|
|
Absolute deviation, 绝对离差$ d/ N, a' y- o9 K. D
Absolute number, 绝对数: N" z0 V9 C, q0 w3 R
Absolute residuals, 绝对残差0 c9 m0 c; k6 V3 w
Acceleration array, 加速度立体阵; `; v2 z) {+ |; I3 Y
Acceleration in an arbitrary direction, 任意方向上的加速度* `8 p7 l ~0 x* j: d
Acceleration normal, 法向加速度
* e% P# ^& `( q( Q* T0 jAcceleration space dimension, 加速度空间的维数' h' T: r5 k. {1 Y
Acceleration tangential, 切向加速度
+ V( T6 x( Y8 J, oAcceleration vector, 加速度向量: p/ E, @6 s1 @% }6 R; f! ^1 a
Acceptable hypothesis, 可接受假设 j. r' p( }5 P/ G1 N# J" h
Accumulation, 累积
" o, V ]$ c, N9 W6 @ \Accuracy, 准确度
' ^: W/ G3 r, L: a# \9 f! [Actual frequency, 实际频数 [: Y7 ?! \* E
Adaptive estimator, 自适应估计量
1 H' e: Z4 n3 j4 gAddition, 相加9 `9 F7 \/ S( i& o' z' Y( a
Addition theorem, 加法定理
8 J6 Y* ?- V- }3 e" TAdditivity, 可加性
6 E9 `$ T' @! J6 d! J- wAdjusted rate, 调整率, I _8 C8 F J4 n( R
Adjusted value, 校正值1 A+ @1 Q2 S# f8 A# d
Admissible error, 容许误差8 J7 Z6 c5 l5 X/ {/ I8 W& L0 R
Aggregation, 聚集性
! Z0 d, h9 J$ S9 \Alternative hypothesis, 备择假设4 R4 O$ s$ A1 k. m. ?" R" `8 w
Among groups, 组间
- `. z' w* ~* r' YAmounts, 总量9 @1 i& e6 K$ M: U3 m( Z$ {$ b
Analysis of correlation, 相关分析0 R- J0 y8 @) I7 k
Analysis of covariance, 协方差分析
* x) Q/ B5 i% _9 v4 AAnalysis of regression, 回归分析
' N* Y4 ^+ x# U7 [Analysis of time series, 时间序列分析
& {9 U. t; b) q" Q! v. B( n/ TAnalysis of variance, 方差分析: u4 s. l( J' N( ^
Angular transformation, 角转换% P8 ?. ~+ _' ^: q
ANOVA （analysis of variance）, 方差分析4 J/ O: G, A7 K3 h6 H* ~/ c
ANOVA Models, 方差分析模型
. [# ^' w. d6 R9 D; SArcing, 弧/弧旋! O' @% y+ [0 n9 N2 ]! Y
Arcsine transformation, 反正弦变换
/ g7 z# T# C: d2 k8 \% ^Area under the curve, 曲线面积' e0 \% \" q" L7 U
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 6 O4 s) Q" Z3 P; A
ARIMA, 季节和非季节性单变量模型的极大似然估计
; l4 ?: V) a$ I/ N) ^Arithmetic grid paper, 算术格纸
3 Y$ S0 c' f( b; b$ L. Q" kArithmetic mean, 算术平均数
6 M* Q. K! {1 x7 p {4 X6 }3 k( R, yArrhenius relation, 艾恩尼斯关系2 b; l9 }( {) W" T, ^4 @
Assessing fit, 拟合的评估
1 x% l5 ]" \8 L+ k" J2 u/ ]Associative laws, 结合律, b% k$ Y0 C Y. \- M
Asymmetric distribution, 非对称分布! o2 k9 {) f; y* F- h: I" S! h
Asymptotic bias, 渐近偏倚
% d' h. C. f. ?, v2 c2 [Asymptotic efficiency, 渐近效率. Y. l$ y$ ^7 V
Asymptotic variance, 渐近方差/ h- R; e9 o- w- f h8 L/ L
Attributable risk, 归因危险度
2 o: Y0 r$ T% u. t1 P) S5 kAttribute data, 属性资料0 y. D3 ^9 q% j' G4 m9 X) I
Attribution, 属性8 S: m) ^5 f7 a- d) X& [5 p/ q7 v
Autocorrelation, 自相关
& N9 a8 ?6 K! T* WAutocorrelation of residuals, 残差的自相关 Z+ B# ~/ t2 N, M
Average, 平均数5 B* ^, }4 w- _" ]' w
Average confidence interval length, 平均置信区间长度1 Q U) g& x$ q1 c
Average growth rate, 平均增长率
" V$ j( E8 J/ w/ I# `$ `, \! v# FBar chart, 条形图
1 K- d3 v0 [* f( aBar graph, 条形图
0 T+ H$ r6 O& V6 ~ _7 g' D: YBase period, 基期6 N8 [' D, v( o0 S* ]" [8 X& z
Bayes' theorem , Bayes定理" Y( i$ p( y5 s' ~, m {4 B
Bell-shaped curve, 钟形曲线6 z0 |9 I4 x* h% P. W( H
Bernoulli distribution, 伯努力分布$ v: t" k" O/ ]& V: W% Y$ F" A
Best-trim estimator, 最好切尾估计量
1 F- m" I# a" A5 _Bias, 偏性
0 @+ B: |2 u' ?1 T6 P: ?" D! dBinary logistic regression, 二元逻辑斯蒂回归4 _' x% j0 i- h8 _. O9 j5 i2 p
Binomial distribution, 二项分布5 Z) d7 L& e7 |0 X% D
Bisquare, 双平方* j/ W1 L0 i6 c/ f! f1 P
Bivariate Correlate, 二变量相关
; |6 R- @+ G5 N2 r; VBivariate normal distribution, 双变量正态分布) ~ ` P5 \& f
Bivariate normal population, 双变量正态总体
" r. `& ~3 W# {- l, [Biweight interval, 双权区间, g8 ~9 S. H' n9 ]3 }. X, O
Biweight M-estimator, 双权M估计量5 C4 }0 Y9 v( U' i" E# F5 z8 O0 k
Block, 区组/配伍组) s* ?: g3 x" |: P5 `0 u
BMDP(Biomedical computer programs), BMDP统计软件包! o8 C9 P) D7 X# W' ?
Boxplots, 箱线图/箱尾图
" T8 e, g& Q: e; B% h; g1 |- QBreakdown bound, 崩溃界/崩溃点
6 d" T9 U* `! e `- JCanonical correlation, 典型相关$ L2 p, Y6 B: `# |
Caption, 纵标目
: G9 f4 M9 V3 r; DCase-control study, 病例对照研究1 C- c T" Y1 T, ?$ J% ^5 c! a
Categorical variable, 分类变量* o# {% t. T" K
Catenary, 悬链线6 j) S8 {1 l% b, C ?" K
Cauchy distribution, 柯西分布5 H- j* o* n- q2 n8 P, M
Cause-and-effect relationship, 因果关系) Y' ]9 W2 R1 k; \' h
Cell, 单元" Y9 y- b4 W: a$ C3 c
Censoring, 终检
+ u" s, P2 R4 J6 M/ qCenter of symmetry, 对称中心
+ E2 Z7 h3 g+ H: y0 y7 x) |! QCentering and scaling, 中心化和定标
+ y7 r- E9 C4 S' n; yCentral tendency, 集中趋势6 m5 \& h4 w5 R' A j6 K( O
Central value, 中心值
- g- u4 K3 B, D) Q& Q6 P/ WCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
X. t) }6 G" C) p. k, D: ?# DChance, 机遇
1 w2 c2 s' h3 q8 x* M. RChance error, 随机误差
5 ^, F! z4 ?% ]' Q, hChance variable, 随机变量
$ Z- v$ `/ r: o B* {* zCharacteristic equation, 特征方程8 \- h( ^& ?% A& E& Y* t
Characteristic root, 特征根8 D: p& d# C, [! m' V' A
Characteristic vector, 特征向量
, P1 [0 N: A0 |. [0 q% JChebshev criterion of fit, 拟合的切比雪夫准则 A" v3 N* H" ^& Z }- z. L
Chernoff faces, 切尔诺夫脸谱图( i4 I# f( D0 T" r0 N* h: l
Chi-square test, 卡方检验/χ2检验' ^ `0 {3 E3 r) ]7 `1 G' Q
Choleskey decomposition, 乔洛斯基分解
: C4 ?- d" Y( tCircle chart, 圆图
5 e7 g9 g S- XClass interval, 组距( q. `" p/ b! a8 K0 z6 N# W
Class mid-value, 组中值
: |+ a7 s9 f- N8 `( X) q+ t5 LClass upper limit, 组上限
$ s7 I1 A5 \" u- H9 }" [$ AClassified variable, 分类变量, k+ B4 B6 j0 H$ d. z" X& _* H
Cluster analysis, 聚类分析. O( _ F* L* W6 j
Cluster sampling, 整群抽样- O0 q& `, J5 y: V
Code, 代码
- L% _: v! j g. I JCoded data, 编码数据
* V2 d# D# ^8 r. {; G' `Coding, 编码
+ p" W. z' \4 tCoefficient of contingency, 列联系数' h2 ^& e1 `6 T' m9 X. n
Coefficient of determination, 决定系数
2 W8 g- c' h7 r- q9 K, `: Q/ GCoefficient of multiple correlation, 多重相关系数8 L0 R' k- m# E' C/ E* ~" {+ L6 P# h
Coefficient of partial correlation, 偏相关系数
. s( L8 V Z4 ?$ k- j9 ]Coefficient of production-moment correlation, 积差相关系数0 P, b4 j0 F: ?4 o: Y! C8 r: G
Coefficient of rank correlation, 等级相关系数% c4 W% ?: ~: `+ k0 ~
Coefficient of regression, 回归系数
* v" V% Y" F/ `( ^7 ]! h( FCoefficient of skewness, 偏度系数
. S @$ v' h9 Y' ECoefficient of variation, 变异系数8 i9 s# X1 A" V Q$ Z5 d) y: c
Cohort study, 队列研究# f( U1 h! R2 l5 l, O
Column, 列
; c4 ]$ u) L8 d' Z6 w* FColumn effect, 列效应
& ]4 x% Y# ^: DColumn factor, 列因素7 F( ^+ ?8 z5 T- s3 _5 ?4 @
Combination pool, 合并
: g3 |: u( Z4 Y2 iCombinative table, 组合表
3 W2 Y2 x( i1 |; dCommon factor, 共性因子: e. G' w+ M8 W5 L8 j( I
Common regression coefficient, 公共回归系数# N$ b, E3 u" a
Common value, 共同值
/ l. i- ~8 g3 P, a6 ?( t# zCommon variance, 公共方差
2 Q: y: X. o8 [* ^) e' t, i) t+ ICommon variation, 公共变异/ ~ l2 V7 _9 d0 a
Communality variance, 共性方差: S& u$ I7 W- I7 V8 v
Comparability, 可比性
" ]+ p5 O: v6 m& A" s! X f. a. [Comparison of bathes, 批比较2 a7 h: C/ |, P6 u5 I' x
Comparison value, 比较值3 i+ G3 ]: q9 _ n
Compartment model, 分部模型
; g. u. n$ y3 k( P$ B, PCompassion, 伸缩8 { W8 |( }9 X* U+ A x2 r) D
Complement of an event, 补事件
0 Y0 K( P* e$ W& pComplete association, 完全正相关
$ c2 U" r0 p7 Z: {* n4 b; YComplete dissociation, 完全不相关
7 s0 U% n6 X7 `# c% g( t1 W. jComplete statistics, 完备统计量
, C0 F: E7 e; p2 I5 _7 z( {Completely randomized design, 完全随机化设计/ [/ x4 w2 a- B4 C4 ?1 v& F
Composite event, 联合事件9 `( `" \& D$ F$ X! v* u0 |
Composite events, 复合事件: C& Q8 ^5 D! e7 R$ @
Concavity, 凹性
% F, ?3 J+ A0 K3 {; L& sConditional expectation, 条件期望+ S$ C4 ?+ M7 @/ T6 B9 g
Conditional likelihood, 条件似然
8 t) @4 i V! ] Q1 R( EConditional probability, 条件概率- w+ {0 ]5 w+ `8 ^3 r9 p$ U, h
Conditionally linear, 依条件线性, h, k% M2 x/ p, r7 m
Confidence interval, 置信区间% T3 \4 I. |2 u
Confidence limit, 置信限
( j' O. V1 M/ i; T9 {# b: A0 K! z; ]Confidence lower limit, 置信下限5 m! J4 x, Q/ D, X z
Confidence upper limit, 置信上限
' e, q. n/ u- `- w+ F! XConfirmatory Factor Analysis , 验证性因子分析7 [: x3 i+ X9 ?3 @! P" L# b+ q
Confirmatory research, 证实性实验研究/ ~+ |. C3 g$ ]' T) t
Confounding factor, 混杂因素" a+ I( n4 W! w" R% ]5 i
Conjoint, 联合分析5 [: D+ c0 v7 `* ?: A
Consistency, 相合性+ [# j, @9 j( B. F" A# o6 [
Consistency check, 一致性检验7 ?+ Z, P& g" P
Consistent asymptotically normal estimate, 相合渐近正态估计' n9 j$ L1 g3 T0 ]* ?* _# s' _$ ?
Consistent estimate, 相合估计
! h7 f( c$ F% ], x OConstrained nonlinear regression, 受约束非线性回归4 ^- p5 E% _- D
Constraint, 约束6 A& `2 o1 ?# h0 O0 b z3 f' U* s
Contaminated distribution, 污染分布
& w# x) f5 e+ m) Z$ w) |Contaminated Gausssian, 污染高斯分布
8 l! D6 d- l' n& _9 T G. ~: QContaminated normal distribution, 污染正态分布
. m \6 j( T- y2 ~- y3 h8 l4 b5 v4 MContamination, 污染$ \& D; T; a: @6 w
Contamination model, 污染模型% h9 l6 \8 R0 Q1 x; y/ W
Contingency table, 列联表+ f# [9 W8 q" K( y+ T( z$ ?
Contour, 边界线
; f2 {+ c9 P( T. R1 ?5 KContribution rate, 贡献率 y( r* o& H$ C! s- G2 ]
Control, 对照: _$ _$ d- S7 B) Q1 l+ i
Controlled experiments, 对照实验
e, u2 Q6 K1 x d" o8 w, fConventional depth, 常规深度
: B% B# ^1 a8 V1 |- X, c+ jConvolution, 卷积7 W0 t$ L7 a' R \- j+ Q2 F: g
Corrected factor, 校正因子8 h F( g$ g: {4 _+ _. p2 V
Corrected mean, 校正均值
; r! W6 T1 @1 g) s7 sCorrection coefficient, 校正系数
; X( r5 C! y: o% H5 lCorrectness, 正确性/ |$ t3 }2 K2 O4 [6 W
Correlation coefficient, 相关系数0 s4 {' D) ~1 x4 g# o0 P
Correlation index, 相关指数
2 m4 W, X- q( ?! NCorrespondence, 对应
; B9 R4 i/ @7 m0 c$ L2 `Counting, 计数
$ ]' _% q1 }. w: @# _Counts, 计数/频数3 A9 E8 T( Z- w( B
Covariance, 协方差
- D4 t& x! A/ P: ]$ T) OCovariant, 共变 3 S2 ^5 I- ^4 F+ V
Cox Regression, Cox回归- W/ n. |8 _* k2 b/ @ Z( J
Criteria for fitting, 拟合准则; X5 r. ?3 ?: b* b; j: X6 O
Criteria of least squares, 最小二乘准则9 H. j6 N& r/ o1 M: P+ F4 x
Critical ratio, 临界比: x# G8 s! t, I) a, |/ e
Critical region, 拒绝域& C/ A6 N+ J5 o$ Z
Critical value, 临界值
! @ q( n |$ x: qCross-over design, 交叉设计
7 T L3 K4 u* u% j, k6 y8 a; e% dCross-section analysis, 横断面分析8 T, ?, C2 j* f0 H4 [4 T* J
Cross-section survey, 横断面调查
6 G$ H9 t# r2 E& s+ s- F nCrosstabs , 交叉表 1 o& p# x3 e) a' U% }( F+ F& ]: \
Cross-tabulation table, 复合表
( u* N8 y% u6 o/ a& rCube root, 立方根0 d- X( D: Q0 R9 a& t7 m; y
Cumulative distribution function, 分布函数
4 Y S3 P8 h! ~# |7 y+ b XCumulative probability, 累计概率
& J% W! T) k1 |( g6 K( z; rCurvature, 曲率/弯曲. D: v( I& s! c
Curvature, 曲率
I1 F. o2 w+ Y2 j; z. QCurve fit , 曲线拟和 , \7 F2 l: M) W
Curve fitting, 曲线拟合
% t1 ~- G$ x1 S' z4 T. ^; [% H \Curvilinear regression, 曲线回归
- x( y+ \, q5 B: Q9 \Curvilinear relation, 曲线关系3 ~/ Y% r, E* o) |
Cut-and-try method, 尝试法8 ~0 W! D6 ^* l/ j- k* Z" q( f$ N6 E
Cycle, 周期
$ M0 ]6 J7 K# |7 W' ECyclist, 周期性
" j: V& }; g+ X+ y8 X- aD test, D检验. P6 g% g e U
Data acquisition, 资料收集
8 M+ T7 C" t1 d. }# G" wData bank, 数据库
5 [# O. L& Z) } N. v- N! d& gData capacity, 数据容量
+ \ q+ ` c l- ^3 t+ aData deficiencies, 数据缺乏
& n2 n1 v3 c/ X3 `, {9 bData handling, 数据处理
3 ^# N9 O8 e) _, n; Y/ FData manipulation, 数据处理. M! D# W- e8 R# |9 u+ q+ x" I
Data processing, 数据处理2 ?- n2 a3 S" p3 |# R
Data reduction, 数据缩减4 ]3 c3 Y* W4 u, ~1 l* a" M
Data set, 数据集/ y1 a& Q7 F8 a. h$ w/ d" X
Data sources, 数据来源1 s4 A6 H) J) @9 q. C# H
Data transformation, 数据变换& I: i# r; E& I! `) d: j* G
Data validity, 数据有效性( X# e) N1 N, F: F5 f
Data-in, 数据输入
4 f0 S7 ]& U% ?" |Data-out, 数据输出9 \) i& o- U9 t( i! w! O
Dead time, 停滞期! A6 o1 S# S6 {) ~* [
Degree of freedom, 自由度5 l4 S( n5 d4 u6 k
Degree of precision, 精密度
6 S! w& a( B0 jDegree of reliability, 可靠性程度
, j, i# f* ~# c l a6 j. vDegression, 递减/ _8 M5 G2 t2 k( a- L
Density function, 密度函数
$ _7 P1 d/ D0 `Density of data points, 数据点的密度) E; Y) ]! N' j( [ i# d, i
Dependent variable, 应变量/依变量/因变量$ o0 x( | f3 s9 x6 w! h
Dependent variable, 因变量& r, `5 s5 C& D/ T6 q. `& V8 Y9 @
Depth, 深度* P+ L! Z5 \* B
Derivative matrix, 导数矩阵
& N1 _( ^, r& L0 QDerivative-free methods, 无导数方法
3 a! C$ y) h1 x4 p" g" q5 n9 Y5 C; nDesign, 设计
$ A% @! @; D+ X8 XDeterminacy, 确定性6 @' r# Y+ y. N. }
Determinant, 行列式' o- a+ \: N0 Z/ ?) ?
Determinant, 决定因素
8 W y: P$ [2 SDeviation, 离差1 u$ T, v7 L+ w, e+ C
Deviation from average, 离均差
/ h/ Y8 s5 k O7 IDiagnostic plot, 诊断图. x' Y: c7 l6 d$ i- G) |, P+ {
Dichotomous variable, 二分变量4 N( C- n. P( r4 \
Differential equation, 微分方程+ i& { N# |: R7 w' a
Direct standardization, 直接标准化法) r7 `& t3 F& @/ e& v7 _7 G- |
Discrete variable, 离散型变量- S" i: k9 t8 T. p0 K* {5 I6 v
DISCRIMINANT, 判断 - |, K) n, l& r, p
Discriminant analysis, 判别分析& A6 u/ x! s E$ f- ~1 q) \
Discriminant coefficient, 判别系数* g: [7 X6 @! i1 C/ w9 R: b" s0 M
Discriminant function, 判别值
* Y$ F8 T; Y, H7 C; MDispersion, 散布/分散度! U- j: G' i/ X
Disproportional, 不成比例的
) F. l" l3 R- P8 s0 Q$ HDisproportionate sub-class numbers, 不成比例次级组含量. n+ }. D( o a/ E3 B- Y
Distribution free, 分布无关性/免分布
; G! J3 g& D% _" vDistribution shape, 分布形状
8 u; G9 {9 Y* H; CDistribution-free method, 任意分布法
+ v* R. G; h. r6 @Distributive laws, 分配律
+ F3 n f m) c$ N' ~% W- K& r' dDisturbance, 随机扰动项
4 |8 n6 M$ L7 U- B( y9 c' JDose response curve, 剂量反应曲线+ q8 V' V; O3 p: ^( I0 Y& |6 E
Double blind method, 双盲法
! ?: V, F/ z7 [- k. c; L* tDouble blind trial, 双盲试验# c6 I8 h1 b o( z, {- E U
Double exponential distribution, 双指数分布3 |- `9 J" `+ r- B! \5 e- [
Double logarithmic, 双对数( O& \* f6 o, I0 f- i7 F$ k' S$ t/ C
Downward rank, 降秩) n) H6 m) m2 F0 I' q( |5 z
Dual-space plot, 对偶空间图, b( I* d- K5 ?
DUD, 无导数方法 U6 }! z) s+ @+ O- E N
Duncan's new multiple range method, 新复极差法/Duncan新法* e, G7 N# c. |1 I$ S/ ^
Effect, 实验效应9 W1 x8 b- z6 Z2 c
Eigenvalue, 特征值$ a* |& J( j2 i' o. t5 ^
Eigenvector, 特征向量
1 A. v5 f7 f5 q I gEllipse, 椭圆
& m4 t8 @; E7 ?7 F7 BEmpirical distribution, 经验分布5 y% V* x% P7 ^( J& ?* M# B: F `
Empirical probability, 经验概率单位+ s: {1 a" V% W$ E1 ~3 [
Enumeration data, 计数资料
; z4 o: b# G, c# K, d* cEqual sun-class number, 相等次级组含量" |9 ?. z; }. M6 u, w
Equally likely, 等可能+ M: i s4 p/ ?% H5 a; s8 d
Equivariance, 同变性
- G0 a( a) { ^: D, B2 P. q) yError, 误差/错误
2 a. W5 G4 C5 l- wError of estimate, 估计误差
! S$ j' {/ x- e& A t% {Error type I, 第一类错误: e' i# A# H8 w9 E' l: O0 n0 k2 r
Error type II, 第二类错误
3 P2 a4 ]8 g0 t6 o. FEstimand, 被估量% L; h: i; L- g9 o
Estimated error mean squares, 估计误差均方
$ p4 @0 |- ]' Y, P+ @2 FEstimated error sum of squares, 估计误差平方和
. z+ [: a$ ]$ S$ xEuclidean distance, 欧式距离
# \* k! o& W+ V6 a& s8 u" uEvent, 事件
" ]5 g" A$ [7 {& x mEvent, 事件
/ p/ T1 E3 ?7 P! K( J( K) o! KExceptional data point, 异常数据点
( _, y7 W9 Y1 v4 \7 T& O" _Expectation plane, 期望平面1 u6 x8 D) k6 [& w+ u5 C3 D
Expectation surface, 期望曲面
3 T" e' ^1 v7 @# d6 v! `; |Expected values, 期望值
% Y2 @. \: H; p& x. `: q# KExperiment, 实验8 [' t, a6 ]+ J; u
Experimental sampling, 试验抽样/ V6 K. |) w ?8 D
Experimental unit, 试验单位
) p+ H n, [# p1 A. W. ?- [Explanatory variable, 说明变量
. }5 E" [: R6 O" a8 N2 @1 |! r+ _Exploratory data analysis, 探索性数据分析- t+ \; g6 `: w$ {, s+ d6 O8 N
Explore Summarize, 探索-摘要
& B0 y/ y; F. a+ J! g) T3 P) H4 F0 KExponential curve, 指数曲线* i. M9 ?6 t, Z8 c7 z
Exponential growth, 指数式增长( C( G6 d9 l! d. Z' l; G, g; W/ r
EXSMOOTH, 指数平滑方法 z1 y: E7 X1 Z: p. d1 g
Extended fit, 扩充拟合
9 Z8 h* O* ]1 _4 lExtra parameter, 附加参数4 ~5 s; _& ?2 n
Extrapolation, 外推法
3 k6 a; F, V0 ~0 C, UExtreme observation, 末端观测值" d/ i9 V m1 B/ S
Extremes, 极端值/极值$ ]' ]1 X1 R" ^8 N- t* P8 k+ a
F distribution, F分布
, n2 t+ K5 q2 A5 O) { sF test, F检验5 v" N9 G6 s( L7 c7 J4 ^
Factor, 因素/因子
% D5 _& `! g' R" g4 Z& `. tFactor analysis, 因子分析) K0 x f' d# o/ J
Factor Analysis, 因子分析
N [! Z1 s' f3 H5 \4 KFactor score, 因子得分 0 R, J4 H0 N* i+ W4 ^9 S
Factorial, 阶乘
; L$ `6 z' T. @, `0 eFactorial design, 析因试验设计+ I: H( _6 D3 ? k
False negative, 假阴性* p# P; I& Q% x; k5 s
False negative error, 假阴性错误* p' ^( o7 ^9 ]! G% c8 c
Family of distributions, 分布族
3 P& h$ z# j! X& v& |Family of estimators, 估计量族1 d0 J) h0 p* L2 @
Fanning, 扇面
. X8 a6 y/ l' y `Fatality rate, 病死率' I6 b( J9 Q- a! I& ^5 O0 L4 h
Field investigation, 现场调查6 Y2 L; z$ F5 O5 L% [$ Y
Field survey, 现场调查! J- j5 ^, X) d6 i" ]7 {
Finite population, 有限总体/ A2 b, x: a* X- A2 ^* \ V
Finite-sample, 有限样本
5 Z1 n) u3 l- x4 y7 N% DFirst derivative, 一阶导数
8 ^+ T4 g& @ E. F: H6 a, ^First principal component, 第一主成分1 h) n9 q, x6 C) H9 A
First quartile, 第一四分位数
0 }! r! f3 C& U4 K& h, n& [0 YFisher information, 费雪信息量$ c! r8 R3 X, @' i
Fitted value, 拟合值3 L3 k/ @, \, J, ~1 n- `
Fitting a curve, 曲线拟合, }' S& l$ C; _" o2 [
Fixed base, 定基
( b' J/ }7 e: }: oFluctuation, 随机起伏6 ]; K9 V2 V. ^
Forecast, 预测
4 P B/ F; N5 ` @Four fold table, 四格表
4 p4 i+ [ U4 P" k6 vFourth, 四分点! H k2 m+ `' w u0 p
Fraction blow, 左侧比率 h T+ w1 O4 i* Q" N+ a( ~) a% A$ Z
Fractional error, 相对误差
) {# ^! M8 E; \9 BFrequency, 频率 p& u+ |! R3 R& X( H1 _+ S6 h. O
Frequency polygon, 频数多边图9 [" e. v1 O. N% r0 `: }' Y
Frontier point, 界限点
! `' a" n7 c W4 c2 z! g/ nFunction relationship, 泛函关系
2 I* T: i" W$ Q$ i; WGamma distribution, 伽玛分布
. l, X+ Z; ?1 l4 JGauss increment, 高斯增量/ }! s* k6 |" J" U# H9 s$ v
Gaussian distribution, 高斯分布/正态分布
- \6 K7 X% [; [+ s& i9 i- n4 G% uGauss-Newton increment, 高斯-牛顿增量
; p& A, c) i3 E& c( N) `* p* u# SGeneral census, 全面普查7 @6 X: @" ?3 M
GENLOG (Generalized liner models), 广义线性模型 - Y) o* I( t9 D
Geometric mean, 几何平均数* P& ?4 W1 z8 X" J) @- v6 }
Gini's mean difference, 基尼均差
4 s1 Q8 w% p7 m; U# o+ FGLM (General liner models), 一般线性模型
: I; ]- L& P/ y5 f% T3 K1 OGoodness of fit, 拟和优度/配合度5 @5 a" l8 U4 k+ Z( U% o& `7 \
Gradient of determinant, 行列式的梯度
: @! d; a( H7 f& M8 tGraeco-Latin square, 希腊拉丁方
. u2 K$ }, h2 n, fGrand mean, 总均值
/ A( K( ?4 i; }) CGross errors, 重大错误
0 Y* t. z; T* R' X1 ~% d' x# \Gross-error sensitivity, 大错敏感度- @# a4 o* i0 {. O
Group averages, 分组平均; l$ U( g5 i/ h' P) T/ c, v
Grouped data, 分组资料0 L$ _7 w+ X" P1 Q: ] {! u
Guessed mean, 假定平均数3 { t& k& |* m4 S g
Half-life, 半衰期2 L# Z8 W+ I: h. \) |/ j
Hampel M-estimators, 汉佩尔M估计量
9 L; {( n; r; RHappenstance, 偶然事件 v' k" q# q0 A& N' r* r$ X8 j: j# u" R
Harmonic mean, 调和均数& }0 ], m3 V2 ]
Hazard function, 风险均数
( u6 c% k3 _( z+ T* l! Y5 f. X8 ^ GHazard rate, 风险率! p0 C/ ~! j- _+ x+ Y d6 P
Heading, 标目
$ Q* h( @) v: z: O) S' ZHeavy-tailed distribution, 重尾分布
! D% l7 I: ?, q9 Z# fHessian array, 海森立体阵$ j$ `$ B3 k s
Heterogeneity, 不同质 f) ]7 o) s; {5 I* h7 i* P/ H
Heterogeneity of variance, 方差不齐
; o+ B- h$ K) R' o4 C2 I8 ]Hierarchical classification, 组内分组3 }; J3 O: _; {0 v! ]2 z
Hierarchical clustering method, 系统聚类法
' t" u% N7 f4 A* v( o& q5 yHigh-leverage point, 高杠杆率点
) k; s9 ~9 \2 {- F, hHILOGLINEAR, 多维列联表的层次对数线性模型
% l3 |% e7 `5 R |4 u) lHinge, 折叶点
$ X; W9 V# c7 h/ h1 UHistogram, 直方图
% m& _1 X8 m: @- tHistorical cohort study, 历史性队列研究 ) Y# d. Z, f# T* \ p" @1 B/ @
Holes, 空洞
6 @- C- a) n: [" ?+ VHOMALS, 多重响应分析
. Q9 N$ S8 I$ h$ l9 }/ sHomogeneity of variance, 方差齐性4 N6 D% l/ C' f, u# n1 k
Homogeneity test, 齐性检验
+ ^" s7 b5 x2 |( Y3 KHuber M-estimators, 休伯M估计量! c! N1 P P1 V- c
Hyperbola, 双曲线 R3 i7 w3 J; g X8 C- e
Hypothesis testing, 假设检验 y9 b! |. K7 u( f& n* y
Hypothetical universe, 假设总体# k# I8 A% k: i
Impossible event, 不可能事件9 ~2 A* h/ U" w8 S
Independence, 独立性, T! J7 Z' Q4 w
Independent variable, 自变量. ^- p) g5 t: A% j/ F
Index, 指标/指数
6 P; N; F: C; j6 K9 I. hIndirect standardization, 间接标准化法
& \ |, s w9 H2 Z+ SIndividual, 个体" E/ E, M$ c! J
Inference band, 推断带 K: R$ G( Z( i0 ^
Infinite population, 无限总体
4 I9 J% X7 b6 m6 P5 T( pInfinitely great, 无穷大
1 x" D' h2 c% {6 |' OInfinitely small, 无穷小 a! D, C: J' z4 N, [5 a
Influence curve, 影响曲线
+ Y3 I# ^+ \8 WInformation capacity, 信息容量( H# k, d+ Z6 b: W
Initial condition, 初始条件
" s* Q2 ~& j2 G! f7 U" r/ ]Initial estimate, 初始估计值* ?) A# d! Z; I' V' }, k( Q3 X
Initial level, 最初水平
5 V4 O8 ^5 t$ v' a! W9 |+ xInteraction, 交互作用6 f' h2 t Y1 m& v2 \
Interaction terms, 交互作用项1 v; [) ~8 e8 v! s, }4 G0 v$ g
Intercept, 截距
- t9 V7 U n- T. W4 YInterpolation, 内插法
4 _- q& ~+ H- X1 LInterquartile range, 四分位距
) f- c7 C$ G7 GInterval estimation, 区间估计
& i. z6 u) j2 r; R) V* mIntervals of equal probability, 等概率区间 {+ _4 l$ y2 I0 V; t
Intrinsic curvature, 固有曲率2 Z) K, }# ?- }& | h- h* _9 y
Invariance, 不变性; r) A f7 j$ Z) T! s3 f M+ G7 I5 Q: ~
Inverse matrix, 逆矩阵
9 t. j/ \* w3 N+ ~5 \- o8 ?Inverse probability, 逆概率7 M# I8 W' N3 L4 [0 r) p
Inverse sine transformation, 反正弦变换8 A! a4 V$ n" j5 ~) W- H& T
Iteration, 迭代
; v- c7 A0 ?- E: f1 C T" `Jacobian determinant, 雅可比行列式$ V+ Y- z; P, W! i
Joint distribution function, 分布函数
+ v( [* B. l3 E" {6 _# gJoint probability, 联合概率
* h) S# I. t2 \" EJoint probability distribution, 联合概率分布
+ j9 r5 d/ x( B) }1 ~6 ^K means method, 逐步聚类法
# Q3 _4 p' e c, i/ l# o6 oKaplan-Meier, 评估事件的时间长度
9 O0 K* e8 w* e3 o" o9 S4 zKaplan-Merier chart, Kaplan-Merier图
0 U7 S& I7 J# @6 m) nKendall's rank correlation, Kendall等级相关9 Y) |- L; I& V
Kinetic, 动力学
0 j; @ l8 b5 z. IKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验; L z1 @+ ~+ b% u. s1 Q5 ~5 C% o% q6 |
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验. D) ~% L6 F* h% {. D) b+ n5 f& w
Kurtosis, 峰度
8 K% D! Q* E4 `$ W* HLack of fit, 失拟
' k ~* X4 o0 s" s& J# u" aLadder of powers, 幂阶梯1 ?* ~2 M& b$ J4 \+ v
Lag, 滞后2 z; h# g/ B$ y' o( u
Large sample, 大样本
" n* G% T7 u6 }! H/ [- ]Large sample test, 大样本检验
2 m7 V! h# u, K$ r4 m, u, ?9 G1 JLatin square, 拉丁方, E- f4 c! ]5 i) }8 q
Latin square design, 拉丁方设计
: u" j W0 b! P$ H2 JLeakage, 泄漏
7 C/ i( s5 |+ iLeast favorable configuration, 最不利构形; `. B. m- X+ O; F! ?( o+ E
Least favorable distribution, 最不利分布# |9 I2 \& r* V E! x/ c. M" h
Least significant difference, 最小显著差法; a3 Y" ^: ^% O- h+ D$ j
Least square method, 最小二乘法2 h" T/ w4 N% ?' u1 h, M* i
Least-absolute-residuals estimates, 最小绝对残差估计4 v. s5 _4 t1 ?0 W* p. B+ @
Least-absolute-residuals fit, 最小绝对残差拟合
! o: t. a3 l- ?% HLeast-absolute-residuals line, 最小绝对残差线
+ n. K, S2 M! c8 vLegend, 图例
# V6 k: m6 e/ C$ y+ hL-estimator, L估计量
1 E, L. P* x& `, X" K6 AL-estimator of location, 位置L估计量
8 W4 b) H: d W! X8 N+ q+ i" AL-estimator of scale, 尺度L估计量
" w6 {0 V) l+ I# _5 v8 iLevel, 水平2 P. @3 h( [1 t1 ~
Life expectance, 预期期望寿命6 |6 s+ ]3 J' G. O- H5 h, ]
Life table, 寿命表( M. j& `* f5 a$ a% N6 C
Life table method, 生命表法/ S E( c: [1 m ?! f
Light-tailed distribution, 轻尾分布
3 } V9 ^5 K. ~* { t* W: QLikelihood function, 似然函数
2 Q) n0 N1 v% t- F! C' VLikelihood ratio, 似然比3 K5 r+ ]6 D: D0 p/ v. n7 D
line graph, 线图' C, s8 n6 T$ v) P2 P- P
Linear correlation, 直线相关- w* p$ B( c t ^
Linear equation, 线性方程
8 Y9 F H1 k; H! L& J. C' s# cLinear programming, 线性规划
9 W6 j$ S" U2 ?5 t& BLinear regression, 直线回归
: v* j( i! F( a, nLinear Regression, 线性回归) a3 n! b7 Z2 B0 j; u! E: r) |$ H
Linear trend, 线性趋势
2 I/ b& f9 U) e$ h1 uLoading, 载荷 5 _& J! g: w, Z) U
Location and scale equivariance, 位置尺度同变性" I3 J) U7 W6 e5 |
Location equivariance, 位置同变性
4 _! K9 J$ ?) g1 ^7 m, cLocation invariance, 位置不变性. k: |9 u. @( {& {% C' a
Location scale family, 位置尺度族1 m9 H& v9 n8 O8 s* J# I; f# m9 g
Log rank test, 时序检验 0 c1 O" j) ?/ [. ~
Logarithmic curve, 对数曲线* u. o9 C0 `1 V5 l, i
Logarithmic normal distribution, 对数正态分布. d) n& i8 k3 L
Logarithmic scale, 对数尺度2 Y* y; `% T2 X0 Y$ p& W$ y/ {' S& z8 y( N
Logarithmic transformation, 对数变换
4 Q5 ?3 k6 e7 N) Y( l" gLogic check, 逻辑检查7 r- [, ]5 E' B- @1 J! A, U: f, m
Logistic distribution, 逻辑斯特分布/ _& u5 i$ s6 M% l6 f
Logit transformation, Logit转换
# r' @- g/ @, bLOGLINEAR, 多维列联表通用模型 " B$ C S3 [' A) R2 u
Lognormal distribution, 对数正态分布. b1 s4 w; Q6 c3 u* [- l; D; o
Lost function, 损失函数/ O0 {3 J7 q, r9 |
Low correlation, 低度相关$ Z- w; r1 ~# W; V9 M1 \
Lower limit, 下限) o1 }/ a$ a/ j, g6 a" d
Lowest-attained variance, 最小可达方差
( e9 t& z J) G7 i nLSD, 最小显著差法的简称
+ B0 }( l- g( b8 N" { H1 c. GLurking variable, 潜在变量" i9 u9 x7 X( _4 V1 ~# J
Main effect, 主效应
, u' y1 d M* C9 f% w- K uMajor heading, 主辞标目
/ G H% _3 j! _. L7 nMarginal density function, 边缘密度函数6 Y6 v* P' d* f' W8 ^$ \
Marginal probability, 边缘概率
. a' i# T0 ?, @3 ~) wMarginal probability distribution, 边缘概率分布- k+ F' N6 M7 C' f# ~7 n
Matched data, 配对资料; K7 M! j1 L, }* H+ z
Matched distribution, 匹配过分布
) [' J7 m: s/ v% g. P+ \# i3 dMatching of distribution, 分布的匹配1 e8 w3 J" w& R' r. D, D# s
Matching of transformation, 变换的匹配
- x0 J k+ a5 Z/ w. d, {% q$ }Mathematical expectation, 数学期望! ?* e3 K4 D: V+ H* r3 } t: I% w
Mathematical model, 数学模型5 |7 [( p4 i$ r. r6 Q3 m: N
Maximum L-estimator, 极大极小L 估计量
d) Z. A6 ?$ o* ~5 c$ pMaximum likelihood method, 最大似然法
1 c2 H8 g8 n9 J" _' G2 u+ MMean, 均数% n% Z# U) z% _' S( P9 l
Mean squares between groups, 组间均方
6 k' [- X( p; F& T3 YMean squares within group, 组内均方3 m( ~" ^' ], O3 w( O2 K
Means (Compare means), 均值-均值比较
1 L6 ]/ m& ~8 J: K# f ?% }1 DMedian, 中位数
B# y/ n' P( L) `3 ~: ^( ?7 PMedian effective dose, 半数效量$ `) n4 Y% `8 ~8 t+ y$ G
Median lethal dose, 半数致死量
( c3 H3 d" ?' _7 gMedian polish, 中位数平滑 D2 y) ?0 u7 V, q+ ?4 ?; W
Median test, 中位数检验
9 c5 Y. l' m* o3 y4 v, xMinimal sufficient statistic, 最小充分统计量
9 Z' `+ F+ m" ]7 GMinimum distance estimation, 最小距离估计8 d6 c8 o: P% m6 N9 d
Minimum effective dose, 最小有效量, \( a/ k& ]5 q; V. m
Minimum lethal dose, 最小致死量$ T( s1 {- @) I" ~
Minimum variance estimator, 最小方差估计量
B- a6 i' k5 m$ g& P$ `% W6 OMINITAB, 统计软件包3 }/ P2 S4 z6 F, _5 _( g
Minor heading, 宾词标目
1 F6 e0 ?! v6 O, lMissing data, 缺失值
5 \, E+ ?% | w( _& i) T. q oModel specification, 模型的确定' F9 S: |. Q3 b4 H
Modeling Statistics , 模型统计, e6 w% g3 I/ w4 G( y- q
Models for outliers, 离群值模型
! f! a4 e2 v5 k; T5 n0 H" `Modifying the model, 模型的修正
?* B: q3 E D$ a. H1 bModulus of continuity, 连续性模* m$ L2 ~9 r. J( Z% m! }; C0 o
Morbidity, 发病率 ' L" V1 X7 V' E* ^2 |- C& I
Most favorable configuration, 最有利构形2 f5 c$ [3 l2 d. d) Q/ Q0 k5 Y, m
Multidimensional Scaling (ASCAL), 多维尺度/多维标度$ W0 \& O% p( t R' Y e( F( B
Multinomial Logistic Regression , 多项逻辑斯蒂回归# ?/ J$ j% _% Z# p4 B/ ]9 t" G
Multiple comparison, 多重比较
7 Y- I* @4 k6 jMultiple correlation , 复相关
1 Q: t0 N A* `' pMultiple covariance, 多元协方差, L7 o) u( a$ @ o- r, O, L" @3 N7 V+ y
Multiple linear regression, 多元线性回归
1 b) p6 C9 I J) m: G& qMultiple response , 多重选项 O* x" S. T& Q/ G- V
Multiple solutions, 多解8 v3 J" G. X* n# P# o
Multiplication theorem, 乘法定理$ w0 \ T( r. V# C9 |2 d( T3 j
Multiresponse, 多元响应
7 H% b2 C' Q& L9 i- Y1 {# {Multi-stage sampling, 多阶段抽样
! g P1 L0 M( M' ?Multivariate T distribution, 多元T分布& g r: d# |- m. G O6 m9 _% H+ w
Mutual exclusive, 互不相容
$ \1 z6 o. @* l2 }! ]Mutual independence, 互相独立
5 c* X6 j+ f4 ^" `9 n' g( cNatural boundary, 自然边界
4 e+ A# j c8 ^5 _: r2 RNatural dead, 自然死亡* F3 ^% G) [ {/ I
Natural zero, 自然零
3 l! D. m' p) g4 hNegative correlation, 负相关 V- ~ z% v, r: G
Negative linear correlation, 负线性相关: n" Q2 }$ R5 e+ g
Negatively skewed, 负偏
: K( Y+ d/ c+ B$ YNewman-Keuls method, q检验0 _* y& L$ r0 u6 j+ S3 I
NK method, q检验
c8 V! m" l2 JNo statistical significance, 无统计意义
' D! Z3 i7 Z# H/ c, KNominal variable, 名义变量
7 H+ x) |$ {% o3 DNonconstancy of variability, 变异的非定常性. E Z1 E6 u3 ]5 Z' h: N
Nonlinear regression, 非线性相关
: V3 C' ?* ~( y u6 F' P. ~! JNonparametric statistics, 非参数统计$ T3 }3 C6 S( k5 D2 M4 g: X, o
Nonparametric test, 非参数检验( B4 Q: p) k ~1 \' U/ n* B3 H& g5 n
Nonparametric tests, 非参数检验
b* I( e# v2 U6 h0 NNormal deviate, 正态离差4 c1 C4 x+ o/ P0 N
Normal distribution, 正态分布
6 c& J" V/ e' C& Q% F4 T1 BNormal equation, 正规方程组4 l! ~, P: q7 u/ {, ?% E
Normal ranges, 正常范围6 W, s7 a) X7 D0 K5 X: v
Normal value, 正常值* V9 |5 u' K s6 y) E, n
Nuisance parameter, 多余参数/讨厌参数9 I; x" |* @# [3 F
Null hypothesis, 无效假设 ! l) Z2 {# b1 d
Numerical variable, 数值变量
( Y- R3 Z2 l2 @; {Objective function, 目标函数
9 O, u9 o4 Q& ^8 YObservation unit, 观察单位
' o$ a- g: j7 H8 \( oObserved value, 观察值$ u4 K1 L+ o. J$ b; }$ ]
One sided test, 单侧检验" X* p0 r0 g3 O
One-way analysis of variance, 单因素方差分析7 X' q0 N* p! ^$ }3 W" L
Oneway ANOVA , 单因素方差分析
+ D3 x6 { V4 H5 A- U9 `Open sequential trial, 开放型序贯设计
6 u/ H: P: k! cOptrim, 优切尾
. _) [( |1 p! m$ f9 sOptrim efficiency, 优切尾效率
" w- s p. P* _Order statistics, 顺序统计量
* R1 Q* e6 I9 x+ C4 {$ SOrdered categories, 有序分类, ?2 n: s( A0 u5 f
Ordinal logistic regression , 序数逻辑斯蒂回归
) Z _% A* U/ U1 d% rOrdinal variable, 有序变量; ]9 B) e- d7 E
Orthogonal basis, 正交基
! w7 {( Y" U5 h8 C& ~: bOrthogonal design, 正交试验设计
: ]' n. U6 P% I% JOrthogonality conditions, 正交条件
6 ~* v& |+ n& S- q! v9 vORTHOPLAN, 正交设计
1 `2 \- N' G3 e5 e( {2 sOutlier cutoffs, 离群值截断点9 j5 `5 _( v! \. V4 Z
Outliers, 极端值
2 V6 }/ e) f) _0 f1 ` H' w; COVERALS , 多组变量的非线性正规相关 6 b' k& M, u+ g
Overshoot, 迭代过度
9 M; J: _! I) |. a/ \Paired design, 配对设计
7 ?) o6 u% R6 U- c+ i6 @6 V: V2 DPaired sample, 配对样本 L3 c5 L. I8 d
Pairwise slopes, 成对斜率
3 ?) U$ B& b! B4 PParabola, 抛物线* e" E% E j Z1 I5 P9 _; B$ _
Parallel tests, 平行试验; g% N% `; R o. [- L4 ~
Parameter, 参数
3 `3 ?4 O9 z9 V/ {, bParametric statistics, 参数统计
" C1 X# k; k; A; Z& @# l1 {Parametric test, 参数检验, ?2 P% F8 m( x8 m( B* v1 j6 t
Partial correlation, 偏相关
5 J& q' s+ `8 H0 k5 S& N, kPartial regression, 偏回归; ] S( ?+ ~" x G
Partial sorting, 偏排序
. G" v( Z5 j* i- z% X# j3 KPartials residuals, 偏残差
& i5 q6 H1 P: V! i5 X. \$ e2 A6 w: xPattern, 模式
# m& d, }- {1 hPearson curves, 皮尔逊曲线
! t$ d+ a4 y# `8 L; t. [; H* SPeeling, 退层 }) m5 e( J( ]
Percent bar graph, 百分条形图
2 S( K5 [+ R" L: P( \# x7 M3 R2 O: IPercentage, 百分比
" h7 m! r4 Z9 q- \Percentile, 百分位数
o- ]4 I5 u" b, o; T/ h/ pPercentile curves, 百分位曲线
* B# X2 T) ?# J8 G$ s* L+ cPeriodicity, 周期性
7 \; k+ t0 n7 i7 q) h) P* S0 KPermutation, 排列
3 c" a& Z1 @/ O4 R9 [P-estimator, P估计量/ E# D+ W2 S/ i6 z: u
Pie graph, 饼图
8 f i! s; J: F' _6 vPitman estimator, 皮特曼估计量
2 g3 t. f0 {. e2 \# c+ @ m- bPivot, 枢轴量
( b: r( K) y* O" n* i: k! FPlanar, 平坦
1 z* s. I7 o+ a7 \: kPlanar assumption, 平面的假设
/ Z* g3 T* J& H! @' [) o1 p5 SPLANCARDS, 生成试验的计划卡
+ N4 \ n% L$ t, H6 e% Z K2 TPoint estimation, 点估计1 ^8 r5 C* D+ p- E7 G# _
Poisson distribution, 泊松分布
- ^2 j U8 [; Q- o [* cPolishing, 平滑
3 }* }1 b% k" J& G. R* }Polled standard deviation, 合并标准差4 t! E% l5 y' {: Z9 F* p% B
Polled variance, 合并方差
c5 N( k7 b8 p6 U# u1 l& s/ qPolygon, 多边图' v5 L$ v9 B+ k. b
Polynomial, 多项式; i' W1 G0 R2 y9 ~# c; ]. U" G
Polynomial curve, 多项式曲线$ N8 S$ J5 _4 B9 z7 Z
Population, 总体
% m8 i$ p/ K& H: H5 Q- UPopulation attributable risk, 人群归因危险度1 O( b7 `" [: L
Positive correlation, 正相关
5 m% D# O& |- aPositively skewed, 正偏
/ P3 F) ^# t2 n. j3 B7 }Posterior distribution, 后验分布
6 O$ v' A4 g) X2 n: @. uPower of a test, 检验效能
; w2 S: f+ H, O( C6 _% P- z; @Precision, 精密度
' ^! S& [3 Z4 d3 w; VPredicted value, 预测值+ j% G: j2 S. X4 U5 E- ^! v R9 x% s
Preliminary analysis, 预备性分析6 L1 ]. ]. R9 ^3 D0 q' Y; n
Principal component analysis, 主成分分析
6 C9 D* I$ [ V8 j9 U' h+ H. uPrior distribution, 先验分布
3 x! I9 q$ F$ T8 O$ BPrior probability, 先验概率
( Z) G* ~, i6 m6 Y) Z0 YProbabilistic model, 概率模型! d a% x4 @& J( z: x
probability, 概率
- W6 ~4 ^1 K$ E& Z* G$ h) H( gProbability density, 概率密度
# d2 `/ u$ ?6 ?. M2 Z7 ]Product moment, 乘积矩/协方差
+ ~0 q1 q- X9 Q$ r: _! y! kProfile trace, 截面迹图! _0 s" O8 C+ E: A) `3 N6 }: z" g
Proportion, 比/构成比
& x! [# L7 U, g5 C& y! ]Proportion allocation in stratified random sampling, 按比例分层随机抽样' _: l+ w; L! e! b/ e' ^- _
Proportionate, 成比例- g+ @5 S. s2 Y/ O+ v7 z) ` ?, e
Proportionate sub-class numbers, 成比例次级组含量4 e5 ^) J: a7 ?* ^# l
Prospective study, 前瞻性调查$ ~, }! ^: q1 O$ P
Proximities, 亲近性 ' I% k" {) X/ c# {0 d; Y
Pseudo F test, 近似F检验
: B+ W) j9 P# P! A% F' }. b4 UPseudo model, 近似模型- \. C8 H# L' R& J
Pseudosigma, 伪标准差+ k, k0 A" J0 P" S' R" y
Purposive sampling, 有目的抽样
) e3 e8 i0 F' ? h+ k! `+ [QR decomposition, QR分解
, F! U& n8 O0 q; v5 hQuadratic approximation, 二次近似
3 U8 `4 ~! I% B4 Z, C2 Q# ?1 e) P' e7 V: `Qualitative classification, 属性分类6 ^; C( f5 |' U
Qualitative method, 定性方法
5 h- }8 z0 r6 u( j4 q5 }9 D! o! N% k/ wQuantile-quantile plot, 分位数-分位数图/Q-Q图
3 p8 @: i$ v( w) W/ V& OQuantitative analysis, 定量分析0 _7 f' m, F0 n+ k# `' j- t
Quartile, 四分位数 K4 M0 a* q1 |: Z8 G6 Q' n. M
Quick Cluster, 快速聚类
" j! Z2 g. |" E3 u% q% w% T. ERadix sort, 基数排序: H6 d$ y+ q _, ?: k! ^6 ^* {
Random allocation, 随机化分组
% l2 v: c; O6 f" K" J; [5 NRandom blocks design, 随机区组设计
/ ]+ U9 ]7 `& }4 o( pRandom event, 随机事件3 B6 b: ?0 [/ P6 O. b" a
Randomization, 随机化. m- v: |9 a8 J
Range, 极差/全距7 |5 e& s9 t( k; W" D, f( g& S5 D
Rank correlation, 等级相关
' x- }8 ?% [* Z# SRank sum test, 秩和检验
4 {2 ]8 r; x' Q* s( O9 iRank test, 秩检验
# J+ ^4 ?3 l. i' sRanked data, 等级资料! G$ A. M3 a: a9 ]! }. p
Rate, 比率
. I3 t2 Q) ^; ~2 L y" fRatio, 比例! d6 M, J; g" t# l
Raw data, 原始资料
8 O' r8 X4 S3 }" o' b& [# `- gRaw residual, 原始残差' {% O8 I! G1 ^6 }9 M% {5 y8 h1 w
Rayleigh's test, 雷氏检验$ G# w8 M# o$ A, K+ g$ s# G
Rayleigh's Z, 雷氏Z值
6 \. X; u/ N: c: D# kReciprocal, 倒数7 ]- \/ W& y# j; h7 b5 g
Reciprocal transformation, 倒数变换
; e9 J9 `* }/ N, {% SRecording, 记录9 V$ Y6 T H+ O# A+ M. ]
Redescending estimators, 回降估计量
% Z! }. q; a; z: TReducing dimensions, 降维/ z0 l. e1 a+ H2 _* y& r# A
Re-expression, 重新表达
% K4 R9 r+ [7 H) |) e& P: dReference set, 标准组; v, S' Q1 ?1 W/ T; r
Region of acceptance, 接受域) q; g4 l) M/ J* H
Regression coefficient, 回归系数
$ k H) m- L/ a0 Y R7 HRegression sum of square, 回归平方和
; Y+ {) H* z! ]; {Rejection point, 拒绝点
{8 V* M/ c: }% C# H3 MRelative dispersion, 相对离散度
8 J% Q, r5 n( A B) i: RRelative number, 相对数0 J; X3 z. X" e
Reliability, 可靠性
/ K5 ~# n7 f) S! D* R! l$ nReparametrization, 重新设置参数
% x" z; c* K6 @Replication, 重复$ `6 G x' }& D+ W u' w
Report Summaries, 报告摘要
% l' ~/ h( g0 f+ c# GResidual sum of square, 剩余平方和9 O% i1 O1 x" l5 U9 @+ D7 w
Resistance, 耐抗性: b8 a0 A1 R* O0 }0 W7 ?0 ?* W2 C
Resistant line, 耐抗线
/ S6 ~* m5 ` T; c. V G7 \. g, wResistant technique, 耐抗技术* L$ G. K2 R3 f
R-estimator of location, 位置R估计量' S# i3 V1 S* J* u
R-estimator of scale, 尺度R估计量
j! F5 E( L& u4 @! O7 b% b; _Retrospective study, 回顾性调查
+ E3 a6 K4 o+ H8 D* o: y1 S6 zRidge trace, 岭迹
- }1 ^; F+ }6 \6 CRidit analysis, Ridit分析! D. S7 u- @/ i& U
Rotation, 旋转
. U9 Y' P" Y% }; x) l0 aRounding, 舍入* X$ Q2 c- n3 {) [& Z$ @# s) Z$ A$ P
Row, 行
7 [2 p1 o6 @* H1 I# q3 ~5 HRow effects, 行效应4 [" \0 s0 ?& }6 |9 m4 H9 V0 T0 S
Row factor, 行因素: }/ B; B2 U$ W5 o+ V& e( g
RXC table, RXC表
4 e; P) [8 z4 X+ e, s6 }Sample, 样本* M4 O0 ^2 v6 c H q. C
Sample regression coefficient, 样本回归系数
+ ^* K2 J" x; N, T% lSample size, 样本量' ~7 x, D# Y/ b3 O4 @7 H" l
Sample standard deviation, 样本标准差
2 r+ R( u) I, i! I3 M% k" l- vSampling error, 抽样误差
+ m* a) P3 K/ wSAS(Statistical analysis system ), SAS统计软件包
, c8 y' H* b( lScale, 尺度/量表
0 ~4 k w! I) O) c2 _Scatter diagram, 散点图6 T/ ^7 k7 c6 t! g. V( u
Schematic plot, 示意图/简图) |' K# _+ }2 e: @
Score test, 计分检验7 f8 f; i/ p* w) s* S
Screening, 筛检: {! k, l+ S, s) G3 W
SEASON, 季节分析
& T' \% Q. D5 r' s1 \" XSecond derivative, 二阶导数
2 r; ]* e% V* U! \! G% V6 YSecond principal component, 第二主成分& k* R5 s' |, s; X
SEM (Structural equation modeling), 结构化方程模型 3 C1 a( F# Y9 ]" E8 {6 {
Semi-logarithmic graph, 半对数图" v0 U8 K& \ j% |5 A+ o
Semi-logarithmic paper, 半对数格纸
: T' v1 e3 p4 l5 H a8 E* V ?Sensitivity curve, 敏感度曲线
0 q+ V* ]4 y( u4 B, A* k6 PSequential analysis, 贯序分析
8 _/ f/ V0 j4 l- P a. MSequential data set, 顺序数据集) |7 m7 _! S7 @- d+ Q
Sequential design, 贯序设计' C# j, [- ~8 b8 ~8 Y, t
Sequential method, 贯序法% h2 u, s( q: K" U# g
Sequential test, 贯序检验法
( |0 h0 E4 ^2 s* ]2 @& A$ N6 iSerial tests, 系列试验
7 Q+ n( Z& E e1 KShort-cut method, 简捷法
/ u, o+ L* j5 q! {: O7 qSigmoid curve, S形曲线/ h* l6 w8 T, f7 E7 f# V- _6 d
Sign function, 正负号函数1 W( O8 u* r0 v' n' j2 U
Sign test, 符号检验
$ q& e+ B5 i' I1 f4 g& a# P, ISigned rank, 符号秩
% r5 Y! X- }: W- x* ?8 P' o* W) ASignificance test, 显著性检验+ Q0 s4 e1 r. I4 x/ r# i/ ] V
Significant figure, 有效数字
9 s- [+ @( @% Q5 a- gSimple cluster sampling, 简单整群抽样2 {8 g* a# E" \ p- ?8 X9 n+ o
Simple correlation, 简单相关
6 n( U% w, V: r$ p4 ^ BSimple random sampling, 简单随机抽样
9 s0 F; x1 j- n* Y! ASimple regression, 简单回归* |$ B4 ~$ R8 |% \
simple table, 简单表" s# `5 f/ p! ?+ X3 r
Sine estimator, 正弦估计量+ b5 L6 r* ], W; t8 H
Single-valued estimate, 单值估计; z0 f; O4 [0 n" ]7 M+ S: R$ a5 E
Singular matrix, 奇异矩阵9 b3 z% \- W# k" s0 O, G
Skewed distribution, 偏斜分布
3 V" F2 O& B+ p! U8 hSkewness, 偏度
+ `# D6 }8 _0 G; x$ u: P4 Y# `+ |Slash distribution, 斜线分布5 V/ Y) y1 Z$ F) \
Slope, 斜率
- k Q% i( A* q6 n5 dSmirnov test, 斯米尔诺夫检验8 R/ U% d" c5 c- }) C, V4 i
Source of variation, 变异来源
5 R* g! w& _$ p6 ^9 dSpearman rank correlation, 斯皮尔曼等级相关
; F M. _ W+ B5 D1 |Specific factor, 特殊因子
# @( W7 C: u! c, B- i' GSpecific factor variance, 特殊因子方差
; J0 h% \& c. D2 d; B, MSpectra , 频谱+ e/ Y Q# M* Q& c( p3 F1 p; K4 v
Spherical distribution, 球型正态分布; l- A* G0 @& h1 V6 w& M
Spread, 展布
: W1 u# N+ @- J6 [, oSPSS(Statistical package for the social science), SPSS统计软件包, n+ w. g3 t3 I5 B+ ^. ~
Spurious correlation, 假性相关
( H1 Z$ u# p! Z% lSquare root transformation, 平方根变换
& o( v1 W- Z) j9 K$ XStabilizing variance, 稳定方差8 Q% s. Q2 L; s a8 C& s
Standard deviation, 标准差- j1 }: A) E" r9 U, V8 s/ g
Standard error, 标准误9 n+ @+ Y6 P' v2 F
Standard error of difference, 差别的标准误
& U. d7 A( F0 VStandard error of estimate, 标准估计误差
# p1 }8 r& f/ k2 U/ }- OStandard error of rate, 率的标准误
( P, O/ ?; i+ [8 p4 xStandard normal distribution, 标准正态分布% w+ B% j, e8 N9 c
Standardization, 标准化
3 ~! P8 ~, i( A) E VStarting value, 起始值0 Y, \$ G4 n2 o$ y
Statistic, 统计量
9 E6 @0 K- x4 Y Z8 mStatistical control, 统计控制- d+ ?0 p# P6 G: S1 k
Statistical graph, 统计图
1 E# ^5 n8 a. A6 [' k* fStatistical inference, 统计推断
6 _' k l* j, s9 W' ^& UStatistical table, 统计表
* C5 a$ U1 p/ T: n: JSteepest descent, 最速下降法- E! g8 `/ o4 b+ L
Stem and leaf display, 茎叶图7 N: U/ I0 v/ d5 i) @$ E6 ~; J" O* u
Step factor, 步长因子
3 J S2 M4 Z. J* B3 aStepwise regression, 逐步回归7 Z% Z$ A1 Q* F
Storage, 存, B& ?( P4 i- f
Strata, 层（复数）; p9 @+ K& }) S( S" k7 r4 s
Stratified sampling, 分层抽样
. e: S$ l2 d& E) {) m& {. UStratified sampling, 分层抽样, V, u8 V. e# C: H
Strength, 强度
, |6 e \4 d3 j+ k2 x, S# pStringency, 严密性
7 ?4 O- v. m" c8 j, m: Q6 ~Structural relationship, 结构关系
; c2 e% k' `; @8 J. OStudentized residual, 学生化残差/t化残差
: F5 k* G2 t: k& [: v, [ q. mSub-class numbers, 次级组含量
* j8 e& r' B. @$ z4 [, D# u" LSubdividing, 分割
0 r; K, V s# W r5 ~2 J6 [* FSufficient statistic, 充分统计量
7 n' E- G; |9 i& T* f. mSum of products, 积和
2 U% [7 H) P; L/ k5 u. m" T4 OSum of squares, 离差平方和
: `0 M$ M) q( B! b( h! XSum of squares about regression, 回归平方和% {% x6 c0 T4 k4 \1 Q: @/ R
Sum of squares between groups, 组间平方和
. ^3 I7 D+ w, Z8 SSum of squares of partial regression, 偏回归平方和
; J2 j* a: H. FSure event, 必然事件3 y, w8 z/ S; \5 U% s3 K
Survey, 调查
- W. I$ ]/ t' } v" v6 ?Survival, 生存分析 ]+ s0 U" v* V) o
Survival rate, 生存率
5 J5 x: x; q+ T5 F D0 B. M& PSuspended root gram, 悬吊根图
6 ]; m3 I" o3 h6 [8 w' eSymmetry, 对称
0 O" B: E2 ~" c# D* pSystematic error, 系统误差$ P$ Q0 Z2 A1 u& B1 Z3 p" z5 O: F
Systematic sampling, 系统抽样2 C& B- Q3 ?6 j
Tags, 标签
# }! D, P+ L! S9 L, A6 ]Tail area, 尾部面积
) S# G& E7 I: i) r8 D$ T& @& [Tail length, 尾长. G0 V' z' u8 ]& \+ X7 y* U
Tail weight, 尾重
; @6 `2 A! ?( i, K+ nTangent line, 切线! ?) L% h1 L6 ?! C. u
Target distribution, 目标分布$ }: z- y, [ X* h
Taylor series, 泰勒级数/ d E+ M3 O$ Y2 F
Tendency of dispersion, 离散趋势
# g% ^5 b8 d# g, {- S6 fTesting of hypotheses, 假设检验
; \, u1 P. d8 W( f) OTheoretical frequency, 理论频数
" k7 N* t4 _3 A, D( S/ F. w+ \Time series, 时间序列, k. V9 g' H$ x' `& u; }
Tolerance interval, 容忍区间; q% d8 `' C; Q' o$ Z( c$ X
Tolerance lower limit, 容忍下限( r" n5 j7 |* i, k, A9 s ?
Tolerance upper limit, 容忍上限
( N9 {9 K; r3 Y- d( ITorsion, 扰率' W# l$ C* G. X0 E
Total sum of square, 总平方和
) I0 V; J. C s0 [, iTotal variation, 总变异
0 h; u( p$ I- q7 D% `* cTransformation, 转换+ \: c; O* P. q/ W
Treatment, 处理
9 z& V0 s) B' O3 W( V1 D& kTrend, 趋势
4 Q0 d7 E# c8 L" V8 O: y4 @+ OTrend of percentage, 百分比趋势
9 S1 V# z0 x4 K% y* wTrial, 试验
9 \) M/ T! }) d& L- Y' r, OTrial and error method, 试错法! Z% Z! P7 w3 R0 c, v
Tuning constant, 细调常数- L) c5 S1 H% x3 V0 f
Two sided test, 双向检验; U7 Z: @8 g" M4 O0 U( v" B" Z
Two-stage least squares, 二阶最小平方
3 D# o! Q$ B, \' R% bTwo-stage sampling, 二阶段抽样
; F+ h+ U. [9 VTwo-tailed test, 双侧检验
2 K' B. |& V0 ~! S) A- c$ GTwo-way analysis of variance, 双因素方差分析) O6 i- }; I. p# G' v$ H0 P
Two-way table, 双向表
' L1 f# l0 D! I, c8 a- e+ NType I error, 一类错误/α错误 l, O; D# y+ g' Y$ l9 p
Type II error, 二类错误/β错误" C0 F: B6 |, C+ U1 g5 `
UMVU, 方差一致最小无偏估计简称1 q& u1 t: ]- I5 L$ L" g' e
Unbiased estimate, 无偏估计
9 m# N5 S1 g( u0 Z% dUnconstrained nonlinear regression , 无约束非线性回归
. j& y- A9 V% j. m7 }0 H4 J2 [Unequal subclass number, 不等次级组含量
2 t2 {$ F$ N1 x' R6 J/ s6 Q% aUngrouped data, 不分组资料
+ ^0 P3 u9 C7 HUniform coordinate, 均匀坐标
7 P2 I9 V6 c: O2 b+ jUniform distribution, 均匀分布
1 n% P, \+ `" j8 p8 xUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
3 F% a, m" w- \ uUnit, 单元
l- S' ~, r5 m% P" T! [ Z8 EUnordered categories, 无序分类3 g! c9 I3 f" H/ v& i
Upper limit, 上限: P4 H7 Y+ h3 V* C9 G2 D
Upward rank, 升秩
" C. J% X5 f! E7 OVague concept, 模糊概念
7 e' {- r. E. i% U6 XValidity, 有效性
5 K2 c5 k( {, r2 p/ ]VARCOMP (Variance component estimation), 方差元素估计% [9 y+ l8 S6 |# I. a* V) y
Variability, 变异性
r; k' L/ t" `: f, V; k, Q. zVariable, 变量2 V) L9 K- ]; V. `1 r7 u! c* q
Variance, 方差
5 a! H3 `( \, g/ m+ w* n- u( jVariation, 变异
- O6 f6 x& {6 U# P$ e( ^( ?+ }Varimax orthogonal rotation, 方差最大正交旋转
; I' [2 q9 T7 X' V, [Volume of distribution, 容积4 ^2 L7 S) X5 X H
W test, W检验' f1 l5 U8 V5 D: f% H
Weibull distribution, 威布尔分布
1 ?- n4 {+ _3 c% z+ uWeight, 权数
2 i8 y W: G4 g7 A7 a$ S' g2 rWeighted Chi-square test, 加权卡方检验/Cochran检验2 S0 y1 R* i0 Z% y
Weighted linear regression method, 加权直线回归, w; w. t0 _1 ]1 Y6 u7 M
Weighted mean, 加权平均数, l7 [: p8 M; r$ ~( n$ ] n7 g
Weighted mean square, 加权平均方差9 P' |8 m% s% p3 e7 J
Weighted sum of square, 加权平方和
, j1 x# r; x8 P4 X2 ]Weighting coefficient, 权重系数3 K u' G0 v& {) K
Weighting method, 加权法 7 y) {% X& @) l% n8 F
W-estimation, W估计量$ `% { n4 X/ W( C" B" q
W-estimation of location, 位置W估计量) C5 w2 Y' i( X6 N7 M7 F; G! L
Width, 宽度
9 S5 r1 `. ?' z* _# M6 T6 p: U5 HWilcoxon paired test, 威斯康星配对法/配对符号秩和检验! L' X1 s7 q2 Z* ?' W x+ E8 R
Wild point, 野点/狂点/ t* e# W* I: p/ m$ v# K1 ^& T# n
Wild value, 野值/狂值
! M0 y: y w0 R! qWinsorized mean, 缩尾均值
. n! \! f6 g3 p: ^0 U v V, aWithdraw, 失访
& O0 i' Q. A2 A3 Q6 |, p0 B8 `* e) o' EYouden's index, 尤登指数
( i* I: n) E3 k) C! I4 z! U% @5 VZ test, Z检验) ^5 f2 e% _& g/ c. _ T
Zero correlation, 零相关; s5 p Q. a7 c& g7 y' k
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
