|
|
Absolute deviation, 绝对离差
# P9 h( A! [; ~9 n, Y VAbsolute number, 绝对数
- Y' C9 ?# e; f# |+ i2 ]& X% aAbsolute residuals, 绝对残差* o$ {+ ]; C: h) C3 O9 k6 m Y( l
Acceleration array, 加速度立体阵
% Q8 [' i! J8 LAcceleration in an arbitrary direction, 任意方向上的加速度: U1 q! m6 A- s7 ?, T
Acceleration normal, 法向加速度
. i6 g+ s8 F& Y6 h/ ]$ aAcceleration space dimension, 加速度空间的维数+ A0 T, ?# l" ?$ Q6 F
Acceleration tangential, 切向加速度 V& Y, j# R$ |4 u& z1 ~2 @
Acceleration vector, 加速度向量
6 X6 i6 E9 u% _" x ?: gAcceptable hypothesis, 可接受假设) \8 w t$ `# [ J
Accumulation, 累积. s' Y, n( V4 S1 V
Accuracy, 准确度3 W. @. u* @' G. L( w
Actual frequency, 实际频数
# Q+ u0 [. D& V& Z4 Z4 w1 QAdaptive estimator, 自适应估计量( A9 v: ] S( R9 v) X: j9 q
Addition, 相加
6 F$ c# I$ M6 l3 i; r7 ZAddition theorem, 加法定理
+ G1 t, i6 j" R/ [Additivity, 可加性
3 P3 u+ v/ M. uAdjusted rate, 调整率
' r, o2 z& ~; E9 C3 r7 oAdjusted value, 校正值
b( H" O% c: ~; t1 |. y0 I' kAdmissible error, 容许误差/ N1 g+ u: F: @# i' E" F( m
Aggregation, 聚集性
1 Y7 A! d! A9 T5 n/ JAlternative hypothesis, 备择假设
1 j! A. p# }' t. O K% R% IAmong groups, 组间8 d0 Q# W) O1 q- Z
Amounts, 总量$ k( ~; A7 x$ p. ^
Analysis of correlation, 相关分析
+ v5 V% G; o% `4 C# j/ l5 gAnalysis of covariance, 协方差分析
' n2 ^" o/ x+ t. a, d4 V8 SAnalysis of regression, 回归分析( Q; h6 w. g0 `6 U. n1 E
Analysis of time series, 时间序列分析
' g/ c0 n6 n0 m/ w7 uAnalysis of variance, 方差分析% v# D) W; b: l/ i# J
Angular transformation, 角转换- r% t5 S7 L; ~2 v
ANOVA （analysis of variance）, 方差分析8 ? w* t: u5 H" R' V u- V
ANOVA Models, 方差分析模型6 Y! O9 ]( v7 a. h3 L
Arcing, 弧/弧旋1 ~0 D$ g4 ]. n0 ]4 Z& @9 v# U" M5 T
Arcsine transformation, 反正弦变换. T7 a0 E2 @0 X, O1 [& g3 z+ [
Area under the curve, 曲线面积
a5 G9 z# _+ hAREG , 评估从一个时间点到下一个时间点回归相关时的误差 : ?5 A, I: l+ m/ F+ X3 P+ M1 r
ARIMA, 季节和非季节性单变量模型的极大似然估计
" O& t4 P( J: m- [. uArithmetic grid paper, 算术格纸
A4 u" {, o+ U7 [: q7 H7 ^9 iArithmetic mean, 算术平均数
; x# I6 t3 \# g6 JArrhenius relation, 艾恩尼斯关系
& w% e9 k* Y- F8 _) P, UAssessing fit, 拟合的评估" ~+ V7 U3 |. W6 P0 e# n. D
Associative laws, 结合律/ J4 n5 L9 z2 V
Asymmetric distribution, 非对称分布
0 e& H+ r& {- ` |# M" ]: hAsymptotic bias, 渐近偏倚# E, A6 w P, \1 _# {# n0 Q
Asymptotic efficiency, 渐近效率" H( D; Z5 c8 g u3 F6 r- w3 L
Asymptotic variance, 渐近方差
: U% Z I1 q% P' |& vAttributable risk, 归因危险度
. U V) _$ G5 k; p+ [, m1 o; GAttribute data, 属性资料
+ y, B3 w3 }/ D3 Z/ |$ tAttribution, 属性( e, @. y0 R! k9 L! f" c5 E
Autocorrelation, 自相关
- Z* o# p2 X" O6 Q- q+ N/ D/ cAutocorrelation of residuals, 残差的自相关" K' q9 e! L3 R0 u) P5 y8 U9 J k
Average, 平均数
6 k! v4 u9 h3 bAverage confidence interval length, 平均置信区间长度
1 p8 D6 q% z8 Z# }Average growth rate, 平均增长率
. W) [. o9 l z7 O9 d; h: OBar chart, 条形图. {* f9 i; i. s: n# ?
Bar graph, 条形图
# u" B+ M& Q ^2 W! e) _$ h" } nBase period, 基期
$ {. f+ m, B; b2 L7 rBayes' theorem , Bayes定理
- g' r' M. I* `7 L8 l- VBell-shaped curve, 钟形曲线) h" k Z; w/ ~
Bernoulli distribution, 伯努力分布' w0 W* Z. C" `/ [) r* P
Best-trim estimator, 最好切尾估计量) p( R! c6 ~5 b1 n; o8 P
Bias, 偏性4 j$ y6 ?; {# P
Binary logistic regression, 二元逻辑斯蒂回归
. r! A9 U4 m9 V, m/ Y, {) PBinomial distribution, 二项分布
. C4 {9 C& C0 iBisquare, 双平方
+ w" a8 c1 J- Q' jBivariate Correlate, 二变量相关! H1 J; Y7 w( \( J5 ^
Bivariate normal distribution, 双变量正态分布
. _; l2 u9 j/ [6 W8 KBivariate normal population, 双变量正态总体; ]* K0 j+ S' h$ q; ] W. L
Biweight interval, 双权区间
' j+ C# q7 D1 _0 v9 k* B9 ZBiweight M-estimator, 双权M估计量, W; r# t. I: d1 E! \. i
Block, 区组/配伍组
O+ o9 j9 N9 [. r5 _/ v: RBMDP(Biomedical computer programs), BMDP统计软件包- y2 m }# p1 K, _% u- N- }
Boxplots, 箱线图/箱尾图/ l9 [5 R( P5 U% `/ J
Breakdown bound, 崩溃界/崩溃点
0 E3 p! Q3 m, Z8 ?+ ]) sCanonical correlation, 典型相关) i0 C$ w# {1 [2 f- E- i
Caption, 纵标目
( u" W7 Z1 R+ C6 e% m2 c# z; oCase-control study, 病例对照研究: D. o Z: N& R* H2 @& O. ~
Categorical variable, 分类变量
& \8 X+ |* X) X2 {5 b8 ?Catenary, 悬链线- Y* a& @+ ]) v
Cauchy distribution, 柯西分布" M; |2 T# `+ G
Cause-and-effect relationship, 因果关系# W/ n; P8 M' L7 d: g! E0 R
Cell, 单元5 v+ w {& a; f; H
Censoring, 终检
+ r- M2 j, O6 l+ CCenter of symmetry, 对称中心- H, _7 F J- p; H" T# a3 S
Centering and scaling, 中心化和定标# @3 N' f( B8 D9 B" r, S
Central tendency, 集中趋势
2 c2 h9 E+ x& N- E5 QCentral value, 中心值
" I8 \& o& j5 P# oCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
9 u" Q0 Z9 p: m( n1 BChance, 机遇8 v: }' q5 \' Z/ X% ?+ t( H7 B
Chance error, 随机误差0 z' H) t! {9 @6 R0 j q% _) Y
Chance variable, 随机变量
- ^& T- t5 k; V! m/ eCharacteristic equation, 特征方程
( N% ~3 |1 ]4 E/ l$ [& RCharacteristic root, 特征根
8 p3 w9 |; I! z- nCharacteristic vector, 特征向量( C+ x& k, {2 b9 _" x
Chebshev criterion of fit, 拟合的切比雪夫准则& f* ^5 \- E7 u% X' D4 q6 V
Chernoff faces, 切尔诺夫脸谱图( o! h, u" @ v$ I; T& B
Chi-square test, 卡方检验/χ2检验
5 |; U, A! F) D# S- d- gCholeskey decomposition, 乔洛斯基分解
- `& D7 F3 p! q2 C7 E* [& _& Y" n, l& JCircle chart, 圆图 0 X$ H8 f% V8 n/ h0 k( ?
Class interval, 组距
. ^" \# T! h; q" R3 kClass mid-value, 组中值. {: A# P7 x& }! j9 T8 q
Class upper limit, 组上限5 l2 I5 r. b& ^
Classified variable, 分类变量
) G6 C; W/ Q" G* |1 ]$ p* kCluster analysis, 聚类分析6 v% q! F& H- |+ K/ D e
Cluster sampling, 整群抽样6 X4 s1 _9 `' a8 G- {* h6 m2 f+ M
Code, 代码
7 m( o* B e: t4 o# _1 YCoded data, 编码数据
$ v% V+ _* v2 p, a9 ?4 s# gCoding, 编码
3 D' R, r# s6 w# G9 j. CCoefficient of contingency, 列联系数
8 }0 l) R4 y( E( N4 N5 {Coefficient of determination, 决定系数
/ w0 B2 Z( ^. F# |Coefficient of multiple correlation, 多重相关系数
. j7 ~( A3 C& l$ ~ {3 k- [( ?Coefficient of partial correlation, 偏相关系数# T+ P3 C; f& U
Coefficient of production-moment correlation, 积差相关系数
. w9 e6 o" d% F9 W! J) iCoefficient of rank correlation, 等级相关系数4 \! \8 Z+ f# ? @" a
Coefficient of regression, 回归系数9 V/ g( a ]5 h0 h* i8 ]8 G, t
Coefficient of skewness, 偏度系数
/ i! \* \. J1 ?. y. _" VCoefficient of variation, 变异系数
0 f* Z4 a" {% K) \! Z \5 vCohort study, 队列研究( F4 C& g j9 ^' F8 A
Column, 列
8 L' Z8 C( _/ r$ d" `8 b( ^, BColumn effect, 列效应# x! J; H4 A$ L8 t
Column factor, 列因素' l! @. o7 r& n: f
Combination pool, 合并
* e; {) T9 P2 ]# b, k/ @Combinative table, 组合表
7 C6 i9 B6 f) A: |; n* {- B8 l' QCommon factor, 共性因子8 v/ H$ P; U3 h H& N
Common regression coefficient, 公共回归系数0 ~ t& h$ g; h+ ?3 l& q
Common value, 共同值
0 w* X5 q4 Q, p5 z1 Q6 \Common variance, 公共方差
; T) h( ?3 Y8 D6 Z1 s# `Common variation, 公共变异
5 @! L$ d, Q: J7 lCommunality variance, 共性方差" [/ ]8 g/ A. ~, U, v7 h
Comparability, 可比性
2 G; `/ N6 B; `, h9 |. RComparison of bathes, 批比较7 _7 y8 K! T- y- t
Comparison value, 比较值
5 ]# p3 @. f9 L5 l* u/ gCompartment model, 分部模型
- x9 ]1 T/ e6 N9 ]! C( O* }1 VCompassion, 伸缩: y& ^$ o: ^5 Z, P: H: P1 H
Complement of an event, 补事件
6 Y- b* w! s7 _ V, V' E/ `1 H5 }9 j) oComplete association, 完全正相关
9 C( n6 K) w y! V9 q' S8 `2 zComplete dissociation, 完全不相关
) b% {& }! p* c" b' l0 ~# {7 P, k9 cComplete statistics, 完备统计量
. ~" }- ?# t; f5 T+ l/ ^& z5 S0 R2 KCompletely randomized design, 完全随机化设计( D* Q( @$ `( f7 @. v) X
Composite event, 联合事件
, ^; O3 w# y; R/ f* {Composite events, 复合事件
6 V. B0 \. S" P. B+ a. QConcavity, 凹性
$ b$ B/ n5 D9 h" [+ X5 DConditional expectation, 条件期望8 S5 r1 P3 N' D, D! e
Conditional likelihood, 条件似然- t8 s/ q g; @
Conditional probability, 条件概率, j% `$ o' a# e/ ^* P0 F! x) A/ m. D4 A
Conditionally linear, 依条件线性
2 F9 k& A3 h, E TConfidence interval, 置信区间. Q2 H+ n7 h d. R2 v: I7 U7 b
Confidence limit, 置信限
% \9 u0 |4 F NConfidence lower limit, 置信下限/ z1 p4 L+ [+ \+ |8 J
Confidence upper limit, 置信上限: b) b0 c4 W& U/ C5 Z0 V; B
Confirmatory Factor Analysis , 验证性因子分析" u6 H& S+ j3 W
Confirmatory research, 证实性实验研究
/ _- J) K, F) y/ J( u4 sConfounding factor, 混杂因素
! {3 S% ^" {, {5 \" JConjoint, 联合分析
+ |; M' ]# V# u# QConsistency, 相合性
& S+ z, K/ r5 d8 w2 v, H* BConsistency check, 一致性检验
3 D# x0 k- N0 r4 ^Consistent asymptotically normal estimate, 相合渐近正态估计
0 h* s" [% s1 y7 \Consistent estimate, 相合估计( Z X& a. ?+ [$ c8 i' P6 f
Constrained nonlinear regression, 受约束非线性回归- A2 b2 w0 u4 A. v
Constraint, 约束
; {3 a1 E2 X$ \: t9 |8 y5 ^: BContaminated distribution, 污染分布
% {4 |, x, r3 @Contaminated Gausssian, 污染高斯分布) v+ w; A7 H; o1 E: w
Contaminated normal distribution, 污染正态分布
1 _! _# s/ w8 ]8 }5 o; ^+ Y' P, I4 J$ A. zContamination, 污染0 F T* r* ?: ^# W$ Q
Contamination model, 污染模型
/ i0 s# S+ X X2 Y8 ^Contingency table, 列联表
' |; a$ D- f$ t' y% h# pContour, 边界线4 l& l, D; \: D. }. _4 n- ^: z8 E
Contribution rate, 贡献率
" X% s) T2 q1 N/ ]6 p- y: T. @Control, 对照" f! m! j3 A! Q6 M
Controlled experiments, 对照实验5 }- E n$ B* {9 ?& L
Conventional depth, 常规深度1 w: _' v+ l& A7 X9 Y) F
Convolution, 卷积" [4 F3 b1 _3 N
Corrected factor, 校正因子
" }* u2 Z; q. s5 D; Z3 fCorrected mean, 校正均值. O( _9 o3 s. B1 i1 \: h ]) H; Y
Correction coefficient, 校正系数
, @( G$ I& ^6 M- B; zCorrectness, 正确性
3 |8 ^4 ^& {1 L. I' x/ }: [Correlation coefficient, 相关系数1 P% E2 p8 ]& c5 I$ T$ K9 X
Correlation index, 相关指数* j2 B+ u5 S5 p* G/ l- t
Correspondence, 对应# n# n1 `9 j+ [) Y
Counting, 计数
$ I4 e5 O- U5 s# v( {Counts, 计数/频数1 D! S# O& r/ ]9 Z l. C
Covariance, 协方差+ C I* ~2 d5 [2 A d
Covariant, 共变
) Q) f; K) d$ G3 UCox Regression, Cox回归
+ b6 R* e' e$ OCriteria for fitting, 拟合准则
$ _! T4 D9 Q& P- {/ P1 ^3 OCriteria of least squares, 最小二乘准则
. I$ w6 [2 o! v+ H# d; ICritical ratio, 临界比
% `/ Y |( b# s% B. \3 |) p4 RCritical region, 拒绝域2 i/ t' f5 H2 M1 [: i2 v
Critical value, 临界值
4 ~+ q3 q; g# D! w, T; E$ TCross-over design, 交叉设计
, i2 |7 k, _0 ~. h! FCross-section analysis, 横断面分析* s0 i/ H8 F% ~' R: M. k. h
Cross-section survey, 横断面调查
6 {- g$ l$ I) O5 _/ _6 u1 _Crosstabs , 交叉表 & g" ?. E( c0 j+ ?5 {$ X2 f
Cross-tabulation table, 复合表- }+ m. {1 s0 b+ @# B6 B) J! ?
Cube root, 立方根
( F/ n+ O4 [8 rCumulative distribution function, 分布函数
E% ?0 t) I0 N/ _" t; [7 c0 Z; Y. x5 RCumulative probability, 累计概率0 K3 j$ j6 n! B! S/ \% b
Curvature, 曲率/弯曲
/ B( D6 M( d$ Z7 c) @' OCurvature, 曲率
4 A6 N8 D6 ~3 W6 k8 XCurve fit , 曲线拟和 5 a2 K3 G7 O% O0 v! z1 V
Curve fitting, 曲线拟合
' B9 M9 E9 j; k+ f% zCurvilinear regression, 曲线回归
4 b8 ^/ o# J# W- t" `Curvilinear relation, 曲线关系# G' @; W n* Y$ f. V
Cut-and-try method, 尝试法
( w4 u b- U% [7 K7 g6 l& XCycle, 周期
. \; S! F4 d! ?% J FCyclist, 周期性
/ a; e' v) X3 K) [/ WD test, D检验$ R- H {, U( T( z) ?0 g
Data acquisition, 资料收集
/ Y0 r" ]( {+ x3 s8 OData bank, 数据库
. X% F% F" d KData capacity, 数据容量
* P4 @! c9 g/ ^$ H$ F$ E; Y b) v+ R4 ]Data deficiencies, 数据缺乏) Q5 W: Z# F! U5 X+ R
Data handling, 数据处理
; X3 k5 ` j; F0 I y3 bData manipulation, 数据处理
a8 ]0 t9 t+ M* u. TData processing, 数据处理9 x* Q9 t, Y1 T& E7 k; n) k
Data reduction, 数据缩减0 O2 k9 b8 W! {8 P' E
Data set, 数据集
& s/ t j2 c( w7 c" ?# IData sources, 数据来源0 i3 g/ } {# C' q. a
Data transformation, 数据变换
+ g6 K% z( T) a- Y: X6 mData validity, 数据有效性4 ^& Q2 ]) w5 K. U
Data-in, 数据输入8 a9 ^. V( N' p2 p* j$ p5 g
Data-out, 数据输出
8 D# k. {: ~) y) O& uDead time, 停滞期* |+ l9 P' w5 t
Degree of freedom, 自由度
@' B/ e2 W. A+ G* L( HDegree of precision, 精密度6 K( k; Z* L! |+ }3 D) l% D
Degree of reliability, 可靠性程度
0 v8 @( h$ F) C8 N Q1 s0 L& `Degression, 递减& Z ?6 n, x3 b8 s% H2 l
Density function, 密度函数
' T6 Y! I# c8 eDensity of data points, 数据点的密度1 r/ U v" m; q0 Y% O
Dependent variable, 应变量/依变量/因变量% X3 d( [7 n8 v0 A& ]' R
Dependent variable, 因变量
7 s+ N4 @7 w3 t' _Depth, 深度
& w2 b% i, a J6 yDerivative matrix, 导数矩阵+ z% L" k* U! D) z- @5 p2 z
Derivative-free methods, 无导数方法) \/ W) I. }4 g# g( ?/ y
Design, 设计
# n; ]: a. u V' wDeterminacy, 确定性7 t: b3 D/ n/ l: Y, n( J8 M
Determinant, 行列式, y* n5 u/ E2 V5 l# ]- u$ L- C3 {
Determinant, 决定因素; b3 b3 A1 s1 B& L& ^4 w2 S
Deviation, 离差" L5 E! S; F1 j: ~
Deviation from average, 离均差
2 i" K- c) a, FDiagnostic plot, 诊断图1 C) X F7 v1 R5 q
Dichotomous variable, 二分变量% K% X0 p9 V1 k) \& e/ @2 ^
Differential equation, 微分方程9 d7 o" r3 n; E$ T- Q1 E& H3 s- r
Direct standardization, 直接标准化法
; R- j2 Y* X( u& c W0 DDiscrete variable, 离散型变量6 H$ H3 N. T1 y7 g/ E8 i
DISCRIMINANT, 判断 ) C! y" U5 X( @/ p" X! v
Discriminant analysis, 判别分析
& x. Q8 V9 A( l0 u2 |3 sDiscriminant coefficient, 判别系数" _5 s3 e, R1 j M# Z
Discriminant function, 判别值
1 T$ p, _$ e4 x" cDispersion, 散布/分散度
4 R+ R: w$ W3 ADisproportional, 不成比例的# ?: p6 B' U% ]6 m0 D
Disproportionate sub-class numbers, 不成比例次级组含量
" F+ w# J. {1 p/ o& mDistribution free, 分布无关性/免分布
& v! v0 S3 J. g e( ] T4 LDistribution shape, 分布形状/ q# E6 Y6 ~: `) _/ K
Distribution-free method, 任意分布法, M. f# ]3 w3 o/ J0 a$ S6 U2 |3 |
Distributive laws, 分配律/ Y2 j' B6 h2 i3 @
Disturbance, 随机扰动项
# x3 f# U* k5 @$ M$ R( @Dose response curve, 剂量反应曲线' U$ e' \8 n1 }8 T m8 `7 c
Double blind method, 双盲法
$ \ c8 n" N$ S+ A; ~Double blind trial, 双盲试验
( ~3 O' i: ^1 W5 G/ s: zDouble exponential distribution, 双指数分布. N1 l1 w/ A! E* c3 _9 _. d
Double logarithmic, 双对数
# q- s; |4 ]: B4 @% c# [* ZDownward rank, 降秩5 s% |$ w, _" P' h5 N
Dual-space plot, 对偶空间图6 i* G# i# C5 e% E7 A6 W
DUD, 无导数方法& V4 n' w$ W5 `* ]
Duncan's new multiple range method, 新复极差法/Duncan新法
4 r1 v3 o7 ?) r5 A3 z) G6 QEffect, 实验效应- @* J/ O# E6 D5 @% O% I9 E
Eigenvalue, 特征值. [5 B+ S/ R( }+ V1 p- ?; M
Eigenvector, 特征向量
4 b: }2 C! v3 F5 SEllipse, 椭圆0 O: j. `& F+ ?' E* ~9 _: z
Empirical distribution, 经验分布3 S" N4 O8 |6 D
Empirical probability, 经验概率单位
) L& a4 A+ _, B+ WEnumeration data, 计数资料
) @6 w! Y! ` ~Equal sun-class number, 相等次级组含量5 b6 R" `! r5 O
Equally likely, 等可能
7 k9 [" R/ x2 YEquivariance, 同变性
! K! I% q" G2 X3 P, i; rError, 误差/错误) B6 ]) G' {! A& f
Error of estimate, 估计误差- ^% q& c3 T6 K9 U: C
Error type I, 第一类错误
4 R5 i5 D( h% b# K/ A8 p' cError type II, 第二类错误. [( ^: F& [9 F: H0 }; L) k: t
Estimand, 被估量! s# k- u$ z- |+ l) q4 a+ q% Q
Estimated error mean squares, 估计误差均方
: ]5 Q, o! a' f& }: f5 ~+ WEstimated error sum of squares, 估计误差平方和
8 ` D7 r$ L1 T2 e7 R0 y( _- H0 E0 sEuclidean distance, 欧式距离
3 ]4 F2 ?% m3 I' q1 T# rEvent, 事件
# @: n9 ^; ~. G) jEvent, 事件
( Z% j4 k' S* }& k0 a# hExceptional data point, 异常数据点$ K) i* b$ u0 K D, c
Expectation plane, 期望平面
2 @# e* o! Y; V8 x6 X/ {Expectation surface, 期望曲面( z9 i% A0 u; s' g! v9 ?
Expected values, 期望值
3 J$ d$ P' Q2 _1 v! uExperiment, 实验
, {& d' {: S7 O$ M x/ `Experimental sampling, 试验抽样
, ? f6 H6 _. O8 a, v* B7 I8 _# O9 mExperimental unit, 试验单位
+ U$ N" g( }3 S/ n' d, _' U! rExplanatory variable, 说明变量
- ]/ V& N$ j; t! }7 A, KExploratory data analysis, 探索性数据分析
0 u: a' m- u* T* L, P6 h- @# xExplore Summarize, 探索-摘要" R& o# `& n" w6 ]" X
Exponential curve, 指数曲线1 t/ B9 Q/ r' w. U* s" x
Exponential growth, 指数式增长# @/ Q% }! [( D g2 V
EXSMOOTH, 指数平滑方法 u, f/ s$ f3 r. H' S" a( w6 i- ]
Extended fit, 扩充拟合& N$ g9 M( J& d' u+ ]$ ]+ u; q5 n; `- z! b
Extra parameter, 附加参数) t" N: g* j+ j/ s& w
Extrapolation, 外推法
- I4 e' _# {3 M. f' gExtreme observation, 末端观测值
9 w; U4 b3 I0 mExtremes, 极端值/极值, q. e! M1 A8 {5 r
F distribution, F分布
* `% I" |& B- E; q: M* MF test, F检验6 J, u4 I$ E! X& h% X
Factor, 因素/因子5 V$ |1 i; V: X
Factor analysis, 因子分析5 {7 D" `$ U& F) L8 K) {
Factor Analysis, 因子分析
8 W5 e% v; {# \; Z# t( }( {9 u! Y# OFactor score, 因子得分
5 N7 l( I9 [8 S, Q" v6 Y, VFactorial, 阶乘6 m2 @2 y4 O2 @6 l X
Factorial design, 析因试验设计3 G/ j, Z! ?# X0 j0 h$ b
False negative, 假阴性
. ], z# k' r! l! Q1 j8 qFalse negative error, 假阴性错误0 a& Y+ m) ]$ q6 t y
Family of distributions, 分布族! w! K5 H2 T, ~/ }, _: q
Family of estimators, 估计量族
/ q T1 D& o9 c) E9 F2 OFanning, 扇面: J9 Y' s5 ^# V
Fatality rate, 病死率/ p5 r. A4 d; S8 p
Field investigation, 现场调查 M; o: E: E. B1 I$ G/ k% l
Field survey, 现场调查
/ R: q) w4 t& G, z* Z5 n! dFinite population, 有限总体
7 h+ ^/ [# I+ D# yFinite-sample, 有限样本# T7 t: ~: _* y" o7 K7 j1 j4 o
First derivative, 一阶导数, @) _6 Q; u4 K1 P/ s. V
First principal component, 第一主成分6 r6 I m7 a# y0 C
First quartile, 第一四分位数- \ z$ w S8 Z* \: N
Fisher information, 费雪信息量# B8 r4 A2 K j- k+ U; g% V
Fitted value, 拟合值# r- a7 u% Y3 d" I& @% E+ u
Fitting a curve, 曲线拟合: ^' Q$ j- ~+ C7 D7 o
Fixed base, 定基; g W7 h) A) I( @* m
Fluctuation, 随机起伏" T8 ~4 ]9 a5 S
Forecast, 预测
4 {8 ?+ F; s7 R4 `0 h4 i$ sFour fold table, 四格表$ T; d# c8 Y+ g/ B j" Z" J
Fourth, 四分点$ ^) b% s1 P4 u" U* A S
Fraction blow, 左侧比率" D6 D( [! v! Q* b
Fractional error, 相对误差
4 k$ G/ z3 A" D2 x( Z' y: |Frequency, 频率
! _3 z- R* p, _Frequency polygon, 频数多边图
% I, \2 V: P$ ^/ j. |$ z! IFrontier point, 界限点
x: r* q0 B! E! R% _Function relationship, 泛函关系, {" J8 ~* Y- F4 e X! Z
Gamma distribution, 伽玛分布5 }1 S* ?1 G/ t6 ]
Gauss increment, 高斯增量4 F* g& G, T- I* c% K5 D7 j3 j
Gaussian distribution, 高斯分布/正态分布1 I4 d3 e+ E/ j: P$ D2 i
Gauss-Newton increment, 高斯-牛顿增量
/ p3 o, |, a( Y$ y7 G- j! L( OGeneral census, 全面普查
& P; C, R$ u7 G+ cGENLOG (Generalized liner models), 广义线性模型 $ r8 V; v( {' L$ K# ^8 _
Geometric mean, 几何平均数
: ?, @6 ?& Q% }* U7 M" w) ?Gini's mean difference, 基尼均差% o% w: R0 p1 |9 S* W' z: ^ c
GLM (General liner models), 一般线性模型
& s( Y7 b* E' ?; NGoodness of fit, 拟和优度/配合度
0 t' M4 c2 l% Y3 A! m5 j: RGradient of determinant, 行列式的梯度
, ~! i/ Y# v$ ]! j* C3 u, wGraeco-Latin square, 希腊拉丁方$ r$ \$ x+ }; F) U. K$ `
Grand mean, 总均值
0 r* n3 Y! }) _, j/ p- S) W5 E: LGross errors, 重大错误
8 [1 m- c; }3 y8 p( z. \Gross-error sensitivity, 大错敏感度
8 K+ I9 O9 J0 k9 _Group averages, 分组平均
% N S; i! f ]4 b9 x4 e+ G$ `% ZGrouped data, 分组资料5 y0 G6 q, M W2 R) |
Guessed mean, 假定平均数% d' i: r! U, ~: Q% i
Half-life, 半衰期. {/ B, g- M7 t4 L+ n8 h% G6 h
Hampel M-estimators, 汉佩尔M估计量! a b, k. j' n6 u. z' {- ^& `0 S
Happenstance, 偶然事件
1 M/ {# ]1 r9 t- k5 SHarmonic mean, 调和均数4 f; L$ Y; }6 o& v
Hazard function, 风险均数' K2 x' w4 I+ w1 V& m7 l
Hazard rate, 风险率
( x- m: Y$ w# y R) g4 PHeading, 标目
7 q P* K! v7 a% h2 Q7 d5 ^Heavy-tailed distribution, 重尾分布# T& \* I2 i; }
Hessian array, 海森立体阵
: v9 K8 T* A/ A! rHeterogeneity, 不同质0 y( K$ Q* N0 X% L9 b# K
Heterogeneity of variance, 方差不齐
0 u* E3 H( O) e" W9 B$ ?7 QHierarchical classification, 组内分组
( z' C# m5 V3 G! HHierarchical clustering method, 系统聚类法1 b7 ~ I: L8 I8 Z8 D2 t' _
High-leverage point, 高杠杆率点% m8 r {8 l2 Q& ]2 j
HILOGLINEAR, 多维列联表的层次对数线性模型3 U; f( { I$ N
Hinge, 折叶点
9 b! M! _ p/ f+ E9 @Histogram, 直方图
) N5 F6 d9 c2 q+ {* P0 {9 w7 ~Historical cohort study, 历史性队列研究
: i4 b. A/ G3 p2 P# qHoles, 空洞
: o) I0 }' W* V" o/ YHOMALS, 多重响应分析7 ]. G2 B, y- O$ p# F: Q
Homogeneity of variance, 方差齐性: |+ ^, m" t( L+ ]3 _( g
Homogeneity test, 齐性检验
( s1 |) f' d$ T7 rHuber M-estimators, 休伯M估计量
' i% p& u1 z6 SHyperbola, 双曲线
( u3 R/ M* ^) U T/ Y/ n6 VHypothesis testing, 假设检验
4 Y5 Q( ~( z: m) @Hypothetical universe, 假设总体5 q2 ?# \, u6 W/ \
Impossible event, 不可能事件8 ^/ i. K& s# }
Independence, 独立性
6 P9 Q7 W+ b# d7 p- `; Y* rIndependent variable, 自变量
. V2 i6 Q& M; }Index, 指标/指数
6 v5 N9 B2 A3 kIndirect standardization, 间接标准化法7 p6 R3 u C& y; f5 s, n" p q
Individual, 个体5 @8 R' Z" ~* l) X% k. d
Inference band, 推断带
% S* \, C: w# R1 A9 Z( QInfinite population, 无限总体: V+ h% _8 X4 `
Infinitely great, 无穷大: T, X: m* h; F4 f7 {
Infinitely small, 无穷小
6 d! m( C$ s2 H, }& C! @Influence curve, 影响曲线7 i8 ^; [' V. x
Information capacity, 信息容量3 U& L* c( b/ d- n7 ?$ |+ ~
Initial condition, 初始条件$ G0 \# w4 H! Q, I: o2 x
Initial estimate, 初始估计值% n: Z0 \; d+ h- u% w4 m( t
Initial level, 最初水平" ?7 L5 }9 {3 O0 Y- k
Interaction, 交互作用
, y0 R. O1 A; a4 F. }! HInteraction terms, 交互作用项
2 |. {; t0 ?% K# H+ lIntercept, 截距) i3 R. o) A' _% j
Interpolation, 内插法
P& v4 E; g2 S5 Y" U5 Q, J0 VInterquartile range, 四分位距$ T5 e# g) h0 m, {5 _" {
Interval estimation, 区间估计( n0 I6 I/ \; V" q1 S
Intervals of equal probability, 等概率区间! |8 J3 W _$ _$ g4 z% o
Intrinsic curvature, 固有曲率& [, t2 [5 N2 h& {. b3 V
Invariance, 不变性
- H3 a# i4 { f, R! y9 xInverse matrix, 逆矩阵- @ L$ c+ ?. T8 |% Q0 N: u
Inverse probability, 逆概率4 k6 x5 l" c( B) `( m" X
Inverse sine transformation, 反正弦变换* w m( E$ F8 n( s
Iteration, 迭代 4 Z$ ]7 R( L9 i9 \
Jacobian determinant, 雅可比行列式2 b/ T. U" V: r( |7 k* T( T8 p
Joint distribution function, 分布函数
& |, y+ a+ M, eJoint probability, 联合概率3 E- y: s0 I) z# K! f# J2 E
Joint probability distribution, 联合概率分布
- `2 J% {1 z* p* NK means method, 逐步聚类法
, K: r& ]7 Y" V, H3 K) YKaplan-Meier, 评估事件的时间长度
! l$ k8 J) g9 r. }9 x5 EKaplan-Merier chart, Kaplan-Merier图
. }: D" L2 k/ `+ [0 JKendall's rank correlation, Kendall等级相关3 ^* J" S/ O/ p* w8 }" P) Y& d1 [
Kinetic, 动力学
( }3 K" ~+ x6 cKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验/ j: H$ k/ E( r
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验* o+ ^) k7 a; n: G
Kurtosis, 峰度3 }. n( [, ^5 L! s) B9 D6 I
Lack of fit, 失拟
0 M* E1 ?) ^. f$ `. FLadder of powers, 幂阶梯. G' |! l$ e; T
Lag, 滞后0 i# g; z/ Q* b* U$ V& o
Large sample, 大样本
! A( _3 ]5 B, Y' X- g Y2 x a' ILarge sample test, 大样本检验7 b" m) m- Q {; h& T/ _
Latin square, 拉丁方/ Y) n4 j \% F: B+ e! j
Latin square design, 拉丁方设计
) N+ U1 k' Q& }1 ]' ^3 N! TLeakage, 泄漏
7 O0 }- ^5 z2 o; @" PLeast favorable configuration, 最不利构形
0 b, c8 Q2 N$ A& a5 X6 ?" kLeast favorable distribution, 最不利分布
4 M$ J" h3 O2 @( HLeast significant difference, 最小显著差法
' X, k6 _+ j0 v; X9 gLeast square method, 最小二乘法
0 V2 c4 F2 V# q; eLeast-absolute-residuals estimates, 最小绝对残差估计5 {$ ~9 q! T2 O% D, d/ B
Least-absolute-residuals fit, 最小绝对残差拟合
" k8 t. U( P# q/ g GLeast-absolute-residuals line, 最小绝对残差线
+ z; b' b5 k, N+ `1 ]- y; FLegend, 图例+ P, Q3 d0 Z6 e0 |2 A! q1 F
L-estimator, L估计量
4 H: j+ k! q; SL-estimator of location, 位置L估计量1 c9 |7 n9 \7 |* _ |$ ~
L-estimator of scale, 尺度L估计量5 ^, n: o# f2 x# q" |9 H
Level, 水平
$ P. l7 h3 J5 R$ KLife expectance, 预期期望寿命
' N6 I6 H) v& Z, R, h4 h* B: G7 _Life table, 寿命表
6 y2 t6 ^2 u2 vLife table method, 生命表法
z$ Q- a; w( P1 S+ \. b2 u0 }% eLight-tailed distribution, 轻尾分布! \8 r; `/ L4 K; I
Likelihood function, 似然函数
% b' I8 r+ D f9 WLikelihood ratio, 似然比
: R; K% P6 ?) W+ I; a" ?. P% Rline graph, 线图; p) n( H0 [+ O# ]9 N( P$ j) B
Linear correlation, 直线相关4 r J" {' x8 X8 [' `% S5 p6 D q
Linear equation, 线性方程 q, y2 l6 f/ h) l
Linear programming, 线性规划
' j9 W: g s- s8 }9 f% YLinear regression, 直线回归 L. W/ `0 `& X+ Q7 D/ W. h& u
Linear Regression, 线性回归
9 @4 t+ {. }) ULinear trend, 线性趋势
5 n" k8 a' k4 b5 v4 MLoading, 载荷 ( E/ a3 L2 X6 o6 m m
Location and scale equivariance, 位置尺度同变性
, O) L8 h) k7 Y( L6 S* PLocation equivariance, 位置同变性
( l9 d- M# Q: V: S1 w& ]1 C6 XLocation invariance, 位置不变性
- C) z5 L# G* r- [Location scale family, 位置尺度族2 S3 e' s) q. S" _/ @; c
Log rank test, 时序检验
; {4 z0 B& e- y, f v/ h$ nLogarithmic curve, 对数曲线
7 B) b# t; d3 B2 C8 y" U3 ILogarithmic normal distribution, 对数正态分布/ l- C8 S! _0 o( A' q* S& {
Logarithmic scale, 对数尺度
# W, u3 Z, k% }$ W( {: @0 H3 v' W KLogarithmic transformation, 对数变换 i1 g$ {4 l% H- N0 n
Logic check, 逻辑检查
% n" Q" ]* E9 L3 U+ LLogistic distribution, 逻辑斯特分布2 W5 Y: I/ N* d" [
Logit transformation, Logit转换# W, B' W6 o& l4 T+ V1 T/ [( E
LOGLINEAR, 多维列联表通用模型
5 ?) p# q: B! _! @. }- xLognormal distribution, 对数正态分布
0 ]; Z, n" z$ X% |. wLost function, 损失函数
' O: y/ ~! j/ a3 S2 R ?8 dLow correlation, 低度相关
" C, z% c _# n6 ^, jLower limit, 下限
/ i4 l U7 ]" y9 C6 D' nLowest-attained variance, 最小可达方差
& Y0 r/ E, Z6 yLSD, 最小显著差法的简称' ^ `8 {) o# m
Lurking variable, 潜在变量
& ?" G1 l3 ~* J: Z& eMain effect, 主效应! {: {8 P( A* ~8 w+ i; U
Major heading, 主辞标目. _; c0 e$ _1 q+ p' I# A- g3 b$ S" b
Marginal density function, 边缘密度函数
8 f) k, J( U. l5 u7 I- hMarginal probability, 边缘概率
7 L" m. R4 ?0 s! F/ D( h6 bMarginal probability distribution, 边缘概率分布. O7 \8 Y% Q7 Q) ~, D: ]. R, ?
Matched data, 配对资料
, N+ q3 V$ p7 @Matched distribution, 匹配过分布
; n2 z" J3 o; s. u) ?% I5 @' S0 k! }Matching of distribution, 分布的匹配+ {# F5 N \/ c( e
Matching of transformation, 变换的匹配
$ F: J- A$ j2 X9 j5 E: SMathematical expectation, 数学期望
! v, h$ |3 {5 _9 R b* _( RMathematical model, 数学模型( x K4 w. w, u+ P
Maximum L-estimator, 极大极小L 估计量
8 L/ K" U' l$ s& v1 E9 H; C V+ qMaximum likelihood method, 最大似然法5 p B D. j U) ^- x9 E' K
Mean, 均数
. u; a1 u* a l3 c* e" ~6 ~Mean squares between groups, 组间均方
& v& Q% B9 u" ]# O' k' V. ?Mean squares within group, 组内均方
C* L4 N% V6 W/ Z8 R. V2 G! TMeans (Compare means), 均值-均值比较9 W" o4 F( d' G4 H& s8 ]4 k
Median, 中位数
) n& C. N# z0 z% V3 @2 ^0 p$ SMedian effective dose, 半数效量: f* \, t# ^8 y! }
Median lethal dose, 半数致死量
7 ]4 `( `% J9 `0 r" ]Median polish, 中位数平滑
4 k* ~9 h. G) @4 s0 |Median test, 中位数检验
% G% t' T/ f/ k3 w, |+ W- UMinimal sufficient statistic, 最小充分统计量& Z$ D, w, s; ~4 _! T1 [/ M# b
Minimum distance estimation, 最小距离估计9 S+ p0 X3 I! ]4 N6 I
Minimum effective dose, 最小有效量+ ~1 d$ z7 }& f' N% k% e1 W
Minimum lethal dose, 最小致死量* ?4 m% ]4 O! o$ D" P5 ~( {
Minimum variance estimator, 最小方差估计量
: l$ ~( J1 q: lMINITAB, 统计软件包7 A( ?$ s% U" |$ V% ~
Minor heading, 宾词标目
4 L. @$ T- a/ ^& ^5 UMissing data, 缺失值: }3 j6 _: n$ b6 f9 q
Model specification, 模型的确定
# @* _7 X+ N! o* Z% AModeling Statistics , 模型统计 o7 \6 ?) w/ F. i, N
Models for outliers, 离群值模型" ]- e# @9 p7 p; A- u
Modifying the model, 模型的修正
+ h; A: G2 o7 |5 b1 @9 W& R1 K, YModulus of continuity, 连续性模
7 r6 ?& x; j, {: e- DMorbidity, 发病率
% R* K# \4 b' A7 e3 MMost favorable configuration, 最有利构形
! g/ Y0 k' K/ y! t/ W1 {5 {Multidimensional Scaling (ASCAL), 多维尺度/多维标度
: R+ }3 R. s" z9 T# a/ q7 jMultinomial Logistic Regression , 多项逻辑斯蒂回归/ |6 N3 q) K7 x
Multiple comparison, 多重比较
8 F; h& g4 y" O P. P2 f6 \Multiple correlation , 复相关* A5 Q& w( v( |$ L. j
Multiple covariance, 多元协方差
: ? A2 i) S2 vMultiple linear regression, 多元线性回归- \' q0 v9 z6 Q1 V
Multiple response , 多重选项6 K3 R: ?, L) l: Y/ z
Multiple solutions, 多解; @& M: q1 ?+ _0 u/ _
Multiplication theorem, 乘法定理
& T9 i9 z. G* L) v! |& M sMultiresponse, 多元响应
$ M7 K' _8 H1 iMulti-stage sampling, 多阶段抽样
; |* I/ X p' Y. q: c4 KMultivariate T distribution, 多元T分布" P2 f* m2 D4 D6 }0 x7 l
Mutual exclusive, 互不相容
- i e3 H7 c( I% I1 ?/ v$ J" N& [Mutual independence, 互相独立" {1 W+ y: o# g0 _1 y1 _3 u
Natural boundary, 自然边界
6 u, L& y2 K9 X7 x9 bNatural dead, 自然死亡4 K% n' G# V/ K0 T* W4 m& k
Natural zero, 自然零
$ k1 E( n; B' M6 A5 ENegative correlation, 负相关
7 x, W9 m2 v4 \) d" bNegative linear correlation, 负线性相关
5 O: R& k. f* q3 W }Negatively skewed, 负偏8 O0 Z$ g8 ^: ~' K$ Q
Newman-Keuls method, q检验
, H8 {5 R3 a2 xNK method, q检验/ u' Y& \- Y8 x) N4 a2 S8 s
No statistical significance, 无统计意义 n3 t7 {! G6 A" ?
Nominal variable, 名义变量
( Y2 i4 V6 W. _5 S8 I8 [Nonconstancy of variability, 变异的非定常性. u8 r: B' S$ T1 X$ ~9 G$ A
Nonlinear regression, 非线性相关- u. p; q$ s' n$ q% ~; D! Z
Nonparametric statistics, 非参数统计
- J z+ g. g8 x( {4 t2 nNonparametric test, 非参数检验
9 b1 E% |) K2 z( G3 `Nonparametric tests, 非参数检验
6 n4 {* Z: e N1 E; b8 gNormal deviate, 正态离差
S4 H: F L2 e+ r1 _/ Q4 ^Normal distribution, 正态分布
( M( G5 A8 \9 M# Y6 ]6 ?" qNormal equation, 正规方程组/ d" k6 T# U5 M: z5 ^+ z" V, K
Normal ranges, 正常范围
3 y2 n3 X, j6 a+ a6 q$ BNormal value, 正常值, u. w* d( [' u7 r
Nuisance parameter, 多余参数/讨厌参数
7 y$ \' N9 T1 dNull hypothesis, 无效假设
: }% j: L6 N, T% JNumerical variable, 数值变量
5 t3 F y! r' s& |# p. h" YObjective function, 目标函数$ Z$ k7 Q' H ^1 R7 U: A! n
Observation unit, 观察单位
% Z: l) `1 H4 n: MObserved value, 观察值
4 ~7 }8 ^4 C/ i* G+ OOne sided test, 单侧检验
b# w+ K$ m1 B) Y% B* W, v- V, R; rOne-way analysis of variance, 单因素方差分析, S0 P8 ]# }( _2 T; r e
Oneway ANOVA , 单因素方差分析$ p2 B, J3 h" Z2 R0 h1 `! `' u. B
Open sequential trial, 开放型序贯设计
9 M% h' C- R6 hOptrim, 优切尾
" Z$ ?6 N! T: w8 A- Q- Z4 kOptrim efficiency, 优切尾效率# ]. y/ c. a- y
Order statistics, 顺序统计量
' y! o2 g# k; e# _$ fOrdered categories, 有序分类
& `4 g7 Q3 t. O' A- n5 F. DOrdinal logistic regression , 序数逻辑斯蒂回归( e2 v: V7 X0 [7 |, w
Ordinal variable, 有序变量6 O7 q' L Y, K% e" X2 _8 j
Orthogonal basis, 正交基4 l# {2 x/ G" R" M
Orthogonal design, 正交试验设计
8 [ ?! l( ~* oOrthogonality conditions, 正交条件
2 d+ L% O5 R8 a U# ~ORTHOPLAN, 正交设计 $ V$ A. V0 u: y
Outlier cutoffs, 离群值截断点! ]- \, k6 P }( L+ z8 x
Outliers, 极端值# E! G$ W3 n S% O% z$ g
OVERALS , 多组变量的非线性正规相关
0 a+ |0 e' x& s+ U3 O6 W- }Overshoot, 迭代过度
+ H* p) @( K+ rPaired design, 配对设计3 v0 e$ I2 S) \" N
Paired sample, 配对样本2 C8 O7 c6 ]: N) D- Y$ j* k
Pairwise slopes, 成对斜率
, B: c" s5 `- M, `- r* c+ \Parabola, 抛物线. Z8 e, v$ l7 h% G% @8 A
Parallel tests, 平行试验. K6 [* j4 z' t) f3 }/ ?
Parameter, 参数
* u8 Q+ Y2 y* H9 A7 i7 W. v wParametric statistics, 参数统计
0 M% ^" K5 v% B9 M: S- _Parametric test, 参数检验2 o9 i# q! O' x
Partial correlation, 偏相关8 a' W, z4 }# o# Y3 D- M; p: Y2 J
Partial regression, 偏回归9 g! D& C( g3 ?4 g
Partial sorting, 偏排序5 r* u; O; o2 l Z
Partials residuals, 偏残差
& D% a/ b4 o, n% u# yPattern, 模式* ?3 ]5 D9 s, ^: u, w
Pearson curves, 皮尔逊曲线9 T2 e2 i' D, c& U* c. N8 j
Peeling, 退层
- A0 C8 c) U+ OPercent bar graph, 百分条形图+ X1 _& Y$ w7 f9 v& N
Percentage, 百分比
1 A. G, g: q! F% j3 B$ B0 L- wPercentile, 百分位数
' _: M5 x! q: S' _9 }Percentile curves, 百分位曲线! w1 p9 t k5 B4 M
Periodicity, 周期性2 j* z c# {9 m$ _
Permutation, 排列$ c! N) U, m$ _+ ?
P-estimator, P估计量8 u- B0 g4 `; T
Pie graph, 饼图, w6 O1 K% h. h! b1 L
Pitman estimator, 皮特曼估计量
. U/ j6 o6 v8 V+ {Pivot, 枢轴量6 x& H( @! H* W) k c" P
Planar, 平坦" }, n8 {3 _! i
Planar assumption, 平面的假设1 A; Z" N2 U9 ^# v; Z
PLANCARDS, 生成试验的计划卡
, s L# z% D% R* ~% [- L# q* NPoint estimation, 点估计3 H% r3 T2 M9 I. H+ e% U
Poisson distribution, 泊松分布4 A; @/ z4 s2 _8 Z+ |- Z& A2 a+ {
Polishing, 平滑1 U; L. ]7 b) Q, d" ?3 r+ a) o6 `1 T
Polled standard deviation, 合并标准差4 g2 H: u3 ~+ g4 A1 P. }
Polled variance, 合并方差0 ~% k! |: {: N R/ i8 Y, j! C
Polygon, 多边图
: k; f. _9 b+ y0 J; v$ X* j( kPolynomial, 多项式 I& M. \5 E: U% D) _6 k% [
Polynomial curve, 多项式曲线
- b ~/ x' ]. WPopulation, 总体" I2 T& x/ v- v* R- c
Population attributable risk, 人群归因危险度3 h8 y0 C: I# x( _1 u. Z3 ?! D
Positive correlation, 正相关9 l# |( X. D2 U( ]. O
Positively skewed, 正偏
5 _+ T W: _) O# U1 H- YPosterior distribution, 后验分布
" q3 Y* X3 D% u3 {Power of a test, 检验效能; a `# T2 O* O4 P F
Precision, 精密度# K) ^8 U( U" O. k, J4 B, [
Predicted value, 预测值3 [/ ~) F+ p4 a _9 N1 J
Preliminary analysis, 预备性分析7 y0 E1 o1 M# J1 ]* V& E% @! U
Principal component analysis, 主成分分析' @& _& Z& w/ Y: v( L# n
Prior distribution, 先验分布8 r5 l3 D2 i$ U; u7 F" a
Prior probability, 先验概率
! r& v# k. l5 l6 d, \Probabilistic model, 概率模型
5 v6 k4 c' T7 }# m5 x: _8 h4 b0 lprobability, 概率" d9 \; F M' k( S$ k
Probability density, 概率密度
" l9 M. P9 `; M: o- pProduct moment, 乘积矩/协方差
% R5 X8 L1 l; q& W) C7 E9 k7 cProfile trace, 截面迹图7 {6 b6 }% O: [5 l
Proportion, 比/构成比
8 [' z" w" {& d! B1 W$ eProportion allocation in stratified random sampling, 按比例分层随机抽样
5 u, H0 N6 H3 A2 KProportionate, 成比例
. p1 {6 J+ L8 {, |% PProportionate sub-class numbers, 成比例次级组含量
- I+ j" h- j- Y0 @1 s& cProspective study, 前瞻性调查
' p, ?" A6 V. h# lProximities, 亲近性 5 g3 `; M" O7 W8 u
Pseudo F test, 近似F检验& |: Y: r; X9 m3 i" K' N
Pseudo model, 近似模型% s% E) r" L; A6 F, j
Pseudosigma, 伪标准差3 l, [) D/ s$ @1 c4 A
Purposive sampling, 有目的抽样0 r/ K# d4 x* g! k9 n
QR decomposition, QR分解) a' F% }% ^3 u: o+ _
Quadratic approximation, 二次近似+ I! x& w( q. f& x7 B8 ^( `
Qualitative classification, 属性分类$ g6 v, V5 `1 p, X
Qualitative method, 定性方法! \. O2 ?' L, a& C
Quantile-quantile plot, 分位数-分位数图/Q-Q图
5 H4 u/ ` _" |3 M& C7 x& j& IQuantitative analysis, 定量分析
. z% a" [* p# `$ a4 c5 wQuartile, 四分位数; E4 k7 V6 o8 x( `, r' ~- g4 x! w
Quick Cluster, 快速聚类 U" {" c3 F1 ?2 H2 M
Radix sort, 基数排序
. _, e# q& f6 R$ L, _2 }Random allocation, 随机化分组
+ }( |* [9 Y; F' i; rRandom blocks design, 随机区组设计
4 B5 z% c# K( A$ ZRandom event, 随机事件
9 y& ^0 z q9 `" r3 ]7 e% iRandomization, 随机化
+ w" ?. i, r. DRange, 极差/全距
( ]. k- r( s5 L; TRank correlation, 等级相关
/ n+ ?' @) a/ Y9 j; H' _5 GRank sum test, 秩和检验
9 h; [! P+ ` g1 IRank test, 秩检验4 q+ ] P a% Z% i
Ranked data, 等级资料; O% f4 @: m% [9 m
Rate, 比率
" m# S* R) [4 DRatio, 比例
. T. V( b) r7 u: F: Y& yRaw data, 原始资料' _7 z! f" p0 X6 X4 J/ S L% ?2 v* }
Raw residual, 原始残差: ]( E3 m8 v1 p8 w3 g' {1 U
Rayleigh's test, 雷氏检验
' d% D0 z& ^7 z' ~0 a* C5 e+ YRayleigh's Z, 雷氏Z值 4 Q3 I* ^ U" w. R
Reciprocal, 倒数
, V) P% u% f& z* I* K9 G4 TReciprocal transformation, 倒数变换7 O5 U! b# h) f. q9 l2 S
Recording, 记录1 u- } J' ?6 Q! @' x1 b
Redescending estimators, 回降估计量
" j% {% R/ H% o8 {Reducing dimensions, 降维' z. A `/ {6 z9 v1 P+ {: K
Re-expression, 重新表达6 a3 _: q$ i' x. y( S% O
Reference set, 标准组. {9 x0 j2 V. O P1 j7 [
Region of acceptance, 接受域: f* N# b6 r* K( }6 C
Regression coefficient, 回归系数6 l7 F/ p# e: I" P8 y" W# c% Z
Regression sum of square, 回归平方和
: I( c1 P6 ~ e( Z$ A! M9 vRejection point, 拒绝点; b/ W. V2 ~( ^' j9 x; H4 `
Relative dispersion, 相对离散度
4 G" B/ N* E- h9 ~1 iRelative number, 相对数
& _; v7 a! c4 e- c% A$ jReliability, 可靠性
5 C, V- x, Y' J3 F0 i8 ~- ^Reparametrization, 重新设置参数
1 n! C# b8 ~# }9 }, i( aReplication, 重复
9 w! \6 L" i. g+ c3 k( ]Report Summaries, 报告摘要4 q2 ^4 v+ Z. i" }4 [- O
Residual sum of square, 剩余平方和& n3 d- `6 K0 E; O" ^% ^ V! m* a0 s
Resistance, 耐抗性$ K# N/ z0 V: s
Resistant line, 耐抗线+ b: {4 Z }* z9 ?6 w: |
Resistant technique, 耐抗技术& o* T, A3 ]; s% p
R-estimator of location, 位置R估计量
0 d b7 E0 D; |; hR-estimator of scale, 尺度R估计量+ R0 f L, ^+ y; A9 W g
Retrospective study, 回顾性调查
/ P8 U* {4 h( Z; PRidge trace, 岭迹2 Y9 V2 _5 ?+ ^+ ]8 p
Ridit analysis, Ridit分析
. @# _" }; \& T6 Q& F4 M7 E8 YRotation, 旋转" M' {& V7 r- l0 r# W9 D
Rounding, 舍入
* G$ y1 {4 I& u' x7 ^Row, 行
! e% u) n) E4 rRow effects, 行效应
3 j+ Q8 c, e: _1 M2 m! oRow factor, 行因素
8 A/ K/ x8 F: N0 k h) aRXC table, RXC表+ M6 _* g' W& c* m
Sample, 样本# G# K* V8 d$ p1 q
Sample regression coefficient, 样本回归系数; p: O% N; m- ?) _1 W
Sample size, 样本量
' |+ w( c$ v# `. SSample standard deviation, 样本标准差
$ B$ A3 P0 k6 V* A! [' A# KSampling error, 抽样误差 d# C S, I7 P! C. p: ~" a
SAS(Statistical analysis system ), SAS统计软件包
# R/ \! e1 Y$ E9 }; r9 u$ z' XScale, 尺度/量表9 q4 K, E5 D! I
Scatter diagram, 散点图
: |7 `1 F1 f% ?! zSchematic plot, 示意图/简图
6 O& f. V1 f, Q4 u) f4 Y4 Z; x. j! e3 zScore test, 计分检验
* @# C, O- m0 }/ R i- gScreening, 筛检
" s: `7 n6 G6 W: q2 u1 XSEASON, 季节分析
9 I+ i- L2 R: |0 R" |$ G: ]( Z3 U* gSecond derivative, 二阶导数( f0 g9 W1 e" k: l& M* ]6 {
Second principal component, 第二主成分
2 k2 `- x3 j: v! n. T4 d# V' wSEM (Structural equation modeling), 结构化方程模型 : s$ z" F h- b7 t3 R
Semi-logarithmic graph, 半对数图
- ]; `# x* ~9 M2 LSemi-logarithmic paper, 半对数格纸
3 R! L% ~5 T8 s# Q" Y7 jSensitivity curve, 敏感度曲线
1 S! ]& {9 Z$ YSequential analysis, 贯序分析
% ]0 q: S) Q: u* ySequential data set, 顺序数据集
0 g! i/ l7 K' d6 d! ESequential design, 贯序设计2 v& d8 _: S& x8 H. {
Sequential method, 贯序法) q: o- Z0 [0 q
Sequential test, 贯序检验法; |' m, y. ^1 s3 m/ O! N3 Z
Serial tests, 系列试验: A" b; V5 }# ]4 m- p
Short-cut method, 简捷法
& t! {) T; W: }2 Q) n2 F& [$ [2 R/ nSigmoid curve, S形曲线) h* p$ B4 q @# |# g& E
Sign function, 正负号函数
$ \- R; \/ ?& }# {0 ESign test, 符号检验
& h% s" }& b( M$ D: nSigned rank, 符号秩7 g* W6 D$ b4 E2 ~
Significance test, 显著性检验 G) K0 Y3 c3 K
Significant figure, 有效数字$ [$ X8 s9 s8 g& a: [3 L) i
Simple cluster sampling, 简单整群抽样
* W! R- S- t, } _Simple correlation, 简单相关% Y- l' I9 f& K3 m, N
Simple random sampling, 简单随机抽样
; C e; z# Y- g; e0 B/ CSimple regression, 简单回归3 X7 T2 t- Q# t0 Z3 O: \
simple table, 简单表
( m X' c* L! C6 Z8 S8 v* LSine estimator, 正弦估计量. J! f8 J4 X9 _2 T% K& S3 M
Single-valued estimate, 单值估计" s4 K. r }" h0 h0 O H0 Q4 P' |
Singular matrix, 奇异矩阵
1 I4 U8 p, h b/ K0 D# `3 hSkewed distribution, 偏斜分布* {& _1 ~0 M/ N! L$ z
Skewness, 偏度
4 f3 }2 V$ g G5 bSlash distribution, 斜线分布, U. o9 r% ` H. v1 w
Slope, 斜率' P! K/ A- j) y9 t6 n- w6 m
Smirnov test, 斯米尔诺夫检验
( Q; ]' e0 ~! E+ D* T9 u dSource of variation, 变异来源
( q/ L& l9 W0 P8 t. g" I4 H3 Q2 uSpearman rank correlation, 斯皮尔曼等级相关
/ _' Y% E9 E/ @/ T+ l; MSpecific factor, 特殊因子. T8 R% z+ Y% ]
Specific factor variance, 特殊因子方差
# z; D+ I) `+ T5 }; q) h( h2 ^Spectra , 频谱5 G2 g: g" F1 @: q! I
Spherical distribution, 球型正态分布% L1 C+ M3 z7 u1 \* ~ o: y E1 b
Spread, 展布: a+ n6 V4 h8 R
SPSS(Statistical package for the social science), SPSS统计软件包
' u" [/ Y ]0 v# ^7 L5 TSpurious correlation, 假性相关: p, r( c; H8 J- T( e2 ^& c
Square root transformation, 平方根变换
( @2 q" v7 ~/ w4 eStabilizing variance, 稳定方差, T( x0 M! i" B2 R5 |0 S+ J
Standard deviation, 标准差' T1 R9 Q* o* J: [1 ]9 S
Standard error, 标准误1 o$ h( X: n: `0 r6 ~! s
Standard error of difference, 差别的标准误9 l& k, r0 X% x. J
Standard error of estimate, 标准估计误差9 A' u, {! @, \! m ~& n% `, [2 C
Standard error of rate, 率的标准误2 j! s; C% _" _6 x; `
Standard normal distribution, 标准正态分布5 s) y/ W. h7 B2 r4 y7 _5 G
Standardization, 标准化: P" _2 G7 z2 \6 I% @2 D1 g
Starting value, 起始值
+ u( V' L) j# P/ W& C; R: O2 ~) BStatistic, 统计量% u* X& a2 S3 B4 C' |. A
Statistical control, 统计控制. `$ t7 W& D" k% [* M5 K
Statistical graph, 统计图/ Y9 u# ~) @6 E% }! \
Statistical inference, 统计推断
3 a) h5 d9 V8 s9 H5 v$ ^Statistical table, 统计表
7 ~) p" T5 }" j4 H5 B* CSteepest descent, 最速下降法5 c# R1 V7 q& q/ p- v6 e; Y
Stem and leaf display, 茎叶图
- v+ y) Q& X( a/ r; @) ?Step factor, 步长因子# G0 e3 n4 D- J5 M) f
Stepwise regression, 逐步回归, D7 F0 |$ h5 Z# y' P
Storage, 存
+ k, Y# j4 @0 A! T/ O; A- a9 FStrata, 层（复数）
G/ D3 {' p$ f+ ]' K0 g' F6 Z3 YStratified sampling, 分层抽样
7 m' Z8 W5 Y y9 uStratified sampling, 分层抽样0 m: T' C. J7 V1 b6 i* Z+ J. _
Strength, 强度' V( a* k& t+ }5 o6 R1 @
Stringency, 严密性
( j* z' u* s. [+ r( H/ ?Structural relationship, 结构关系( k4 L; i% ~4 F/ W
Studentized residual, 学生化残差/t化残差
# f; {: Q; L; J# x: p- \) B, USub-class numbers, 次级组含量
% p- \; n) D+ t! X+ J& H- tSubdividing, 分割" C! G) }$ W, y& E" q
Sufficient statistic, 充分统计量
1 S. t8 q1 f, ?# o \, gSum of products, 积和/ |* N8 W7 j+ U- A' r
Sum of squares, 离差平方和, ^2 K! @* M- J* g, X+ d
Sum of squares about regression, 回归平方和
D; `& R+ b" f* w1 e6 k+ \Sum of squares between groups, 组间平方和/ L* ~1 P; j0 Q
Sum of squares of partial regression, 偏回归平方和
' t/ I' N5 n1 M# G/ r/ |* i5 w7 G5 {Sure event, 必然事件) j8 B$ P" f. x4 H4 Q/ P
Survey, 调查: p' C" E1 B: j
Survival, 生存分析
6 K9 F& x6 e5 K) i( ]3 R" d% ISurvival rate, 生存率! d- r" L1 H* {' I2 Y
Suspended root gram, 悬吊根图3 H/ \+ Q$ M+ E6 ]' P; q' E3 @( u
Symmetry, 对称 R7 \+ ^* a3 G
Systematic error, 系统误差$ [% _1 R/ N- p7 z& [- ^
Systematic sampling, 系统抽样7 R! P8 d6 N3 f6 f
Tags, 标签( y9 ?5 n& z3 M* U- s1 G4 @+ M7 i
Tail area, 尾部面积
) W% p4 I" s0 I. g3 y9 lTail length, 尾长
! [$ \% I2 s* @- ETail weight, 尾重
7 o+ G( ? n& Q$ GTangent line, 切线
6 j4 d i: U. n/ B" g* G5 Q; {Target distribution, 目标分布- n* r* V6 w8 i% A& O
Taylor series, 泰勒级数
. M: R# A4 _4 `Tendency of dispersion, 离散趋势
8 x2 D0 ?2 ~$ w" n6 G rTesting of hypotheses, 假设检验
7 G" l6 `+ M) @2 Z9 y% U) n/ gTheoretical frequency, 理论频数( k% k+ L0 {8 K5 p: ^" ~! }0 R
Time series, 时间序列
7 p8 M# v j$ N5 `) v9 [3 _' L' D- uTolerance interval, 容忍区间: h$ r3 }+ C% T3 n! y/ i" F
Tolerance lower limit, 容忍下限
0 V) P0 _' L, H+ r5 }Tolerance upper limit, 容忍上限
: ` v# |- R( x- |! nTorsion, 扰率
8 {1 u; e- G* ]* e) k. ~Total sum of square, 总平方和
$ _% S9 y0 r1 ITotal variation, 总变异+ |' {7 d9 |9 s: ~
Transformation, 转换. ]0 O/ m {) s
Treatment, 处理
- W: v% R; \) I/ s; u1 J. J( W8 RTrend, 趋势/ e) q4 \2 V4 U2 F3 V6 [
Trend of percentage, 百分比趋势
5 ]' R. w; K/ E( O6 yTrial, 试验0 R) Q- ^ c8 e7 V1 ?% R. K
Trial and error method, 试错法" ?2 M$ {, E1 ^' m9 _ r
Tuning constant, 细调常数
7 w0 M/ z0 ] iTwo sided test, 双向检验; Y/ ?, b) K9 P' V% F& j) S, K
Two-stage least squares, 二阶最小平方1 w m) F- P$ S# x6 c9 ^4 j
Two-stage sampling, 二阶段抽样
* d! R2 g q$ S/ d4 [) ATwo-tailed test, 双侧检验
. ? L( A5 R0 d: F0 H: MTwo-way analysis of variance, 双因素方差分析
0 Z/ S2 f: M2 u! x. x& vTwo-way table, 双向表
( z$ @, Z! |1 ZType I error, 一类错误/α错误
% l. S+ p, N7 a1 @1 p: u8 WType II error, 二类错误/β错误! y* U, K( g8 q7 Y) A+ h
UMVU, 方差一致最小无偏估计简称; } Y* s+ d+ I% q0 z
Unbiased estimate, 无偏估计6 Q2 F* e% Q4 J7 q# H5 b: D
Unconstrained nonlinear regression , 无约束非线性回归3 \; X' ]5 y! E4 a5 S3 P- V
Unequal subclass number, 不等次级组含量
; ?+ E6 Z$ @6 E5 X* QUngrouped data, 不分组资料: r4 D4 @0 b e: ?
Uniform coordinate, 均匀坐标
: \7 q' y2 t" @* X% f" [. bUniform distribution, 均匀分布, O' _3 G$ ]7 Z' X! w+ C8 u+ F
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
* C8 r1 {) F" i' ?/ }* mUnit, 单元
$ b# T; S$ Y3 K" O( UUnordered categories, 无序分类
2 x t, h" V: y# y- \. eUpper limit, 上限
' ~ A* T$ ~* EUpward rank, 升秩5 _; \- i+ i: ?
Vague concept, 模糊概念
2 ~7 v. V; U4 L7 V$ eValidity, 有效性( ` ]3 O% B% x, A7 I
VARCOMP (Variance component estimation), 方差元素估计
. Z1 Y+ N7 C( x) UVariability, 变异性6 P* d" W, S( `: U$ _
Variable, 变量1 g! s0 z/ a6 [" [8 e8 l
Variance, 方差
. K! Y+ T8 Z& l- g7 pVariation, 变异
7 N% i& t% y7 [) L7 V# Z# YVarimax orthogonal rotation, 方差最大正交旋转
8 h8 L- V7 g3 w5 C( s" {Volume of distribution, 容积
4 [2 `% ~ H9 D* n/ jW test, W检验; z$ D2 b! f* {+ d7 d
Weibull distribution, 威布尔分布( j! a+ J: `# T) g1 ]. A$ F
Weight, 权数
! X4 G R% s; EWeighted Chi-square test, 加权卡方检验/Cochran检验& \$ t& o7 v8 ^% {# A* f) \
Weighted linear regression method, 加权直线回归
+ K2 u r, b2 cWeighted mean, 加权平均数' S7 m' f/ R4 C R
Weighted mean square, 加权平均方差
# p, F3 U, J: f/ ~Weighted sum of square, 加权平方和, P# J* ^: }6 a6 J4 s9 _2 A- R
Weighting coefficient, 权重系数: y9 g6 s+ w+ r- g" K+ z
Weighting method, 加权法 % t1 h. F; P3 C; d5 N7 O! |
W-estimation, W估计量4 T; q: H/ Q& J5 D' P8 y
W-estimation of location, 位置W估计量
) E1 y( L" U; a6 G$ fWidth, 宽度8 j' g! d; S6 W2 G6 @6 C. ^3 b& _
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验+ M3 f7 r3 @, s+ T& d
Wild point, 野点/狂点" j9 p) C) d; B l: Q
Wild value, 野值/狂值
9 G5 W: N* ]3 r6 s* t9 IWinsorized mean, 缩尾均值
. [; C/ {1 m( X* M9 a. rWithdraw, 失访 # ], {- }- ~, u1 |( \2 O4 S
Youden's index, 尤登指数
& _( |8 n# S, ?Z test, Z检验
! K& A5 U0 X/ uZero correlation, 零相关8 G3 n* L- h/ r; _
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
