|
|
Absolute deviation, 绝对离差
/ A, d: E9 E/ }Absolute number, 绝对数9 ~0 r( M8 I1 |
Absolute residuals, 绝对残差
0 M! z) N: h+ }7 S( jAcceleration array, 加速度立体阵' {2 U# \# z! D' D+ m
Acceleration in an arbitrary direction, 任意方向上的加速度
6 |" ?* j/ f- y3 }' |Acceleration normal, 法向加速度
1 j) Q4 N; w" E, i% RAcceleration space dimension, 加速度空间的维数
4 z- x4 {; _* a- n8 w1 @/ DAcceleration tangential, 切向加速度
; P0 u2 X! a8 h7 X# s9 a& h) ^ MAcceleration vector, 加速度向量
/ \8 a0 ^3 w8 sAcceptable hypothesis, 可接受假设1 I2 s* S D0 j& F, ~$ P
Accumulation, 累积
2 B; |; f1 z: ]& fAccuracy, 准确度
2 C6 L D( I9 qActual frequency, 实际频数; E! O/ ?: } z( e4 n6 x
Adaptive estimator, 自适应估计量
& U- a j7 j0 ?5 V7 J: JAddition, 相加
/ Z, |, @6 d+ lAddition theorem, 加法定理* u A+ ]. P' @1 K) N) K1 o
Additivity, 可加性
; L9 h7 Z7 \1 k2 X7 dAdjusted rate, 调整率& v- G4 {5 H9 ?$ ]/ z+ k
Adjusted value, 校正值+ s6 {! g8 }# n" L4 n/ [+ u
Admissible error, 容许误差
; v( g. b0 {# |. JAggregation, 聚集性( N* {% c$ y+ p( q+ w
Alternative hypothesis, 备择假设
% s7 y7 C, f6 R# X" KAmong groups, 组间/ z4 X- X" y2 J) n+ N
Amounts, 总量
/ U/ K' q0 D7 uAnalysis of correlation, 相关分析
% S& w9 P% V6 _4 h1 a t* y6 oAnalysis of covariance, 协方差分析
. [8 S5 `8 }2 }5 MAnalysis of regression, 回归分析
- u) ~' j, F' i, I" }* tAnalysis of time series, 时间序列分析
3 m9 p0 I+ l# \% y: i4 D7 z3 UAnalysis of variance, 方差分析
) d+ @" x# }& dAngular transformation, 角转换' y5 E& E* F5 P$ I6 [# P7 ^
ANOVA （analysis of variance）, 方差分析
4 h J4 Q( G4 oANOVA Models, 方差分析模型, p! R7 h' n: J3 P+ ?' r
Arcing, 弧/弧旋
1 _) F$ _. Z- Z/ t! f! G( KArcsine transformation, 反正弦变换
1 I$ P) s) L6 Y5 Q4 oArea under the curve, 曲线面积
X8 a: O1 a8 I$ B3 iAREG , 评估从一个时间点到下一个时间点回归相关时的误差
# O. k1 r& s* a2 l, H( q2 n' N xARIMA, 季节和非季节性单变量模型的极大似然估计
\' z5 v* }% N" yArithmetic grid paper, 算术格纸
8 _' {3 H! \. w- V0 g- ZArithmetic mean, 算术平均数
, ?2 s2 v' F# V$ ?Arrhenius relation, 艾恩尼斯关系
% v+ B4 q/ j# g }& _$ z+ i' ]Assessing fit, 拟合的评估
; H4 Z$ e# ]+ Q* u3 HAssociative laws, 结合律2 U& @4 p6 e( O
Asymmetric distribution, 非对称分布
/ L% y+ X. F) bAsymptotic bias, 渐近偏倚
/ V7 _' M H" ]' m. L3 TAsymptotic efficiency, 渐近效率
* C5 Z1 Y8 W- |6 Y6 cAsymptotic variance, 渐近方差
8 Q" ?+ P: y# h4 G! |& \Attributable risk, 归因危险度
2 N% S, | n2 J, ^$ l% S* cAttribute data, 属性资料
3 [. O# l4 j1 f; ^4 pAttribution, 属性
9 k1 r- w6 n* ~8 \Autocorrelation, 自相关
+ y. N/ k! E. t3 dAutocorrelation of residuals, 残差的自相关
% U( R8 Z! l. uAverage, 平均数( \; Q! z" N0 ^
Average confidence interval length, 平均置信区间长度% s% K0 p, e( Y9 ]/ n
Average growth rate, 平均增长率- k/ b( Z, b/ \9 ~" A
Bar chart, 条形图
0 a, J" C/ Y1 u# f9 J% l7 yBar graph, 条形图: |% U1 ?* h$ m
Base period, 基期
2 X3 Q+ F6 W1 p) ` xBayes' theorem , Bayes定理/ a; M- z2 T9 |5 e3 Q
Bell-shaped curve, 钟形曲线
. ?' h, n4 u' m; R7 x* }5 \+ _Bernoulli distribution, 伯努力分布
' n9 A3 O4 g' `& D" i4 ?: u1 kBest-trim estimator, 最好切尾估计量
4 {0 f3 h6 r/ U+ }Bias, 偏性
2 ~) ^3 D! f8 @) eBinary logistic regression, 二元逻辑斯蒂回归* j6 q* x. c% h) S P3 p
Binomial distribution, 二项分布
+ V1 X9 a2 c; F ~0 z+ {Bisquare, 双平方: s; b7 c) j, `$ L/ K9 d
Bivariate Correlate, 二变量相关
" m: R1 }' d7 r2 ]Bivariate normal distribution, 双变量正态分布
" ?( U3 d* D8 cBivariate normal population, 双变量正态总体
' d d, m5 I' n7 E7 ^" A( kBiweight interval, 双权区间3 D8 v0 T6 O4 ^& f' K* ]% ~* W
Biweight M-estimator, 双权M估计量* \0 G, {& P+ r- X9 O
Block, 区组/配伍组
( q) q& A4 z8 R3 TBMDP(Biomedical computer programs), BMDP统计软件包
& J4 c @# e* H/ lBoxplots, 箱线图/箱尾图' a2 P# l5 N& G1 w
Breakdown bound, 崩溃界/崩溃点6 _" Y2 L/ C, m* b6 E
Canonical correlation, 典型相关
) w2 { i- K W! @2 [/ F! \Caption, 纵标目+ @# z! @3 V2 _! z- v+ i
Case-control study, 病例对照研究
3 a, F3 n' v) Y) c$ M" k5 BCategorical variable, 分类变量
+ A6 z$ t8 V) Y9 g$ ^+ D: mCatenary, 悬链线+ G# `; u5 A' W `0 T, Q
Cauchy distribution, 柯西分布
) ]9 e- C( X9 S$ Q% {" KCause-and-effect relationship, 因果关系
/ f7 ?' n e; ]% `! RCell, 单元, C" Z, A, x6 ?3 h6 g! I& ?/ }' J
Censoring, 终检8 k* w9 @/ a( d' Q# h# Y/ m. h
Center of symmetry, 对称中心- J" t" j6 ^: t: D8 ^4 A8 d
Centering and scaling, 中心化和定标# }3 Q2 ?$ L- x3 O+ h1 ]
Central tendency, 集中趋势3 S, s# h5 y, f3 p/ W0 ?
Central value, 中心值, i5 t# o" G4 [3 u
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测+ E# `! |# I# H# t
Chance, 机遇4 k4 |( m5 i& ~: C
Chance error, 随机误差! q5 r: }2 X4 k0 v
Chance variable, 随机变量
D3 K% ~ Q# |7 }' I2 e" |Characteristic equation, 特征方程- A R5 { A' m0 z# D i
Characteristic root, 特征根# I; A: T6 G$ b: a' u4 Z( W- Q
Characteristic vector, 特征向量( x# h' x) u9 v* R% U, l- u
Chebshev criterion of fit, 拟合的切比雪夫准则+ d6 L* l+ r7 H
Chernoff faces, 切尔诺夫脸谱图' j* |4 a- m& X, c4 \
Chi-square test, 卡方检验/χ2检验+ g n( p, A. d8 P$ Y
Choleskey decomposition, 乔洛斯基分解
' N/ t2 a- Z& D& W7 Y1 Z TCircle chart, 圆图 ( Y7 X' p! I0 G5 v
Class interval, 组距
) i* g- ?# A7 Z- j4 \) \7 fClass mid-value, 组中值, J' H, f7 Q p9 r/ Q, p, e: W8 W
Class upper limit, 组上限$ b- R9 ^; T D8 p: |5 y- G
Classified variable, 分类变量+ G0 c( k5 z( S9 |! G' V6 E- V
Cluster analysis, 聚类分析& K- E2 _. W# s6 f: V- z! q; ]# a" u& ]
Cluster sampling, 整群抽样
+ g4 y& Y( i0 o5 xCode, 代码2 b2 g" g0 u2 H% ~/ N6 H; W* u
Coded data, 编码数据8 L2 x1 L+ M9 g* C3 B( q6 c
Coding, 编码
, b: |8 J- O5 iCoefficient of contingency, 列联系数, N9 h/ E. v' K" ~
Coefficient of determination, 决定系数' l( j2 R# I0 z! M m2 a
Coefficient of multiple correlation, 多重相关系数
) U4 ~2 m+ `" w! o, VCoefficient of partial correlation, 偏相关系数
/ Q! Q7 S8 x: M5 o7 S* YCoefficient of production-moment correlation, 积差相关系数
4 U9 j7 ^; p- N+ ~) x% ZCoefficient of rank correlation, 等级相关系数
1 a2 O6 X& U& R0 ]4 [Coefficient of regression, 回归系数, i/ l. i( T: C% Q- Y4 H' D: L
Coefficient of skewness, 偏度系数3 c4 l) H4 \/ w) M& H$ m7 B
Coefficient of variation, 变异系数
y* \/ c) X9 N+ D' b3 vCohort study, 队列研究& l: x9 i3 C5 m3 c m5 t( l9 L
Column, 列
1 s# T. u; ~" m$ z7 L n0 R" O3 M$ wColumn effect, 列效应6 }3 s& l8 O3 h1 a
Column factor, 列因素
7 Q/ T. p, S' M& z9 r/ A9 NCombination pool, 合并; H: u1 W: c# s! o4 n: s
Combinative table, 组合表; o1 B3 o! \6 F' r7 x
Common factor, 共性因子5 R: l- M! f) |' U( T5 K
Common regression coefficient, 公共回归系数
* N3 @2 T1 H- o- cCommon value, 共同值
6 w7 |- h: V2 a; p5 QCommon variance, 公共方差$ P+ ^* I2 T7 Z
Common variation, 公共变异5 j# U0 _4 p( Z+ d
Communality variance, 共性方差. Z( ^/ l3 t9 ^. u7 ~
Comparability, 可比性
7 A" ~' j% J6 f6 XComparison of bathes, 批比较
! d- m. ]) _# {# vComparison value, 比较值! X* P( D& ?" g/ v+ |4 a
Compartment model, 分部模型9 o; d$ ?; m1 d& F6 w" Y
Compassion, 伸缩3 ?% K7 n* z5 F6 F6 E
Complement of an event, 补事件6 @. A; n( `! C
Complete association, 完全正相关+ T) w7 K7 W1 c d1 j
Complete dissociation, 完全不相关' q! u7 m& E0 z4 |
Complete statistics, 完备统计量
; z$ u9 ^9 L7 UCompletely randomized design, 完全随机化设计
. v3 |# W0 X0 A9 |: P6 @+ |- PComposite event, 联合事件
q3 M9 ~- l! _Composite events, 复合事件8 `3 Y) `1 M5 ?
Concavity, 凹性
6 U0 ^! o6 T1 d6 n7 g% {Conditional expectation, 条件期望! y* t( Z0 _" t3 G
Conditional likelihood, 条件似然 `, d& m0 N# q) J
Conditional probability, 条件概率
' i* ]' K" E; qConditionally linear, 依条件线性3 }; T( a+ v7 L, I: T, V0 o
Confidence interval, 置信区间
) J; M; f( o l: |) _. PConfidence limit, 置信限
! H* ~6 }, ]& S9 u8 OConfidence lower limit, 置信下限, O# }5 C7 A7 W* J* D1 C- C
Confidence upper limit, 置信上限$ n$ b3 v! V4 F0 c) r3 a; \( d: ?$ `
Confirmatory Factor Analysis , 验证性因子分析) X8 A, u& E! N. c5 L
Confirmatory research, 证实性实验研究
* S4 [3 Z2 D2 lConfounding factor, 混杂因素
* p( q6 \3 ^$ c6 ~; `! i2 ]Conjoint, 联合分析
1 f- I; G+ H0 H% m. T& |Consistency, 相合性! G: P3 x5 A) E& t. n U/ ~0 z+ q
Consistency check, 一致性检验
- [9 p; ~8 P' V8 lConsistent asymptotically normal estimate, 相合渐近正态估计2 ~7 Y: P) _) a8 O; I2 I6 o: d
Consistent estimate, 相合估计 t* u5 y8 R4 T' E1 k
Constrained nonlinear regression, 受约束非线性回归
9 c; Y) E& q5 @. V. B2 t7 [* NConstraint, 约束
; E. Q+ W* \. |1 S6 U& L M0 H* r( CContaminated distribution, 污染分布, a5 J1 b. N. K) [& v
Contaminated Gausssian, 污染高斯分布, ~8 _; S, Y+ L9 b6 K% t) V
Contaminated normal distribution, 污染正态分布
3 J+ H u& p6 z2 e* oContamination, 污染+ H4 L9 k5 |% P- C$ C" U
Contamination model, 污染模型; [* ]" z8 K) g/ m% a
Contingency table, 列联表
. Y5 Z: [4 ?$ D( A; B% OContour, 边界线
# @* Z/ j7 v' g `Contribution rate, 贡献率$ }& i4 s, Z# b% z6 Z4 k( }
Control, 对照
; X# [: [: p: i1 `3 h+ g8 Q4 cControlled experiments, 对照实验( }2 x3 l+ d9 ?$ P' ?) X
Conventional depth, 常规深度8 I* l8 _0 H8 k5 w% w
Convolution, 卷积
2 y' W3 O7 Q$ V/ W/ KCorrected factor, 校正因子
- e( G8 l; ]* ^Corrected mean, 校正均值" Y& H" ?$ k6 V4 c. o! Y; L
Correction coefficient, 校正系数
1 q% U* z: i- B" u3 _* F2 C9 S; bCorrectness, 正确性
7 b: v" R* p2 t, `0 e% j0 Y; cCorrelation coefficient, 相关系数
* z1 C1 ]0 a* {9 c1 {Correlation index, 相关指数
6 ]% u7 V; T ^Correspondence, 对应
* _' [5 V3 v TCounting, 计数
* a- _0 M& _4 K: @; j, v( V2 ^6 [Counts, 计数/频数. s! X4 I3 f/ v% Q. ~
Covariance, 协方差* H# [$ M8 ^% A5 f4 `) K
Covariant, 共变 " D( Y2 @, e5 F% {9 _ B
Cox Regression, Cox回归
9 c8 Z0 @" R" |: f& ]+ R% p* tCriteria for fitting, 拟合准则
$ E Z& m U+ x0 {' e( _4 SCriteria of least squares, 最小二乘准则% \% |( d+ j( q5 d3 p9 H$ {" \
Critical ratio, 临界比8 d3 Z0 N+ n3 @9 u
Critical region, 拒绝域
& n2 j/ t# U" @; E6 W# VCritical value, 临界值
5 v4 X6 h# \- m0 ~ H; RCross-over design, 交叉设计
5 q9 Z( ]3 y1 U4 F! p# eCross-section analysis, 横断面分析. s; C4 ~; b6 x
Cross-section survey, 横断面调查
0 b5 C9 ^' {( k" d7 b/ v$ rCrosstabs , 交叉表
4 W0 {& O7 h8 G$ N; J4 |Cross-tabulation table, 复合表
( @+ p; T7 ~. p/ Q) T0 |& u4 WCube root, 立方根8 C* m1 ~7 b9 u7 s+ s3 {) k
Cumulative distribution function, 分布函数
* C: O, y! B0 [Cumulative probability, 累计概率$ x9 K }8 `! I) X; `
Curvature, 曲率/弯曲. p5 @5 J) u! D4 R
Curvature, 曲率
- P0 G+ c* H) |; t* g9 m8 ]8 eCurve fit , 曲线拟和
; p" L5 w' L" L) a# Y7 x9 t5 BCurve fitting, 曲线拟合
/ b7 M6 {" K% L8 qCurvilinear regression, 曲线回归
, @; v& |, V' C: c( K- pCurvilinear relation, 曲线关系
, }& g/ U* D4 }# B1 dCut-and-try method, 尝试法$ t8 S, E. b3 Q- P1 t
Cycle, 周期$ z' o, I$ l: K! [& P
Cyclist, 周期性3 o) b1 [' A! h" b0 m
D test, D检验
4 f3 B( x5 x" w+ h% qData acquisition, 资料收集 `, [5 T. |8 n" }2 |, A) f
Data bank, 数据库+ T) v% O( f/ ]4 R& r D
Data capacity, 数据容量
$ x6 l$ R j9 FData deficiencies, 数据缺乏
5 F- }$ C& O: x# _Data handling, 数据处理
- {, _9 o( T: g# S; zData manipulation, 数据处理4 E- Y# s7 _7 G5 U( K
Data processing, 数据处理
6 Q& k5 f G6 K6 L! UData reduction, 数据缩减8 M0 z* s- }' G5 o
Data set, 数据集2 B! I# X5 {( j/ u- m
Data sources, 数据来源
3 L! P, X& W; fData transformation, 数据变换. Q4 P5 D7 W* ]% J; u
Data validity, 数据有效性
) T$ M8 ~( h# ~) FData-in, 数据输入7 j* [. M0 A+ E3 Y
Data-out, 数据输出
3 D2 d" q7 _8 F G8 LDead time, 停滞期 W' u) x+ Y' p) F8 L
Degree of freedom, 自由度
+ t0 X' Q# C7 Z+ X S4 h9 B2 ODegree of precision, 精密度9 _/ X( a' ], {# z0 |: E
Degree of reliability, 可靠性程度" d, e1 m) C9 I& s W' r8 l
Degression, 递减
: L6 x5 t8 t6 A4 e, P: F3 U! bDensity function, 密度函数4 J& q8 A. B; u6 m7 v
Density of data points, 数据点的密度( o# B1 w% I4 g4 F9 v; X: C
Dependent variable, 应变量/依变量/因变量. [# |! D5 |6 {9 @! m# O* A, ]
Dependent variable, 因变量! A0 G0 c# J' Y5 b' J$ O, u
Depth, 深度' i$ F8 A, U; ~2 I F4 Y
Derivative matrix, 导数矩阵
' v1 Q7 f8 L4 aDerivative-free methods, 无导数方法7 l. i) I. P3 j$ y$ f! F
Design, 设计" e0 v, ~) |7 K$ a0 z. x
Determinacy, 确定性
$ B6 S4 }/ B; {+ i) b7 x) {1 a0 G/ fDeterminant, 行列式4 T1 M8 Z2 v& e0 @% x p
Determinant, 决定因素7 m; e, U/ c8 d, y$ y8 y
Deviation, 离差
0 N, j' Q6 c% u5 E3 TDeviation from average, 离均差
9 H1 J$ M/ B4 W% iDiagnostic plot, 诊断图/ H" b, S" d$ r9 M
Dichotomous variable, 二分变量
" b! g/ [7 {5 u7 J6 PDifferential equation, 微分方程
2 u1 \6 i2 Q' I+ F; |( K* sDirect standardization, 直接标准化法, g1 u2 r/ [9 j, G4 z
Discrete variable, 离散型变量
8 I; c: F2 N0 l! P" wDISCRIMINANT, 判断
# k# T2 {9 y9 ~4 E+ c( NDiscriminant analysis, 判别分析
. [3 R% i. } ~6 E! D. JDiscriminant coefficient, 判别系数
' Q* |# }& I( X8 DDiscriminant function, 判别值# U- H0 `& R* Y3 O" u
Dispersion, 散布/分散度
9 ?# Q C- S+ j; QDisproportional, 不成比例的, b8 J8 m+ Q! Y$ C! p
Disproportionate sub-class numbers, 不成比例次级组含量' M! F( G2 j- i' W. Y% y8 w
Distribution free, 分布无关性/免分布
; d5 R# {. n O7 o1 X/ a7 P7 m" UDistribution shape, 分布形状( d7 s* }4 _- n, `2 J; T; a
Distribution-free method, 任意分布法
* ^& V( K% i2 W- {" ZDistributive laws, 分配律
, W6 k/ j3 P' E1 d# w) s& b$ m8 T+ ~Disturbance, 随机扰动项
2 a4 ?" B) n8 sDose response curve, 剂量反应曲线
, v( `0 D$ `1 [1 S3 ^3 cDouble blind method, 双盲法1 ?# a7 R. G# ]5 [6 Z5 ^" D
Double blind trial, 双盲试验1 P, {: o1 p/ b- S; J
Double exponential distribution, 双指数分布0 H) R; R4 J6 O6 s
Double logarithmic, 双对数7 [" u b, O* `% O. |
Downward rank, 降秩3 R+ W3 C" \3 u3 S) v- u j) B
Dual-space plot, 对偶空间图+ w2 J9 t6 ]1 O
DUD, 无导数方法
) g7 [: ~9 d) @' S0 d! X4 A+ uDuncan's new multiple range method, 新复极差法/Duncan新法0 e+ k9 `9 K+ J$ E# o4 j1 J
Effect, 实验效应4 f; T1 q8 k6 y$ y+ g7 t8 I
Eigenvalue, 特征值
* \; R f' ?% U! Z7 g# W( PEigenvector, 特征向量' _& S/ r/ a' W# R( O2 c9 X
Ellipse, 椭圆) `, x2 E2 ~5 r L" X' ]
Empirical distribution, 经验分布! w$ C% P7 v) z
Empirical probability, 经验概率单位% P$ V M: N+ K& c
Enumeration data, 计数资料
7 W# |. p/ |" y& S5 G+ ~5 KEqual sun-class number, 相等次级组含量
- G5 D- I0 V" }$ W xEqually likely, 等可能
8 h- i* n2 M zEquivariance, 同变性
& \7 r! W1 ^, U! T! oError, 误差/错误/ L. U7 d9 V0 A* k; h
Error of estimate, 估计误差
* R9 D% j! C8 t, U& b( xError type I, 第一类错误
, l1 U( O; y @) L: R. OError type II, 第二类错误
8 a+ ~ g/ a* j" m W7 qEstimand, 被估量
/ \ |" {! f3 OEstimated error mean squares, 估计误差均方* @5 l( |2 n4 i
Estimated error sum of squares, 估计误差平方和5 v9 K* Q. s" H! E2 q5 }, r
Euclidean distance, 欧式距离
# Y9 ?. ^" ~" A5 ]Event, 事件
$ e& D9 j$ k. ~7 a& CEvent, 事件- Q% \7 d9 e! v; F% F; b; C
Exceptional data point, 异常数据点
# Q$ i6 `$ x9 @. Y6 D9 K0 G+ nExpectation plane, 期望平面 e& F. f2 o. Y; ]
Expectation surface, 期望曲面
3 H, w- b6 v7 C; L! \4 }Expected values, 期望值* x* }( }3 l! ]
Experiment, 实验2 k# @$ K' Z( T R0 O' o* h
Experimental sampling, 试验抽样( ~8 g1 T% }# s# _& m; P1 t
Experimental unit, 试验单位4 I6 y: `( X0 Q: I
Explanatory variable, 说明变量
; l1 Z9 O- F5 n" ?3 D) jExploratory data analysis, 探索性数据分析0 U5 L. G' [* ~ I* `$ T
Explore Summarize, 探索-摘要
; m6 o* k/ ]% h& v. zExponential curve, 指数曲线2 u% C& H h% M9 H
Exponential growth, 指数式增长
1 S. s4 r+ R' I5 ^) V! ?. V% YEXSMOOTH, 指数平滑方法 / N' Y0 u3 V5 v: f. y3 O
Extended fit, 扩充拟合- J7 B5 S3 h0 U; I, A4 o# `
Extra parameter, 附加参数- ^3 s. Q4 L; Q5 X; L
Extrapolation, 外推法
6 |1 O; H) m D6 Q/ V z1 oExtreme observation, 末端观测值6 v4 H' I' _7 C& e9 U- O6 t
Extremes, 极端值/极值2 p) ?' b/ g0 ~
F distribution, F分布
3 q5 d6 A8 e! |$ h$ aF test, F检验; H% l# N$ w |" M2 D) R$ ~
Factor, 因素/因子
; I, p6 \8 B) B2 j3 v# H! _Factor analysis, 因子分析
- m! ~. k0 {' }% t( d% x3 IFactor Analysis, 因子分析3 R' B* A$ p) Q O. P+ n8 I
Factor score, 因子得分
% k1 I P2 k0 W" Z2 F" `Factorial, 阶乘/ E9 h: q' @ T/ x. n [6 P
Factorial design, 析因试验设计+ _- G; E! N0 p( C5 @# k
False negative, 假阴性
2 U8 v) G; q x* M5 e& q% Z8 DFalse negative error, 假阴性错误% u" m* M1 e8 X$ ]- r) i
Family of distributions, 分布族0 y6 P! s: i& Z; B* s. L; k% J
Family of estimators, 估计量族
& P q x$ h' z3 @. T3 K& LFanning, 扇面( `/ M. \' q. `# _+ \2 d1 W6 w# X
Fatality rate, 病死率
8 Z. i5 ^+ D+ {. X M% W! f0 eField investigation, 现场调查
$ R' ^3 Z7 Q* }- R3 S* XField survey, 现场调查
4 H( i" e, N- p- \: E9 r. YFinite population, 有限总体7 v6 E P$ d ]
Finite-sample, 有限样本
8 q, H- |; e3 `) oFirst derivative, 一阶导数$ Z: q4 n7 J( f: [" m4 ~) O# N
First principal component, 第一主成分/ O6 X$ ]) [& b& n+ k* P# h6 v
First quartile, 第一四分位数
7 Y4 J/ A3 k. |- `. @ kFisher information, 费雪信息量
$ W. ^! X2 K7 U5 O% d/ r6 y& F6 xFitted value, 拟合值! e+ q+ Y& w! E+ n E
Fitting a curve, 曲线拟合
4 X) T v4 V6 ~. p$ M1 HFixed base, 定基
; {4 x, y( W8 }Fluctuation, 随机起伏
( a5 U0 D' X9 T: XForecast, 预测
- a }( _) r0 v9 bFour fold table, 四格表) i& r! W; {& Y4 a1 g
Fourth, 四分点# e; f' ^. O4 H2 b( c* Y6 q% v, r# b
Fraction blow, 左侧比率
8 s; @4 Q& I# ~5 K- H1 ZFractional error, 相对误差2 U9 t! I8 i. G$ |+ f( Z/ }0 q
Frequency, 频率* ^& H8 h, J" z8 r6 U+ y, u* e
Frequency polygon, 频数多边图. L$ ^* ~' _0 n& h1 {8 f8 L# |
Frontier point, 界限点7 E0 r1 w- N$ m- `, E: f/ F; i# [
Function relationship, 泛函关系. q3 A2 {: p5 g$ y* U2 }
Gamma distribution, 伽玛分布
- u7 }" c; q" ~( Z( ?8 S+ _( b4 rGauss increment, 高斯增量
' F! V, Q b% T4 m' qGaussian distribution, 高斯分布/正态分布
; K) O- p& ~8 ]! x" TGauss-Newton increment, 高斯-牛顿增量
8 J. s' n# U0 z' @; K* J8 z0 B/ kGeneral census, 全面普查% d+ {: P: N2 z" P+ H" G! Y3 R
GENLOG (Generalized liner models), 广义线性模型
- k, [2 v9 a' @; xGeometric mean, 几何平均数
$ v" D+ f/ d' HGini's mean difference, 基尼均差
$ t7 n. d+ f; W2 X" }GLM (General liner models), 一般线性模型
R4 K9 ?# D( D! K8 O bGoodness of fit, 拟和优度/配合度; ?& q, _- W. v
Gradient of determinant, 行列式的梯度& D6 n* F& U* v. ?7 ^. G1 A
Graeco-Latin square, 希腊拉丁方
% u" z& [9 t( LGrand mean, 总均值) k# K/ b7 H6 ] c# i+ ]' |
Gross errors, 重大错误 T; e' ?# Y3 v* a" i6 I# ]
Gross-error sensitivity, 大错敏感度" s: l/ H3 x8 N- m
Group averages, 分组平均( ~: r* j6 n9 C* l. X& f
Grouped data, 分组资料- k6 H. d1 {- ]
Guessed mean, 假定平均数+ F* x6 _% t% |8 p. j6 Q
Half-life, 半衰期
. M/ K$ a0 x9 d) Z- S, OHampel M-estimators, 汉佩尔M估计量: i9 \. W* b8 B' d6 G
Happenstance, 偶然事件# Z$ Q' o; r i1 s! n
Harmonic mean, 调和均数
3 |5 e( d9 e1 B( D o, jHazard function, 风险均数
6 i5 g- T( [/ B; g- L% O* r( NHazard rate, 风险率# s# k. M) m% [8 S r- x
Heading, 标目 / S9 I# \8 ]2 e; U
Heavy-tailed distribution, 重尾分布% R+ B3 Z, M, R6 k0 v. n
Hessian array, 海森立体阵
9 i7 m; o5 e. o0 bHeterogeneity, 不同质7 t" M4 X& d( o$ @4 d
Heterogeneity of variance, 方差不齐 0 ~* @5 d) Z% `; w+ k
Hierarchical classification, 组内分组) u) U: J% e( |/ B% W# x
Hierarchical clustering method, 系统聚类法
4 e7 u& `2 y1 x2 D& @7 S6 Q% @High-leverage point, 高杠杆率点
1 w1 ` c4 @8 yHILOGLINEAR, 多维列联表的层次对数线性模型
6 W, D# k9 c' O; r7 T$ s. ~7 C6 v1 x* qHinge, 折叶点3 G1 O1 c$ q5 d- X$ N8 {5 d
Histogram, 直方图
! c/ ]3 o$ X/ aHistorical cohort study, 历史性队列研究
% K a3 X+ U, n% j% m- ^7 KHoles, 空洞, L: Z% c% _1 B3 z
HOMALS, 多重响应分析
` K4 P$ Y. L! e8 V3 UHomogeneity of variance, 方差齐性
" ^, G5 u P; _7 hHomogeneity test, 齐性检验
% u0 V6 ?& ]& H6 ~; lHuber M-estimators, 休伯M估计量% x# S. c* K6 H$ Z
Hyperbola, 双曲线
0 H4 |% h h7 `( x8 r" r0 pHypothesis testing, 假设检验' }9 x- Q5 I; C: M% h
Hypothetical universe, 假设总体
; e. D4 J+ P& q% wImpossible event, 不可能事件8 N# M0 Z1 ^9 m$ m" U
Independence, 独立性
/ k! ~4 f$ d% ~Independent variable, 自变量6 Z: T3 H. }& B) F B
Index, 指标/指数
0 Q0 a& ~( X% c, a9 hIndirect standardization, 间接标准化法
- i9 j1 h" x5 X1 {5 K9 PIndividual, 个体. O! s2 x9 U ]: B" I
Inference band, 推断带1 C4 i& |/ _4 F/ ?6 x
Infinite population, 无限总体
9 y7 K j) }# o9 \- U0 TInfinitely great, 无穷大* K$ A; u" L( p4 K
Infinitely small, 无穷小6 c$ B/ s. `1 `, a h
Influence curve, 影响曲线" ?) {( d* N4 x. Z% p% s
Information capacity, 信息容量8 N% M9 b% W' D) @. l6 T
Initial condition, 初始条件
' ~( E2 }, F" y; m0 PInitial estimate, 初始估计值/ ~9 @* M" \# J2 S! A5 Q
Initial level, 最初水平
5 E$ W, Q, c; z9 yInteraction, 交互作用0 v3 R& c6 }+ ~
Interaction terms, 交互作用项
% F& H, t$ q' Y! V" f/ |4 x bIntercept, 截距
9 b/ v5 H0 P0 P6 |: w0 p! G+ FInterpolation, 内插法
0 |( {2 G% u1 a' q4 M9 g# d q; lInterquartile range, 四分位距; c4 Y5 w; f/ V, ~( O
Interval estimation, 区间估计' F q/ ~1 g' s( y9 N" j7 P5 n/ F
Intervals of equal probability, 等概率区间0 X2 i3 d( y& o) F
Intrinsic curvature, 固有曲率! `: C, q* s6 A' v
Invariance, 不变性3 q {' _9 _( e3 I1 J
Inverse matrix, 逆矩阵
4 N# Q" P% L% G- u" U# R5 @/ bInverse probability, 逆概率, ]* K4 @! P# T, {
Inverse sine transformation, 反正弦变换5 a5 K9 j- i' ^
Iteration, 迭代 ' _1 G1 h: Q/ |
Jacobian determinant, 雅可比行列式
% A5 o0 C- l/ F4 N/ h3 u2 t! SJoint distribution function, 分布函数3 _. ~( h5 j7 e7 O, z
Joint probability, 联合概率( ]- M- W& s) J" K/ i0 W, Y
Joint probability distribution, 联合概率分布5 s. M/ E# z# y9 i# Z0 r
K means method, 逐步聚类法+ G9 e; c5 m: q3 l( I8 F. t; x0 ]
Kaplan-Meier, 评估事件的时间长度
8 F5 D& g) I$ ?$ }" \+ B" d( MKaplan-Merier chart, Kaplan-Merier图' Q1 i* E1 b2 y; r; F; n* d7 G
Kendall's rank correlation, Kendall等级相关
1 q1 f3 x3 U! Y: u& ?Kinetic, 动力学
. N1 e' \# H$ M' g0 x- L8 z3 e, QKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
. d, I. k2 x: }" `Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
% l- |+ N" T2 U" |! q( }1 v* A. ?Kurtosis, 峰度) r" n& D8 @) S1 o6 y
Lack of fit, 失拟& L; }. I$ Y% o( H: \
Ladder of powers, 幂阶梯3 V: N; [# f* ?: c4 B6 g
Lag, 滞后% _0 |# u# M. O" M. j
Large sample, 大样本
0 s0 ?) t9 L9 Y/ J- g1 ^- R3 ELarge sample test, 大样本检验
/ T) Q( \' k L7 sLatin square, 拉丁方
- G3 ?# Y. ]/ b; ?' P4 |# {Latin square design, 拉丁方设计* ^5 D% M% k1 c. V2 K
Leakage, 泄漏: {- [" v. m0 V
Least favorable configuration, 最不利构形6 w& |. ~) c4 H5 m3 V9 K
Least favorable distribution, 最不利分布
9 X% t- n, l# y: ]Least significant difference, 最小显著差法
# g1 ~# ~8 F4 b- A1 gLeast square method, 最小二乘法
" V9 ^% ] K8 M3 JLeast-absolute-residuals estimates, 最小绝对残差估计
9 I, F8 I9 ~( Y$ F( d( c: {+ tLeast-absolute-residuals fit, 最小绝对残差拟合0 N5 C1 |1 w1 s5 J2 R: P- {9 I
Least-absolute-residuals line, 最小绝对残差线
/ t- c9 l+ O" D6 C, K+ eLegend, 图例# l2 E) J i6 G+ F
L-estimator, L估计量4 O$ T% S% q2 f) k/ A7 |
L-estimator of location, 位置L估计量0 q- d7 q+ \0 f |5 J
L-estimator of scale, 尺度L估计量* M/ \6 a9 m, g0 @/ T2 o5 m* u
Level, 水平
. F' `: B. e/ K6 ?% Y) f1 hLife expectance, 预期期望寿命2 k' v" b4 j4 b. H- M
Life table, 寿命表
- e/ k/ n* j Z A, ALife table method, 生命表法" H$ q2 P: e* F, q0 p1 O# Q* g
Light-tailed distribution, 轻尾分布2 p+ |7 E3 t0 }/ H! M. c9 K
Likelihood function, 似然函数) W+ h, U" k7 B
Likelihood ratio, 似然比/ f# i h& P4 e, u1 G
line graph, 线图6 `( p( w2 B( q5 C, h9 U, Z
Linear correlation, 直线相关
1 p G! A5 V3 y! A* rLinear equation, 线性方程9 F" i4 z" [/ x. f, O9 K5 J2 `
Linear programming, 线性规划) q9 C) N0 h; X k3 b
Linear regression, 直线回归
3 I9 d) A' u' u5 w6 U+ x7 ALinear Regression, 线性回归4 D- u- Y, l; z$ ]/ m( P2 G
Linear trend, 线性趋势$ N. T4 D: ^! u. X. A2 \: x& A
Loading, 载荷 9 ^% b8 Z( Z( n0 d/ a3 _( K/ S( L
Location and scale equivariance, 位置尺度同变性
- |' e/ g6 { f$ Y: m4 aLocation equivariance, 位置同变性
: \* V9 h5 r4 }/ @/ M/ Z' MLocation invariance, 位置不变性4 @8 \$ R: a, I. D# l! D
Location scale family, 位置尺度族
9 _. ^) C6 ~2 p3 u+ B- i1 Y& SLog rank test, 时序检验
) X" g3 ]( J) j) O7 Z2 rLogarithmic curve, 对数曲线: Y+ P$ d) L4 y* R7 ` Q+ i
Logarithmic normal distribution, 对数正态分布 W/ Q, P5 r0 L, |$ W, p O
Logarithmic scale, 对数尺度" g. `1 e6 n6 |+ T/ Q+ i5 v
Logarithmic transformation, 对数变换
" Y( T) Q! C( ]- { A1 G" p! xLogic check, 逻辑检查2 b- ~$ ?6 s! {/ p/ B1 ?
Logistic distribution, 逻辑斯特分布
: O% X! r* y9 K; JLogit transformation, Logit转换
8 H9 @0 }2 i/ M) A) ~; VLOGLINEAR, 多维列联表通用模型 % j# a; N, ^; `1 T) C5 i, Q3 z, A' w
Lognormal distribution, 对数正态分布4 h' L X1 s9 {# W; c% x
Lost function, 损失函数
6 h+ Y _7 M" s+ N& b' I4 }Low correlation, 低度相关1 u6 l6 Z& S- h( t0 I
Lower limit, 下限
$ { t, ~6 K3 G/ pLowest-attained variance, 最小可达方差' g$ y% m+ q$ D8 Y: |; m
LSD, 最小显著差法的简称5 e' N6 c! R9 M! n
Lurking variable, 潜在变量
. i3 e! [9 s2 t9 LMain effect, 主效应
2 s' b, ^9 y7 w2 C6 p! S( ^Major heading, 主辞标目
) S0 Z6 X+ x+ @# d% p1 s7 sMarginal density function, 边缘密度函数8 y) a3 t( T1 c2 @: ~+ E7 w
Marginal probability, 边缘概率
0 h3 k5 y% {/ ^" S% g' }* bMarginal probability distribution, 边缘概率分布
7 c8 U! \0 X! X( ?6 NMatched data, 配对资料
! ]! G% D/ a2 Q8 FMatched distribution, 匹配过分布
8 O2 i5 V. B& D% i1 MMatching of distribution, 分布的匹配
7 J% g* F1 W) Q3 R/ nMatching of transformation, 变换的匹配- X; k" x5 i7 L; ?3 |
Mathematical expectation, 数学期望0 X5 r. F+ [1 p; Z( d9 r" ]/ g
Mathematical model, 数学模型
$ T- j; p" T q3 Q; HMaximum L-estimator, 极大极小L 估计量8 H; f, m9 h: z0 ]: t
Maximum likelihood method, 最大似然法$ C ?6 ^1 g& j ~. g( }( z1 l
Mean, 均数- `& p5 a; f" h
Mean squares between groups, 组间均方# I% h {2 g o& j1 `" X# g
Mean squares within group, 组内均方# i* c4 ^* B' t# S# ]
Means (Compare means), 均值-均值比较- Y% S6 n( X/ _5 _* M, ~
Median, 中位数: s& D; t) Q" c! ^) b0 L- F
Median effective dose, 半数效量
9 q* M2 P/ i, @+ L8 C, tMedian lethal dose, 半数致死量
+ L! D0 S7 c$ M" J$ N! KMedian polish, 中位数平滑
, |9 ~1 p" t9 eMedian test, 中位数检验
$ q5 T% h) J- N3 T! Q3 dMinimal sufficient statistic, 最小充分统计量7 x( Y7 E, {7 n! N$ @4 ^) P
Minimum distance estimation, 最小距离估计
% |* H8 p0 a; S8 E* m5 S5 m7 M8 y7 LMinimum effective dose, 最小有效量5 z+ s) B7 E2 G. G8 Q/ Z1 \
Minimum lethal dose, 最小致死量5 f2 T7 [: s- g. z0 o
Minimum variance estimator, 最小方差估计量: K" n- d* P- `4 t( K% P. Z
MINITAB, 统计软件包
! R. M$ h, s) `. S+ \" SMinor heading, 宾词标目/ _* F0 R* s. D# Y& H" v b% v
Missing data, 缺失值# a% [+ y# a" ^7 {7 P R6 z* A" ]
Model specification, 模型的确定
' b3 G3 u" k/ R5 n fModeling Statistics , 模型统计
% O4 f5 h% ~6 j) Y* I; }* iModels for outliers, 离群值模型- j4 i% ^" |) A. U5 Z
Modifying the model, 模型的修正
- _6 v3 }* Z T' {$ a, X% C7 W8 xModulus of continuity, 连续性模
# _9 L. a* _$ ^Morbidity, 发病率 ( a( x! v, [: h( ]. x3 K' J- l
Most favorable configuration, 最有利构形
3 `6 _/ {; o+ `, ~5 X8 ?Multidimensional Scaling (ASCAL), 多维尺度/多维标度
/ {2 p% L1 G4 Q/ x. sMultinomial Logistic Regression , 多项逻辑斯蒂回归 ~, _: @$ b: Z& P4 k6 k
Multiple comparison, 多重比较
0 z3 I- Q t* L! TMultiple correlation , 复相关" [( d6 J; A; H. A$ R$ Y3 w* {, f6 Q
Multiple covariance, 多元协方差, `- [6 e% S/ N, |7 e
Multiple linear regression, 多元线性回归; l; a/ G6 ~! K% H8 G& D/ ^
Multiple response , 多重选项6 U+ w1 d' |+ O! \& {" N
Multiple solutions, 多解4 i7 J: ?$ j6 N3 S7 Y0 h8 e
Multiplication theorem, 乘法定理! }, L3 X# K7 h# h& X$ M
Multiresponse, 多元响应
1 r+ J' j3 B; h- n/ L" k% `0 P6 E' RMulti-stage sampling, 多阶段抽样9 n' }6 b# L( o- [* m
Multivariate T distribution, 多元T分布' {* H a6 I" k. _
Mutual exclusive, 互不相容8 G, V; i! A% f
Mutual independence, 互相独立
1 `) F4 G; _2 ?9 N( k+ P- dNatural boundary, 自然边界% n' b/ p7 ?- z9 J. b" W
Natural dead, 自然死亡9 q- R' o+ V+ Q6 U2 _
Natural zero, 自然零) C0 t3 w% ]+ r# |# i% Q) l
Negative correlation, 负相关' S$ H# f/ o# D9 t; ~
Negative linear correlation, 负线性相关+ Q0 w/ U) ]( I4 M
Negatively skewed, 负偏
m" ^$ @& @9 `, A3 R. P& nNewman-Keuls method, q检验
! ~, L7 U0 c* ?0 j% |NK method, q检验7 m- m* ~0 a8 Q
No statistical significance, 无统计意义) r3 J, K- F7 \6 t
Nominal variable, 名义变量" z! W) R2 q% U6 O4 l2 M
Nonconstancy of variability, 变异的非定常性
6 e, U: w$ }4 I8 {) Q4 ?Nonlinear regression, 非线性相关. b4 t! C: _/ g0 T f
Nonparametric statistics, 非参数统计6 i" E$ ]. t( C6 _/ b0 U) N+ C
Nonparametric test, 非参数检验
8 N0 h" A* m; Y, @# w8 x1 }Nonparametric tests, 非参数检验% I0 ]8 `+ m9 f
Normal deviate, 正态离差, q8 P$ M( [- U" U; _
Normal distribution, 正态分布
& A" F4 d4 H, V7 Z+ e' gNormal equation, 正规方程组* j0 j% s$ s( ~8 E9 w* |3 ? V; v6 r
Normal ranges, 正常范围: m! @5 Y' j6 a
Normal value, 正常值, o/ q+ @9 A+ m& d3 S
Nuisance parameter, 多余参数/讨厌参数: t- M# }: x) N1 h, n: A4 O
Null hypothesis, 无效假设 & X$ T; k) }6 U: ?
Numerical variable, 数值变量
. O) U$ v8 i9 gObjective function, 目标函数
( C' @ @/ C5 G) YObservation unit, 观察单位
# W2 x, z4 \/ {# q/ {9 K. L, m2 XObserved value, 观察值1 H2 U9 t* o- t. G4 D8 I I
One sided test, 单侧检验& r* [$ H! C! ]6 j; Z
One-way analysis of variance, 单因素方差分析
+ O) }' o' w# v- c: Q% [) L8 N! L* COneway ANOVA , 单因素方差分析% d. u6 A6 @% h# i7 L$ c* }9 s; L
Open sequential trial, 开放型序贯设计 i7 q, K, {/ z' N0 {( V
Optrim, 优切尾0 x: a* ]' N" \. a+ y7 m
Optrim efficiency, 优切尾效率
3 m/ B) [! ?' W4 _Order statistics, 顺序统计量
; U0 V6 H5 m4 P0 }: @Ordered categories, 有序分类
& T& [" ^/ V2 h7 o5 c; U7 z2 e/ u4 jOrdinal logistic regression , 序数逻辑斯蒂回归( }, w7 k2 h8 J' G
Ordinal variable, 有序变量. T; s, L+ Z. R+ G
Orthogonal basis, 正交基
. I# \: K. j2 N7 C$ H! ~Orthogonal design, 正交试验设计
- p. q9 k) X4 dOrthogonality conditions, 正交条件
% U! Q6 K( Y) m$ l1 H" R% tORTHOPLAN, 正交设计 + ^/ S I, w+ w! }
Outlier cutoffs, 离群值截断点
& f" h8 C) |! m% a6 \% yOutliers, 极端值
" {' @) X) g& Q) l0 ?OVERALS , 多组变量的非线性正规相关 % x; }, x0 B( G% D6 k
Overshoot, 迭代过度
9 t& s: j( I+ J3 {# j6 \Paired design, 配对设计
- |# ^* k/ r! @( g( _# ^- t- LPaired sample, 配对样本# @" `, d X- R
Pairwise slopes, 成对斜率
9 ~% ^, f0 @0 c* Y6 }- w8 jParabola, 抛物线
3 t/ P$ p! V& A8 B! {! Q# U1 |- gParallel tests, 平行试验8 a2 Y5 \& a; l+ F4 o
Parameter, 参数
0 ^, s8 _. p# U. W% `" P* OParametric statistics, 参数统计- G2 e( z" V, E1 g: O! }- f
Parametric test, 参数检验
1 }) l* U( l6 `9 lPartial correlation, 偏相关( o$ S8 h; p, T- U! c/ P
Partial regression, 偏回归
, I- R) R" Y5 }Partial sorting, 偏排序- e/ Z# j5 e' n( W$ \
Partials residuals, 偏残差
# |2 l, u) i' [% B' N/ VPattern, 模式5 B( m6 r( F+ T5 m: E) z; g1 V
Pearson curves, 皮尔逊曲线
( ?. Z- n- T1 [# gPeeling, 退层
; ~* K' ]. H: p2 N9 sPercent bar graph, 百分条形图9 R/ e1 t- M2 j' \
Percentage, 百分比
G) K, M O# H2 ~2 g$ V7 UPercentile, 百分位数* L# V1 B$ W/ k! M- ]
Percentile curves, 百分位曲线
% \$ N% g! `' s' zPeriodicity, 周期性
. P! e1 J! P6 I- IPermutation, 排列
5 K3 S; Y" W) tP-estimator, P估计量
3 ^8 ^& Y& d$ p3 D2 T( w" {4 YPie graph, 饼图
3 L5 ~5 C: h3 E m5 p% ^ APitman estimator, 皮特曼估计量' _, u( D5 O, m9 r% }, r; j" z
Pivot, 枢轴量
2 D, k4 s Q: m O/ m kPlanar, 平坦
: L/ v; C% q" z- yPlanar assumption, 平面的假设
# V$ B, F- e3 [9 I- ~ ?0 yPLANCARDS, 生成试验的计划卡7 ~6 p _1 Y1 x5 P( z2 R& p; m. D
Point estimation, 点估计
1 T" W/ S3 y, s: E! pPoisson distribution, 泊松分布
% c |$ g$ ]6 [( m) u4 EPolishing, 平滑
5 W( v+ u2 K* o. U: v: C8 APolled standard deviation, 合并标准差
! `! s, ^+ Z# cPolled variance, 合并方差; j0 D+ O+ h9 H1 p7 v9 W* h
Polygon, 多边图7 g Y7 F5 X- w" Y; y4 I U0 h6 G
Polynomial, 多项式# L4 X% y. x9 o2 y0 V
Polynomial curve, 多项式曲线
8 \: d; P, F0 a* VPopulation, 总体
) g5 ]( [0 A" W1 g4 APopulation attributable risk, 人群归因危险度
- y6 A+ n5 s/ Q. I% BPositive correlation, 正相关
$ ~4 k( H0 E& NPositively skewed, 正偏: V4 i$ O& u0 K3 r- H3 j% V
Posterior distribution, 后验分布5 }% p- o9 c% J7 d
Power of a test, 检验效能
6 } F' {4 [" V9 W' `, C. l4 y$ _Precision, 精密度
0 ?- z8 `& X7 y" XPredicted value, 预测值) I4 d- l( m" s; A2 k; t% p0 F
Preliminary analysis, 预备性分析% P5 z1 U6 e- N
Principal component analysis, 主成分分析; D% o6 H4 [' T, j; J
Prior distribution, 先验分布9 s: h$ f" y% y" R9 |( f+ n- }
Prior probability, 先验概率
5 |6 s1 d* I6 G7 I8 R8 O5 H" D# oProbabilistic model, 概率模型
( r7 ]1 C8 z1 W* i( kprobability, 概率% T* R- L. a- e
Probability density, 概率密度* b1 l+ R. X! S* J7 A
Product moment, 乘积矩/协方差) @, n4 o: R0 c" a
Profile trace, 截面迹图9 d- r5 O* ^ S* D* U @- L
Proportion, 比/构成比
. k# b1 p3 p* W6 ?2 yProportion allocation in stratified random sampling, 按比例分层随机抽样1 g+ f8 }7 \- U9 B% M/ o& L1 i
Proportionate, 成比例
9 p% ]5 h: E/ V1 b/ o' ~9 ^Proportionate sub-class numbers, 成比例次级组含量, U" V: i5 L3 g" @& {# }0 }
Prospective study, 前瞻性调查
: z: d$ ?, s6 I' r+ z/ XProximities, 亲近性
1 `% ~6 }; J6 w! Q( }+ oPseudo F test, 近似F检验
% w5 Y7 u9 J. D% FPseudo model, 近似模型
/ V6 u$ V! }/ q, ~' ~3 P0 T! OPseudosigma, 伪标准差4 g( n- u; ~5 ~4 G
Purposive sampling, 有目的抽样5 T7 L, H- I( ^: X$ B" W
QR decomposition, QR分解
# Z' w" x1 R/ ?; S2 aQuadratic approximation, 二次近似
' ?8 r& z# B* q2 F& Z3 U, i+ }Qualitative classification, 属性分类# i* J" W5 f- R2 H- E( r' J3 V
Qualitative method, 定性方法/ \& D: W2 K9 x$ c/ G& R
Quantile-quantile plot, 分位数-分位数图/Q-Q图
: [( V! A( ?! U1 z; b' i- xQuantitative analysis, 定量分析; Y' \# l/ `7 k6 [9 ]# ]
Quartile, 四分位数* j7 P) y& N# k2 h8 P
Quick Cluster, 快速聚类) k0 y& G+ W3 w, A% b2 k7 n! i; t+ T
Radix sort, 基数排序
! J1 n! N) a8 D9 R5 a$ y# o4 p9 ?Random allocation, 随机化分组5 J7 Z3 Z+ u5 S; H) \" s
Random blocks design, 随机区组设计
; A; _# K) V3 I' I2 s. R# xRandom event, 随机事件/ D _" Y9 t; k5 Y) G0 F
Randomization, 随机化
2 O% [# K9 U: IRange, 极差/全距
" Y# a$ T" t& v( L$ T) N$ `Rank correlation, 等级相关1 s8 m- r) l3 q( ~0 B
Rank sum test, 秩和检验
V3 [' h w) }- h$ ORank test, 秩检验
+ h! [# ^4 f- ^Ranked data, 等级资料4 f' M0 ]. W' {' A; `/ B
Rate, 比率+ _5 r( U/ _8 ? _( h+ Y
Ratio, 比例 N6 Y& U/ k- _) K" N
Raw data, 原始资料
! r2 _; e( \- J4 @- aRaw residual, 原始残差
4 q1 Y5 s- T* ^( o( d+ U! nRayleigh's test, 雷氏检验
: V1 G$ {& N; z7 ?$ O* WRayleigh's Z, 雷氏Z值
4 N6 ]& A2 o" S; @Reciprocal, 倒数8 Z6 T& I8 @; t& I5 o% t' c3 r
Reciprocal transformation, 倒数变换
( `3 Z% I& t) G3 g9 R4 ZRecording, 记录7 h3 [: C6 H" |7 l. `1 D% V
Redescending estimators, 回降估计量8 `& S0 s1 e- b, J3 o
Reducing dimensions, 降维
- F0 u. Z# l2 SRe-expression, 重新表达& r' B2 L9 k2 I4 q# j
Reference set, 标准组7 L* _5 C" m0 @7 T9 N
Region of acceptance, 接受域. s8 @5 K3 l$ t) S
Regression coefficient, 回归系数
2 u# r$ ^$ \9 C% gRegression sum of square, 回归平方和
- U8 n( l. z+ b; Y% D: BRejection point, 拒绝点8 j0 i$ Z& e! W6 _2 h
Relative dispersion, 相对离散度: t6 S! s: j& Z- o
Relative number, 相对数5 E F# d1 z' s' Y; I
Reliability, 可靠性6 g' ~6 E6 _: x3 H
Reparametrization, 重新设置参数
9 f/ Z; d( h r) L2 ^Replication, 重复: m# V! H9 O* q1 q- A
Report Summaries, 报告摘要% q4 h. }* J- i* i2 ?
Residual sum of square, 剩余平方和
' U u% L/ @7 q; J' |& P8 ~5 a$ [Resistance, 耐抗性
, s- ?3 z6 \1 y* B% j, nResistant line, 耐抗线/ L- J+ J# |: y1 X4 x% x
Resistant technique, 耐抗技术
]! I3 n3 v; h! t( H# l8 TR-estimator of location, 位置R估计量
( \( X( O- E9 h5 g. wR-estimator of scale, 尺度R估计量
( t3 g) u) R4 {* n1 Q7 }- JRetrospective study, 回顾性调查7 W* u& P7 Z5 X( y5 }
Ridge trace, 岭迹
5 C! O0 p" v. S6 _* x, {Ridit analysis, Ridit分析
+ Y& |+ [- L( W: I' J0 m5 r0 \Rotation, 旋转
/ H5 ^5 t. @- h6 c6 y0 D0 ^Rounding, 舍入
( Q* B; P8 e8 g- vRow, 行
/ o1 q: @1 r+ n* xRow effects, 行效应
/ Y" N) P. P0 A' y/ x2 |& T" Z8 MRow factor, 行因素
' g* J% k! x! e& f( f/ H2 ~RXC table, RXC表
- ]6 j4 p. v: |Sample, 样本0 @- @3 G* j* S% g6 q
Sample regression coefficient, 样本回归系数
' r! }8 t0 e- t, x- R7 i6 KSample size, 样本量+ z/ m3 @& \ q% z+ K- D
Sample standard deviation, 样本标准差
' c% ` o' W' c) Z) l. N4 w2 iSampling error, 抽样误差6 |5 J4 s! \0 ?6 _5 Z, Q
SAS(Statistical analysis system ), SAS统计软件包* o$ i( S" r; Q4 d2 h, E2 n
Scale, 尺度/量表
4 e, H* q! j, `: N1 YScatter diagram, 散点图- Q2 V" ~* }8 b9 j* R; j
Schematic plot, 示意图/简图
0 V( x- y7 z: g0 |: i8 g8 p4 HScore test, 计分检验
! K# W# @) u" m& hScreening, 筛检
; q1 V- J' G; j3 N) X: l5 a* ~SEASON, 季节分析
' h/ w! a4 p) I+ u) I% LSecond derivative, 二阶导数
* |# I0 S0 u9 GSecond principal component, 第二主成分+ _0 y: k5 A! [% c- a$ x$ C
SEM (Structural equation modeling), 结构化方程模型
7 c: T/ O5 W1 u$ m8 l# ], u' i" sSemi-logarithmic graph, 半对数图
# c( C- V) H# M- qSemi-logarithmic paper, 半对数格纸! c0 y2 K, `$ e, S2 G* Y* ?
Sensitivity curve, 敏感度曲线) ?6 F( W$ Y6 U+ w5 U) C
Sequential analysis, 贯序分析$ x- ]1 V" O- N+ E( k' T- Q
Sequential data set, 顺序数据集% C7 C+ O9 T {) A) V5 [/ c1 ]
Sequential design, 贯序设计% j y Z* M, {
Sequential method, 贯序法- s1 k% Q' r) d' K
Sequential test, 贯序检验法
, r4 J$ c5 a' ISerial tests, 系列试验5 N. f. k* D$ ^$ G9 L
Short-cut method, 简捷法
4 K8 G Y8 z# N& e: YSigmoid curve, S形曲线
" i T8 T6 j8 S5 x0 u: DSign function, 正负号函数" G' u5 b- {& P3 J
Sign test, 符号检验1 ]2 V0 b; |8 v f2 F) V
Signed rank, 符号秩
: v! o& k7 E" DSignificance test, 显著性检验9 {* r% Y p4 Y" [
Significant figure, 有效数字
* P) a H( M! }4 E# s+ nSimple cluster sampling, 简单整群抽样, T, M% x6 X* E2 U3 U9 K
Simple correlation, 简单相关! M! m( M1 `' b2 u f
Simple random sampling, 简单随机抽样, `, Q& K* H2 `6 [" f8 H
Simple regression, 简单回归9 }. T# Q: p9 R; G+ Q
simple table, 简单表' v5 \5 w' ~. N& S8 Y
Sine estimator, 正弦估计量
4 n5 ~$ _) V$ U' l4 p! \& _Single-valued estimate, 单值估计: Y9 j8 T. P( ?9 d
Singular matrix, 奇异矩阵0 C. K2 n$ [* p# B0 S$ G' b
Skewed distribution, 偏斜分布" N+ m% `' X* ]$ |
Skewness, 偏度
, T+ E6 Z% p H! k& G$ t5 u5 OSlash distribution, 斜线分布
4 V3 J0 E" W' e" FSlope, 斜率
. k6 f1 l* e2 G5 n; ?Smirnov test, 斯米尔诺夫检验) r; }4 m7 c" W* \/ m I+ r5 [8 v" o4 r
Source of variation, 变异来源
: e) J1 G% S3 Q$ }Spearman rank correlation, 斯皮尔曼等级相关
3 x7 H( P6 v* q6 u, u: eSpecific factor, 特殊因子
5 e/ m$ F r5 k$ D2 LSpecific factor variance, 特殊因子方差$ ~ q& {" d. m2 i
Spectra , 频谱5 \! Q& ]' ^% H- x
Spherical distribution, 球型正态分布5 C/ q6 x3 f( @" K- E
Spread, 展布/ g6 m+ T G2 b
SPSS(Statistical package for the social science), SPSS统计软件包
3 t7 w0 ~, W0 o9 \+ f. z! ]& gSpurious correlation, 假性相关
1 i6 s5 Q0 n0 @) U" s0 }9 S2 ~Square root transformation, 平方根变换+ K2 D; E! V* T3 Q b
Stabilizing variance, 稳定方差
* p! f% I& c( rStandard deviation, 标准差3 p4 y7 K! K& u5 Q7 N8 O4 K
Standard error, 标准误
; B% z6 e* M. I( ^( |- eStandard error of difference, 差别的标准误3 y) A: T1 h2 {" O
Standard error of estimate, 标准估计误差8 {. [6 { E7 n+ r, j' x+ h5 _
Standard error of rate, 率的标准误
q% r' ^7 z' W* s' dStandard normal distribution, 标准正态分布5 `% u* q! j0 I2 g
Standardization, 标准化6 s- i& |* R h3 b9 W5 u
Starting value, 起始值5 l& @6 \3 N. }4 ?3 _) {
Statistic, 统计量% Y% c" F; k4 D, J7 k
Statistical control, 统计控制
3 a! X u1 Z: X8 f2 F6 X8 ]Statistical graph, 统计图
8 e5 @6 e e1 mStatistical inference, 统计推断( c+ l! c& D5 I6 z7 E- _6 R
Statistical table, 统计表8 x0 d% | [5 }. y# }
Steepest descent, 最速下降法% U% A5 ?" d ?$ ^# S
Stem and leaf display, 茎叶图
" X! d/ M( V9 U% J' j4 H9 ]5 KStep factor, 步长因子4 O/ |5 G9 Q! U- }" G3 h
Stepwise regression, 逐步回归( t2 Z# Q8 l K! @0 r0 l( @
Storage, 存( p2 n; J+ d* W8 f: w
Strata, 层（复数）+ r, y9 f5 {! [( p/ Z# l; {4 Q
Stratified sampling, 分层抽样
$ m& D+ o k' H5 g0 } \Stratified sampling, 分层抽样
( ~2 N/ m3 d5 ]# b: {Strength, 强度: }, w+ ]# C0 a M
Stringency, 严密性
7 D$ x! ?* h7 G2 [Structural relationship, 结构关系
9 W6 p; s2 V, \" R1 i4 RStudentized residual, 学生化残差/t化残差! }; L- T" L d
Sub-class numbers, 次级组含量
9 ` n5 ?: d# Z9 B- GSubdividing, 分割
1 {# @) M# t& M, p2 a/ ESufficient statistic, 充分统计量
7 O- p5 f5 z) ASum of products, 积和# p/ z: u. T% k6 R* b1 `2 G; \
Sum of squares, 离差平方和( V1 H, }1 V' l& w% z$ y) I5 N
Sum of squares about regression, 回归平方和3 J& i- e, R# u
Sum of squares between groups, 组间平方和
' n/ h: ] D% s6 q8 hSum of squares of partial regression, 偏回归平方和& `1 H' K8 O( a( D
Sure event, 必然事件
; [$ a1 t, }4 ^* cSurvey, 调查# g) u/ A" j$ n6 p7 { _
Survival, 生存分析
6 ^/ R4 P2 T0 S0 [% e9 T7 tSurvival rate, 生存率
4 W2 ?$ Y, u QSuspended root gram, 悬吊根图
" m" s& L8 e/ y3 h# n4 NSymmetry, 对称3 ]+ W* L; ^- X2 K
Systematic error, 系统误差
' u$ k. j; J1 ~Systematic sampling, 系统抽样
+ k L) q$ Z4 w+ y) hTags, 标签 U' H; l5 G1 k& J) z
Tail area, 尾部面积8 q0 l& w# t. `6 R1 l3 f
Tail length, 尾长, `& Q5 c* E+ }8 ~
Tail weight, 尾重
* R \5 M% Z8 t& O; D+ ^# ~! }0 F$ N& @Tangent line, 切线) P, H; m" p# ~: G- ]5 K& \
Target distribution, 目标分布
# _: l2 P; C: ZTaylor series, 泰勒级数
( `' j4 X+ k# E H6 B$ RTendency of dispersion, 离散趋势0 r0 y8 H% d; G' ]; ^+ _, j }
Testing of hypotheses, 假设检验
9 t: l: R% _! g: s# rTheoretical frequency, 理论频数5 w( V4 B: @0 k
Time series, 时间序列$ J# `2 H* b: c- W' I8 G. P, e8 U
Tolerance interval, 容忍区间, |5 s$ b& c5 y7 A
Tolerance lower limit, 容忍下限4 B% I- G ]2 P2 X/ U8 Z5 l9 F
Tolerance upper limit, 容忍上限
7 y& p: p8 m6 d! p+ M9 t8 yTorsion, 扰率
0 _( T* m2 h0 h) |' t4 GTotal sum of square, 总平方和
A' ^9 E: A, y$ u5 b, vTotal variation, 总变异
0 q; ~) R4 K# u% `1 e+ zTransformation, 转换) R) z% _6 V0 M, L8 m$ V
Treatment, 处理
, ]& s9 K; g" s7 f5 e7 [ n8 {Trend, 趋势
6 A9 ^- q4 g5 @5 hTrend of percentage, 百分比趋势
' I, m: O/ B! L. z) [% RTrial, 试验4 \" x+ @$ c5 w1 O! y2 |3 N" a
Trial and error method, 试错法8 G9 h" ]; b0 w9 E4 g9 Q9 u
Tuning constant, 细调常数
2 J- Z0 a- S' ]6 z9 e+ h. @Two sided test, 双向检验
8 K9 ?* a4 X3 a- t. d6 ~: WTwo-stage least squares, 二阶最小平方
% p9 X( @5 r1 `7 c4 KTwo-stage sampling, 二阶段抽样
: a+ b$ e7 `7 V vTwo-tailed test, 双侧检验/ [7 L5 I _7 t
Two-way analysis of variance, 双因素方差分析3 l4 b% |9 A. |$ E& h
Two-way table, 双向表
- b) w/ ?/ v4 GType I error, 一类错误/α错误6 j: K5 ^* e7 m9 h: {
Type II error, 二类错误/β错误! Y3 A# Y4 V% J) T! a
UMVU, 方差一致最小无偏估计简称 D/ k: H0 c/ M* {( g& h, v9 a
Unbiased estimate, 无偏估计
* k6 K) Z$ ~$ u* \2 W$ D) QUnconstrained nonlinear regression , 无约束非线性回归
3 }$ p, A0 G/ F3 ~# P' G2 BUnequal subclass number, 不等次级组含量; F1 f K! ] R l! Q" h
Ungrouped data, 不分组资料
4 U r7 Z$ C1 a( ]; Y* DUniform coordinate, 均匀坐标
" I. X, _9 b# M1 h* rUniform distribution, 均匀分布! j2 r; v6 K! Q! s
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计3 b3 a" Y- r% ^1 C( l7 H5 ?; p
Unit, 单元
6 X; b* w: b1 pUnordered categories, 无序分类" z& l- D& U4 b$ l R6 Q, ^( g9 d
Upper limit, 上限- G3 c# v y2 ^. C+ B1 v3 @
Upward rank, 升秩, t c# Y8 _$ ^( r
Vague concept, 模糊概念
& ]+ \$ U( u7 p u/ gValidity, 有效性
4 E* y0 p1 a5 y3 wVARCOMP (Variance component estimation), 方差元素估计
3 h! N9 n/ a; `! W, t# R9 s5 KVariability, 变异性: c+ Q0 b! {8 Y- ~( v7 {) Q
Variable, 变量
5 b! o- N0 {0 t% @2 X8 @$ [Variance, 方差 R% ?. d( @- A8 g9 a
Variation, 变异
2 C, D( U+ |: T" }/ }Varimax orthogonal rotation, 方差最大正交旋转
5 f6 S1 g2 _, X) i2 fVolume of distribution, 容积
1 n6 m/ h1 ~7 X5 b o4 P) y4 n5 \' [/ wW test, W检验6 T# o4 p* K* V9 ^
Weibull distribution, 威布尔分布: w k( b- o) n' G% B# J- L6 u3 g
Weight, 权数
$ [( _) Q3 t5 i t2 e' K8 ZWeighted Chi-square test, 加权卡方检验/Cochran检验
; D5 ?* \% j, T2 C9 A4 R; P! EWeighted linear regression method, 加权直线回归
; J' k9 v% b7 _+ [% r/ `+ i$ MWeighted mean, 加权平均数& F+ z$ C& @* a$ F- }; M0 o; f) V
Weighted mean square, 加权平均方差
& U# K6 v* P: J2 O+ }$ J) aWeighted sum of square, 加权平方和
% b( A3 l" k3 c/ c3 ]Weighting coefficient, 权重系数
% X$ O7 C7 ]) G9 vWeighting method, 加权法 9 r& m8 k! ^$ f4 p; ^6 T
W-estimation, W估计量& |0 E% F! J' y! C" [. X
W-estimation of location, 位置W估计量
7 T1 _$ _& v/ @/ s j* s! [1 zWidth, 宽度
0 f' l7 _0 V* [; VWilcoxon paired test, 威斯康星配对法/配对符号秩和检验$ O0 ~8 ?, }; ?" Y5 J2 y' {
Wild point, 野点/狂点
& k1 K5 ?! A+ {9 Q, TWild value, 野值/狂值9 X, g9 ~( s/ n6 X
Winsorized mean, 缩尾均值2 W1 l3 K. d* V! ]2 z
Withdraw, 失访
7 m) ^/ H0 H. U4 K6 ~# PYouden's index, 尤登指数
3 Y2 ~* h( L9 a+ qZ test, Z检验
- X6 y4 f& @* W$ Y" N9 k3 cZero correlation, 零相关
8 S5 P% J/ a, o/ U, sZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
