|
|
Absolute deviation, 绝对离差
! w* j" y9 c$ g: z5 P' @6 XAbsolute number, 绝对数% H; I% ^8 K2 A+ r) L, p; d
Absolute residuals, 绝对残差- C5 H+ k) r4 G$ F$ z. i& N
Acceleration array, 加速度立体阵) j @4 K2 G# g' ]' e! M& U3 A! J& ~; `
Acceleration in an arbitrary direction, 任意方向上的加速度
0 q# s+ O0 E- Y" y/ cAcceleration normal, 法向加速度1 ^# B% X; P% f, b Q
Acceleration space dimension, 加速度空间的维数
, }: Z2 ~5 u# ^Acceleration tangential, 切向加速度8 t, ?) b3 P7 B0 _& l
Acceleration vector, 加速度向量
' i. Y S5 t! G+ p" ?$ QAcceptable hypothesis, 可接受假设
- E. z* w1 [$ I6 @Accumulation, 累积+ \. P5 \! |% f4 ?
Accuracy, 准确度
$ m5 E/ c! r. j& V; r' [2 A" O4 |Actual frequency, 实际频数+ d, P! @7 x3 E. t+ f
Adaptive estimator, 自适应估计量9 E3 y5 h* j% ~# K( ^+ {
Addition, 相加) f( `& K3 g$ s; E7 r1 [
Addition theorem, 加法定理
2 ~' ^& B5 y3 c o; sAdditivity, 可加性8 l: i; D) S2 a! N! J3 x3 d
Adjusted rate, 调整率9 ~+ Y5 P# D5 C/ r
Adjusted value, 校正值9 [* p" N) F$ c) w
Admissible error, 容许误差
% X8 n$ \6 i$ TAggregation, 聚集性9 m: ?" T6 t; E) l
Alternative hypothesis, 备择假设
& T& {1 s' P/ V6 T' Y3 NAmong groups, 组间
3 [, }# Y8 |. e" G; Z$ v& @0 lAmounts, 总量
) q8 J8 [8 k5 f0 C4 V8 C oAnalysis of correlation, 相关分析6 @1 e# z* y3 k! C4 K
Analysis of covariance, 协方差分析
" U; o+ f; n2 V2 P% s: W7 wAnalysis of regression, 回归分析8 M& j# |) H4 h; T ~
Analysis of time series, 时间序列分析 W! a" F' a% ?, Z$ a
Analysis of variance, 方差分析
& O& E! k- _' r* wAngular transformation, 角转换4 c3 ~$ L! }2 q( c
ANOVA （analysis of variance）, 方差分析
2 F- N4 s& E" t: u. I6 f' v6 J9 L1 UANOVA Models, 方差分析模型
& f4 B0 h* B9 H; B9 cArcing, 弧/弧旋/ G' r2 O+ e/ a" [' x" _
Arcsine transformation, 反正弦变换
! a( @) N5 _' G6 {3 LArea under the curve, 曲线面积
/ Q, I) ]2 C, T0 I+ DAREG , 评估从一个时间点到下一个时间点回归相关时的误差 ( [4 h6 K/ ]. x. j: m* f/ u; i
ARIMA, 季节和非季节性单变量模型的极大似然估计 P/ |: n! n7 {0 j# {
Arithmetic grid paper, 算术格纸" q4 c3 P2 j( Z- y) ?; K: z$ R
Arithmetic mean, 算术平均数
# k& O+ n5 g9 B6 z8 C( \! aArrhenius relation, 艾恩尼斯关系
6 r; F+ x0 |8 [) g7 L& c# uAssessing fit, 拟合的评估9 J- x' s2 \% _: `! C% w$ H
Associative laws, 结合律
! |: v1 n5 ], O* M9 ~4 |Asymmetric distribution, 非对称分布6 y* t4 F' m0 ?; G* R2 J+ ~# g
Asymptotic bias, 渐近偏倚
" R! V1 u2 I, f4 NAsymptotic efficiency, 渐近效率
1 o) C* n6 ?! U8 S, B# eAsymptotic variance, 渐近方差5 _. B; `4 j; Y
Attributable risk, 归因危险度2 B) Q7 _9 z; g1 A
Attribute data, 属性资料
2 c4 R2 `5 H5 X; MAttribution, 属性
# J8 y% H' i6 q4 {Autocorrelation, 自相关. \. U+ a1 j: d( T) L
Autocorrelation of residuals, 残差的自相关* S4 F; V0 J V* m n: P' e
Average, 平均数+ h2 N( x! z3 W. X
Average confidence interval length, 平均置信区间长度; o; Y1 K/ G6 u6 }! p
Average growth rate, 平均增长率
$ a7 V% ]6 f! `! T: t8 u b x) uBar chart, 条形图, o$ t+ E, w4 L/ \
Bar graph, 条形图* p% W8 n' v/ X! p( _' B- \0 u/ K
Base period, 基期
, j0 ^" V# z1 d5 W2 yBayes' theorem , Bayes定理
1 C/ |2 I' |! t' | ABell-shaped curve, 钟形曲线4 Q9 n- N/ R+ v
Bernoulli distribution, 伯努力分布4 t$ ~# M& B8 j9 D) u' A
Best-trim estimator, 最好切尾估计量
\; i% P2 A( k$ G T7 WBias, 偏性( ?3 ^/ ~1 A# Z, u' X
Binary logistic regression, 二元逻辑斯蒂回归
5 i5 A9 s) ~" t' bBinomial distribution, 二项分布
* `$ ]* e& Y' @$ RBisquare, 双平方
2 G9 \: d+ p& e7 ?Bivariate Correlate, 二变量相关6 g) h' W; f* a7 d3 i4 a R
Bivariate normal distribution, 双变量正态分布
8 F: j$ t% L( l) t5 ~2 bBivariate normal population, 双变量正态总体4 {# r# H) L" e
Biweight interval, 双权区间* v% B8 P1 T' ?: [! X* q% e
Biweight M-estimator, 双权M估计量
( Z# @( ~) l1 M: n' f+ oBlock, 区组/配伍组" j9 y5 ], q7 |; S# j. O
BMDP(Biomedical computer programs), BMDP统计软件包# p4 q$ h( r, U7 R
Boxplots, 箱线图/箱尾图
8 I# v( q+ h* F2 @8 {+ pBreakdown bound, 崩溃界/崩溃点
, v. T/ `& @* u/ OCanonical correlation, 典型相关
2 b' v; S( E& E/ v$ P: hCaption, 纵标目
: o l6 }- ^0 x. E2 o+ r* W* w2 F6 ~Case-control study, 病例对照研究
) G+ e3 G3 J4 A- BCategorical variable, 分类变量; R3 O+ p g/ S1 E2 r3 }$ o2 p
Catenary, 悬链线) X! E+ U$ }* z# B8 ]; ~
Cauchy distribution, 柯西分布
8 w p1 i8 }4 t0 f+ HCause-and-effect relationship, 因果关系
$ k7 b8 J8 e( d4 f8 X) @Cell, 单元% ?7 N" }0 S! u' {0 N
Censoring, 终检. x) v* o- W6 P1 R& w
Center of symmetry, 对称中心2 S4 e; D+ t! p
Centering and scaling, 中心化和定标; c7 M/ m' H8 Z; l$ i
Central tendency, 集中趋势9 m N, D7 c! f0 a4 A* ~8 i
Central value, 中心值
* w) x5 Q1 s0 U6 _0 x! YCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
3 m2 e9 `! z- ZChance, 机遇
9 ~1 c1 m1 S, Y5 o! F5 rChance error, 随机误差
7 _0 W. M6 K+ d% o! d% w, jChance variable, 随机变量
7 f1 l) q" \2 ~0 X; q, CCharacteristic equation, 特征方程- v5 _4 |" y* H0 g Z! u6 ?
Characteristic root, 特征根
0 `) A; |) c9 {. `& n$ b4 }Characteristic vector, 特征向量7 p L7 B1 V& a' p) T0 h8 D$ J
Chebshev criterion of fit, 拟合的切比雪夫准则% V: }* V( X( ~) o# O1 C
Chernoff faces, 切尔诺夫脸谱图& r6 e- i) E# X) `9 s/ j5 o
Chi-square test, 卡方检验/χ2检验
$ f" ]) b' ~, t5 JCholeskey decomposition, 乔洛斯基分解) D& @6 |& S3 e4 c: A
Circle chart, 圆图
& G; C2 d$ P% S5 m9 gClass interval, 组距
' ]0 b# n0 |( h% t& {Class mid-value, 组中值
7 ]. T' _/ z- b( WClass upper limit, 组上限
4 {2 i7 T) L/ i# gClassified variable, 分类变量
, h5 p, X- h5 q9 J" z4 q3 `Cluster analysis, 聚类分析
- X4 N* F$ Q3 G( CCluster sampling, 整群抽样
0 I! X: v& a* w6 _3 Y/ @7 o5 Q+ ?Code, 代码
1 O2 ?& p w6 ~. t( Y. sCoded data, 编码数据 P! B! `+ X n$ q8 f9 A
Coding, 编码
# K& O4 [9 x. ]+ wCoefficient of contingency, 列联系数) w% l, T$ g" q) h6 z
Coefficient of determination, 决定系数- W8 _0 c2 s/ e' S
Coefficient of multiple correlation, 多重相关系数! S r2 `- _- B% Y2 [
Coefficient of partial correlation, 偏相关系数( I$ P4 x. X6 C9 h3 i
Coefficient of production-moment correlation, 积差相关系数
# u1 C( f' `( ~7 xCoefficient of rank correlation, 等级相关系数
. i* `9 Q7 [# tCoefficient of regression, 回归系数
9 ^! N- X- k7 XCoefficient of skewness, 偏度系数
6 z- a! X) F; o! x- x/ O' JCoefficient of variation, 变异系数
9 m0 S8 k& x) A0 K/ `$ bCohort study, 队列研究5 K6 K$ k5 k- g5 _" `* s
Column, 列
4 G6 m8 f/ f+ }1 m) ~! B5 GColumn effect, 列效应* V) W1 z5 O' g
Column factor, 列因素5 y S' X/ E9 C: v* ?6 V w
Combination pool, 合并& w% {" V7 s, Q$ R1 T1 f% [& _2 Q- S
Combinative table, 组合表4 E9 k/ O, _7 U( P( N
Common factor, 共性因子: I( l! N; G; [% \# i1 i9 _% M
Common regression coefficient, 公共回归系数
" z: N6 z C, T$ N4 DCommon value, 共同值
" S4 C/ Y1 K( vCommon variance, 公共方差4 E( ?5 F( n# A1 f1 e
Common variation, 公共变异
/ `3 u0 ^4 s2 p) r. w5 e5 ]Communality variance, 共性方差, W' b, m; E- d4 a1 m+ T/ _3 V
Comparability, 可比性
$ `4 U- O; t( k* v) iComparison of bathes, 批比较1 s' K3 C/ q9 s5 Y) {$ @
Comparison value, 比较值
, ^* B7 Y4 D! r& g) S$ I0 sCompartment model, 分部模型/ @$ M/ l* @" F7 y+ z
Compassion, 伸缩+ E" P; \( d( a& w
Complement of an event, 补事件
1 U4 Q) b' P: Z/ N5 XComplete association, 完全正相关. L% }- \6 @# U' Y$ [" x2 f( ]7 c% s
Complete dissociation, 完全不相关# V. D- A0 O9 V' I3 K( k
Complete statistics, 完备统计量& q( w: l; g @; }' k. I1 J
Completely randomized design, 完全随机化设计
) g2 s% y3 F( t6 u' _Composite event, 联合事件
. Z# h* u" B+ q' Y7 o7 _& pComposite events, 复合事件
$ D+ }8 c4 _: l. @" iConcavity, 凹性5 K) p4 u8 v% m6 Z! W
Conditional expectation, 条件期望/ S e$ Q. y3 w# Z
Conditional likelihood, 条件似然
" A7 \; H6 x* GConditional probability, 条件概率+ Q5 H9 z5 v- Q+ {; j
Conditionally linear, 依条件线性( x( K+ y3 I& a3 ^; O4 l* c
Confidence interval, 置信区间
/ m& K. X0 O4 n8 A4 j% H& B& BConfidence limit, 置信限" W* M. s" A. i5 ~: z r
Confidence lower limit, 置信下限4 K$ ^+ H1 R% d# r# y/ Q' t" `9 }
Confidence upper limit, 置信上限
2 y. S( R+ _: s" _+ o. m( ]Confirmatory Factor Analysis , 验证性因子分析2 q) b2 r" q! K( w) Z* ]; s; U
Confirmatory research, 证实性实验研究
3 ]6 N: v+ m/ R( _# D% nConfounding factor, 混杂因素1 X3 G) G- h2 @1 m. E! I
Conjoint, 联合分析6 o/ g* \1 `2 u4 @6 ?4 P
Consistency, 相合性! m3 ^$ V' t9 _2 U5 n3 s
Consistency check, 一致性检验* l) c W: u5 q2 ?& b' G6 ~
Consistent asymptotically normal estimate, 相合渐近正态估计9 q5 \+ ]' D6 E' [
Consistent estimate, 相合估计( U3 d3 `2 X$ `
Constrained nonlinear regression, 受约束非线性回归9 v% F. E6 n( |" c8 d
Constraint, 约束
, \3 b G' n, R( T$ b2 N, b+ ^Contaminated distribution, 污染分布
$ m7 X( `2 i" D! MContaminated Gausssian, 污染高斯分布1 L: X4 h7 z% V/ x9 \ @4 `
Contaminated normal distribution, 污染正态分布
, I2 G4 c4 G) F7 R6 MContamination, 污染9 Q! a) ?7 u4 u9 o0 r+ U
Contamination model, 污染模型
8 x: Y0 N' P1 LContingency table, 列联表( s' z# v% m4 t7 r
Contour, 边界线, @( x& H/ S4 q: L. Z( f; L4 Q9 ~
Contribution rate, 贡献率* G% \& l( _# v; |3 u: u% k% r
Control, 对照8 u% e ]/ L$ [6 ?9 M
Controlled experiments, 对照实验* m" O+ a8 R; n2 _2 l; m
Conventional depth, 常规深度! V9 H2 n, }' T y# `( c, d
Convolution, 卷积
6 K8 c8 V% i: r' Z5 u0 c- dCorrected factor, 校正因子
4 }+ C/ @5 K M+ l8 |5 nCorrected mean, 校正均值$ t* k6 Y5 i1 [1 m4 Q0 ]( t
Correction coefficient, 校正系数2 L7 h+ ^! y' E. K5 F
Correctness, 正确性) n& w( j" H3 n- l4 C% Z
Correlation coefficient, 相关系数
% C2 L3 U; Y8 v! I% \# ^Correlation index, 相关指数
, s# Y8 _/ \- Y: D3 }: S ECorrespondence, 对应/ B" L5 E0 P+ {0 b
Counting, 计数2 I* \7 I( }, A% l) s9 J
Counts, 计数/频数6 G8 v7 b- l) x. e* V/ I7 D
Covariance, 协方差7 L4 W/ j6 f, \2 Y
Covariant, 共变 8 i3 o; n7 h1 V0 _* H# @' t
Cox Regression, Cox回归
# U$ V; `- L$ ^; E; d& ]. W+ jCriteria for fitting, 拟合准则' `0 o9 W$ s3 h
Criteria of least squares, 最小二乘准则6 ?2 P+ a6 p( \$ P4 ~0 W
Critical ratio, 临界比
+ r7 ? w9 f' E. O$ jCritical region, 拒绝域1 Q% j% P" B p) T' r1 m6 F) |
Critical value, 临界值
/ S; `) I* ~3 L: m4 C1 ~) @, ~Cross-over design, 交叉设计6 P0 h9 f* ^* {# L$ ^
Cross-section analysis, 横断面分析" B5 n3 }- T# s& v3 B) h8 s
Cross-section survey, 横断面调查
$ D$ v# M0 Q! I- n9 z; t3 a( RCrosstabs , 交叉表 8 g; w1 }% \9 E. R2 ]% p0 Y; H
Cross-tabulation table, 复合表
8 V3 k# y7 `5 K* ?1 c9 QCube root, 立方根
) Z8 q% X3 r- v4 R6 vCumulative distribution function, 分布函数
; |: ^" v% d3 c' [! QCumulative probability, 累计概率
; M; w" e0 q$ Q; E- ]/ N2 G/ fCurvature, 曲率/弯曲
6 C2 R$ C K& Y0 _% CCurvature, 曲率
: d! ?6 E4 N" d0 n mCurve fit , 曲线拟和
# k; L4 n8 M, A* h$ p; V: a/ R! pCurve fitting, 曲线拟合8 H) |$ T- {$ T0 C o- C
Curvilinear regression, 曲线回归
' Q: a5 ?1 Y1 L1 O4 z' b, h7 K. i; FCurvilinear relation, 曲线关系
. @+ `& p, O1 [ V' C, m8 X# ?Cut-and-try method, 尝试法
3 e5 \% x$ T" r4 u. \Cycle, 周期
: D7 @7 |1 I6 f9 n* M1 M2 ECyclist, 周期性
9 c, S* y! `5 Y, i" MD test, D检验
# y& F/ F7 f3 U4 g. Y) m! H0 E# fData acquisition, 资料收集0 A% Y$ D, H% c; |" L
Data bank, 数据库
+ |2 M' V$ G1 hData capacity, 数据容量
6 g: }9 \5 F* j& {# d& AData deficiencies, 数据缺乏
- J! y- N: J# N+ o" ~% c/ e# IData handling, 数据处理" H2 t% x- j- R. K D7 y
Data manipulation, 数据处理
3 Q% h: n- B% a) o. L$ X2 ^( @Data processing, 数据处理$ [; {+ T" ^2 O6 C
Data reduction, 数据缩减
5 m0 @/ Q# s, j/ i" J# QData set, 数据集4 I( O1 b: I0 y* M, a7 J
Data sources, 数据来源! T: Y! C" l& G% {$ _
Data transformation, 数据变换" q3 H/ o$ a7 h0 z0 @6 M
Data validity, 数据有效性
; @) z/ v# p( f( F% Q" {Data-in, 数据输入
" ]" c, l$ I x5 Y: R7 E- aData-out, 数据输出: h6 m- X( T5 ?: ~0 o8 X+ r3 M
Dead time, 停滞期
: z2 p# o) P4 m6 tDegree of freedom, 自由度
+ D6 L2 p% ?$ f; ~& r+ qDegree of precision, 精密度$ ^. _0 |/ N7 X" h# k# F8 o! `5 Z
Degree of reliability, 可靠性程度0 V1 t; V/ V: _ e$ c/ R. N' @
Degression, 递减
1 m, y: [1 u1 hDensity function, 密度函数
( W$ I" C3 d) I) W) {Density of data points, 数据点的密度 i7 b/ M2 E1 T1 E' _ A! v
Dependent variable, 应变量/依变量/因变量
1 N1 L5 M( \0 i: v; a% @Dependent variable, 因变量
2 d% `/ Q8 k7 ~. w. s6 _) \Depth, 深度 U8 v9 S4 f3 _" Y7 U/ q
Derivative matrix, 导数矩阵
0 G- @$ I( P; TDerivative-free methods, 无导数方法
8 K. s5 y6 c4 G4 ^0 M6 BDesign, 设计
6 M+ Q3 f3 D( wDeterminacy, 确定性
0 H: S' C& q8 e0 B" [- K( g8 I0 ZDeterminant, 行列式
% N0 }, Y1 w6 g& vDeterminant, 决定因素* Z$ s/ u4 j9 K0 `
Deviation, 离差. u6 J. e( O) X: j. m) v# i
Deviation from average, 离均差- G/ a: j+ k- y) u; H
Diagnostic plot, 诊断图 Z6 f6 H' J3 y. x. W ]- L
Dichotomous variable, 二分变量
% ]2 L9 F6 P' ~" l3 M" `Differential equation, 微分方程
`: a( P3 e O! Z( I# MDirect standardization, 直接标准化法) }0 l! x. q$ A+ B' s
Discrete variable, 离散型变量
5 Z# R9 @& e" [* q" p* MDISCRIMINANT, 判断
) q& D; F% Y6 R6 O5 W* TDiscriminant analysis, 判别分析3 ]8 }) L1 X; n, Z
Discriminant coefficient, 判别系数1 B1 v. A/ I0 Z- V! ^ p
Discriminant function, 判别值
: U/ D& h' _/ ^9 w; T/ {Dispersion, 散布/分散度: }3 A% `6 R9 g: D' H+ R
Disproportional, 不成比例的2 k$ [, W. h% ]4 L
Disproportionate sub-class numbers, 不成比例次级组含量: K# _& I) Y. A* _- a
Distribution free, 分布无关性/免分布$ h1 f" ~/ N% N' [7 e
Distribution shape, 分布形状
$ X4 ?3 d9 s5 ]9 e0 F# HDistribution-free method, 任意分布法
2 J1 |% a0 q5 @ v6 ^Distributive laws, 分配律
- x9 r6 O, {8 c# D9 B- kDisturbance, 随机扰动项& U9 S% ~! E4 J4 Z* u
Dose response curve, 剂量反应曲线
& h2 N7 U* Z- b7 z7 z0 Z( `Double blind method, 双盲法2 x4 g) X2 |. ^# v# u9 L6 ?
Double blind trial, 双盲试验9 V6 M$ K6 ~. Q
Double exponential distribution, 双指数分布
3 G& c$ Z/ h& R; R# ]: KDouble logarithmic, 双对数+ a- o, j6 h: J# r8 e* x$ i
Downward rank, 降秩
/ K8 C- q; {/ A# n$ |4 j. Y) QDual-space plot, 对偶空间图* Z/ k! s1 p* R
DUD, 无导数方法1 V, \! J4 F. T4 `; H
Duncan's new multiple range method, 新复极差法/Duncan新法& @. v& I% v- e: s1 _6 y
Effect, 实验效应
! |& t$ Y1 J Y7 ~1 SEigenvalue, 特征值
' S4 D5 p- O+ e5 O5 KEigenvector, 特征向量
% B) C/ R! b# ^Ellipse, 椭圆4 T, ^) t) ` g9 Y2 g
Empirical distribution, 经验分布- u- R, P- K: T$ s
Empirical probability, 经验概率单位
! i' [9 q/ A5 B$ e2 h+ F2 MEnumeration data, 计数资料
7 Q; ?0 J6 a, QEqual sun-class number, 相等次级组含量
9 K3 ?8 f) s/ y! ~# P8 zEqually likely, 等可能
* O! V K3 Q1 b. ]7 REquivariance, 同变性
& i+ |' `. R( E$ z* @) u- |Error, 误差/错误
1 p3 ]$ u) I0 f6 @, l) K$ xError of estimate, 估计误差9 t6 U# x4 s) K' f4 J* A) h/ ]
Error type I, 第一类错误
3 N* v6 W h+ }, U- a. ` p! dError type II, 第二类错误
5 Z4 w/ g% S) l4 n" j. g1 vEstimand, 被估量5 }4 x- K! D1 b% |
Estimated error mean squares, 估计误差均方; c. a: I0 z# v7 Y- D6 W( G
Estimated error sum of squares, 估计误差平方和
! T0 o- V' x1 D1 A% B: M+ fEuclidean distance, 欧式距离
/ p7 C7 ?8 B1 u2 A- Y, b6 u# rEvent, 事件8 `- T+ g9 I; ]
Event, 事件9 Q# M2 m3 \9 |# F i! m h
Exceptional data point, 异常数据点0 D0 N, l' p" q, @5 F
Expectation plane, 期望平面
# i; k+ U' \8 {) m2 v# `Expectation surface, 期望曲面7 m+ g! t! d9 J+ ^
Expected values, 期望值* d! ~3 p0 ~9 U: ]2 n
Experiment, 实验
D) x. x9 f+ N7 }$ _4 O" Q" o, ^Experimental sampling, 试验抽样7 X4 @9 d1 y9 e! Q
Experimental unit, 试验单位
. [9 v5 P) N' O! eExplanatory variable, 说明变量
7 S2 T. Q3 K7 P2 ^: U2 iExploratory data analysis, 探索性数据分析+ L& E. e/ [- f, t+ J! o: j* X
Explore Summarize, 探索-摘要
- ?5 {9 Z# W: J& `9 g& t3 I# dExponential curve, 指数曲线) S+ i n+ C, _0 e5 D9 k2 x) f; L) R
Exponential growth, 指数式增长
7 f- p3 A$ j6 ZEXSMOOTH, 指数平滑方法
1 \. e, z% v RExtended fit, 扩充拟合
- j3 s3 B( d& }Extra parameter, 附加参数" a) \) d. Q$ F5 S+ Z' J: g% \
Extrapolation, 外推法+ a* i. L8 L' l* a. h& S
Extreme observation, 末端观测值
: }8 M! f( T/ i; F% g/ x: YExtremes, 极端值/极值
- z$ D+ A/ B2 m \% iF distribution, F分布. j; d) t {% R. k/ r* ]
F test, F检验
5 U( A% K6 t7 [: P4 _+ h3 e& T8 ZFactor, 因素/因子
7 v; d9 E0 h& v& f8 t6 MFactor analysis, 因子分析
# `0 F6 r5 `+ O9 B3 o: r6 @Factor Analysis, 因子分析/ r; `: T# v% M- _ L% f
Factor score, 因子得分
) `5 |) `% c* ~, m- _' uFactorial, 阶乘0 y. @( `7 R' G' x
Factorial design, 析因试验设计
* \& y9 [; v4 O$ u8 J, Y9 Y2 ZFalse negative, 假阴性 r$ c. \6 a& [5 o$ h: F
False negative error, 假阴性错误
: P" e9 ^5 V1 g5 o( p4 r# Y! yFamily of distributions, 分布族
2 h1 _' X3 @$ A1 c+ A2 ]Family of estimators, 估计量族
8 |4 n* z1 ~5 }$ h5 N3 j. K+ _* G3 LFanning, 扇面3 @9 [+ g7 `& Z1 {' B+ b8 ^9 f
Fatality rate, 病死率
9 e8 \$ V8 S9 `1 kField investigation, 现场调查9 p k$ R+ b- P9 }8 o7 ]( k3 t: Q
Field survey, 现场调查
% }% @1 r( z/ ]. zFinite population, 有限总体+ Q8 ^7 k8 s; d6 `8 `2 W+ U$ [; V
Finite-sample, 有限样本
' [5 J! N, c6 V7 d5 gFirst derivative, 一阶导数. H8 g& d/ l' O+ \
First principal component, 第一主成分
" z5 n! s" ^4 W8 m7 h3 ^2 rFirst quartile, 第一四分位数
" u3 T) _$ u+ A$ u- J9 eFisher information, 费雪信息量
- `% H- I8 l9 ]; e- XFitted value, 拟合值
# V; A- R; [& M% u$ A* _0 HFitting a curve, 曲线拟合
& u; ~* U) T: k# LFixed base, 定基. ?4 y( y" t8 _8 \: |
Fluctuation, 随机起伏
9 N5 E! A4 U; X+ s. Y. D. DForecast, 预测7 ?' g1 ?, S* w, ^5 o
Four fold table, 四格表
- C4 ~1 _, l$ K9 q" Z) uFourth, 四分点- A, C' R1 ]- U6 r9 r! u6 o
Fraction blow, 左侧比率
0 C6 ~, z5 q6 Q0 NFractional error, 相对误差
6 A/ B6 E1 v. w; l0 I% w: ?& K% eFrequency, 频率# l$ Q3 _# R2 d3 }$ H: W. G& D
Frequency polygon, 频数多边图
6 [) E9 l; b* v" O& A6 s& }Frontier point, 界限点
" ~; b7 i! W8 VFunction relationship, 泛函关系
( B2 r6 m" Q2 N/ \! PGamma distribution, 伽玛分布
. z7 ]+ g+ Y5 Z, L8 aGauss increment, 高斯增量
- A. U! Y! m9 G' I& QGaussian distribution, 高斯分布/正态分布5 D4 s" @' x# }& D; F" w' g
Gauss-Newton increment, 高斯-牛顿增量. y4 q {) g- t. E6 q+ s" |( t
General census, 全面普查6 F N: o2 j; s& O$ |( @7 H5 R
GENLOG (Generalized liner models), 广义线性模型
g5 o9 Y3 z2 a. e, h$ H% F+ |Geometric mean, 几何平均数
) y' j& n t p! d' f& t% t. vGini's mean difference, 基尼均差$ s" O! c4 t2 F" p; A. p
GLM (General liner models), 一般线性模型 , m$ y& \" e5 |, c
Goodness of fit, 拟和优度/配合度
8 U3 l3 T8 w8 u8 O" XGradient of determinant, 行列式的梯度& [3 W( l" r1 P% e
Graeco-Latin square, 希腊拉丁方2 y* T. x- X5 L4 t( Q
Grand mean, 总均值- t" v, u- }0 F' |- T- `; F
Gross errors, 重大错误
0 W9 c( Y( v; b) X, yGross-error sensitivity, 大错敏感度
) M* B' M2 c+ xGroup averages, 分组平均9 |3 V" N+ p+ D' ~, U S j
Grouped data, 分组资料
. z5 `: J# f2 M5 g dGuessed mean, 假定平均数
4 M7 C5 Z: U, _" o) p/ f4 ^. tHalf-life, 半衰期
, Q4 {1 P, l+ JHampel M-estimators, 汉佩尔M估计量
: c* \ Y3 g, m0 p1 @2 ~8 mHappenstance, 偶然事件8 J+ y+ O- z$ Q1 l
Harmonic mean, 调和均数
9 }; S1 J2 S5 S3 P/ v2 u: ]- mHazard function, 风险均数! Q% O8 Z8 v0 r6 L7 P+ g0 k
Hazard rate, 风险率- g( \3 A8 | b7 {5 [9 k9 |9 c" h
Heading, 标目 6 t7 S* w5 x( s7 Q
Heavy-tailed distribution, 重尾分布
) k4 B' F6 w) O q, tHessian array, 海森立体阵
1 a5 Z! k' b Y8 p: M P) |Heterogeneity, 不同质* l- c: D" `8 ]# c* g$ R& Z
Heterogeneity of variance, 方差不齐
6 t; X7 k* R6 |Hierarchical classification, 组内分组
+ Z9 U9 F8 L/ U7 v/ x) _Hierarchical clustering method, 系统聚类法
& G8 K9 \' l% M4 F3 V# B3 h* KHigh-leverage point, 高杠杆率点/ _8 l+ n0 g: U1 L8 d0 l
HILOGLINEAR, 多维列联表的层次对数线性模型
1 s; H8 _8 L4 ?9 E# oHinge, 折叶点
4 B9 ?$ f) V1 Z- @Histogram, 直方图4 r9 L: Q! n; e+ U
Historical cohort study, 历史性队列研究
! J3 o4 Z( u1 }! VHoles, 空洞
# K& n3 n" ^$ O7 j. HHOMALS, 多重响应分析
! \ f Z& E0 o0 k- @7 HHomogeneity of variance, 方差齐性' o+ E& a* ^( u! C9 S- l1 Q' M" T; O
Homogeneity test, 齐性检验; d$ i' R$ @& v! L
Huber M-estimators, 休伯M估计量
9 `! k. z {. jHyperbola, 双曲线# y3 D, O' w- V: g( U# W7 v
Hypothesis testing, 假设检验
9 z# d1 D9 o3 B8 QHypothetical universe, 假设总体7 f. w* [, k3 y
Impossible event, 不可能事件
/ B i# U9 H0 ]- h, y# Z0 cIndependence, 独立性
1 c$ w$ p! v9 B+ [3 e1 E, q+ @Independent variable, 自变量+ l' B4 u( x! `! B" g. v
Index, 指标/指数9 V/ V) a% b& C4 K, \- X
Indirect standardization, 间接标准化法" I" J7 k4 s" Y
Individual, 个体
5 Y4 V* W' A! F: o S# ^# a6 ~9 RInference band, 推断带
# @7 N6 E9 e! |7 a" R6 I( eInfinite population, 无限总体 T: Y- P! M( y) o' i( W
Infinitely great, 无穷大
1 I" }; n6 ~* Z5 l vInfinitely small, 无穷小/ A( q$ s! a' k, o3 P. D
Influence curve, 影响曲线4 {2 U8 y% X5 y0 w0 k9 ~! V. S* ^
Information capacity, 信息容量9 @3 w# P* \; n) b. K& p8 e
Initial condition, 初始条件, c7 L8 P. G3 T8 l9 ^( l
Initial estimate, 初始估计值$ U4 t& X: R% q
Initial level, 最初水平
$ k. ^/ f$ u) v2 A1 {! EInteraction, 交互作用: f0 c. [; t2 o8 E% t5 v
Interaction terms, 交互作用项1 l. L9 ]3 V& A1 T0 E
Intercept, 截距
: u; o1 r" q- Z o+ _Interpolation, 内插法
4 b/ ]- Q/ [. o/ ]Interquartile range, 四分位距2 n0 Y4 g2 k" \' g
Interval estimation, 区间估计* ~! {+ o( J |6 f9 A
Intervals of equal probability, 等概率区间
+ R% L8 q3 g: Z7 }* g7 MIntrinsic curvature, 固有曲率3 j6 y4 c& k! J: H( G
Invariance, 不变性
$ E; H0 {! b; A2 N' t& cInverse matrix, 逆矩阵
( \; \, E0 s/ hInverse probability, 逆概率
: h$ I2 X0 ^4 H+ s! J% e7 B( v9 cInverse sine transformation, 反正弦变换
( u$ q3 q- ~" S" n6 E2 l6 oIteration, 迭代 . h0 x7 k8 g/ n" \% I4 Q8 }- V" c
Jacobian determinant, 雅可比行列式
0 m. F3 E; N V. a, q4 DJoint distribution function, 分布函数, `: d8 |6 U9 B
Joint probability, 联合概率7 H1 e; w7 d, J, F2 s
Joint probability distribution, 联合概率分布
0 z/ M) J4 E( C/ _2 L3 WK means method, 逐步聚类法 X% d9 g: p4 l# I& u9 E) j/ u
Kaplan-Meier, 评估事件的时间长度
% v- \7 |" E$ d4 S1 R4 h- aKaplan-Merier chart, Kaplan-Merier图
' b5 e5 k: u+ Y3 ] a7 bKendall's rank correlation, Kendall等级相关( I! G' @# q3 P* g
Kinetic, 动力学7 F& q( J& @" q8 W A
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
! J, J+ x8 z/ a! _/ AKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
! y! X7 e( v3 t/ mKurtosis, 峰度
1 ?$ n& T% m- hLack of fit, 失拟
& ?2 |0 S- h1 g5 V! ^Ladder of powers, 幂阶梯
" J/ T, Z9 M1 u1 ?6 @+ FLag, 滞后; W: m% O: }1 o4 l1 \6 u
Large sample, 大样本' w. C: Y5 S1 F
Large sample test, 大样本检验4 o; ?4 `3 ?% g$ ?9 V
Latin square, 拉丁方" n$ D, X+ o9 v$ h0 |$ v
Latin square design, 拉丁方设计
, l7 \" {" W% G; @$ {% R+ vLeakage, 泄漏
8 M: ^& H, N& L4 l' I* D9 zLeast favorable configuration, 最不利构形2 {, \& d6 c, F2 s r8 ^
Least favorable distribution, 最不利分布5 K: b8 q! M. d7 s
Least significant difference, 最小显著差法4 z2 }7 m) u0 Q6 H. Y& O. V
Least square method, 最小二乘法. o, a2 ] H0 e% J7 _+ {- e% b; l
Least-absolute-residuals estimates, 最小绝对残差估计0 V3 j2 ]7 |9 H& }7 p7 s
Least-absolute-residuals fit, 最小绝对残差拟合
& w' T; U$ S0 S! h6 ?7 i( Y% BLeast-absolute-residuals line, 最小绝对残差线3 x6 R* S! `( @: N
Legend, 图例
/ B* a1 _ _& S& Q* B W8 {L-estimator, L估计量$ m" ]+ a; {/ F6 K! f% m0 v
L-estimator of location, 位置L估计量9 |& T, ?3 p; U4 _0 s$ ~( Z
L-estimator of scale, 尺度L估计量: p- I; U1 f( {1 s2 |( F9 S
Level, 水平
) K; G$ L$ ^7 A; T; a; p8 rLife expectance, 预期期望寿命
5 \. x8 u6 T; mLife table, 寿命表
5 S; a- W$ F3 b- U5 eLife table method, 生命表法
- d$ i8 Z# |4 M/ g: a6 v( rLight-tailed distribution, 轻尾分布
. z! l2 Y" X" R5 F6 x" nLikelihood function, 似然函数4 u/ `! k! k; O
Likelihood ratio, 似然比
8 T* c$ v! w+ t* U, y' gline graph, 线图
0 o' v0 D8 B8 V- q: p( `1 u. HLinear correlation, 直线相关
; ^+ K! S& i$ F% I3 y3 i ?Linear equation, 线性方程
+ H2 ^( Z& A* m: q- P6 M) W% d" sLinear programming, 线性规划
. z( r0 y" I; VLinear regression, 直线回归
( T9 e8 g8 A4 B* B' d' F. v6 ILinear Regression, 线性回归% T3 i0 d: D. d& T* e6 J0 q
Linear trend, 线性趋势
6 K/ a9 \# s+ b, A% ?- T, C) ]. y4 NLoading, 载荷
( B% a% [9 ~( `6 F, ?5 D# _Location and scale equivariance, 位置尺度同变性
4 S" \3 m% T( \Location equivariance, 位置同变性
3 C1 K* Z1 r! ^Location invariance, 位置不变性/ b2 v9 O M6 q# V6 ^
Location scale family, 位置尺度族
" k' l% f# E, G" m1 mLog rank test, 时序检验
; E- {7 S& z2 B# N; ZLogarithmic curve, 对数曲线
. s; C H( c# c/ s" R+ F. wLogarithmic normal distribution, 对数正态分布
7 e. {. c/ ^7 @! F8 ?; ?Logarithmic scale, 对数尺度' _0 m/ A) \* [" V \2 ]" K' r
Logarithmic transformation, 对数变换
3 a3 q+ o' u- }Logic check, 逻辑检查
$ I/ N+ {* _3 W/ LLogistic distribution, 逻辑斯特分布8 r( t) M- }1 u2 I& \9 q- ^
Logit transformation, Logit转换
# j4 I% L) ~) m, CLOGLINEAR, 多维列联表通用模型 2 S; b- [9 m2 D, _1 g' S6 G* e
Lognormal distribution, 对数正态分布7 n" } C$ ]' E9 _, S0 Q0 P
Lost function, 损失函数
5 i6 V3 Q+ t3 b$ kLow correlation, 低度相关
^( c0 s' t4 C6 S9 v' qLower limit, 下限
+ _1 V3 H& L- I2 ~4 l mLowest-attained variance, 最小可达方差
* p* S- k6 F/ `' J" ?& F/ JLSD, 最小显著差法的简称
( ]5 T" l! H% p: g6 `0 v; M: ?Lurking variable, 潜在变量
( b) K- d* q- N9 H+ `% y) zMain effect, 主效应$ y8 o. I: K n, A
Major heading, 主辞标目1 i6 \* o1 e" s6 f6 O
Marginal density function, 边缘密度函数
3 P; Z# `9 m* M1 B$ s: M! OMarginal probability, 边缘概率' }/ ]! }4 s& a- J( D
Marginal probability distribution, 边缘概率分布
$ ^0 a, _3 g- E. G; lMatched data, 配对资料! e2 F0 N7 M* r9 K
Matched distribution, 匹配过分布4 m0 C3 e1 H( O! X r' h
Matching of distribution, 分布的匹配" w. g! v" u" b0 y% c
Matching of transformation, 变换的匹配" Q/ w+ H5 t+ \; i7 g% e4 F
Mathematical expectation, 数学期望
5 ^) `) J: G; M' C @& S- g$ OMathematical model, 数学模型
8 O1 }* C* u, R1 Y( _Maximum L-estimator, 极大极小L 估计量
! P: `8 K1 a9 V% D1 h& Y& zMaximum likelihood method, 最大似然法7 C+ i# @3 v6 J
Mean, 均数! t j7 ?; b) M' |- @
Mean squares between groups, 组间均方) C% k( o4 j1 R }& B
Mean squares within group, 组内均方4 A5 p. F; Z1 C/ z; p+ T2 a
Means (Compare means), 均值-均值比较$ d/ e3 u" L7 J
Median, 中位数: X6 ]2 m/ X8 O7 E6 \1 @
Median effective dose, 半数效量
; v) V9 K6 b" T" o2 K( y% [. xMedian lethal dose, 半数致死量* y& K( o+ G9 z( F+ z4 \
Median polish, 中位数平滑& d+ ~5 p x3 p D# n. P* C2 ?
Median test, 中位数检验% p' e2 z( F' [' x; b. o6 J
Minimal sufficient statistic, 最小充分统计量
" r1 F* G% }( k; f) ?( LMinimum distance estimation, 最小距离估计
- h9 o$ S: X' D4 NMinimum effective dose, 最小有效量7 |3 Y9 \% V9 f d, |' i
Minimum lethal dose, 最小致死量2 D* i' Y; ?: }7 I' K
Minimum variance estimator, 最小方差估计量' y% G e' S2 @7 s) J0 x
MINITAB, 统计软件包
9 h) d, ?( V3 `Minor heading, 宾词标目
) a& O; N/ H5 ^! W s2 cMissing data, 缺失值, `7 S5 a- j# y" K
Model specification, 模型的确定& [8 V- Q5 Q1 C' n/ b7 g3 _
Modeling Statistics , 模型统计) q4 C4 b8 |) V% O* s) t& K$ v
Models for outliers, 离群值模型
& F$ s4 C! \* J$ q! G$ L0 jModifying the model, 模型的修正4 o# M. q+ u& i$ Z3 D" W' H
Modulus of continuity, 连续性模( k+ Z: ?) e, m3 G+ V$ n5 S
Morbidity, 发病率 # F6 m6 y# J1 y$ D
Most favorable configuration, 最有利构形
( q" m# g9 p1 H3 {, R6 f; T* ZMultidimensional Scaling (ASCAL), 多维尺度/多维标度
4 C0 W6 ?2 K7 _5 S3 O% Z. E3 _; {- fMultinomial Logistic Regression , 多项逻辑斯蒂回归
7 C* d: `- c8 iMultiple comparison, 多重比较) m1 w7 k D. O! h5 o3 G M
Multiple correlation , 复相关% j0 c" Q; ?6 R% I9 u& x/ W2 j
Multiple covariance, 多元协方差
9 }1 [0 }( q8 c6 X' @Multiple linear regression, 多元线性回归
4 y7 o& ]& M% d6 x9 P4 i/ _' H7 [Multiple response , 多重选项; j( ~1 }# R7 T: }0 N
Multiple solutions, 多解8 P! ~: g7 i: j* v& t
Multiplication theorem, 乘法定理/ B) o$ i. y. i8 R0 z: }
Multiresponse, 多元响应5 `3 d; T( D7 J3 z' Z
Multi-stage sampling, 多阶段抽样
9 @* g$ n3 E# g( IMultivariate T distribution, 多元T分布0 a* ]. k2 g! \/ x) a" h8 h$ c" \
Mutual exclusive, 互不相容
, `$ l8 _6 j; t, W0 ?# XMutual independence, 互相独立7 \( q8 _- B/ V! |
Natural boundary, 自然边界4 C8 P7 D* W+ ^( P) }
Natural dead, 自然死亡9 B7 d8 P7 i$ U! [
Natural zero, 自然零( d- F( i5 N, [4 G# a$ x) t/ `1 ]+ I
Negative correlation, 负相关
! @! s( W. w, |! }3 H. CNegative linear correlation, 负线性相关- v$ f/ g$ E3 z4 G/ ^
Negatively skewed, 负偏
- w) U/ T @* u1 F& x. CNewman-Keuls method, q检验
2 z. n9 l# E1 W+ w' QNK method, q检验
. g1 l* e4 {6 j1 oNo statistical significance, 无统计意义
( M9 R2 X3 E. |* L* FNominal variable, 名义变量
, Q7 L' t8 s( L& F0 {: i' x3 vNonconstancy of variability, 变异的非定常性& b1 F' B' I8 u4 q' T
Nonlinear regression, 非线性相关
1 J- P8 o X @3 t) pNonparametric statistics, 非参数统计: Y, e: S# w! }8 ]) |8 [
Nonparametric test, 非参数检验0 V |9 O2 z7 h, i# D! E
Nonparametric tests, 非参数检验
4 X; }7 j- I* e8 R7 c8 N+ ZNormal deviate, 正态离差/ x" y6 v, I3 p. ~. a- p
Normal distribution, 正态分布
8 N" k o+ V$ H. B9 j9 PNormal equation, 正规方程组
/ m5 W. ^6 a% q9 D7 ]1 C2 J5 dNormal ranges, 正常范围
, d% z4 f6 U& Q) M- _" X6 dNormal value, 正常值
1 F+ B: G2 ~8 L" F% H1 b) ~% x3 ONuisance parameter, 多余参数/讨厌参数
0 K1 h% S4 f4 CNull hypothesis, 无效假设 2 C3 J" n( U9 \/ n1 `% Y' ?+ r
Numerical variable, 数值变量
. |# ]4 t u# a5 m( q% C( n& @# mObjective function, 目标函数
/ x; Q Y; _7 s* oObservation unit, 观察单位
5 F9 G& N/ f2 ]# m3 L3 B/ uObserved value, 观察值
2 H: A% h/ k. t0 d; U) z0 COne sided test, 单侧检验
2 {# M) G' Y' OOne-way analysis of variance, 单因素方差分析
& N7 O& ^" D- j6 p i: AOneway ANOVA , 单因素方差分析
& u; L3 e, J: b8 k2 rOpen sequential trial, 开放型序贯设计$ l* _$ Y. L; m1 g: N9 o
Optrim, 优切尾# e- d S% e3 `5 C
Optrim efficiency, 优切尾效率8 c, S: u! Q, V" r2 ~$ D
Order statistics, 顺序统计量
: b! Z* A. ?- t SOrdered categories, 有序分类8 X* X2 e, D+ d( E0 `7 j2 I
Ordinal logistic regression , 序数逻辑斯蒂回归) f. ]3 m1 w% J: y, ]: K
Ordinal variable, 有序变量
5 U, R% I- J7 M ROrthogonal basis, 正交基
# Y) C/ {% G" x1 {Orthogonal design, 正交试验设计: q+ r3 E( Y) ^+ ~) T2 S/ \$ |) q
Orthogonality conditions, 正交条件$ {3 @7 K! _# b# ?/ Q. \
ORTHOPLAN, 正交设计 5 z+ R B4 E4 J" f% }; {4 S
Outlier cutoffs, 离群值截断点3 Q9 ~, o7 c, e
Outliers, 极端值
7 T& W& n$ B! Z! XOVERALS , 多组变量的非线性正规相关
9 [6 s2 H9 \, w5 x* aOvershoot, 迭代过度
. I# j1 j( g" H' Q8 NPaired design, 配对设计
$ _$ k# _* C3 Z. n% mPaired sample, 配对样本
% B% ?1 j$ a y$ a; c {Pairwise slopes, 成对斜率
! S" r7 K6 Y* x2 L" ^0 y" N" JParabola, 抛物线/ _. K$ r. |+ }1 R" F1 [
Parallel tests, 平行试验' K3 K! p. J0 H$ k. a9 u& U6 |
Parameter, 参数, X; K% d: p; x+ x. f9 O1 M% _
Parametric statistics, 参数统计
7 v5 K/ H( V8 l1 Q: M$ C: O6 FParametric test, 参数检验
1 ?$ T2 ^3 u- b2 ~Partial correlation, 偏相关, ^: }0 g8 X, P0 O4 w8 L
Partial regression, 偏回归) g$ O8 u: T$ C; S7 Q- L2 ^
Partial sorting, 偏排序3 b E7 k8 Z# s& l
Partials residuals, 偏残差5 @2 _- y$ J% P- N! z1 i
Pattern, 模式: B1 I9 q% y/ Q! u! J3 u! N1 Y7 J
Pearson curves, 皮尔逊曲线+ p4 D' c/ o% s& W- H' R
Peeling, 退层
# {5 u1 T9 a" u9 h" Q, @Percent bar graph, 百分条形图' l5 a% f& x/ e- A
Percentage, 百分比
' c* w, s5 j; N+ K# jPercentile, 百分位数6 z1 I( \1 } ]3 V) n2 |
Percentile curves, 百分位曲线2 z' ^+ \) r; B; s
Periodicity, 周期性/ H' H2 M; J) N% k I* G+ t, Y" f% E
Permutation, 排列
3 [& L t8 ^, ~' K dP-estimator, P估计量
2 l. H2 n# i/ Q6 y: VPie graph, 饼图
4 n9 b2 O. H3 h+ R( BPitman estimator, 皮特曼估计量/ [0 X9 J/ M1 L
Pivot, 枢轴量3 u! m* b! z# q( [& b
Planar, 平坦
4 ?2 `9 K$ K/ `Planar assumption, 平面的假设# D3 h' I W% {
PLANCARDS, 生成试验的计划卡. P) g2 u+ F% Q& U$ p( y+ k; ]
Point estimation, 点估计
: ~9 H/ _1 ?2 ?Poisson distribution, 泊松分布
/ |) |( `" S2 Q4 aPolishing, 平滑6 G7 H7 P9 O+ P# @& ?% N F
Polled standard deviation, 合并标准差" u2 c, c. X' }8 e- B
Polled variance, 合并方差
2 M7 p! l( B2 V3 b2 O& {9 nPolygon, 多边图6 f% y1 w9 ?! x& j- A
Polynomial, 多项式
: _" R" @) _8 c8 F' H, }2 sPolynomial curve, 多项式曲线6 n# ~) B9 j k9 P; ?0 z$ r
Population, 总体
' B4 j N* n$ ?# ?. p: |/ jPopulation attributable risk, 人群归因危险度
a, J( x: z! _& V( N8 P" g' wPositive correlation, 正相关
0 g0 P5 R! _1 w3 oPositively skewed, 正偏9 A; R/ y; Z a1 [0 x5 m1 |' ^
Posterior distribution, 后验分布$ e0 ~2 _7 J# V1 G
Power of a test, 检验效能
, H9 O: R4 u' jPrecision, 精密度! @/ H- W: u) S& c
Predicted value, 预测值3 E$ Y- m1 f0 |2 R; C$ t+ `( S, \
Preliminary analysis, 预备性分析* n8 i) i" N! B" p8 {
Principal component analysis, 主成分分析
- x' Y. @) g" e) t6 z9 @Prior distribution, 先验分布
) d5 D' K( T& e- Y! \, m# IPrior probability, 先验概率0 r! V4 { U k+ w
Probabilistic model, 概率模型: C3 m' m& D& w, a4 d
probability, 概率
^% U2 w8 h3 ~& B+ S' }Probability density, 概率密度
# u' p' k: m' ?6 t6 MProduct moment, 乘积矩/协方差6 ? a1 J# g! h
Profile trace, 截面迹图3 j. `( d! a3 f- r
Proportion, 比/构成比, h$ k; |2 }/ K+ ^9 \
Proportion allocation in stratified random sampling, 按比例分层随机抽样
. n7 l' P4 b+ b5 g; ?8 t: H* gProportionate, 成比例7 X2 l8 h) f$ F7 ?
Proportionate sub-class numbers, 成比例次级组含量! H2 l; Y/ R& j0 w2 N: j
Prospective study, 前瞻性调查
3 P+ t |+ X8 n! lProximities, 亲近性 6 n/ y% B) G+ j6 [+ j& B i- w# W
Pseudo F test, 近似F检验9 W$ Q3 T s! v" n5 X4 @
Pseudo model, 近似模型% f$ ~$ I* x3 Z, t; \
Pseudosigma, 伪标准差
f% y: s ?$ k6 J& ePurposive sampling, 有目的抽样4 V6 }+ }4 U/ [) U$ x
QR decomposition, QR分解
8 z0 j/ Y; d* J$ y6 e9 jQuadratic approximation, 二次近似
. ]) T) i* [5 b! a/ EQualitative classification, 属性分类
4 L/ u K5 _! A+ c6 QQualitative method, 定性方法/ q2 P' L6 }( ^
Quantile-quantile plot, 分位数-分位数图/Q-Q图6 [, j1 P8 Y! W/ r. M' q
Quantitative analysis, 定量分析" \1 G) H' F. r2 @3 g$ W$ w8 m
Quartile, 四分位数3 c& `6 w) {* F- E* D6 ]$ c
Quick Cluster, 快速聚类3 ?/ O4 |8 a& G4 \1 G. F, P
Radix sort, 基数排序
4 d0 A. X8 H7 s0 o0 O+ C \0 f2 Y7 KRandom allocation, 随机化分组
w$ K% {$ k1 X- U. o& Y5 {# JRandom blocks design, 随机区组设计
3 \! d V0 l0 T7 K% B; V7 t/ s& RRandom event, 随机事件! V3 x( p1 ^) d% G- p( h
Randomization, 随机化& l7 S4 J9 S# R( Q9 X
Range, 极差/全距
; Q. \" h. I& m$ J TRank correlation, 等级相关
+ R5 w, b( u! G5 S, c3 L- `Rank sum test, 秩和检验
: t; L* g. ^4 z7 kRank test, 秩检验
4 U6 z5 l- _7 l% R1 G, X5 P: YRanked data, 等级资料7 e% ^ C4 w9 M1 b2 d: T
Rate, 比率
' z: ^5 g6 t5 d* X. s |Ratio, 比例
# y, e1 l# u ]% NRaw data, 原始资料
/ M. X3 T' k1 n0 ^% I5 ERaw residual, 原始残差
5 A4 P: V/ e* V+ ^6 qRayleigh's test, 雷氏检验( g) H# h# @1 l+ l# M8 N
Rayleigh's Z, 雷氏Z值
7 P' }) n, S' s" n: C2 [Reciprocal, 倒数1 i# G) w# P0 E n. A4 c
Reciprocal transformation, 倒数变换" i) }0 r. }, m$ E: X+ z
Recording, 记录
c3 a: x6 i9 k! jRedescending estimators, 回降估计量. X6 [( ^+ q- m
Reducing dimensions, 降维) B. c8 ?% ?, ]' E5 p6 j& `( Y
Re-expression, 重新表达# }: ^6 T" p$ S* [( L+ z
Reference set, 标准组2 T! u; Z" l, T) s9 \
Region of acceptance, 接受域
* m' V- v+ s! j3 L5 i/ RRegression coefficient, 回归系数
9 r: K- j* g* LRegression sum of square, 回归平方和* f9 b5 P! e' Z0 x0 E: n
Rejection point, 拒绝点5 J) S3 X/ U2 W
Relative dispersion, 相对离散度6 a3 G, x& V: M' ^# Z: o' |5 r4 B
Relative number, 相对数7 a. d' ], [9 Q, \5 p
Reliability, 可靠性
# K( _ }5 _( z# t0 _+ d/ AReparametrization, 重新设置参数5 K. }- u- g) k* O P6 C
Replication, 重复
' c( v9 w' ?# u" ?+ n- l$ mReport Summaries, 报告摘要 o! j8 j! ~7 v6 \
Residual sum of square, 剩余平方和
' ?" n( E' K& T K9 A8 aResistance, 耐抗性 d- w9 @3 r& e. W7 j. K. [
Resistant line, 耐抗线. M4 O) W e4 G! y3 K2 n( H
Resistant technique, 耐抗技术
' ?* Z7 i& j4 ~R-estimator of location, 位置R估计量6 a" A' F+ C. y9 f) v1 o0 g& O3 o
R-estimator of scale, 尺度R估计量
5 Z6 H# b& I9 TRetrospective study, 回顾性调查
/ c, h7 g9 z. g/ N$ y% CRidge trace, 岭迹6 r/ d! p0 F, }! t1 }# s" u
Ridit analysis, Ridit分析
1 h4 E" j1 K; [" e1 V! H4 ARotation, 旋转: g' g4 |. x* B* N9 R
Rounding, 舍入
" ?& |' n; U2 S- mRow, 行! q8 o% ?& D6 c) p
Row effects, 行效应$ B$ T4 ]6 a, ? x; B$ O2 D$ h2 t0 {
Row factor, 行因素: Q: U, l5 p/ b+ H, ?2 P
RXC table, RXC表
! s' t+ E, u+ }' v fSample, 样本
% Q( q6 b: u8 p4 |8 D' d6 d# ~Sample regression coefficient, 样本回归系数
; I: o$ ]# R2 f2 E) E: Y" OSample size, 样本量) S8 {; a. i' f- s3 V
Sample standard deviation, 样本标准差" o9 l" q2 H& Y
Sampling error, 抽样误差! y9 P* {7 W5 ]' N+ Z7 \
SAS(Statistical analysis system ), SAS统计软件包
4 g& w( M0 p8 P0 r7 @Scale, 尺度/量表) f+ r2 x; {' _* E8 Q
Scatter diagram, 散点图% b" V, ~' z4 U, W4 L; }
Schematic plot, 示意图/简图: @2 b* q. i: |) K
Score test, 计分检验! O( Z9 c# k! e3 S1 R) Q
Screening, 筛检8 S6 H- Y- ~$ H& k9 c4 A2 F
SEASON, 季节分析
: K. ?: n* U9 y, e6 qSecond derivative, 二阶导数
) H0 e5 k- E3 ^Second principal component, 第二主成分
# }7 V1 \# l* @: h" F( a+ BSEM (Structural equation modeling), 结构化方程模型 % g, o7 z6 i8 R$ }
Semi-logarithmic graph, 半对数图
* m* ] n+ T0 `Semi-logarithmic paper, 半对数格纸% T. Y; ?$ Y u( S
Sensitivity curve, 敏感度曲线
6 r+ z w% r2 |: p# ]: mSequential analysis, 贯序分析. O% ]# h5 B8 y& ~
Sequential data set, 顺序数据集
& A [ `0 L+ t& ?+ U9 cSequential design, 贯序设计: Q2 ^% c9 \9 u% v1 a% \
Sequential method, 贯序法
, e, f9 [2 T2 Y* {( R- ISequential test, 贯序检验法
3 n, G4 [! q% ^( ]4 m5 G* YSerial tests, 系列试验+ j7 @2 _4 K6 t; T2 \6 k u: [
Short-cut method, 简捷法
' p, c8 ]$ Q: B5 C: fSigmoid curve, S形曲线
- U3 Q4 h* }7 r' E+ e3 dSign function, 正负号函数
# T6 o, u4 c2 H) B' C% d- HSign test, 符号检验
' g: R6 q- p* nSigned rank, 符号秩
+ \5 L4 c6 s* C# fSignificance test, 显著性检验
! m- i0 @+ E, x: lSignificant figure, 有效数字
* z% |! u7 q* J, \! D; _4 f" nSimple cluster sampling, 简单整群抽样7 T5 ~5 F9 o! f- ~
Simple correlation, 简单相关
! g: t+ N2 l- x' `7 ~6 p+ iSimple random sampling, 简单随机抽样3 ? c- e6 ^$ b2 ~
Simple regression, 简单回归
9 x4 ^$ A2 P& ^7 u2 @simple table, 简单表( e6 W# L* w7 T. J8 ^4 Y* w
Sine estimator, 正弦估计量
4 }; A$ d* r5 {Single-valued estimate, 单值估计
( I7 O* u* z* [) H4 Y+ H8 lSingular matrix, 奇异矩阵4 n' t+ E+ J' ?" E- [1 p; T' W5 r& Q& ^
Skewed distribution, 偏斜分布# q9 X/ o% Y/ I$ H& e3 h
Skewness, 偏度+ z5 C+ g- D( z' U/ P
Slash distribution, 斜线分布
. D7 i5 ?; y7 S( {' a' e% n) CSlope, 斜率- s5 |0 h. b; f% K, d( x/ v
Smirnov test, 斯米尔诺夫检验
& o" R, G; I- c$ B* L) _( i2 [8 ^8 u- KSource of variation, 变异来源
# B" x0 U" T& ]1 W- b9 i4 {* VSpearman rank correlation, 斯皮尔曼等级相关+ Y! O# ^, ?( {( U8 e
Specific factor, 特殊因子
- T" F( U1 L4 \# N+ ~* H* E0 U2 {) V% ^Specific factor variance, 特殊因子方差, Q. ~: I, t9 N
Spectra , 频谱1 ~) z. Q* E- ?5 ^& I
Spherical distribution, 球型正态分布* A" w) o$ N1 v
Spread, 展布
) p- r9 k3 ]% L5 Z: ~0 \/ j7 F: SSPSS(Statistical package for the social science), SPSS统计软件包 ~# |( q7 ?$ x: b4 B$ E
Spurious correlation, 假性相关
3 @2 J4 A! ?$ _: HSquare root transformation, 平方根变换
) `+ F$ B3 r& @6 x8 @% T6 nStabilizing variance, 稳定方差
/ w& u' h5 A1 i( \& [Standard deviation, 标准差
) f7 f) Z6 `9 q) k$ g! T) f6 uStandard error, 标准误
; X4 j4 T; N3 RStandard error of difference, 差别的标准误
8 o2 U% ~! A# @: }Standard error of estimate, 标准估计误差7 n7 D0 r' }9 C) M
Standard error of rate, 率的标准误
$ U* a! a! R( F7 |! ?6 y K- lStandard normal distribution, 标准正态分布$ H) [: D: i6 J( E
Standardization, 标准化& ^% R4 `; }. l, C( J
Starting value, 起始值- E8 j% [" ~; |- P
Statistic, 统计量$ M& A# J- X0 ?1 U( W4 p3 O. K4 g, Q% m
Statistical control, 统计控制8 e9 q. B. q1 o/ J+ e
Statistical graph, 统计图! p# `. g- C7 X b0 z7 ? b/ @7 ?5 b, r
Statistical inference, 统计推断 }4 ~4 q8 V0 u4 O/ u: d4 o
Statistical table, 统计表
# u" l n1 n& W! [5 kSteepest descent, 最速下降法
/ O7 r6 |) j$ X5 M/ }0 _4 o/ H$ AStem and leaf display, 茎叶图
3 W; t+ ~% o: q; `' m: p( JStep factor, 步长因子7 G; E& ]/ O6 m5 k* R
Stepwise regression, 逐步回归
4 v) w4 ~ f8 s$ {! RStorage, 存8 o% n. Z( \7 j9 K2 B: L# v
Strata, 层（复数）
( f- a! U2 R& F/ b: |Stratified sampling, 分层抽样
9 E% e R v& ]6 n: k3 C/ _' cStratified sampling, 分层抽样
) G! S) k$ M' O# M NStrength, 强度
7 h2 `$ N/ U# Y5 e0 PStringency, 严密性6 G: Z+ v- A! U0 X
Structural relationship, 结构关系
+ u% J2 }4 E! P8 WStudentized residual, 学生化残差/t化残差; x6 p- t6 k4 M4 r8 N
Sub-class numbers, 次级组含量
$ P* J% \4 j/ M" uSubdividing, 分割
' h' u4 ^3 z! B1 N m; N# [9 v5 ^. _( lSufficient statistic, 充分统计量9 W$ C* c1 b2 ]+ f
Sum of products, 积和- }0 T4 c. ]6 Y, \' m- g+ O' u
Sum of squares, 离差平方和
- Z& b0 G: T" G/ N7 E5 oSum of squares about regression, 回归平方和: _0 m6 C5 F, X" W4 @: Q; h, s
Sum of squares between groups, 组间平方和
$ H, r8 E: g0 NSum of squares of partial regression, 偏回归平方和" v" B$ s K6 Y; F
Sure event, 必然事件6 I+ h* g2 O) S& J: q! N) {
Survey, 调查
2 w3 h+ j/ f' `" DSurvival, 生存分析
8 A ?& V) j- o% U6 x6 G5 hSurvival rate, 生存率! g% p% U: @. A
Suspended root gram, 悬吊根图
/ X( ?$ l( ?% o2 F1 r+ CSymmetry, 对称
/ S* s* G, x H n8 @' P* W' O: BSystematic error, 系统误差5 y: n# `+ u( p' z* K4 Z
Systematic sampling, 系统抽样4 W2 ?/ a1 ^/ Y$ d7 [( C6 n. q9 t7 f
Tags, 标签
6 b- E- v2 ?7 A6 [4 J5 `Tail area, 尾部面积# E# f1 Z8 I) p2 K' r& X2 _1 }, v; L
Tail length, 尾长# C* L/ q' M- Y1 a5 R+ g
Tail weight, 尾重
\, v- [* A4 c1 ?- jTangent line, 切线7 M! a1 H1 E- _/ T
Target distribution, 目标分布
! q0 G8 D s! ~ JTaylor series, 泰勒级数
4 \7 a: A9 m/ Q& N1 ^Tendency of dispersion, 离散趋势
+ N( Q% c9 O7 m9 W1 e5 t/ L& ^! aTesting of hypotheses, 假设检验- P# `0 y l a8 X. k# [
Theoretical frequency, 理论频数7 O. X: P5 u0 u- n/ E
Time series, 时间序列6 a0 J S4 d* E2 a% u7 p+ [- ]
Tolerance interval, 容忍区间: E! |9 T# T+ |+ z9 d
Tolerance lower limit, 容忍下限
0 w6 g! V4 v4 c/ B# zTolerance upper limit, 容忍上限
9 e+ T2 P' s: d' H9 U5 mTorsion, 扰率
6 |% u' x( F2 S# g7 A4 N5 vTotal sum of square, 总平方和
) T a4 d- |; h6 w4 eTotal variation, 总变异
4 u9 Y- h! R* cTransformation, 转换
5 k$ u4 K/ A3 v4 p e1 }- F2 C$ qTreatment, 处理 c8 ~) ^/ _ u- H0 A/ V5 b. ~
Trend, 趋势( U! s6 E4 _: F: Z
Trend of percentage, 百分比趋势3 x: L: v: f0 b1 l
Trial, 试验( s8 _# Z% J k. K# O' a
Trial and error method, 试错法
: |7 @8 V3 l. c* b7 gTuning constant, 细调常数( d- d% [4 B$ P4 l
Two sided test, 双向检验
# \5 u# W6 o' Z2 BTwo-stage least squares, 二阶最小平方
' A* Z% r8 j& F! g; T1 _4 d! tTwo-stage sampling, 二阶段抽样& S2 z& A& a3 e% H" q
Two-tailed test, 双侧检验
7 F E* ?+ p0 W0 k) G- m$ L- k; kTwo-way analysis of variance, 双因素方差分析' M. a0 _6 k1 N5 O, a& A6 ?
Two-way table, 双向表
1 Z/ N9 n) [/ z O& IType I error, 一类错误/α错误
: s6 J" I* s; p- OType II error, 二类错误/β错误; d& O+ A! ?& p7 B6 i& s7 {6 S
UMVU, 方差一致最小无偏估计简称& B1 B3 B* M$ w
Unbiased estimate, 无偏估计3 b! b+ J# y! [: s5 z8 B( \
Unconstrained nonlinear regression , 无约束非线性回归 T& k6 K! x, J5 [
Unequal subclass number, 不等次级组含量
- G, n/ }2 ~% y: H/ B+ k. mUngrouped data, 不分组资料
# _; @; k5 Z! _' |5 ZUniform coordinate, 均匀坐标
6 |. x3 l& n- [" r! L+ jUniform distribution, 均匀分布
3 A0 a8 I1 a) R( R$ C; a8 qUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
- t" h; K: C. rUnit, 单元
$ Y* o) I% S, ]& O3 Z) e# HUnordered categories, 无序分类, g' B, Z9 M, \- j
Upper limit, 上限 H0 \! Y4 n8 L1 p% R, m3 X0 Z
Upward rank, 升秩
+ b1 ]6 ~% R. M7 c' c/ d6 mVague concept, 模糊概念1 A1 ], @( Z; N/ w) c
Validity, 有效性 M. |( Q) J) N- m7 O( a% [
VARCOMP (Variance component estimation), 方差元素估计
3 j A3 s; c' A; |Variability, 变异性+ p( Q1 G# p+ w. e# [$ R
Variable, 变量/ k$ j# F1 ^3 v+ z
Variance, 方差: A8 B. O( S3 h' I B
Variation, 变异
7 y% @, p1 |* CVarimax orthogonal rotation, 方差最大正交旋转/ V- J G( Z+ Z! N5 K/ w
Volume of distribution, 容积
2 E ?7 c8 L& t1 Z- f7 jW test, W检验' j) ?- X- r& t) Q T0 [
Weibull distribution, 威布尔分布: g- y ], m6 n' p+ K
Weight, 权数0 A! ^' V1 E. C7 M& ~ |
Weighted Chi-square test, 加权卡方检验/Cochran检验- Z7 {& I7 D/ a$ b; H0 F
Weighted linear regression method, 加权直线回归
' ^5 x4 o6 J; P% W7 VWeighted mean, 加权平均数
& I: F: E5 j1 Z0 NWeighted mean square, 加权平均方差2 _7 o4 i) T% E$ b( M4 B! Q
Weighted sum of square, 加权平方和' J# [, t; v2 {. f p- o2 a
Weighting coefficient, 权重系数
/ Z4 B- d% g6 d$ q2 oWeighting method, 加权法
8 ]' N/ g6 ]/ c0 i% t# AW-estimation, W估计量' N! h$ V" d Q+ L! I5 t
W-estimation of location, 位置W估计量# A7 k, o U D5 g) j3 B
Width, 宽度7 r; v! d& B- v+ \" [# p
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
* I4 W/ Q# A9 ~) SWild point, 野点/狂点8 e9 K e* {* h0 E% z, U
Wild value, 野值/狂值
7 ]& U4 y( W0 ]- W, qWinsorized mean, 缩尾均值* _$ {7 X8 X+ R) s
Withdraw, 失访
! a$ H6 N, g& e5 J* C, B, QYouden's index, 尤登指数' @) @; u9 V6 C# I# y2 {1 a7 ~
Z test, Z检验
6 L* k; p$ P) Z* n: e( NZero correlation, 零相关- F6 q9 _* ?" F; O. H' m5 @
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
