|
|
Absolute deviation, 绝对离差" O' q. d) e& V# w6 |5 f* J; Q$ {3 [1 W
Absolute number, 绝对数5 X/ D, f! n2 c/ K. T
Absolute residuals, 绝对残差: P! v2 B | j ^2 w+ k
Acceleration array, 加速度立体阵2 V$ o5 P3 U, d: |) b1 O r9 W, C$ E9 q
Acceleration in an arbitrary direction, 任意方向上的加速度
& K: B; g6 [2 s2 {Acceleration normal, 法向加速度
; N3 J/ Q$ {. E# T5 J2 p: c# dAcceleration space dimension, 加速度空间的维数- O+ z' I* B( h g
Acceleration tangential, 切向加速度, S- m& z& C; b3 O; N( b+ {
Acceleration vector, 加速度向量
. i: n9 W) R# O: C" R2 H) z- LAcceptable hypothesis, 可接受假设 C A6 u5 v! z/ K% |$ L# n
Accumulation, 累积
5 X8 f3 A/ s* g2 S# I2 cAccuracy, 准确度2 |- F @8 z( X. ?/ U; @6 |
Actual frequency, 实际频数
1 o; r0 P9 v( X( o( M0 oAdaptive estimator, 自适应估计量
, I2 P& F7 ~ L* [6 sAddition, 相加) [( r6 N7 L2 h- c
Addition theorem, 加法定理; w+ @7 P/ l X, u/ K+ r
Additivity, 可加性2 q9 T8 i& }, H5 ^3 s
Adjusted rate, 调整率
, @+ j( }: P% n7 y+ G: i& h' A: n/ }9 PAdjusted value, 校正值1 j: B: D% A% P1 C4 E
Admissible error, 容许误差7 ~: v W8 ]3 v' z
Aggregation, 聚集性. l, ^! H2 I- ^
Alternative hypothesis, 备择假设+ B6 n% H% `5 p: p" \
Among groups, 组间
# O8 Y7 f& J3 r) lAmounts, 总量$ b: {) }- h1 O1 Y4 x3 k
Analysis of correlation, 相关分析+ {$ k1 k6 J& A" B
Analysis of covariance, 协方差分析, j( e% K: R; x# [
Analysis of regression, 回归分析
0 i; S% {& D9 l/ W) B6 C( s8 a* tAnalysis of time series, 时间序列分析
1 N: L& }4 G, D; d& ZAnalysis of variance, 方差分析
+ S/ b: {* @! A ^- T7 p5 KAngular transformation, 角转换
( ^2 X: i; m6 O6 [: [ANOVA （analysis of variance）, 方差分析
2 w& f' P$ c" ]7 w" DANOVA Models, 方差分析模型
: M1 W9 O% X3 h& _Arcing, 弧/弧旋) W: _" ?5 w" _9 \; N. M
Arcsine transformation, 反正弦变换
4 G4 {, L0 Z* x) W& T" z/ {" F3 pArea under the curve, 曲线面积% @' p/ b8 [& H m/ L# u$ q- A
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
% V! f. r4 a4 N2 a( f1 x/ ?ARIMA, 季节和非季节性单变量模型的极大似然估计 " |/ r3 X5 q, e1 _9 N& N: [
Arithmetic grid paper, 算术格纸
6 m/ ?% d; Y4 v y2 pArithmetic mean, 算术平均数- R+ {, v0 E0 S0 z2 ?
Arrhenius relation, 艾恩尼斯关系% N% J4 J& X4 a8 c! S( p
Assessing fit, 拟合的评估$ @6 |& G% G! v/ p# b" {
Associative laws, 结合律3 ^- {( K' o. W" \# l0 C
Asymmetric distribution, 非对称分布
0 D _6 f# [ @3 UAsymptotic bias, 渐近偏倚 K) Y3 @1 Z; m
Asymptotic efficiency, 渐近效率$ B& F A, J) c3 d) d( m. t
Asymptotic variance, 渐近方差
: a' F* q- ^, C3 ]3 ^Attributable risk, 归因危险度% g2 \: y X$ V. c8 t" f5 n4 _
Attribute data, 属性资料* [& v4 E6 ^3 ^2 r4 Q- \4 _7 @
Attribution, 属性* Y2 f$ x( O, _) p! P; h
Autocorrelation, 自相关. c+ t2 f c& u$ s# N: |8 A
Autocorrelation of residuals, 残差的自相关" d% D- m4 A* T) P. R7 u
Average, 平均数8 f2 N1 W" `# p9 a$ i% S* Y4 f6 y
Average confidence interval length, 平均置信区间长度6 A9 j+ y3 t9 f, `/ s
Average growth rate, 平均增长率
5 o7 p. U# A& D" o0 lBar chart, 条形图$ Y7 k8 i9 @' \
Bar graph, 条形图( F1 Q+ g- p% ~$ t5 v s
Base period, 基期, \. h5 H0 F- B% {4 \
Bayes' theorem , Bayes定理4 B) g. C9 |1 U/ Y1 O9 D
Bell-shaped curve, 钟形曲线7 k+ G4 i3 g, m. E
Bernoulli distribution, 伯努力分布
7 n! r* y& R3 \9 g7 gBest-trim estimator, 最好切尾估计量. k4 d. t8 T" g" |% J& a! E* c
Bias, 偏性; z8 v8 |+ O* Q/ M1 ?' z( q
Binary logistic regression, 二元逻辑斯蒂回归
; k4 r$ N! k4 ~* [# z/ m+ Q! IBinomial distribution, 二项分布
8 X2 i& q; B( e# P8 JBisquare, 双平方. {1 i i3 s7 l2 u, t
Bivariate Correlate, 二变量相关
3 N3 H- S% r' H8 u i2 s' pBivariate normal distribution, 双变量正态分布
' y& t3 q7 p- R( I8 eBivariate normal population, 双变量正态总体: D0 e) x4 V; z. I j1 F! {6 f% R$ A
Biweight interval, 双权区间
; y5 R/ J7 \. E% j9 q3 W4 [Biweight M-estimator, 双权M估计量1 u" F9 M, s4 `7 s" Z
Block, 区组/配伍组
5 @- i$ @; [- Z$ Z, q+ _9 L/ I# h8 ]BMDP(Biomedical computer programs), BMDP统计软件包
2 W" M: }+ O& H( aBoxplots, 箱线图/箱尾图
7 \) |% h6 U: Y( @4 P$ a% ]Breakdown bound, 崩溃界/崩溃点" v/ |# ~- K* P @% X6 F
Canonical correlation, 典型相关5 y! f1 s0 a" w4 H# n( }# q
Caption, 纵标目; l2 x! g3 X* I: ]
Case-control study, 病例对照研究
6 ~* R9 V8 Z) e" _Categorical variable, 分类变量) r4 n& D9 [: F7 G
Catenary, 悬链线' D( c x( E X
Cauchy distribution, 柯西分布! Y0 Y t% L, @
Cause-and-effect relationship, 因果关系: c/ l" {. Z3 v
Cell, 单元
. _! I8 F8 g x- o. l: j, H8 ?; GCensoring, 终检
1 X$ ]9 V J3 b) D1 g) JCenter of symmetry, 对称中心& W8 _( D( U& e O
Centering and scaling, 中心化和定标1 I+ ?2 ?* D j
Central tendency, 集中趋势+ _( q# y( r7 z. z* y3 f/ ^
Central value, 中心值
- g! c9 i. X- p7 c; K* V. XCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
% u1 B% ^. Z. T r2 {" z" oChance, 机遇
% q% a6 b7 U" m+ L ^6 xChance error, 随机误差# L1 A, Y$ x3 y6 L$ q
Chance variable, 随机变量 n$ t4 O9 o6 t
Characteristic equation, 特征方程2 {) K. m0 G3 K1 Y* U
Characteristic root, 特征根6 `9 j) ?3 e4 H5 ?/ I
Characteristic vector, 特征向量
7 D) F, N# M0 y9 J Q4 K3 G! n) GChebshev criterion of fit, 拟合的切比雪夫准则
! w" V8 X% O `5 m6 Q7 K' ?2 YChernoff faces, 切尔诺夫脸谱图
& S/ q9 ^: _' g7 f: F- C) i: EChi-square test, 卡方检验/χ2检验4 y9 f- L' D, [2 j, }' y
Choleskey decomposition, 乔洛斯基分解
+ R( w) P' b4 C" T PCircle chart, 圆图 $ y. W) E. e+ j
Class interval, 组距
& d4 q4 F e7 TClass mid-value, 组中值
; c: e( Z$ H4 t3 ]% QClass upper limit, 组上限0 Q5 Q3 C! J* G5 r- D6 @6 {* M' E! ~1 y2 i
Classified variable, 分类变量: C+ H4 ]6 A+ }) u- ?
Cluster analysis, 聚类分析
, j& B* @0 c* U, ^Cluster sampling, 整群抽样, A G# ?( d0 C( F0 j R% ~) A
Code, 代码* \& R* Z; s7 C8 Y6 d% V
Coded data, 编码数据
/ r0 l; T+ y- V& q/ yCoding, 编码4 y/ H( S7 A7 G, r7 o
Coefficient of contingency, 列联系数 k m$ y$ _% b# E1 O% b+ o' P
Coefficient of determination, 决定系数
L9 [+ m+ ~1 ~3 r% c6 F# MCoefficient of multiple correlation, 多重相关系数
; c* A* U7 h' t3 } B' e% vCoefficient of partial correlation, 偏相关系数) Y$ c4 L" t0 q- T( H& w
Coefficient of production-moment correlation, 积差相关系数
9 y- o2 X5 `9 c( _* zCoefficient of rank correlation, 等级相关系数; Y. e+ T9 y+ H! g/ }2 h
Coefficient of regression, 回归系数9 F* \ d! ?; L+ W
Coefficient of skewness, 偏度系数# s" O. k; w5 }3 C ?0 \' I8 {$ Q
Coefficient of variation, 变异系数
1 {) D. U9 n2 K( ZCohort study, 队列研究0 {3 [) y# w( U0 C* o* S6 d+ Y, y1 E
Column, 列+ A w P% z' p2 @2 L
Column effect, 列效应% H, M+ n5 b, a
Column factor, 列因素$ ~% x5 r: X; `+ ?
Combination pool, 合并
4 R, F8 R. g* O9 o" BCombinative table, 组合表1 H! r3 L7 R s
Common factor, 共性因子/ b1 T) g0 }$ |
Common regression coefficient, 公共回归系数7 b- x& f; i6 y0 u# K6 s" ^
Common value, 共同值
7 k& U6 {( |7 r& p% w( `Common variance, 公共方差- |2 G4 l; B3 U) S7 [; d
Common variation, 公共变异 t3 e6 N% f0 m
Communality variance, 共性方差
% X; C$ O6 k/ c) L! Z/ V3 j% x. mComparability, 可比性
% ?$ K' b6 F0 J4 vComparison of bathes, 批比较
6 P' P% }8 P" N! \( ZComparison value, 比较值
- T, A" f0 j2 d6 @3 a3 W3 h, lCompartment model, 分部模型. h" }& h+ M3 s4 L, Y- z$ A
Compassion, 伸缩
# `! R5 f+ k" j* h( XComplement of an event, 补事件
. W d; J5 W: u) DComplete association, 完全正相关% Z2 L) f; N5 _
Complete dissociation, 完全不相关
" K0 E5 J ^# P# Z2 _% qComplete statistics, 完备统计量
, r* Q+ f- A! rCompletely randomized design, 完全随机化设计* {% c- Q8 q! W3 J. \ m
Composite event, 联合事件
) L& N2 I9 }8 fComposite events, 复合事件
7 e8 n5 {( j1 |- S% A5 F& yConcavity, 凹性& d% X# o* T; V2 \
Conditional expectation, 条件期望' d* K5 O1 C! W
Conditional likelihood, 条件似然
) c W) I+ _/ G# ~9 a0 Z+ G, IConditional probability, 条件概率
3 F, E( ^# h. XConditionally linear, 依条件线性% T6 q! H: r7 E3 j& Y6 |
Confidence interval, 置信区间
2 A1 s8 g' B- S: T( gConfidence limit, 置信限
, y6 y( V" Q0 i; W% c( `) F, ^Confidence lower limit, 置信下限
; a5 ]4 h- p% b! Y/ d2 l- B( d% CConfidence upper limit, 置信上限% D V) s d/ t5 s
Confirmatory Factor Analysis , 验证性因子分析
5 B3 h" g9 }9 U) a+ IConfirmatory research, 证实性实验研究, E( O X% U' V4 R9 u, T9 Q
Confounding factor, 混杂因素
* y1 u/ I; S3 A! R' ZConjoint, 联合分析
2 X; C# I# R1 M* I6 ~7 F- ?. uConsistency, 相合性
. H) B: E) _' R& \' d$ R" pConsistency check, 一致性检验! Z9 T( p0 T5 V3 A
Consistent asymptotically normal estimate, 相合渐近正态估计3 ? X" c, O- r' A
Consistent estimate, 相合估计4 u1 s% e/ J' S" c( m+ [4 r
Constrained nonlinear regression, 受约束非线性回归
% X. L! D5 k: L6 wConstraint, 约束" s+ r" ]: a _( U8 K4 A9 n- R
Contaminated distribution, 污染分布7 G% h- w- \, n0 v$ f
Contaminated Gausssian, 污染高斯分布
+ Q+ G5 _: _: c6 nContaminated normal distribution, 污染正态分布6 \/ m* j4 D M9 O* z4 U8 W
Contamination, 污染3 `7 k- |" h8 w9 E% K
Contamination model, 污染模型+ M0 G. l' X# V! F# q Y
Contingency table, 列联表% ?8 D. x; n+ x b! x
Contour, 边界线3 M. x. G$ i2 J6 M1 M) Y3 b7 W
Contribution rate, 贡献率
& B2 B1 I/ l" ~) e: \Control, 对照% X! G* U, P( Z- b/ F
Controlled experiments, 对照实验+ O" `8 P( W( Y& w2 Z0 |
Conventional depth, 常规深度6 \. ]) I/ [: @. r, n
Convolution, 卷积
8 t, m; _0 X/ X0 B6 L% vCorrected factor, 校正因子
4 b# Z; ^6 o0 f. aCorrected mean, 校正均值
+ B' H3 W! K! x0 Y/ ?9 a1 |' GCorrection coefficient, 校正系数. p7 c2 b+ n0 P8 U7 V
Correctness, 正确性
9 y, R) U/ w dCorrelation coefficient, 相关系数) ?# ?1 f( h3 ^+ f
Correlation index, 相关指数; q/ W% _, a+ t8 r* Q
Correspondence, 对应2 p1 n; _3 B5 _6 G+ ]$ M: V5 E0 g
Counting, 计数
7 K9 e9 [) J( ~ l' s% GCounts, 计数/频数: B2 ^3 }, E- p" f
Covariance, 协方差3 D5 @* C* j" W$ U _" O
Covariant, 共变 2 S0 n' W& X$ U5 o, r; E% x
Cox Regression, Cox回归
" E# g* w( ?8 G$ `% @9 WCriteria for fitting, 拟合准则7 y2 O! A, w& g1 \0 U* [
Criteria of least squares, 最小二乘准则
! F! i. n: \- u6 \0 x( r( sCritical ratio, 临界比/ @/ R% \2 g4 J' E& g
Critical region, 拒绝域
/ o: V! S( }3 S1 a0 S( cCritical value, 临界值
1 z8 h! u+ _/ F) m' e6 L0 ]- @Cross-over design, 交叉设计! }* |0 i* T. E0 Q
Cross-section analysis, 横断面分析
2 i% `$ W: C4 `) b+ P/ F, C s; ECross-section survey, 横断面调查. A' }: R: Y5 V5 @8 H! j
Crosstabs , 交叉表 * G3 A( @* S7 e+ w
Cross-tabulation table, 复合表4 i R9 o4 Z: C3 Y% P9 G l2 t' P
Cube root, 立方根
$ p* O6 m6 i) r! N1 V6 c u- kCumulative distribution function, 分布函数; G" G6 T9 x) g/ ^
Cumulative probability, 累计概率
# P4 Y4 F1 t4 f% ~/ nCurvature, 曲率/弯曲
" D& I) m2 Q1 k0 {Curvature, 曲率/ p6 o3 a3 j+ [" o
Curve fit , 曲线拟和 ( |6 Z0 U4 k3 C; X
Curve fitting, 曲线拟合
3 D5 P4 j8 {* g- l, iCurvilinear regression, 曲线回归
3 g, q# h% W: |1 Q/ \4 ICurvilinear relation, 曲线关系( T% |- |9 \# Z7 n1 \
Cut-and-try method, 尝试法
, c" Q2 k% n' E* wCycle, 周期
+ ]' I8 _5 b9 A; N0 Q! nCyclist, 周期性
; T/ s3 p1 ~" d3 j8 ?* r: a% [D test, D检验
8 m e$ A( V0 Z1 z; yData acquisition, 资料收集
4 t9 W: F3 S& T' m% g( AData bank, 数据库
* p1 _; P' f% G; }: Q. xData capacity, 数据容量 h' g& T# n9 G
Data deficiencies, 数据缺乏# x+ _0 \0 I: s9 y: E4 t0 ~/ E; k
Data handling, 数据处理
# X1 m/ v2 S8 [' ~2 BData manipulation, 数据处理
2 |$ \* L3 _' @/ E* G1 mData processing, 数据处理
0 B' m4 m0 V& R# _+ ]; rData reduction, 数据缩减
% l# L' H' m. f$ u zData set, 数据集$ B x1 f- A$ Y2 H, m/ O& ]
Data sources, 数据来源+ c# G0 o" y1 t. }6 A
Data transformation, 数据变换
. G/ ]6 r% E. G9 M! j! \Data validity, 数据有效性- P2 j- K7 Y" g* V4 s/ A
Data-in, 数据输入
: N7 a8 V X, a" D# d, KData-out, 数据输出% u. F# z6 R" G) y. P4 U
Dead time, 停滞期
5 Q8 t8 r. m. n) uDegree of freedom, 自由度
5 t% B' k- r: y( pDegree of precision, 精密度. L' H7 A- b* m# E8 Q0 @
Degree of reliability, 可靠性程度
. g; w& d: B" [% l9 @Degression, 递减
7 B S% z# K! t- Y, EDensity function, 密度函数& ]) Y; J8 P# g( Q5 b2 ~
Density of data points, 数据点的密度
; ?8 ~* u" L4 b* j; eDependent variable, 应变量/依变量/因变量8 V, Y9 r! Y6 M8 y; x, l; m
Dependent variable, 因变量
* y3 O" \: w1 Y$ ~7 O' |Depth, 深度3 {- D! m- k0 ^4 A
Derivative matrix, 导数矩阵
( J! D0 `5 w; Y; p; `0 [/ FDerivative-free methods, 无导数方法1 X( W `# b6 ~
Design, 设计$ F2 p3 }# j. y1 V
Determinacy, 确定性
4 r. `1 a$ O8 L# tDeterminant, 行列式
4 t+ |6 d! F; {* f" i0 G( H/ K/ cDeterminant, 决定因素5 x( O% B, u7 h# z; k, `
Deviation, 离差
$ z, S. J- v, X+ _$ [Deviation from average, 离均差$ B6 s$ j; Y1 \! B" f
Diagnostic plot, 诊断图8 S% o- i- l1 b
Dichotomous variable, 二分变量) |! n* ?% Z0 l( f& ]6 {9 {1 h
Differential equation, 微分方程2 V3 g) y Y# j0 ]9 J
Direct standardization, 直接标准化法4 [/ C; r& |; v B$ s: U
Discrete variable, 离散型变量
9 q) ? y$ u5 K0 M$ N, ~9 i& nDISCRIMINANT, 判断 - K R8 @: R2 e6 t! Q
Discriminant analysis, 判别分析
2 o* h9 z: B6 ~5 {Discriminant coefficient, 判别系数7 d4 p6 @% n7 N: I, B6 V* F
Discriminant function, 判别值
2 [: p# Z# x, u% S8 f; [- U( _Dispersion, 散布/分散度
: e1 H: l4 C/ v! z# eDisproportional, 不成比例的
9 s3 s4 s( z% W; Q# S) xDisproportionate sub-class numbers, 不成比例次级组含量
5 z( c# V; L1 ^3 G/ J( aDistribution free, 分布无关性/免分布; G/ @2 t3 S7 u
Distribution shape, 分布形状
9 E! ^: E& |* p) |+ V8 kDistribution-free method, 任意分布法
' H4 S' a, T$ ]$ c+ hDistributive laws, 分配律
9 z( P! |* B! E3 k1 V. }Disturbance, 随机扰动项# o3 K6 `3 V: V- o5 Z! ^
Dose response curve, 剂量反应曲线
2 c+ f8 t/ J% D" W+ K+ A! `) oDouble blind method, 双盲法. n, k- r) [1 y
Double blind trial, 双盲试验
# ?6 q7 K8 W; u% P4 N: rDouble exponential distribution, 双指数分布# A- l3 k" U0 v1 b
Double logarithmic, 双对数
% [' W+ M3 G4 U- x: m( e! j6 \Downward rank, 降秩
5 i+ d2 C0 n) JDual-space plot, 对偶空间图$ N5 u' O& y" f4 `
DUD, 无导数方法4 \: `- j# F3 E2 @
Duncan's new multiple range method, 新复极差法/Duncan新法
2 B3 u5 S- r8 g( q5 tEffect, 实验效应
, a' \ o# _, Q8 r1 [Eigenvalue, 特征值$ u2 E. s# @ C' [" l
Eigenvector, 特征向量
3 j$ D; H1 m3 @! G0 I- OEllipse, 椭圆
$ T2 n c* L5 U K) jEmpirical distribution, 经验分布
0 c) a1 I: L/ S" g L; F8 `* hEmpirical probability, 经验概率单位+ z1 L' G. x8 s* Z+ B- o
Enumeration data, 计数资料- _5 N t' q5 Z1 U/ _
Equal sun-class number, 相等次级组含量( n5 h- ~5 r d. |
Equally likely, 等可能. h" D( t3 g3 K4 f0 E
Equivariance, 同变性: L& m; ?# T1 \& W1 U: |' a+ x
Error, 误差/错误7 `* m, ^. o( S0 ~0 p. |9 A3 h
Error of estimate, 估计误差
7 L3 g% E- Z6 ZError type I, 第一类错误
1 N6 K: D4 {0 n# b9 ~Error type II, 第二类错误; V) [8 N# ^$ z8 K" }) G
Estimand, 被估量
7 ^5 z8 g; R; L! P6 C5 W+ SEstimated error mean squares, 估计误差均方
7 s6 r. @$ j9 s) Q* f; LEstimated error sum of squares, 估计误差平方和6 n$ K+ ~. T2 o
Euclidean distance, 欧式距离( z( q" W& J5 d
Event, 事件) u4 p6 o1 W; p
Event, 事件# o; H- o% R* n# e0 f
Exceptional data point, 异常数据点4 k0 }# ~9 i! l% r7 W1 D4 n
Expectation plane, 期望平面4 ^8 d; r' o4 M/ @7 L2 B
Expectation surface, 期望曲面! h9 K- d4 r p8 |3 x9 I1 u
Expected values, 期望值0 T1 o! W3 N! D; s0 S0 d- q2 _% R" m
Experiment, 实验
% s% K5 X1 A! k5 o5 }, mExperimental sampling, 试验抽样5 T5 m0 K% m/ a; ?1 U
Experimental unit, 试验单位: {' h& ~, Z/ i, \6 {3 P1 t# I
Explanatory variable, 说明变量! ~" u1 o1 l9 ^8 _( K( X B! c
Exploratory data analysis, 探索性数据分析9 g; D& Q, u v8 C
Explore Summarize, 探索-摘要
+ {6 k# [& ?! ]4 i, P& QExponential curve, 指数曲线/ s4 Y, u* N7 p6 e( x& b
Exponential growth, 指数式增长0 _- ^5 \7 S% i' c8 E9 H# b O3 s
EXSMOOTH, 指数平滑方法 ' _* ^* v+ q# q# ]$ {( Q
Extended fit, 扩充拟合% @/ H0 J3 y5 ?+ Z- v" Z% n
Extra parameter, 附加参数; u8 e* J. [6 b9 D0 z1 {6 I
Extrapolation, 外推法% K6 Y& u6 Y' a5 U z
Extreme observation, 末端观测值
% H B8 g m2 r( t( `. a: P9 wExtremes, 极端值/极值
) X+ M) H7 j! y/ g. ~0 u2 aF distribution, F分布
+ R4 X) {& r5 {8 S* N& _! n; FF test, F检验, K9 _' o. O7 m& h" b% h5 t3 h
Factor, 因素/因子
j8 }3 C/ D1 S' ^9 n- z* J5 fFactor analysis, 因子分析+ F) t2 w1 }) R0 f, f
Factor Analysis, 因子分析& z/ t: ~, M# p* I: J1 b
Factor score, 因子得分
) \* L: }7 U* i& O6 [Factorial, 阶乘0 V( B( V1 a0 ^$ S) \
Factorial design, 析因试验设计6 B7 K+ G$ g% k' D
False negative, 假阴性% T& `+ U9 x) @
False negative error, 假阴性错误
1 q7 f `- @+ E8 {4 }Family of distributions, 分布族& k8 g0 M+ i" m- f
Family of estimators, 估计量族# A$ y1 k7 w; L4 d
Fanning, 扇面
6 l1 F( ~' B: G+ |5 KFatality rate, 病死率: G# h8 n- e4 D) }6 M6 @) w
Field investigation, 现场调查5 V% {, J$ y* s) d) }8 p
Field survey, 现场调查
; f& J8 f$ Z6 a d( _' h: ZFinite population, 有限总体+ T" e' D* c- m: T1 [+ y) Y. \
Finite-sample, 有限样本
1 L6 J# b$ c! m: M4 KFirst derivative, 一阶导数
2 t) I1 G: \% {# |# K- h0 P& qFirst principal component, 第一主成分, t; w* H, v0 o6 s6 Y
First quartile, 第一四分位数
2 G# S3 G" u$ y8 p4 i8 \Fisher information, 费雪信息量
p& Z) {/ }$ B; i! jFitted value, 拟合值
k/ s; q# L9 p4 O( } d7 J, B" QFitting a curve, 曲线拟合
! W+ ~) c, t$ \" H# {0 K# h& V& QFixed base, 定基/ Z& s- n) f- r. t7 w
Fluctuation, 随机起伏$ g" l4 q' J1 q6 W& z2 d$ r& l
Forecast, 预测$ t& g) m# b' p6 D, _& K0 @
Four fold table, 四格表
" M: a; R; Y9 U7 z% lFourth, 四分点
& B( C9 w( V$ a PFraction blow, 左侧比率
6 C m& R0 U6 o+ D) o' mFractional error, 相对误差
8 o* @2 v% \$ w4 F5 R# \/ Y/ I I7 qFrequency, 频率8 F0 U9 s4 w# n5 l
Frequency polygon, 频数多边图
4 E3 M* t/ S, Z# xFrontier point, 界限点- R3 r, g. |/ k/ |+ Z! X
Function relationship, 泛函关系# r* ?1 X8 ]* }1 E2 ]# ]5 T: X4 X# Z( o
Gamma distribution, 伽玛分布
3 P$ M4 K. q2 P3 b( aGauss increment, 高斯增量
/ V4 `, X$ E( w5 ?& q0 A: YGaussian distribution, 高斯分布/正态分布) c3 a; A% j! W! E3 s% f: U/ F
Gauss-Newton increment, 高斯-牛顿增量; A. X1 }+ T- a! a! e7 A
General census, 全面普查
' G! g4 y- K) h1 O K" g) jGENLOG (Generalized liner models), 广义线性模型
* e; `' e0 M$ tGeometric mean, 几何平均数 }& o" ~3 i9 N* k5 g
Gini's mean difference, 基尼均差
! f, A, @7 a b1 X( q6 rGLM (General liner models), 一般线性模型
, \7 A Y0 ?/ ?6 ^6 F& MGoodness of fit, 拟和优度/配合度' P$ R6 e- G+ }
Gradient of determinant, 行列式的梯度
4 F7 c, }7 K9 a3 m: R qGraeco-Latin square, 希腊拉丁方
3 s8 W& h5 z- w) y4 P1 I1 S# e. x+ YGrand mean, 总均值0 J5 F' |3 U+ y; H
Gross errors, 重大错误
; t* S$ F+ U0 K, Y9 h) ~Gross-error sensitivity, 大错敏感度
( d9 H5 s, C8 a" [5 s) XGroup averages, 分组平均
$ i+ A$ k8 `" l. j+ t, DGrouped data, 分组资料
+ ?- l8 k5 I4 g8 F+ hGuessed mean, 假定平均数* A: l. ]( J3 a+ {3 c2 r
Half-life, 半衰期* Z( a0 }) @6 ?9 }
Hampel M-estimators, 汉佩尔M估计量
+ _6 U/ N/ Q8 a- U% y: j( |$ ~9 DHappenstance, 偶然事件
$ J* P8 E% Q& j3 U1 N9 xHarmonic mean, 调和均数. ~8 y& [3 p1 o. m3 z: A
Hazard function, 风险均数
% V! e- V- J( y6 s- ZHazard rate, 风险率& d0 B2 n. g* p; W/ V* U
Heading, 标目
. W3 Z% ~- u& z( h5 c) EHeavy-tailed distribution, 重尾分布
; v8 [+ ~$ x; x+ m2 kHessian array, 海森立体阵
+ v" h' F4 N1 Y' w9 \Heterogeneity, 不同质
/ a3 \. W& e7 P) i! \0 vHeterogeneity of variance, 方差不齐 % d4 D. D8 V# }& s6 ?- i `# @
Hierarchical classification, 组内分组9 m: k, Y' c& N* [; Z
Hierarchical clustering method, 系统聚类法& V7 v% r4 \; J
High-leverage point, 高杠杆率点
, e) \& q! ?/ I7 THILOGLINEAR, 多维列联表的层次对数线性模型$ m' Z6 A2 n$ I) b/ B$ U# W# F+ `
Hinge, 折叶点
7 d1 Y& f" \$ [ k: nHistogram, 直方图
& W3 ~. l2 c8 L7 bHistorical cohort study, 历史性队列研究
( C F0 ?3 Q% P+ E5 R7 Y- Z9 i. gHoles, 空洞! ~3 x$ f6 E7 u" z
HOMALS, 多重响应分析3 @( q: I# D, G( E2 g8 ]' z4 z
Homogeneity of variance, 方差齐性+ H5 n4 r& E3 i6 f$ u; C( V6 K- a
Homogeneity test, 齐性检验
& s! f2 V+ Q5 w/ l7 I! {Huber M-estimators, 休伯M估计量
. t2 k V3 e! {Hyperbola, 双曲线; \. \$ A9 m8 S& ~& [/ [
Hypothesis testing, 假设检验' b ?, ?5 m2 }( E& p' ]" p. Z: }
Hypothetical universe, 假设总体
/ ?# u2 I( Z1 q* h4 e6 mImpossible event, 不可能事件
g2 E/ P/ q/ R7 @5 DIndependence, 独立性
+ T4 I o. D: ]5 v8 r. H$ g% MIndependent variable, 自变量
8 G+ l3 d0 j2 RIndex, 指标/指数
& p% n7 Y4 X6 eIndirect standardization, 间接标准化法
2 o6 j" H3 Q/ h0 K8 KIndividual, 个体
; r) r: |( b$ Z- \3 r- m) N" }Inference band, 推断带
8 o _5 ~% I! a$ tInfinite population, 无限总体, e" a8 x7 W3 v, }% s. t( r6 ?
Infinitely great, 无穷大: C9 j7 U' L2 D/ z. [. f* h1 B
Infinitely small, 无穷小
) a. L' ^1 `) `4 `, @2 c1 LInfluence curve, 影响曲线
1 `& C+ r- W1 _Information capacity, 信息容量. U! O6 o8 m8 @0 t2 I
Initial condition, 初始条件
6 W$ I5 `4 ~ c! E& v# H5 I/ G$ cInitial estimate, 初始估计值
* L9 F! ]; p# I6 h: G8 o- G0 XInitial level, 最初水平
8 T% m) I4 L2 u7 L+ s) N0 IInteraction, 交互作用7 ?3 i$ Z* X2 `% v4 u
Interaction terms, 交互作用项0 x) j; P$ V. |% v2 ]( a; e
Intercept, 截距3 ^1 Y9 c! [0 P% I& }
Interpolation, 内插法1 ]3 G$ ~* }0 i* z" F& h
Interquartile range, 四分位距2 I; J7 h. B- v! r# g, G0 ?
Interval estimation, 区间估计
* j/ G5 [* G* v9 T" @, X3 oIntervals of equal probability, 等概率区间
2 l1 X3 N5 f: B; z1 j3 eIntrinsic curvature, 固有曲率; [4 w6 @2 w5 S# V9 Y
Invariance, 不变性
; T5 J5 }2 x. W6 N6 eInverse matrix, 逆矩阵
& q# X1 L! k9 W% U, xInverse probability, 逆概率- L+ j* {8 M1 V) F
Inverse sine transformation, 反正弦变换
4 ~3 B/ f3 E. c5 m, o- `; VIteration, 迭代
. Q4 `1 r! c% OJacobian determinant, 雅可比行列式- W* @" B, h1 o! V* c7 }% J
Joint distribution function, 分布函数
% B1 }) |, t) v* ?1 s5 K& _/ OJoint probability, 联合概率2 O7 x; t' [ O& z# V8 O
Joint probability distribution, 联合概率分布
, q' Z7 X' r6 k3 r8 I3 d+ y* BK means method, 逐步聚类法$ S* Z: l& m9 ?4 ?: Y
Kaplan-Meier, 评估事件的时间长度 , U2 V+ X2 O+ A8 k0 e) F
Kaplan-Merier chart, Kaplan-Merier图
0 A6 `5 I0 ?+ A2 X, mKendall's rank correlation, Kendall等级相关
( q, V- i1 p! G3 [* ?# D" yKinetic, 动力学
- O# j* d8 G- _$ m% o' ?/ rKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
! {1 ?) u% h9 r: z" JKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
7 s* U, u% g* Q" Z, {% x7 T3 uKurtosis, 峰度* C- X9 ?& L1 `3 h% O5 s3 B" o" k% ]. z& `
Lack of fit, 失拟( Y* Q9 `* p4 y% v# z
Ladder of powers, 幂阶梯3 u% O+ m- n) C2 b3 D
Lag, 滞后
: `/ g G; R: p+ J7 xLarge sample, 大样本
, G# ~) ^" [9 i7 lLarge sample test, 大样本检验4 O1 {, D8 @' p/ J1 e
Latin square, 拉丁方- ?; g- s% y+ l+ P: s. L
Latin square design, 拉丁方设计" q- A4 C# J6 z6 o8 L0 F7 C
Leakage, 泄漏
( O( T9 d) `+ G9 r& h0 B8 b% P( cLeast favorable configuration, 最不利构形
. n7 f, k3 }4 L$ j* q' a) b! sLeast favorable distribution, 最不利分布
" X. [" q8 Q9 w1 z+ N* x8 @Least significant difference, 最小显著差法
& C) I& K( y& V1 ~# A& j8 RLeast square method, 最小二乘法
6 i7 u. W3 ^8 U3 TLeast-absolute-residuals estimates, 最小绝对残差估计9 J5 D" g0 U6 d0 k& \$ r2 }
Least-absolute-residuals fit, 最小绝对残差拟合
6 ?4 S& X x5 D; ^7 @Least-absolute-residuals line, 最小绝对残差线) U) G4 D! }# q. E$ x; F! l2 p
Legend, 图例
- _2 W9 l2 \+ Y1 U- z, U5 a7 HL-estimator, L估计量
2 H( n; Y* u2 I. n; q# f0 M7 [+ _L-estimator of location, 位置L估计量. L) ^) j2 E1 F/ C0 A. Z; }3 d
L-estimator of scale, 尺度L估计量$ I/ k5 D9 `$ r; n" T: |5 y- ]
Level, 水平6 N7 N2 W/ P a8 q' T. F
Life expectance, 预期期望寿命: Z, E* c/ k# x
Life table, 寿命表4 e F& E# @+ c
Life table method, 生命表法
# \8 W! w+ F/ h" g, O* C' O+ ZLight-tailed distribution, 轻尾分布
. h( S1 ?3 D2 W, m0 eLikelihood function, 似然函数- Z% H5 c" Y9 c* _
Likelihood ratio, 似然比( N& f3 K( S6 L8 j+ V
line graph, 线图
: F1 C' A0 Q ?% A; XLinear correlation, 直线相关 i0 X' l; d' p# O0 \3 `
Linear equation, 线性方程; E: u# H. c2 r6 i" R0 z
Linear programming, 线性规划; X* x Y6 q5 [6 @5 f1 R2 p
Linear regression, 直线回归
, _$ I5 w) q: {# M5 yLinear Regression, 线性回归
x4 }; \* S( K$ {Linear trend, 线性趋势1 m7 I- j; T' U1 H9 O; N
Loading, 载荷 / q5 q4 K' o6 i7 J+ t& y1 `; L
Location and scale equivariance, 位置尺度同变性/ Q& t! {8 ~3 _! B
Location equivariance, 位置同变性
3 G E* t8 b5 s9 p& G/ F* ]Location invariance, 位置不变性
) I# [& v* [$ U% i) I, ~Location scale family, 位置尺度族
7 E1 w/ u& M) W1 }! LLog rank test, 时序检验 . y: M3 x' m! ]- g) z
Logarithmic curve, 对数曲线& t: c- C: A2 V" r: F& @
Logarithmic normal distribution, 对数正态分布
8 D' S. \8 v) p" Y7 XLogarithmic scale, 对数尺度" j8 r. f. o* [/ Q
Logarithmic transformation, 对数变换5 n! L* l. N% g
Logic check, 逻辑检查/ S2 j7 \! c; ?* `- I& h& f
Logistic distribution, 逻辑斯特分布& m6 y0 }9 a' c4 }4 ?
Logit transformation, Logit转换
( ]/ |2 b+ v: [LOGLINEAR, 多维列联表通用模型
; r1 Z1 D. H6 x8 z" r9 YLognormal distribution, 对数正态分布9 T: F& d* X9 Y4 L) C8 O% B Q
Lost function, 损失函数
' C& [, ^. K- hLow correlation, 低度相关 L- F2 n$ f3 N: ]7 f
Lower limit, 下限& H: V/ f! I0 L
Lowest-attained variance, 最小可达方差
! @: Q" g% s# ?' a0 d; }" fLSD, 最小显著差法的简称: J8 o9 a% {- U: B, R: N
Lurking variable, 潜在变量
. L g8 E* d5 s% u a4 Y/ F# DMain effect, 主效应8 E% p" K: X8 o# G
Major heading, 主辞标目
' s9 B- X6 F1 H8 IMarginal density function, 边缘密度函数1 ~6 h# V1 |3 k/ Q* Y6 Z
Marginal probability, 边缘概率. C, K# S. ~) Q& `' _9 M- S
Marginal probability distribution, 边缘概率分布
; k; o0 d/ ?2 }7 G2 ^* pMatched data, 配对资料' K6 r# H7 J& }- Y2 g! G+ H
Matched distribution, 匹配过分布
/ d) [) Y6 Z2 v' r' M1 W! qMatching of distribution, 分布的匹配
5 o# E8 C- ]' [* oMatching of transformation, 变换的匹配
6 _1 m0 m% B' K5 h: Z9 V1 xMathematical expectation, 数学期望! Z' o+ }3 Z& g, J/ o/ T- N
Mathematical model, 数学模型
) O5 n0 z. d& \Maximum L-estimator, 极大极小L 估计量+ C1 V" J0 f! F8 V, d, H
Maximum likelihood method, 最大似然法
5 V; [3 v8 G# g6 u3 I e+ k! T" VMean, 均数1 P l/ Y, Y" O) f$ C
Mean squares between groups, 组间均方
. ^% k5 f: O! G" R- k8 SMean squares within group, 组内均方4 K4 }8 x ]: F2 k$ ~9 |
Means (Compare means), 均值-均值比较: n0 ]$ h0 j3 \8 z1 P! H
Median, 中位数2 _, [; r1 d' i. H+ g) v0 p
Median effective dose, 半数效量
- v3 }* f$ T1 U5 W9 hMedian lethal dose, 半数致死量
4 y* X" X; j5 L% NMedian polish, 中位数平滑1 q7 J( U* d9 x4 r5 [" B
Median test, 中位数检验
" Y6 u4 [9 }" W' v3 W" W7 aMinimal sufficient statistic, 最小充分统计量
6 V4 p2 Q$ I) R! OMinimum distance estimation, 最小距离估计
E" j8 J! G- o* MMinimum effective dose, 最小有效量8 g. i( A1 o% w: h& _, ~6 q8 T
Minimum lethal dose, 最小致死量6 C+ _3 p: H3 _
Minimum variance estimator, 最小方差估计量9 Q A& B1 X2 \9 t) U; s
MINITAB, 统计软件包
5 X) y& Q: a. ~' Z6 ~Minor heading, 宾词标目
; l# J+ e; \7 c1 e' b# }Missing data, 缺失值7 A/ d7 j9 \1 ] J6 r8 G$ V
Model specification, 模型的确定* T4 p( ]4 X3 w/ O
Modeling Statistics , 模型统计 j6 d* }- S, b& B
Models for outliers, 离群值模型
: X6 Z3 P/ u. A9 [7 }/ S" B" PModifying the model, 模型的修正( `% ~- u% ?, |4 t
Modulus of continuity, 连续性模4 ]: _) |, }$ W3 P) h( I
Morbidity, 发病率 / ?+ }3 d4 l# @/ t. p9 Q4 U0 A( V
Most favorable configuration, 最有利构形+ z, E% Y# _( y
Multidimensional Scaling (ASCAL), 多维尺度/多维标度3 u2 {/ `9 z3 z% L5 P) ^5 q7 e0 o" |8 P
Multinomial Logistic Regression , 多项逻辑斯蒂回归3 q. }9 [; ?, R8 E4 g' I! W
Multiple comparison, 多重比较2 m8 s! M5 }6 F6 i9 C" u
Multiple correlation , 复相关! L W& y9 J5 x4 q2 Y& r
Multiple covariance, 多元协方差( c. J5 ^4 F0 u9 C. E5 H# K
Multiple linear regression, 多元线性回归$ T. c) A: Y. R+ c4 b# H u
Multiple response , 多重选项( D/ P6 v+ f. R s) s$ o% m$ q
Multiple solutions, 多解) d7 x1 k0 N4 z h4 `& I7 Q
Multiplication theorem, 乘法定理' w6 u! W' v B( l$ h2 x5 N
Multiresponse, 多元响应
8 O% u& \! E: O+ `, ?& {9 RMulti-stage sampling, 多阶段抽样8 O7 D' D5 R5 Q" H5 @3 R6 p* h
Multivariate T distribution, 多元T分布
4 L0 I3 J6 u3 Z9 E/ }7 _0 {+ d9 OMutual exclusive, 互不相容
" U: O X/ l! e( G# ^Mutual independence, 互相独立2 }5 a7 g$ e4 E- ~$ [ b. j& g
Natural boundary, 自然边界
0 j- e( e. ]4 P5 F: L0 J# w0 VNatural dead, 自然死亡
O6 K# x% Q/ h5 aNatural zero, 自然零+ O9 A7 J' w- q
Negative correlation, 负相关
) p. D! X4 h2 N3 sNegative linear correlation, 负线性相关 e% X6 G5 d) ^* V
Negatively skewed, 负偏
# _4 B, O4 H6 @( B8 |Newman-Keuls method, q检验
* ~! c' K% Q: W0 q: y, LNK method, q检验. @6 Q. c n L( ~. w7 d
No statistical significance, 无统计意义
/ P- Y p$ Y! a9 {6 z: R! s8 [2 e5 SNominal variable, 名义变量' m9 @2 D6 w6 z" l/ R8 J7 x2 P/ P
Nonconstancy of variability, 变异的非定常性- @ ]% ]1 i' E& m; L/ s
Nonlinear regression, 非线性相关9 k1 j0 s; Y, t) s
Nonparametric statistics, 非参数统计
/ K0 g ~0 n1 }0 ANonparametric test, 非参数检验
- F5 N* }: {. X, ~7 Q! S5 pNonparametric tests, 非参数检验
9 P4 s$ m* X, b& m0 F+ A. ]8 E, ]Normal deviate, 正态离差# X0 G* [4 }4 h6 M q
Normal distribution, 正态分布
. p, W" u% U9 ]/ i d' dNormal equation, 正规方程组# ^! X: B2 k1 v/ k( K0 d
Normal ranges, 正常范围
- Q* I2 T+ c. O" D6 k+ JNormal value, 正常值
% B2 v; j$ u" p' wNuisance parameter, 多余参数/讨厌参数
. i0 t, d* ]( b" r& {Null hypothesis, 无效假设 ; Z# w) x6 g! X, \% O; S6 o
Numerical variable, 数值变量; y; O- U: x- ~$ D4 G/ ?! f: i
Objective function, 目标函数
0 e& S) r( w3 D+ uObservation unit, 观察单位/ d; G4 N% \; _# Q: k8 [2 Q3 N) y
Observed value, 观察值
& l6 X/ E& X; H. L/ l; jOne sided test, 单侧检验
3 L4 C: O4 D. a9 Q1 J8 H! {2 LOne-way analysis of variance, 单因素方差分析# e% p& ]( I4 Z8 t
Oneway ANOVA , 单因素方差分析# Z* ?. |0 Y" p2 x G8 k/ k& p
Open sequential trial, 开放型序贯设计; Y" a8 r8 P+ h5 B& b- _
Optrim, 优切尾8 N2 Q: c: Y9 r1 @, e8 j
Optrim efficiency, 优切尾效率
2 S, r6 ]' ^ ~) oOrder statistics, 顺序统计量
/ ^. W# x& r, Z7 v, a6 ZOrdered categories, 有序分类
4 B- q* q: r4 @' m" q4 p& aOrdinal logistic regression , 序数逻辑斯蒂回归
' m E/ q) l9 S$ v$ POrdinal variable, 有序变量
# W2 ]/ L$ w' F; J6 Q7 t4 lOrthogonal basis, 正交基
; h7 L6 Z) V: E$ Z3 `! h2 L- n0 SOrthogonal design, 正交试验设计
) `- r u) j* i9 |Orthogonality conditions, 正交条件
+ T8 z1 t# E4 _3 N6 _- c. I) L7 vORTHOPLAN, 正交设计 + Q8 @$ q* S* w9 q( S
Outlier cutoffs, 离群值截断点
0 s) {3 j; a( o& qOutliers, 极端值7 q, g1 r! |* a9 | q6 `$ j) _2 E
OVERALS , 多组变量的非线性正规相关 5 u) U1 J( Y* C0 V; o" j
Overshoot, 迭代过度, C5 R4 ^$ x$ \5 x6 v+ V0 ^
Paired design, 配对设计
: o/ m. R3 @9 A7 g* }- O: ?2 L7 {Paired sample, 配对样本
0 o0 l q" d: q" n8 vPairwise slopes, 成对斜率
* p& K7 z+ J* C9 h# l5 d4 K9 cParabola, 抛物线
/ I5 c- s. ~* L1 g, h9 X, e; y0 QParallel tests, 平行试验/ t( p0 d% h6 Q" }8 |
Parameter, 参数, N1 K/ H/ C: N7 }: C, l* [8 d" P; L
Parametric statistics, 参数统计
' t0 b, E& L! d& DParametric test, 参数检验( Q, Z+ @9 E( V9 {5 s8 Q+ v
Partial correlation, 偏相关# b8 N {! o' T$ E0 w0 a
Partial regression, 偏回归
9 l% A; W2 P0 U8 z! y- q0 T3 ~Partial sorting, 偏排序! k0 S5 {, |, Q6 D
Partials residuals, 偏残差
1 R8 h9 _0 s+ kPattern, 模式
- K1 T/ k. E0 Q6 Q& m& L \% ~Pearson curves, 皮尔逊曲线
- g+ y4 o4 u5 {' ~2 BPeeling, 退层
: Z5 e0 N1 ]8 Q& l6 h7 B) i; fPercent bar graph, 百分条形图
! I8 N9 @, d$ a3 ~; N! sPercentage, 百分比+ h4 Z" U. o$ E1 G" a1 E
Percentile, 百分位数# S/ ?7 V8 z) E& m
Percentile curves, 百分位曲线9 z/ t: ]6 j+ k0 b8 X! e, N3 z
Periodicity, 周期性/ C( O" Z+ w3 c5 m! n# F7 @/ M6 f; l
Permutation, 排列
% G$ f+ E1 f" c5 n5 q/ N8 j; t- _P-estimator, P估计量
( e+ D$ t0 s9 ^Pie graph, 饼图
8 H9 v- U6 ^7 o! |1 vPitman estimator, 皮特曼估计量
7 j6 L7 V, {7 M, KPivot, 枢轴量% g8 X g" V& v% g, h
Planar, 平坦- J6 e. n$ |- D1 `7 _2 l
Planar assumption, 平面的假设 L# S- |) [) z3 ~
PLANCARDS, 生成试验的计划卡' L: i6 c" P1 b/ F P
Point estimation, 点估计
9 d' c9 c6 {. ]Poisson distribution, 泊松分布; l+ E7 `8 R9 _
Polishing, 平滑
# O2 |& r( u1 x$ }' A# cPolled standard deviation, 合并标准差
. k" o$ X; b, ~8 ]: V) X xPolled variance, 合并方差& Z7 R8 V/ i& n2 a8 @; }
Polygon, 多边图
. f0 B* y+ l O2 }Polynomial, 多项式; ?& C* e1 X- j
Polynomial curve, 多项式曲线
" D/ w8 T4 V& ^Population, 总体
! n- ~2 J" o' M% ~0 Z- PPopulation attributable risk, 人群归因危险度) F+ }' q( I! e r
Positive correlation, 正相关
' {; F2 [& W; A8 B0 BPositively skewed, 正偏
& P; F6 K8 D5 `" LPosterior distribution, 后验分布4 ]: k v- [* n; `; n+ z5 \
Power of a test, 检验效能: E+ K: ^+ r! b6 [2 y: `
Precision, 精密度. E0 g5 X6 b; ]8 ~# f2 d! t
Predicted value, 预测值% D4 b& q* x: X& C. b$ E9 C
Preliminary analysis, 预备性分析) H6 d1 m( k- r7 ] D( J6 M
Principal component analysis, 主成分分析
$ ^+ x9 I; x* GPrior distribution, 先验分布
) F9 t7 q$ P) K7 N/ U8 J5 J! YPrior probability, 先验概率0 r: |' [- \! j7 H
Probabilistic model, 概率模型
/ Q2 A" I' i. ?8 s1 Bprobability, 概率. h5 e( F' J( A1 A2 [. F# L
Probability density, 概率密度( t$ j: I0 l: H. M6 m0 ~/ {
Product moment, 乘积矩/协方差
8 G0 K- E. x2 c2 [Profile trace, 截面迹图
@* P+ F G; T$ I& H- u% {Proportion, 比/构成比
+ |- F2 C8 e* R: P9 AProportion allocation in stratified random sampling, 按比例分层随机抽样
' O8 I9 i7 l7 kProportionate, 成比例
2 `# y- k# ~3 ? F8 _- DProportionate sub-class numbers, 成比例次级组含量7 g% N" i# I- x5 v2 g' N
Prospective study, 前瞻性调查) q* B! g! R# _- b
Proximities, 亲近性 & x, Z* z5 p* \: u' c5 M# U
Pseudo F test, 近似F检验
- f4 c; u# d* p; e, k5 _& VPseudo model, 近似模型 t* J! ], o4 f
Pseudosigma, 伪标准差9 A' O# v0 G% \8 u" C& L3 V8 E
Purposive sampling, 有目的抽样
/ P. U# [% y. @1 DQR decomposition, QR分解$ a7 ]9 U( ~. ~
Quadratic approximation, 二次近似
3 j6 I/ F' @! EQualitative classification, 属性分类
0 p) C# X' t5 @$ W8 Y4 O3 P% G; {) oQualitative method, 定性方法& H% ?" c1 R/ x5 U) Z
Quantile-quantile plot, 分位数-分位数图/Q-Q图+ Z C' ^3 l% z$ D$ p8 e/ y
Quantitative analysis, 定量分析
. g4 _9 ^$ D; |4 T* L: UQuartile, 四分位数" I1 q7 u; l( J
Quick Cluster, 快速聚类
- E# S5 f% _: ^7 P7 ?5 DRadix sort, 基数排序- x9 n3 e' G3 |0 B7 P
Random allocation, 随机化分组
3 s( g+ J0 a+ b. KRandom blocks design, 随机区组设计* c) V4 g, G) n/ c4 c8 n* {
Random event, 随机事件
; `5 L" y/ a; h |' N! H6 C1 ~Randomization, 随机化
2 M ], i5 o% a9 t& sRange, 极差/全距7 }4 E, N/ F# g6 V \6 p
Rank correlation, 等级相关
2 o" H9 @' `# t& U" F5 Q. C2 fRank sum test, 秩和检验
& _) E |2 I2 WRank test, 秩检验
# n( p, t- O5 _0 ^3 c2 @Ranked data, 等级资料
. r8 _9 q! c S' Y0 V0 l+ S9 rRate, 比率
' ?, [9 A8 o8 W% o( j3 a& X0 `Ratio, 比例
+ [2 `' r. q DRaw data, 原始资料/ `' ?# \7 s- L+ u3 R1 c
Raw residual, 原始残差7 A. h% X% ^# j# V: H% p
Rayleigh's test, 雷氏检验* ^1 l, O$ ^$ u; _2 n
Rayleigh's Z, 雷氏Z值
8 h) W8 Z* p. e# q) M5 wReciprocal, 倒数
" g% x+ R2 _4 Y3 e3 C6 hReciprocal transformation, 倒数变换
+ |1 G. c7 R& ~2 ZRecording, 记录: {* H8 P) d, n0 t& y
Redescending estimators, 回降估计量
. o3 }1 J" F! Y" ?) y. BReducing dimensions, 降维
' ^, n; z( `/ F0 z2 i/ ZRe-expression, 重新表达
' \. @& F" J ?3 x( n" mReference set, 标准组
6 ~, S$ M5 }" o( v2 ?, RRegion of acceptance, 接受域
* _9 I, n, Z2 C! TRegression coefficient, 回归系数
: H# T$ B9 G2 O! \ CRegression sum of square, 回归平方和- f: T( g2 K2 X' O* I$ I0 {! P
Rejection point, 拒绝点1 f+ a3 {9 R6 z
Relative dispersion, 相对离散度& J4 `) N5 N8 v% t# A& K
Relative number, 相对数
2 g% s1 d* u0 [. \/ i2 G9 iReliability, 可靠性
0 V4 e$ H- r7 m+ LReparametrization, 重新设置参数" @* g, _7 c& X! B& ?
Replication, 重复
1 p# Z& J' a* u2 s$ @Report Summaries, 报告摘要
7 |; T, ]! s' `6 s0 CResidual sum of square, 剩余平方和, W2 U' C6 a( _4 i e( z4 y
Resistance, 耐抗性
( J& `- X |! F/ m! Y9 Q/ b2 eResistant line, 耐抗线
4 s* Q: N- `. k2 M% _1 AResistant technique, 耐抗技术 m- \" Y" L3 J1 p# E2 H" C6 n
R-estimator of location, 位置R估计量
5 I) H, w7 _' Y4 R; V4 R/ o; C( XR-estimator of scale, 尺度R估计量% h; Q- m% X6 D
Retrospective study, 回顾性调查( m- m2 M( E9 u0 |) M; X6 G
Ridge trace, 岭迹
$ b4 E7 N( S7 W. Y5 I* ARidit analysis, Ridit分析' t4 z5 [- S8 \- Y7 I1 X. j* X9 S
Rotation, 旋转4 H$ D' ~9 T. [) r( k' N
Rounding, 舍入
& w2 r; }1 B& l/ y3 B2 g; s1 oRow, 行" I% k+ P' G0 x1 d% ~% e
Row effects, 行效应
4 M. U/ F H" P- `8 r+ x6 u( U0 CRow factor, 行因素2 I; ~& A1 s" P2 W: t3 g$ ~) _
RXC table, RXC表6 C7 ^1 O$ G! R6 U- g: c
Sample, 样本
: r3 `" r5 X5 x4 h0 qSample regression coefficient, 样本回归系数. s: T+ m1 `' `& m3 K/ i
Sample size, 样本量
9 ?% K9 l- a' W9 \$ ]; jSample standard deviation, 样本标准差
8 c Y; Y! L G+ M" X8 j5 RSampling error, 抽样误差' k, n. h0 j3 |. L) |" U. b
SAS(Statistical analysis system ), SAS统计软件包
! ]3 ?+ l1 }3 BScale, 尺度/量表6 R' B$ X y3 f6 h! g
Scatter diagram, 散点图
: [" B( W! F Y$ s( [7 E/ oSchematic plot, 示意图/简图
6 v3 t; H8 V2 d, y/ i/ B% t' BScore test, 计分检验 r) `1 D% D" |9 R( |
Screening, 筛检8 L+ b( ^ {3 A- k9 |7 c1 R
SEASON, 季节分析 0 p4 M2 ?. K0 y( q1 U3 X# S
Second derivative, 二阶导数
+ M) p4 L& Y) \: r' JSecond principal component, 第二主成分5 T# s5 d- I( |0 ^, C1 {5 O
SEM (Structural equation modeling), 结构化方程模型
+ R* _* b& b/ m3 Y0 gSemi-logarithmic graph, 半对数图& g/ C- V. [( _2 I& |
Semi-logarithmic paper, 半对数格纸, A! z3 W' G0 R9 m$ B" N; q
Sensitivity curve, 敏感度曲线3 e& h" P' j# A
Sequential analysis, 贯序分析, F- H8 |5 D$ g3 Q# B2 g, T2 d
Sequential data set, 顺序数据集
5 k, ~% ?8 A$ CSequential design, 贯序设计
& r3 L d: v( u3 F# W2 }0 lSequential method, 贯序法
0 |2 z* v7 ?( k T( T+ LSequential test, 贯序检验法$ M2 u$ ~$ Q2 G
Serial tests, 系列试验9 [% @5 f7 k$ ~/ U4 n9 A, e
Short-cut method, 简捷法
" [3 p# _* [* C5 L! w5 N7 h! fSigmoid curve, S形曲线
, w4 v1 i/ T- f! I& JSign function, 正负号函数
6 A$ L# M3 v) @& z1 BSign test, 符号检验
, C7 {1 }% ]! u' sSigned rank, 符号秩1 V$ h6 T: o7 w) @
Significance test, 显著性检验
2 L8 ~$ C1 t3 O) e, H: @/ {Significant figure, 有效数字
$ O+ S; q! F5 u4 T' HSimple cluster sampling, 简单整群抽样; J, l9 d4 ?: I5 D y1 V
Simple correlation, 简单相关0 e8 a8 ?# O6 u( I
Simple random sampling, 简单随机抽样" K7 K N/ |9 Q% m: [7 q0 ^; d
Simple regression, 简单回归' D9 \5 w; s0 t6 @ t7 c* [
simple table, 简单表0 b5 T& @+ e" F7 r
Sine estimator, 正弦估计量6 h+ d c$ t' h( m: R
Single-valued estimate, 单值估计
8 A V& t7 N; J) T6 o9 i' m4 {Singular matrix, 奇异矩阵9 v! Q) A/ M3 ~: h) N" S' a- A0 b
Skewed distribution, 偏斜分布/ E% h! o3 w" u
Skewness, 偏度. ~" G2 U( l1 k& m6 _* E
Slash distribution, 斜线分布
2 c/ c! [8 U. g% V# [' o2 P; KSlope, 斜率
) ]4 o, {0 c( x+ ^+ a6 `' f7 `Smirnov test, 斯米尔诺夫检验
: z4 q2 u; \: vSource of variation, 变异来源1 C3 l+ [7 d5 z. s6 E2 u6 `
Spearman rank correlation, 斯皮尔曼等级相关$ R/ K% ~+ r; Q3 X$ K. }- C$ n. Z# i
Specific factor, 特殊因子
2 w9 y4 D7 X3 E$ }1 J" aSpecific factor variance, 特殊因子方差
9 l+ q! I* U9 K: S6 x$ l( uSpectra , 频谱: ]7 o- V, j! V- S/ h
Spherical distribution, 球型正态分布" ?' l6 i5 c' Z8 ]. x, `4 h) D
Spread, 展布7 @3 E( F m. ^7 @
SPSS(Statistical package for the social science), SPSS统计软件包
& L" g- s: M0 m# d$ ~4 f5 k. O" hSpurious correlation, 假性相关
3 J/ x- M+ B+ w+ g- j5 \Square root transformation, 平方根变换
( P4 [$ T5 v3 ]$ ?Stabilizing variance, 稳定方差
! F; x# ~; }- H, O" WStandard deviation, 标准差
9 V/ Z; U/ G/ u, O( ?Standard error, 标准误) S \4 M/ r" f) I q& X
Standard error of difference, 差别的标准误
5 {" q8 L/ p7 z0 Q6 T E9 ?4 {2 t% sStandard error of estimate, 标准估计误差
/ g1 s( M* _6 B( R8 ]) @2 ~Standard error of rate, 率的标准误
3 ~ e( \, n5 X7 f6 I5 N$ lStandard normal distribution, 标准正态分布- b5 N3 h0 L3 i; E7 _* O
Standardization, 标准化
1 f: `& c) k9 W9 D6 @1 r2 u! J. x9 YStarting value, 起始值
5 T1 \& b( z+ \4 ^7 L+ N$ {' IStatistic, 统计量 r' P3 c! R. a: d& d* j# t
Statistical control, 统计控制
|) _& v* z, g7 E* bStatistical graph, 统计图
' G* D( S2 y. O# B/ xStatistical inference, 统计推断8 p6 B3 y5 P# e& L" ^- J) d- v# g
Statistical table, 统计表5 \& L8 O) A. C
Steepest descent, 最速下降法
: g/ f: Q! o' B8 LStem and leaf display, 茎叶图5 |. V& q8 j0 `
Step factor, 步长因子- [9 T! s/ K* v9 X
Stepwise regression, 逐步回归
' R& }, ~) `; PStorage, 存
( }. C9 z( i9 {) y! G6 {9 b/ o gStrata, 层（复数）5 X$ O% X3 F0 D
Stratified sampling, 分层抽样) P$ ?2 o3 G1 K0 Z3 S2 B+ J7 j
Stratified sampling, 分层抽样
! B( O$ _, k0 k' x9 k- xStrength, 强度1 @( {7 [5 W& N. B
Stringency, 严密性; x z# o- \7 D5 ~, U7 s5 |: {1 w ~
Structural relationship, 结构关系
6 e: G0 Y i4 ~4 V( D1 `$ \/ iStudentized residual, 学生化残差/t化残差
7 l, D; T. g1 S6 sSub-class numbers, 次级组含量
! e( X, z5 L- z6 _ l E5 rSubdividing, 分割
$ c# _7 `, V2 e) J9 ~ b. t6 iSufficient statistic, 充分统计量
# \+ A2 R; c% M; k, s3 `, Z2 _Sum of products, 积和) b% f! r" Z% z5 v1 |5 F1 K% b$ ?
Sum of squares, 离差平方和/ ]7 T3 T/ M3 ~, v% O
Sum of squares about regression, 回归平方和; U) @: j$ P3 S- Y* m
Sum of squares between groups, 组间平方和% M( D; f3 z0 W: ?! u/ w% l, e( f8 [
Sum of squares of partial regression, 偏回归平方和
: S% ?% F( S# N, b1 CSure event, 必然事件
6 N8 ]. G! v$ e3 kSurvey, 调查$ A% D' L" e6 ?
Survival, 生存分析# C- W8 P1 s$ c8 T
Survival rate, 生存率6 J! s' e2 [( Z0 \' c+ u
Suspended root gram, 悬吊根图3 r1 a4 V5 T W$ j
Symmetry, 对称
6 o5 v/ |# `, y2 N0 }6 gSystematic error, 系统误差" y7 ]; ~( V3 u3 {. Z$ a
Systematic sampling, 系统抽样
0 T, [; i" ^* C# ATags, 标签% w o, \6 C- r
Tail area, 尾部面积/ I1 w4 R2 s4 a( G( a
Tail length, 尾长! f4 W, e; k. C
Tail weight, 尾重% [+ h# z' {! @4 e7 I
Tangent line, 切线) X c! C8 ]5 b4 d5 G# h
Target distribution, 目标分布
! V+ V2 H d4 s8 [' o2 C# r9 }Taylor series, 泰勒级数) D1 M3 m7 [) E3 Q* P: A; o9 O; P
Tendency of dispersion, 离散趋势
9 Q7 L8 a7 ]* rTesting of hypotheses, 假设检验
) N9 h. i" K- T; OTheoretical frequency, 理论频数5 Z- u6 P( @7 t! G* Z+ f9 M
Time series, 时间序列
+ q1 V9 i. L/ X+ E& QTolerance interval, 容忍区间' N4 _3 h' R4 W# S8 R; Y3 K& M) W
Tolerance lower limit, 容忍下限
0 I+ o1 J+ r7 h; UTolerance upper limit, 容忍上限- m* A2 A, y5 m6 ~! i0 Q
Torsion, 扰率
g! c/ p# X% r: A* W4 c9 [Total sum of square, 总平方和
/ ?8 i: Y$ B* @4 ]* q5 d' D/ u0 ]Total variation, 总变异
2 v$ }* v$ I. C: cTransformation, 转换
4 J+ E& o n; ^4 R Q5 }/ pTreatment, 处理
, k# M w. l. e) Q% x3 o4 yTrend, 趋势- G9 I0 D! K: m% W* [
Trend of percentage, 百分比趋势
/ N% |& \2 a1 q# q% @% u8 i+ S5 g4 G( ETrial, 试验
7 f3 b" ~- w$ ]8 i$ t0 w2 \8 k( M2 }. vTrial and error method, 试错法: } s) w" s! n; B1 }( O$ _
Tuning constant, 细调常数$ Q& q K9 S* ~& S, X( s: [: B9 i
Two sided test, 双向检验( M5 q* o. v% A( F4 P* P
Two-stage least squares, 二阶最小平方
2 K! G; T( v; i. v$ x; h6 F$ y8 pTwo-stage sampling, 二阶段抽样
w8 N; _+ P( Y# u; H; V4 ^- ETwo-tailed test, 双侧检验7 u, |7 a, ^7 ^! e
Two-way analysis of variance, 双因素方差分析
$ s1 M A. `6 U3 k6 [2 ZTwo-way table, 双向表 o W. A% X( p2 d9 @( E. z
Type I error, 一类错误/α错误
' @5 \2 `9 [2 b( f0 `0 wType II error, 二类错误/β错误
# y! u% s9 |* ^4 U$ ZUMVU, 方差一致最小无偏估计简称
' D2 a. z% u- u% h+ Q0 O% ]2 Z3 nUnbiased estimate, 无偏估计+ n; d% A/ o9 \; r' x
Unconstrained nonlinear regression , 无约束非线性回归# X+ {/ |9 W5 \! {" p
Unequal subclass number, 不等次级组含量7 s ]+ Y) v% Y% R0 }
Ungrouped data, 不分组资料
. w4 V) x" j$ r1 ~2 ~7 RUniform coordinate, 均匀坐标$ t' S" N8 q" M# k0 d
Uniform distribution, 均匀分布
7 S! v; b0 n& N+ Q7 I: S XUniformly minimum variance unbiased estimate, 方差一致最小无偏估计' g+ o) n3 H! m2 @
Unit, 单元
' E8 m- D" N2 S* q$ L5 c. MUnordered categories, 无序分类# u7 X4 I6 T- Y8 s6 P! i
Upper limit, 上限
1 j f" s1 x, {. p3 J+ K! NUpward rank, 升秩$ l' m! `, {. c/ x( \4 z* _0 Y5 o
Vague concept, 模糊概念% @" C; O% x) ?# s
Validity, 有效性4 e- {( p: C4 M( Y2 O8 a
VARCOMP (Variance component estimation), 方差元素估计
& d4 _" S) s( HVariability, 变异性
3 D6 g% O7 e' L- S4 {- [9 pVariable, 变量
. j* ^+ S8 n+ o8 j! K9 @/ cVariance, 方差# l9 u* T5 I$ M1 r6 K! k d$ P
Variation, 变异& s$ _5 E& ^% s' Z" I% r9 X
Varimax orthogonal rotation, 方差最大正交旋转
! X$ d$ z6 R% @9 ZVolume of distribution, 容积
$ G9 \+ h) {2 [W test, W检验
3 _% J) n7 x3 r V B) H. qWeibull distribution, 威布尔分布
# z+ U6 B& z* _& P \Weight, 权数- r3 E; K7 A2 d D& X9 `
Weighted Chi-square test, 加权卡方检验/Cochran检验
' O- E a8 h M! JWeighted linear regression method, 加权直线回归
' z& ?" z" M6 ?. i& w% AWeighted mean, 加权平均数1 o" g! e5 M' T% w. Q
Weighted mean square, 加权平均方差
8 c0 p! ~' H( ^! W8 y, l7 v1 ]0 MWeighted sum of square, 加权平方和7 \# \+ s' r- H+ I
Weighting coefficient, 权重系数8 F3 \7 t4 u1 M& n1 F' F
Weighting method, 加权法 7 f3 ~$ t. @& H. ?
W-estimation, W估计量! E" g- ~+ d/ C$ `
W-estimation of location, 位置W估计量
3 j# M5 O G |5 k7 q( cWidth, 宽度! [; [/ N9 T+ R/ D3 Z. p" O; d
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验9 N" M- `0 a8 r4 c: h
Wild point, 野点/狂点
* f, ?6 V5 N! f1 e2 gWild value, 野值/狂值
% b, C {& [! f9 Y: E! P% TWinsorized mean, 缩尾均值
( H- `! D- r o/ ^3 q* [Withdraw, 失访 k2 t+ N( l) E S; u; }. s8 w4 @
Youden's index, 尤登指数
( v& H4 |8 O! v* X; IZ test, Z检验
, E0 G! \* \% @. d5 C, v: s# ]& [Zero correlation, 零相关8 P6 ~* [, W0 z% \4 f) X
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
