|
|
Absolute deviation, 绝对离差) m+ N1 h5 v. S) u
Absolute number, 绝对数" q$ C# W5 S5 N
Absolute residuals, 绝对残差& J7 [2 K ^. U& H2 Y' o, c
Acceleration array, 加速度立体阵* X5 b; H; T3 {! Z- \/ `
Acceleration in an arbitrary direction, 任意方向上的加速度
/ F, z5 }. V% P! NAcceleration normal, 法向加速度
9 t2 H+ R& d4 ~Acceleration space dimension, 加速度空间的维数
; M8 t8 Y6 g4 F2 U+ v/ p+ H5 YAcceleration tangential, 切向加速度( w& }, p/ ]+ Y+ k
Acceleration vector, 加速度向量
8 W2 J3 m0 Q3 u1 ^6 U; Z6 B, t4 gAcceptable hypothesis, 可接受假设
& ]6 f$ p b6 kAccumulation, 累积, V5 ^! q" d) m: j4 H7 I
Accuracy, 准确度
$ {. U% i9 D% D: q9 wActual frequency, 实际频数: N( K% V6 W/ c) ^( I, {1 s& i
Adaptive estimator, 自适应估计量6 H# C) Z! x+ A7 K
Addition, 相加
' m+ z% Z7 f& S9 s/ ^Addition theorem, 加法定理
# ^, F3 ^' W6 b/ B+ VAdditivity, 可加性* y; q1 S' u) K% a3 f A8 g
Adjusted rate, 调整率3 @* P' S( g" K7 U
Adjusted value, 校正值
5 D0 A2 u Y9 v, NAdmissible error, 容许误差7 l Q# q8 x9 C" c
Aggregation, 聚集性9 e, X8 W4 L. {4 g& V
Alternative hypothesis, 备择假设
9 T/ H+ v M8 m* GAmong groups, 组间
- W( c2 N8 }/ D( U: x/ n# KAmounts, 总量7 h- E1 b( z" Z' q8 c: @3 r1 r
Analysis of correlation, 相关分析. f/ o6 R3 J1 D- d3 N# r
Analysis of covariance, 协方差分析
$ }! ]- d" O/ @/ f) zAnalysis of regression, 回归分析
5 z! A9 I9 A5 t5 L1 s9 gAnalysis of time series, 时间序列分析/ x1 a8 A# a5 \1 }6 }5 w1 g' I
Analysis of variance, 方差分析
* r% d- y, w3 D" ZAngular transformation, 角转换
, x; ?3 [9 {3 L5 w! Z& HANOVA （analysis of variance）, 方差分析
3 ~; y7 u4 g& ]! I' [. HANOVA Models, 方差分析模型2 O7 N# `% j M
Arcing, 弧/弧旋% c" `! t a5 x
Arcsine transformation, 反正弦变换" K) i# o/ ~& a! ?9 u
Area under the curve, 曲线面积
1 g k- u7 ~( n" A0 c) AAREG , 评估从一个时间点到下一个时间点回归相关时的误差
5 _ B) O* l; CARIMA, 季节和非季节性单变量模型的极大似然估计
+ |( R3 M: H+ ZArithmetic grid paper, 算术格纸& c ]! l* j* F, k4 x3 l! N
Arithmetic mean, 算术平均数
) J3 o8 n" I6 b' p; hArrhenius relation, 艾恩尼斯关系, w0 M) I' y7 E$ w6 H( a/ b+ b
Assessing fit, 拟合的评估 ^; w# Q5 W, T' C8 E3 }9 m
Associative laws, 结合律! E5 M) D' l/ P a& H
Asymmetric distribution, 非对称分布7 `4 I% k# e. v
Asymptotic bias, 渐近偏倚
G: W* g* ^: v; W- s- L! ^/ H6 v: C4 IAsymptotic efficiency, 渐近效率: P5 O( B5 V+ A$ M2 h! I: Q: r4 R+ l
Asymptotic variance, 渐近方差
* m" E0 S. P& U6 O% fAttributable risk, 归因危险度
2 [1 \6 O/ o; U- D4 rAttribute data, 属性资料- m- p9 t" l! t) }7 ]& F+ |% _
Attribution, 属性( A+ E, R4 P/ J$ I
Autocorrelation, 自相关
* b/ v; `7 R( P l7 A1 w$ vAutocorrelation of residuals, 残差的自相关8 m3 L/ p$ U$ W# l
Average, 平均数& U! X# ~# _+ g. Q
Average confidence interval length, 平均置信区间长度" j: l: g& u2 j! ?" W5 s! e5 p
Average growth rate, 平均增长率
3 }! u9 F9 Z9 v7 @* ^Bar chart, 条形图5 U! W: A2 R/ w+ |6 d9 l Q5 @
Bar graph, 条形图+ Y8 V# r+ x3 V' N8 l
Base period, 基期/ A7 x$ d6 x6 p: ^( V c
Bayes' theorem , Bayes定理
) n- |! Q; v1 l7 T1 U' LBell-shaped curve, 钟形曲线& G* |9 P( I$ L; d
Bernoulli distribution, 伯努力分布
) m& k4 j/ d: P- a/ c8 y* ZBest-trim estimator, 最好切尾估计量+ }, U5 c2 q! m4 [* H6 T
Bias, 偏性
* k1 m( ~% F. M: A8 \ }Binary logistic regression, 二元逻辑斯蒂回归, O/ a9 E* z! J4 o; V8 A. n6 ?
Binomial distribution, 二项分布0 B- D# j: i% ?2 D* ~
Bisquare, 双平方1 Y6 W5 {5 G; }% ]% \* g) W% b
Bivariate Correlate, 二变量相关6 E: B, A0 H- l- ] y
Bivariate normal distribution, 双变量正态分布
' \* g9 U1 j0 ^ q6 rBivariate normal population, 双变量正态总体+ C8 p5 B( A h9 e; q' d7 _
Biweight interval, 双权区间8 o& E/ a& c* w: F
Biweight M-estimator, 双权M估计量8 ^1 q" e; f# `' h! U( h# x8 @9 q
Block, 区组/配伍组0 B- z$ q3 h+ @) ~6 [4 A) p7 V
BMDP(Biomedical computer programs), BMDP统计软件包( ~3 I; d+ p( o
Boxplots, 箱线图/箱尾图( w- n- y4 ^+ ^; t9 X0 J" F
Breakdown bound, 崩溃界/崩溃点$ i% h; E4 _+ P# `- u8 u
Canonical correlation, 典型相关
/ n9 S. l- V6 ~' O) pCaption, 纵标目. @1 v! V5 Q! b/ V$ \
Case-control study, 病例对照研究
3 b7 B) j* D( mCategorical variable, 分类变量
8 T' V7 [) A, k8 B1 I. w+ xCatenary, 悬链线
, v4 m. @9 H4 @ C8 O" |Cauchy distribution, 柯西分布' R. g6 @* K% a7 o7 Y
Cause-and-effect relationship, 因果关系
1 `8 _# P* f5 r! ]' }Cell, 单元7 ^. P' r) K; l
Censoring, 终检" J0 H, k, |/ z7 O
Center of symmetry, 对称中心
0 x" {, f* _: `1 Y, ~' _2 QCentering and scaling, 中心化和定标
3 [2 s! }: y7 GCentral tendency, 集中趋势; r, _9 \/ r: @$ z
Central value, 中心值
1 `: o) H, \) I8 l* kCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测! X. @# ~9 l" |7 Q: |' ~" ?7 z
Chance, 机遇
$ ^2 ^! w5 R6 {+ x' GChance error, 随机误差6 D( j2 H; ^5 h& j' O
Chance variable, 随机变量
) r* n4 `- h1 wCharacteristic equation, 特征方程8 r' T r1 G- u1 ]
Characteristic root, 特征根
, C# O( h# L9 h ^$ w2 Y4 \Characteristic vector, 特征向量0 @( B( X. V' T8 \
Chebshev criterion of fit, 拟合的切比雪夫准则/ m( V+ b& g% D# ^
Chernoff faces, 切尔诺夫脸谱图% ^5 K9 [, w! Q, F% P& \
Chi-square test, 卡方检验/χ2检验" {, ~8 t0 l/ J& M7 S
Choleskey decomposition, 乔洛斯基分解$ P5 ~8 {, D$ l; z n3 \; I
Circle chart, 圆图
( D8 w. ^" V$ K0 y9 nClass interval, 组距 B" R, a! K" I( [) f7 i
Class mid-value, 组中值
8 v' x4 ~" h. j( c* |Class upper limit, 组上限4 }6 \ s G( f" Y5 B2 A
Classified variable, 分类变量
% h9 F: E0 A& T$ {Cluster analysis, 聚类分析
0 W2 t! g5 I7 W3 e" zCluster sampling, 整群抽样# |* ~7 ]2 @* x. `/ q
Code, 代码
! b6 U4 \ b/ c# O1 ?9 X2 XCoded data, 编码数据& r7 U5 c' i4 Q( ^% O
Coding, 编码
|5 M* o& X2 w5 A- r9 dCoefficient of contingency, 列联系数; O7 q% W& k' x: ]" u& H
Coefficient of determination, 决定系数7 B( b$ j2 C5 i+ X9 B* F
Coefficient of multiple correlation, 多重相关系数4 |6 D: }- v5 z* J$ S1 |( y: l
Coefficient of partial correlation, 偏相关系数6 T* q( ~2 ~+ p- e
Coefficient of production-moment correlation, 积差相关系数( E7 \0 l+ i2 g+ a/ s
Coefficient of rank correlation, 等级相关系数6 E: O2 D* m+ H4 D
Coefficient of regression, 回归系数
; M6 O- H8 r5 P/ X- f# k9 {7 Q9 J/ VCoefficient of skewness, 偏度系数* `* i1 C) A7 H2 D. _0 Q0 r
Coefficient of variation, 变异系数
) u% A" Y' y$ n; M q h6 y& J" s FCohort study, 队列研究
: [7 V4 P6 `1 jColumn, 列+ k& X- ?' u) C# d1 w
Column effect, 列效应. S* d! x/ D2 k
Column factor, 列因素
' C% p# `! z9 r* C! b4 f& eCombination pool, 合并
4 L: z; c3 J6 C# E E: C' RCombinative table, 组合表; h! ] v9 [: ^8 b T
Common factor, 共性因子- M, w: R- Y8 J @: ^7 f" _
Common regression coefficient, 公共回归系数- J+ n8 R2 P! N
Common value, 共同值/ m' S# M3 s! }& r
Common variance, 公共方差
: B+ G7 I3 } D/ U* iCommon variation, 公共变异, N/ p* I+ d% ?/ w6 }* Z. M
Communality variance, 共性方差
- a7 v1 H4 ~. ~' @( G6 mComparability, 可比性
: s1 ]6 e3 J4 o0 o) i4 XComparison of bathes, 批比较0 W5 q+ E$ V$ S: j% z8 `1 }
Comparison value, 比较值
9 ]6 c; z# F" ^" \# p3 M0 KCompartment model, 分部模型
5 s7 G1 a& Z2 T/ s0 e/ V) bCompassion, 伸缩/ P& e7 K# H1 q8 g5 i
Complement of an event, 补事件
. A6 n: T5 N! n! ]) ~Complete association, 完全正相关
, Y; @% u& }- S% }8 _ JComplete dissociation, 完全不相关
|; X9 X) A ]Complete statistics, 完备统计量3 J! m8 r: E" v' h7 Z, T
Completely randomized design, 完全随机化设计
9 t7 e9 p6 @% H; y0 eComposite event, 联合事件
! l! u; p: v/ @2 SComposite events, 复合事件
0 F& R& f) D: Z9 U; SConcavity, 凹性, D; K$ s) \+ b w4 J/ Y
Conditional expectation, 条件期望
4 `( H; @8 L. O6 kConditional likelihood, 条件似然# m3 N3 M7 k4 c2 B1 s- T9 e
Conditional probability, 条件概率9 }7 B$ r. J+ ]$ \4 O& A
Conditionally linear, 依条件线性
5 K* T8 x# h. d4 b6 E) wConfidence interval, 置信区间
5 W5 d* ]0 n" O! |Confidence limit, 置信限
5 b V: p+ X1 {5 [7 jConfidence lower limit, 置信下限
9 ^& x& M1 u- x, `5 V4 _Confidence upper limit, 置信上限
& ? u, i' F$ A0 s7 QConfirmatory Factor Analysis , 验证性因子分析
0 K- d& ?; ^4 \1 yConfirmatory research, 证实性实验研究) P; x$ V% d# w0 {* I$ u
Confounding factor, 混杂因素
! h& s6 d* @ V, Y* kConjoint, 联合分析
' U; p0 Q) z; r8 x: Y: _. a& uConsistency, 相合性
% r5 E2 `( ]: T+ A( kConsistency check, 一致性检验
3 z: q0 L1 f! G' oConsistent asymptotically normal estimate, 相合渐近正态估计
8 p& M6 U6 {& j4 LConsistent estimate, 相合估计
; i7 T/ b `& e( J4 \Constrained nonlinear regression, 受约束非线性回归4 t. u2 U) M6 H" C* c5 f5 t" H
Constraint, 约束; v% ], t0 n+ v2 ? e
Contaminated distribution, 污染分布
) U5 n. b. a' ~" b( j7 wContaminated Gausssian, 污染高斯分布
3 M0 R3 L* S8 B# N5 ?, A, gContaminated normal distribution, 污染正态分布* {2 h. `" E; ^; n2 b0 O* C
Contamination, 污染
/ [. q* N' K( F! q& o9 o4 ^ @Contamination model, 污染模型) T' ^8 l8 r9 M
Contingency table, 列联表0 f' N3 X( D4 h I) Q* f/ Z1 n
Contour, 边界线
1 D8 G+ Z" j! |/ t( _6 HContribution rate, 贡献率: _) ^1 J* @6 e+ \, b
Control, 对照+ k5 _* y) X& w: F) v6 e
Controlled experiments, 对照实验5 @+ X( j5 [" Y+ D
Conventional depth, 常规深度
3 X- u! \" F% u+ zConvolution, 卷积, O: z0 u$ [. y/ N' r% N: a
Corrected factor, 校正因子
5 M: o5 a* E# W$ {) v+ M# JCorrected mean, 校正均值: R3 a6 r6 X) B, @7 {
Correction coefficient, 校正系数, ]2 j+ V4 o! a$ c
Correctness, 正确性
]$ z. q/ T1 ?/ z& k+ ~- gCorrelation coefficient, 相关系数
* p. c: s* _, k3 ]- g, A; RCorrelation index, 相关指数* I, \" g& ^ ?: J+ g
Correspondence, 对应; \. \/ Q; `; y$ K
Counting, 计数
9 @! ~. l. R8 P& ^7 T* LCounts, 计数/频数7 t, D: k% e* G& N
Covariance, 协方差
`8 W. G# s2 E; h; mCovariant, 共变 2 k1 r0 A- x6 F( q7 d4 C5 \
Cox Regression, Cox回归; v0 F+ X) L& Z! m; k2 q8 S
Criteria for fitting, 拟合准则+ C( k1 X+ J, n) Q% e
Criteria of least squares, 最小二乘准则
: t1 `0 G: Q0 n% z" RCritical ratio, 临界比) @( W$ h9 t, R' r/ @/ Q: e. [
Critical region, 拒绝域
; ?6 T8 B' O! ACritical value, 临界值: e n$ v$ l% r0 e
Cross-over design, 交叉设计
/ s% L, |7 L7 j2 L& Z- g lCross-section analysis, 横断面分析
4 s& V1 \, B3 D6 ~: [: _Cross-section survey, 横断面调查
4 q4 Y. B: Y' g! I+ [/ ?3 GCrosstabs , 交叉表
$ ^2 J2 X' z4 w' E0 UCross-tabulation table, 复合表+ {) i6 J0 v- N4 }! @$ i' X
Cube root, 立方根1 x b) m. J* D. V/ _4 j
Cumulative distribution function, 分布函数2 e' ?+ I9 v1 X2 z# K8 ]" C
Cumulative probability, 累计概率) b8 Z7 c% G9 f% ]: R& I7 j
Curvature, 曲率/弯曲/ y% P" Q! j) n) P) U5 F* K5 f2 F0 d
Curvature, 曲率 V( v9 c5 t2 W" K4 O1 U! U
Curve fit , 曲线拟和 $ R4 s5 P5 `8 Y
Curve fitting, 曲线拟合% w1 F( p% v1 e+ I6 o! R' `5 V* \5 h% I7 _
Curvilinear regression, 曲线回归3 s7 B0 G. o! h/ H; ^/ g1 G
Curvilinear relation, 曲线关系
2 ^7 C5 \% J! C3 i# e+ s* xCut-and-try method, 尝试法" O* B8 a, S f! F1 P7 ?$ m
Cycle, 周期5 d$ M: M# b, G& v' o W, U8 U
Cyclist, 周期性
& g/ V6 c: `( ]4 [$ U# cD test, D检验: `. v2 b; J" w1 M; \) C
Data acquisition, 资料收集
; V; z& Y1 T+ V5 f8 JData bank, 数据库8 c% f% P9 I7 w6 e1 F, |
Data capacity, 数据容量/ B) o, Z# X/ i5 W
Data deficiencies, 数据缺乏
3 |3 l% u: J% ]* ]Data handling, 数据处理
; f3 W, M' d7 ^Data manipulation, 数据处理
, v: T2 `- y0 a' D9 FData processing, 数据处理
* r! f3 {" t% p% T( f# c( D8 jData reduction, 数据缩减) g8 `2 `0 D! P8 d
Data set, 数据集
# A; z$ P1 X3 b2 rData sources, 数据来源
0 K$ C; u: H8 r4 z; [/ UData transformation, 数据变换
: E0 T( e) I/ V6 P& J9 z3 HData validity, 数据有效性; X1 S7 g) W. g5 k& R C% E6 P
Data-in, 数据输入& l# H5 [1 ^7 Y( b# [* k( k& d% V) n
Data-out, 数据输出( X/ Z2 n; T7 r! k. {& r
Dead time, 停滞期
& p' m7 o4 m4 W6 V x1 E" h1 LDegree of freedom, 自由度5 P2 g, W- G# Q. ~
Degree of precision, 精密度
* K1 w" c7 \- j* e5 R2 eDegree of reliability, 可靠性程度
2 v2 B& J) ?/ z4 W& `Degression, 递减
8 ^; V. \" Q# z6 a$ u0 QDensity function, 密度函数
8 f5 a7 s6 `$ B- GDensity of data points, 数据点的密度5 V( B& I+ n/ u8 S+ r
Dependent variable, 应变量/依变量/因变量
+ E3 o5 T3 F+ x, D% N+ DDependent variable, 因变量
2 Q9 ^2 C. R- v6 f% qDepth, 深度
5 S' I8 s% _2 J* W% @Derivative matrix, 导数矩阵
8 d, R8 D6 [* d* D# mDerivative-free methods, 无导数方法) ?( ]/ t7 x8 O. Q! G" y9 M) c% y
Design, 设计. _: c5 E. [. L6 x
Determinacy, 确定性
$ v- {1 I- m. m; } ?Determinant, 行列式
/ [" I5 W9 D& j& a0 ?Determinant, 决定因素2 q+ g) R1 L7 [1 j% y8 Y
Deviation, 离差" F( H6 z0 m5 x3 O: b/ `1 l
Deviation from average, 离均差
" ^4 s' ~# L4 U) B* rDiagnostic plot, 诊断图3 X+ F" r+ H; A3 U3 [
Dichotomous variable, 二分变量& W7 [3 H$ D( |4 W, x
Differential equation, 微分方程( V% m, G) Z; d0 I# A9 S
Direct standardization, 直接标准化法
- `# M8 }: k# J' C* U; EDiscrete variable, 离散型变量; k6 [3 n( d& h$ s" z6 P+ r
DISCRIMINANT, 判断 1 J |4 f Z" @) b9 {5 n
Discriminant analysis, 判别分析
) [. B/ z: x K* W8 fDiscriminant coefficient, 判别系数
3 G* z9 k5 T0 [Discriminant function, 判别值
, x' c2 H: Q0 T5 F& r: F) qDispersion, 散布/分散度3 H+ y6 {3 I8 D
Disproportional, 不成比例的% F: R4 Q* x: A) u2 I% V) V
Disproportionate sub-class numbers, 不成比例次级组含量, t- W7 X' Y0 i$ Z! G2 C* M
Distribution free, 分布无关性/免分布
- b8 b! a S) d1 U' S9 ]( x* UDistribution shape, 分布形状) }& [# m# N4 b' j3 k% r
Distribution-free method, 任意分布法( l4 \* D+ Y( z9 E) @
Distributive laws, 分配律
* O9 r: Z% q( V; `$ uDisturbance, 随机扰动项# A* ?( N9 v1 m, [# W
Dose response curve, 剂量反应曲线
9 q! j; F3 K0 q! i2 U; {% RDouble blind method, 双盲法
, Q$ h* g+ W9 m* i, s. ODouble blind trial, 双盲试验7 }1 P& |& p1 e) b+ \! \
Double exponential distribution, 双指数分布
: X$ g+ X7 d- UDouble logarithmic, 双对数
W5 j X+ @% uDownward rank, 降秩
0 g+ l7 v' W$ g; g" y+ R, M& aDual-space plot, 对偶空间图
5 y+ c5 x% t3 ?( W' |DUD, 无导数方法3 q4 \% ~1 A' A5 `5 F% U/ }
Duncan's new multiple range method, 新复极差法/Duncan新法
( F9 |$ E' [. x/ L3 fEffect, 实验效应. R3 ^+ P5 M L {+ ~7 w9 T3 y% f
Eigenvalue, 特征值
" P* t* X7 q1 [. wEigenvector, 特征向量6 G( T, t4 A8 }1 u
Ellipse, 椭圆: v+ i; T$ D$ U
Empirical distribution, 经验分布
* T8 e, i& Z# S1 NEmpirical probability, 经验概率单位2 V# B1 ?$ x1 M) x
Enumeration data, 计数资料3 c8 }: J# h5 u5 F& c2 r6 G5 f
Equal sun-class number, 相等次级组含量! X& B' B' s: | R" x3 t X# @$ S
Equally likely, 等可能) d/ y) ~" n, I% [8 b R
Equivariance, 同变性, }* X2 Q5 F; T* n$ E
Error, 误差/错误
" j& v% P! \1 ~. N, s U! {! AError of estimate, 估计误差9 m! o1 ?8 ?5 s9 ~% B: i
Error type I, 第一类错误- R# A; R4 R% v: F! L
Error type II, 第二类错误
7 {/ ^( K8 N' d% V! |( g' O# ~Estimand, 被估量
8 L* o6 `3 s5 [Estimated error mean squares, 估计误差均方
+ j H* Z! Q8 ?+ f+ p" KEstimated error sum of squares, 估计误差平方和
5 \" b8 t# S9 W3 l: GEuclidean distance, 欧式距离
- M% h$ x0 u( [( A" ^: CEvent, 事件3 ^ w+ D, H+ m. o4 {/ w' o
Event, 事件
* I1 J5 S% Q3 B7 N) u; j/ v. `6 hExceptional data point, 异常数据点3 I! D/ P/ }. [' s9 C( U
Expectation plane, 期望平面
& ~9 H. F; x/ k) n! BExpectation surface, 期望曲面
! b5 W6 M, P9 N# G% r4 BExpected values, 期望值& h1 V" T- V! w; S
Experiment, 实验
* p% j0 R& ~/ m5 e7 j& x9 SExperimental sampling, 试验抽样 [) Y' {$ v# m! i% l
Experimental unit, 试验单位
: t9 b) f" n! W9 J! X ~2 w& oExplanatory variable, 说明变量
$ T! P5 l6 \" G0 w s# T, _Exploratory data analysis, 探索性数据分析
1 S* R9 d9 s8 _! c \: mExplore Summarize, 探索-摘要
i& _. l' l% n; U/ U8 O! QExponential curve, 指数曲线' S4 c- [* ^" ~+ h) H, H1 {
Exponential growth, 指数式增长
5 r# [# i1 J) u$ u+ {% z g6 LEXSMOOTH, 指数平滑方法 ' T: Y/ M% k- T
Extended fit, 扩充拟合
; A: b8 |; U" @6 NExtra parameter, 附加参数
1 O4 z. w" @ }Extrapolation, 外推法1 A1 h- c+ `: H3 y$ V
Extreme observation, 末端观测值
+ S5 X4 _& c$ PExtremes, 极端值/极值8 i; _( a# a4 X
F distribution, F分布; X+ L% o/ s7 Q% N [' F
F test, F检验
/ T: i. m- J; O1 L9 X( UFactor, 因素/因子% x+ u6 c* D& ~0 ~% y' y$ \$ I
Factor analysis, 因子分析1 v5 x2 a* M! \ X$ _
Factor Analysis, 因子分析
9 b& f* G4 A, j- o4 J" {Factor score, 因子得分
; A2 K7 |) b5 D/ J0 w' j1 ^Factorial, 阶乘$ t1 \- o+ H' {+ w) f
Factorial design, 析因试验设计4 G# j; ], R3 \5 x
False negative, 假阴性
, U; T. W4 F8 B* j7 z! Z! _' wFalse negative error, 假阴性错误
$ f) h* A/ N1 J# wFamily of distributions, 分布族
# j! y0 O: f5 n% [. c# ZFamily of estimators, 估计量族& m" n* z$ p9 b$ E* m6 U( \5 Q% R$ A
Fanning, 扇面5 ?2 s2 S0 N& u6 N
Fatality rate, 病死率- C) }8 u& \; C" n
Field investigation, 现场调查
0 b' J, o8 I, m' zField survey, 现场调查5 y8 D ~; y( z3 j$ h* _5 W
Finite population, 有限总体. c' D) O6 P. R. T- _! W
Finite-sample, 有限样本
3 S) X% P) i1 _: j: ?First derivative, 一阶导数
; t+ ? T" d+ I3 I* Y, HFirst principal component, 第一主成分0 f7 ~ n7 \" Z7 o1 G
First quartile, 第一四分位数/ C$ z0 y9 X/ r, i; f: E! d5 y
Fisher information, 费雪信息量+ ^! E; Z' b( l2 P4 l& {$ Z
Fitted value, 拟合值
9 k. d& A# x) i) v+ U' o9 bFitting a curve, 曲线拟合; N1 N, ]6 ]% W9 b
Fixed base, 定基
, q6 |, |( L5 A4 q9 d. dFluctuation, 随机起伏
1 ^! u! g ]% {6 R+ dForecast, 预测! k- s' \# h7 Z* x5 t5 i$ p4 Y- y
Four fold table, 四格表" \! Q$ [! ]# m8 ?% S! W
Fourth, 四分点" T! H- n' @" M# J& r1 N1 v
Fraction blow, 左侧比率
$ X/ |4 K# N1 I6 RFractional error, 相对误差# d q- G- V# j- X7 Y0 j- y% `* K* ^
Frequency, 频率
3 [# I) c0 X+ p1 _+ k0 E4 KFrequency polygon, 频数多边图+ h' B! P. p _
Frontier point, 界限点7 l/ N8 h+ r6 s9 d+ c) g
Function relationship, 泛函关系3 u8 v* @# T! Y* }3 W2 b& S5 X
Gamma distribution, 伽玛分布- Q1 r8 X$ k9 u8 R3 {: G
Gauss increment, 高斯增量6 G' g& T0 y7 y, ^: g( g- Y
Gaussian distribution, 高斯分布/正态分布# P! H0 L8 Z" L% {
Gauss-Newton increment, 高斯-牛顿增量
& i, ^% W% e. R: J. l/ K2 _7 S$ VGeneral census, 全面普查* @& g7 p- g& N: O! E
GENLOG (Generalized liner models), 广义线性模型 $ c4 c0 ^6 U. O. m
Geometric mean, 几何平均数
% n5 T$ I1 b$ B- lGini's mean difference, 基尼均差4 `5 o) b; U2 f1 E1 f
GLM (General liner models), 一般线性模型 9 ~# S' N5 ?8 l2 [* @# a( A- b E6 H) p
Goodness of fit, 拟和优度/配合度
* R5 Q0 K/ Q" v0 |Gradient of determinant, 行列式的梯度
0 J/ V% m. y s% O7 f7 ]6 `1 K5 XGraeco-Latin square, 希腊拉丁方
8 f$ l9 M- v v2 v8 yGrand mean, 总均值
1 K" c# U4 _9 [" r4 tGross errors, 重大错误( R1 Y1 x3 k; R" y' `
Gross-error sensitivity, 大错敏感度
/ {( I3 `# r* Q2 aGroup averages, 分组平均
, e/ W* Y1 n% I) @# V0 B fGrouped data, 分组资料
( F6 ^" ^4 l( M9 A! hGuessed mean, 假定平均数
" z- }. O# a+ G# KHalf-life, 半衰期5 [# c& j1 k& b$ l2 c8 [" r$ P% k; l' g
Hampel M-estimators, 汉佩尔M估计量. P% p6 ~2 U. d9 S" h& ?" _
Happenstance, 偶然事件
( w) z/ v1 W1 l+ s) KHarmonic mean, 调和均数
% r* ~+ T6 G5 x0 g9 dHazard function, 风险均数
' K6 G; Y, n% B3 d$ KHazard rate, 风险率; ]4 {) m; C# [! I2 e) F
Heading, 标目 3 n d& q5 S- i
Heavy-tailed distribution, 重尾分布+ _0 A) A6 _7 _2 S7 h; T& ^: m9 c
Hessian array, 海森立体阵5 F) l. m9 |; ]/ k; e
Heterogeneity, 不同质. y% y8 D, T2 o2 M1 L
Heterogeneity of variance, 方差不齐 7 b4 K# \- ^5 Q9 a( H. ]
Hierarchical classification, 组内分组6 R: z* c* Y; V* s; q( V
Hierarchical clustering method, 系统聚类法, \" {% C% _7 A/ X, r
High-leverage point, 高杠杆率点
3 z- C& ?8 P. nHILOGLINEAR, 多维列联表的层次对数线性模型
2 V! D$ T" Y0 S' FHinge, 折叶点8 o& C. u5 [ F5 Q9 L; C [2 h
Histogram, 直方图
) W& v2 H; u7 [: d2 y( wHistorical cohort study, 历史性队列研究
: [, L0 g" r9 QHoles, 空洞
* m: h& l' s( ?HOMALS, 多重响应分析
$ w, {+ j2 L+ n# w) z& U6 B4 ZHomogeneity of variance, 方差齐性
) B$ n U) |' p% D! a2 m$ A0 sHomogeneity test, 齐性检验
* a3 U6 @0 P g+ f0 |Huber M-estimators, 休伯M估计量, O- V8 z; z; u( u
Hyperbola, 双曲线$ D/ ~1 p- Q F7 {# ^8 u8 P
Hypothesis testing, 假设检验
% \% ~/ `9 o8 z5 f# X3 l/ A( ^Hypothetical universe, 假设总体1 A8 q7 [5 F0 U5 h7 F
Impossible event, 不可能事件
' S9 V' Q( v: \3 J" g y ^Independence, 独立性' c% D7 ?9 p$ b( p* F2 S+ v
Independent variable, 自变量0 [8 o+ V6 {/ w
Index, 指标/指数- M: B: S( q5 d) q
Indirect standardization, 间接标准化法0 e5 y8 V! q9 p
Individual, 个体2 B* s; o) s% u. O/ F+ v9 L2 {8 f
Inference band, 推断带9 {2 a; V3 Z: W7 g, E! W; M
Infinite population, 无限总体
% M9 T& C1 R( M+ J0 t' l8 zInfinitely great, 无穷大
& o( F2 p8 ] VInfinitely small, 无穷小3 C, t! E8 W$ e* B5 m
Influence curve, 影响曲线6 ^7 U7 S- j; [$ G: ]$ e2 X Y8 i
Information capacity, 信息容量# \0 D& K, W; }! B
Initial condition, 初始条件
# K1 Z9 m- o7 q2 F$ w G4 dInitial estimate, 初始估计值$ V8 h3 }2 M6 q- U
Initial level, 最初水平5 ]: B: e y4 z7 b0 g
Interaction, 交互作用& G" C @: Q2 G6 L
Interaction terms, 交互作用项
) J4 i6 g+ t% A9 q$ DIntercept, 截距
5 |: D" {7 O* E- M; N# ^Interpolation, 内插法" H: r+ u* n: G; Q1 w
Interquartile range, 四分位距: r. f$ K/ S5 X+ K! V, T
Interval estimation, 区间估计# w a2 U0 j: m, ~% }* F
Intervals of equal probability, 等概率区间
; e0 \4 s# m( F+ \# nIntrinsic curvature, 固有曲率
) i0 B7 ~" X; N! K# }+ ?Invariance, 不变性
" M2 I! g6 N) j3 H/ O& K0 zInverse matrix, 逆矩阵9 s9 H% Y# N/ H! t
Inverse probability, 逆概率
4 I' a+ s, I; ]Inverse sine transformation, 反正弦变换
# N1 b7 g0 ~1 CIteration, 迭代
' ^& x( ^1 }+ h* o) GJacobian determinant, 雅可比行列式& E- I& s! p" [5 `8 w6 N; t& e: o
Joint distribution function, 分布函数2 _4 `% S6 S7 ?. F! _: _5 A
Joint probability, 联合概率
7 k4 H$ j7 H3 o3 O' ~Joint probability distribution, 联合概率分布
* v5 V& q: `2 ^) Y* C) yK means method, 逐步聚类法+ ?& k2 z! k" \4 h7 e0 B
Kaplan-Meier, 评估事件的时间长度
8 `4 Q# h# M4 ?- B: |& h" ]Kaplan-Merier chart, Kaplan-Merier图
, b" `; |7 J7 n% P4 _% e6 nKendall's rank correlation, Kendall等级相关
& x" z) Q9 Y# x3 G# E2 IKinetic, 动力学
0 u0 |$ b2 {! J5 Y6 |6 OKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验6 F* [" }& K6 i: ]8 H3 s. l
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验4 U+ O/ v6 ]) F {
Kurtosis, 峰度
5 r i% _$ j& G/ {6 ]0 [; [Lack of fit, 失拟
; J Q x2 u; [6 X, jLadder of powers, 幂阶梯
1 V( `0 w, c( h; [: b, kLag, 滞后
" K( ~7 S) j6 [8 J. W" g: ]8 bLarge sample, 大样本
5 ^* J7 B! L+ A& t: c* d" P1 cLarge sample test, 大样本检验
/ P; Y, W% s* s' ~Latin square, 拉丁方
8 p6 ^& ]/ [& r# C8 vLatin square design, 拉丁方设计
8 M$ F, ^- J5 i* R! A8 T4 lLeakage, 泄漏+ L4 I% s/ ?. r, b2 k. N* @
Least favorable configuration, 最不利构形2 n3 @. W5 Z: F
Least favorable distribution, 最不利分布5 k2 k, b3 ~* y% [% L3 _
Least significant difference, 最小显著差法: X2 e, _+ E" {2 a
Least square method, 最小二乘法* y$ N$ }6 @. i' F1 o* I I
Least-absolute-residuals estimates, 最小绝对残差估计/ i' O b1 b, L q! t
Least-absolute-residuals fit, 最小绝对残差拟合( }* {# I4 g1 z# v* I R% H
Least-absolute-residuals line, 最小绝对残差线! c2 F4 U( t( c& N+ z0 x' l$ g' L
Legend, 图例
$ o4 B* I1 a. e/ h: f' v0 j& X& v% S2 vL-estimator, L估计量; x; B% h; X# x4 P9 R% \; a
L-estimator of location, 位置L估计量: O9 n( C5 Q& E7 X" p3 K4 s4 }3 O
L-estimator of scale, 尺度L估计量
" l" Z1 T4 o0 @* w: ]9 a+ c+ gLevel, 水平2 n; s7 B# b- o) O3 \
Life expectance, 预期期望寿命4 s$ f* o$ w, h
Life table, 寿命表6 Q6 g2 _5 [- x6 K _5 u
Life table method, 生命表法& v5 ]. {7 g& A' U% \9 i/ A: P
Light-tailed distribution, 轻尾分布
# M& V# B; q7 E" E1 ~4 u/ xLikelihood function, 似然函数
1 g' Z& H9 R) x% K. LLikelihood ratio, 似然比3 B: j7 u. ?7 F' [
line graph, 线图5 M C/ p! _. H9 z
Linear correlation, 直线相关5 I) k$ e) s. U# A! X2 R
Linear equation, 线性方程% R# [5 B3 ?9 ]) M- Z) `4 [
Linear programming, 线性规划( J, @1 v3 e9 \7 g, @' B7 G
Linear regression, 直线回归
% Y7 w: m8 ^3 j4 Y; p2 G1 DLinear Regression, 线性回归
# n) v# c7 z! ^9 eLinear trend, 线性趋势
9 e: F- I! J3 d# `Loading, 载荷 ; @, |2 m; W& m0 [
Location and scale equivariance, 位置尺度同变性
5 p$ s9 A9 X2 X- ?Location equivariance, 位置同变性9 F' y, t& W) Y9 x/ {9 q7 j% `7 k
Location invariance, 位置不变性
9 G5 k4 j6 P1 t2 p( L; N" bLocation scale family, 位置尺度族
2 J$ b [* P: X2 g$ jLog rank test, 时序检验
7 F* t4 @* k/ C* ]9 z gLogarithmic curve, 对数曲线
' ]8 R2 r- Z; c, [Logarithmic normal distribution, 对数正态分布
7 y- T, L0 q' hLogarithmic scale, 对数尺度
4 {' _, `4 g; ]( rLogarithmic transformation, 对数变换
/ L5 h! s. h# H$ K; `- @Logic check, 逻辑检查+ g4 z; t, @/ @5 @
Logistic distribution, 逻辑斯特分布5 O- ?# A2 b$ K- i' h
Logit transformation, Logit转换
; w6 `4 Q" i+ o. fLOGLINEAR, 多维列联表通用模型
) C# Z' V9 @4 F3 D0 l/ L- PLognormal distribution, 对数正态分布
0 G/ [( o! f' k4 B! ULost function, 损失函数
1 a( ]+ I3 @2 f2 q; k8 J* f$ wLow correlation, 低度相关: b9 V W" B2 g! k- C
Lower limit, 下限8 ?+ i& h; W2 v& Y7 J; `* T
Lowest-attained variance, 最小可达方差2 r, F* N; w7 B1 D5 U/ A1 @
LSD, 最小显著差法的简称
# L8 N! Z( Q B+ Q0 BLurking variable, 潜在变量0 P; H9 t P0 y4 W& ^8 Q; F
Main effect, 主效应6 M3 i, f* q4 O0 X3 ? ~% V! a7 u6 }
Major heading, 主辞标目
0 o0 D* D- |: L# \% XMarginal density function, 边缘密度函数
+ Y; a" q: n* J: H* \6 |2 jMarginal probability, 边缘概率4 n3 s4 B+ ?' Y2 `; S2 r1 e/ i; v
Marginal probability distribution, 边缘概率分布' I+ O# i! E ^1 O: E9 F
Matched data, 配对资料3 M7 O3 K1 R1 @6 U& l5 p G
Matched distribution, 匹配过分布2 t, s0 `3 t+ Q j0 T' M/ L2 Z2 Y
Matching of distribution, 分布的匹配8 M) g6 u L, Y, a! ~- _, r
Matching of transformation, 变换的匹配
) e3 f/ C' t+ H) g! D( f' TMathematical expectation, 数学期望
$ J$ ?; S7 B0 E$ RMathematical model, 数学模型
) D P- j5 p) A5 SMaximum L-estimator, 极大极小L 估计量3 ?! C7 o- _. w6 r
Maximum likelihood method, 最大似然法+ |( z/ d. ?( s0 m
Mean, 均数6 c7 `! }5 ]% t
Mean squares between groups, 组间均方3 m% |. M! c4 ]$ Z
Mean squares within group, 组内均方& k7 h( w* ~& V6 c+ Y$ k/ S
Means (Compare means), 均值-均值比较
2 H% f o5 k# a& l+ [ ^6 X4 SMedian, 中位数
* e p) d1 m2 }8 h9 ]Median effective dose, 半数效量' g0 u7 ]6 h# @
Median lethal dose, 半数致死量( }5 d% E- `, Q8 {
Median polish, 中位数平滑
$ v4 i8 L0 D) L( a5 xMedian test, 中位数检验
1 i! F/ R, j/ vMinimal sufficient statistic, 最小充分统计量" M( [; j. M a! Q
Minimum distance estimation, 最小距离估计" S* i6 [; Z" u- a5 y
Minimum effective dose, 最小有效量+ O" z$ i, u _) L' e+ |
Minimum lethal dose, 最小致死量
8 {2 B- @: W# z8 h; WMinimum variance estimator, 最小方差估计量
! ?7 x' [/ ~ a( vMINITAB, 统计软件包+ m. f4 y7 i, S
Minor heading, 宾词标目8 ?# h- G. S4 C3 R) b
Missing data, 缺失值+ ^ R+ c7 J( p* B
Model specification, 模型的确定
" e" f6 W) O$ {7 K3 M6 qModeling Statistics , 模型统计
4 j7 k( }" u6 S+ S1 FModels for outliers, 离群值模型
8 `9 Q! r7 P" x+ ~% k, m IModifying the model, 模型的修正7 b- ]/ W/ l4 P5 D! W
Modulus of continuity, 连续性模4 R, B0 N* W4 F. [
Morbidity, 发病率 3 ~- x# [# q; \# ]) O3 O4 L
Most favorable configuration, 最有利构形4 E( w! }( H; m( U) u& n1 s
Multidimensional Scaling (ASCAL), 多维尺度/多维标度0 h1 c9 q+ J& Z: g, M# d" W- @
Multinomial Logistic Regression , 多项逻辑斯蒂回归
4 c% [, W' [" J; }9 K* K& GMultiple comparison, 多重比较( ?6 r9 b1 e( X2 P% W% `5 A- K
Multiple correlation , 复相关
2 ~5 C/ n0 d3 N6 b2 O9 g) d3 vMultiple covariance, 多元协方差
1 O% R6 K: w8 P! g6 A wMultiple linear regression, 多元线性回归7 G( ?. L3 r4 @) K6 ]8 m j' x' r1 q2 _* c
Multiple response , 多重选项
9 ?$ |) D3 h% Z4 n X8 [Multiple solutions, 多解
& X, B* r E( M* [' i, iMultiplication theorem, 乘法定理
' Q2 F- I6 D2 `/ FMultiresponse, 多元响应
2 c4 T# M3 |& W9 C( p+ ~Multi-stage sampling, 多阶段抽样2 V% ^, `' x" o/ D$ Y; O6 s4 u
Multivariate T distribution, 多元T分布
& w! w/ y# p$ d$ W @Mutual exclusive, 互不相容: [" }7 W2 ~0 A) b$ K, l2 p1 g. R
Mutual independence, 互相独立; D& M) @9 Z3 G3 }" t
Natural boundary, 自然边界* ~. u8 L( s2 k; \
Natural dead, 自然死亡
/ u9 \/ U* |2 g- j1 J z8 s! jNatural zero, 自然零
4 {2 F; z c, G8 r" `; KNegative correlation, 负相关 n9 z u" L" W' g) G/ w
Negative linear correlation, 负线性相关4 |* T5 A8 ]; ?+ @
Negatively skewed, 负偏
/ x. V4 i; x7 |! {4 @+ lNewman-Keuls method, q检验% ?9 q& B# e6 i. [
NK method, q检验
4 l$ X) J/ @2 dNo statistical significance, 无统计意义
2 w; S1 `; `/ r3 c8 fNominal variable, 名义变量- e4 [8 H$ `# |4 x9 p3 M
Nonconstancy of variability, 变异的非定常性2 u9 \ D3 s, l
Nonlinear regression, 非线性相关" U2 ^. V) m: [7 Q+ p4 m0 `$ R
Nonparametric statistics, 非参数统计3 | L1 V0 D8 _3 f- h& k
Nonparametric test, 非参数检验6 G1 a# a9 v4 @6 k+ g
Nonparametric tests, 非参数检验
2 G: M2 z5 R$ E0 d; aNormal deviate, 正态离差
) e( G4 B, n8 g; WNormal distribution, 正态分布, Y3 b) H% r7 r# a% ~
Normal equation, 正规方程组4 I3 H2 |2 ~' e5 _$ K) `3 i
Normal ranges, 正常范围4 y6 }* ]. a* F% m0 G
Normal value, 正常值
4 d0 [: I$ f$ @5 [) E/ Z+ _Nuisance parameter, 多余参数/讨厌参数9 q" C: s! F2 P9 X2 |( o
Null hypothesis, 无效假设
" L6 z8 {. W# d/ VNumerical variable, 数值变量
; Z# a5 d# w8 GObjective function, 目标函数% X/ L0 l+ I+ t
Observation unit, 观察单位
; ~' r I! m( n. w$ f0 i H8 AObserved value, 观察值
. [4 _0 ?) L; ^1 OOne sided test, 单侧检验, k1 H9 d6 c3 S( X
One-way analysis of variance, 单因素方差分析/ y2 }' a, O, K; J' P I1 o7 o
Oneway ANOVA , 单因素方差分析' X' R" D, a3 M2 U+ w; v0 _: ?" ]
Open sequential trial, 开放型序贯设计
' i7 k6 Z3 A y5 j tOptrim, 优切尾9 p) _/ k6 L& m
Optrim efficiency, 优切尾效率0 n( G, l/ L0 _% a5 d$ U7 ?! U
Order statistics, 顺序统计量
7 d. j. y& F+ rOrdered categories, 有序分类0 o; N6 z Q8 R5 l8 M0 }
Ordinal logistic regression , 序数逻辑斯蒂回归" _% K3 Q; P5 I! p& v2 H" D9 F
Ordinal variable, 有序变量
\/ _. P/ b6 @Orthogonal basis, 正交基1 d# Y& }4 @% o9 {* S- t3 h
Orthogonal design, 正交试验设计
) y, h# G* n4 ]& t: R% yOrthogonality conditions, 正交条件
3 t4 ^! R+ U4 G; iORTHOPLAN, 正交设计 * X% q+ G5 @% R$ R) Y
Outlier cutoffs, 离群值截断点7 o0 L) ^ I) @) p- ?
Outliers, 极端值
: c7 g1 G1 I4 fOVERALS , 多组变量的非线性正规相关
, M, _# ~8 {+ B0 Y MOvershoot, 迭代过度
6 E2 x \0 D7 |Paired design, 配对设计
, q8 D) z5 g. r9 S: sPaired sample, 配对样本
% E0 r0 ^% ?$ V" ] IPairwise slopes, 成对斜率: b0 a' V8 {; o
Parabola, 抛物线
! c" G1 x! d8 B# ~4 P' KParallel tests, 平行试验) V8 {) U, T+ C9 V* J
Parameter, 参数
: t* ]' Q; |( v3 ?& ] f' J! VParametric statistics, 参数统计. Q: v0 I* `0 l! Y7 v& c
Parametric test, 参数检验# {/ P$ g* j+ j! O" y: A
Partial correlation, 偏相关
* ~$ ~/ O* r7 v. O7 B* {Partial regression, 偏回归* L# v9 C, L3 o$ S
Partial sorting, 偏排序
1 m' j6 J6 p1 v0 o% [' fPartials residuals, 偏残差8 [) z0 k7 k1 U( a) @
Pattern, 模式- \! B& D' Z4 W& b2 O3 @
Pearson curves, 皮尔逊曲线" P) L* r3 y: X& u! g' L( \
Peeling, 退层
! u8 d$ U: g# c3 ~. J/ U: y' M0 EPercent bar graph, 百分条形图5 Y6 a4 _( L& _: Z4 x9 j$ f- A
Percentage, 百分比4 O2 f! Q# {9 S" V- ]4 t
Percentile, 百分位数& B* \- O8 J! r' T
Percentile curves, 百分位曲线
; d- i) d& a5 s3 K' ZPeriodicity, 周期性0 o+ a) Z* L5 g) f$ ~
Permutation, 排列# L7 y, d- ]) U; i) I
P-estimator, P估计量
' _0 ]& k4 |( Y9 F* _" C, i3 iPie graph, 饼图" |0 f, a5 t$ e
Pitman estimator, 皮特曼估计量0 b+ \4 q+ u+ F$ a
Pivot, 枢轴量( H7 K D$ g! e4 G
Planar, 平坦
( b S9 `) L8 i! x1 x4 w$ kPlanar assumption, 平面的假设( a8 J( j1 V% |, E
PLANCARDS, 生成试验的计划卡
i9 @# |& n6 q/ SPoint estimation, 点估计
% d, W O" v9 FPoisson distribution, 泊松分布
8 }; }; H7 ^- f/ N& L. A" e* m+ _Polishing, 平滑
$ ^0 S: _* Q% L. W2 f( BPolled standard deviation, 合并标准差
2 Q' {( }; a2 b5 q' J& tPolled variance, 合并方差5 A, E* v5 U( l4 B
Polygon, 多边图4 r" B7 \/ l& c j. v; U
Polynomial, 多项式
1 ~7 {: x; L# [( J# K3 V# kPolynomial curve, 多项式曲线
! E- x$ }- z8 e8 PPopulation, 总体2 s+ l5 q/ X5 k/ f9 O
Population attributable risk, 人群归因危险度
7 x% ?8 F2 M4 g/ [Positive correlation, 正相关5 _( I6 c; \) k+ u' Q
Positively skewed, 正偏
7 z# @% I5 t$ E, m5 iPosterior distribution, 后验分布% ^9 o7 c/ B7 r/ g/ n
Power of a test, 检验效能- a# F4 h! v1 S) b
Precision, 精密度4 t1 P9 P8 [: Z* p0 r
Predicted value, 预测值! G8 f4 k# T" \( r8 ` i2 `$ E+ q
Preliminary analysis, 预备性分析2 u: z9 U* V7 }8 S+ y) }/ P8 Z. h1 F
Principal component analysis, 主成分分析& t [3 [, X% ?8 @3 ] o P7 M
Prior distribution, 先验分布8 u7 ?7 B% M5 Z
Prior probability, 先验概率
, W0 B7 P( k- x5 U) v& sProbabilistic model, 概率模型6 U7 C" r, S1 i
probability, 概率, U, H' V4 \( b& W6 k% ^
Probability density, 概率密度
5 }0 L* u* G. U# PProduct moment, 乘积矩/协方差5 ?7 b2 l; ]4 M/ K7 l9 Q
Profile trace, 截面迹图7 R7 J- R, B4 N. v, K6 C
Proportion, 比/构成比' j0 @- _8 ] {2 M+ F
Proportion allocation in stratified random sampling, 按比例分层随机抽样
+ u: p1 a4 }) m9 _$ a6 ]. JProportionate, 成比例
% a' X5 y5 c: u2 F' M9 G; G7 m( }Proportionate sub-class numbers, 成比例次级组含量6 Z/ j% h4 _& W w" V
Prospective study, 前瞻性调查+ f7 J5 C$ \9 B8 f. a
Proximities, 亲近性 6 @& K3 D1 ]0 `$ k5 T& b
Pseudo F test, 近似F检验
# c. G+ ^6 L b( e, f! E. kPseudo model, 近似模型* M9 g! }! L- D) K' Y
Pseudosigma, 伪标准差* _! I l5 c$ n5 k
Purposive sampling, 有目的抽样+ T" C }1 k; y' p. w; O, O
QR decomposition, QR分解
* ]) E% E G2 `/ T4 C9 WQuadratic approximation, 二次近似, g" ^" a; H7 {
Qualitative classification, 属性分类, j' o1 O: t% s; M
Qualitative method, 定性方法7 y2 b$ a6 o: M1 C) u$ n" K
Quantile-quantile plot, 分位数-分位数图/Q-Q图
2 Z0 u! x, \4 R+ F( i2 L0 gQuantitative analysis, 定量分析
, z# T7 I2 [' Y* E% G- H8 }6 JQuartile, 四分位数
+ D# D, q6 S( Z: yQuick Cluster, 快速聚类
( F4 k; K- Y; u$ ERadix sort, 基数排序0 J: c6 w8 [1 ^3 {8 Y$ |- d- L
Random allocation, 随机化分组5 v6 R. _$ i3 d2 ^! {: L
Random blocks design, 随机区组设计6 V5 g9 T/ }5 H. s: r6 z6 z& Y
Random event, 随机事件3 C2 a6 h! b4 d9 d
Randomization, 随机化6 h6 ]$ p" Q0 q
Range, 极差/全距' j9 d( X; P9 k$ h, |6 z; r9 v3 v
Rank correlation, 等级相关" |$ h5 p4 k J, k3 j* }. t2 o7 N
Rank sum test, 秩和检验
& S$ n1 t1 I$ i9 uRank test, 秩检验
: d4 S# u1 U3 hRanked data, 等级资料( F7 I+ [! }& J
Rate, 比率
5 T/ ?; D/ `# ?" p& @+ v" ^Ratio, 比例% K: R2 A* {1 O7 P0 X
Raw data, 原始资料0 T5 o4 k$ s& ~+ X
Raw residual, 原始残差- |3 V2 o" S r: r% G
Rayleigh's test, 雷氏检验9 M4 P7 k' C, Z, d
Rayleigh's Z, 雷氏Z值
3 F+ V5 X$ |0 Z1 x+ }0 d0 }Reciprocal, 倒数
! N8 y+ p s7 f" |Reciprocal transformation, 倒数变换
" H% M' R# H8 M, U) MRecording, 记录! t) d/ ^! O! q7 g
Redescending estimators, 回降估计量) z9 J/ Y% k; c0 _6 _1 d6 ]
Reducing dimensions, 降维. J. z, d/ ] e2 K( W
Re-expression, 重新表达
6 y" U7 d- L0 r1 o. ~Reference set, 标准组
+ B8 h* \( Q3 y1 RRegion of acceptance, 接受域+ k5 @ E* y: M8 e6 a0 ~
Regression coefficient, 回归系数% J9 _9 r. ]$ w$ o% e
Regression sum of square, 回归平方和! j& W# `2 I: @2 Z. m* B+ d# i( S- a
Rejection point, 拒绝点
7 G# R9 H( k/ R4 J! \7 P. x: @Relative dispersion, 相对离散度
* F7 a; C# X& TRelative number, 相对数" \" h7 I/ I0 I: M
Reliability, 可靠性) s( k H5 r: l! [! O! X: }/ |
Reparametrization, 重新设置参数1 ~0 M0 l/ w4 P, O
Replication, 重复' x& v, z8 Q; k- M/ T6 H
Report Summaries, 报告摘要2 \* a' T# J; x/ i5 F) i
Residual sum of square, 剩余平方和
4 h' j* v. a* x4 j( {) q3 |- fResistance, 耐抗性
5 m9 o6 v7 j' ^$ R9 h5 VResistant line, 耐抗线 Q0 w9 o9 v+ p% c
Resistant technique, 耐抗技术
2 B0 K% b( R, o5 n/ r V: D$ p7 ?R-estimator of location, 位置R估计量
: C* F- h [. p) G" C9 D. x' cR-estimator of scale, 尺度R估计量
6 g! g$ `% w4 ~: ^Retrospective study, 回顾性调查
( h0 g' Y) S( x. U2 ]/ L1 B, m# mRidge trace, 岭迹
" O' Z) g8 \% ` [$ \Ridit analysis, Ridit分析
8 F5 H$ s, J0 x9 \Rotation, 旋转
# f3 ]2 `! j! n& c( GRounding, 舍入
* [, H$ W: m& RRow, 行& K" l) A6 |) [7 T, u6 J
Row effects, 行效应) J7 |6 c0 l) Z3 g5 A) U* F
Row factor, 行因素; e3 Q6 B( M, G8 k0 c( ~5 ^- \5 w
RXC table, RXC表* M" U" B$ Y/ g& D. n% F8 Q
Sample, 样本
3 p0 I0 T6 x. g6 I/ JSample regression coefficient, 样本回归系数- y6 k. a" W% n# U, Q- k
Sample size, 样本量
8 x9 E& l( G* X' i8 @1 y2 l3 h$ lSample standard deviation, 样本标准差7 v: p* \$ D8 X5 m- p" K
Sampling error, 抽样误差9 u; x5 [1 [% W
SAS(Statistical analysis system ), SAS统计软件包
: r$ Z1 ]& `: S6 d) P6 B7 i: cScale, 尺度/量表
! V6 x( W. |4 r! b" @Scatter diagram, 散点图
4 V0 p! K0 p7 j" PSchematic plot, 示意图/简图
+ O' L4 L2 Y, f" v* \Score test, 计分检验# }! m& e1 `7 p! R8 r
Screening, 筛检
3 `7 j- M1 `" j) \7 ]6 \+ [9 R/ @. z; nSEASON, 季节分析
+ B: _6 d* r# uSecond derivative, 二阶导数/ b( P# i$ \) `' B
Second principal component, 第二主成分8 C2 d* Q. W, B3 A, Z
SEM (Structural equation modeling), 结构化方程模型
4 n7 S$ j9 c, H7 g L& l/ ~! n- hSemi-logarithmic graph, 半对数图2 k# U# b% J% @9 n( Q6 V- _' n- l5 i
Semi-logarithmic paper, 半对数格纸
6 S( X) {7 M. mSensitivity curve, 敏感度曲线
$ ]* d8 N9 V9 g8 a7 [ o0 s% tSequential analysis, 贯序分析# G8 c& q6 b3 h' w! K& U' b. O
Sequential data set, 顺序数据集0 j! P U0 i3 V& |! o5 u N& H
Sequential design, 贯序设计0 V! q3 W' c9 W
Sequential method, 贯序法
$ {9 r! J: p5 b& ZSequential test, 贯序检验法; u3 L: E$ Y! w! X
Serial tests, 系列试验9 F- \2 g( k) X/ @0 W _2 o
Short-cut method, 简捷法 % _+ @6 e' ?* C; N2 i
Sigmoid curve, S形曲线
1 p8 z l! H+ P1 n$ ^0 p# x% oSign function, 正负号函数8 b2 K) {% H, w9 a% ]
Sign test, 符号检验
. e2 C1 q: J \2 @& m1 r- R, CSigned rank, 符号秩8 l: z% q1 e" S
Significance test, 显著性检验4 w; ?/ k/ k4 q) n# T3 R# X( ^
Significant figure, 有效数字$ w( R! a4 @4 ]! S; }1 O
Simple cluster sampling, 简单整群抽样
2 _5 p6 N7 p3 `) j5 U1 j) F6 XSimple correlation, 简单相关6 Y" g/ Y* `1 v3 q
Simple random sampling, 简单随机抽样
8 W: P2 s# g; D$ y+ R' oSimple regression, 简单回归
# C6 F( ~4 u3 v8 Lsimple table, 简单表
/ ]5 p% [& G; zSine estimator, 正弦估计量5 t. m/ p- y$ b5 G
Single-valued estimate, 单值估计
6 f5 y6 f$ P- O& z4 S4 J# DSingular matrix, 奇异矩阵
* R4 l- i5 [4 F8 ~4 K# a# ZSkewed distribution, 偏斜分布
" h% _- W. |( J: b& {Skewness, 偏度) g" X/ x ?, W$ A F! U
Slash distribution, 斜线分布, R- l# w* Y# @6 }5 C6 K: W; w/ R
Slope, 斜率4 V8 l8 m$ {: x7 Q7 {, _1 j
Smirnov test, 斯米尔诺夫检验
7 Z' f+ {7 M% D3 i8 ~ Q6 l+ tSource of variation, 变异来源2 q" g0 M3 [7 w# E+ c
Spearman rank correlation, 斯皮尔曼等级相关
5 N( u; c. ?$ O$ LSpecific factor, 特殊因子
5 J' H$ ^( O* n, K$ ?Specific factor variance, 特殊因子方差/ ` ?, {# x" {, C
Spectra , 频谱4 {3 B5 p# Y* L; C; T$ c* `
Spherical distribution, 球型正态分布 y3 e& }) k+ d7 s, ?1 d0 U2 }
Spread, 展布
0 h6 ~! u1 u7 d/ H2 g0 ~) QSPSS(Statistical package for the social science), SPSS统计软件包) S5 o6 Y' J8 g/ g
Spurious correlation, 假性相关$ E0 T$ t$ d$ Q5 P$ D
Square root transformation, 平方根变换
5 a: k5 ]( [4 \Stabilizing variance, 稳定方差- N7 m: E$ q+ Q! {0 ~! K
Standard deviation, 标准差% {6 q1 B. j. _& ` c
Standard error, 标准误
A4 w9 q5 ~) C7 d- k UStandard error of difference, 差别的标准误
1 t5 Q, d/ u3 l$ AStandard error of estimate, 标准估计误差3 _% w4 m4 t" X
Standard error of rate, 率的标准误
, O8 _7 y, }/ Q2 {4 HStandard normal distribution, 标准正态分布
& X9 q# B# h7 N2 K, dStandardization, 标准化$ K, j, m! |% |( ?+ d a7 ~
Starting value, 起始值# l" R+ p/ _" C/ J% c
Statistic, 统计量
; m0 q" o( D4 P# ]: ^; B+ ZStatistical control, 统计控制
6 b) W, P7 W5 N8 U0 ^0 f9 HStatistical graph, 统计图
5 z$ _3 i0 O, x& UStatistical inference, 统计推断
0 U: R0 C+ \- L* g% o4 nStatistical table, 统计表
: m% p( v) c# @7 VSteepest descent, 最速下降法# L) V$ |( `7 s$ j6 v8 G7 \
Stem and leaf display, 茎叶图- P+ O5 u, }) |% A; G8 Z: {
Step factor, 步长因子
! N5 O, B/ n# ^+ V9 }! O6 h/ mStepwise regression, 逐步回归2 R* @8 `/ Y) F3 z1 i' U
Storage, 存
& e( O6 S- m$ P+ pStrata, 层（复数）- T) u g! ~! k
Stratified sampling, 分层抽样
! u+ V) K2 k( N3 d! OStratified sampling, 分层抽样
6 G) q) r; q% Z5 lStrength, 强度
~% q+ G- n' v D7 QStringency, 严密性
* x& a' r" C0 D. b8 dStructural relationship, 结构关系
6 f5 Q% c5 A5 W0 {Studentized residual, 学生化残差/t化残差 Q$ u5 B/ A5 M# t5 v
Sub-class numbers, 次级组含量
" p, Q( u' `; H7 D( {1 HSubdividing, 分割
9 r8 `' z6 w- U% x" T1 ]Sufficient statistic, 充分统计量/ w% s4 ~6 h6 f }, {& K, a8 [, I# F5 t: a
Sum of products, 积和
( ^& \0 w$ @$ L5 M, H: s; hSum of squares, 离差平方和
. ^2 r% p+ z. ]4 Z, w0 CSum of squares about regression, 回归平方和$ U3 g% V4 S; p }* g |
Sum of squares between groups, 组间平方和9 u( a; r3 ?7 U) P& E
Sum of squares of partial regression, 偏回归平方和
4 F4 |9 a* | t" P/ v2 \Sure event, 必然事件
* {9 V' n" H, j" a" wSurvey, 调查8 U. ~, ?; g \$ V
Survival, 生存分析* D$ v, a& {. I9 n) ~+ g' U8 \9 ^
Survival rate, 生存率' T0 c+ d8 E# x1 @# k) g
Suspended root gram, 悬吊根图9 j' l4 J3 a2 D1 w6 G9 C Z1 V
Symmetry, 对称( l* x& Z- I" h: m- Z, B" K4 d
Systematic error, 系统误差
9 ?& T, ~" [0 n9 |/ y( G. D' jSystematic sampling, 系统抽样- I& l( q' F' o
Tags, 标签
7 d$ n5 n0 B2 _, W! zTail area, 尾部面积) ?3 o# Y: ~9 V6 b% u5 W
Tail length, 尾长( ?6 z: ?' u# t ^9 G- g
Tail weight, 尾重1 P; F" d: S! z: E
Tangent line, 切线& |: u) p) L$ ? d
Target distribution, 目标分布 A( `. T V( s3 E) e: W$ g/ g: i. f; N
Taylor series, 泰勒级数
' m4 X: b: Z M2 WTendency of dispersion, 离散趋势
4 \' X$ {) f) x! H1 J: B' ZTesting of hypotheses, 假设检验! _0 C7 r, z! t! q1 N
Theoretical frequency, 理论频数
4 m! @, d2 i; `2 c2 ^Time series, 时间序列& f. S) w; z) Y) z+ ^/ ]
Tolerance interval, 容忍区间+ s' y) R7 _) `, n/ k: K+ m6 Y
Tolerance lower limit, 容忍下限
; l3 |8 M" l; X0 F/ x' @Tolerance upper limit, 容忍上限6 ~! }- b. v5 B7 U8 K1 a& D7 Z
Torsion, 扰率
/ o: D0 G. J# T ^Total sum of square, 总平方和) }: R5 z/ m0 h" D+ ]$ k* }5 _
Total variation, 总变异
4 \8 b$ Z; ^5 g3 T9 V$ S5 ?Transformation, 转换
" K, }7 O# ^0 H5 H6 mTreatment, 处理
$ _1 H' Z* s2 u# ?Trend, 趋势
( D: T/ a6 h% H( Q5 q/ [8 oTrend of percentage, 百分比趋势+ F6 P: p& g9 M# Q' U7 G$ @0 w5 ?9 E
Trial, 试验. c$ C; E* m1 f- ^
Trial and error method, 试错法! x9 D1 S7 \6 |7 e' a" ?0 B' {
Tuning constant, 细调常数5 b, m/ w5 j4 D# |2 a% b
Two sided test, 双向检验5 N) {7 X+ W& X$ h: \- V
Two-stage least squares, 二阶最小平方
1 a5 u' {' { ]% i; n; X5 zTwo-stage sampling, 二阶段抽样
1 | e$ {: \1 dTwo-tailed test, 双侧检验
+ j" l) {/ Y! r( y' J# Q# u+ l$ OTwo-way analysis of variance, 双因素方差分析3 r, x! @8 m& p% y. c* j/ O
Two-way table, 双向表
. b- p5 [' c4 q. B; p# U$ N" PType I error, 一类错误/α错误( D$ E- y2 f! g0 L
Type II error, 二类错误/β错误
/ i5 K+ Z% V& xUMVU, 方差一致最小无偏估计简称, M$ b; n- G/ e$ K& [! ?6 k1 @
Unbiased estimate, 无偏估计- z3 C' \: L4 U8 Q. y5 f. Y" j
Unconstrained nonlinear regression , 无约束非线性回归
1 ]$ }: S* ~: Q3 m/ }( n4 JUnequal subclass number, 不等次级组含量) U2 g }& ?2 n( Z. U
Ungrouped data, 不分组资料1 F I4 X' C( l _. { ]. P
Uniform coordinate, 均匀坐标
6 o5 a+ W+ h- g5 @9 BUniform distribution, 均匀分布/ l, W) T. A) B1 i. z: ^
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
6 ]& ?) H% t( C; L& J: RUnit, 单元
8 v, n/ H+ T: ? f B$ AUnordered categories, 无序分类 O3 A; O8 \; W. ?! {+ ?
Upper limit, 上限& o! B, i! H& T
Upward rank, 升秩
7 \6 x( n3 F$ C2 b# V6 H, U. dVague concept, 模糊概念& D% ~2 y& K( X1 V, g3 H
Validity, 有效性* z! W8 X5 L1 C Q1 c
VARCOMP (Variance component estimation), 方差元素估计
$ Q ^0 ~) X! F8 d# [! ZVariability, 变异性) u5 s6 Y7 Z$ s% V8 G2 U
Variable, 变量9 h- S* v9 B( E0 H/ q" L+ E
Variance, 方差4 |0 j" N; D" o' p6 S; d
Variation, 变异" O S1 D6 E, ~
Varimax orthogonal rotation, 方差最大正交旋转9 O r7 F4 X; y; h2 v
Volume of distribution, 容积# z$ x$ H( r! Y6 y4 v
W test, W检验
6 \7 v0 T# P0 x* a- _; @, _Weibull distribution, 威布尔分布2 r0 c$ U! t- D& }. @
Weight, 权数& U7 T1 z5 F! l+ K. n7 Y6 c9 _
Weighted Chi-square test, 加权卡方检验/Cochran检验2 ]# U% z) W& U4 {& M
Weighted linear regression method, 加权直线回归
' U4 A1 D: b* X4 ?" g0 p. rWeighted mean, 加权平均数
) i- h; v' @$ [9 mWeighted mean square, 加权平均方差& m* H; n1 W- W4 P
Weighted sum of square, 加权平方和
N1 L" T3 H/ ^3 ZWeighting coefficient, 权重系数
- y2 H x- ] L2 w3 `Weighting method, 加权法
3 A) g2 C0 M$ f4 B: QW-estimation, W估计量
9 ~+ P6 y3 }: v4 AW-estimation of location, 位置W估计量
! k& \7 M/ Q7 a: R8 r6 rWidth, 宽度5 o2 ? f! t# ]. V1 p! y% V' R+ u
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
, |4 ^! }2 n6 u! n3 y$ mWild point, 野点/狂点; o3 U* \: `; C9 D) L" Y
Wild value, 野值/狂值* b* F$ N% W7 J1 O
Winsorized mean, 缩尾均值
1 U7 b8 K( p. f8 @6 O! ^Withdraw, 失访
6 E" n* m1 ]$ ?& OYouden's index, 尤登指数
* s2 A4 g# J8 j( ^' H1 `Z test, Z检验, F7 c$ O8 o% A7 m
Zero correlation, 零相关/ p1 ~$ \" u7 k# d3 G/ }! d
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
