|
|
Absolute deviation, 绝对离差
, m$ }7 f6 L( Z6 ^4 QAbsolute number, 绝对数
9 i- T" A% e* qAbsolute residuals, 绝对残差8 `# p' ?5 t( x; r- c. R
Acceleration array, 加速度立体阵/ H" ~0 A( Z5 M. l
Acceleration in an arbitrary direction, 任意方向上的加速度3 r8 `- H* p/ e( M0 _0 r
Acceleration normal, 法向加速度# t ]/ @0 d$ b; P% Y" c0 f
Acceleration space dimension, 加速度空间的维数$ X& K2 ]. m0 i6 X
Acceleration tangential, 切向加速度
1 i g5 ?( L" M0 M6 ~2 n$ R- d/ x5 L8 BAcceleration vector, 加速度向量. P! h9 ^9 r& Z$ `( F
Acceptable hypothesis, 可接受假设: Z" f& r# ?) [$ {
Accumulation, 累积
& S/ i, |! H+ b1 I! z' y1 s8 j3 lAccuracy, 准确度
^8 n, [% \& m* PActual frequency, 实际频数
+ G& H$ i5 @( }0 s9 J8 X( WAdaptive estimator, 自适应估计量
! G2 n4 I4 C& ?0 AAddition, 相加& A* ?" n5 f: t5 O! W0 ^$ ?
Addition theorem, 加法定理
, s% e! m9 A" h7 Y; iAdditivity, 可加性6 \0 R* x9 \; C% C5 ?+ Q
Adjusted rate, 调整率
! v9 K2 @- O( R- i7 y2 sAdjusted value, 校正值
/ M p, n3 ?& V+ O5 M3 E: m; R7 M, w8 rAdmissible error, 容许误差
5 c" G4 [: M X, h( [Aggregation, 聚集性
4 T6 x2 s9 D2 k8 LAlternative hypothesis, 备择假设, w3 E% |4 T' C* F
Among groups, 组间
) r3 c: e* R- z0 V6 kAmounts, 总量, B" y4 x5 f9 d: M9 |3 W. y
Analysis of correlation, 相关分析7 T, p$ a) R" @1 L
Analysis of covariance, 协方差分析
9 k" O5 B) \, L9 mAnalysis of regression, 回归分析! V1 `8 i, Q5 V+ T2 a. I8 `3 @
Analysis of time series, 时间序列分析
, A& }3 H: D- \6 ^# s, y$ nAnalysis of variance, 方差分析
0 x; W0 ]7 o% A$ W1 n; L; kAngular transformation, 角转换
1 p1 @# S" k) ? V" d6 OANOVA (analysis of variance), 方差分析5 F5 `9 t* z2 S8 u, l7 i( W
ANOVA Models, 方差分析模型
0 M a# U! a8 c: M- s$ TArcing, 弧/弧旋
, Q6 J( s7 m; p( P1 Q9 H* ]Arcsine transformation, 反正弦变换
+ ~8 I' c) p+ X2 @- H( \1 Q/ fArea under the curve, 曲线面积+ [$ Q: ]" ^% _& l1 Q& m
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 " B5 `7 X/ ] q8 F- z c; b
ARIMA, 季节和非季节性单变量模型的极大似然估计
+ D7 r0 `2 O9 X+ ^# u- ~) A( v1 ^Arithmetic grid paper, 算术格纸8 s% c' k1 B' s9 L8 S' F5 J3 q
Arithmetic mean, 算术平均数
6 w' _4 q" [! c9 W6 OArrhenius relation, 艾恩尼斯关系
/ _) n& H: r- i9 j1 A8 m- KAssessing fit, 拟合的评估3 R) D) Q8 n6 s* U
Associative laws, 结合律
5 M. I; H) v4 H3 J5 Z& wAsymmetric distribution, 非对称分布
, U- ^$ s7 L+ N5 x- f5 T& ^Asymptotic bias, 渐近偏倚
1 r- |# l p8 [ S- r# RAsymptotic efficiency, 渐近效率
: @6 M- Z; @( c2 q# TAsymptotic variance, 渐近方差+ h0 ^3 ~* G( Y% n% e4 x, j
Attributable risk, 归因危险度
! d/ d, d7 B5 `1 {3 lAttribute data, 属性资料1 f# z0 U# O" Z
Attribution, 属性
* p$ d* m: s4 C6 u. P4 {9 E$ m8 ?! jAutocorrelation, 自相关% ^; i8 h$ U- t* P3 g- z$ `
Autocorrelation of residuals, 残差的自相关
- v( l5 P6 o0 J q/ `+ BAverage, 平均数
4 i, P4 C7 K# _9 W% G: FAverage confidence interval length, 平均置信区间长度
5 @$ @! p3 N1 E: u$ M9 oAverage growth rate, 平均增长率 j6 m: |# T, s( Y+ U% C6 f: H
Bar chart, 条形图
; E3 H6 A! E4 L, G2 \& V: p* }Bar graph, 条形图# n4 `1 R1 V# Q2 k
Base period, 基期
, O* Y7 {+ i$ I9 c2 P7 v8 pBayes' theorem , Bayes定理
6 ~/ K$ ~& C! d2 {Bell-shaped curve, 钟形曲线' c! V9 h- l w" N. l! u* U
Bernoulli distribution, 伯努力分布
$ r6 r/ N8 p+ f" `8 O7 LBest-trim estimator, 最好切尾估计量0 p# C/ X2 @& h; \+ @) E: N' r
Bias, 偏性
+ I2 |/ f7 [) C4 g7 ^. l4 bBinary logistic regression, 二元逻辑斯蒂回归
. O4 b) f+ X3 A: IBinomial distribution, 二项分布0 U" {6 e6 @, l( i5 V
Bisquare, 双平方
, I( N. N0 ~6 e$ EBivariate Correlate, 二变量相关+ H5 |; N. D! l( d5 N# ^
Bivariate normal distribution, 双变量正态分布
- L5 v- a' ^6 Q7 ?2 b) a* JBivariate normal population, 双变量正态总体- L6 q) O- ? z0 h9 R3 l5 b
Biweight interval, 双权区间/ j; x. p& ?/ ` H! s) b! y
Biweight M-estimator, 双权M估计量& N, n0 [" q) R# [* M4 g
Block, 区组/配伍组5 B2 n( G E; \2 h$ @
BMDP(Biomedical computer programs), BMDP统计软件包
3 J0 P" {7 a: k/ c/ ZBoxplots, 箱线图/箱尾图% }4 W4 |) l9 P
Breakdown bound, 崩溃界/崩溃点7 s& ], C- ]) s, N+ r1 }
Canonical correlation, 典型相关
( ^& C, X9 P; b. VCaption, 纵标目4 G9 ~- i4 D" e
Case-control study, 病例对照研究
# h O |/ r* t. _5 [. L ?# t$ kCategorical variable, 分类变量; `0 @: B0 p& ?
Catenary, 悬链线2 b# z" A3 I. M: v9 H% @7 H
Cauchy distribution, 柯西分布
9 e" L2 O, R. `# H" ^, p$ g# J& [Cause-and-effect relationship, 因果关系
% ]: S$ ^3 E0 D5 @; e# I4 aCell, 单元0 G5 {! w0 d# H# ]# z" o
Censoring, 终检5 S) h3 ]6 m6 S/ D8 q
Center of symmetry, 对称中心7 C; L$ L) ~! m
Centering and scaling, 中心化和定标
, L) I; _5 d5 A$ K" Y8 E( jCentral tendency, 集中趋势
. H3 j' H- I1 g, S+ X+ lCentral value, 中心值
" h% }$ M3 G4 t& {7 }9 LCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测: i3 r. ^5 Y% I% t6 M; a8 P- P
Chance, 机遇4 n( G( K/ n: @8 p1 { J @
Chance error, 随机误差/ ~8 C b. S) Y: b- T3 L- d8 y
Chance variable, 随机变量; U+ {+ K) u0 m$ ~9 c
Characteristic equation, 特征方程
6 c* s) t* r& g, TCharacteristic root, 特征根# ]( r$ ]) u0 U% X! v
Characteristic vector, 特征向量 e* ^# l3 {* i' J8 h# L
Chebshev criterion of fit, 拟合的切比雪夫准则
' \# A7 ]# A) _, t4 `5 M, FChernoff faces, 切尔诺夫脸谱图% V8 F: ~# ?0 O2 i6 W3 x. d
Chi-square test, 卡方检验/χ2检验
. ^% G9 n% ^4 ]' U# c* kCholeskey decomposition, 乔洛斯基分解, ^6 z0 u8 t& M+ @
Circle chart, 圆图 * @# l9 s. F9 B9 p' c% W
Class interval, 组距" Y5 Y! H, \! @3 R0 l& F1 f
Class mid-value, 组中值
- L4 P" r# q/ R0 T* yClass upper limit, 组上限
0 f* }6 b6 s" [& T" ~& xClassified variable, 分类变量
# s$ e; k" t- _1 ~Cluster analysis, 聚类分析
# w4 g' B$ V ICluster sampling, 整群抽样
! G, \1 |9 H: l a0 v- h7 A; r# h G, uCode, 代码, `& }+ b) S5 ]" c0 \) r
Coded data, 编码数据
1 }. ?" J; H% [Coding, 编码
- n! A; b& i- tCoefficient of contingency, 列联系数
; k& h" t0 c4 A* d. @* p3 q# `- dCoefficient of determination, 决定系数
7 _: t4 S9 V( O6 HCoefficient of multiple correlation, 多重相关系数
( u b1 E d! Q* lCoefficient of partial correlation, 偏相关系数
8 g$ x& Z7 I; WCoefficient of production-moment correlation, 积差相关系数7 W7 c6 w) N2 f ^- |
Coefficient of rank correlation, 等级相关系数
' u+ v, Z1 \2 V8 d# C% YCoefficient of regression, 回归系数
- }: E# Y' U: g. a9 `0 mCoefficient of skewness, 偏度系数
, [8 H& N" d7 g1 {Coefficient of variation, 变异系数
' }! @; o7 z$ b- e N& f) S+ LCohort study, 队列研究
z/ g. r+ H- ]; y7 `% GColumn, 列$ n/ l: \# f" i3 J2 b+ l, q, @
Column effect, 列效应3 l; m \( M$ w! R; e) f' a
Column factor, 列因素
% x$ ]! I# y' V8 P! DCombination pool, 合并- {( f! C% x& z
Combinative table, 组合表
; ?5 P" k! b2 u _! ]. HCommon factor, 共性因子4 T' [: A5 C+ Z; ?9 e- {
Common regression coefficient, 公共回归系数
0 T$ N5 }5 ]3 O- UCommon value, 共同值 @7 u3 K1 d2 g
Common variance, 公共方差
9 ^0 J( t3 E. {1 _; ?7 BCommon variation, 公共变异
0 W; V5 {; M0 _& {: D, m0 GCommunality variance, 共性方差! L$ @2 J0 s1 T0 P, z
Comparability, 可比性
3 O3 U7 x; o1 b; b/ TComparison of bathes, 批比较1 B* u! Y/ y0 d
Comparison value, 比较值
. Q: I" \) |! S4 j8 g% OCompartment model, 分部模型
0 l) E3 D' O! A0 p9 T; @Compassion, 伸缩
) y2 Z" Z+ ?6 [Complement of an event, 补事件4 ^- Q3 ^, P L! e9 o6 ?8 @0 A
Complete association, 完全正相关- \% l# r4 F! c: K1 x5 r3 d+ y
Complete dissociation, 完全不相关9 I+ U( s4 l8 e' N: @) K
Complete statistics, 完备统计量
! b: x. ]3 p: X; Q8 h& c+ pCompletely randomized design, 完全随机化设计$ w6 z: S7 e# g- u9 @: [, t' i3 F
Composite event, 联合事件& j3 l& p5 P9 Y/ Q5 N, c8 R: _
Composite events, 复合事件
% ^% D/ ^( ^6 Q9 u0 L2 ZConcavity, 凹性# u2 Q! ?' L! F' s; N
Conditional expectation, 条件期望$ w: \( |4 n N. v9 W8 }
Conditional likelihood, 条件似然; a0 ^/ H2 d9 ` t
Conditional probability, 条件概率
) F/ P* T5 u9 u5 k0 ^) w1 QConditionally linear, 依条件线性. q, o0 d; }+ ~; h8 ?( g# `# m6 V
Confidence interval, 置信区间
1 d; F" r4 d+ _" \Confidence limit, 置信限4 \6 c; A9 l9 ^ C
Confidence lower limit, 置信下限3 L& B/ u" c6 ]* Y* J, H8 e; j1 e
Confidence upper limit, 置信上限
3 K' X) ?4 d6 W) _' zConfirmatory Factor Analysis , 验证性因子分析- F+ S; P+ W5 i! x
Confirmatory research, 证实性实验研究
: n6 v0 c' L0 `( A4 c8 HConfounding factor, 混杂因素. e4 H3 U ` b: F$ M/ J
Conjoint, 联合分析
! ^" z3 E2 n* }( s; n( fConsistency, 相合性
! e, K8 ?# x7 K7 p& C9 q. W8 _1 CConsistency check, 一致性检验" X0 z( g4 }2 E. B$ g, w! |' l
Consistent asymptotically normal estimate, 相合渐近正态估计0 z6 h y. l( X
Consistent estimate, 相合估计6 o5 J4 O7 W2 t% e& e7 L
Constrained nonlinear regression, 受约束非线性回归9 B- h8 b# \ d; G. C# `4 i% d* O; D. w
Constraint, 约束( r# z; E! r! `" t% Q
Contaminated distribution, 污染分布 Y7 F% a! h+ g1 ~
Contaminated Gausssian, 污染高斯分布
4 q" R# |1 ~7 B0 a- D' W9 W, `Contaminated normal distribution, 污染正态分布/ L' A+ y, B0 `6 |& k) x8 R
Contamination, 污染
- e( t0 j1 E1 ^* n/ S/ X6 CContamination model, 污染模型8 E' {9 k# M4 o+ a
Contingency table, 列联表
* h4 b( F& j! |$ e Y6 d. B7 jContour, 边界线) ?5 P8 z8 c, V% a+ I" \
Contribution rate, 贡献率/ n @/ b- R# @" g$ f3 p! |6 I
Control, 对照% u7 z) G& z, X8 H1 [5 m% ?
Controlled experiments, 对照实验
|: i$ s" m! eConventional depth, 常规深度$ s$ Y# P0 W' A% ?" y! W* j) Z: l
Convolution, 卷积
k3 @4 C9 X% J+ B$ |7 B3 K/ D ACorrected factor, 校正因子4 j: }; P/ D& t# n" C' o
Corrected mean, 校正均值
+ C! Q& m: X- G9 h/ L6 GCorrection coefficient, 校正系数
" v( l" R- y9 `: I: }" JCorrectness, 正确性
T: q! Z6 m7 g# I2 ]1 Y4 X0 sCorrelation coefficient, 相关系数5 ]; F0 j z. @
Correlation index, 相关指数
- {$ s A8 c" T5 VCorrespondence, 对应
: A* O+ E* I" j0 {( [; X5 a @Counting, 计数
/ K+ ?% }3 O4 X5 Y' {3 zCounts, 计数/频数
" d' w& O3 `9 u* cCovariance, 协方差4 L5 P6 Q8 n4 h# i" m) Z
Covariant, 共变 ( Z3 }& j( M4 W G
Cox Regression, Cox回归
4 E, ]9 c; X- L" f2 j+ cCriteria for fitting, 拟合准则
# s0 O) D, c& YCriteria of least squares, 最小二乘准则
9 Y6 A$ L, O E' C7 F s. @2 vCritical ratio, 临界比3 u0 U& Y5 h- B1 s% ^7 T
Critical region, 拒绝域+ w) [: g$ j/ X q% Y: y1 }) j
Critical value, 临界值
7 @4 A3 i6 e+ ^9 |* }Cross-over design, 交叉设计- @. B7 O }1 {; W7 J1 u, D
Cross-section analysis, 横断面分析0 f( r; c9 W/ y. e: V# t
Cross-section survey, 横断面调查% E e8 A4 ]$ y
Crosstabs , 交叉表
- B N5 P; T% S7 j8 j7 U% _Cross-tabulation table, 复合表
8 J& H! R+ @. w2 t! i$ {Cube root, 立方根
* X5 Z8 W0 T/ V. Z5 V G/ U& kCumulative distribution function, 分布函数
- E' `$ \. ~$ ~0 m# b2 R# G3 {+ SCumulative probability, 累计概率
" i9 m8 q7 g5 g- A7 h5 W( B' [- @2 JCurvature, 曲率/弯曲1 M5 |$ v: ]' z/ s
Curvature, 曲率* c" K. s" Q, H' ?) b0 g; a
Curve fit , 曲线拟和
6 K6 m1 T, U: b5 P. t, i0 z$ NCurve fitting, 曲线拟合6 h3 J* T9 V+ n' A$ e2 z
Curvilinear regression, 曲线回归
: L1 |; |1 r6 q* k( `) mCurvilinear relation, 曲线关系; h: R1 z9 {4 s5 ], w
Cut-and-try method, 尝试法
4 c4 S& p- Z8 ?; {) @, RCycle, 周期
8 o# j; z; W- D) c" w: y# g$ N1 eCyclist, 周期性
9 i1 {: z7 f: n" P/ g- M3 ]D test, D检验
6 C2 r# ]9 K- [4 B4 o/ {; H0 m; eData acquisition, 资料收集1 o# e$ K) m7 l6 r& T" r& ^0 L
Data bank, 数据库
2 _% s( O* ^- S9 k" hData capacity, 数据容量
( K \; }- C: \' mData deficiencies, 数据缺乏
# m* s. X7 [# G5 i+ TData handling, 数据处理
+ v: _0 W5 u( hData manipulation, 数据处理
- {. T% O+ d7 ?; i# X& JData processing, 数据处理
( B" G8 n9 W% o7 l5 g' vData reduction, 数据缩减$ R$ J1 m$ B; Q3 O% {
Data set, 数据集
( @' N' l6 I+ k" DData sources, 数据来源: `, k# n6 L! K" k t; B. H) g
Data transformation, 数据变换
5 g9 S* V1 D, N- j1 _ ?8 O+ eData validity, 数据有效性/ W+ d& x4 A4 [' l
Data-in, 数据输入1 o8 l$ k( B+ L5 M) k
Data-out, 数据输出
- {: j1 p( c: t" l5 n' M2 ^2 e/ rDead time, 停滞期
. Z: T% D8 w6 }1 m& MDegree of freedom, 自由度
5 w: W7 }' z5 R7 p. D* t2 }( q2 IDegree of precision, 精密度( e/ f3 b4 t. M6 W# o
Degree of reliability, 可靠性程度- f5 y* b W/ m( I0 L1 D l
Degression, 递减) D" a. U4 z9 ?$ d% u# g' {7 s
Density function, 密度函数
; l- F- K0 T5 _0 k: U4 JDensity of data points, 数据点的密度
* @. x5 c. d! y3 ]% LDependent variable, 应变量/依变量/因变量
6 b$ ?+ v; r: K: qDependent variable, 因变量- ^4 o1 k3 F# g' ~$ q
Depth, 深度# v. c) q9 \* h) @
Derivative matrix, 导数矩阵
~$ r7 a: e2 P, e% a& IDerivative-free methods, 无导数方法
& Y9 V% B6 ?* z! FDesign, 设计
" s* J6 X8 h5 i- _7 M1 W/ v: UDeterminacy, 确定性
" ~3 Q% g; e6 N& Q1 v; ]+ XDeterminant, 行列式: K5 a6 R! }) _, l% `
Determinant, 决定因素
: X5 E3 {4 e' ^) ]; bDeviation, 离差1 O" S* b; s0 h# a4 r5 G+ S+ g
Deviation from average, 离均差
8 ], O, Y- ?" g, Z* R) K& N# cDiagnostic plot, 诊断图
$ ]2 J$ w8 N8 \ M, I) X& FDichotomous variable, 二分变量3 i( L6 C/ {9 b. K
Differential equation, 微分方程
0 m3 t( g6 F5 p9 z1 v+ HDirect standardization, 直接标准化法1 L+ \/ U1 \. i1 `3 J2 `" P
Discrete variable, 离散型变量2 i1 e$ `- h6 H f+ V5 f3 t
DISCRIMINANT, 判断
" f$ c1 M ?( a: S1 _2 |. l6 aDiscriminant analysis, 判别分析
3 t% k8 P" G3 q3 gDiscriminant coefficient, 判别系数
c# N3 J F0 _- J- l3 QDiscriminant function, 判别值3 p( s# X( W D
Dispersion, 散布/分散度
9 a: V! B, Q) {+ h! g( @Disproportional, 不成比例的
/ Y: o( @2 O) `2 s, |' b9 wDisproportionate sub-class numbers, 不成比例次级组含量1 J, T: c( Y. c! B
Distribution free, 分布无关性/免分布
( X _( S ^$ J# ZDistribution shape, 分布形状- w) k* ]7 ~8 r2 y. Q% S5 x
Distribution-free method, 任意分布法
: G1 K- @# B( c3 o4 e5 w, p$ DDistributive laws, 分配律: V# I: d2 }$ ? r7 e( l9 t+ C
Disturbance, 随机扰动项: B- O% Q A r& `
Dose response curve, 剂量反应曲线5 g& R1 E; p7 y' y9 G( y
Double blind method, 双盲法
1 p, W0 w0 O1 S1 Z: y& d9 EDouble blind trial, 双盲试验 Z6 e& J+ _3 D# z" B5 U x
Double exponential distribution, 双指数分布' z! `" u, N: U0 o/ s3 G8 T
Double logarithmic, 双对数
% T9 [+ r- j6 |4 U: m8 w; xDownward rank, 降秩3 X* o; |! v7 x7 ~% {2 O
Dual-space plot, 对偶空间图5 Z1 C7 A2 D. z# \* {5 y5 D
DUD, 无导数方法+ j7 x$ ^9 O$ B4 y* F5 P1 g5 k& L
Duncan's new multiple range method, 新复极差法/Duncan新法
5 q! ~/ C4 [0 P' K; I" ?& m" IEffect, 实验效应
2 s/ |5 |) g q: GEigenvalue, 特征值: K. d7 _" T* H l! ~5 v+ g/ u+ f# g2 T
Eigenvector, 特征向量# N V' Z3 s- O2 I3 g% Q/ X
Ellipse, 椭圆
- L5 Z m0 ?7 w- d: c6 I6 M- eEmpirical distribution, 经验分布! P/ _0 Q. p& {
Empirical probability, 经验概率单位
" K2 E8 |; b1 c; c% NEnumeration data, 计数资料
5 R$ M/ N$ r2 E; u) q7 HEqual sun-class number, 相等次级组含量$ U! k; a: w3 |& @
Equally likely, 等可能
1 i: J' e4 \, L, N; ]1 pEquivariance, 同变性
2 Q" g: N1 O9 O, N6 l$ o9 WError, 误差/错误
$ w o- B% R! j" ? l' FError of estimate, 估计误差
6 z# y; s3 m3 N- eError type I, 第一类错误' \4 h. t$ ^* W* b8 {( ^% z$ q7 A7 w6 \
Error type II, 第二类错误. k* L: |3 n0 a. m
Estimand, 被估量
# [0 w e6 r$ I! ]: CEstimated error mean squares, 估计误差均方
. |) H; p* R& r* t- ?Estimated error sum of squares, 估计误差平方和
4 D8 X" z. E. v& wEuclidean distance, 欧式距离" c+ Z. T l- x) v) G
Event, 事件6 u# d- M* F/ @
Event, 事件
8 T; G- y0 W# WExceptional data point, 异常数据点1 d5 M8 C! y( O, K
Expectation plane, 期望平面0 A3 `9 d7 g' [: j+ r
Expectation surface, 期望曲面
1 ]- n$ D2 L) ^& s% h; {Expected values, 期望值) z! s+ T5 K% x/ W O# d" E
Experiment, 实验
1 S1 z+ e4 D+ X) nExperimental sampling, 试验抽样" {. U3 C& ?5 o" f; m+ ^( g c
Experimental unit, 试验单位8 t# W$ q4 Q/ P: ~! t
Explanatory variable, 说明变量) E9 ^: u- S- n$ y0 j" a) |
Exploratory data analysis, 探索性数据分析
, x9 s6 |# q( z% kExplore Summarize, 探索-摘要1 F5 {" o- i* |1 U$ `' c% b
Exponential curve, 指数曲线
6 O2 H$ u; \. WExponential growth, 指数式增长
' P# c+ B8 H3 J0 Q3 AEXSMOOTH, 指数平滑方法
6 b9 g- l% n) y0 K. gExtended fit, 扩充拟合
; h' ?/ y. p0 S- B4 L) ?Extra parameter, 附加参数
8 P; J. |- s; w# ZExtrapolation, 外推法
U- y8 p; q7 }4 ?Extreme observation, 末端观测值
: z6 G( E2 u* m8 a) F/ cExtremes, 极端值/极值6 k) b, ~) H* ~$ g+ }% W& g
F distribution, F分布! C& D5 b: j' x/ O. l# n
F test, F检验6 l7 k* d! L; N ]4 |
Factor, 因素/因子
' e) s% ?& v2 LFactor analysis, 因子分析7 P- W! L, w# l2 W; Y
Factor Analysis, 因子分析3 t8 W. ]" u) [; L3 ^
Factor score, 因子得分 * m) ]; w" V! J. K+ U
Factorial, 阶乘9 r- s& \8 \5 O+ c
Factorial design, 析因试验设计4 p6 ^. I, |, w* C
False negative, 假阴性
& L" M. I( d0 A0 qFalse negative error, 假阴性错误' d: H2 r1 F. v3 a1 z' O
Family of distributions, 分布族. g! F! Z1 r* z+ P6 l
Family of estimators, 估计量族
& h5 i0 d) n$ UFanning, 扇面' j1 y" ?$ j% W4 z0 N9 V( r6 ?
Fatality rate, 病死率; L# m- V& F7 r9 }! S; d! N8 k
Field investigation, 现场调查
) @# j+ ?( [9 k+ jField survey, 现场调查
: h* e8 W0 q1 E T8 z1 f# _3 WFinite population, 有限总体2 ]9 Z! ]( E0 x' O9 O
Finite-sample, 有限样本
' V7 `; @9 A% _' n9 {6 v& ^$ @First derivative, 一阶导数
. q' D* _( k( O0 j" P7 sFirst principal component, 第一主成分
; F' l) l* z5 M( L7 z# S, [First quartile, 第一四分位数6 E. M# r# P( H8 J" Q2 y
Fisher information, 费雪信息量' h- q: s) X! n4 G% v8 x0 T' s
Fitted value, 拟合值5 {+ K+ \& ?9 q J" O* q8 ]
Fitting a curve, 曲线拟合0 \7 [( A+ b6 n R# ]% ~% y1 w
Fixed base, 定基% l- S2 d% ]$ ` t$ o3 N/ s! N
Fluctuation, 随机起伏
" s9 r/ W$ M- x5 K+ }Forecast, 预测' o8 H7 U1 V* g$ W
Four fold table, 四格表4 [8 E( C' g) ~% A
Fourth, 四分点
5 e0 o. Q9 w R. S8 o* i4 dFraction blow, 左侧比率
; }/ q7 Q! { ?, y$ H$ F& T5 k/ H- kFractional error, 相对误差# n: s$ i Z- U, r- ?
Frequency, 频率
' D# r! a$ i7 M6 S! N( Y- kFrequency polygon, 频数多边图* g! R$ R* w) f/ Q3 G8 z( O9 r% }. O
Frontier point, 界限点/ b2 \+ X0 E: o: w& V4 b, N" ~. ^( |! k
Function relationship, 泛函关系) p: O( a$ [ {
Gamma distribution, 伽玛分布/ t% d) O% m* g# B4 z0 [
Gauss increment, 高斯增量% f( a Q/ p! Z/ I" \+ e
Gaussian distribution, 高斯分布/正态分布7 i6 y; S& y/ T* v- @8 j
Gauss-Newton increment, 高斯-牛顿增量 F4 v: q8 f* Z) l4 }; u
General census, 全面普查
, G1 e* x5 l3 S% o7 D) QGENLOG (Generalized liner models), 广义线性模型 2 E1 E# q8 q' ?4 L
Geometric mean, 几何平均数# {4 s& l6 ^0 g* J
Gini's mean difference, 基尼均差
; N: {% I) Y2 y* |2 G3 D# w- WGLM (General liner models), 一般线性模型
( R( S* T' e% r O' r- I4 U, jGoodness of fit, 拟和优度/配合度, J. }: n a( \! D
Gradient of determinant, 行列式的梯度. _/ n! z. L) N1 x% [ d
Graeco-Latin square, 希腊拉丁方
# _3 j- `/ M5 UGrand mean, 总均值; [- Q% }! b! P5 L
Gross errors, 重大错误/ [1 V+ H% U- ?! ]* m, m! t8 }' X7 y
Gross-error sensitivity, 大错敏感度
* j/ S- I2 q8 ] ^" KGroup averages, 分组平均
9 x8 i3 b" B8 ~" {1 K' m$ RGrouped data, 分组资料
5 U4 G+ ]5 X5 {( G: p# xGuessed mean, 假定平均数3 u5 r1 {3 u2 k5 u+ p M
Half-life, 半衰期
8 S. X. l! I( i2 G* I u5 h1 IHampel M-estimators, 汉佩尔M估计量
, [# C- v/ z* N. T: V; }4 GHappenstance, 偶然事件
% {5 P$ A/ t" V0 ]: uHarmonic mean, 调和均数
! R, H9 G K# ~5 tHazard function, 风险均数
/ J( M B% v# M3 d# zHazard rate, 风险率* G. k' L5 u) x; r& @* i
Heading, 标目
_8 w' ? `6 Q& uHeavy-tailed distribution, 重尾分布0 ~/ d& [* `$ W* J
Hessian array, 海森立体阵
( G4 G; a! t9 V$ m4 s' BHeterogeneity, 不同质
5 z3 a" a% o. {: [6 [Heterogeneity of variance, 方差不齐 . N- u" ]. F1 T R6 O% m
Hierarchical classification, 组内分组
# r& I" Y& w$ ?$ z) MHierarchical clustering method, 系统聚类法. z4 \) V4 @8 Y3 S% P8 R. C
High-leverage point, 高杠杆率点* u& P! s* N @
HILOGLINEAR, 多维列联表的层次对数线性模型/ ^- n7 U& q* L7 o+ d
Hinge, 折叶点7 G/ g5 V2 o! a. {5 J
Histogram, 直方图7 D% G5 V6 l, ~( \/ a: S, n
Historical cohort study, 历史性队列研究
3 g& R2 s& G( P- RHoles, 空洞
2 i% x* v: K- q. K0 oHOMALS, 多重响应分析
$ F( f8 h1 y8 b* @* R$ S$ l& K+ wHomogeneity of variance, 方差齐性
: |! n5 B5 }& J) i, K5 SHomogeneity test, 齐性检验* |3 _# l( q# s8 N2 d1 U
Huber M-estimators, 休伯M估计量8 T! v E/ E. t' j
Hyperbola, 双曲线
7 e9 S( T% Y3 f) y4 zHypothesis testing, 假设检验
: H) z* G, t% dHypothetical universe, 假设总体% Q: f/ {# b( |) j$ z# M
Impossible event, 不可能事件
$ Z* R# j# @7 X" t& l5 g1 C, fIndependence, 独立性
* g& e& N' r( N/ Z9 @' YIndependent variable, 自变量
3 A8 u9 K- A. mIndex, 指标/指数
: H2 h8 U+ z" Q: K7 l8 ^! QIndirect standardization, 间接标准化法2 h) s, g# w+ q: |+ Y' e0 c0 f5 g s
Individual, 个体& m; S3 X) `) e6 P4 u
Inference band, 推断带
/ _# v* t, J! X. pInfinite population, 无限总体
% t# J( o& D% e' v0 c. BInfinitely great, 无穷大8 e) V; Q8 S6 A8 U n1 A! z
Infinitely small, 无穷小8 H/ v% r7 j. E9 R f
Influence curve, 影响曲线
* Q1 Q9 p* i! \2 q+ P1 T( {' v" U* gInformation capacity, 信息容量% R# f( @0 J; A2 p9 }* w0 b
Initial condition, 初始条件
- j7 p4 V, n3 |Initial estimate, 初始估计值7 Z( ^3 l% w- p* N( W# ?+ {
Initial level, 最初水平- @6 P! p( y/ e* H9 ^4 m
Interaction, 交互作用
E6 c+ | f, v) y+ b+ y0 W* h3 S7 XInteraction terms, 交互作用项/ F8 w* Z" _3 @1 R
Intercept, 截距
+ X! _' d9 J8 C6 ?+ _/ QInterpolation, 内插法) G( C4 F+ o2 h& O* ?) \
Interquartile range, 四分位距! [. y# ^5 ~+ N6 i9 v) s
Interval estimation, 区间估计; m' i2 P2 o- k% V5 u
Intervals of equal probability, 等概率区间
: }; O3 r4 Z, _Intrinsic curvature, 固有曲率
; g: u3 l/ k- z+ ]2 }Invariance, 不变性9 U& w0 q. d7 i
Inverse matrix, 逆矩阵
* N+ k8 I# D. B1 e" J4 n5 IInverse probability, 逆概率
& ^" m6 V: D3 E8 H) T2 ^2 k; @Inverse sine transformation, 反正弦变换" m j! p; Q1 X: X' |
Iteration, 迭代 + c9 j d1 [0 _! r1 J# ?# X
Jacobian determinant, 雅可比行列式' y$ b# x' ^3 W
Joint distribution function, 分布函数
_4 ~7 v7 k# u/ RJoint probability, 联合概率
+ _: e$ f# U C; H$ FJoint probability distribution, 联合概率分布6 i' T6 c& m3 b! i9 D( q5 K' w# E5 u
K means method, 逐步聚类法
3 t8 @# J# J$ S y( l7 ^! zKaplan-Meier, 评估事件的时间长度 ) n8 E1 R% `! a9 [% o$ l7 X
Kaplan-Merier chart, Kaplan-Merier图
2 M2 h2 y7 _+ y' AKendall's rank correlation, Kendall等级相关
: _% \! e# J( ?, oKinetic, 动力学
& }% v' {" j, y# |) lKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验% ?. B: ^3 B8 W7 i6 S9 K% L/ V: _
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验+ v) X. l# J- l$ N0 H; B
Kurtosis, 峰度
3 Y8 w' c: J8 ELack of fit, 失拟- h9 C+ ?4 X4 v |- K$ J' r9 T z& H# e
Ladder of powers, 幂阶梯3 c. t9 K: T8 q9 u
Lag, 滞后
9 f6 b& {% G7 \- O: pLarge sample, 大样本2 O3 p9 P5 r: ]3 _! k2 n8 j3 t
Large sample test, 大样本检验
% _) H& d6 ~- {, ^! r( B8 NLatin square, 拉丁方( M# L4 e/ S: X
Latin square design, 拉丁方设计
. e, `3 e/ D) Q& T, K6 BLeakage, 泄漏
# F S9 A4 n- b2 _$ ~+ s6 e* I$ SLeast favorable configuration, 最不利构形
( E/ v' k0 ^9 x( VLeast favorable distribution, 最不利分布
0 P8 D0 Y* J5 k7 x5 p7 W( GLeast significant difference, 最小显著差法
( n: \6 [* |* s h' Q. @$ d% w" C) CLeast square method, 最小二乘法
+ N3 f" e, F, N. A! ]/ G, r* _Least-absolute-residuals estimates, 最小绝对残差估计9 X7 K4 u3 k- P8 o7 r- A1 R# `
Least-absolute-residuals fit, 最小绝对残差拟合
% ?0 h; D/ A( d4 x$ pLeast-absolute-residuals line, 最小绝对残差线
& \ j' h4 S3 \# B) \Legend, 图例
9 E$ `( x/ ~. m, {L-estimator, L估计量7 L% s. O$ S5 R3 u3 Q: V
L-estimator of location, 位置L估计量
) z7 I0 ~& |. W+ b. ]1 K9 ]0 H# hL-estimator of scale, 尺度L估计量8 S% O8 k& E6 J2 ?) e3 A
Level, 水平
+ t: ^% P( f5 r: f/ bLife expectance, 预期期望寿命
3 P6 W) c& J8 q4 j" R" t0 C& yLife table, 寿命表- f5 r2 L$ o6 ~" b' U* x5 l6 u
Life table method, 生命表法
3 {; m" Y+ w$ k/ JLight-tailed distribution, 轻尾分布
. z! m8 G7 a; [Likelihood function, 似然函数
* T' T" O; V+ a! D8 H- HLikelihood ratio, 似然比
! ]9 S. k' g6 R2 Fline graph, 线图
& W5 x. c1 I3 @% GLinear correlation, 直线相关. i8 ?8 K* f. D- |$ ~" T
Linear equation, 线性方程8 c! j4 E& k/ M' C5 D/ M
Linear programming, 线性规划, [* J% N9 ]( |; }9 F q1 M5 f9 Q
Linear regression, 直线回归
/ P0 g; B% s; [5 o6 U' _Linear Regression, 线性回归: T. c& x: Q+ {7 B" G
Linear trend, 线性趋势9 F9 A/ Q, y/ J0 l1 q. M
Loading, 载荷
& o8 D9 q9 F4 Q! g- c' Q& YLocation and scale equivariance, 位置尺度同变性
! ^- y! q" w5 Q hLocation equivariance, 位置同变性2 E( O3 ]- K; o" D, d- E: c q
Location invariance, 位置不变性7 c2 ]. a- s& ~
Location scale family, 位置尺度族' v! M6 ^: K3 j- y9 Q" y* K
Log rank test, 时序检验
" h, Q6 F9 C# MLogarithmic curve, 对数曲线
1 R: d; V6 c; |- PLogarithmic normal distribution, 对数正态分布9 A8 n" U+ p- n( o6 e+ z
Logarithmic scale, 对数尺度) b5 H3 D$ T. |/ |
Logarithmic transformation, 对数变换
* @/ M4 C; ] a4 QLogic check, 逻辑检查
/ \. ^" s0 \2 H6 xLogistic distribution, 逻辑斯特分布; d1 W5 a5 b7 N6 w. D
Logit transformation, Logit转换: {* m* l$ {. Z) \2 J
LOGLINEAR, 多维列联表通用模型
' J6 L+ a, b( Z* V W" ULognormal distribution, 对数正态分布! \7 u7 P7 e( y& o0 n" v
Lost function, 损失函数7 [3 S+ y: }5 |; {% x' a
Low correlation, 低度相关* D k1 }2 O z- ?
Lower limit, 下限6 M5 I, J7 V4 |
Lowest-attained variance, 最小可达方差% V' |% ]+ l' K7 m2 q7 O
LSD, 最小显著差法的简称
N( N9 j( N: J& bLurking variable, 潜在变量
1 ^: E8 S+ O8 fMain effect, 主效应, ^& D' ~; k! r" Z
Major heading, 主辞标目
5 `6 V+ h' W. C4 H" i) UMarginal density function, 边缘密度函数
: y8 F6 e7 S$ C$ [Marginal probability, 边缘概率
5 }) y* O) n8 TMarginal probability distribution, 边缘概率分布
B; y% ?" G2 ~9 ^2 T1 k3 dMatched data, 配对资料( q2 @- d4 E0 X+ f1 G
Matched distribution, 匹配过分布
& {( j$ h! \* R- E2 \$ oMatching of distribution, 分布的匹配' j g$ e+ d$ M( N
Matching of transformation, 变换的匹配
: @& h: N! ?+ u% Y# F: kMathematical expectation, 数学期望1 C4 j. W0 I) y* W
Mathematical model, 数学模型5 [. w. @9 J3 l$ L- s
Maximum L-estimator, 极大极小L 估计量9 K% k* v" n( L* h% s
Maximum likelihood method, 最大似然法
4 Y4 v' N2 k1 ?5 gMean, 均数
y& b$ X9 ?1 k" LMean squares between groups, 组间均方
) j5 d+ q/ v+ n# L3 O0 J8 I/ a- FMean squares within group, 组内均方 A% H, e- V; i7 V$ Q7 }5 w2 o: i. C' h+ b
Means (Compare means), 均值-均值比较
" k0 P4 c# N" F1 V: k" s0 f! m6 sMedian, 中位数
) z# N, I9 j V. y7 }Median effective dose, 半数效量& t+ v9 y/ P; ^4 B( {$ Y
Median lethal dose, 半数致死量2 n$ T- Q1 { r) L
Median polish, 中位数平滑* s6 q: X; l& v9 E4 F4 B+ K
Median test, 中位数检验' H! }' Q1 F J3 u X( @% R: L1 a
Minimal sufficient statistic, 最小充分统计量% z. p% v8 l M
Minimum distance estimation, 最小距离估计& S( o, f" a: \! l6 Y
Minimum effective dose, 最小有效量
1 e0 t/ w$ a: Q7 Y; x; lMinimum lethal dose, 最小致死量
3 g4 w# g( r* ]! }- Z- IMinimum variance estimator, 最小方差估计量9 E% f$ Q+ `: V. C
MINITAB, 统计软件包. C6 b1 S( X- M
Minor heading, 宾词标目" E( d; `; {- z' t N
Missing data, 缺失值5 d) P4 X8 e6 v: ]$ e- p
Model specification, 模型的确定& s; D7 B7 P% J- ~9 {" `3 N
Modeling Statistics , 模型统计0 S9 l k% }0 T. n
Models for outliers, 离群值模型# i5 Y: I& a5 b* u6 Z- ^
Modifying the model, 模型的修正/ D/ N) ]7 h' q4 G" o) W7 Q/ v7 ?) W
Modulus of continuity, 连续性模
! E" ~2 b5 b0 P& t$ eMorbidity, 发病率 ' M2 r9 b. j' V* c4 R
Most favorable configuration, 最有利构形4 X1 t( ~( g' y) T) x& f* f* G) m
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
6 E3 d6 ], q) H1 H) J8 F0 P8 fMultinomial Logistic Regression , 多项逻辑斯蒂回归
" b# P" g! b$ n WMultiple comparison, 多重比较$ {% h/ W+ b& ^
Multiple correlation , 复相关" r. c( `5 a6 e# I* g
Multiple covariance, 多元协方差" k5 m1 n- I8 z( Y- M4 i* {1 c
Multiple linear regression, 多元线性回归 o" O, y7 B2 w% }6 {
Multiple response , 多重选项; }: H0 r: A' U
Multiple solutions, 多解
5 [0 j: t6 a+ r N2 _' `* ~1 o7 |Multiplication theorem, 乘法定理
7 G2 x* g0 ?/ v$ B& n0 e. n% \2 _Multiresponse, 多元响应5 ]+ k9 ]9 H3 g
Multi-stage sampling, 多阶段抽样1 Y! Q3 ~4 M3 O
Multivariate T distribution, 多元T分布3 h: |: u8 \ W
Mutual exclusive, 互不相容
! ^$ g- J, {0 ]" k' t; E7 `Mutual independence, 互相独立
$ l; N y+ C* y: c* G' f+ J* vNatural boundary, 自然边界
# |+ R+ u, P' L+ KNatural dead, 自然死亡
1 }' }& ?0 r' R0 PNatural zero, 自然零0 @& m) Q; V5 f0 Q' }0 F! O2 a
Negative correlation, 负相关2 L1 H$ Y1 [$ x1 x% j9 }
Negative linear correlation, 负线性相关8 L+ ~5 r, M2 q1 K9 G* s
Negatively skewed, 负偏( ]3 U# W5 H6 N" m4 A. x5 H, {
Newman-Keuls method, q检验" _2 X. ]0 ^, }+ y
NK method, q检验
2 ]. O0 c3 z4 Z J G: fNo statistical significance, 无统计意义
2 P( B8 b1 v# `3 e: UNominal variable, 名义变量+ s* D/ k, ?, B( r! S1 ?/ }
Nonconstancy of variability, 变异的非定常性7 w. I# [/ d7 j4 b2 z
Nonlinear regression, 非线性相关& X1 e, H: e" j# O' ?6 Z- W) h
Nonparametric statistics, 非参数统计
, n$ h8 k4 G9 X8 E6 DNonparametric test, 非参数检验- L- C8 w/ B! r( S( N$ @
Nonparametric tests, 非参数检验
% D7 b' Q/ g1 X Q9 e iNormal deviate, 正态离差
: f2 u4 ~8 Y* q# Y* H) }& kNormal distribution, 正态分布& u9 {2 Y! ]$ e: O* l9 ~% r
Normal equation, 正规方程组
- ~' ?) g) |( @- w: L, g+ T9 |Normal ranges, 正常范围
# z7 @8 G. S" ?0 q# n! r; WNormal value, 正常值
3 L' {6 ^; f+ O3 @0 o4 X. {Nuisance parameter, 多余参数/讨厌参数0 o! t2 I1 n5 r; X& F, N5 ]
Null hypothesis, 无效假设 8 m* i3 m, B E6 ?! R" _, t
Numerical variable, 数值变量
5 X1 w1 i4 ~3 L8 v3 }* _, d( O* _6 oObjective function, 目标函数
+ ]7 o: a V( L' @7 zObservation unit, 观察单位
, S4 V7 r/ u$ o- |Observed value, 观察值! w# }! W8 _0 a! I4 U1 H
One sided test, 单侧检验! \8 l' r% D0 n8 y
One-way analysis of variance, 单因素方差分析/ @' c! L* ]; S% Y
Oneway ANOVA , 单因素方差分析7 x- t$ J$ ?* z, T* B J/ d
Open sequential trial, 开放型序贯设计4 T6 r0 f' v0 O$ @& U: S& c* S
Optrim, 优切尾0 t% l2 X) k4 A; C
Optrim efficiency, 优切尾效率
; Q( l. X- p0 e% S, r, POrder statistics, 顺序统计量
4 \( D/ c$ `8 l2 a6 _' TOrdered categories, 有序分类
2 p+ p5 n- U1 c$ R: I' a5 G; _Ordinal logistic regression , 序数逻辑斯蒂回归! Q m! Q) J4 A' e1 Z1 _9 a
Ordinal variable, 有序变量; W, v4 `* T8 C9 ^8 \9 O* L# |, N' ?- a
Orthogonal basis, 正交基
. R1 O9 b8 |2 |Orthogonal design, 正交试验设计' ^$ [9 s3 w& S. @1 f
Orthogonality conditions, 正交条件: |! o `% e1 P% X' X
ORTHOPLAN, 正交设计
J+ m: f3 k: o& U! t- n+ q( KOutlier cutoffs, 离群值截断点, J' b8 Q [& I4 z# P' s
Outliers, 极端值. R' l7 ], b/ r- n" S: k( R
OVERALS , 多组变量的非线性正规相关
" U' d/ ]* r( `$ N* G8 Q0 I xOvershoot, 迭代过度
* h. X3 y$ R4 mPaired design, 配对设计
2 W7 g( J, v* M1 T7 o4 L1 OPaired sample, 配对样本 F+ m5 P+ f: ^. e" |) O* Y' G. L
Pairwise slopes, 成对斜率
- o3 M; `6 _) W3 e# S0 B7 a fParabola, 抛物线$ ~" p) j% w( V; h/ S- E
Parallel tests, 平行试验1 b$ V* x) h- U) z7 T
Parameter, 参数
" h8 k' S1 x2 o, \Parametric statistics, 参数统计! V! q! {! ~8 b
Parametric test, 参数检验
3 y, D% z- j; g4 cPartial correlation, 偏相关
4 k4 k* B' n( e: w/ [Partial regression, 偏回归
* e- g/ x6 f' e/ VPartial sorting, 偏排序
5 L2 U3 ^- }( s9 F/ q$ C! ~Partials residuals, 偏残差% X: j/ ? o; _' O
Pattern, 模式
' i! w: ?+ e/ s$ Z) Z/ i) UPearson curves, 皮尔逊曲线# F4 U+ ? I9 W6 d+ ~3 k6 @
Peeling, 退层
% E; N+ T9 z: ^1 WPercent bar graph, 百分条形图: P+ R) h! `/ Z
Percentage, 百分比
) Q5 \4 l( n+ c _ oPercentile, 百分位数9 D& i" P q1 u# Z1 g( o! i1 s) O" z
Percentile curves, 百分位曲线5 V7 e# |9 C9 b7 Y$ w, i# g
Periodicity, 周期性
, t5 A+ v) ^. rPermutation, 排列8 _7 X5 J2 d2 f' Q$ N
P-estimator, P估计量3 T9 ~- Q1 J! a3 \& a# s
Pie graph, 饼图5 B/ \" k- Q* y! t/ L" `" W- ~
Pitman estimator, 皮特曼估计量9 @9 ?" x- l- ~/ b6 o
Pivot, 枢轴量
+ A& A) j: s) X1 i6 n* L5 ^. xPlanar, 平坦
+ P1 e9 x+ t: qPlanar assumption, 平面的假设' H! f, E5 e; p8 z
PLANCARDS, 生成试验的计划卡2 P3 }- B6 Q% P+ N; r
Point estimation, 点估计5 g: {+ p' e/ [+ ^
Poisson distribution, 泊松分布
& ?1 ]1 v6 }- G) L- c$ C4 ?Polishing, 平滑
; @- I! \" p, ?Polled standard deviation, 合并标准差. L7 e G4 K N o; J$ e
Polled variance, 合并方差
/ v) l& ?6 I: [7 k* rPolygon, 多边图2 V' G" P; f: t, X( S
Polynomial, 多项式
' a" d5 k; P) X; t0 bPolynomial curve, 多项式曲线
0 \( m8 C& t; P B* j+ m* Y5 }/ `Population, 总体# [# h2 l2 X* L
Population attributable risk, 人群归因危险度
: p+ f) p, _5 V! s% e- [Positive correlation, 正相关( b% h ?+ w& M: [& n. {5 ]
Positively skewed, 正偏) a9 U2 [. j$ ]1 s! r9 j
Posterior distribution, 后验分布, O5 f$ F- z( s8 h
Power of a test, 检验效能
' c6 M$ u' H q& _+ S6 wPrecision, 精密度
1 F' ^$ K& x0 R* ^Predicted value, 预测值. U' w" a: \8 q0 N4 @1 U! i
Preliminary analysis, 预备性分析
% M' o* ~. x8 F8 x( I! O9 ]! K' ]( `Principal component analysis, 主成分分析2 I. Z( Z' |% M+ u% E
Prior distribution, 先验分布
9 r" p4 `& @+ b, W* pPrior probability, 先验概率9 C& H0 C% h) d" f' L. W$ v- M
Probabilistic model, 概率模型
% o6 Y3 V6 x6 O4 Kprobability, 概率* x4 p6 H9 e7 U. {
Probability density, 概率密度* F0 k& R: ]0 b" J' Z: v
Product moment, 乘积矩/协方差5 b# p3 D, ~4 `6 k0 ~
Profile trace, 截面迹图/ I' }& r3 F$ R; J0 ]2 \( u
Proportion, 比/构成比
! v9 l6 J8 G$ }2 T% w' XProportion allocation in stratified random sampling, 按比例分层随机抽样/ o6 L+ o+ {. A
Proportionate, 成比例7 E9 f2 p0 n* a. J4 ?
Proportionate sub-class numbers, 成比例次级组含量
; k6 z. ` h* V- W( S* v: B2 x' u% uProspective study, 前瞻性调查
; D( Z, a4 j9 A, V4 {Proximities, 亲近性
3 W$ T; F5 V P# \Pseudo F test, 近似F检验
: X1 N# b1 q$ d$ D0 h& Z Y: fPseudo model, 近似模型9 S9 l+ _3 _, |# R+ E
Pseudosigma, 伪标准差
0 i5 d2 B8 M1 v4 }/ [1 GPurposive sampling, 有目的抽样
. Q M- t% ]( g2 wQR decomposition, QR分解
$ _0 \ F) D$ G& }. g: Q$ f3 gQuadratic approximation, 二次近似5 m, c+ ?3 O& |5 _, E+ V* C5 m
Qualitative classification, 属性分类
9 d6 a/ I- X, A- ?- E; @9 s+ Z1 UQualitative method, 定性方法
R+ N; M' l/ z2 lQuantile-quantile plot, 分位数-分位数图/Q-Q图: V) p% ?. p) ?( O% f6 R, R
Quantitative analysis, 定量分析: E% v. O2 Y. H/ |
Quartile, 四分位数9 w+ }0 L+ ]8 l8 C! i( n. c
Quick Cluster, 快速聚类8 X( G- s) L P' X; U- }: h
Radix sort, 基数排序# C6 M( p" l2 M! v
Random allocation, 随机化分组
; V. H/ M' e& ~+ b) gRandom blocks design, 随机区组设计
% h. j' ]) j) P3 QRandom event, 随机事件
2 g4 D5 U6 y: q: g- v, mRandomization, 随机化& Z* B& U( |2 r: }: v: n; Y
Range, 极差/全距
* t2 S9 G: V0 B' O$ z% C$ ZRank correlation, 等级相关
. p5 J( j" j$ H7 U- u9 hRank sum test, 秩和检验
- a8 p3 T: Z" N8 L- j7 \, bRank test, 秩检验 }6 X5 F0 E/ J" s8 S
Ranked data, 等级资料
0 {& Z4 J% H; v0 Y, F: H8 fRate, 比率
# ]; k2 \- \, u& ~8 n0 R2 w6 }7 D. nRatio, 比例: S$ M+ |& k: |. {" {/ A/ g& X2 \: g- I
Raw data, 原始资料, K T( C5 `: W* Z V- f
Raw residual, 原始残差
: M2 Q% A9 j: j! N/ y; J8 |Rayleigh's test, 雷氏检验
. d9 D: `3 [! \; S' _Rayleigh's Z, 雷氏Z值
+ E, k7 D! \ B# \Reciprocal, 倒数# A8 u& I! v' {4 D
Reciprocal transformation, 倒数变换
; Y: t6 u& N5 h9 M% R+ lRecording, 记录
# F! i- @% }* i5 {6 p* M) Z! y1 A/ zRedescending estimators, 回降估计量6 g$ z/ S0 B' a' U1 M3 L- z8 [
Reducing dimensions, 降维, d" p- P# F3 X# O0 w; N
Re-expression, 重新表达
7 v6 f/ j, f2 C1 }2 v* r1 K6 ~- cReference set, 标准组" _; k/ U* K; V/ c) p
Region of acceptance, 接受域3 L( n3 h8 a% s5 ?) R1 o
Regression coefficient, 回归系数% N: Z1 y2 k' n* b5 V
Regression sum of square, 回归平方和
5 `1 H9 f$ N" W( M& |Rejection point, 拒绝点7 e1 q* ?: ]+ ?9 x3 k
Relative dispersion, 相对离散度8 T9 n' b; [! k4 G! p; |
Relative number, 相对数
7 R0 _- N4 @$ o6 XReliability, 可靠性
% e" V$ H2 S# _ jReparametrization, 重新设置参数
9 U7 M% P& K+ m ?' o1 m/ @$ kReplication, 重复
0 N& N1 n2 I3 {# g* x& t( jReport Summaries, 报告摘要. s; P9 m3 B( t$ T
Residual sum of square, 剩余平方和* \6 t3 |7 B/ E( E
Resistance, 耐抗性
2 S6 N& U% I. F8 AResistant line, 耐抗线2 K8 x( }, q+ M7 [5 i- D2 ]
Resistant technique, 耐抗技术0 Q; V l/ j1 c; Q
R-estimator of location, 位置R估计量
+ }. R% d7 D p. T7 DR-estimator of scale, 尺度R估计量
: D6 O P2 `( ~" ~# C8 P: P- ERetrospective study, 回顾性调查% \% V1 S3 p0 U
Ridge trace, 岭迹
/ S( K7 ~! x* q0 |# ~Ridit analysis, Ridit分析0 ]; l3 _, e/ z9 v% O
Rotation, 旋转/ A# A- _, |% P" a R( N# g# j' g5 R
Rounding, 舍入1 Z8 v, X; e+ l% |* K
Row, 行
6 _ F# P* r' {9 p- ]Row effects, 行效应
6 s( J1 A1 u$ x2 aRow factor, 行因素. D7 ?- ?8 }( b6 ^5 R
RXC table, RXC表& P. k) e# e4 j' a8 t+ ]- O
Sample, 样本
' b' N3 R+ t S0 h, eSample regression coefficient, 样本回归系数
/ |- c' h8 ?. l: \6 LSample size, 样本量
3 L# Y5 J) J9 x CSample standard deviation, 样本标准差
7 w% e: x% K# M1 p) I: K- P5 E& F( LSampling error, 抽样误差
( g: L3 m) {+ K f7 xSAS(Statistical analysis system ), SAS统计软件包
T5 F1 r6 ?0 V8 o- P; O( xScale, 尺度/量表
( }/ H- w8 A r t' HScatter diagram, 散点图
& G: t- x1 O5 }9 I( Q& `Schematic plot, 示意图/简图7 }6 x5 J7 i' J) P$ O
Score test, 计分检验
d$ R+ I/ E; W: ~Screening, 筛检3 O( T" \2 ~% \3 O2 E; l
SEASON, 季节分析
0 V8 d2 @% \3 u& M t6 HSecond derivative, 二阶导数
8 N: m$ N* ?5 {Second principal component, 第二主成分
) ]/ N) S. i2 J; R N( w, ^9 @SEM (Structural equation modeling), 结构化方程模型 , @' o/ l5 h; {
Semi-logarithmic graph, 半对数图1 `4 z. q9 }7 l7 h3 |, K/ p7 {$ p
Semi-logarithmic paper, 半对数格纸' C- W# N9 d8 A
Sensitivity curve, 敏感度曲线
) C; b8 X \. J' l% dSequential analysis, 贯序分析5 r X* V$ }) u8 n0 v, Q( z; z
Sequential data set, 顺序数据集
* s% J. J8 j# ySequential design, 贯序设计* \6 V. c! H- `, I
Sequential method, 贯序法
: Z1 ~8 j3 g7 q7 ], k( DSequential test, 贯序检验法5 ]; L; m6 u& x! t% b# Z2 | Z8 ], @
Serial tests, 系列试验
3 o6 Q0 b* R9 A6 bShort-cut method, 简捷法
1 N3 r3 R3 ?$ ^7 Z9 wSigmoid curve, S形曲线( f/ g+ _; z3 G/ R3 `: n
Sign function, 正负号函数
8 }/ E6 j0 ?# G3 ? OSign test, 符号检验6 r2 _' V3 Q: W- h) ]9 T
Signed rank, 符号秩
, b' y0 O- I- ^ c/ ^Significance test, 显著性检验 w/ P5 j3 ?6 w# W! \+ y
Significant figure, 有效数字4 n: `( k. C) Y$ |: Y
Simple cluster sampling, 简单整群抽样* h6 l# v1 ~. t: M1 J
Simple correlation, 简单相关" O v! d: ]0 y. P: o& E
Simple random sampling, 简单随机抽样' S" h; a1 o# C! [
Simple regression, 简单回归1 ^0 w) V1 ^$ O8 p
simple table, 简单表9 ~1 _' O/ V: r: H0 N
Sine estimator, 正弦估计量
5 p% F5 y$ \# ~$ V7 K4 _Single-valued estimate, 单值估计
4 v X/ y G+ ~5 nSingular matrix, 奇异矩阵' G4 j* M0 }. A5 }" S
Skewed distribution, 偏斜分布
, c1 d( {5 x: U9 DSkewness, 偏度
7 h# U1 }9 F* T9 b4 VSlash distribution, 斜线分布
: j, P h$ }: GSlope, 斜率
: e* l9 f. y4 D6 a* |% uSmirnov test, 斯米尔诺夫检验1 N6 m6 Q, A( ?1 l, ]; L
Source of variation, 变异来源
, y; ^7 c, L* ~+ k+ hSpearman rank correlation, 斯皮尔曼等级相关* h3 q8 o' t+ o9 Y
Specific factor, 特殊因子; N% B. R5 Q( f' M* [5 Q2 O
Specific factor variance, 特殊因子方差
% [0 M* b' k3 G4 n1 P) S. ?2 CSpectra , 频谱
. E% f9 |3 l- {3 m* v, LSpherical distribution, 球型正态分布) j/ o; }, p1 {& `
Spread, 展布
) e) q) |8 j) U2 F4 aSPSS(Statistical package for the social science), SPSS统计软件包
% d$ O* \) ]0 Y/ d) ^8 oSpurious correlation, 假性相关
, g. C6 [0 c* L" A7 J( WSquare root transformation, 平方根变换2 K& G8 @6 F6 L+ ~# I" y
Stabilizing variance, 稳定方差
; u: L! l( }7 v8 L. YStandard deviation, 标准差
5 S1 E! p ^+ {$ C; o8 `Standard error, 标准误 L" ~1 t1 \% j6 D3 E# d
Standard error of difference, 差别的标准误
8 C5 z$ g `, Q: l: kStandard error of estimate, 标准估计误差
( b$ K8 t- ~% u2 I; y* ~1 KStandard error of rate, 率的标准误
$ W6 b( D5 ]1 Z8 k6 D2 m- {3 tStandard normal distribution, 标准正态分布# k4 b) L- r* v. o1 w8 D, h( E B
Standardization, 标准化$ [) x+ [1 M6 L. l" z
Starting value, 起始值" _# i# w- C1 N0 U
Statistic, 统计量
4 k% [6 a+ ?/ ~. w. E, oStatistical control, 统计控制
+ O O3 g8 Q8 @6 P2 _- c9 a, d/ YStatistical graph, 统计图0 N) ^5 ?+ z/ J0 Z
Statistical inference, 统计推断% g$ L8 J- K* U1 G" [0 s% K: d/ L
Statistical table, 统计表
4 A$ J* p9 A$ V, r: p3 FSteepest descent, 最速下降法
/ R, Q& Q, m9 \9 X- u4 iStem and leaf display, 茎叶图
! T" k9 O; B% ~% F9 y! q! xStep factor, 步长因子, p+ |, V5 X# `2 k- |$ F5 f
Stepwise regression, 逐步回归; m) m4 X' C8 _4 y" E! R0 F
Storage, 存$ t. k4 c! W5 b/ u) Z3 j
Strata, 层(复数)
$ N4 D: ^, L1 f9 cStratified sampling, 分层抽样
* u1 o- D t2 Y" C) @Stratified sampling, 分层抽样/ x# @ ]6 e x% _" E0 }
Strength, 强度& D5 |' J# x# u: m8 L( X2 N% T
Stringency, 严密性
h4 M* V, s1 ~5 I$ U9 HStructural relationship, 结构关系
& K$ s1 F6 G3 U# {, c JStudentized residual, 学生化残差/t化残差
7 @5 t) @9 W5 U/ p3 B0 TSub-class numbers, 次级组含量9 }, {6 |& a$ S1 M
Subdividing, 分割; k+ U4 I0 _; K5 [! N
Sufficient statistic, 充分统计量# ~# r* a* W! v, X8 [4 f
Sum of products, 积和
8 s: M7 G P( ySum of squares, 离差平方和
& M3 I" Q2 f, O/ s' A$ a* ASum of squares about regression, 回归平方和# x& \6 d( f( b9 t
Sum of squares between groups, 组间平方和- ?7 N8 B* p$ A; s2 T
Sum of squares of partial regression, 偏回归平方和
* F1 q, Z- F) O( f9 _5 ^) nSure event, 必然事件
+ Z8 X" {* |8 y; Y/ D3 S- \Survey, 调查
) h& V# [( j: z% i" y" L8 rSurvival, 生存分析2 l( v! ^% m! R
Survival rate, 生存率' m. ~2 Z6 i; s# _
Suspended root gram, 悬吊根图5 r3 x) a6 ~( L
Symmetry, 对称* V, F. u' S( L% ]; i4 S; q
Systematic error, 系统误差2 d, a9 F/ {) b* `: U
Systematic sampling, 系统抽样6 E* `8 l( x [' m+ h$ d: n
Tags, 标签
' z+ V' g$ k7 G, ^4 w" @' X( qTail area, 尾部面积+ a5 E6 a( S, K$ m- p) J# `( H
Tail length, 尾长- R* y- p& a" U5 Z6 i
Tail weight, 尾重. r1 v) T2 ]8 j( N2 U
Tangent line, 切线" Q B4 r& k' h0 v$ Q
Target distribution, 目标分布9 K2 s. v' i1 ~/ T2 d3 v/ W% N& v
Taylor series, 泰勒级数
+ P6 s, T, i N: `- e: B3 STendency of dispersion, 离散趋势
7 O7 s/ P4 S9 }4 D: v# WTesting of hypotheses, 假设检验
7 E/ H6 K. V: w- }* A! B% ^Theoretical frequency, 理论频数
4 @% L0 n% Z0 k6 L7 A% S; {* X, RTime series, 时间序列
% Z3 D9 {& }8 hTolerance interval, 容忍区间6 \* G, \* w# u+ g
Tolerance lower limit, 容忍下限 u& x) v: d8 w4 T, J$ E3 |
Tolerance upper limit, 容忍上限
/ z2 D9 s# {. T4 J$ Y) LTorsion, 扰率
! c, `+ a, a5 U% ~Total sum of square, 总平方和
2 z& c& _/ T0 N8 y. |' E# g0 YTotal variation, 总变异 k' |0 [' T- F- `4 `0 { Z
Transformation, 转换! t0 A5 c2 V! ]" u" v$ [. H% [
Treatment, 处理
v; f7 Z. w S4 W& M5 RTrend, 趋势6 R$ V5 _& M. V$ _
Trend of percentage, 百分比趋势; d- T* o- W0 e9 \, t
Trial, 试验4 } e1 j: y7 B( \9 X r
Trial and error method, 试错法
* e) `/ c- G( w- `# @+ NTuning constant, 细调常数4 D" f2 l0 a: [4 b6 ]/ C8 T
Two sided test, 双向检验- L+ n3 M: R i) O' j
Two-stage least squares, 二阶最小平方
8 v H, x: _ r; {9 GTwo-stage sampling, 二阶段抽样
) F! k* q' C4 {3 d% NTwo-tailed test, 双侧检验
' l) {, V: Y1 ?- A* oTwo-way analysis of variance, 双因素方差分析: }: s; n4 J* T: |+ H' l0 _8 M _
Two-way table, 双向表
! F0 L2 ~4 G, q6 p. Q" a4 D2 W, y5 _Type I error, 一类错误/α错误; ?, `; C; Y3 S* h5 s# x
Type II error, 二类错误/β错误
2 K) t/ m) q. lUMVU, 方差一致最小无偏估计简称
4 a9 L/ n2 {$ |+ s3 _8 }# q5 pUnbiased estimate, 无偏估计* |6 p* |# R; b3 t" `" P
Unconstrained nonlinear regression , 无约束非线性回归- r! E* R+ J3 z; ]2 U
Unequal subclass number, 不等次级组含量
9 n. I; ^. A9 I) L6 \5 nUngrouped data, 不分组资料
. I* S) [: e2 X4 u4 [8 EUniform coordinate, 均匀坐标
. M' _5 K' D& w& |Uniform distribution, 均匀分布
: f( }6 z2 d$ VUniformly minimum variance unbiased estimate, 方差一致最小无偏估计$ W5 A4 X$ x: m3 ?* S- l- v
Unit, 单元- S7 L% ^9 A% G( X$ t
Unordered categories, 无序分类3 g) Y4 V; Z* }% q' f
Upper limit, 上限! n6 A2 N) _1 b6 _; d
Upward rank, 升秩
) g" u8 @, j! |8 N& V& N5 l+ T( ~Vague concept, 模糊概念
, i- z4 P8 C1 h6 E4 u5 S- A- r. vValidity, 有效性- D/ A# q5 K( S8 s
VARCOMP (Variance component estimation), 方差元素估计
% M6 `+ p' h5 i2 N K% cVariability, 变异性0 \$ V6 s3 z. u5 R" K
Variable, 变量
7 Y" V7 R7 c5 ]) N. NVariance, 方差
: `, C5 J0 D9 f z2 I sVariation, 变异
5 t6 N5 q: f! gVarimax orthogonal rotation, 方差最大正交旋转
" r; j* b' ^; o$ HVolume of distribution, 容积) R A$ I) i( v9 L, X
W test, W检验6 o- i5 p& L3 |0 g, ?
Weibull distribution, 威布尔分布
7 }- q. p, x3 T B& e+ s8 `% p( E FWeight, 权数- `9 e( t Q* m
Weighted Chi-square test, 加权卡方检验/Cochran检验0 x( G. D2 S" V6 ]- s0 x: w4 l
Weighted linear regression method, 加权直线回归
! Q* u6 m7 \& PWeighted mean, 加权平均数
) E b, D. w' R E a9 k- Z- yWeighted mean square, 加权平均方差& `& G' V$ f. B' l& w# y- A
Weighted sum of square, 加权平方和
3 F8 L; b$ {2 K( @* FWeighting coefficient, 权重系数2 U3 W+ h& K# {
Weighting method, 加权法 5 j6 v" x) W" l4 H3 T1 K9 b( p" a
W-estimation, W估计量3 f/ g, {6 S: ^6 S8 r9 w% s; `: _
W-estimation of location, 位置W估计量. Z& Q2 l; b" [4 E
Width, 宽度8 ]- P1 x) _! K) h$ [ u+ R2 T% @# |" v e
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
8 } v7 k! u3 UWild point, 野点/狂点
' ?& q# {) l4 `6 C0 dWild value, 野值/狂值& O; x$ |+ w. y( V+ y0 s! j& e- k/ h
Winsorized mean, 缩尾均值
! m( C8 p7 G! y$ f$ F1 r& GWithdraw, 失访 ; U/ k" I: O/ B: J; \
Youden's index, 尤登指数" U& @9 f2 k5 A! r ~
Z test, Z检验
; i* h0 B. N, O: G: `+ F9 h9 o! CZero correlation, 零相关
. B7 ~* v; g' [& [0 ?3 h: n9 pZ-transformation, Z变换 |
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