|
|
Absolute deviation, 绝对离差; {# O# l+ H/ E6 o4 ]/ n. ^
Absolute number, 绝对数& ?3 j. Q3 _! ~* J" _
Absolute residuals, 绝对残差, P5 |# [& p8 G
Acceleration array, 加速度立体阵- `) v1 F4 s) o) H% d4 D& H1 p' e
Acceleration in an arbitrary direction, 任意方向上的加速度
( G4 _' y# I( r3 K9 N7 V6 T) JAcceleration normal, 法向加速度0 Z& {( n+ s4 d* v, @
Acceleration space dimension, 加速度空间的维数
9 z* e4 t4 ]3 B' V$ aAcceleration tangential, 切向加速度
0 K: j t4 y+ g& z: V6 xAcceleration vector, 加速度向量
! A% O! Z+ _) H0 IAcceptable hypothesis, 可接受假设7 t: g0 C0 M! E8 i+ n
Accumulation, 累积6 a& }+ m5 |2 @# h3 i1 `/ e
Accuracy, 准确度# h- f) C2 E3 F* W
Actual frequency, 实际频数& x4 k6 x; r* h& G" ~
Adaptive estimator, 自适应估计量1 b" k7 D3 U; \; C
Addition, 相加: t7 A* j( o6 U# o9 {
Addition theorem, 加法定理2 c7 e; F6 \; x2 `
Additivity, 可加性
# u1 E+ W) w" [9 _' H: O7 {Adjusted rate, 调整率
9 \1 a& r9 c5 D K. s8 l4 n, gAdjusted value, 校正值4 @- d# w' H3 N: h# N. i
Admissible error, 容许误差 p0 @* {3 `) A- G! F' N
Aggregation, 聚集性- z3 O$ B+ K* v6 [8 D$ F! D
Alternative hypothesis, 备择假设
# ~1 C( W; k5 P! LAmong groups, 组间
( ?. y; F$ k6 j1 uAmounts, 总量+ ?# c+ ^4 u: ^1 G/ p5 j5 p
Analysis of correlation, 相关分析
: b0 }) s1 P' C3 ?Analysis of covariance, 协方差分析 r1 f) |2 w9 ~! n$ w; D8 M" V
Analysis of regression, 回归分析3 m( l$ n* o" w6 T
Analysis of time series, 时间序列分析& z$ y/ e8 m7 p/ I( q3 O5 y7 _
Analysis of variance, 方差分析
0 u+ l% K" y* [% }- e# ]Angular transformation, 角转换& h% K* [9 y; Y! J( w8 ^
ANOVA （analysis of variance）, 方差分析7 H$ H, F, s, f, H/ [$ c- B/ O
ANOVA Models, 方差分析模型
; D) w$ c. l& j8 A) O/ QArcing, 弧/弧旋
/ X8 m3 }* N# hArcsine transformation, 反正弦变换1 e: f3 L+ v4 g: M/ f
Area under the curve, 曲线面积1 g+ V6 x7 ^' i. m s8 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
' t* H" R6 d, H2 p: K( iARIMA, 季节和非季节性单变量模型的极大似然估计 # J4 \6 b& m0 Q. L
Arithmetic grid paper, 算术格纸1 q' s! M! f5 u3 ?# R) u1 H
Arithmetic mean, 算术平均数% h2 \; L' b; f3 b9 P; H
Arrhenius relation, 艾恩尼斯关系, ]( t$ S2 x$ c1 J0 Z
Assessing fit, 拟合的评估& s) A/ x4 ~' r T( p
Associative laws, 结合律9 p2 T) y) T. M8 h8 E
Asymmetric distribution, 非对称分布
9 F! z. X* |' o0 x7 g, Y9 @/ qAsymptotic bias, 渐近偏倚
9 `! m% P5 u) {" a2 w. P, OAsymptotic efficiency, 渐近效率
+ M7 K O" F0 e. T+ GAsymptotic variance, 渐近方差9 w. J# \' b Q2 d$ ]2 w; f
Attributable risk, 归因危险度
* x m# q& o9 J- }Attribute data, 属性资料
) \- m3 u8 W. F0 x4 T- o. ZAttribution, 属性
/ t: c' g2 Y* ?# IAutocorrelation, 自相关' _, N/ Y- y& Y
Autocorrelation of residuals, 残差的自相关
& i; X o/ W$ u! H& W5 u/ o4 ~Average, 平均数
0 \0 Q$ F: j; p% p/ }2 O! hAverage confidence interval length, 平均置信区间长度
. v% w# o, s( w J/ ?Average growth rate, 平均增长率
; w4 J( H* }1 j; o$ Q2 C2 z/ \' L* aBar chart, 条形图7 x' `1 i& d l7 J2 U3 u
Bar graph, 条形图
/ z2 }# \- P: R" P. sBase period, 基期
# n2 C& v5 c7 R1 V+ y% e4 OBayes' theorem , Bayes定理
6 `. ]6 L1 `! f) Q9 q1 D9 n8 i$ hBell-shaped curve, 钟形曲线: N+ P* y# J! P" P
Bernoulli distribution, 伯努力分布 l$ c0 @: \9 [* b1 J0 k1 Q1 y/ ^; f
Best-trim estimator, 最好切尾估计量1 `( I% ]+ B [$ c) U+ d, V* o2 `
Bias, 偏性! y& `8 H r! m# R9 A& U/ T5 A, A" k; Y
Binary logistic regression, 二元逻辑斯蒂回归7 F* z3 k5 ^, z0 Q+ n7 A
Binomial distribution, 二项分布3 j5 w* p p, ?) t0 x
Bisquare, 双平方$ U0 z4 s0 z5 Y7 F% S( C7 q/ s" Q
Bivariate Correlate, 二变量相关
% g- u* @7 I2 h7 T% IBivariate normal distribution, 双变量正态分布
' Z1 n$ ?7 `" w# FBivariate normal population, 双变量正态总体
$ S; G& `$ B5 F# o6 Y; B! U+ }4 hBiweight interval, 双权区间
1 ]2 G( F2 h& [( F0 k4 j% s! M0 A- _Biweight M-estimator, 双权M估计量
8 Y% J4 f; h0 a7 a3 \Block, 区组/配伍组
3 y% P* p3 C& K$ gBMDP(Biomedical computer programs), BMDP统计软件包) t4 x0 |7 k) x6 @, o
Boxplots, 箱线图/箱尾图
& S4 G$ H* _5 |& l2 D+ O- k& qBreakdown bound, 崩溃界/崩溃点
) s, J$ l6 V5 {: DCanonical correlation, 典型相关
) q5 J& O# L3 o1 GCaption, 纵标目- }" }' @ x7 {3 h. P( F' l; d: C
Case-control study, 病例对照研究- q0 i: X( _% b- i C
Categorical variable, 分类变量% Y- Z+ t9 c( D" H) t
Catenary, 悬链线+ d0 q3 y% ~0 a4 F% S7 T7 C7 R
Cauchy distribution, 柯西分布
1 c+ D( v4 g2 B" u; j& R2 L5 }: CCause-and-effect relationship, 因果关系3 X2 ?. f5 [5 Z* G2 v
Cell, 单元5 _+ _0 \+ @( c; C) a9 Z
Censoring, 终检$ }& l' [4 G& g& M) w
Center of symmetry, 对称中心. ^2 ]6 l# W* `# I
Centering and scaling, 中心化和定标
! P" T* U. e; ?% F/ mCentral tendency, 集中趋势
# r5 w0 T5 [2 eCentral value, 中心值 t2 L1 G! T( [. @
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
; e$ T/ B) s, Y* e/ s8 B* FChance, 机遇
8 ?; C, O$ ]* v6 M1 U& eChance error, 随机误差
9 W- b$ ^* H" S7 d' s7 OChance variable, 随机变量
+ ~4 H+ u$ ]" @8 }; Q# I+ PCharacteristic equation, 特征方程' U6 Q" t0 U [) k; j
Characteristic root, 特征根6 a4 E5 W: v n! J) r- _8 z* Z
Characteristic vector, 特征向量2 ^* l2 ?& P: |& R6 U3 U- H9 @$ U
Chebshev criterion of fit, 拟合的切比雪夫准则" f& L$ e. X' s* @6 e9 ~
Chernoff faces, 切尔诺夫脸谱图6 E3 e+ j6 `) R4 h5 A
Chi-square test, 卡方检验/χ2检验
* ]4 y8 S ~: ?6 I% q3 d2 {Choleskey decomposition, 乔洛斯基分解
6 ?, i) S9 {( L& m% M( k* l! W6 s$ UCircle chart, 圆图
! \3 A! v# s) m; z/ U- D7 u& Q, vClass interval, 组距$ B. @/ l3 }) @6 H
Class mid-value, 组中值
/ j2 Q4 p; M8 q HClass upper limit, 组上限
! o! P3 T7 E' Y/ z2 EClassified variable, 分类变量$ c$ L3 w! j/ ]* y3 J
Cluster analysis, 聚类分析5 [: g/ X+ Z$ O7 g k3 @. z
Cluster sampling, 整群抽样3 u: A; |2 p8 O" _4 j$ |6 C
Code, 代码3 e- H+ y) G# r! X- X7 X2 `& p
Coded data, 编码数据
: m4 x' |. u' `( S9 x3 ?Coding, 编码
6 J* {8 Z" D& V' fCoefficient of contingency, 列联系数
+ f8 |6 Z0 h. y5 T8 g' d. s& OCoefficient of determination, 决定系数8 [& m9 a" A7 {6 i7 t' C
Coefficient of multiple correlation, 多重相关系数% Y" {7 X( ^2 y
Coefficient of partial correlation, 偏相关系数
: ^7 C( \& m+ w8 p; lCoefficient of production-moment correlation, 积差相关系数
, Z0 h7 i6 j7 N. n" A' x$ XCoefficient of rank correlation, 等级相关系数8 Q8 U1 X9 _/ J3 m1 f
Coefficient of regression, 回归系数
# {! K# O+ _' ^4 ^! i1 mCoefficient of skewness, 偏度系数+ d; c( m8 ?9 `3 _- L% q0 C& Y
Coefficient of variation, 变异系数
- L% F- \ r) p5 s6 q9 ^8 `: ZCohort study, 队列研究
- C, N2 h' x$ P" V, q' q w2 w; qColumn, 列) X# D j1 c8 d4 F# P( D+ q4 M
Column effect, 列效应 k& W7 B" l& ?- t( O5 |. ?
Column factor, 列因素* k% Q5 I: s- J7 D$ @9 Z
Combination pool, 合并
( s1 q) S1 u* g- S( sCombinative table, 组合表8 Y8 b; J; \1 K' c/ e+ G! |! _
Common factor, 共性因子) ?- W* h" w/ L; P5 v4 ]
Common regression coefficient, 公共回归系数
6 F7 K- `- J5 T, N2 q. LCommon value, 共同值
2 c6 _* X8 P3 b# t1 p ACommon variance, 公共方差8 Z: v# f9 d r" K6 V) g: D
Common variation, 公共变异
9 B" E+ ]! F( e- {Communality variance, 共性方差
+ R; S8 Q; ]* EComparability, 可比性
4 u5 ?8 G; `. q) M) gComparison of bathes, 批比较
0 M& D, n; `8 ?* \- ?+ WComparison value, 比较值, x/ }5 {1 J% a8 Y* d" o
Compartment model, 分部模型
M, \4 }+ B3 {5 w) u/ @- k7 u' ECompassion, 伸缩
?& i. y; c5 cComplement of an event, 补事件
; l- ~) c* ^2 L3 T8 ~0 o% gComplete association, 完全正相关 [: t% e8 h/ B; ?. _( k* X5 y* b* k
Complete dissociation, 完全不相关
9 Y! T: f- q0 l3 i# W+ tComplete statistics, 完备统计量+ F c' V% Y8 a
Completely randomized design, 完全随机化设计' b, }# f7 t! p1 V% u
Composite event, 联合事件) [3 u# z3 P" k1 M+ J& v
Composite events, 复合事件) V/ C) m. m' b' k6 h& p7 Y0 }
Concavity, 凹性- v% C9 o" U u
Conditional expectation, 条件期望
" r. d2 u, p' j; w" |8 c; N0 xConditional likelihood, 条件似然
: w; r5 L- y2 k v$ w8 KConditional probability, 条件概率
1 l& f5 P# q' W1 g/ e9 KConditionally linear, 依条件线性* E+ B$ W) [7 G' k$ l* U1 |
Confidence interval, 置信区间
' L8 s G; W4 |+ |( ^+ UConfidence limit, 置信限6 V( J3 d0 f! Z; I
Confidence lower limit, 置信下限
. I3 N/ a7 W: v- B, r. f% zConfidence upper limit, 置信上限! ~" V( n: F, O; [. e d+ V4 s; Q
Confirmatory Factor Analysis , 验证性因子分析
) j' K3 a6 D" f# d% Y1 F9 w" jConfirmatory research, 证实性实验研究
: i9 u% M3 l$ u$ \$ w. LConfounding factor, 混杂因素/ y5 B1 J; s( Y k
Conjoint, 联合分析; K. F# \ B9 U
Consistency, 相合性; `8 L0 G+ B* C
Consistency check, 一致性检验. Q% h2 p* V5 w
Consistent asymptotically normal estimate, 相合渐近正态估计
! B$ w* |3 g, o6 T% I; XConsistent estimate, 相合估计
2 `2 u5 N) T8 _! a+ T' Q4 x" ]Constrained nonlinear regression, 受约束非线性回归
' _+ u y) u! jConstraint, 约束
# j% i5 K, F* V9 aContaminated distribution, 污染分布
1 Z0 u- V% J+ u! V+ O/ AContaminated Gausssian, 污染高斯分布
2 A/ Q) E" Z [! \% P* \Contaminated normal distribution, 污染正态分布
6 J# g8 S7 E$ {* q {Contamination, 污染/ }' h6 I1 r. p, u# T8 D
Contamination model, 污染模型9 y$ R( i4 [, p7 c- @; ]5 q
Contingency table, 列联表
: r( Z' ^4 y: D$ CContour, 边界线
) d: G7 L) z: {; ?% i0 W UContribution rate, 贡献率
2 `* k) h+ x+ P' G. hControl, 对照( n' A6 p2 I, z8 g- A( @
Controlled experiments, 对照实验 @. Y# z* g! i, [! L
Conventional depth, 常规深度5 k0 n$ r; f7 u1 ?* I- [. ~
Convolution, 卷积8 ?6 \2 A F" k, \
Corrected factor, 校正因子* ?7 V. A5 u# F$ S" I3 U0 \
Corrected mean, 校正均值
- u$ w, j& c/ u7 i0 d+ vCorrection coefficient, 校正系数
* c4 U$ C, K* S4 L* g" @, D0 vCorrectness, 正确性
3 F. j D4 Q# gCorrelation coefficient, 相关系数$ l3 R9 n. K$ ?# j' l
Correlation index, 相关指数0 G: m, L+ m3 B) H( z% n
Correspondence, 对应
s/ G- k! g: fCounting, 计数
4 R8 o8 r3 U: X1 u; |9 oCounts, 计数/频数
( I! `2 |. }! X( _% hCovariance, 协方差
1 g5 a9 s' \ LCovariant, 共变
& K7 R o, l+ b: |: F {$ C3 W4 i7 s+ XCox Regression, Cox回归7 O. x+ w/ l7 ]
Criteria for fitting, 拟合准则% y4 {8 `% M" y- {* W8 q
Criteria of least squares, 最小二乘准则
- G3 M3 b$ \7 b; `. }$ o; X& zCritical ratio, 临界比
, v9 g" G4 W. o3 j3 c9 {Critical region, 拒绝域
0 ?4 V7 p+ c6 `- z+ r" R, G9 yCritical value, 临界值
* g. f' R: G% Q7 _3 LCross-over design, 交叉设计! {( b0 k- y7 C! V8 s/ T% u) M" ~
Cross-section analysis, 横断面分析' B5 n; K: \5 C* U* c4 F
Cross-section survey, 横断面调查* U0 R; @' ?' y9 y' B, p* I' s! B
Crosstabs , 交叉表 , d: S, T9 m; }
Cross-tabulation table, 复合表+ Y" a6 S8 Z- y+ o) H
Cube root, 立方根& w0 |( Q. ?) J; k
Cumulative distribution function, 分布函数, y5 O9 B% b0 \7 Y& t
Cumulative probability, 累计概率
+ e5 n% {6 v# I8 V* QCurvature, 曲率/弯曲
, @5 u0 G; y$ kCurvature, 曲率
8 k! L/ L8 B& bCurve fit , 曲线拟和
: W6 v+ U0 n0 ?- ~* ?% ?, MCurve fitting, 曲线拟合 P& H. ~+ ~1 V# R+ O2 L4 Z; g2 Y
Curvilinear regression, 曲线回归# g6 |! ^2 e( O1 L( L C: l
Curvilinear relation, 曲线关系
% N# P- g" d; c: XCut-and-try method, 尝试法
- M: ]1 p/ q$ D5 S" G; _) _' `Cycle, 周期+ H! O; f2 t. R, \
Cyclist, 周期性
6 r% O- R; {' W j9 G1 L' J7 `D test, D检验2 j) I# x5 ^. f* I# @% |2 V
Data acquisition, 资料收集" m1 C$ N2 Z+ H4 k T3 [
Data bank, 数据库
; W3 Z1 K. d4 W2 I5 l; qData capacity, 数据容量
7 }) i" R* f" `" jData deficiencies, 数据缺乏6 S; W" T; `* [8 ^5 c3 w
Data handling, 数据处理5 l- r }! c' j: R1 v
Data manipulation, 数据处理6 x+ q( _8 M, F) Y1 Q- y
Data processing, 数据处理; l( A/ }2 ^$ `; t
Data reduction, 数据缩减* I2 i3 }2 ?1 K1 s" c3 k: O
Data set, 数据集
# w# V2 u4 G! L, f+ [ ^. t7 JData sources, 数据来源
7 X8 s/ i5 @9 [3 r4 |4 n. K4 g( JData transformation, 数据变换- j, D, [$ Y2 Q5 S7 b2 u6 ^
Data validity, 数据有效性2 `8 S0 r- f9 J( ^7 q
Data-in, 数据输入
' h; ^# ~2 t% Y) Q$ }6 O0 VData-out, 数据输出
9 s$ J* d0 w9 u! w8 W$ u6 pDead time, 停滞期 ^% J# P6 ~/ ~" Y3 V+ g" b1 i! Y
Degree of freedom, 自由度
9 P2 e- d1 z3 ^2 S$ EDegree of precision, 精密度
2 t$ D: U4 P* I3 h6 eDegree of reliability, 可靠性程度8 O f, a5 | ~. S8 R
Degression, 递减
% B X; M3 A" CDensity function, 密度函数4 ~1 t" l9 E6 F7 N
Density of data points, 数据点的密度7 [9 n$ X( }- W9 i
Dependent variable, 应变量/依变量/因变量' t. ^ @) u' ]# R* n% T0 l: S1 Q
Dependent variable, 因变量
( [" |. F+ q* E! V6 b/ i! {Depth, 深度
4 ^, W& J# B3 t0 FDerivative matrix, 导数矩阵% w1 B- x1 I$ v. g
Derivative-free methods, 无导数方法* B: `3 T3 M! j9 K( Y5 m: Y
Design, 设计
$ m( [9 l1 h& R/ w6 ~Determinacy, 确定性
; V4 I5 H9 m6 sDeterminant, 行列式
' f9 [1 |, i9 S1 S6 `Determinant, 决定因素; N+ }: d2 ^+ \. }8 Q0 P7 Q
Deviation, 离差
1 ?, h" N7 Z/ j& [8 M; O( dDeviation from average, 离均差
1 g& S& X1 D5 l* c# D. T) `! k- nDiagnostic plot, 诊断图
@. \) L$ E3 q: S+ \* IDichotomous variable, 二分变量4 r+ z; `3 \; P
Differential equation, 微分方程
! H! X- i" v; u" [2 V7 V9 KDirect standardization, 直接标准化法
- Z/ _+ Z B- _! Z" g) ^5 \& HDiscrete variable, 离散型变量
7 c9 ]3 y% Z8 MDISCRIMINANT, 判断 6 ]% S7 g# ~- a! [) g- |! \& m! U
Discriminant analysis, 判别分析$ s$ \; S! e: ]$ ^2 l0 Z
Discriminant coefficient, 判别系数& W1 J0 q% g. H! m( s( p9 k$ u
Discriminant function, 判别值( e2 D0 |# r7 A, Y/ g; i- ?
Dispersion, 散布/分散度" |; }. c& f9 h* |" i% ^) ]/ N
Disproportional, 不成比例的
|# V5 u! Q) O6 d" I gDisproportionate sub-class numbers, 不成比例次级组含量
9 g5 m- G. B1 y9 gDistribution free, 分布无关性/免分布' U2 b6 U6 o" [) G! e
Distribution shape, 分布形状- [$ k4 S4 z- J. M
Distribution-free method, 任意分布法
/ C! K: O0 J! aDistributive laws, 分配律7 N7 p! S" K6 o* K2 |
Disturbance, 随机扰动项
! g; s* v. {# Y( I* l$ KDose response curve, 剂量反应曲线
* O6 d! q6 \/ F0 |, I) qDouble blind method, 双盲法3 p# T, l3 k( r5 {
Double blind trial, 双盲试验+ V9 V" j# `6 c& \2 h
Double exponential distribution, 双指数分布
/ y' P! C$ }' u) ^6 A) T& i+ ~/ xDouble logarithmic, 双对数
: U0 x* A" w. s3 \8 W+ a) N8 mDownward rank, 降秩
( M8 q! N/ [6 |# \$ d$ |" W' HDual-space plot, 对偶空间图6 G$ N q! c2 l* I. I' E4 J
DUD, 无导数方法
! {, ?2 A) M W6 q9 aDuncan's new multiple range method, 新复极差法/Duncan新法8 \: w6 Q+ A( R1 d4 t) q
Effect, 实验效应
) \% W: \# w8 \/ @- x( tEigenvalue, 特征值" @& Z ], `! R
Eigenvector, 特征向量
7 s: f6 h: ]5 T& c- F% g bEllipse, 椭圆
: P6 ~# \/ A: F+ s" C$ A+ rEmpirical distribution, 经验分布2 B# }6 c! {# m9 v$ ?8 R
Empirical probability, 经验概率单位
4 x7 F. p+ U6 @- Y) d; gEnumeration data, 计数资料/ @% g D5 T5 {3 N5 X) p# D( _
Equal sun-class number, 相等次级组含量" t9 V/ i+ {8 n$ k' Y
Equally likely, 等可能! z v5 Z6 X9 L: y) S/ U- C( F4 j
Equivariance, 同变性! X$ ?% `8 {4 @5 e/ h
Error, 误差/错误
5 j2 |: F$ `6 Q3 Z- UError of estimate, 估计误差# h" H% k% o- @- H& W, `
Error type I, 第一类错误
" X( S$ k% b1 h1 \+ b) Q* k) tError type II, 第二类错误' _' N B" ^0 }, O j
Estimand, 被估量
3 S# d" d& C h* `Estimated error mean squares, 估计误差均方2 J; U" K, C/ o( [+ I4 ^3 X
Estimated error sum of squares, 估计误差平方和
y# z1 N3 p6 N( |4 P8 |9 rEuclidean distance, 欧式距离
2 t5 P; P9 s6 D+ q2 CEvent, 事件
0 c, u1 s- g: U5 G" D0 o# E; O9 oEvent, 事件/ r! D/ d: Q( S/ A; ?" w
Exceptional data point, 异常数据点+ _& o- B# v+ U, J8 C! N$ v
Expectation plane, 期望平面
7 v7 ?( w# }- e, v5 y8 `: J" p' TExpectation surface, 期望曲面* \. }- a$ w3 V Q+ O; I+ E
Expected values, 期望值) E; j" l3 c- G1 L6 d
Experiment, 实验
/ c6 h3 r/ c: M* ?Experimental sampling, 试验抽样
|. c4 U- f7 T" hExperimental unit, 试验单位( v A9 B( k! a; k
Explanatory variable, 说明变量3 X* w4 ?% K1 o! J3 r* B) c
Exploratory data analysis, 探索性数据分析
( z2 a3 a4 u: p2 X( n3 tExplore Summarize, 探索-摘要' h" j1 @3 f ~7 x' c# H. h
Exponential curve, 指数曲线
1 G3 h( k" ?$ f# e" hExponential growth, 指数式增长
* A5 w) k! v3 f6 [( m- O. EEXSMOOTH, 指数平滑方法 - i7 P' M" H* k, Q' w
Extended fit, 扩充拟合4 z+ ~1 B( V% p% u' @
Extra parameter, 附加参数! ~0 F' C+ N& n0 E8 ^; X
Extrapolation, 外推法
- q4 e+ \6 I L& m/ ZExtreme observation, 末端观测值
5 j' D& [1 h4 b' IExtremes, 极端值/极值
& R0 ]3 ~: R1 P3 IF distribution, F分布4 | Q( e+ x- Q# L
F test, F检验
! ^* Q/ E. m, l: JFactor, 因素/因子* |) s5 v+ u/ W$ R+ Q
Factor analysis, 因子分析
4 M" W" y: @, q5 D1 E1 V6 w1 GFactor Analysis, 因子分析% G/ l5 T0 B/ H: g( Q8 M" y' A2 M, @$ N
Factor score, 因子得分 9 |( E1 k& W4 R, t/ E. J
Factorial, 阶乘7 ~4 V( e4 O3 c* l: E
Factorial design, 析因试验设计
/ a- c: k( m' \/ X# j: F) wFalse negative, 假阴性8 m ]& D# P; {6 O$ g! |9 V$ o
False negative error, 假阴性错误' N) h5 H# I( P
Family of distributions, 分布族
! g& ~1 l1 K7 \. u2 Q/ H# eFamily of estimators, 估计量族# W- I" y/ s. P0 f
Fanning, 扇面6 e- S: P% E" H2 D1 Q
Fatality rate, 病死率3 E6 J6 C5 {: u7 p: O
Field investigation, 现场调查
8 ? R% c" }% b! M2 q. ]* PField survey, 现场调查( g3 d. f( o! e
Finite population, 有限总体$ j6 B- W/ }4 P4 y( r. [& U
Finite-sample, 有限样本( F/ N, f4 {, O
First derivative, 一阶导数. \5 l3 I7 l: H2 H! u0 T
First principal component, 第一主成分
; H- a2 \4 h) t* ^% S8 w' |& [, JFirst quartile, 第一四分位数
1 [9 @* O+ N" i( K& d5 cFisher information, 费雪信息量
4 O$ \& n7 T% N5 [% ?* lFitted value, 拟合值( z; `' {$ W/ t) I8 S# k8 q% O
Fitting a curve, 曲线拟合8 n) W1 ?' O8 f6 r# t( l
Fixed base, 定基! v+ C! z ^- P: J
Fluctuation, 随机起伏* `! `7 {& x* i3 B2 W& B8 @
Forecast, 预测: g- i) v! x( K: S b. ~
Four fold table, 四格表
8 O n$ E% g0 E% Q% xFourth, 四分点
& Z; Z4 ~- s" Y, m) n( HFraction blow, 左侧比率
( [8 H6 }# i/ vFractional error, 相对误差4 b' W7 X: d- {% l+ o
Frequency, 频率
* _' w/ f6 x! E( b& H% ]+ JFrequency polygon, 频数多边图
% _7 ^, z# l& R# ~2 vFrontier point, 界限点
. K1 t0 `: \! X/ QFunction relationship, 泛函关系
2 j$ R# t: J$ @! }+ yGamma distribution, 伽玛分布
4 B- `" d" {# P$ T* u0 fGauss increment, 高斯增量6 V' m3 w* y) S7 q
Gaussian distribution, 高斯分布/正态分布; V! ?! `% N4 |* z
Gauss-Newton increment, 高斯-牛顿增量
6 o% A, O& K. y4 N6 FGeneral census, 全面普查 \+ e% [) H( q! V/ w, D# n
GENLOG (Generalized liner models), 广义线性模型 2 c3 s3 n& p5 \; h& o$ \6 x
Geometric mean, 几何平均数
3 C+ ^4 \9 o' X/ Z, U Y5 ]; k9 jGini's mean difference, 基尼均差* z U c2 \& h& X6 @, X6 p7 r4 G, G
GLM (General liner models), 一般线性模型
6 B& U6 j+ d, p; p; E. TGoodness of fit, 拟和优度/配合度& o$ r% B( R& A& F2 T# `& z
Gradient of determinant, 行列式的梯度. {. v' K8 V8 x: G) v; w
Graeco-Latin square, 希腊拉丁方 T) o* V; M+ D$ j8 r
Grand mean, 总均值& m4 C) M5 S8 r1 N; b+ m/ B/ b
Gross errors, 重大错误# P3 n3 h6 ` _4 j" ]$ g
Gross-error sensitivity, 大错敏感度' d1 h- ]2 D2 B) m0 H
Group averages, 分组平均
# V$ u# A, M2 u& iGrouped data, 分组资料
% t: |- ^* N9 h3 J$ }+ q9 OGuessed mean, 假定平均数( K- ?; O# u7 [* P" `4 P
Half-life, 半衰期1 k! u$ ^* M P% E" S9 r- ~8 L" `
Hampel M-estimators, 汉佩尔M估计量5 U, W' J/ i' s3 r
Happenstance, 偶然事件
7 d, _3 H _0 H: G# p# \Harmonic mean, 调和均数
& @$ Q3 B/ y3 S3 _) [8 o8 A- S8 ?Hazard function, 风险均数! T$ |2 l6 N! W* z+ W/ t
Hazard rate, 风险率& A) O" e/ W" I/ E$ j
Heading, 标目 1 V, {4 B& m \1 g' v. }
Heavy-tailed distribution, 重尾分布
; l- X/ ^( b7 ~2 F" B& ^* o; i. ^Hessian array, 海森立体阵& s9 l7 O9 {5 f G* V' r0 f
Heterogeneity, 不同质
. W; ?( _2 J5 x9 `( jHeterogeneity of variance, 方差不齐 : X6 X( l( r6 m8 j1 k
Hierarchical classification, 组内分组
9 W X7 s3 L" {Hierarchical clustering method, 系统聚类法- M* d9 \, [/ p! h
High-leverage point, 高杠杆率点
' i! U2 Z6 _* V0 T& XHILOGLINEAR, 多维列联表的层次对数线性模型; C. Y4 Z" R: P9 C4 R1 _
Hinge, 折叶点1 C, v" Y9 E6 h& n, Z; y
Histogram, 直方图
$ O, f$ i9 ?( c# S' v' f ~Historical cohort study, 历史性队列研究
7 I6 f0 N8 w7 oHoles, 空洞% x2 B4 `! D- N' r1 ^: H
HOMALS, 多重响应分析$ C) a1 M/ t$ v$ k" {
Homogeneity of variance, 方差齐性! t% N" C. l8 f2 r
Homogeneity test, 齐性检验
- J/ t$ _7 N- s$ _' h/ uHuber M-estimators, 休伯M估计量
4 y' u, m+ |" A4 ?3 v6 NHyperbola, 双曲线
$ v0 A: y% o% K0 Z% v* D1 Q1 bHypothesis testing, 假设检验
+ E$ b7 |8 ?7 EHypothetical universe, 假设总体
7 ]% m' T. D% a; LImpossible event, 不可能事件$ _) Y M2 U+ P- a$ a8 |3 w3 c
Independence, 独立性, j! H3 C, I- u5 V N
Independent variable, 自变量: R2 J9 ?2 f6 q
Index, 指标/指数
2 `$ k2 Q, M$ wIndirect standardization, 间接标准化法
" ^& \- m- r* j: a7 M1 R9 xIndividual, 个体9 U- b1 [/ B1 Z. v8 Y) R8 V
Inference band, 推断带
5 T, a/ E5 |! K. e, i) ^7 h# XInfinite population, 无限总体8 T1 d; H; e8 P' v. E3 m
Infinitely great, 无穷大
) \5 o, |0 }' _- G5 y" } mInfinitely small, 无穷小
/ h' o/ Y" }! H! }& L( [+ c* w( VInfluence curve, 影响曲线
/ Q2 E8 R6 D) dInformation capacity, 信息容量3 I1 Z; g. i5 n( |
Initial condition, 初始条件
g4 m) g$ ?: CInitial estimate, 初始估计值8 n$ a' a0 Q4 s' P+ F
Initial level, 最初水平
; Q, @1 t" k, N5 HInteraction, 交互作用5 ~% v9 G. J: ]
Interaction terms, 交互作用项
' Y3 I( z/ k* P& |- o& [Intercept, 截距& n v8 ^+ y& C
Interpolation, 内插法
* ]% ]: m7 L0 e ]Interquartile range, 四分位距
$ y% e3 _& S8 O2 G# k$ t8 ^; rInterval estimation, 区间估计- H4 I+ M: `1 ~7 s& {( _
Intervals of equal probability, 等概率区间2 X1 S- C8 a# A) q3 _
Intrinsic curvature, 固有曲率
, q9 ^5 Z; Q5 S% f* s+ S8 h6 C NInvariance, 不变性
- E) @$ b) y7 R3 dInverse matrix, 逆矩阵& Y! t( W% j7 A) E( B, j/ h! I8 F
Inverse probability, 逆概率
3 E8 O: k$ t, E1 M* W: V9 ?* N2 RInverse sine transformation, 反正弦变换6 M* P4 y* J1 C- c
Iteration, 迭代
6 T7 c; N, f0 P" @! D5 fJacobian determinant, 雅可比行列式) A- d$ |' H" }, B* s; d* n
Joint distribution function, 分布函数- b. m% X @ ?, R, c
Joint probability, 联合概率0 q9 t6 b% s: n7 ~6 `0 c; o; O+ q
Joint probability distribution, 联合概率分布
, f5 \% G8 K1 v# `0 C% ~! qK means method, 逐步聚类法. w X' ]: |& C7 [" G
Kaplan-Meier, 评估事件的时间长度
- C' r- C' H$ i6 b' S: VKaplan-Merier chart, Kaplan-Merier图8 C: n4 o* z& `8 R% |
Kendall's rank correlation, Kendall等级相关5 A: l' X2 ` v7 h1 v
Kinetic, 动力学: M. l( U! v1 j2 ]
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
, g& s. Z" P; y, F8 w Q. J6 }, @& ?Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
4 [( [2 {2 K- D: FKurtosis, 峰度
% Q8 c: n! B) Z1 A$ wLack of fit, 失拟
$ P) ]* `5 \$ \' Q/ X0 H, z5 X, r) iLadder of powers, 幂阶梯1 Z8 q; C( ?, R! o
Lag, 滞后* _( A2 H3 b2 S) q# t! u9 `
Large sample, 大样本
+ b+ ?9 X n* f6 N3 CLarge sample test, 大样本检验3 g$ P9 Z2 S; o5 h4 `2 V* g) K+ z
Latin square, 拉丁方: j! Y0 n. R; t0 q6 w
Latin square design, 拉丁方设计8 I) L* |7 o8 f* o3 t8 \ B& l
Leakage, 泄漏
2 n7 ~; f% p. L" gLeast favorable configuration, 最不利构形" y: s$ h7 e: r3 W
Least favorable distribution, 最不利分布
0 M; F& B, E( @2 Y* o5 a/ wLeast significant difference, 最小显著差法
/ b3 E+ \$ s& U& k5 l+ z, oLeast square method, 最小二乘法
9 a6 W4 S. \7 r) `4 y6 c# rLeast-absolute-residuals estimates, 最小绝对残差估计
0 l! { q! E% A# iLeast-absolute-residuals fit, 最小绝对残差拟合
8 X _" a. ?9 [7 C8 zLeast-absolute-residuals line, 最小绝对残差线
; j. V2 d4 j4 u8 E) \Legend, 图例
! P9 Y$ G; b* T7 ]6 |L-estimator, L估计量
( n4 r- R1 D" X! } m0 Q [L-estimator of location, 位置L估计量
. V1 P. }6 o1 B0 a* WL-estimator of scale, 尺度L估计量, B$ C, A, `& I, m3 N# B! g
Level, 水平% K$ y# L" X) l( [% M" {
Life expectance, 预期期望寿命& U2 M0 U: H+ k) F/ J! |/ O& S: @
Life table, 寿命表( k6 R2 `3 `. h7 I2 R
Life table method, 生命表法
' }2 {2 D* z$ D) h7 CLight-tailed distribution, 轻尾分布
5 T# A, p5 @" i _; {, NLikelihood function, 似然函数: w0 b5 x) n- }# C
Likelihood ratio, 似然比
. O" L }9 t$ {+ Q; k. r7 Aline graph, 线图2 s* j# V. a, X; y9 Z' t5 m
Linear correlation, 直线相关
# G/ L. d) \( q, k& @) p! GLinear equation, 线性方程0 p' ^% I. V% L# @/ j5 P3 y
Linear programming, 线性规划$ |$ C/ u2 e9 U% }; Y
Linear regression, 直线回归# o' d& o& G/ a, q. ?
Linear Regression, 线性回归' G7 B. M4 z: z
Linear trend, 线性趋势/ O1 i# x' V2 p# Z6 ~! M, X
Loading, 载荷 " J5 j4 i$ N) Z' j
Location and scale equivariance, 位置尺度同变性, M& n% a9 Y1 W# S
Location equivariance, 位置同变性* g7 R' O$ k/ ]' o# ^
Location invariance, 位置不变性: n/ L3 w- K8 y# h3 ^( y9 c
Location scale family, 位置尺度族
0 M d9 n4 j! n3 k* `9 l- HLog rank test, 时序检验
" T: a7 p2 R! j& ]) U: U9 I# O z8 a: jLogarithmic curve, 对数曲线2 ]) D. U: n/ K; X: B; Z4 N- L
Logarithmic normal distribution, 对数正态分布
9 G: f& k3 K, F8 p8 ALogarithmic scale, 对数尺度1 } K* W; G$ x3 Q
Logarithmic transformation, 对数变换
; t- D* ?$ _. x( T. e0 jLogic check, 逻辑检查% ~) ~4 v: z9 m' s1 U: j
Logistic distribution, 逻辑斯特分布, I& k2 Q/ T- W4 ]/ t+ [
Logit transformation, Logit转换
. G) i X0 m) v# [ CLOGLINEAR, 多维列联表通用模型
- g; w! I, T4 ~Lognormal distribution, 对数正态分布1 e" M. i0 [3 a' ^7 a4 A. a- Q: b! N
Lost function, 损失函数
; z: Z, B4 f; U X' ]/ H$ l8 BLow correlation, 低度相关
. ^! Q0 w9 [; U3 @! JLower limit, 下限
. p5 B) r( v" d' A8 rLowest-attained variance, 最小可达方差
1 X, H* }2 C0 d6 S1 M) CLSD, 最小显著差法的简称1 \0 ?% v! X7 r
Lurking variable, 潜在变量
* U* L, i" Y) v4 y: P9 y7 ZMain effect, 主效应; @2 B( ^( r3 V. P) ]) y, m
Major heading, 主辞标目; P' m1 f: e! w0 X' f
Marginal density function, 边缘密度函数5 U- k( G8 a* e' u
Marginal probability, 边缘概率2 C+ m; `4 I4 ^, I4 H
Marginal probability distribution, 边缘概率分布# V5 U$ J- B6 Z. g2 q/ M
Matched data, 配对资料
, d$ ` c, s+ L$ q5 i1 |4 {" TMatched distribution, 匹配过分布1 F0 W. }$ Z5 a2 D k! Z8 M# u
Matching of distribution, 分布的匹配/ B; X, Y+ H1 m7 c4 M: X8 E
Matching of transformation, 变换的匹配
3 G( K: I: k4 a* E, _* mMathematical expectation, 数学期望6 o" x2 ]) M i1 ?" b) A9 \4 K
Mathematical model, 数学模型
@" m+ W9 a% c7 ]# T% M fMaximum L-estimator, 极大极小L 估计量
# w' i0 z6 J4 ]5 C; \( t& j. IMaximum likelihood method, 最大似然法: c2 D4 A* Y& e: s- x" z
Mean, 均数5 T) d3 t5 E2 T$ u+ A
Mean squares between groups, 组间均方
! [1 w2 c# }, k( i$ A; C( n' rMean squares within group, 组内均方% t8 B- N( u- ?; I" a
Means (Compare means), 均值-均值比较
1 Z- j8 z/ P5 Z# nMedian, 中位数 L8 M1 j! d+ i) {" C+ m
Median effective dose, 半数效量5 Q7 [0 n7 O( b1 F. n* @
Median lethal dose, 半数致死量+ h- X0 E- [( e
Median polish, 中位数平滑% X, V, ~" a& t* M" V# g
Median test, 中位数检验0 q) G, H t+ d3 Y' l A3 q( u
Minimal sufficient statistic, 最小充分统计量
1 \6 x+ Q4 {( O- u; g+ J' ^Minimum distance estimation, 最小距离估计
3 n* Y8 c) X, n: l' mMinimum effective dose, 最小有效量3 g7 y- J- K, f* \7 G, }/ h, z
Minimum lethal dose, 最小致死量
$ a- Z. }4 }* J/ e. N. oMinimum variance estimator, 最小方差估计量
- K+ Y9 h/ l' B1 g: }MINITAB, 统计软件包
4 ~, A% ^+ F9 z; Q3 V; ?Minor heading, 宾词标目
y/ a7 D) C' v& _3 GMissing data, 缺失值
+ `+ a. V+ B- z2 n7 ~5 LModel specification, 模型的确定* b" S5 d% X9 T
Modeling Statistics , 模型统计1 z' t, f+ B. h v
Models for outliers, 离群值模型$ z7 n- U: _2 h7 \" Z( [/ m
Modifying the model, 模型的修正
/ L- t% y @+ _ c8 t% i+ aModulus of continuity, 连续性模3 O( b! X$ R4 U2 U( o$ a1 F) V
Morbidity, 发病率 . @- S' H! ^# E: l3 U
Most favorable configuration, 最有利构形 B" Q0 J7 k7 K0 T, h6 ?
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
: [0 R+ X: |3 ?& v0 \: w; R# j8 q- BMultinomial Logistic Regression , 多项逻辑斯蒂回归
+ F+ I" f) U- ]6 V. r: KMultiple comparison, 多重比较3 q7 V! z% b1 c8 R8 t* c
Multiple correlation , 复相关
! j$ g4 }& w9 v5 z9 dMultiple covariance, 多元协方差' b K( X9 a2 E6 y B" ?; |! c
Multiple linear regression, 多元线性回归, ?7 |/ S+ t, A3 B* e- a5 P
Multiple response , 多重选项' {* a# f9 s' Y; O4 H# b
Multiple solutions, 多解
9 s1 F7 g8 f3 k) ^Multiplication theorem, 乘法定理* z7 q* S9 m' t4 }! ` w/ C% |" B9 X
Multiresponse, 多元响应6 X5 e B# d" t: Y W
Multi-stage sampling, 多阶段抽样# c9 j# x8 {+ n: n
Multivariate T distribution, 多元T分布* U8 n! e6 m3 k/ M! g
Mutual exclusive, 互不相容
. v7 C/ Y& a* O8 U; |* gMutual independence, 互相独立
& ~) a9 Q. c* u: s3 I( ]Natural boundary, 自然边界" F. f( ^1 D/ h
Natural dead, 自然死亡
% @0 I8 `4 Y/ A9 c: r9 S# i* I1 gNatural zero, 自然零' V5 I1 v4 ~/ b4 F, q# l2 \1 A I) R0 e/ O
Negative correlation, 负相关
/ A$ K; u- l/ D8 mNegative linear correlation, 负线性相关
9 X7 r1 o$ i* FNegatively skewed, 负偏, i* C" t3 q; T; ?, Y# W' e
Newman-Keuls method, q检验, X/ D4 O7 X7 W: f0 j8 v
NK method, q检验8 R& K; Y& n8 s0 ?$ ~$ s
No statistical significance, 无统计意义
, V7 V* ^6 {7 I9 v1 j* PNominal variable, 名义变量$ S( }- A' F1 H& _9 ^* h2 _7 G% D
Nonconstancy of variability, 变异的非定常性" X( Q$ m( f: h& J6 }- ]
Nonlinear regression, 非线性相关$ `& v3 M+ i0 c
Nonparametric statistics, 非参数统计1 f( d9 r( _" s! _
Nonparametric test, 非参数检验
6 O# M! C7 ]0 qNonparametric tests, 非参数检验2 n, S8 x; b% ?& J A7 b" V% N6 @% w
Normal deviate, 正态离差
+ Q% Z. k1 r, PNormal distribution, 正态分布8 K' }2 P" s7 J2 {
Normal equation, 正规方程组. }5 p* E0 y z: K
Normal ranges, 正常范围3 C% Y: z- b! E2 B% ]; d
Normal value, 正常值
0 F X# P ]1 [+ Q4 G8 FNuisance parameter, 多余参数/讨厌参数
& Z2 Y- r# n6 P/ M0 _& V6 vNull hypothesis, 无效假设 ! F& H4 B, t" P6 R1 l# E/ @) O
Numerical variable, 数值变量
) }7 }) i Y3 b+ c1 j0 \Objective function, 目标函数& S7 F0 m' @. m3 @
Observation unit, 观察单位3 Z, t9 Z% q( Z# F; u9 }4 m
Observed value, 观察值
! ~4 Q# g& R! e4 i: x. COne sided test, 单侧检验
* d# q& F! p( t. BOne-way analysis of variance, 单因素方差分析
' x4 N. Y+ s# Z5 Q% O+ [% R4 {Oneway ANOVA , 单因素方差分析
4 l% V5 }6 i5 s5 n' sOpen sequential trial, 开放型序贯设计. n" p6 |: u' e8 w* V6 D
Optrim, 优切尾2 b! U* a4 R4 m* [$ _/ y5 `; K
Optrim efficiency, 优切尾效率* r) B! u7 \. t9 {* n: `/ A
Order statistics, 顺序统计量
( `( G: r# W9 K- hOrdered categories, 有序分类3 X6 M# {. J, R0 Y) k2 |8 w* W3 X
Ordinal logistic regression , 序数逻辑斯蒂回归+ [; S, M- z h
Ordinal variable, 有序变量: i+ h& f% z% y' C5 ?
Orthogonal basis, 正交基" w5 R6 E; r3 G9 @; Z
Orthogonal design, 正交试验设计
6 ]5 Q/ \' q( V% n( N. m- wOrthogonality conditions, 正交条件
$ b& Z3 R/ I3 wORTHOPLAN, 正交设计
/ Y$ m- f1 z6 d' ^2 h' FOutlier cutoffs, 离群值截断点" i) `) R! e% A+ ?) A# I
Outliers, 极端值
' t2 f' F; E: y8 w- X6 GOVERALS , 多组变量的非线性正规相关
: M( T7 L( e6 {: ?Overshoot, 迭代过度
0 Y# k2 X! X* M" P# H5 f0 {Paired design, 配对设计6 ]) ]* K2 P7 R3 Z# p; X. J
Paired sample, 配对样本$ ^6 c: h Y& E% J2 b, Q
Pairwise slopes, 成对斜率
- Q8 |3 j' v2 G9 P: C/ yParabola, 抛物线
8 X" ^7 T4 ~# @& t' B }Parallel tests, 平行试验( E* o! i0 {% |+ G; c9 Z* r
Parameter, 参数
1 C) c8 K7 I% NParametric statistics, 参数统计
. S3 Y; H; O$ \( JParametric test, 参数检验
! {) f/ B8 p4 W# o% n* ]6 }' Y5 jPartial correlation, 偏相关. m" U$ { H6 ^$ }. U0 P
Partial regression, 偏回归
0 G! T3 L2 u% r) R4 h$ |Partial sorting, 偏排序0 p6 X* G/ y' w9 P. a2 ?& z
Partials residuals, 偏残差
g3 d3 y. L8 v. [) hPattern, 模式" N' r2 [ u- s' d: M2 l+ V* B
Pearson curves, 皮尔逊曲线
' T) g$ s1 I7 f" F0 I* sPeeling, 退层0 ~& ]1 s" F0 {7 s
Percent bar graph, 百分条形图/ e! V! ?) c4 j4 K
Percentage, 百分比
5 v9 h1 m' ^" i( P ePercentile, 百分位数2 ~4 H: l$ q. U$ n# m
Percentile curves, 百分位曲线 |- @: W7 v0 P& ~# Y+ k
Periodicity, 周期性
9 S* \, Z2 M- d# Q1 {5 QPermutation, 排列6 q* m* s% {1 e2 C+ A
P-estimator, P估计量
, Q' i. x% i& M6 [8 d$ L0 zPie graph, 饼图
. Z: W; A* j3 ?+ I2 S9 |Pitman estimator, 皮特曼估计量
' L$ G) {2 B, e2 pPivot, 枢轴量% h" Q8 h0 }1 G
Planar, 平坦
# a8 d, X# m& a; ]$ QPlanar assumption, 平面的假设3 G9 K+ w3 I9 l
PLANCARDS, 生成试验的计划卡
' f* b t p* v- wPoint estimation, 点估计0 X* k+ g/ B, Q$ e
Poisson distribution, 泊松分布8 g! Q0 A- c9 b+ w% U- E
Polishing, 平滑+ e; m! Y0 o V2 }/ u4 Y6 A" V M$ c
Polled standard deviation, 合并标准差/ M1 f% J+ a8 d
Polled variance, 合并方差
- ?/ y" O9 _! E- l2 C) u- IPolygon, 多边图+ k A; n& u' ]3 q" s
Polynomial, 多项式
. C" N v: V* d) |' `9 ]Polynomial curve, 多项式曲线
- R3 J% j/ h9 pPopulation, 总体
5 Q; U& \/ e$ c7 ~# UPopulation attributable risk, 人群归因危险度
9 ]& I0 C& y; @' N' r+ p2 }3 k0 r5 PPositive correlation, 正相关% v: ?6 W3 g4 ], T! H7 g
Positively skewed, 正偏
( l- P k. s) lPosterior distribution, 后验分布
3 }0 A. {2 r" [8 T6 [Power of a test, 检验效能( d. S9 ]' A% j
Precision, 精密度
$ O+ v, A! x1 g0 {) S0 q3 h$ w$ pPredicted value, 预测值
# N& Y: i, G1 Q7 h# o SPreliminary analysis, 预备性分析 w4 B- [: ?8 V8 W
Principal component analysis, 主成分分析0 F" [2 A0 w% j) I+ f
Prior distribution, 先验分布6 E3 l- ?% t* U
Prior probability, 先验概率
3 m. e& E4 c8 b0 P' V0 qProbabilistic model, 概率模型. M. f8 H* [' o$ g9 z1 X* y
probability, 概率3 B1 A1 T6 h. I# Q; j
Probability density, 概率密度4 H+ g+ z$ B' v8 o& Q
Product moment, 乘积矩/协方差+ ]4 z k* O- D7 a) M
Profile trace, 截面迹图$ S2 |: g6 n( X, X/ p- J' m/ ?
Proportion, 比/构成比
- N2 J: i+ W2 V" ~3 h6 FProportion allocation in stratified random sampling, 按比例分层随机抽样
: E/ {3 |8 b7 A# I" }Proportionate, 成比例$ \6 U- R9 P# P
Proportionate sub-class numbers, 成比例次级组含量3 o ~9 v# @: a5 m8 E) h
Prospective study, 前瞻性调查
2 z: n5 p z3 U. f4 R3 xProximities, 亲近性
' }( r" p- z- A" k5 H. t- ePseudo F test, 近似F检验: i7 r) n& J. j5 L' _, N- k5 T! `+ i4 k
Pseudo model, 近似模型- E7 K7 @+ m4 _: j* l
Pseudosigma, 伪标准差
& h' V, h9 S, j* f& F7 Y; r* N: x1 @Purposive sampling, 有目的抽样
0 ] {. ]$ n. ?. u$ H2 x- z& d, PQR decomposition, QR分解9 n+ E$ @- y. Q4 ~( n% R" G% D8 P! o* |
Quadratic approximation, 二次近似- C. V1 c2 j7 p/ V
Qualitative classification, 属性分类1 [4 y& v- ~+ J( [6 V7 T
Qualitative method, 定性方法" y+ }1 O1 \% V7 Z1 F: a$ X& W
Quantile-quantile plot, 分位数-分位数图/Q-Q图
5 T( _7 X# y/ K1 I$ UQuantitative analysis, 定量分析
9 I8 t( h7 n+ \/ E1 `Quartile, 四分位数* U6 f5 L6 R2 n, {$ k0 a7 m
Quick Cluster, 快速聚类2 a- |2 l) K- C7 I
Radix sort, 基数排序
6 I: H/ b- |: s( e( t* y; cRandom allocation, 随机化分组
. C7 V4 D- H9 I, `; F; _Random blocks design, 随机区组设计
9 ^' B6 _3 Q# b* L/ t- g$ f7 WRandom event, 随机事件
% Z! O' L; f/ [. s# t$ m) zRandomization, 随机化& [% Z4 `4 b* X* a8 e' v/ ^4 N
Range, 极差/全距
/ u5 A; i8 u# ERank correlation, 等级相关
I/ _5 u# q1 l7 x- ~) XRank sum test, 秩和检验
; X2 b$ m- ?! RRank test, 秩检验9 m P" E( e2 G. `$ d s& p: O& O* D
Ranked data, 等级资料1 }9 I" _* I* t! I
Rate, 比率& m5 I; K2 _% s6 f# W: q
Ratio, 比例: u+ I* ]& Z. W& T
Raw data, 原始资料
0 R* [9 j8 g, z) |; XRaw residual, 原始残差+ B/ |9 y" W2 C4 Z* R
Rayleigh's test, 雷氏检验' ]2 e& x2 [/ [/ f+ c+ w
Rayleigh's Z, 雷氏Z值 0 \% r/ m w4 h2 x
Reciprocal, 倒数
! V& A" ?( J: u+ O: wReciprocal transformation, 倒数变换
& x9 g5 ^% J7 Z( ?% h1 k% ORecording, 记录+ p1 s$ W" B$ |* ]+ b1 K8 y
Redescending estimators, 回降估计量
& s4 J4 X; Y% ?, x" D1 w/ w. bReducing dimensions, 降维. i0 ~+ i/ S# B8 u' V
Re-expression, 重新表达
1 V: E0 y$ c" h. K3 MReference set, 标准组
4 M) [8 Y; [* `8 m- h2 [. J, BRegion of acceptance, 接受域
' Q- C( j9 o8 qRegression coefficient, 回归系数; P6 T5 X% N) Q! G% ?0 Q
Regression sum of square, 回归平方和
. e9 @7 j4 a: d( KRejection point, 拒绝点1 j5 x+ G8 p! Y. |0 _0 D
Relative dispersion, 相对离散度
. G" _4 n/ q" C0 q) y3 KRelative number, 相对数 C" F+ p. S5 X2 n3 x
Reliability, 可靠性- U( r# Q& b f: ` G# N9 _
Reparametrization, 重新设置参数
# a; _) g T0 [% tReplication, 重复* v2 b# J* |1 F8 |- m1 d8 }
Report Summaries, 报告摘要+ B) _ p& g- T; f5 N0 _
Residual sum of square, 剩余平方和
, {" D3 d5 n$ G9 gResistance, 耐抗性
0 Q2 `' I3 t) `! i8 {: zResistant line, 耐抗线+ Q' f! B5 V& p4 ]) c
Resistant technique, 耐抗技术7 t* u5 a( m P5 Z/ {. z0 x( J
R-estimator of location, 位置R估计量
6 }+ s6 u2 V7 UR-estimator of scale, 尺度R估计量
5 Q" k* q. V' T2 u2 Q( mRetrospective study, 回顾性调查& M1 _+ l5 N1 C& c: i: ~
Ridge trace, 岭迹5 c- `) u8 h! O% h
Ridit analysis, Ridit分析2 Q+ J0 _4 f6 D! t
Rotation, 旋转
) ^4 P9 q$ O# u2 Y$ C" H3 cRounding, 舍入
5 m* Y9 l) _% s3 l, I7 ~3 S% s# |Row, 行
' D7 B' E- R' r- ?/ x, q2 ?Row effects, 行效应
) k7 d$ E$ k5 B: z7 `Row factor, 行因素
' h( g4 \ E* u8 U( M4 w& a# V0 QRXC table, RXC表
& V7 E& Y# ^7 L% W" g2 }4 x mSample, 样本* t8 d1 p% n* k/ ?9 p% n
Sample regression coefficient, 样本回归系数- A- [7 F# K" f2 f
Sample size, 样本量
7 u# B! O7 F" w& dSample standard deviation, 样本标准差
* n5 H7 L; d& \8 sSampling error, 抽样误差
- Z% C0 H" @* B2 k. aSAS(Statistical analysis system ), SAS统计软件包: P& O1 W$ n( D" A
Scale, 尺度/量表* @3 v {) _( o2 H5 p& \
Scatter diagram, 散点图, R( n/ a/ K) I
Schematic plot, 示意图/简图6 j1 v) r4 o) V* J* {
Score test, 计分检验
" A1 l+ I9 E9 kScreening, 筛检
7 A/ m7 R! F' g0 j) P0 ]SEASON, 季节分析
r" q: r' o, z) e. J. w6 y0 M$ }Second derivative, 二阶导数
" u" J+ ?0 M4 j4 H, Q% GSecond principal component, 第二主成分
7 }. `, M/ {- x6 a6 S) }. qSEM (Structural equation modeling), 结构化方程模型
1 N, c! M+ A" U& u3 e6 PSemi-logarithmic graph, 半对数图, r. i! I9 H% c* C+ G
Semi-logarithmic paper, 半对数格纸& i0 v- w- {; ?$ V- o
Sensitivity curve, 敏感度曲线# V5 R8 J' i- u8 I
Sequential analysis, 贯序分析
" q+ g1 l7 G2 cSequential data set, 顺序数据集
5 q6 \% O8 G% `9 }, K) ?# W/ R. v! W" `Sequential design, 贯序设计1 Y9 m1 n; D( `2 q% D
Sequential method, 贯序法) z3 k1 W" ?, r: V9 O4 F- V
Sequential test, 贯序检验法1 N0 S8 Z8 d% p; Q. N: [* F
Serial tests, 系列试验7 A5 x/ {) A8 i- j. G1 ^+ X
Short-cut method, 简捷法 * `# Q$ {: E8 `) d
Sigmoid curve, S形曲线+ V( O3 S4 K/ Z
Sign function, 正负号函数
- i$ V$ H1 t1 {- G" Y; M9 NSign test, 符号检验8 L* y. [# t1 S5 a8 R& ?
Signed rank, 符号秩: V0 l1 Q9 F# Z7 c) I3 d
Significance test, 显著性检验6 q- |# }* I8 k4 u
Significant figure, 有效数字2 x' Y6 U7 V" R4 l1 t9 q
Simple cluster sampling, 简单整群抽样6 m8 g7 `* h. Y
Simple correlation, 简单相关
! b. w i) t5 R x# q- ^Simple random sampling, 简单随机抽样1 w4 d5 s$ b" b# H- Z: J" e
Simple regression, 简单回归) D6 b, D6 Q8 X# l) Z
simple table, 简单表. }4 {) j$ q$ O3 G5 V7 T' `
Sine estimator, 正弦估计量) H' J/ A' _( f+ c d
Single-valued estimate, 单值估计
. i, m- y6 p- R' G; W5 lSingular matrix, 奇异矩阵
/ m( L9 ^1 q0 C5 _! B- gSkewed distribution, 偏斜分布; r: h# N( f$ T" K
Skewness, 偏度! k- ~8 e' y4 b
Slash distribution, 斜线分布& J, O. e2 l3 y! S$ ]
Slope, 斜率
1 P8 r1 Q' C! E* L" ?" pSmirnov test, 斯米尔诺夫检验
' { j \; ~ E- i/ vSource of variation, 变异来源
1 l: `' ~' n: q: }1 j1 O5 U; @Spearman rank correlation, 斯皮尔曼等级相关
; W1 ~% e/ Y, ~. D6 V: PSpecific factor, 特殊因子# f/ m _9 O, ~; y; Y5 u- \
Specific factor variance, 特殊因子方差
8 U/ L; N8 w3 v+ h+ _. RSpectra , 频谱
- D* L9 K7 V) b Q* J3 d* tSpherical distribution, 球型正态分布
% n3 J- ` D5 c0 I+ w- k tSpread, 展布4 [7 o+ O) H- q$ w
SPSS(Statistical package for the social science), SPSS统计软件包! ` C( W( W+ Z: q7 R
Spurious correlation, 假性相关
( u6 g, S$ t1 tSquare root transformation, 平方根变换
6 ~8 S* T! h$ Y7 g. l0 |. XStabilizing variance, 稳定方差4 W4 u) y. v0 A9 e8 R0 S
Standard deviation, 标准差
- ~& ?; F4 W7 G2 u9 D, G+ TStandard error, 标准误
) _3 a! S( W( H5 R( ~% E: }Standard error of difference, 差别的标准误3 D4 {( z8 c" I- e8 h2 C7 A
Standard error of estimate, 标准估计误差7 Q5 U2 J- G; w! l4 s$ J, ?+ L
Standard error of rate, 率的标准误
7 K4 F$ L5 g6 {5 Y6 ]# YStandard normal distribution, 标准正态分布( P: F. n/ j* \9 S, N4 b8 v8 ?
Standardization, 标准化
, @9 d" o7 m) [: ?Starting value, 起始值$ R! S) P5 @7 v. W6 z
Statistic, 统计量
+ y$ a9 _! d5 K$ o7 g' b# X! vStatistical control, 统计控制
/ z9 k* y- ~1 K b, LStatistical graph, 统计图
- V3 T" r2 {2 ^+ ?, v, a; O/ nStatistical inference, 统计推断0 I; e" |0 i' W$ i: D
Statistical table, 统计表
8 N2 E7 e. Z+ S) ^# j7 WSteepest descent, 最速下降法" Z4 e ]' |- a* z
Stem and leaf display, 茎叶图
1 |* G! B7 S) {8 d9 H- U r* \Step factor, 步长因子
1 Z# R* K% N8 {3 N1 [Stepwise regression, 逐步回归
& c) J' R! }4 `2 x% h( h. fStorage, 存' I6 Y8 F% R3 u6 F$ _7 a
Strata, 层（复数）% h7 z, c3 y! {. _* m6 \
Stratified sampling, 分层抽样
7 Y' N5 S( r8 m' R# `3 C, NStratified sampling, 分层抽样8 I& D/ g7 }2 e8 a1 [& {$ L
Strength, 强度$ x& d, V6 Q9 u3 ^9 G6 l0 c! X
Stringency, 严密性
C9 J2 a0 T; `! iStructural relationship, 结构关系) m+ z2 N2 `5 }7 O
Studentized residual, 学生化残差/t化残差8 |1 T7 [# ~3 K
Sub-class numbers, 次级组含量
$ j3 b2 r o6 C9 ^Subdividing, 分割* w. v; z: d9 _
Sufficient statistic, 充分统计量1 |, l3 |* n* y% g2 y
Sum of products, 积和4 M3 D) L" N1 ~
Sum of squares, 离差平方和" Z' E1 \: h1 Y6 R( l
Sum of squares about regression, 回归平方和
' }( [+ I h2 B" N0 J2 b/ a. b% dSum of squares between groups, 组间平方和
9 V) v9 v3 l( r( E- hSum of squares of partial regression, 偏回归平方和
& y" h* q- {4 a+ K- Q+ pSure event, 必然事件
& F8 M1 Y) ?. j3 I6 j5 P0 A P5 iSurvey, 调查
# s8 p; n3 Z. sSurvival, 生存分析
8 m/ U4 K: V+ j! `2 l* ]Survival rate, 生存率8 |( Z% a- }( W' U; E0 @- D8 [
Suspended root gram, 悬吊根图4 r G! `# s( F
Symmetry, 对称0 O" N, d, z9 r% D' r
Systematic error, 系统误差
" w5 y' ~8 D) _4 Q- T7 jSystematic sampling, 系统抽样
! R8 K2 m, c. V* e0 I1 BTags, 标签6 I4 E6 m$ K$ _. Z0 k! k9 C$ o
Tail area, 尾部面积
0 Z" h/ `4 N% tTail length, 尾长6 r% ?7 n) }2 ^' ]( L$ W
Tail weight, 尾重9 N- g; x1 m* @1 h+ j. f
Tangent line, 切线) e7 \8 }- |3 B1 V. P6 q5 C
Target distribution, 目标分布
, c" m d) x3 W" O7 YTaylor series, 泰勒级数5 n. W( q8 H+ q/ _# |& d
Tendency of dispersion, 离散趋势* V: W7 a( H+ m. t9 y4 l
Testing of hypotheses, 假设检验- g9 E$ N! h4 d
Theoretical frequency, 理论频数
- I. ?- o; v$ M& s& w7 C! jTime series, 时间序列* C! M3 M; ~6 b C
Tolerance interval, 容忍区间7 r4 \$ Q6 G+ U5 [. `! B3 F# V
Tolerance lower limit, 容忍下限3 s0 [6 A; j! l8 R/ \% Y
Tolerance upper limit, 容忍上限7 T- ?& Z, f: n- x V
Torsion, 扰率0 q' q$ q" i( D! X$ h
Total sum of square, 总平方和: H" r7 [& O# P
Total variation, 总变异
, N2 }, P) X" t9 [" T% F, hTransformation, 转换
& A; i# ?/ c& U. C; O6 Z0 gTreatment, 处理
7 o' C' D+ ^+ O* aTrend, 趋势
: Z: c& v) n/ [% p+ iTrend of percentage, 百分比趋势, d* @; [9 y/ b2 u2 Q! h
Trial, 试验
' T, @" |4 Y: X8 [" yTrial and error method, 试错法
% A1 c; g. F' b9 a. |Tuning constant, 细调常数
7 z7 N; R* q) z# H4 R6 ATwo sided test, 双向检验
: H9 s. K. }: G; `" lTwo-stage least squares, 二阶最小平方( [; X/ |% L0 r" S( e
Two-stage sampling, 二阶段抽样8 E6 \7 e- N7 l E" o
Two-tailed test, 双侧检验1 d( K9 S- W b+ {; |
Two-way analysis of variance, 双因素方差分析) a: |3 L' T( M$ k% }3 }
Two-way table, 双向表
$ h! S0 D: v. ?% |1 E! w8 \; ~Type I error, 一类错误/α错误
Y2 d/ R: M$ W* ?" `+ L u5 @Type II error, 二类错误/β错误; g/ `# p6 w: i6 G( L$ N
UMVU, 方差一致最小无偏估计简称8 }( V9 |- _8 j3 z1 {
Unbiased estimate, 无偏估计
& I7 G) Q- r l U% nUnconstrained nonlinear regression , 无约束非线性回归: U( c E4 c- d. F0 b
Unequal subclass number, 不等次级组含量5 h% I j* G( i0 S- ?; |
Ungrouped data, 不分组资料1 }8 O; u9 _+ X6 F
Uniform coordinate, 均匀坐标* n- [9 K3 w5 z) [
Uniform distribution, 均匀分布
. J- i1 l# T* ZUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
; e" j- Y4 |# H+ H: XUnit, 单元
+ L) W3 }3 B# K3 b. eUnordered categories, 无序分类, U3 j' I; A/ G1 b L
Upper limit, 上限
' w; J) v8 ~0 \7 `, vUpward rank, 升秩; y2 c Y k$ }- N
Vague concept, 模糊概念- p) X" P# \! K
Validity, 有效性
) w; l( ~+ g4 d1 \VARCOMP (Variance component estimation), 方差元素估计- k! P, k; m! v" Y( l
Variability, 变异性
+ X6 c# t3 |$ D; W8 rVariable, 变量
7 |& r/ J9 ]4 g! }6 `3 t- Q- D3 wVariance, 方差
4 R4 V# t; g! s" r: s2 xVariation, 变异. ]$ ]9 `8 g' N
Varimax orthogonal rotation, 方差最大正交旋转% t8 n! b, C; l- J+ s) e1 }
Volume of distribution, 容积
0 s6 i7 w# ]! y6 N1 r9 |9 \+ zW test, W检验
1 g/ V2 K8 j s# J! {6 DWeibull distribution, 威布尔分布/ A1 P5 F9 N: A0 m8 [
Weight, 权数
; Z. K, w) l. C; J7 U( E4 `Weighted Chi-square test, 加权卡方检验/Cochran检验
8 }% j+ f7 t3 H) pWeighted linear regression method, 加权直线回归8 @2 T# r0 c' e7 X) H( @4 X9 t/ s
Weighted mean, 加权平均数" J% G) R) K9 }. k$ I- A
Weighted mean square, 加权平均方差9 x$ L9 S0 ?9 q8 g/ s1 j
Weighted sum of square, 加权平方和
# D4 c+ m% u! KWeighting coefficient, 权重系数; ?2 R7 G6 W. E
Weighting method, 加权法 3 J4 }! }! R1 ]* A8 J
W-estimation, W估计量# s ^; e9 Z; U- y" L8 |
W-estimation of location, 位置W估计量
; I5 |# X) |/ {- OWidth, 宽度4 B+ ]4 Y4 P5 v. {# T! g6 ?
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
4 @, @* W" n6 r; sWild point, 野点/狂点
8 y& Z- u5 Q0 k7 d6 DWild value, 野值/狂值) i, e2 V7 F) A& j) Y9 Q A
Winsorized mean, 缩尾均值' a8 M9 n$ Y( m# q9 x7 R
Withdraw, 失访 4 O: ~6 h' S* }
Youden's index, 尤登指数
. _( [4 ?- M% \( R0 u6 E$ ~( [Z test, Z检验! x& {$ q- h! {, o: g2 V5 M
Zero correlation, 零相关
5 W7 _: u+ [) y6 x( ?0 bZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
