength, 强度% d Z0 F% Z; `, M
Stringency, 严密性
' x) D: ]2 ]0 n" e0 K. TStructural relationship, 结构关系5 C0 O* t' N0 J/ y/ R/ ~5 x
Studentized residual, 学生化残差/t化残差
! o3 h/ c0 x3 b% uSub-class numbers, 次级组含量
6 t' Y6 A8 `& a" Y! X+ f2 \3 [Subdividing, 分割
$ V# a2 N: j+ J5 PSufficient statistic, 充分统计量/ T3 }( I, s0 l" Q
Sum of products, 积和4 v# B; \$ F& b' A1 p- D* n, b. A
Sum of squares, 离差平方和
k+ v4 C5 |" ?0 s( ZSum of squares about regression, 回归平方和
' G' ], _* z) B R+ G) m+ n' T6 aSum of squares between groups, 组间平方和
4 ^1 o( J1 ?' _0 Z USum of squares of partial regression, 偏回归平方和
0 Z4 d! i u+ O1 v; h( s. n6 ] ~Sure event, 必然事件% C5 n3 E8 y; t
Survey, 调查- A1 S0 M$ p' t# Q
Survival, 生存分析1 ]* ?# X! \) ?; @
Survival rate, 生存率* J8 _. y: \7 O% P1 s- m9 B( p9 e
Suspended root gram, 悬吊根图
* R ?8 X& B2 N2 sSymmetry, 对称2 v' t& C4 v, g
Systematic error, 系统误差
/ K7 F, k: q) ?5 {1 m, ]! a# RSystematic sampling, 系统抽样0 [9 J' ~4 T* c! i9 Z3 q' G
Tags, 标签$ `, ^! X. r- u; H, i
Tail area, 尾部面积
" o$ A3 T3 ^6 C; F8 xTail length, 尾长
* e& _7 R8 ~0 q9 U4 GTail weight, 尾重! k' k/ I( H" Y8 V% W* D5 J) G
Tangent line, 切线
) q) F5 \7 X* a( zTarget distribution, 目标分布+ r$ e! i9 O1 u7 s# o% ~: x
Taylor series, 泰勒级数$ X2 q' `. V9 @/ B5 P
Tendency of dispersion, 离散趋势
- F b6 [9 V v, |1 z3 D. c( \6 \Testing of hypotheses, 假设检验% D! K0 _ \' U" n5 L: b1 S
Theoretical frequency, 理论频数. \+ H, A( K# z% J
Time series, 时间序列" S- I& {2 K' {- ` _$ j0 s
Tolerance interval, 容忍区间5 \( D, w. n5 q& ~ P/ v& r6 f8 W
Tolerance lower limit, 容忍下限
; A/ X( Q& B7 h: {' _% XTolerance upper limit, 容忍上限
& W% J7 v! y) Z5 f% o& ~Torsion, 扰率. y' R. m2 C% P
Total sum of square, 总平方和; S7 P0 S: @+ C2 _* G
Total variation, 总变异; k1 r8 O, w3 }. r
Transformation, 转换0 d% @: U3 J8 z! d+ ^! s
Treatment, 处理
. M( R4 h6 l. P2 a+ a7 V; @ VTrend, 趋势7 y8 K7 I( Y4 n* f# U$ w1 D+ h* W
Trend of percentage, 百分比趋势
% H1 ` \* G; L/ pTrial, 试验
: I p2 @$ y! l; dTrial and error method, 试错法
; P0 e+ R* f/ t: K7 f7 y' i! `Tuning constant, 细调常数
: ]; u! t% n. S1 tTwo sided test, 双向检验
0 w/ g+ j" s, CTwo-stage least squares, 二阶最小平方! O2 Y2 Z+ Q% S( M4 B
Two-stage sampling, 二阶段抽样
6 C5 R6 {7 k" ^. G/ L. |" JTwo-tailed test, 双侧检验
+ @+ s2 [* _3 K; ^; a0 lTwo-way analysis of variance, 双因素方差分析/ k' B+ R% M# q' e) T# b9 }7 l3 e
Two-way table, 双向表
$ E3 |6 F! t _) {. \Type I error, 一类错误/α错误
/ Z5 v. t q0 }9 tType II error, 二类错误/β错误0 P7 c5 X e" p" a
UMVU, 方差一致最小无偏估计简称) Q) l$ k$ x9 u
Unbiased estimate, 无偏估计% }9 v; u V( R6 M$ Q( o' _% @
Unconstrained nonlinear regression , 无约束非线性回归) @7 }1 }) \ d0 W
Unequal subclass number, 不等次级组含量
5 e. R; D4 x. T% q2 |# q; oUngrouped data, 不分组资料: V" y' o$ d: G& {+ x+ d, W
Uniform coordinate, 均匀坐标
+ x' V' d' Q/ T: n# q3 \& p. uUniform distribution, 均匀分布
, N) V" [4 d7 D; }Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计& m: w8 G' g5 j, h4 V1 P
Unit, 单元
+ D. ?0 @% y1 |Unordered categories, 无序分类0 I2 }. s7 k4 g8 j* M
Upper limit, 上限 m; L( I- ~( ]9 G$ e( r
Upward rank, 升秩 T4 h x- o2 L+ @2 c
Vague concept, 模糊概念6 h" T7 X# a; ^; Q! e+ C5 i
Validity, 有效性( w3 D1 D+ X' D3 Y8 M( m# O0 A
VARCOMP (Variance component estimation), 方差元素估计2 G) ~" |) x4 E# T
Variability, 变异性+ M8 M+ G& Y+ y* `
Variable, 变量5 w9 ]) G9 i ]) _3 W
Variance, 方差0 a4 T# \3 C0 W
Variation, 变异
2 p" O! l) F+ [) a' fVarimax orthogonal rotation, 方差最大正交旋转
" O# x1 R& Y7 x& k' j2 [% ~Volume of distribution, 容积
" a- _# g+ [0 J4 qW test, W检验, x: c6 K1 E2 q+ U- d) h# L1 M0 ~
Weibull distribution, 威布尔分布# w1 e1 v: F* H" B- C
Weight, 权数
5 _# _, K) o# G+ r% bWeighted Chi-square test, 加权卡方检验/Cochran检验* w, T! ?! O6 p; s
Weighted linear regression method, 加权直线回归 e2 q4 O; F1 t* t& j3 \/ Q, s
Weighted mean, 加权平均数
s( T5 p8 v; A8 ~2 s( i! LWeighted mean square, 加权平均方差* n* Y* ]7 w' ?! M5 e8 T" d
Weighted sum of square, 加权平方和
9 w# H" E4 |$ q9 o% kWeighting coefficient, 权重系数
8 t& g& G! z3 Q5 L) \: KWeighting method, 加权法 2 y% c- J1 z+ Q- t1 q' N
W-estimation, W估计量3 E: n& Y* I! W3 A. v
W-estimation of location, 位置W估计量
7 K6 r p$ R$ h6 n( WWidth, 宽度
% z) A& y* ^+ o( nWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
, Y: ]5 a4 g/ _/ ~: P4 w, s1 `0 RWild point, 野点/狂点
- {: Y' S+ I. g$ MWild value, 野值/狂值) z/ s& Z6 [( z/ W
Winsorized mean, 缩尾均值
% Q$ h5 s F! v, Q" _8 _Withdraw, 失访 1 b# J M! L$ f+ h# R" }
Youden's index, 尤登指数: J# A5 \- u9 Y% l+ J
Z test, Z检验
) U& r% N+ ^: g( U- @Zero correlation, 零相关0 t6 O; o2 x$ ^
Z-transformation, Z变换
M-R
Main effect, 主效应
2 ?& |6 _. _/ ~4 F, n1 N0 yMajor heading, 主辞标目
- M8 H% e3 W' U: k3 yMarginal density function, 边缘密度函数0 ~$ r! m8 {1 R" b* T
Marginal probability, 边缘概率) _4 G2 Z! r6 q7 n$ ~
Marginal probability distribution, 边缘概率分布
d+ a* `+ Q9 y- `. Z1 X! |5 pMatched data, 配对资料
, Z4 c8 R- P8 t S0 q' n) EMatched distribution, 匹配过分布7 g+ `+ z, X" o0 L
Matching of distribution, 分布的匹配! J4 |: o. ^) a2 \: H( Y1 u7 V
Matching of transformation, 变换的匹配. Q; o0 l6 f0 L, ? f
Mathematical expectation, 数学期望
( x- [ g5 c6 ^% q' H# y# {Mathematical model, 数学模型
, h `9 l) d v5 pMaximum L-estimator, 极大极小L 估计量' V& { C8 O( l- R. a8 I# U
Maximum likelihood method, 最大似然法9 ?) K$ c3 {0 P9 M
Mean, 均数
5 F2 q- v0 B) eMean squares between groups, 组间均方6 P+ _/ f4 b- A$ |2 M: w# x
Mean squares within group, 组内均方) _- R! |) N P4 X" O, b: d
Means (Compare means), 均值-均值比较1 ?! K7 g- b' V9 i; ]7 T9 c Q; m
Median, 中位数; E4 M" }3 `) a0 K M6 ^ ^" D( |
Median effective dose, 半数效量
9 [& \. X, V& H. Y2 WMedian lethal dose, 半数致死量 Z7 O/ l% U6 O( S6 K7 q4 f
Median polish, 中位数平滑
" }8 `( R! M l9 NMedian test, 中位数检验
/ n/ Z- w& l; C, J O* JMinimal sufficient statistic, 最小充分统计量: @8 C2 i/ F* B2 U1 A) z8 M
Minimum distance estimation, 最小距离估计; X9 Q+ c) I- B/ _, g" H: ~
Minimum effective dose, 最小有效量3 w& b- L5 p$ J, p. j- p" L
Minimum lethal dose, 最小致死量
( G: R Z- t0 x6 r% U% y, EMinimum variance estimator, 最小方差估计量
8 y9 U4 m2 K% zMINITAB, 统计软件包
: t1 _ Q3 f+ f+ y+ M7 uMinor heading, 宾词标目
4 k% j/ a, J3 P) Y+ R B" \Missing data, 缺失值
- ^' d# w. a/ ^1 p2 ~Model specification, 模型的确定
7 O3 `0 t$ L: z; ?* r3 wModeling Statistics , 模型统计
2 \8 o2 m% ?; @0 Y+ U: QModels for outliers, 离群值模型
Q, M# m) P6 L. S% Q( Z2 IModifying the model, 模型的修正0 W* d. \: O. t, {5 _9 Z
Modulus of continuity, 连续性模/ Q# \7 O: y* g" E$ N. s0 c
Morbidity, 发病率 3 @3 M& s" \" c
Most favorable configuration, 最有利构形
, e+ T+ _7 l5 UMultidimensional Scaling (ASCAL), 多维尺度/多维标度
- Q v! ^7 z7 @/ W, d& B0 w6 IMultinomial Logistic Regression , 多项逻辑斯蒂回归
3 i3 C; K" R" I( M' W; TMultiple comparison, 多重比较
- c9 F' o4 E( L, X9 D# u' |' [/ ]2 EMultiple correlation , 复相关
( b% \" r+ y, m! _4 hMultiple covariance, 多元协方差
5 c: M" \# {9 h7 V5 U! C" sMultiple linear regression, 多元线性回归
! L( |( \! K9 R3 UMultiple response , 多重选项
2 x6 ^" |" W. E+ w. hMultiple solutions, 多解
- ~& o4 [! }* uMultiplication theorem, 乘法定理
& P- F( M+ f' XMultiresponse, 多元响应
) m' L+ G. P6 ~5 O- {2 x S2 iMulti-stage sampling, 多阶段抽样
5 G) g. c7 P8 \# ?Multivariate T distribution, 多元T分布+ d4 m5 A, i6 k! L
Mutual exclusive, 互不相容9 C4 [+ v* [# g7 A& V- U4 j
Mutual independence, 互相独立
4 D& ]% `; P4 z: c, K5 o- ?1 U8 uNatural boundary, 自然边界- b: X$ X" D% L Q) e7 m. y2 G* j/ l! E
Natural dead, 自然死亡
5 p% t" _ |% z" PNatural zero, 自然零
6 j0 E3 A7 k0 INegative correlation, 负相关$ x1 [0 k; t4 f( S
Negative linear correlation, 负线性相关
! H; l* c. ^* p) G4 B" f) TNegatively skewed, 负偏
0 {" J$ N) x: g6 U2 fNewman-Keuls method, q检验
/ M8 @! \: p" |% a( C; e3 `NK method, q检验& B7 q& j S5 i
No statistical significance, 无统计意义
: u3 p0 N2 u% p( t( c# q, INominal variable, 名义变量
' T; U* f( }9 F/ v$ t' ~Nonconstancy of variability, 变异的非定常性1 _8 t" O5 x/ B" m% H
Nonlinear regression, 非线性相关2 x& o j( M3 D: U5 h, ]
Nonparametric statistics, 非参数统计2 w9 a* H5 ?1 C0 J6 Q: N5 B8 L
Nonparametric test, 非参数检验
, T3 ^8 E& ]* B5 y+ B. gNonparametric tests, 非参数检验6 h' ?1 m% l+ _" w9 }/ u, z1 R
Normal deviate, 正态离差
- M2 k1 a I, G4 x$ N: s5 @: ` RNormal distribution, 正态分布' F: }7 @4 x4 m' O! d3 Z7 E
Normal equation, 正规方程组0 K# U4 N$ P. b. P# m, q
Normal ranges, 正常范围( H. Q6 M( u2 J, [) s
Normal value, 正常值
# O# w. G5 x2 \' @Nuisance parameter, 多余参数/讨厌参数
5 u& N$ O9 g, L. ~- v" l9 {% DNull hypothesis, 无效假设 ! v( X* C6 y7 U' U0 ]: a/ h, K& M
Numerical variable, 数值变量1 G5 J( Q4 Z0 k4 j- X. }6 X6 c) P
Objective function, 目标函数3 C& u" E: z6 r& i/ E/ } C
Observation unit, 观察单位3 k4 L) f9 p `" s. B5 A- K* y
Observed value, 观察值
t2 J7 C( r0 Q) h( C+ b3 L" E+ DOne sided test, 单侧检验
7 q6 |/ T/ a0 I4 {& V- L/ XOne-way analysis of variance, 单因素方差分析! `, ~" \3 B9 d. O! Y
Oneway ANOVA , 单因素方差分析6 e$ i* K: t* i
Open sequential trial, 开放型序贯设计
& b: _8 k9 G. \$ W( x. |" ]Optrim, 优切尾
) z+ j! g9 S9 v9 |Optrim efficiency, 优切尾效率
- i$ C( _2 H) F+ S6 h3 i+ `2 pOrder statistics, 顺序统计量; O/ n; [( |8 l, p
Ordered categories, 有序分类5 b, u/ }6 n& r0 i
Ordinal logistic regression , 序数逻辑斯蒂回归
, T+ K& a2 T6 T% ^ q) z6 U' I3 J5 |Ordinal variable, 有序变量
! L7 D! @4 k+ u: }2 wOrthogonal basis, 正交基
o" ~$ e6 v4 f( bOrthogonal design, 正交试验设计
2 y: H% O6 h# @0 P" LOrthogonality conditions, 正交条件; n2 Y; H7 A: X( I
ORTHOPLAN, 正交设计 / o& T" h+ X) H2 y5 p+ ^7 f
Outlier cutoffs, 离群值截断点
6 A6 B- S* L- C, ?1 {& _ dOutliers, 极端值
1 V* x, x0 y L, z& j! EOVERALS , 多组变量的非线性正规相关
7 [6 p2 N9 c4 T+ t1 s% wOvershoot, 迭代过度8 G6 a" o/ r$ X8 a3 L- f: \+ [
Paired design, 配对设计- p1 M; }5 I2 }2 ^4 |! |* h
Paired sample, 配对样本7 \; ~7 i6 m' G6 a/ @
Pairwise slopes, 成对斜率4 A( o, B- r. p( O0 w3 L* B
Parabola, 抛物线
" T# s% m# \0 l% TParallel tests, 平行试验 Q7 |: ^5 d1 A! t; P2 f
Parameter, 参数
# j% x* P* b2 |Parametric statistics, 参数统计
6 y/ X# W" C; IParametric test, 参数检验, t3 {: T3 a6 ^& _1 D6 p
Partial correlation, 偏相关
6 _2 P7 r! b) F& R9 I) }Partial regression, 偏回归
4 s$ ^5 m/ T0 ~/ G, _Partial sorting, 偏排序- y. R/ w- V* l) w" E' E3 A
Partials residuals, 偏残差7 F: m' ]% g, u8 J/ S
Pattern, 模式2 V6 ^/ _8 B( d+ e
Pearson curves, 皮尔逊曲线
; u8 b8 p I% a% F0 h2 h5 G: vPeeling, 退层
8 u- B6 y9 ?9 {4 d9 `2 i4 P8 R8 Y9 LPercent bar graph, 百分条形图) d% S3 W8 M9 B2 {
Percentage, 百分比" T- T6 g, n$ }0 u" n
Percentile, 百分位数
- {+ E! p1 @; R8 u" `, VPercentile curves, 百分位曲线+ Q$ k% g* G' }! {3 c/ B
Periodicity, 周期性' x7 H3 u2 r% c: B5 O
Permutation, 排列
) _1 n) B) U4 w) y& A# bP-estimator, P估计量7 ?0 c/ `: @0 U3 d
Pie graph, 饼图, k j' O& W! q: }$ y' |( M# |1 v
Pitman estimator, 皮特曼估计量
( I b% H& g' E6 K) ?8 CPivot, 枢轴量
+ K7 E6 P' ~% l9 W6 m# IPlanar, 平坦8 d [* z9 o, z, l, q* ^4 M( ]
Planar assumption, 平面的假设
0 _9 h' s' n/ SPLANCARDS, 生成试验的计划卡# J" T* N% f+ f q
Point estimation, 点估计
' I+ i. J3 J% X# H4 s3 s7 _Poisson distribution, 泊松分布
1 W- A- r8 o. TPolishing, 平滑8 N1 s2 E% G) ], \8 Y& V" `! C
Polled standard deviation, 合并标准差' t; @ s1 I. M: w8 k- C% q
Polled variance, 合并方差
! w4 Y5 B, C J% DPolygon, 多边图; j0 \2 Z9 n1 N
Polynomial, 多项式
. K7 l4 [7 T6 z- l8 uPolynomial curve, 多项式曲线3 b2 c* Q+ D1 _( }: W- w D( a6 I
Population, 总体6 n2 @+ [6 h+ l; j4 N t3 U M$ } y
Population attributable risk, 人群归因危险度
! E5 P. O, b8 `( j* I6 dPositive correlation, 正相关# j/ Q+ d; b9 c+ T! g* [
Positively skewed, 正偏
& K4 C/ a0 \5 g+ V2 f( dPosterior distribution, 后验分布& h% |; U9 p: T8 }$ |3 X8 A
Power of a test, 检验效能0 i6 W2 ?3 y% q* @; b
Precision, 精密度
3 S+ j0 W9 C5 \% Z# c% S" LPredicted value, 预测值
2 P9 d3 l8 j# CPreliminary analysis, 预备性分析5 h# U) Y" F& G, V( J( [
Principal component analysis, 主成分分析$ A/ g1 r7 H4 X8 O
Prior distribution, 先验分布
+ M) t+ m7 O" j+ |0 Q0 O* RPrior probability, 先验概率
. \7 C) h5 f+ ^; ~) iProbabilistic model, 概率模型
$ b6 T; S( w/ h& n; M3 ~probability, 概率
0 S4 q- n7 I2 t! ]' j% vProbability density, 概率密度
' G/ u8 U& _5 Q' \5 s4 dProduct moment, 乘积矩/协方差, b. a, \6 o s, h; u
Profile trace, 截面迹图* w s( x' W- t
Proportion, 比/构成比9 r/ C" i$ M' w8 V/ A
Proportion allocation in stratified random sampling, 按比例分层随机抽样- }; b' v* }: F; I7 {5 z
Proportionate, 成比例( g c+ K$ e s$ d3 H! G3 U/ D3 G Z
Proportionate sub-class numbers, 成比例次级组含量
y# @* Z6 q/ |1 n9 w7 w. K/ _Prospective study, 前瞻性调查( ], y1 ]) I/ j) v* S
Proximities, 亲近性 % A" N0 q5 e3 D2 b
Pseudo F test, 近似F检验
+ Y5 |! K5 F/ H" E% U. bPseudo model, 近似模型
' ~; j/ {8 M3 Q; KPseudosigma, 伪标准差5 P$ A n( _# ^, ^9 @2 u
Purposive sampling, 有目的抽样
3 Y3 R/ e. Z2 ^4 ]QR decomposition, QR分解
9 A; X! }5 T2 Q/ w7 t5 QQuadratic approximation, 二次近似2 k- n# l* m/ n9 |) |$ F
Qualitative classification, 属性分类
; U a; |: j* |5 v ~! R) H NQualitative method, 定性方法: I' O/ ]2 m; ^" p, H9 [$ b/ I
Quantile-quantile plot, 分位数-分位数图/Q-Q图
& G' i* G" T# W9 j: ]Quantitative analysis, 定量分析' a8 P+ `( |' d I0 j& A6 Y1 H7 ?
Quartile, 四分位数
0 c. b9 @ {# g1 k- ~% ?6 ?Quick Cluster, 快速聚类
) T _" z1 I$ O. s) TRadix sort, 基数排序: `3 K( |$ X) \' `% L; L
Random allocation, 随机化分组, ^/ |7 o3 _. [
Random blocks design, 随机区组设计( J* i0 g4 r" E( o
Random event, 随机事件* m3 O& V; t% r4 V$ r. `8 D" A4 u
Randomization, 随机化5 n% o5 R9 f3 ?' X
Range, 极差/全距: L: V5 u1 V0 M& ]( F6 x/ N
Rank correlation, 等级相关
. c8 H) \3 a% w- H5 v& |- z2 `Rank sum test, 秩和检验
5 j$ c% Q U+ RRank test, 秩检验
M" V6 t/ j' {* rRanked data, 等级资料
3 \# G" q. e3 r* ~Rate, 比率 a* y! H4 {. c) s Z3 }8 P
Ratio, 比例3 M0 K( T/ X% f$ l% n. Y8 k: @7 V' Z0 u
Raw data, 原始资料( ~$ |, @1 q" ?1 t# e! M
Raw residual, 原始残差$ K! A: j# F Z8 D* W0 o$ a
Rayleigh's test, 雷氏检验" U: p: [% U3 w9 I' J
Rayleigh's Z, 雷氏Z值 8 B/ n5 K' T' c/ h6 E Y1 ?
Reciprocal, 倒数
0 m; P/ s% E# s/ J+ d3 t5 xReciprocal transformation, 倒数变换
1 s" Z( D/ I3 xRecording, 记录/ M& r0 T+ C; a+ L% s
Redescending estimators, 回降估计量
0 c' B/ C7 y% Y. L7 r2 _Reducing dimensions, 降维
8 n8 r- E. u2 H' E% P. E& CRe-expression, 重新表达
9 D2 d1 p/ o% VReference set, 标准组
! o( V' c9 a" n9 zRegion of acceptance, 接受域
* j8 {( E- A. NRegression coefficient, 回归系数
8 I4 T) l/ P& BRegression sum of square, 回归平方和 , o& z' }1 ^: M0 \$ T
Rejection point, 拒绝点& F9 A1 M, o+ f. y$ |
Relative dispersion, 相对离散度
) _4 F; U6 @5 V7 L" ]Relative number, 相对数8 B- R+ ~: a# g# u
Reliability, 可靠性
C& c, e7 C# s/ l7 OReparametrization, 重新设置参数
% K3 Q0 q2 i7 AReplication, 重复
" c& h3 _. i9 dReport Summaries, 报告摘要 b1 l" I, @0 v/ U3 o
Residual sum of square, 剩余平方和 j, g* X$ F' }6 D
Resistance, 耐抗性* ~5 K; ~9 E& a
Resistant line, 耐抗线
" `, J- L1 ^" J8 g" a* u, o/ M, Z4 p% VResistant technique, 耐抗技术% U' K! i3 w% c
R-estimator of location, 位置R估计量
, W m# _ I: a; a& QR-estimator of scale, 尺度R估计量
N1 E0 k' O9 ^( bRetrospective study, 回顾性调查
# i5 A6 ^6 u4 u. m! ]Ridge trace, 岭迹
4 T1 f( q& X; j# j* Z" ^1 p0 nRidit analysis, Ridit分析# s+ g- q1 y/ e
Rotation, 旋转8 a) N1 ] x, C; q
Rounding, 舍入
8 L, R2 z" T/ gRow, 行0 u- j( l7 b5 `4 m0 e6 o3 j
Row effects, 行效应$ I- w& X5 R( V D/ Z/ H
Row factor, 行因素( Z5 B' p4 n) P5 p" Q- O8 F: X
RXC table, RXC表
E-L
Effect, 实验效应7 D8 T$ z6 Q8 m
Eigenvalue, 特征值7 N" n" S$ i% x! w1 s; y9 h9 h5 k, d: M
Eigenvector, 特征向量1 _$ R( ~( t6 i1 H" I) v
Ellipse, 椭圆: H# H# T: l. e5 K# Z' P5 k+ b: O" O
Empirical distribution, 经验分布
7 p% `1 L& [1 j8 ?- J+ R- J* P1 sEmpirical probability, 经验概率单位
- j" @% d' A' ?* y# |& kEnumeration data, 计数资料
/ s* P, U6 q" W) xEqual sun-class number, 相等次级组含量
9 M+ R* b( Z3 q4 KEqually likely, 等可能
. J) i. X0 N- ]6 g# o R, `6 xEquivariance, 同变性
4 p7 m+ b( J* a* G7 r( k! e# T; @Error, 误差/错误
$ \( }! U2 d5 v" CError of estimate, 估计误差7 f) t; ] ?* `3 l; l9 g0 R2 q9 r
Error type I, 第一类错误* y4 U' J5 ?- n- n) O; \5 d- J
Error type II, 第二类错误
$ a S& a3 j. [. u7 BEstimand, 被估量
. E2 F7 X4 m6 tEstimated error mean squares, 估计误差均方. k, W6 l6 C& E6 A
Estimated error sum of squares, 估计误差平方和
- ?; p4 g. Q% U* t! L2 F1 e& bEuclidean distance, 欧式距离
) ~7 I7 j( h. U( C' ?Event, 事件& W( z" o; r+ ~$ @! g
Event, 事件
/ O# F3 s- n+ QExceptional data point, 异常数据点. y5 G3 W" u# {# X; @; {
Expectation plane, 期望平面
1 r& D5 s* I) P4 ^* |6 h; X/ SExpectation surface, 期望曲面2 x# @) D. F8 W p5 a
Expected values, 期望值
$ ^$ P. K$ k5 t0 ~" U. lExperiment, 实验: p2 z: A- \6 l: |+ x
Experimental sampling, 试验抽样; b" Y, t0 X' s: @! ^% [
Experimental unit, 试验单位- D, |" l* K& e% o6 I
Explanatory variable, 说明变量+ N+ I) o( |# l3 o/ u
Exploratory data analysis, 探索性数据分析
1 Q, |% K! l4 W3 f# v5 K) d- ?Explore Summarize, 探索-摘要7 u2 g" m& `2 D; s T
Exponential curve, 指数曲线. A9 U( @7 m: G4 F W: `& G
Exponential growth, 指数式增长
+ @$ m2 V: m- L* u+ ]EXSMOOTH, 指数平滑方法
% A- n3 }) A0 G- Y/ LExtended fit, 扩充拟合
2 q6 @7 T: F/ O! lExtra parameter, 附加参数
* j( Z+ }- n$ B6 }' aExtrapolation, 外推法, @) j" t: B4 M, l1 P* j2 \$ f
Extreme observation, 末端观测值
/ i3 W$ I' m. s9 uExtremes, 极端值/极值9 @; t2 J7 C/ C$ j2 a) _
F distribution, F分布& Q! ~1 x8 w; Z) d: L# w0 t
F test, F检验
4 i6 ]8 F( b! }3 G* Z3 qFactor, 因素/因子
0 n+ `+ N* ]1 ?% @7 X& a0 Y& YFactor analysis, 因子分析0 t0 y8 K7 q% g% E( \) _
Factor Analysis, 因子分析
# g, r# S2 d1 c" G4 ? H4 R/ bFactor score, 因子得分 J" J @' |+ q* @4 R M, t& ?1 Q
Factorial, 阶乘
6 ~* U# z8 I5 MFactorial design, 析因试验设计# o- `* M* T8 Y2 D, j! W" B* \
False negative, 假阴性
) u5 k& f9 g! x% r+ cFalse negative error, 假阴性错误
7 L+ s5 w/ D. u: K6 X& l+ B4 g' XFamily of distributions, 分布族. M6 d$ S' H& U4 d& {, U3 l
Family of estimators, 估计量族
; [' N) M0 ~5 J( ]8 DFanning, 扇面2 q! P$ B& A, @4 L
Fatality rate, 病死率
- M1 I/ d8 w: ~8 r, F$ nField investigation, 现场调查
, a6 A7 ^8 K( }/ Q6 @Field survey, 现场调查6 C; l4 H& \* k+ Y, N E7 t! c: b
Finite population, 有限总体
. F7 b* ]( G# k1 {& z' qFinite-sample, 有限样本4 F& T5 g# J$ k, B$ c) c. {( Y& y% n- h2 V
First derivative, 一阶导数 / W( E, c" t( T1 F" m% S$ `
First principal component, 第一主成分9 Y. S# M, _. g6 m& y
First quartile, 第一四分位数
) S9 ?/ V0 q) P) i) q' xFisher information, 费雪信息量
! Y: W0 Z# B4 e4 LFitted value, 拟合值9 E9 [& Z' Q! R. K
Fitting a curve, 曲线拟合1 [& V% E$ ~: M
Fixed base, 定基$ }: W: f5 n2 N4 u
Fluctuation, 随机起伏
' Y' E, z# e5 n- D- c+ nForecast, 预测
5 o- x6 g5 X5 h; M9 TFour fold table, 四格表 P4 n3 ^: H8 m, N" { y2 ^9 I: O
Fourth, 四分点
) k0 _' }5 h" y8 AFraction blow, 左侧比率! H' Q! j; |) i. S& \1 v& Q
Fractional error, 相对误差1 g$ a0 ^: i; M$ q1 N. F4 W5 {
Frequency, 频率0 r; m5 a3 H- F3 t% n! ^% X
Frequency polygon, 频数多边图
% o$ S( _, ?& h oFrontier point, 界限点
& A L" }) n2 t/ s! b7 l, CFunction relationship, 泛函关系
7 ^/ G: z$ D& Y2 {& s) jGamma distribution, 伽玛分布
4 A) i, k: N! \, O$ r- Q# }Gauss increment, 高斯增量
/ j, i, i, v+ @4 J0 f& ?# O* eGaussian distribution, 高斯分布/正态分布
7 ?# N& X* e, w0 [+ c# n5 B0 sGauss-Newton increment, 高斯-牛顿增量+ T0 b! ]( L. J* a( j4 [& A# T9 D4 f
General census, 全面普查
+ x3 J4 H w- A3 N# J+ |GENLOG (Generalized liner models), 广义线性模型
+ n! L0 Y% D2 ^$ N; [Geometric mean, 几何平均数
1 T7 V% o2 \. Y8 r5 O; `Gini's mean difference, 基尼均差3 `2 J$ l- r; G. Q# S9 `/ p
GLM (General liner models), 通用线性模型 % W$ B- b( ^+ C9 ?. z7 S. Z
Goodness of fit, 拟和优度/配合度
' n+ L+ m- h. y/ x6 WGradient of determinant, 行列式的梯度
5 s, U: c, l0 { kGraeco-Latin square, 希腊拉丁方
6 _, A; P; V+ v/ L$ R0 vGrand mean, 总均值
+ a% p/ n, @) m& r: T' \3 tGross errors, 重大错误4 k: w- w \, ?! v( |
Gross-error sensitivity, 大错敏感度
* e5 S+ r% o" ?Group averages, 分组平均& D2 L$ o0 m" N- |( `" v% v* q
Grouped data, 分组资料, ]- t, I* c3 L! b" ~7 e7 V
Guessed mean, 假定平均数
9 T7 R3 _0 U. u" U1 c- g: r0 wHalf-life, 半衰期
0 o8 |% q7 a; u3 F& @" EHampel M-estimators, 汉佩尔M估计量
! C6 }4 G$ \) b. m6 ~6 y9 ~Happenstance, 偶然事件
2 F, S8 V! B1 W" l$ }Harmonic mean, 调和均数& C) z/ C6 q3 P9 ?7 S4 ]2 r/ P
Hazard function, 风险均数
/ Y$ G4 E8 }; ^- c1 d& n% THazard rate, 风险率
) E8 @ S2 K- C3 h2 G$ P9 N/ pHeading, 标目
- B: I; k' r1 x3 P( S" h _9 {) eHeavy-tailed distribution, 重尾分布: x0 o& |! U! \' l; `
Hessian array, 海森立体阵
' M* b l& n% ?0 LHeterogeneity, 不同质. S* L* Y% h1 d# w
Heterogeneity of variance, 方差不齐
b0 L/ _" c& @Hierarchical classification, 组内分组
: O" | q; L- y& ^1 g& K$ ?Hierarchical clustering method, 系统聚类法
4 {& D. r1 \- H0 J4 [High-leverage point, 高杠杆率点
( c) z8 m v8 v* q# SHILOGLINEAR, 多维列联表的层次对数线性模型% ]* c' {9 D0 R
Hinge, 折叶点: X7 q5 O1 d" a( q# G
Histogram, 直方图6 [8 h2 Y# U2 r1 U
Historical cohort study, 历史性队列研究 # q7 u, D- L, M3 e0 R5 \. s
Holes, 空洞8 ]0 b9 D% v+ \* z7 h5 n3 W6 n& A5 y
HOMALS, 多重响应分析; A/ u( d+ r+ l3 K6 x" M) K
Homogeneity of variance, 方差齐性' M- O: M# M9 `" r9 v* {* Z! |8 O
Homogeneity test, 齐性检验# `7 k' J1 P- x F7 e7 V
Huber M-estimators, 休伯M估计量
0 v$ K$ g2 h# N5 e( F0 }& U. tHyperbola, 双曲线. q( e1 w9 K2 R: e3 M
Hypothesis testing, 假设检验2 P' E. z1 T, b. t |3 A
Hypothetical universe, 假设总体
$ z3 C4 L6 V' D# U8 }; t9 oImpossible event, 不可能事件
9 O/ L' q D/ O2 Y- l1 F2 S, eIndependence, 独立性
/ m- p! D( W+ G; Y- l. a$ q& @Independent variable, 自变量
6 X0 R+ K+ X g2 gIndex, 指标/指数# g% B: s V/ K
Indirect standardization, 间接标准化法$ x* d+ f' O/ P" e7 ~8 I
Individual, 个体
2 q2 ?, n3 e5 n7 A/ IInference band, 推断带
8 b; W# G% [6 o5 e& Y7 _! E, D' \" BInfinite population, 无限总体
, b8 |( U' B" s" ZInfinitely great, 无穷大
* h" |4 `$ @ `6 M/ h7 `4 eInfinitely small, 无穷小
; i( I8 x+ b, S8 ] e: LInfluence curve, 影响曲线& R6 Q4 a, }4 m8 o* v4 p& ~
Information capacity, 信息容量
; C9 a+ w) R$ h, }, J, IInitial condition, 初始条件
- D& m# O0 e+ W' s- a0 aInitial estimate, 初始估计值
; Q$ g* L$ T9 w0 xInitial level, 最初水平
# @: R2 z g( B* f, B" o: x/ AInteraction, 交互作用. w* w0 |. T5 W' A. X7 |8 x$ {
Interaction terms, 交互作用项( N% D: \& {& \6 j: `! `( Z( L# Y
Intercept, 截距' B% k, g# R5 ^2 Z
Interpolation, 内插法
i# }' K3 X# t7 ]Interquartile range, 四分位距
$ |( ]8 }: I( N( T& C" X# {2 q8 qInterval estimation, 区间估计
/ ?3 `+ Q v* y2 f' qIntervals of equal probability, 等概率区间. O* [) x: b3 O! b4 [% s3 h& l9 J
Intrinsic curvature, 固有曲率
4 o2 ~) R" f& n% |9 }Invariance, 不变性, n$ b5 N# Q' y4 O( k0 s
Inverse matrix, 逆矩阵
* i1 \' s# Z* `) D2 Q" wInverse probability, 逆概率3 N. o/ x+ ]4 f; P2 F
Inverse sine transformation, 反正弦变换
* {8 X6 P% i2 {, @# u* QIteration, 迭代 5 l; X- t/ ^8 A+ c$ z2 v+ G" F
Jacobian determinant, 雅可比行列式/ D4 B) p$ I" D9 E- Z6 B
Joint distribution function, 分布函数
' c2 m8 |/ t( l4 g) M% y1 hJoint probability, 联合概率2 g5 a2 G2 t: h7 u$ |! W
Joint probability distribution, 联合概率分布# `! F2 | T' x' `
K means method, 逐步聚类法$ y1 @9 a3 {' b
Kaplan-Meier, 评估事件的时间长度 3 E7 F7 H; j5 {, }+ o0 v
Kaplan-Merier chart, Kaplan-Merier图
; L1 E% t% ~% f% q+ B* wKendall's rank correlation, Kendall等级相关' ]5 M9 d# ~ ?6 E5 }4 X
Kinetic, 动力学
6 n$ t' w# y8 fKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验, [5 [" h: q! {; |$ e
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验9 ^/ i+ m' Y4 n! `
Kurtosis, 峰度" u/ c) R5 e ?
Lack of fit, 失拟# _( q! V1 S9 m9 k; \
Ladder of powers, 幂阶梯 v$ L7 K8 N m7 D
Lag, 滞后) ]! F2 E/ A$ c+ M1 q
Large sample, 大样本$ Z7 c1 T$ i" j
Large sample test, 大样本检验) n8 X' h/ b! j4 c$ }; c
Latin square, 拉丁方; a0 I/ W* x5 K8 B% w4 F
Latin square design, 拉丁方设计
: u7 b8 Q, F! u5 MLeakage, 泄漏& s- O0 B s2 M9 ?) `% d
Least favorable configuration, 最不利构形! f- W# g0 T Q/ u
Least favorable distribution, 最不利分布
( h. O# @* M+ ULeast significant difference, 最小显著差法1 B: F) A8 i# w5 |1 S1 |9 c
Least square method, 最小二乘法, w" Q2 k" z! l, n4 n8 l' c- e3 n
Least-absolute-residuals estimates, 最小绝对残差估计# e6 n$ F, y1 I6 j
Least-absolute-residuals fit, 最小绝对残差拟合
( `' w. Y0 e6 u6 @Least-absolute-residuals line, 最小绝对残差线
: u8 a% h0 L/ D3 ~+ DLegend, 图例
+ s/ r1 ^3 _2 m _L-estimator, L估计量
+ I% b$ ?& Z! ~- I# k5 P+ [' d7 [L-estimator of location, 位置L估计量& d9 i3 D. z5 t' C6 @, D0 F+ \
L-estimator of scale, 尺度L估计量 a2 a4 W) Q4 v O
Level, 水平7 A4 H* Y+ K; `* b1 A
Life expectance, 预期期望寿命
# b; m5 b4 ^# ~+ ^ QLife table, 寿命表6 x3 V# Z9 B5 p0 s
Life table method, 生命表法
1 D, |" |# ~) f) B. }/ fLight-tailed distribution, 轻尾分布3 X$ X7 I. r9 W/ L! L
Likelihood function, 似然函数* w( F* i3 w U* ~0 o
Likelihood ratio, 似然比
' W+ j; t0 T! _line graph, 线图
# \; _: D9 O6 J6 x- ]Linear correlation, 直线相关, S+ ?3 r6 Z* s: P! D+ M
Linear equation, 线性方程2 S* z/ l& T$ [; W. t# K
Linear programming, 线性规划 f: ?! i. n* C7 E0 h3 t+ G% O; Y
Linear regression, 直线回归
: C+ k% ?9 v; m( Z Y7 M- S1 rLinear Regression, 线性回归& Q, w/ @6 B: Z: k
Linear trend, 线性趋势
- a S2 @" `) R, B2 |Loading, 载荷 L6 n* F% [: _" ]: J0 U M1 v
Location and scale equivariance, 位置尺度同变性
2 P' W6 {. j2 ~2 S; C8 B4 H0 P& YLocation equivariance, 位置同变性5 C0 M* P( J1 L/ J: G5 O
Location invariance, 位置不变性" q% F$ x+ m d _- h5 E
Location scale family, 位置尺度族+ X9 ?$ w' O/ G1 N
Log rank test, 时序检验 # [6 C7 }- {' [. W
Logarithmic curve, 对数曲线4 }" a+ O: s, c2 D+ ~
Logarithmic normal distribution, 对数正态分布. _: S N9 L5 Q( t4 ^6 s
Logarithmic scale, 对数尺度
9 A& U4 K& n+ n4 S( K/ ^7 cLogarithmic transformation, 对数变换
" T2 R7 T a4 W6 H/ G" jLogic check, 逻辑检查& e9 s8 M/ Z: M* y- l, H
Logistic distribution, 逻辑斯特分布
! ?: O8 @ p% [: o9 n3 bLogit transformation, Logit转换- h7 X# i+ R2 v. f
LOGLINEAR, 多维列联表通用模型 , e# o; \" R7 O9 D
Lognormal distribution, 对数正态分布3 ?% A7 J4 A! T8 A
Lost function, 损失函数, A1 h, M h9 z2 t ~
Low correlation, 低度相关! d+ S% v# c+ j: N7 A
Lower limit, 下限# k$ w0 o* W! h0 ~6 ^; o
Lowest-attained variance, 最小可达方差
6 B0 C9 s: |' |& p: T7 S" aLSD, 最小显著差法的简称
: T" J" ?8 M8 Q9 Y- k/ ^Lurking variable, 潜在变量
A-D
Absolute deviation, 绝对离差' {$ A4 ^% o/ U5 c( T( V
Absolute number, 绝对数
+ V K7 ~' z0 W8 T, X4 D: SAbsolute residuals, 绝对残差" V( s8 j- @ W1 k1 C; _
Acceleration array, 加速度立体阵) f$ F+ \# ~/ p" v$ ?) u
Acceleration in an arbitrary direction, 任意方向上的加速度
' K& ~" K. M) H. t# rAcceleration normal, 法向加速度
: w+ Y/ I7 R. x5 Q5 }Acceleration space dimension, 加速度空间的维数
" S$ ?8 S' |" y7 j3 QAcceleration tangential, 切向加速度: w4 U6 n+ W9 z% \
Acceleration vector, 加速度向量
$ p l! ^, l8 g, S: ~Acceptable hypothesis, 可接受假设0 s7 K4 D% L: z/ Y D6 U
Accumulation, 累积
. B8 k0 Y' V0 c; A/ `' z9 F$ h' qAccuracy, 准确度5 U% C6 v6 _' F3 G [
Actual frequency, 实际频数
. u U* A G) G0 I4 DAdaptive estimator, 自适应估计量
5 K3 N, w7 \: L+ JAddition, 相加* b" q( m* f" u; i) z
Addition theorem, 加法定理
7 H8 k0 y: e3 hAdditivity, 可加性
6 c/ q- o( Z# _3 zAdjusted rate, 调整率
/ J N; o f: R6 F4 o6 S. xAdjusted value, 校正值: D. A. W6 J7 t( X1 L4 j- L- W
Admissible error, 容许误差
& r* r1 O3 V5 o: V+ z4 bAggregation, 聚集性
1 k7 J9 `1 i" W) ]3 ^9 U( EAlternative hypothesis, 备择假设) g/ q# U4 K! d9 {. ?0 r9 D
Among groups, 组间
5 L: f% G6 |' V7 a fAmounts, 总量
) X9 A) G- O1 T: dAnalysis of correlation, 相关分析
2 N4 \# A% g- ^ u7 L0 oAnalysis of covariance, 协方差分析, V- ^% A% F& b8 @+ H
Analysis of regression, 回归分析
% g" N7 b& Q! g i/ {Analysis of time series, 时间序列分析
, p% h G9 T3 eAnalysis of variance, 方差分析# m2 L6 ^# d& q- `- [ [4 h( B% D
Angular transformation, 角转换: I# K: {+ `, ~$ F. j! `
ANOVA (analysis of variance), 方差分析: t! S1 I4 \4 v
ANOVA Models, 方差分析模型
1 y0 S1 n" Q" p- Z: kArcing, 弧/弧旋/ z+ [2 ^: G4 X, Q3 ]0 C
Arcsine transformation, 反正弦变换# r$ L! W3 r/ u1 K" z$ _# ^
Area under the curve, 曲线面积& u$ x9 x: U7 L, q- A
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 9 I: L, z3 r6 s, \
ARIMA, 季节和非季节性单变量模型的极大似然估计 3 [, E. a9 x/ z9 e
Arithmetic grid paper, 算术格纸
/ I3 k' L' N6 r+ I0 OArithmetic mean, 算术平均数: l& S9 a! ^8 `6 q
Arrhenius relation, 艾恩尼斯关系8 b4 M5 H0 `+ A/ @) }
Assessing fit, 拟合的评估+ P9 T1 J; Q/ z$ G" g1 ?
Associative laws, 结合律
! h$ {4 N0 ?: x" X6 k8 \9 O/ v$ CAsymmetric distribution, 非对称分布5 c$ ~" P; c4 s" y
Asymptotic bias, 渐近偏倚
% n$ E7 I8 J+ n5 cAsymptotic efficiency, 渐近效率" x7 H6 F( Q" `, l
Asymptotic variance, 渐近方差6 M/ Z) I) X+ |+ _$ t. l
Attributable risk, 归因危险度
/ p# A2 G. \- e$ K$ V9 sAttribute data, 属性资料 {2 ^& S* c8 V- i$ a) t5 O# l0 T
Attribution, 属性7 A4 R! \# r$ c& o. ~
Autocorrelation, 自相关
, s0 u/ ^( H' P' d- kAutocorrelation of residuals, 残差的自相关6 o# ~; o9 l( ], T" u0 g1 b
Average, 平均数
7 U/ B$ ]. x1 D: O: s6 Z$ rAverage confidence interval length, 平均置信区间长度. q) [( o! j* q7 B, u
Average growth rate, 平均增长率# u! S4 g) d7 s, s: X8 Z
Bar chart, 条形图! y: w+ Z1 K/ K$ I _ ?
Bar graph, 条形图4 L; F+ V+ z& Y( u3 h9 {3 i; P
Base period, 基期$ `& q- Y( b9 u: {6 q$ @
Bayes' theorem , Bayes定理
& Q/ w, G9 l1 d5 G; C9 RBell-shaped curve, 钟形曲线! B4 W% o& _) p" p
Bernoulli distribution, 伯努力分布
8 H D% H+ M# x# i7 H* t4 DBest-trim estimator, 最好切尾估计量
4 F5 h* O: U0 n2 P1 KBias, 偏性. o. W3 W" q. K7 h: Q5 U8 ]% u
Binary logistic regression, 二元逻辑斯蒂回归
6 w* N$ W, K! ~' |1 EBinomial distribution, 二项分布% I. ~# Q( v; R& r. R
Bisquare, 双平方
, k) @# a, @$ q$ h. L' c1 R; pBivariate Correlate, 二变量相关
% v6 n+ o& u% e: LBivariate normal distribution, 双变量正态分布6 ^: I0 _6 |+ F
Bivariate normal population, 双变量正态总体
" D; q9 W+ ]1 e) `' p( g" w0 qBiweight interval, 双权区间& d" [# r" ?- A {0 A' T$ D
Biweight M-estimator, 双权M估计量9 j! C0 o5 R9 h$ J) P
Block, 区组/配伍组
$ Q, y7 y' m* a8 i5 ^+ Y) wBMDP(Biomedical computer programs), BMDP统计软件包
3 C. ?! [# A) g4 {* w4 p1 ~Boxplots, 箱线图/箱尾图
* @; o5 L1 e) v5 jBreakdown bound, 崩溃界/崩溃点( |& \/ Y' s1 C3 I. T" `2 I
Canonical correlation, 典型相关
e. m2 |" l$ `8 n) vCaption, 纵标目8 k0 G0 u6 q4 l) V" t
Case-control study, 病例对照研究
6 n$ V* ^- I1 [. X7 w9 @6 s p6 gCategorical variable, 分类变量. M8 ]2 ~- U2 n) l4 `0 f
Catenary, 悬链线- N) p/ R8 k2 A5 [/ a
Cauchy distribution, 柯西分布
) v& q5 j3 c+ A, xCause-and-effect relationship, 因果关系
! `3 {/ O9 _! U& l$ H/ fCell, 单元
: m: r0 n2 Z$ o. aCensoring, 终检
; O: I0 k& b9 W! a& bCenter of symmetry, 对称中心0 h7 J1 W9 P/ q/ G
Centering and scaling, 中心化和定标
9 f: q+ h) o1 h* L6 n2 W4 NCentral tendency, 集中趋势
: K3 S0 J6 l$ x8 V( l) V6 kCentral value, 中心值
7 M8 O3 h m) H: Z+ WCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
6 ~2 C8 j) |7 R, `# AChance, 机遇3 p/ d& a+ {5 b* u
Chance error, 随机误差: U% S# p- e* \, J
Chance variable, 随机变量
2 s+ o" s0 M" sCharacteristic equation, 特征方程
3 ]9 B4 |5 @. f( ~3 Z& VCharacteristic root, 特征根1 d4 e% L5 `* ^
Characteristic vector, 特征向量7 `" p2 ?; b+ J: W
Chebshev criterion of fit, 拟合的切比雪夫准则( t& h% R& x( S' s
Chernoff faces, 切尔诺夫脸谱图3 d* [# \# [ l9 B9 r
Chi-square test, 卡方检验/χ2检验
% o: a- O+ p+ O2 X3 F5 g, z9 ?Choleskey decomposition, 乔洛斯基分解! u9 d: A5 l! {
Circle chart, 圆图 4 S0 a# }; B& I% A
Class interval, 组距4 d9 I9 |/ J+ d. y# ? l$ B" ], [
Class mid-value, 组中值
. c: b5 p5 u7 A) L" Z% eClass upper limit, 组上限
" a$ ]- S2 x5 ]% O( e3 kClassified variable, 分类变量# L4 s, g2 Z0 W# G g* _* P1 h
Cluster analysis, 聚类分析0 R& K% b0 S1 I' }2 O ^# J4 p/ |- d
Cluster sampling, 整群抽样# k- D; c+ ?$ ^3 [; v
Code, 代码8 D; U. p$ M: w( _! x" R: `1 {: W
Coded data, 编码数据
% y+ ^( u" H% WCoding, 编码
& N9 _0 x0 B, TCoefficient of contingency, 列联系数1 x* L7 v2 Q; o' J5 D
Coefficient of determination, 决定系数
8 V" {" a( W1 ^* V/ G8 R# \, y; QCoefficient of multiple correlation, 多重相关系数
4 z; J- t* @! z$ H: ~( PCoefficient of partial correlation, 偏相关系数
4 F" F9 m5 z( o& S6 G; g7 tCoefficient of production-moment correlation, 积差相关系数
/ R# s5 q3 J4 Q& ]Coefficient of rank correlation, 等级相关系数! O" I. E4 J* a+ L* O+ L/ J: R
Coefficient of regression, 回归系数- s3 |! W H" `
Coefficient of skewness, 偏度系数
$ g, n- m8 `& t2 c# lCoefficient of variation, 变异系数
- |. D' h: Y3 C- dCohort study, 队列研究
4 [6 F; Q H) z- ?% p& S) tColumn, 列
) y5 ], z1 l& ^9 q% wColumn effect, 列效应% W6 i& y' }$ f
Column factor, 列因素6 A+ b! B" i' l( x
Combination pool, 合并' H+ I; R" L2 l8 b5 E, g
Combinative table, 组合表
6 \! L# k, U, U4 M% |9 q/ QCommon factor, 共性因子
* ?+ ]; t+ E. `) K( Y9 O1 SCommon regression coefficient, 公共回归系数
3 _( m/ D, f1 B" |Common value, 共同值0 _4 e. R$ B$ w9 P* y: T5 H
Common variance, 公共方差
. t2 d/ \4 O& h$ w+ G2 V+ D/ ^7 P5 hCommon variation, 公共变异: h6 F7 v- Z' [
Communality variance, 共性方差
& l) H1 w: E# J' @; mComparability, 可比性
, c6 ?: W, i* aComparison of bathes, 批比较1 j5 a N y! r/ M1 C* x6 Q' D
Comparison value, 比较值9 t3 Z+ C: g5 W) `$ I. ^; N
Compartment model, 分部模型
1 q' u1 i# x9 L* y n' ~- ?+ ^0 iCompassion, 伸缩7 a3 p+ Z; y7 d3 N8 Q& f, d
Complement of an event, 补事件
' X- q# o9 y" U8 b7 M" }' D5 K3 sComplete association, 完全正相关
5 O1 u3 ?) F% ^Complete dissociation, 完全不相关' R1 l8 M( \. L( D. y
Complete statistics, 完备统计量
! n: b- s8 C9 K# \6 U( u- ~Completely randomized design, 完全随机化设计
" A+ T P) l% q, GComposite event, 联合事件& G; T8 d6 @6 Z% _+ r
Composite events, 复合事件
1 y8 R1 X2 _! x+ s; U' q; t7 fConcavity, 凹性
" Y* \0 X9 y5 p& W( `- ?8 b0 c3 _Conditional expectation, 条件期望- X% D5 A* b x$ G, O8 l9 w
Conditional likelihood, 条件似然) P2 I1 F' D: q! S5 ~+ q0 T# x! I
Conditional probability, 条件概率5 G8 k" v( x; z- O7 i
Conditionally linear, 依条件线性3 v/ K2 M. H; |- r. u+ d0 h7 x, e
Confidence interval, 置信区间
# X/ ?1 {2 e8 I/ ]1 B1 RConfidence limit, 置信限( h3 @( G- [+ J' y
Confidence lower limit, 置信下限
1 P6 F: i4 P+ @; i: QConfidence upper limit, 置信上限* M: H7 W* W, T1 N7 M5 O
Confirmatory Factor Analysis , 验证性因子分析! i3 R( o2 G# ~' G4 z; i; V
Confirmatory research, 证实性实验研究
/ a5 e* E5 V1 w- x* E9 p- UConfounding factor, 混杂因素; Q- o* T; o- ]7 l1 L
Conjoint, 联合分析
% k6 V C+ T# k' h* a; FConsistency, 相合性, l. N' m8 b' y8 R. N
Consistency check, 一致性检验
, D. i5 m8 Z! ]( r" A9 hConsistent asymptotically normal estimate, 相合渐近正态估计4 a, p0 s" S2 I! v2 M& P
Consistent estimate, 相合估计/ p5 d* B; K4 M5 F9 L
Constrained nonlinear regression, 受约束非线性回归 h: Z9 `: Z* I5 T. [
Constraint, 约束
# {5 B/ f6 o% ~Contaminated distribution, 污染分布! Z1 R6 ^2 [6 i2 D
Contaminated Gausssian, 污染高斯分布
3 Z" g3 L7 }3 N5 g6 j% W2 J: E/ `% ~Contaminated normal distribution, 污染正态分布
& B% V2 `" G* PContamination, 污染' }9 r* C9 e0 c1 C& v
Contamination model, 污染模型
2 _) ~- U1 |: _Contingency table, 列联表
9 U4 B, j& c/ H; H: w; l0 t7 j( M! jContour, 边界线
) V5 _3 Q/ U- S- |" JContribution rate, 贡献率, D, {# ^8 ]% v8 J! l8 E$ T2 e
Control, 对照
l+ H% z, p+ |$ ]. gControlled experiments, 对照实验! P! e& U s/ T0 n. e, p7 C4 {
Conventional depth, 常规深度2 u' D* W1 J" m) _- [0 J* q
Convolution, 卷积
% W' |2 |1 v9 b; v0 |Corrected factor, 校正因子6 x8 m% \+ G; {) [1 J* e
Corrected mean, 校正均值* t1 m4 k+ t- _- S2 }/ i
Correction coefficient, 校正系数
- C& E7 M! ]6 S0 [; A- XCorrectness, 正确性 ! {2 s4 g' D2 b; U$ Z8 Z
Correlation coefficient, 相关系数) W2 M2 S$ D/ E& n7 J6 t
Correlation index, 相关指数8 D' f0 y4 Z4 k2 t
Correspondence, 对应 q7 y$ Q. M" I+ ~( G+ F
Counting, 计数
7 |9 n ^( I- X0 \Counts, 计数/频数
$ | t0 x8 J- k4 [0 wCovariance, 协方差* V8 B! [ W1 @# @6 e) Y2 E
Covariant, 共变
- g2 l8 d$ X( `$ }Cox Regression, Cox回归
1 X+ Y' V; k% S; f( n. y' B* N# ]Criteria for fitting, 拟合准则" g. z% D9 ^5 E! @* o
Criteria of least squares, 最小二乘准则: b& t+ b, T% B. n. H2 j0 }
Critical ratio, 临界比) {& @+ D6 D& l1 T" n' ?+ F4 ?
Critical region, 拒绝域
1 t* l" j, g9 ^$ B7 u8 S1 J; h4 XCritical value, 临界值4 ^: V( r* {0 F4 L* ^2 \
Cross-over design, 交叉设计
- n# g3 X2 D7 U6 KCross-section analysis, 横断面分析% M( W2 Y2 h# m, P) G- H5 T* P
Cross-section survey, 横断面调查
# { i3 O+ a( I |Crosstabs , 交叉表
! c F& I: Q4 B8 P! N$ ^2 u3 ^Cross-tabulation table, 复合表7 }$ c7 x, `8 w6 M
Cube root, 立方根: o' D5 f8 @; \1 W
Cumulative distribution function, 分布函数2 N! |" y, z1 v6 p
Cumulative probability, 累计概率
9 x: @, b" ?8 Z! g3 f. b+ ]& z5 E+ B3 rCurvature, 曲率/弯曲4 C7 q9 @3 l% Y; \
Curvature, 曲率2 X( V2 s# g, Y& |
Curve fit , 曲线拟和 # L0 v' S/ C0 ]: O$ i I
Curve fitting, 曲线拟合
^' B. `! d# A: y- F& f4 mCurvilinear regression, 曲线回归# P# @2 m3 ~; `* e
Curvilinear relation, 曲线关系
2 q6 A. l9 l: H, Y% ^( n5 ICut-and-try method, 尝试法9 q; B6 b- \) z1 [: e
Cycle, 周期
& F/ X: |' O$ T- ~8 C" p5 M" U! lCyclist, 周期性
# @/ w# ]; P* m0 p: WD test, D检验
8 [: u: ?* Z3 e4 LData acquisition, 资料收集" s I8 J( Q% u3 j5 S3 F7 V
Data bank, 数据库2 f$ i4 b a+ Z# w$ z) p" k
Data capacity, 数据容量# x0 B. a7 X5 _' \
Data deficiencies, 数据缺乏 D" o5 p8 n' F( `! _4 u' b; P+ \
Data handling, 数据处理# X0 N! Q% G7 x$ o) z: u
Data manipulation, 数据处理
2 ^9 B5 r G/ uData processing, 数据处理
2 T+ o6 l5 E4 Z0 A" X z) jData reduction, 数据缩减
8 y8 d C( J! e/ A. D! UData set, 数据集
# V+ D! H! L; Y' [, ^* e& C! DData sources, 数据来源# z X) A7 p9 _! @2 ^' S7 ^3 g6 X
Data transformation, 数据变换
8 M8 t4 [4 }& @" c" FData validity, 数据有效性
9 j/ V5 _% w4 ]- _: I( r! K, JData-in, 数据输入2 G) A4 j9 a# n' p: {0 T( ]
Data-out, 数据输出) }3 |4 f; t' P( r+ g
Dead time, 停滞期- c; e, w8 _+ |# O3 z
Degree of freedom, 自由度
E* X' I, n+ B4 i1 @0 K( O- }, TDegree of precision, 精密度
" v O& f+ A% N; ~$ o! ], \Degree of reliability, 可靠性程度
% X7 O8 |& `" l k* yDegression, 递减
, d% U0 K' p* x6 R4 U6 A' ADensity function, 密度函数9 X$ n/ a; C; _" ?6 V
Density of data points, 数据点的密度
& @ j' t2 t; R( L4 M9 g% IDependent variable, 应变量/依变量/因变量 # y2 t& q ]. P- N
Dependent variable, 因变量) y: I( n; U7 [
Depth, 深度/ F/ v: d) ?9 a3 c2 m7 I1 U
Derivative matrix, 导数矩阵+ k% h w7 O) U5 B4 ^- v
Derivative-free methods, 无导数方法
5 w! L" f: r& s! F1 {9 A6 YDesign, 设计
8 S. S- j; U1 L" Z7 Z3 yDeterminacy, 确定性
! P" n. C3 a1 q7 N, a8 N9 qDeterminant, 行列式' i/ [0 d* I! ]; M+ U8 F
Determinant, 决定因素
+ r' R, G1 U) S$ HDeviation, 离差
3 O# F; G- Q- D! q2 v% CDeviation from average, 离均差
0 |3 U, H- s. G1 |5 a7 o O( }3 PDiagnostic plot, 诊断图; e( v1 |$ U& g( F) R! A" ~
Dichotomous variable, 二分变量
1 w: l( d4 S; ^2 |: B( O HDifferential equation, 微分方程! Z( v9 A) I7 K' |+ H3 i% N8 A
Direct standardization, 直接标准化法0 c, L# |4 y& u
Discrete variable, 离散型变量
8 @) F1 B' W$ ?DISCRIMINANT, 判断
% _% t; ~* ], Z8 HDiscriminant analysis, 判别分析3 x o, U- z) |% z1 Y0 I
Discriminant coefficient, 判别系数- r; j6 Q4 i' k T% N! f+ E
Discriminant function, 判别值' C# s% X8 G1 M! X- @0 [
Dispersion, 散布/分散度
$ z* s6 H0 |' D" I( lDisproportional, 不成比例的0 `) C4 A% L3 a8 S
Disproportionate sub-class numbers, 不成比例次级组含量! w* _# {; E/ b
Distribution free, 分布无关性/免分布
- m0 J- l, c" PDistribution shape, 分布形状4 C; w7 N2 c8 T9 C# c+ s, H- m v
Distribution-free method, 任意分布法# {3 {. z: ]0 @( K( H0 W* h" |
Distributive laws, 分配律 E; y% J; K3 z
Disturbance, 随机扰动项
( ~9 }# a9 y1 Y8 wDose response curve, 剂量反应曲线 * ?% Z) P1 [. X; P- l$ f* a
Double blind method, 双盲法
+ i2 S8 B9 n1 Z& C1 xDouble blind trial, 双盲试验4 p6 @, x A' X: P9 n1 P9 M
Double exponential distribution, 双指数分布
5 u( J) @2 ~) S! L" y4 M* lDouble logarithmic, 双对数: ?' g# Q: G1 R
Downward rank, 降秩
; Y" P1 j$ i% B' {& b9 IDual-space plot, 对偶空间图
5 E, a8 K3 k! t) u l" }/ B8 uDUD, 无导数方法* T7 H- ?2 }) V5 Q' @6 ^
Duncan's new multiple range method, 新复极差法/Duncan新法