|
|
Absolute deviation, 绝对离差- {, d+ }# ?( i+ _
Absolute number, 绝对数
3 ~! p. h& v/ f' L* AAbsolute residuals, 绝对残差
3 w# s' \4 V. T! k& f; TAcceleration array, 加速度立体阵
% Q( u2 j& N4 u) ]0 [* R6 Y" v1 vAcceleration in an arbitrary direction, 任意方向上的加速度0 Y0 i' C1 N6 F5 x
Acceleration normal, 法向加速度) u6 z1 u; I7 @% l
Acceleration space dimension, 加速度空间的维数
: V4 {+ M) a7 q6 T3 ^* N% ZAcceleration tangential, 切向加速度* P" l6 T5 B" t% K& R4 R. Z s
Acceleration vector, 加速度向量 _$ R/ e1 M! n C7 ?. p" V
Acceptable hypothesis, 可接受假设
4 D& m" t/ D3 q. BAccumulation, 累积
2 u0 e" u3 I3 m8 T3 i( ^% [% K/ [Accuracy, 准确度+ }% p- R1 o% y+ d% Q" t
Actual frequency, 实际频数( t5 b: K# u4 R3 r
Adaptive estimator, 自适应估计量) O0 g9 L# |. @: e7 y
Addition, 相加 E$ |3 s$ Z- O' f% f9 c
Addition theorem, 加法定理
( B0 o( T. `2 u* Y: ~: e T: R( OAdditivity, 可加性0 j- y" f3 l- x! a
Adjusted rate, 调整率; Q* B$ W( U6 [
Adjusted value, 校正值
, C# \& y6 F+ c- `Admissible error, 容许误差3 x( c4 }9 f" x$ V7 t, A8 E" e% G
Aggregation, 聚集性8 F5 R* k$ C; `9 Z
Alternative hypothesis, 备择假设
, I! V, r, x) P. m. S/ ~* ]Among groups, 组间
7 V% J2 e4 A% l! yAmounts, 总量6 e; K8 I% Y8 M ^# A5 s
Analysis of correlation, 相关分析
1 d& u9 `, J9 ]5 D# h& s' Q$ UAnalysis of covariance, 协方差分析; i+ h5 v! R+ E" k% j0 c
Analysis of regression, 回归分析
1 u; Z- V% `( x8 k c- T3 IAnalysis of time series, 时间序列分析6 k- R; Y2 C: i
Analysis of variance, 方差分析4 ?# R$ r4 |$ g8 V) F
Angular transformation, 角转换
6 z' D) ?# I8 Y7 Z: EANOVA （analysis of variance）, 方差分析
: z2 n+ l/ _4 Z! x4 H) MANOVA Models, 方差分析模型% r; u! C/ c& h& q |* d! E
Arcing, 弧/弧旋2 D7 x8 @: Q9 w; P
Arcsine transformation, 反正弦变换
3 i0 @0 T' X+ MArea under the curve, 曲线面积
: P% A1 q; X( lAREG , 评估从一个时间点到下一个时间点回归相关时的误差 + M# _2 e# V) S
ARIMA, 季节和非季节性单变量模型的极大似然估计
& k3 |. s( B& f& u) Z7 JArithmetic grid paper, 算术格纸+ a, {% U: b/ |4 z
Arithmetic mean, 算术平均数5 a9 ^: k8 Z$ i) O0 W& c1 c) j
Arrhenius relation, 艾恩尼斯关系* s+ m5 P! P: I0 t9 Z
Assessing fit, 拟合的评估( @7 V g9 \# K: I- o- @4 v
Associative laws, 结合律
$ Z8 ]( a. e. {" f4 v5 M* oAsymmetric distribution, 非对称分布
3 ^7 Q, q1 a9 PAsymptotic bias, 渐近偏倚2 H. k* N% M( n- i" m! T. Q5 ]0 R
Asymptotic efficiency, 渐近效率: R! q+ S5 S& A
Asymptotic variance, 渐近方差! }% ]- E6 Q9 J1 l) L% }
Attributable risk, 归因危险度8 g9 I% p0 y, e* L/ J, Q& A6 L
Attribute data, 属性资料
9 O" n, K' w4 r6 d; l5 jAttribution, 属性 m1 q2 y1 P" `+ m
Autocorrelation, 自相关" |5 v3 B. F6 _
Autocorrelation of residuals, 残差的自相关
% x& ?2 I6 P0 DAverage, 平均数
/ ^ i' E/ |. }- C* LAverage confidence interval length, 平均置信区间长度
3 v* S6 q. s5 M2 U) A, ?+ E9 oAverage growth rate, 平均增长率
8 x0 f, V# g4 F) |9 @* cBar chart, 条形图( H" y7 E& R. {5 h# D
Bar graph, 条形图# c9 l* M. l- s& _5 q- N
Base period, 基期3 @& [# J. [3 ?' @' G4 p f8 V
Bayes' theorem , Bayes定理
2 \1 k0 O. s- e* HBell-shaped curve, 钟形曲线
0 m+ F1 s+ E5 v4 u2 z1 A+ t7 UBernoulli distribution, 伯努力分布) x7 O3 U7 H1 m5 J/ G
Best-trim estimator, 最好切尾估计量4 y$ ~) ]: v @/ l( x
Bias, 偏性
' @$ D/ i; N9 a) ?Binary logistic regression, 二元逻辑斯蒂回归) j' e) W9 {8 I7 @
Binomial distribution, 二项分布
" _. |# y3 I8 e+ P& G8 LBisquare, 双平方6 ]6 q! j# ]) K4 T
Bivariate Correlate, 二变量相关' k1 s9 v0 ]$ K4 ]: {3 B
Bivariate normal distribution, 双变量正态分布
( j+ d! {5 |4 V6 K C0 oBivariate normal population, 双变量正态总体4 O0 c! ~/ W$ c- w6 M
Biweight interval, 双权区间5 p6 P; Z6 m: ?0 Q3 Q
Biweight M-estimator, 双权M估计量( P" g- ]9 j0 j$ F1 z* f
Block, 区组/配伍组
/ K( x' N6 c" a( A/ N1 t/ U7 IBMDP(Biomedical computer programs), BMDP统计软件包9 `& M- {. j, N3 g7 s
Boxplots, 箱线图/箱尾图( }/ u9 y) X: B' B! a
Breakdown bound, 崩溃界/崩溃点
4 l) U# [: ~* @+ zCanonical correlation, 典型相关& l. [6 M$ \+ o0 K N: F
Caption, 纵标目& f& V8 G4 \* B- g" O. @
Case-control study, 病例对照研究
2 H5 U' U3 E. M, ~8 x0 FCategorical variable, 分类变量( r: p6 P) G! j1 g7 o8 p
Catenary, 悬链线! T/ n0 {/ S# N4 V
Cauchy distribution, 柯西分布; K, ]' P+ U! V5 L. M7 y
Cause-and-effect relationship, 因果关系
! d2 ^8 ~9 A3 l0 z6 ?Cell, 单元
0 [$ c n5 X9 KCensoring, 终检
: f5 `! j+ ?2 {6 ~Center of symmetry, 对称中心% f$ ^, ~7 @0 Y# p
Centering and scaling, 中心化和定标
$ w2 ]6 `5 G" q5 H i# |4 VCentral tendency, 集中趋势 T/ d& w% L, ?, h2 o; r8 [( G
Central value, 中心值
b6 h% j& h3 g: b4 P! S' ZCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
- `/ T6 o* `0 S- S. i/ EChance, 机遇6 q9 u7 N/ s% p$ t5 z
Chance error, 随机误差8 U( i5 y' L. v; {! i
Chance variable, 随机变量
8 `: D8 r' K* F" S0 tCharacteristic equation, 特征方程5 j: t* h2 w6 K5 D* @ `
Characteristic root, 特征根& {- X/ M. N# t. Z; \* f3 n) F
Characteristic vector, 特征向量5 [8 ?, O# f# Q6 P! i3 _
Chebshev criterion of fit, 拟合的切比雪夫准则
: t, K5 v" c/ l1 W" A5 F C7 pChernoff faces, 切尔诺夫脸谱图
3 d+ ^! z- `1 `/ Y5 n* hChi-square test, 卡方检验/χ2检验) A- H$ J/ W2 u/ {+ C
Choleskey decomposition, 乔洛斯基分解8 Y) j) \0 `. Y* _) B2 y& w: o
Circle chart, 圆图 ' f. M* j2 ^2 l0 l! a- C ]
Class interval, 组距: F5 k0 z6 ~) C! r
Class mid-value, 组中值
: j0 @0 c, S8 qClass upper limit, 组上限
, O0 s f, N6 q: h1 j- oClassified variable, 分类变量1 L8 v4 V# V# n* a+ p- q
Cluster analysis, 聚类分析
7 c$ K" ~# |6 f: T1 v* e1 WCluster sampling, 整群抽样. `/ \9 W$ i0 K: A/ D
Code, 代码
/ T, B1 P: N- [% q! G4 NCoded data, 编码数据
( V0 h% m, `7 _2 C5 d; |Coding, 编码 F6 z c4 f, F# T
Coefficient of contingency, 列联系数
- M1 L* {5 o8 y9 E: HCoefficient of determination, 决定系数# K) {4 l" }. q* k' i- J) ]
Coefficient of multiple correlation, 多重相关系数
3 x, n* u! r6 _6 Q ?& J' mCoefficient of partial correlation, 偏相关系数
1 ?" g. O! l) ]1 L5 N: P. zCoefficient of production-moment correlation, 积差相关系数
V& X/ r8 ]7 E( m8 e! ? \2 nCoefficient of rank correlation, 等级相关系数
( O" G# o! ~7 j' O9 S$ p$ rCoefficient of regression, 回归系数9 i1 Q) x* d* W: e* v
Coefficient of skewness, 偏度系数
: }3 p- U6 s3 \- iCoefficient of variation, 变异系数
6 |, _- U1 {# j+ ?7 g' W. a% rCohort study, 队列研究
, L! T9 M; z1 u; _/ Q1 ~. OColumn, 列5 K+ u9 ~- T; Q0 @: G. K8 R
Column effect, 列效应
0 a, v$ ]& S! X+ TColumn factor, 列因素: D: O1 o9 D5 N" H& E8 g* Z
Combination pool, 合并
% b3 A) y; y* N& f/ hCombinative table, 组合表4 @( I. Q5 g) V9 p6 j2 g
Common factor, 共性因子
4 w! A' i6 v5 s9 yCommon regression coefficient, 公共回归系数
- T& P$ |. z( k1 W1 a+ A- xCommon value, 共同值
; P; D" T- R. h0 j8 KCommon variance, 公共方差) y) D0 j f) }% J6 Q3 t' V
Common variation, 公共变异
. c' Y r2 B/ N/ T) q4 xCommunality variance, 共性方差0 r0 _' k! B2 Q3 `/ L2 ~0 v
Comparability, 可比性
. I% h6 g; M" _* T* Q6 w+ }Comparison of bathes, 批比较
; X" F6 e2 L: K2 AComparison value, 比较值% g8 ^- |6 d, P6 h
Compartment model, 分部模型- E+ G2 o- X4 h9 B* ^: N
Compassion, 伸缩4 q t4 U2 h5 A: v; J
Complement of an event, 补事件$ e: w) @1 u3 u6 K
Complete association, 完全正相关# a% g" p5 { {( E& D7 h i
Complete dissociation, 完全不相关. M* o( q! N" z4 ?
Complete statistics, 完备统计量; w+ S P- w/ O3 z) Q/ @) n3 v
Completely randomized design, 完全随机化设计
2 b6 T/ O% h( [8 _0 ^6 m7 w3 `Composite event, 联合事件
8 M1 _, z; m2 R- [& m* tComposite events, 复合事件
* g& A2 h9 E1 K3 t z; K' y. Z. \Concavity, 凹性) _# o2 w5 L3 g- P! x0 I
Conditional expectation, 条件期望
% G+ m6 O0 m' ?# Z4 h* l" @5 S; I OConditional likelihood, 条件似然
* h+ \. G, L: O# C6 Y WConditional probability, 条件概率
# k. K) p! O" b1 A: v3 d3 Y3 hConditionally linear, 依条件线性7 K/ y0 `5 R6 h
Confidence interval, 置信区间0 C, t7 e$ l i+ x0 w
Confidence limit, 置信限
# V0 E# q; M) a0 x* J6 R) Z qConfidence lower limit, 置信下限
( \9 }" X# n! {* p2 aConfidence upper limit, 置信上限
# T2 Q. J/ ^7 T9 GConfirmatory Factor Analysis , 验证性因子分析
C& }/ O5 s: Q" tConfirmatory research, 证实性实验研究$ e4 h e. [( t* Y! |& {) x; b1 U2 i
Confounding factor, 混杂因素1 W6 u2 m: U! Y! O
Conjoint, 联合分析
4 B" ~% G0 U+ eConsistency, 相合性8 P' [1 Q2 P/ e* @$ e& |1 n
Consistency check, 一致性检验
; H8 {; Z. d& I: @$ X. j# f1 VConsistent asymptotically normal estimate, 相合渐近正态估计4 g$ u z8 g. ^( \" A
Consistent estimate, 相合估计5 f7 _7 K' g" I1 U$ ^4 w C
Constrained nonlinear regression, 受约束非线性回归/ S4 s5 \3 A1 C+ t7 k% h
Constraint, 约束
' ^1 S* F- e) E# ]Contaminated distribution, 污染分布" i) o$ X ]5 z/ f; s: I0 I
Contaminated Gausssian, 污染高斯分布
- D0 ?" P& {: ?Contaminated normal distribution, 污染正态分布0 m; a- p; q* u
Contamination, 污染4 b1 X% C" ^ ]. R! ~
Contamination model, 污染模型0 A0 }0 x6 c1 p6 w9 Q7 }& ~
Contingency table, 列联表+ h. z d% [; L
Contour, 边界线3 G4 q7 P! i* |. @" p
Contribution rate, 贡献率8 l# B4 j) R" I$ ?% q0 |, S8 ]) ?
Control, 对照! b, q+ u% P- R g6 U a9 T# T
Controlled experiments, 对照实验
; y4 \- y6 J4 }0 L0 d% bConventional depth, 常规深度
+ [; T6 S5 t7 xConvolution, 卷积/ G$ Y" Y- O J, _9 o9 E: q- _
Corrected factor, 校正因子
: t0 z( m; Z: n; F. DCorrected mean, 校正均值$ @7 [5 C; H9 `% C3 Y
Correction coefficient, 校正系数/ s; K3 m* }- f+ C4 T. s
Correctness, 正确性
8 R. {1 o" y7 K+ a9 H, `Correlation coefficient, 相关系数0 M" g. {& y9 ^, M o
Correlation index, 相关指数0 I* K* y" A, j
Correspondence, 对应, f7 ]" e5 b; \. F. _
Counting, 计数
# {. [3 X4 a9 c+ q$ R I4 J" gCounts, 计数/频数
2 B0 w- T4 s) L: ZCovariance, 协方差) m9 _6 F2 V, ^; x8 T) N6 B' H% N
Covariant, 共变 # h( ~, w2 s m
Cox Regression, Cox回归
! L! k3 |0 i2 Z- Q" K; bCriteria for fitting, 拟合准则4 X% Z# z5 X: r$ R. a
Criteria of least squares, 最小二乘准则7 L z, f% L; j8 a( _/ n
Critical ratio, 临界比
, r. ]- K5 T! _. u. G3 tCritical region, 拒绝域
6 d6 z5 H# m6 fCritical value, 临界值' h/ E: K. P, C8 A
Cross-over design, 交叉设计3 ]4 ^7 z. W" e3 [. y. h
Cross-section analysis, 横断面分析
, L4 z/ `+ z5 ~ UCross-section survey, 横断面调查5 k% v4 h; X+ T& x0 }6 x
Crosstabs , 交叉表
O0 T4 E9 J# N0 a' _( v: OCross-tabulation table, 复合表' b( t+ G5 s: J3 @& i" z/ F2 U f: e
Cube root, 立方根8 ?1 J2 H# Z1 v j
Cumulative distribution function, 分布函数( L3 Z+ _4 f9 k% L4 g% |$ R" X
Cumulative probability, 累计概率
+ |! q8 @' |7 [& Z. H) v8 @Curvature, 曲率/弯曲' x5 l% u5 J( c* I
Curvature, 曲率% m2 T: d$ ~# N
Curve fit , 曲线拟和 0 j& S5 H, [# }& c/ Y8 `' y
Curve fitting, 曲线拟合! V7 A- e: Y+ t4 y* I6 R# @2 G
Curvilinear regression, 曲线回归
5 K4 g% ~; j. ~1 t' A& w F8 c9 [* MCurvilinear relation, 曲线关系
0 H) _. m/ M0 z P* D. w5 YCut-and-try method, 尝试法9 C5 T( s4 L: }% u& P
Cycle, 周期3 H5 Q# |* p7 Q/ H
Cyclist, 周期性
' k- J' P# l3 \8 X$ d0 `D test, D检验
+ H! |" R! \; U+ j! bData acquisition, 资料收集5 b( I# S( |, q2 f
Data bank, 数据库 y% P( d! M/ }6 C8 G. F9 g* M
Data capacity, 数据容量
" b m- i$ d6 X8 O Y0 q9 ]Data deficiencies, 数据缺乏* S! g, p; n3 Q6 I0 X' M) h
Data handling, 数据处理9 ?; Q" M L( d! U% }
Data manipulation, 数据处理
* U( Q- i: `% U! B& z! P! H, x4 Y! w; gData processing, 数据处理2 u! X! h8 x' I( j. Y
Data reduction, 数据缩减' t. A- K. V3 q) H, b* A( B2 B
Data set, 数据集! C" t& ^. p& K9 v
Data sources, 数据来源& L4 z6 n0 C7 L1 V
Data transformation, 数据变换
& ^0 e8 m% W. Q* ]( jData validity, 数据有效性& ^+ g) F, H) F: v
Data-in, 数据输入0 A4 [5 k U) s5 I. t% t
Data-out, 数据输出/ {4 |, l1 n s- @- N
Dead time, 停滞期2 [9 K; @5 I7 P) q' R0 E
Degree of freedom, 自由度) P+ }& V B1 b
Degree of precision, 精密度
! n( e- X8 F& @9 S) F1 VDegree of reliability, 可靠性程度
6 I7 t+ s& y& A) v" R4 RDegression, 递减
# T# w2 r) j0 HDensity function, 密度函数
$ T7 ~+ f% J, `" O( F1 m1 iDensity of data points, 数据点的密度
6 i9 B; G# {. X4 Z8 X: I& ?, dDependent variable, 应变量/依变量/因变量5 b ?1 X7 C1 H0 }* o
Dependent variable, 因变量* W* p# L! ?. [0 ^8 v8 T
Depth, 深度
S1 D, j' Y+ W! b" r1 l; lDerivative matrix, 导数矩阵
. ^8 d3 ?8 s2 c' C2 B. TDerivative-free methods, 无导数方法 \# V& q: e$ @" z3 `: B7 B
Design, 设计
5 b- s# o3 w/ g' R( Q$ j0 wDeterminacy, 确定性+ n: ]4 {; V7 c0 P
Determinant, 行列式
6 c9 Y2 N# f6 G& G& ?* @Determinant, 决定因素
# w$ ?9 g6 x! {' U6 S# o) _# LDeviation, 离差. R8 y4 r! n# I5 G8 D# ^- a
Deviation from average, 离均差
0 k( C* U) T7 m5 ]0 FDiagnostic plot, 诊断图
" K0 }7 U; g! EDichotomous variable, 二分变量
. g; M& n1 \& p( n1 Z5 s1 lDifferential equation, 微分方程. ` C- t2 \& I! @5 K+ r
Direct standardization, 直接标准化法
" k5 O" f( F8 n! W# U3 m# E" V9 i, m. qDiscrete variable, 离散型变量
) J6 g0 |0 |) c. t, _4 Y8 L# L. ?DISCRIMINANT, 判断 3 w; [+ ]2 z! a- h
Discriminant analysis, 判别分析0 E) m/ H; r7 v0 y
Discriminant coefficient, 判别系数
5 S. B$ V( {% cDiscriminant function, 判别值
4 J5 t4 d. r3 ^) D: PDispersion, 散布/分散度5 {! \ L* ^; D6 g
Disproportional, 不成比例的" U# Y. p+ `3 V; j& F R
Disproportionate sub-class numbers, 不成比例次级组含量
2 r+ B* Z* S5 _0 o. CDistribution free, 分布无关性/免分布
/ W) k& u3 _" {, fDistribution shape, 分布形状% W( U: y+ V" z5 a( c
Distribution-free method, 任意分布法
) R; a. B% L! t; C2 iDistributive laws, 分配律7 \6 F9 Q% y% o' s
Disturbance, 随机扰动项3 U7 t( w# e% l& N. J
Dose response curve, 剂量反应曲线, w+ s0 r/ u9 }' @# A D
Double blind method, 双盲法# s [) U q0 S m, w. |2 X9 o
Double blind trial, 双盲试验" p3 h p( z/ n, A' V
Double exponential distribution, 双指数分布
: Q$ g) Y0 V5 p2 YDouble logarithmic, 双对数3 r, x* y; u& C5 t
Downward rank, 降秩
2 [( S5 L* X/ y- m; @9 N. b" ADual-space plot, 对偶空间图8 N( ?5 S& J0 x
DUD, 无导数方法) ^2 a7 g/ ^. C/ A3 ?7 A9 a7 H/ ^
Duncan's new multiple range method, 新复极差法/Duncan新法- i! S3 W1 k$ k* w/ Q% B# K4 {! d
Effect, 实验效应$ X9 `* H- j( L! S3 k' ` C
Eigenvalue, 特征值2 r" p0 g0 o$ l2 J7 D" w
Eigenvector, 特征向量
" h! J8 h; g) L( O [9 j) _- LEllipse, 椭圆6 a" }0 F" D7 P! j9 N$ r
Empirical distribution, 经验分布
! p2 j& T |1 a" qEmpirical probability, 经验概率单位8 k' l! w# P+ Z+ |0 p8 \) P- w
Enumeration data, 计数资料: f: L9 V" f- E" x3 R
Equal sun-class number, 相等次级组含量
* u1 C0 h: |; E: r( |8 IEqually likely, 等可能* Z5 b6 Q! f/ a( F, v9 s
Equivariance, 同变性
* X4 }8 `$ B& P8 e3 D& e r$ ]6 N1 VError, 误差/错误. K/ g" y1 @/ c( @
Error of estimate, 估计误差
! i) V. d Y" Y( I/ _Error type I, 第一类错误
/ \, Y9 m& x1 @$ |* F( m LError type II, 第二类错误
) r% J4 v7 U# v$ E/ K' W5 oEstimand, 被估量+ N" N+ r6 R1 y
Estimated error mean squares, 估计误差均方! y+ Z6 I" E# k& c5 I
Estimated error sum of squares, 估计误差平方和7 K( ~9 {. \1 ]) @ \
Euclidean distance, 欧式距离; R1 Z z" f3 a$ Y9 ?
Event, 事件 g- K! f% f8 J e# I
Event, 事件
" P1 h' R9 ]8 T' I7 v2 FExceptional data point, 异常数据点8 h4 v1 i( o, Q% X7 o! x% ]
Expectation plane, 期望平面 _' P6 b& d! B. p; G% R+ E
Expectation surface, 期望曲面
$ k U3 e- R- x7 C0 _Expected values, 期望值
- o, |; r4 e! {$ f0 dExperiment, 实验 I v6 y% m, h) g
Experimental sampling, 试验抽样
/ o/ J, p& J0 x6 G7 f+ h/ b8 tExperimental unit, 试验单位% k2 |$ r. s4 D3 t: m$ D
Explanatory variable, 说明变量
+ }" F# W% k7 G, ~+ g. KExploratory data analysis, 探索性数据分析
+ n# M" s$ \+ f; aExplore Summarize, 探索-摘要* T( z+ [ t* Z' h% W* U
Exponential curve, 指数曲线
; {0 m6 d7 r) j4 U+ KExponential growth, 指数式增长
( t' i( K4 R% HEXSMOOTH, 指数平滑方法
* c* p2 q4 H+ a( d- F1 vExtended fit, 扩充拟合% ?5 j- D9 U5 t; a
Extra parameter, 附加参数) q) L1 _! L, P& {7 R8 ?
Extrapolation, 外推法. W" j# p9 G7 ]8 t* l4 a
Extreme observation, 末端观测值- P5 H2 A9 `3 ^; N8 u' C; L+ b. L& B
Extremes, 极端值/极值
. T1 A; Z! Z3 I) u0 n, fF distribution, F分布8 a7 ]! \2 S5 j* [9 X( m+ [
F test, F检验; e" `. Y9 x# `" y. J
Factor, 因素/因子% i" c0 b5 L7 [
Factor analysis, 因子分析+ A2 U, n4 G% x& l$ a1 j
Factor Analysis, 因子分析 l$ }) I# W* A9 X+ y7 i' l
Factor score, 因子得分
8 S' T$ g; M+ l3 ^8 SFactorial, 阶乘" d; g1 F1 U% d# r
Factorial design, 析因试验设计, R4 u* e; N0 n# C, Z
False negative, 假阴性& y% \% k' j" b; X. b$ f' o0 a$ @
False negative error, 假阴性错误
: m2 f# Z5 L) d" h! C8 `5 e$ k& IFamily of distributions, 分布族% } J5 m6 X; H$ o
Family of estimators, 估计量族 m/ g0 s" k& M# a3 p
Fanning, 扇面
! w: u' H& I0 W8 G0 [Fatality rate, 病死率% E- P. _! n% \$ M
Field investigation, 现场调查
9 y! n; B% U/ \" ?9 Q- L0 R& OField survey, 现场调查
" c9 N9 K/ M+ {5 W" @0 aFinite population, 有限总体6 `1 W& `- k+ O
Finite-sample, 有限样本
9 z0 u+ q) `6 D: y( }: f* ~% [' EFirst derivative, 一阶导数
. d; q5 z- C* ^, A0 h6 p/ c! W/ |0 {First principal component, 第一主成分
0 [) o- f0 A0 m; c tFirst quartile, 第一四分位数3 B$ s' O! t* A7 A% S9 f, X
Fisher information, 费雪信息量, I" Y. H5 r7 @
Fitted value, 拟合值1 Z& G/ A( L( Q8 E
Fitting a curve, 曲线拟合- p! I9 z* W+ m5 i' S' F' U; |
Fixed base, 定基% f9 E7 h q; F0 h' i4 ^
Fluctuation, 随机起伏
% s7 e! b: b$ m: d" X- H' j5 l5 SForecast, 预测
* H a& A7 ]. E: U) XFour fold table, 四格表
2 \ s4 c* x+ dFourth, 四分点. T b( v0 J# B" ]$ l
Fraction blow, 左侧比率
! y8 x6 ?9 {9 O J7 t, B" VFractional error, 相对误差
; s6 L8 B# b2 p- dFrequency, 频率) O$ o0 D6 ~1 ~% @( z/ a$ J
Frequency polygon, 频数多边图2 J. A! g$ D, a
Frontier point, 界限点3 h, x1 U# F2 j
Function relationship, 泛函关系
# m( o* G- A# l4 ~' IGamma distribution, 伽玛分布
+ A" F/ p L4 ^1 `" AGauss increment, 高斯增量1 B1 T* x3 p. j) w0 u$ Z
Gaussian distribution, 高斯分布/正态分布* ^ L( k' m) F
Gauss-Newton increment, 高斯-牛顿增量 I. B* \) ~% L/ { B% B4 c* {) _
General census, 全面普查0 h+ g! N% J) y, ]. W
GENLOG (Generalized liner models), 广义线性模型
# h! J4 i7 |& [. b; YGeometric mean, 几何平均数
3 q; r4 F# g0 o9 D9 ?( ^9 YGini's mean difference, 基尼均差. Q9 b# s* M A8 r
GLM (General liner models), 一般线性模型 * G$ j2 b1 K6 _: Y z B
Goodness of fit, 拟和优度/配合度
0 F q/ r% ?0 @$ S" z; \* GGradient of determinant, 行列式的梯度
' k3 j& k: \$ U- L3 u1 j# eGraeco-Latin square, 希腊拉丁方, k( D: I6 q% ~" M5 Q" i, M
Grand mean, 总均值1 k( ^4 \; G* a2 a
Gross errors, 重大错误
- m/ e" ~) t) K0 G3 \- t6 ]. R0 q6 y& NGross-error sensitivity, 大错敏感度
L9 d1 L4 ]2 _% f: MGroup averages, 分组平均- _/ L3 {. E! a* x
Grouped data, 分组资料 b8 v8 \. k" Z- Y: U
Guessed mean, 假定平均数
+ J. C+ U6 [7 ]. FHalf-life, 半衰期
4 i) M7 p! k! D- `9 EHampel M-estimators, 汉佩尔M估计量2 i! g9 a5 |7 g3 q3 w
Happenstance, 偶然事件* H' s) v! k8 q" y1 j' D
Harmonic mean, 调和均数
- o G+ D. @$ `) U/ ~8 ?! z6 s' o" mHazard function, 风险均数0 w# U, B- U1 m! `& y; ~3 M& ~
Hazard rate, 风险率# A, Z4 }" M" o6 f: f' j [9 ]
Heading, 标目 * ^4 L& l) ]' w- ?! |
Heavy-tailed distribution, 重尾分布
( E6 v+ ]/ a( P6 iHessian array, 海森立体阵
1 s: u! }3 ~( PHeterogeneity, 不同质/ ^ r0 _. K4 J* e8 m# }
Heterogeneity of variance, 方差不齐 2 p0 l' _& E9 d" K$ N
Hierarchical classification, 组内分组
3 u: ]1 e! X, x: d/ I! T& F. x8 ?0 WHierarchical clustering method, 系统聚类法- h. k2 L/ D7 I# r" |) R
High-leverage point, 高杠杆率点
: }9 A4 P% l& Q9 x; a4 lHILOGLINEAR, 多维列联表的层次对数线性模型 t5 t3 T* p x% L5 p8 b8 y: q
Hinge, 折叶点! q3 P0 Q9 h. i Y% g* P
Histogram, 直方图3 U8 N7 ?) \# ]4 M" c
Historical cohort study, 历史性队列研究 3 g r' ]/ P$ |2 \
Holes, 空洞
3 [0 L* N9 t/ {& bHOMALS, 多重响应分析+ }! X; Y% D4 x0 y( y3 f: L. o5 S
Homogeneity of variance, 方差齐性9 u5 b. S. M, D4 l) G6 e2 A
Homogeneity test, 齐性检验
3 q4 i2 _4 u5 y/ U" g5 RHuber M-estimators, 休伯M估计量6 ^5 i1 L" |: o& m x' _" Y3 e; V
Hyperbola, 双曲线
& }: H" x% q4 F6 j0 V0 k8 Y. IHypothesis testing, 假设检验
8 ?6 f- i7 r# ?* W; {3 c5 MHypothetical universe, 假设总体
5 K9 w; i1 L$ w2 IImpossible event, 不可能事件
2 {: Y! [) [; q2 K$ F4 K4 ? p% [Independence, 独立性' z$ H8 w* A9 U8 [: a
Independent variable, 自变量
4 ]2 o. Y1 u3 Y0 F$ N3 EIndex, 指标/指数/ x3 W; W! k* c4 \/ X
Indirect standardization, 间接标准化法$ X" w' K$ q }+ Z% z3 o0 ?" i
Individual, 个体7 e& l0 y: n3 c* j- U v
Inference band, 推断带" J: r0 I. x3 c* v( W7 ^1 h) m! _
Infinite population, 无限总体* l% Y! o% ?7 i
Infinitely great, 无穷大7 B" Z' X" j( U
Infinitely small, 无穷小3 P. I/ G9 [( u% d' N
Influence curve, 影响曲线1 }* [2 f3 _- R U* u
Information capacity, 信息容量
" w, U. p& R7 @! z) n4 AInitial condition, 初始条件
2 |5 ^6 ~! i/ J3 o8 Y1 u: NInitial estimate, 初始估计值
; O0 x( n1 d- e9 N7 \' w2 J) @9 KInitial level, 最初水平! x" o" l( U5 t0 W
Interaction, 交互作用2 z4 j w) y$ W; x& s; f
Interaction terms, 交互作用项
' m1 R$ I0 R- Z1 @ DIntercept, 截距
; n3 X' j8 H* Z8 [ O w6 ]" {Interpolation, 内插法
7 K+ G7 ]0 d0 c( s# g. DInterquartile range, 四分位距
( D$ S, z8 B! u% aInterval estimation, 区间估计
# b6 h' a% g+ ~8 }; m3 s! ]) CIntervals of equal probability, 等概率区间
3 G$ l* r/ T* U! \Intrinsic curvature, 固有曲率5 c9 S/ O ?" N. K; }
Invariance, 不变性
L3 f# S" I d8 R7 d" kInverse matrix, 逆矩阵
! s8 r' w# F: ~Inverse probability, 逆概率, g. n( D4 R J) s
Inverse sine transformation, 反正弦变换
0 I. L# Z, }1 A0 h% G( jIteration, 迭代 2 A, K {0 E) w* B5 u- ]6 y
Jacobian determinant, 雅可比行列式; o& U" i. A5 X. N' t8 M) I
Joint distribution function, 分布函数
% [+ j% R! X% U: c: }; w6 `Joint probability, 联合概率
7 d5 c) B& v+ d, S2 H& l6 {Joint probability distribution, 联合概率分布
7 e& \0 D1 ]6 S& lK means method, 逐步聚类法; o2 ~9 C' g6 w4 `4 O! ^. \; I
Kaplan-Meier, 评估事件的时间长度 $ D2 D1 S, R7 |8 C* b
Kaplan-Merier chart, Kaplan-Merier图
" T* l5 [( L; z9 d, yKendall's rank correlation, Kendall等级相关
# f( C6 W6 N5 U! ~: F/ J$ ?! qKinetic, 动力学- C, F3 N$ G* ?- F! f3 y. v9 \
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
& i$ V" w# [* `* m- X- k) B( IKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
! W7 s5 }% ^% E2 TKurtosis, 峰度
3 d. v5 M+ n. w/ t2 _Lack of fit, 失拟
" Z) n8 } F+ E, j+ v0 X$ R* tLadder of powers, 幂阶梯5 U e/ t& {2 u v+ A
Lag, 滞后
* _: }( T9 ]4 t7 S- X: x2 r& d! r8 tLarge sample, 大样本
9 W/ h& n4 f z4 w. M p/ SLarge sample test, 大样本检验: g! x1 V% m4 V
Latin square, 拉丁方
! f. Q0 x- e: a4 ELatin square design, 拉丁方设计) B) b7 \. X1 A7 w; R. c0 _
Leakage, 泄漏5 u6 u) N$ o6 d8 c2 ^' K0 Z6 _
Least favorable configuration, 最不利构形. [" _* R% T$ r6 r
Least favorable distribution, 最不利分布
- a) e+ w9 M4 `( zLeast significant difference, 最小显著差法
6 Z$ y6 O6 @9 d- N K' fLeast square method, 最小二乘法
3 X. H3 x& U- i' f% NLeast-absolute-residuals estimates, 最小绝对残差估计( U- M! p. A. S7 |& J
Least-absolute-residuals fit, 最小绝对残差拟合
/ `9 [- z3 Y s% m) k4 zLeast-absolute-residuals line, 最小绝对残差线) P: L+ p- p) `6 T4 R% M/ w. \1 J: y+ B
Legend, 图例
0 ^5 P: w/ Y0 C: q$ W4 gL-estimator, L估计量7 n1 m0 J3 u- h$ Z& t
L-estimator of location, 位置L估计量# C" o2 N! c U9 {4 d- A8 ]
L-estimator of scale, 尺度L估计量
6 s+ n4 B* j( c8 [, xLevel, 水平# N% D' N; z( y/ K
Life expectance, 预期期望寿命
8 r, p/ D6 F. F9 o/ ~$ A/ [Life table, 寿命表
4 x3 \* c2 W$ d, Z& KLife table method, 生命表法" _& s8 |; c7 w7 }! s
Light-tailed distribution, 轻尾分布
- U9 K, I, b( u8 k2 p) {% BLikelihood function, 似然函数
( u0 b! {, f+ h NLikelihood ratio, 似然比8 r2 M+ o' ]+ Q! r ~7 U- W
line graph, 线图" F, n3 v6 u2 j/ J3 K. P
Linear correlation, 直线相关
. T% D0 m) C3 _+ [' U2 Q9 |. HLinear equation, 线性方程
& e. ?- y: p* w+ v- K" yLinear programming, 线性规划' ?+ V( p3 @6 C! \' b
Linear regression, 直线回归
/ H. ^( D: x1 t: e( vLinear Regression, 线性回归8 ^+ X+ m9 t9 G% Z# ]6 k- z
Linear trend, 线性趋势$ ]4 M2 s9 @7 _5 u# F: e
Loading, 载荷 ! N6 u' P# c. C* `4 T" t
Location and scale equivariance, 位置尺度同变性
8 F& x) @. S, d! M0 rLocation equivariance, 位置同变性/ t; n0 F2 g4 W' w% H
Location invariance, 位置不变性5 M8 \0 }3 |5 c5 r$ e3 B, x, e0 K
Location scale family, 位置尺度族
8 ]- y/ u2 I+ t' J: A! nLog rank test, 时序检验
# k; ~3 n1 S8 c g: P7 HLogarithmic curve, 对数曲线
) V1 m$ u: T0 ]6 _Logarithmic normal distribution, 对数正态分布# g( t( f" W$ M0 c8 A$ ]6 x
Logarithmic scale, 对数尺度2 l- x- x! A+ D U; l
Logarithmic transformation, 对数变换& N( @5 A& j$ y1 t
Logic check, 逻辑检查. O) L+ p' h- l6 |; G
Logistic distribution, 逻辑斯特分布( V9 q4 ?7 K& l; T: F' Z
Logit transformation, Logit转换6 h1 c T% m) A/ e
LOGLINEAR, 多维列联表通用模型 * \6 d! h( |2 l" _1 o- }6 ^
Lognormal distribution, 对数正态分布
" G/ |, c# Z& |4 r% g/ v: {Lost function, 损失函数
( x7 O" c% z& x# ~* u5 xLow correlation, 低度相关: F$ N( J& l2 l, l, b6 Y8 D* k+ p2 X ^
Lower limit, 下限
# |0 x( r* j4 O% `- P0 D! PLowest-attained variance, 最小可达方差
6 n% i) ~0 c" x4 V& Z9 q# SLSD, 最小显著差法的简称: n6 p0 o! F( Q
Lurking variable, 潜在变量
# N; I/ p8 P! d0 T! PMain effect, 主效应
* P9 M6 c# f: S; B9 SMajor heading, 主辞标目
' K$ ~8 C# Y2 d; \Marginal density function, 边缘密度函数
/ D0 R7 Q: X8 {+ |" v6 QMarginal probability, 边缘概率! a5 `/ J* C5 K7 u. ?+ b
Marginal probability distribution, 边缘概率分布. G/ ^5 O# L2 O( I3 z( O
Matched data, 配对资料' g8 z1 |- A1 B3 H/ F! G) A
Matched distribution, 匹配过分布. O: U7 b: \( y5 e- j
Matching of distribution, 分布的匹配- \0 e6 L0 _1 |$ h% X7 G
Matching of transformation, 变换的匹配% Y0 i( n: S+ y0 B4 w: Z
Mathematical expectation, 数学期望
& c) ? R- |, q" P, D ]Mathematical model, 数学模型
) G9 S' S! _5 q7 t9 I# a; {Maximum L-estimator, 极大极小L 估计量1 K7 H5 G7 Z* X/ |
Maximum likelihood method, 最大似然法# n" Q* W7 B" t+ Y
Mean, 均数8 T: O, @5 `1 n" d$ [( I
Mean squares between groups, 组间均方
( t1 ~3 n6 G1 ^+ D' o# ^7 oMean squares within group, 组内均方0 k3 b6 c7 v5 A E9 a- |
Means (Compare means), 均值-均值比较
4 L* Y) J0 S$ A9 @Median, 中位数. F9 U5 d4 `& C* I# d1 e0 e, ^" |
Median effective dose, 半数效量
, |8 J9 B4 Y- F( oMedian lethal dose, 半数致死量" e' g. i Y7 Z- Q+ c1 O
Median polish, 中位数平滑3 _1 x+ f6 ^ E& `) X0 y1 A$ I
Median test, 中位数检验
- N. S( p3 u( g' [- M5 T. J/ I* lMinimal sufficient statistic, 最小充分统计量
5 q6 ?7 w/ G1 V+ T7 C% T, NMinimum distance estimation, 最小距离估计( \( Z/ D3 H0 Z7 x3 y& j
Minimum effective dose, 最小有效量
. g1 a. ?0 R7 H" n- V7 I( ]Minimum lethal dose, 最小致死量1 H4 g# I! ?6 N, X' J6 r+ w5 U
Minimum variance estimator, 最小方差估计量
9 d, D6 `8 S/ p! \; y. Y: LMINITAB, 统计软件包
* m; r) s1 o$ M7 LMinor heading, 宾词标目
3 K3 x# R4 a" W9 ZMissing data, 缺失值
5 d- |2 _! B4 s4 n; nModel specification, 模型的确定
' \( u$ Z8 D! e, q' A' NModeling Statistics , 模型统计1 `. r4 X7 Y3 r& [& u$ d* a- K
Models for outliers, 离群值模型8 o0 F+ N1 s) D
Modifying the model, 模型的修正
7 l% N# m. }7 [% bModulus of continuity, 连续性模9 @' ?: {4 Y; b( O+ |/ \' \6 {
Morbidity, 发病率 7 y6 Y3 m! h% f0 @5 V
Most favorable configuration, 最有利构形3 l: X$ G/ c+ d. j5 M) e
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
0 O8 o: c9 r2 i" S2 LMultinomial Logistic Regression , 多项逻辑斯蒂回归, K" v: K+ I" X0 `! n) F
Multiple comparison, 多重比较6 v- o: I! F& u; F( j
Multiple correlation , 复相关7 X# K# f; @9 [ L, h& |. ^! V
Multiple covariance, 多元协方差
: j$ ^# P9 j# T) e/ \; Y* w- \* xMultiple linear regression, 多元线性回归
( d: q+ U& o# oMultiple response , 多重选项; Q/ t5 |$ X5 P6 U
Multiple solutions, 多解
5 u( M6 Q" B7 x8 ^! j4 `" ^Multiplication theorem, 乘法定理
! U5 ]' D! S" r+ u7 k; @4 VMultiresponse, 多元响应
7 O- W6 P6 r" e% OMulti-stage sampling, 多阶段抽样
$ o' O- G3 s _- X8 \2 ]" M ^Multivariate T distribution, 多元T分布) k; S" S( u' |* E
Mutual exclusive, 互不相容5 ^" Z5 E& I* {& u
Mutual independence, 互相独立, O: m/ L, k! ~3 R" J6 ~
Natural boundary, 自然边界
/ X4 E& i' i* B8 X7 T7 ZNatural dead, 自然死亡
4 k) N3 [: w- pNatural zero, 自然零! \ q, Q# {4 }( W+ N; M) }8 U% M) h
Negative correlation, 负相关
2 U8 j+ Z2 Z1 S4 ^. `* G, `0 r2 j& o `8 ENegative linear correlation, 负线性相关
$ _+ I1 L1 p6 E$ ]0 ]: P) y& A5 NNegatively skewed, 负偏6 G) b' \# x2 h |# I8 q
Newman-Keuls method, q检验& f& r# D2 ]5 F0 {; D7 D
NK method, q检验! D6 \# Y! x# Q8 _9 |/ o- Y K
No statistical significance, 无统计意义6 K" b0 D0 ~6 K: y+ |! w% h2 o/ Z; Q
Nominal variable, 名义变量
# n( m" h& I y) V4 F9 BNonconstancy of variability, 变异的非定常性
( W$ r& F2 ~( z! h4 pNonlinear regression, 非线性相关
9 J) J3 q2 m% x. z/ b; mNonparametric statistics, 非参数统计
$ ~1 T; I% U; `Nonparametric test, 非参数检验
+ ]% X9 V# i" D' G( ANonparametric tests, 非参数检验
4 f) z; P A/ g2 n9 cNormal deviate, 正态离差
/ ?# I) P5 o6 B1 F0 U jNormal distribution, 正态分布
, [0 A; s% V4 W+ f8 o5 y0 BNormal equation, 正规方程组
& T9 m6 A" _& }# N6 ]% Y& oNormal ranges, 正常范围6 J8 p6 x2 i7 M) T
Normal value, 正常值+ J9 a. r0 x3 n$ U( w4 l3 W- _
Nuisance parameter, 多余参数/讨厌参数" z* A7 y! ~# K* }$ n6 H
Null hypothesis, 无效假设
7 A! M: _3 W; S! n8 z2 g" K$ kNumerical variable, 数值变量 t) T2 H) r- v2 |- Q
Objective function, 目标函数
/ R4 l* a4 {: @5 F4 _Observation unit, 观察单位& [5 u( i* v# T6 E
Observed value, 观察值
) ?4 f- G) O& mOne sided test, 单侧检验6 p8 F# ` b6 r9 H3 s2 Q
One-way analysis of variance, 单因素方差分析
' n1 N- I3 L5 _+ e4 z {Oneway ANOVA , 单因素方差分析4 I3 p1 a3 @$ h1 `8 J2 b2 g! @
Open sequential trial, 开放型序贯设计( c1 i$ w5 _! ^0 b
Optrim, 优切尾 Y8 R/ F3 p; T" Q5 z
Optrim efficiency, 优切尾效率
: q( Y- ^- n) @6 iOrder statistics, 顺序统计量
3 _$ ^( X4 i% s& Y9 M' l fOrdered categories, 有序分类& u# d z1 T0 ?
Ordinal logistic regression , 序数逻辑斯蒂回归
2 h$ \( W$ A6 I% s/ x: EOrdinal variable, 有序变量
9 r, D1 t, u7 R$ o0 ^Orthogonal basis, 正交基
- T9 B6 p3 {) L5 fOrthogonal design, 正交试验设计
8 }- O. N/ E! N: ], V* UOrthogonality conditions, 正交条件
& @+ Z, Z& X7 k5 D6 G. [! rORTHOPLAN, 正交设计
& `. [0 |) s- |7 M, N: D0 `Outlier cutoffs, 离群值截断点7 {% f0 {/ t& E
Outliers, 极端值5 E: t. } i% ?; b8 U/ O: Q
OVERALS , 多组变量的非线性正规相关 % H& e2 s# a# N3 f- ?
Overshoot, 迭代过度
8 [) j1 E* r; @, Q$ @0 Q( T* QPaired design, 配对设计: }9 ?) M b9 p! G2 i* v
Paired sample, 配对样本7 e; {& Z* L4 U2 v$ N* L
Pairwise slopes, 成对斜率3 X/ r6 I8 `! c8 |) Q
Parabola, 抛物线
# d8 H: N& f: p8 S( L$ Y) P5 bParallel tests, 平行试验# B# N" G' f( f a! L7 `/ [
Parameter, 参数) G: h1 g* a6 j5 `3 k, ~6 r# v" t
Parametric statistics, 参数统计5 G" l! C" e, d: K- G( A
Parametric test, 参数检验+ J: a& k) s# v9 Y) u2 Z- I' o, Y
Partial correlation, 偏相关
0 I6 ?& V, f4 g* ePartial regression, 偏回归1 c6 h+ a. W: x! D' w, k/ _1 N) @
Partial sorting, 偏排序
6 F8 y* U( X, L3 iPartials residuals, 偏残差
+ o0 A8 C' Z5 m" Z$ L7 \# jPattern, 模式
, V( F" n, A! q7 aPearson curves, 皮尔逊曲线
' x4 D1 d1 P2 E" \, _Peeling, 退层
( p' g9 D# k* a! p! p0 BPercent bar graph, 百分条形图
c7 J* l8 Z9 {; lPercentage, 百分比. e' u3 k( r0 Y8 K5 U
Percentile, 百分位数+ ^, e% b; m- I3 p5 {" d
Percentile curves, 百分位曲线
% c) w W) v. Y0 y6 A) EPeriodicity, 周期性' H3 f/ j$ ?' t( B- M8 k. a
Permutation, 排列$ ` N, s: M5 \) W+ o1 f2 n
P-estimator, P估计量
$ H" y2 p* P! o3 KPie graph, 饼图# v, L' f, [- E1 L
Pitman estimator, 皮特曼估计量: Z* H4 P4 U4 G6 Z% b# r- ], M
Pivot, 枢轴量. ^! C! A! C6 R4 O4 T; G6 ~0 D3 {
Planar, 平坦
( t/ [% j! G8 BPlanar assumption, 平面的假设8 q& Q7 E1 z3 ?$ v1 H, I
PLANCARDS, 生成试验的计划卡
! J `7 K' y+ `: |: ^, A" e# F( aPoint estimation, 点估计
, F1 X/ q$ o9 [Poisson distribution, 泊松分布1 s$ Q! G% _6 ]2 C
Polishing, 平滑
\& H# U, a5 @# HPolled standard deviation, 合并标准差4 ^& E1 ~2 }+ ~+ U Z
Polled variance, 合并方差/ b4 ]4 W* ~. ?$ s; ^9 h5 X6 H
Polygon, 多边图) N& p7 F0 O1 d7 |7 n6 X7 ~9 L {
Polynomial, 多项式
" s9 l: q/ w& j! k! RPolynomial curve, 多项式曲线
0 `# @6 L, @ s: f$ X cPopulation, 总体
$ p8 Y- l5 C; a2 APopulation attributable risk, 人群归因危险度) }3 G# Y1 C3 Q: S0 V! P' ~
Positive correlation, 正相关0 E ]6 w/ ^6 Q& i: w
Positively skewed, 正偏2 l$ v) J" e( D9 Y' H* q# R
Posterior distribution, 后验分布
: ]4 }$ t5 M8 k, q8 \+ M$ OPower of a test, 检验效能
7 Z; r$ X' k7 L% _- n1 APrecision, 精密度
& d8 f$ g) i3 P5 t$ j8 IPredicted value, 预测值
" R: o% d' Q6 u6 {0 JPreliminary analysis, 预备性分析& `: X. N6 m+ @8 M$ ^8 w1 {
Principal component analysis, 主成分分析
7 x8 N* L" D z1 _7 ~Prior distribution, 先验分布% `8 C" g( K# F7 X0 l1 x; X2 `9 P
Prior probability, 先验概率) C4 v6 p1 E7 q& b; _- o
Probabilistic model, 概率模型
4 @/ v Z( T! _/ A2 Cprobability, 概率
, \2 n# ^5 }, A5 sProbability density, 概率密度" l( T# X8 J N% q
Product moment, 乘积矩/协方差4 r8 I* i# _1 Z) r8 S2 a0 g
Profile trace, 截面迹图
2 [( w3 N) o( b7 V& LProportion, 比/构成比
& X2 T8 D3 z4 y9 @ X) uProportion allocation in stratified random sampling, 按比例分层随机抽样! w" z9 v# M' b+ J# ~1 s' ^) V
Proportionate, 成比例$ Q% e4 @/ c; M0 n+ S. }" ]- E
Proportionate sub-class numbers, 成比例次级组含量7 h& j0 g* l- @( K A$ z% k
Prospective study, 前瞻性调查
* H# f. f9 Q6 ~7 ?1 b5 jProximities, 亲近性
8 ]. v# k0 W, h6 b0 k" @Pseudo F test, 近似F检验
& @0 U: N+ w2 L# e% a BPseudo model, 近似模型
" A) d* [3 r# u* y" O: ~Pseudosigma, 伪标准差
/ k% ~! c: Z/ U- JPurposive sampling, 有目的抽样
$ Z' S& I$ z3 w$ qQR decomposition, QR分解
6 Z ?; P; j! ?0 @Quadratic approximation, 二次近似
* k7 [$ h6 f: u3 I0 z4 I; z CQualitative classification, 属性分类
' |* |+ i" B* N6 C; @Qualitative method, 定性方法
3 K# F F% K8 I! V2 ~3 AQuantile-quantile plot, 分位数-分位数图/Q-Q图1 V8 d: z% M: o6 w1 L
Quantitative analysis, 定量分析
. x1 w. G/ A5 A. zQuartile, 四分位数
; O% A3 ?; ?; D9 U0 J; E2 T/ Y# sQuick Cluster, 快速聚类! w/ Y7 K X$ H3 K1 J9 P
Radix sort, 基数排序( ]+ o6 v7 Y e4 Q
Random allocation, 随机化分组
+ m5 s2 C' R8 d9 k* |9 |/ f9 U3 @Random blocks design, 随机区组设计
- F m n5 d2 C# {Random event, 随机事件
8 o: n; t/ h9 W; H- Y9 v$ U7 KRandomization, 随机化8 C4 `/ {4 H& F
Range, 极差/全距: t% T; z7 A& o7 M6 o' L/ @ V
Rank correlation, 等级相关
) V9 Y# `# N7 R, w7 j' XRank sum test, 秩和检验
/ Y/ h: T% f4 {8 P4 `) \$ D- [Rank test, 秩检验& z) D0 U: X) U1 K" T
Ranked data, 等级资料
9 E- O/ U }) @1 E$ f" p( O, O, fRate, 比率! Y& S" E) ]) _- l
Ratio, 比例
0 h; ` M% ~* s* g dRaw data, 原始资料' R8 w9 E- O3 Q1 T! C
Raw residual, 原始残差
) k4 Z @: ^5 Z# s7 C" [( T( RRayleigh's test, 雷氏检验) E7 j# m! }% S" x) \( V6 n
Rayleigh's Z, 雷氏Z值 & r0 [# Z- K7 w% L( T1 ?8 R0 i
Reciprocal, 倒数: `4 J) J4 c$ T0 y) ]4 X
Reciprocal transformation, 倒数变换
4 t# u9 ~% |4 i0 ?1 S w# DRecording, 记录
8 o; M/ L$ m4 |! v2 X' KRedescending estimators, 回降估计量
& ?( a& w3 E: _# r3 R2 qReducing dimensions, 降维4 ~: q0 h C3 m6 ]0 X6 c& w: ~0 z
Re-expression, 重新表达
& T: ?4 y! ~6 yReference set, 标准组
: M3 A6 E! Z# `- L" K# T4 SRegion of acceptance, 接受域, b8 S3 v# A; m2 {
Regression coefficient, 回归系数 [2 `. j& q8 O
Regression sum of square, 回归平方和
; ^6 g' D7 _) |$ |0 d* SRejection point, 拒绝点
1 `0 }$ r6 h% X m# D8 lRelative dispersion, 相对离散度
' }7 P. O4 T! |( ERelative number, 相对数0 b& O, ?2 L7 }" y, ^5 m
Reliability, 可靠性
3 i8 q6 y; ~$ pReparametrization, 重新设置参数
0 H9 } X) C9 xReplication, 重复
1 g. V- X: v6 F* S' `8 D! vReport Summaries, 报告摘要
5 G% S& d8 i" UResidual sum of square, 剩余平方和
/ g, m/ ?) E- I& q$ kResistance, 耐抗性) s L, \6 e5 b# A3 i
Resistant line, 耐抗线& \# S8 }0 ^* U" g5 I
Resistant technique, 耐抗技术
1 X- Q2 C" R/ W% q1 b8 M% z; yR-estimator of location, 位置R估计量
; E$ y! `- f& Y4 XR-estimator of scale, 尺度R估计量+ p2 R3 y$ q4 C" h# ^! E" V
Retrospective study, 回顾性调查
) i3 X6 ~8 j. ^3 }! V' yRidge trace, 岭迹
: |) L1 s, r6 A0 T+ c+ uRidit analysis, Ridit分析
' ?) j$ p a9 V+ }9 M8 HRotation, 旋转
1 z: E5 V+ X6 @Rounding, 舍入
" I; `$ N( w; @% v7 X& q& G3 IRow, 行- H' L3 R, ^' p, t
Row effects, 行效应9 ~: j" m8 ]& `! e' b/ g
Row factor, 行因素% p$ N; c& t h9 i
RXC table, RXC表
& l% U% _& o: t o. d& HSample, 样本; }8 s1 x8 Q W) E4 ]/ X L; z
Sample regression coefficient, 样本回归系数
3 r+ I# {, E, U/ E- ]Sample size, 样本量
" A" n4 K, z2 [& Z. E PSample standard deviation, 样本标准差
; h7 J' B- y% t- O' V- _Sampling error, 抽样误差8 H7 S" _9 I. o+ y
SAS(Statistical analysis system ), SAS统计软件包1 K& i' A+ o- ^9 F8 m1 n& m" W; F
Scale, 尺度/量表
7 ?$ x2 m# b, H3 I1 l4 jScatter diagram, 散点图+ X8 V6 W5 T3 s0 H* j: C
Schematic plot, 示意图/简图0 m! h8 I+ ?0 p/ w$ q
Score test, 计分检验- \1 ?3 ^: ~; I x$ w3 ]
Screening, 筛检
# n% t. Q, w [0 L4 {: [SEASON, 季节分析 ; ]3 M; R% L x7 l0 ^& M I
Second derivative, 二阶导数0 W& c+ C" c. k( b! Y4 q1 Z
Second principal component, 第二主成分
. j( E V' i! L" y8 R* lSEM (Structural equation modeling), 结构化方程模型 o8 k! B3 }# p% Y t r1 i L! _
Semi-logarithmic graph, 半对数图
, W! d t/ V! Q- w4 V7 i5 VSemi-logarithmic paper, 半对数格纸9 m" p+ N* X I$ }: Z$ Z0 Y
Sensitivity curve, 敏感度曲线
9 k! ?+ [1 m# [# E! |7 `0 OSequential analysis, 贯序分析" a- h l, l# q
Sequential data set, 顺序数据集4 ~( g: j6 P2 |/ {
Sequential design, 贯序设计
6 b4 _7 e I' [$ d# b; e8 iSequential method, 贯序法
& ~; c" L) k2 I' aSequential test, 贯序检验法# w" [( ^& M% X& a
Serial tests, 系列试验
N/ b% _4 X# s A2 P: eShort-cut method, 简捷法 7 H; _( f1 W2 }$ L
Sigmoid curve, S形曲线, L2 z- b6 n- P) H# v$ w
Sign function, 正负号函数
/ A) R- ~4 U9 I/ G3 ]! `Sign test, 符号检验8 m- b9 N! L* |2 x8 R9 s5 b5 \
Signed rank, 符号秩
; P2 i6 z6 m" I" m% `Significance test, 显著性检验
: S$ M4 X/ X% l6 P1 Q+ LSignificant figure, 有效数字
3 p) _) `: g( |' E1 T. I- t) \Simple cluster sampling, 简单整群抽样$ o# {; _( B: R, Y) \0 l E* D$ h
Simple correlation, 简单相关
* d3 N& G3 d# _5 D$ XSimple random sampling, 简单随机抽样
7 C/ D. S9 ]$ `! dSimple regression, 简单回归, L* \( H% T- c) d3 T8 o
simple table, 简单表
6 h& ^$ }' C# }9 ~$ d( S6 i& P3 \2 a: i VSine estimator, 正弦估计量1 V( o7 _3 }' B! K7 X7 ]
Single-valued estimate, 单值估计1 z# g* c+ `7 s# T; g, _: z( U8 ~
Singular matrix, 奇异矩阵; M6 c( r( P/ R0 `2 ]6 D) U* e
Skewed distribution, 偏斜分布
- ]& t a' C/ ^" q8 jSkewness, 偏度
" K6 v1 b8 b: o7 |4 }Slash distribution, 斜线分布9 Q# l, p& j; M+ Q1 \' F7 ]9 f
Slope, 斜率
5 o9 g7 N+ w" N& lSmirnov test, 斯米尔诺夫检验* Q( Q+ [% W, K% `/ N
Source of variation, 变异来源
9 F/ x( ?; a/ _8 ^" Z# w0 wSpearman rank correlation, 斯皮尔曼等级相关
: U# _# o4 ?- }& ySpecific factor, 特殊因子
( [3 q6 P7 J! L. Q9 {Specific factor variance, 特殊因子方差
' K2 [& J/ V9 C+ ]2 ySpectra , 频谱
& P+ v% J$ r" Z! `; L4 c: dSpherical distribution, 球型正态分布2 G: H! k8 M9 r
Spread, 展布8 a' t7 ^/ z( x. P
SPSS(Statistical package for the social science), SPSS统计软件包# `! ]+ k. E( y& B6 L* v! `
Spurious correlation, 假性相关! f3 g! W8 I. t, T
Square root transformation, 平方根变换
( X2 j# a1 w5 G! M x1 H4 aStabilizing variance, 稳定方差8 H3 M* @1 A, z+ c1 C
Standard deviation, 标准差8 G j. B1 M9 u! Z( U
Standard error, 标准误. i% A) k3 z0 A/ n* o# H. p
Standard error of difference, 差别的标准误' J& z: f. |9 ]) W1 s k7 ?7 S
Standard error of estimate, 标准估计误差
4 W3 F7 Y5 Z- I* q8 zStandard error of rate, 率的标准误 M" U- J- H# k) U9 m
Standard normal distribution, 标准正态分布
2 [2 u" G- H0 N/ s* Q- e) @Standardization, 标准化
# [1 L& F1 M( H" cStarting value, 起始值) v0 y& x& ]+ G/ j5 [- w
Statistic, 统计量3 T3 e0 N4 _+ v$ E) t
Statistical control, 统计控制
3 i. h2 a/ Z4 b" Y a7 ]Statistical graph, 统计图1 K' K7 g4 l( U+ z
Statistical inference, 统计推断
6 W2 n+ [2 K$ v9 h& YStatistical table, 统计表
! t3 H& a2 f6 S: e# T. `5 ]Steepest descent, 最速下降法8 b/ g, F0 T% A; W. A( ~7 F Q; C
Stem and leaf display, 茎叶图
7 l B" J |# q! t$ k. P8 _) u xStep factor, 步长因子
; `- h3 U, Q. O* `8 ^$ b3 }# M% J9 KStepwise regression, 逐步回归" U7 @2 _- j7 _) l5 b+ F5 ?
Storage, 存( ?" |" ` l T, x1 h5 y: @
Strata, 层（复数）! ?; R9 s- R) f) d1 V
Stratified sampling, 分层抽样9 S' X, I- g0 K$ a# z
Stratified sampling, 分层抽样
4 ^8 G+ x5 r( S+ o' j7 }3 Z' HStrength, 强度 e3 x0 V- j) P$ M6 q5 Q% q
Stringency, 严密性# K [8 k: H" Z* b
Structural relationship, 结构关系8 n# c; @3 p0 {
Studentized residual, 学生化残差/t化残差
Q6 i: {3 J# I6 {Sub-class numbers, 次级组含量& ^" H* }2 H; R' D) O m4 o
Subdividing, 分割0 K5 H5 H: X& S3 g! d6 _' m, ?
Sufficient statistic, 充分统计量
7 V& W7 n, ^7 h; I+ x' vSum of products, 积和3 V/ O9 s$ `3 Z G3 s
Sum of squares, 离差平方和
6 I, l g6 p9 D" C, R1 j$ dSum of squares about regression, 回归平方和: \5 G) x2 t; L; Z6 e
Sum of squares between groups, 组间平方和1 ~. k8 T( G# ]3 z
Sum of squares of partial regression, 偏回归平方和$ ]$ k; a. _4 E# O0 H
Sure event, 必然事件8 b7 E6 h0 S$ m0 i* f* ?# B
Survey, 调查
) d4 W* \0 ^" USurvival, 生存分析5 W: v' o) I' ]- G) {0 \
Survival rate, 生存率
: y2 _* Y8 b& Y1 q2 q1 n6 fSuspended root gram, 悬吊根图. D C; M2 R, t0 }, d
Symmetry, 对称
1 I/ M( ^/ l% g* @Systematic error, 系统误差* G; \) y6 f) [
Systematic sampling, 系统抽样
3 |" A9 }7 ~( S. p+ A$ D( T. DTags, 标签/ W8 m8 i$ \: T- ~- A0 v
Tail area, 尾部面积
' g4 Z5 h$ a) t: tTail length, 尾长6 c: Z0 ]; e4 `+ p; c% \4 {
Tail weight, 尾重
5 Z1 t( l) I) S3 N- WTangent line, 切线
8 O' z5 d- f: L" _3 O/ |Target distribution, 目标分布- J o+ M- m! V p' a
Taylor series, 泰勒级数8 B, X D; F0 \0 r- q3 ~! I
Tendency of dispersion, 离散趋势+ \+ v: U3 D+ [! Z1 f3 V0 U
Testing of hypotheses, 假设检验
2 [1 ~# K+ d8 a" {6 l2 [Theoretical frequency, 理论频数
) }9 ?3 n3 [ p: h2 u2 dTime series, 时间序列
9 Z) H. R2 n" L6 e. v0 ~8 VTolerance interval, 容忍区间! Z0 h8 r6 s# U& G) S4 d
Tolerance lower limit, 容忍下限
2 [* x# R0 ?: }4 K+ A5 u/ ]Tolerance upper limit, 容忍上限( ?$ V( N; Y8 ?& r0 |. q
Torsion, 扰率; T7 x0 Z9 @9 [) \/ q: M
Total sum of square, 总平方和
! w& G1 b( X/ Z8 c# bTotal variation, 总变异) {" o" H9 K* Y3 g# [! `
Transformation, 转换
# r% m$ w& i5 d8 i; R* jTreatment, 处理
9 [7 K. T: ?8 e5 b; yTrend, 趋势
! y& I0 K2 u7 e0 I" V4 ~" gTrend of percentage, 百分比趋势
0 p1 W; G( ?& C1 \# H6 @. h J5 R8 uTrial, 试验
9 F2 i- Z1 Q1 U9 a, i6 j! o; iTrial and error method, 试错法/ n& W: z y/ G2 z
Tuning constant, 细调常数
) h1 y, _9 u. l& z1 tTwo sided test, 双向检验
8 C- z# [ {" q( S+ t6 STwo-stage least squares, 二阶最小平方4 \+ Y/ F1 a) A8 ~: A% n
Two-stage sampling, 二阶段抽样
) H. D' m% V( p6 hTwo-tailed test, 双侧检验2 h$ k3 o% ?0 @$ V) }3 S3 T
Two-way analysis of variance, 双因素方差分析3 Y2 i8 ?. |! M; S" @
Two-way table, 双向表6 D! O" W. n }" P( z
Type I error, 一类错误/α错误1 y+ U0 S3 q1 f* V
Type II error, 二类错误/β错误* ]* x4 _* x) O) N( n
UMVU, 方差一致最小无偏估计简称
: q' c6 r# y/ G& i3 n+ U$ AUnbiased estimate, 无偏估计+ W$ }- P" [% M9 j. B; r; w
Unconstrained nonlinear regression , 无约束非线性回归
! a: T0 ^# U9 [! y# |0 [Unequal subclass number, 不等次级组含量7 h# _) i5 p6 k
Ungrouped data, 不分组资料9 c- @! O% t7 z' ?/ U
Uniform coordinate, 均匀坐标1 |% l9 i' m; o0 l' G
Uniform distribution, 均匀分布2 ?0 N! v# U L) R
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
5 z- Q6 V! N) D8 g1 _5 IUnit, 单元
& u( Y9 B! \3 q$ X8 }1 T DUnordered categories, 无序分类9 [) `4 B* d/ Q$ j* {# y
Upper limit, 上限
* m; u* G2 ]! W* V7 xUpward rank, 升秩
9 c8 D; C6 r2 kVague concept, 模糊概念6 N! o& Z6 d2 [7 Z
Validity, 有效性
3 V0 R; }8 `6 L! }VARCOMP (Variance component estimation), 方差元素估计
, i: z9 M4 X, O" bVariability, 变异性
$ X N) ~% K1 l) ]& NVariable, 变量* H+ X% \3 S L
Variance, 方差
0 i$ F( ^* x1 r0 w. J" nVariation, 变异" O' e* N5 E, G* A5 R
Varimax orthogonal rotation, 方差最大正交旋转
: u7 V, O8 e/ k+ j! @& F$ a5 c' @Volume of distribution, 容积% A) G u, D& X& @
W test, W检验
5 y) U% ~1 N; e" @$ w1 KWeibull distribution, 威布尔分布: z& B) Q, W: u+ T: F0 |4 W( z
Weight, 权数
. }4 N# D0 T2 }4 E0 yWeighted Chi-square test, 加权卡方检验/Cochran检验
" W8 m" y$ A5 A% D4 z4 R7 r/ [Weighted linear regression method, 加权直线回归$ G' ^2 Z: n) Z C/ z
Weighted mean, 加权平均数
# \7 e- Y# H. YWeighted mean square, 加权平均方差; Q z. w' p- ^. G3 T! \8 R# R. Z% v
Weighted sum of square, 加权平方和
' k% u& l+ Z5 N- `Weighting coefficient, 权重系数
! K2 ]1 q3 t, u8 S- uWeighting method, 加权法 $ c! @0 ?. l& ?4 b/ Z7 ^+ L B
W-estimation, W估计量
! `% S& _0 T$ g! Q7 pW-estimation of location, 位置W估计量
2 k0 @6 E9 N' R% vWidth, 宽度) P$ M8 ?4 L. Y+ C
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
1 F0 d- L. F- B: ]2 TWild point, 野点/狂点. V M: _. @: e7 m: C. R# f
Wild value, 野值/狂值/ ^+ q- `$ O3 c5 q' j
Winsorized mean, 缩尾均值
# O0 f# L7 A/ e9 ?Withdraw, 失访
; ]& E M0 r- b! K5 R" r0 A8 SYouden's index, 尤登指数6 m8 R y/ T6 \5 @" @* a: s/ g: V
Z test, Z检验3 a3 u+ d% m( s# t8 d1 a
Zero correlation, 零相关" z& \) g2 |# K" Q( w, b2 @9 p' G7 s
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
