|
|
Absolute deviation, 绝对离差
) j0 a) J2 o8 CAbsolute number, 绝对数2 ~7 N% b) ^1 R* U4 S
Absolute residuals, 绝对残差
( B; C6 Q7 P0 B, u$ x. t; }Acceleration array, 加速度立体阵
6 d! I. P; {! O RAcceleration in an arbitrary direction, 任意方向上的加速度
1 r# K* R8 I1 u6 ~1 QAcceleration normal, 法向加速度
& P4 p* r9 s) S) m8 R8 e- ~" cAcceleration space dimension, 加速度空间的维数
* W! R2 _" k+ Y1 H. {' {( F: ]$ AAcceleration tangential, 切向加速度, L( R, m5 K9 `$ o+ w
Acceleration vector, 加速度向量
4 l, L' F2 i! g" l9 dAcceptable hypothesis, 可接受假设* a! o) {! E E
Accumulation, 累积
1 x4 _( A6 ]' s! [0 x# k( ^Accuracy, 准确度
- y0 k: g9 N& c( r( NActual frequency, 实际频数6 {; T/ d$ n/ L4 b3 W& f
Adaptive estimator, 自适应估计量2 O: Y- F2 K1 x& ^
Addition, 相加
. ?; j# x% n3 t- C# TAddition theorem, 加法定理* U, A6 ?# t) A3 H& f
Additivity, 可加性+ n9 ?0 s; f# c' Q' O$ N, ~) _: Y
Adjusted rate, 调整率: z* m* D1 |4 o+ m6 R" X
Adjusted value, 校正值* L$ W* q @2 m* F& r4 i5 u3 T
Admissible error, 容许误差/ N: w1 R3 a" Q4 [
Aggregation, 聚集性
6 O4 ~% @+ }9 ~Alternative hypothesis, 备择假设
- n- @) q; Y+ z6 H% aAmong groups, 组间) O: B, C& c- M2 f
Amounts, 总量
. j+ G8 ^# W: ^- O5 X* MAnalysis of correlation, 相关分析
- R5 e0 t, A7 g, f$ ?: r. ^Analysis of covariance, 协方差分析, M1 o' n1 m4 t2 x6 N2 Q1 H0 ?, c
Analysis of regression, 回归分析3 j9 Q7 N6 c" q# S' p
Analysis of time series, 时间序列分析( Y! ~/ S- x0 [+ b' X9 @
Analysis of variance, 方差分析; E1 t. G0 m3 n/ ]6 g
Angular transformation, 角转换
+ b2 J2 W3 C9 W+ G4 [ANOVA （analysis of variance）, 方差分析
D# `* f# N1 s( Y+ ^% p' D" \! ?ANOVA Models, 方差分析模型% k3 Z d! b7 Y" C3 U; x b6 v) J
Arcing, 弧/弧旋
- f" z; j. u/ a# ^* `5 W9 j+ IArcsine transformation, 反正弦变换9 S; e" C9 \/ k% ^$ g
Area under the curve, 曲线面积% c0 ^$ n% U6 T* }- V
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
9 C1 u, [( V% G: oARIMA, 季节和非季节性单变量模型的极大似然估计 0 K* U! w+ v( _
Arithmetic grid paper, 算术格纸
! C) }8 D) ~: {2 q4 h" M, y6 fArithmetic mean, 算术平均数
2 W/ ?% j- n, i1 G$ p4 B) MArrhenius relation, 艾恩尼斯关系
' C$ L& o# e5 w c! M6 wAssessing fit, 拟合的评估7 c+ A/ A6 h2 G3 y- A
Associative laws, 结合律3 R* i5 w# R. d+ p% D7 C
Asymmetric distribution, 非对称分布$ I0 s& k$ n% B, S* H
Asymptotic bias, 渐近偏倚2 d, B4 u4 ~" a! p6 j
Asymptotic efficiency, 渐近效率
* e2 L3 c6 l5 G: e0 a& Y+ o- D9 KAsymptotic variance, 渐近方差
; T+ }! x m1 c2 ^. P% jAttributable risk, 归因危险度
+ c! V; f4 X( GAttribute data, 属性资料: u6 K5 e# C* L/ ?% n2 e9 f
Attribution, 属性; |) S) T( u+ T- Y* j2 H
Autocorrelation, 自相关
9 {) ~( M; Y" Q' X8 y' j& mAutocorrelation of residuals, 残差的自相关
$ |+ {4 @- F; jAverage, 平均数
+ u: p6 u! h* }Average confidence interval length, 平均置信区间长度
: E$ P- \; j3 E' ]7 JAverage growth rate, 平均增长率
$ [; Q1 w2 J, q1 E5 ?Bar chart, 条形图
( }2 F( H) i+ @# c8 j' U; {$ P5 nBar graph, 条形图
1 w- E/ t( ^. J4 w4 d. v( k* k! U4 {Base period, 基期' }9 ]" h* n+ f/ M, C
Bayes' theorem , Bayes定理" A( S% B8 f9 x/ J( \
Bell-shaped curve, 钟形曲线2 ?; d: J! x6 f% g, _6 j
Bernoulli distribution, 伯努力分布1 K+ O: v6 |# A' s! A: u, W4 u, g
Best-trim estimator, 最好切尾估计量
2 D# o z: C, L( oBias, 偏性$ w2 j8 I% f% w: m: W& C7 }& X
Binary logistic regression, 二元逻辑斯蒂回归
% I6 Z& f) {% P7 M! F2 ~; [Binomial distribution, 二项分布$ j; {0 J% g. q8 B. Z# ~
Bisquare, 双平方
0 s; N8 W% f* p( P5 fBivariate Correlate, 二变量相关
; g6 R2 _( K+ k v3 u7 iBivariate normal distribution, 双变量正态分布
! {' [/ o: k$ ^( Z" iBivariate normal population, 双变量正态总体
' R; ^6 O9 |# s" F2 u' sBiweight interval, 双权区间
3 W( _5 m1 v# Z% H! x o+ m) eBiweight M-estimator, 双权M估计量8 x8 }7 G, A0 v2 L4 M8 f
Block, 区组/配伍组9 `3 d. ?7 U# K+ e. _
BMDP(Biomedical computer programs), BMDP统计软件包
e+ z1 P9 ^$ T* HBoxplots, 箱线图/箱尾图
; g+ [7 M, Q: F5 L0 rBreakdown bound, 崩溃界/崩溃点) |0 ?0 z' n1 J+ S0 i5 u) b: L$ D
Canonical correlation, 典型相关4 z; C1 ~9 Q* ^' [( ^+ i. s
Caption, 纵标目
: B0 ~( l6 C( H1 V- l$ [Case-control study, 病例对照研究
S. K& ~% L3 E; ~) ECategorical variable, 分类变量
3 y5 q/ Z# A) k5 O; J! vCatenary, 悬链线
3 E: h. Q0 X/ C9 d3 b" oCauchy distribution, 柯西分布- A0 [: e; W- E$ U/ J$ b% A
Cause-and-effect relationship, 因果关系3 V* Y! A# T9 e0 p6 y. ~
Cell, 单元1 v- }( X+ y8 _: D) o/ h
Censoring, 终检, L+ B4 O3 f$ y
Center of symmetry, 对称中心8 _ i' p# `. f
Centering and scaling, 中心化和定标! w- r' X8 K) `1 s6 e2 p
Central tendency, 集中趋势0 \& R P% |1 j
Central value, 中心值# J: w6 H t2 o7 D0 e& h
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测! J& {! e* w; |' z9 h, u' e
Chance, 机遇( u! N; Q, a" }1 c5 ?5 d- _3 M& X# Z
Chance error, 随机误差
: l3 E6 p8 y- e) w( m7 s: ~Chance variable, 随机变量# P, @$ E! r8 X( U7 c
Characteristic equation, 特征方程/ | @6 J4 N2 b; ?8 I
Characteristic root, 特征根
* Z; J# K! F% {# ^; E- lCharacteristic vector, 特征向量
" b, B; |+ w9 \Chebshev criterion of fit, 拟合的切比雪夫准则 p2 ?9 g8 x- `5 q& l
Chernoff faces, 切尔诺夫脸谱图
$ A3 d7 @3 Y; jChi-square test, 卡方检验/χ2检验
: E4 b& }- o! d6 C, s1 J2 D, o, LCholeskey decomposition, 乔洛斯基分解# [" Z5 F" I+ Y3 m0 `
Circle chart, 圆图 ! _& w, d) F) I
Class interval, 组距
% a, `: q( n9 L" f5 e) V. VClass mid-value, 组中值
, d' u r5 B; |3 g% mClass upper limit, 组上限
/ b( Y$ v' x. q0 qClassified variable, 分类变量
& `& Z8 _4 i6 j' x, f( X5 qCluster analysis, 聚类分析5 [/ K+ G' P% _4 [3 d' T% a
Cluster sampling, 整群抽样
0 T. R4 n5 x0 @7 q# d# z5 X* ^Code, 代码
2 L& \0 ~8 Q0 Y+ XCoded data, 编码数据
/ n6 U2 q; y3 S- ^4 z: t* RCoding, 编码1 t- e) }3 o: A/ p+ o# D& m1 g3 l) c
Coefficient of contingency, 列联系数
- X2 Z( {: C2 c* m% }Coefficient of determination, 决定系数
" C: `4 C0 |* ]* cCoefficient of multiple correlation, 多重相关系数/ E6 b0 ?$ G& d$ v; p5 f: p
Coefficient of partial correlation, 偏相关系数
$ `0 @4 o; d$ q1 b8 G) YCoefficient of production-moment correlation, 积差相关系数* }) V( M0 l0 s8 h: S) L0 c
Coefficient of rank correlation, 等级相关系数
, M- w/ i& D rCoefficient of regression, 回归系数. @0 c* U/ `- D1 T5 C3 q
Coefficient of skewness, 偏度系数
* ^* {! M" c# E6 g# m4 q; j7 UCoefficient of variation, 变异系数
7 i& E. ^* ?& S2 _$ [7 Q% k% ^1 SCohort study, 队列研究6 r. g$ ?$ ^# Z8 n
Column, 列% h& L, J- s- m! t0 B) A. a
Column effect, 列效应! c5 ?7 k+ f2 |* x5 ?& ^
Column factor, 列因素. A4 D6 c. K! X: N7 }+ c* b3 h
Combination pool, 合并
~: }! `7 E! f3 LCombinative table, 组合表 X. L5 e* x& `9 c# T
Common factor, 共性因子
; g% J% z! O. [. }, PCommon regression coefficient, 公共回归系数. g0 c1 q6 U% \% s; j8 U- e( R
Common value, 共同值# [4 H, @( B1 o/ ~. ]
Common variance, 公共方差( j6 P: C, {- V. \' C% E7 a
Common variation, 公共变异3 l& u9 ~4 ^5 `
Communality variance, 共性方差
6 k/ }" |& D: O( AComparability, 可比性
- h. z8 F) R8 Z3 v$ {. r) h: ~Comparison of bathes, 批比较% y' A( Z/ w- F
Comparison value, 比较值
9 r5 q/ _" X( ^+ m, x( S4 ECompartment model, 分部模型4 O2 y& C- D- U! f6 [6 u+ g% x
Compassion, 伸缩
3 i$ U2 g# p ZComplement of an event, 补事件
4 e! F# _' }9 j4 f/ f4 l0 gComplete association, 完全正相关
; _" s- v, a7 t* p# ^; m' ]+ X; |Complete dissociation, 完全不相关
( T- ~6 U) e0 {, L1 [5 N& nComplete statistics, 完备统计量
9 \9 N" S5 t5 VCompletely randomized design, 完全随机化设计
( Q0 c( ]) T& @& i1 f9 N) gComposite event, 联合事件2 N* A) \. k- T: u7 R; W
Composite events, 复合事件2 h! h+ d7 X' I) i* ~
Concavity, 凹性
8 B5 U# x) g- U; w I* lConditional expectation, 条件期望( B E2 u* A: ?
Conditional likelihood, 条件似然
) y. d2 i0 X8 B, m( P5 o$ _Conditional probability, 条件概率
9 e8 R* @0 T3 I; p1 sConditionally linear, 依条件线性2 _6 w6 l. c8 w: o
Confidence interval, 置信区间
4 l, W7 c3 |. l6 J7 F) MConfidence limit, 置信限
e1 j7 B) P: Y. T9 N+ h% \Confidence lower limit, 置信下限) y/ B' |9 f/ }3 O1 R/ W) n
Confidence upper limit, 置信上限
. P8 _, o- ?+ ?5 }4 }Confirmatory Factor Analysis , 验证性因子分析
B( |; R) s( l& j6 d0 s0 RConfirmatory research, 证实性实验研究
! t& q' q+ ~0 L4 o7 O; [9 DConfounding factor, 混杂因素
+ g- J) ?; V7 p0 @& {( k7 MConjoint, 联合分析
_7 ]9 i' l: IConsistency, 相合性7 b% Y* I9 i: E# l9 \$ [
Consistency check, 一致性检验/ i( R" H4 \- ~# X1 L
Consistent asymptotically normal estimate, 相合渐近正态估计; m6 K# A' |" C
Consistent estimate, 相合估计9 I3 t( f2 I) ~' ]; J
Constrained nonlinear regression, 受约束非线性回归
+ r$ V2 E4 U* P& pConstraint, 约束2 J& N3 c3 p: N3 w) v% t5 l
Contaminated distribution, 污染分布2 |& ]# ?5 `* U! G( k! \
Contaminated Gausssian, 污染高斯分布7 k" R' ]9 \2 a
Contaminated normal distribution, 污染正态分布
Z4 e% |' G& `' t* w! C# eContamination, 污染
' i% f8 a" o9 Z! V1 s5 Q* S6 D* bContamination model, 污染模型& m! S% w) L; Z2 y) w
Contingency table, 列联表+ a! Z' R' m8 I7 k
Contour, 边界线9 x" c* P/ }! x" ~/ ]
Contribution rate, 贡献率 E% d& D' \3 H
Control, 对照
% L0 ?* _3 a9 OControlled experiments, 对照实验
- J% w" c1 h0 m4 b5 h" X4 R. vConventional depth, 常规深度: b8 l; C* \5 Z) X: [" q" r- L0 y- Q
Convolution, 卷积: W" J) h k! U f8 _3 B$ {2 K+ G
Corrected factor, 校正因子- u) `* O5 J6 u n3 ^
Corrected mean, 校正均值, L3 A# e: G# E3 ]+ H; ]9 Z
Correction coefficient, 校正系数
7 I8 D; I7 J3 N6 K$ L2 pCorrectness, 正确性$ ]& l/ [) p& V& t# y
Correlation coefficient, 相关系数
8 G3 X" G3 M& `- ^5 YCorrelation index, 相关指数3 y( k$ o) |# Q4 z
Correspondence, 对应
3 m1 ]7 f9 k8 Y# q5 fCounting, 计数
9 B# K* u9 c; x pCounts, 计数/频数- X. }: Q4 \9 Q9 M9 I5 Y7 ^
Covariance, 协方差
/ P- p8 ~3 {; @7 E( k6 ICovariant, 共变
) D3 u& W( }. A/ N$ X/ Z$ m4 DCox Regression, Cox回归
0 i* x+ S' _* ~: k8 X3 M9 V+ nCriteria for fitting, 拟合准则
9 D$ m% V/ I6 }" b: kCriteria of least squares, 最小二乘准则
$ x; A! ], j" E$ R; _0 {# s) t' A! }Critical ratio, 临界比3 ]4 Q8 v& l' ?, }8 y- N- s% L
Critical region, 拒绝域
' [; ?% O; g {. m6 |6 ~Critical value, 临界值
, ?. r" D/ H" @) m ~Cross-over design, 交叉设计. l6 J. K2 W) ?* V
Cross-section analysis, 横断面分析" _1 [7 O9 G. ?2 K- c8 C
Cross-section survey, 横断面调查6 |' N) Y% L) L, I
Crosstabs , 交叉表 ! p* O" v3 t) y- B2 ~ L
Cross-tabulation table, 复合表
; B, O- A+ B. Y9 K0 H# ]Cube root, 立方根
, J$ s9 b: Y5 j; bCumulative distribution function, 分布函数
7 D3 |8 x- K \' v2 \ ^Cumulative probability, 累计概率
- t3 J T: q/ o, HCurvature, 曲率/弯曲
- a( `: n$ ~( P6 ^+ ^7 UCurvature, 曲率
1 O; o7 e' }& @( yCurve fit , 曲线拟和
; H' ~; w# y, ?" p. h. }Curve fitting, 曲线拟合
) Z% r/ P" R6 p# D) G2 hCurvilinear regression, 曲线回归; i' ]/ @4 S- X: d( `2 P$ E
Curvilinear relation, 曲线关系* d* q+ I/ \* c& k$ [
Cut-and-try method, 尝试法5 A! w, ]6 g6 X; q+ {8 ?
Cycle, 周期
$ X. ^4 D' {0 jCyclist, 周期性5 |8 R$ n% H k6 ]
D test, D检验2 y# R- c( Z& ^' B! z
Data acquisition, 资料收集6 M/ q" Y' o6 ]
Data bank, 数据库/ Q8 C* g7 v4 Z2 V6 c8 \( Q) w
Data capacity, 数据容量0 a) G- T1 O. W
Data deficiencies, 数据缺乏- \0 F+ c. v; j$ B, D
Data handling, 数据处理8 Y0 R+ J* y2 f
Data manipulation, 数据处理
+ d& L9 U- D) E0 I& LData processing, 数据处理
1 F9 g1 T+ G9 V# ?9 N: T& nData reduction, 数据缩减2 P4 L2 X9 V* B L' u$ }
Data set, 数据集7 p! G) H! r( H2 s
Data sources, 数据来源3 H3 e+ i2 z# T5 e0 y
Data transformation, 数据变换% b0 `; K% J. @
Data validity, 数据有效性
& A& u @7 L/ E hData-in, 数据输入
8 z- L- O, Z. _( XData-out, 数据输出 w7 x$ E8 n6 V9 j, H
Dead time, 停滞期
; }9 g( {) w. x: ~Degree of freedom, 自由度" {1 H' J* U: r- W V1 f2 o% M3 Q
Degree of precision, 精密度* V! i, b1 d3 N: G9 s
Degree of reliability, 可靠性程度
. c9 R2 H, J, }& mDegression, 递减
. G$ ^* N7 @* E- {Density function, 密度函数% D3 a" _2 M: N. t6 d. q% d
Density of data points, 数据点的密度: v: |; k5 F/ U
Dependent variable, 应变量/依变量/因变量% k0 x2 S* }; A- A+ J
Dependent variable, 因变量% c1 e2 M6 l& m
Depth, 深度1 ]0 F! j9 \* b5 V$ Q& A
Derivative matrix, 导数矩阵$ I4 p/ y- \/ ]% [
Derivative-free methods, 无导数方法
9 Y3 `) y/ B3 M# n4 vDesign, 设计& J% T9 N. a9 ]$ N, j* H- U
Determinacy, 确定性
5 \9 u5 @+ @& s+ a `0 g9 SDeterminant, 行列式
% K4 R3 o2 S3 [# E3 jDeterminant, 决定因素( V3 _$ H: F0 K, V7 [
Deviation, 离差% S2 [4 C6 Q" V. P" F5 Z" {) J' _4 [
Deviation from average, 离均差. c T- _: Z5 v) j [6 D U
Diagnostic plot, 诊断图
0 A8 J3 ]$ c9 [/ I, mDichotomous variable, 二分变量+ A- v) v+ O2 x' I( S! p5 E* \
Differential equation, 微分方程3 M6 K. G1 Y+ {$ Q2 V' l8 z
Direct standardization, 直接标准化法
8 r4 Z, K: N1 \7 UDiscrete variable, 离散型变量! G, ~* d. e* {% |8 v
DISCRIMINANT, 判断
3 }" B/ L/ k6 `. N. d- t9 gDiscriminant analysis, 判别分析
/ N+ q( h: Y( n2 A! l! ^Discriminant coefficient, 判别系数
- F; P/ Q! n! X4 ~2 S+ jDiscriminant function, 判别值( I4 F7 l( r3 t
Dispersion, 散布/分散度& b0 L/ ~& [5 t! V8 Q
Disproportional, 不成比例的2 R% m0 G' V3 Y+ I# L7 ^7 f
Disproportionate sub-class numbers, 不成比例次级组含量4 Z% j6 l' y! l* H) e
Distribution free, 分布无关性/免分布
* V9 E2 E: t4 E" ^: v5 Z4 E2 ]Distribution shape, 分布形状& c; u% g4 s' r0 G
Distribution-free method, 任意分布法0 l, l# n2 e7 Z- z, O0 c
Distributive laws, 分配律
- C0 a9 h5 j/ m1 E& l* ZDisturbance, 随机扰动项
+ ]0 {% G8 p, }$ m! V0 BDose response curve, 剂量反应曲线
% @0 H) b) @4 T1 e3 HDouble blind method, 双盲法
- X, {" L: i1 d5 nDouble blind trial, 双盲试验
( u! J# \" p2 M( N% u0 n$ B5 }Double exponential distribution, 双指数分布6 k* J2 j9 l; |6 ~% V
Double logarithmic, 双对数" \( |2 D7 t# ~( W6 @' C1 l
Downward rank, 降秩
0 _; }9 p/ s$ @6 m! k+ o. ~; g3 x [; DDual-space plot, 对偶空间图% C9 I3 ?! b: G- t$ i Z
DUD, 无导数方法6 B- [% y. H6 M' j$ E4 p6 r+ E( A
Duncan's new multiple range method, 新复极差法/Duncan新法6 L' ~2 n8 Y, n# q2 W, }. u, ]
Effect, 实验效应
( f5 B j. T" U* x" f( ^7 R, @' U/ C- MEigenvalue, 特征值
m, z* p) R$ MEigenvector, 特征向量* M$ P5 K$ U4 a4 \$ e6 a# J! h
Ellipse, 椭圆
: M& U* M$ i/ d3 h: `6 B- {+ [Empirical distribution, 经验分布
3 e. {' i7 `) q7 |6 B9 qEmpirical probability, 经验概率单位, M: s" S7 q/ |
Enumeration data, 计数资料
- f9 t5 R' z% N( \3 }" U& L6 bEqual sun-class number, 相等次级组含量; W$ t& P$ R' g& B1 j! v9 D
Equally likely, 等可能* g( A; g. Z. H! m( z* D8 @# E
Equivariance, 同变性
0 y# w, H& B; v P+ B4 @% _8 h( SError, 误差/错误
; i b; m- u! c$ j3 F: ^Error of estimate, 估计误差- \5 S* O2 V; z5 t
Error type I, 第一类错误
. W$ ?* j5 ^# J& dError type II, 第二类错误
5 g' N' T* N! \" H4 ]& ]- N h! ZEstimand, 被估量* G4 _% d6 Q% X0 |& n# Z
Estimated error mean squares, 估计误差均方
/ k% ^+ {8 O- {& U8 ~, I4 E0 XEstimated error sum of squares, 估计误差平方和
5 E& ~ ^& x# e0 O) \# X3 L$ OEuclidean distance, 欧式距离
# ~' J6 j. Z( H, ~5 C# ~( ^8 uEvent, 事件
# G) l+ f* L: r: f$ I- u, jEvent, 事件4 H0 _. D; j. c& l) b; a
Exceptional data point, 异常数据点
' g* d0 c' `1 Q. s* EExpectation plane, 期望平面
n* g O. R7 b& ]" cExpectation surface, 期望曲面
4 I1 O3 r; `! U; C- q8 @* ~* UExpected values, 期望值0 z2 R4 Q; d4 p+ x
Experiment, 实验1 [) a% y& ~& e# f; V# F$ |" a
Experimental sampling, 试验抽样
5 \* k6 w$ W3 g' i3 r) BExperimental unit, 试验单位
* g0 s' D; b( [2 ^Explanatory variable, 说明变量
' R* }( r& D' n4 Y4 F9 WExploratory data analysis, 探索性数据分析0 P! l! p8 Y+ M) ?1 J$ I/ }0 X1 I
Explore Summarize, 探索-摘要: ~2 ]. q4 K. C7 A) Z, p% J
Exponential curve, 指数曲线' B, v- R$ ]) r$ J6 G
Exponential growth, 指数式增长' S1 _* }3 k" v0 A( O
EXSMOOTH, 指数平滑方法 . Y# @% L* Y& f. J. a2 C
Extended fit, 扩充拟合- P9 G2 c/ A+ [+ H* M
Extra parameter, 附加参数/ r& P5 t( Q& a' F" r
Extrapolation, 外推法7 ?; u) S( ?6 \* {. c) C
Extreme observation, 末端观测值$ \4 p, E6 j' s& Y& P
Extremes, 极端值/极值
+ ` Q8 f+ _7 WF distribution, F分布8 D! o) }) a! `+ z; T3 K3 P
F test, F检验3 s# [( Y4 t% U9 Q
Factor, 因素/因子
4 T, P& z" H; s& \$ rFactor analysis, 因子分析
" k' m5 M6 y: xFactor Analysis, 因子分析6 _1 F1 Q. `5 G4 v6 Y5 ^$ Y
Factor score, 因子得分
' ]. w0 B. y6 kFactorial, 阶乘
; D9 d) X$ Z7 L* m5 }4 EFactorial design, 析因试验设计4 S# _% G: [' z
False negative, 假阴性- d/ i# i2 Z0 r+ q$ X5 ]3 Y0 I
False negative error, 假阴性错误
2 r* H" C" J. z d( B& n b rFamily of distributions, 分布族# A6 e+ g1 h; w- e1 J
Family of estimators, 估计量族
% Q9 R- Y) r) s7 |' @Fanning, 扇面
, g, Z0 G' y$ Q+ a4 kFatality rate, 病死率
9 P, W) o/ F9 r aField investigation, 现场调查
3 s$ y. Z1 e5 Y/ ~" I8 `# iField survey, 现场调查
6 o4 z# j' g. c5 |9 q1 h6 n6 nFinite population, 有限总体
6 v. f5 i4 _6 m3 I! c* M" e' r1 VFinite-sample, 有限样本" w2 V- C3 h3 F# V" b
First derivative, 一阶导数
+ O j6 S) l2 ?+ B! ^7 J5 ^9 nFirst principal component, 第一主成分# \# P( i- @/ o0 C* t5 l
First quartile, 第一四分位数
, g( U7 N8 s6 |! G; u( i" lFisher information, 费雪信息量/ |1 U5 x! T! k* K
Fitted value, 拟合值
, v ^+ ^/ g( T3 M& g+ @3 V9 uFitting a curve, 曲线拟合) F3 R% w% K$ ]- i f. B4 J: k
Fixed base, 定基
0 k# _) J7 I4 ]Fluctuation, 随机起伏
$ A P# N7 A4 M1 y: M+ ]2 {& I. GForecast, 预测
8 a0 x; ?' E4 E; T& z: P$ NFour fold table, 四格表6 q2 u4 {3 C% P. _, \$ w- a
Fourth, 四分点8 \% ?9 Q; s3 W C0 c/ A8 F G
Fraction blow, 左侧比率
8 D h2 r1 _& e8 m$ v; JFractional error, 相对误差. X5 \. M! ] L4 L: z+ C' X
Frequency, 频率( G) `2 z# I- m9 s4 \
Frequency polygon, 频数多边图% C# A! d& M: q( {; F
Frontier point, 界限点9 z' C0 y2 R1 V& c7 m7 D
Function relationship, 泛函关系
8 y6 i" |& A! G7 [Gamma distribution, 伽玛分布5 ^% [8 ^" ~3 h# z1 R/ T
Gauss increment, 高斯增量* `% O6 S# C7 n( I
Gaussian distribution, 高斯分布/正态分布
1 L# R% G' D# E. u7 kGauss-Newton increment, 高斯-牛顿增量
/ n1 e) |% V) h1 rGeneral census, 全面普查+ ^2 _* F/ R% s7 L# N
GENLOG (Generalized liner models), 广义线性模型
6 ?2 X7 V4 }* U& Y' ` @4 GGeometric mean, 几何平均数
' {* [% H% I: ]$ D# b9 kGini's mean difference, 基尼均差
, B# P5 u% R% S' H+ J' \) G# UGLM (General liner models), 一般线性模型
6 {# d* i3 c' LGoodness of fit, 拟和优度/配合度/ b3 _ w5 E# x5 u
Gradient of determinant, 行列式的梯度& b( g6 y) u1 ?+ I, `3 n. n0 ?
Graeco-Latin square, 希腊拉丁方
. w+ J! m# ~9 e' b" ]Grand mean, 总均值
& g, r9 |4 c1 B2 D% gGross errors, 重大错误1 }% s5 |$ ]- E* m# [7 p: S
Gross-error sensitivity, 大错敏感度
9 X) f- E# D# _" e# k* b# {% I/ M8 P/ WGroup averages, 分组平均2 H- d" d" j6 r0 [" J1 ]! c
Grouped data, 分组资料! T" H4 M1 w! D0 z5 v. l4 \
Guessed mean, 假定平均数4 A# w+ w' r5 }9 M9 a9 L! t3 G: s2 t% }
Half-life, 半衰期5 \( ?. N: B5 ^6 X+ S m, a0 C
Hampel M-estimators, 汉佩尔M估计量
+ I* o) D) W& A# T& U9 A# mHappenstance, 偶然事件+ p# |' J( ~+ }- N" J+ I
Harmonic mean, 调和均数! W8 \" }, Z' x. q4 }7 G1 J
Hazard function, 风险均数" e, w2 o2 z! ]( R8 {: Q
Hazard rate, 风险率! w' S& Z& X. U" j1 L3 G' `; V# D
Heading, 标目 2 K9 F b8 d9 @
Heavy-tailed distribution, 重尾分布0 l0 l+ k2 }' E) ?1 [
Hessian array, 海森立体阵. A! _" v5 i7 g7 b: X h' Y
Heterogeneity, 不同质3 F* b: d6 B3 n: ~ @0 f2 P
Heterogeneity of variance, 方差不齐
0 H! M0 T3 i2 Z- c; I" X5 T+ mHierarchical classification, 组内分组
+ v" q; A4 s4 r7 |, n; U* [! uHierarchical clustering method, 系统聚类法
' U. e/ V9 Y3 j2 Z& B3 [+ {8 V8 ~0 V' OHigh-leverage point, 高杠杆率点
9 @* k8 ^' x1 X" j3 v0 S2 L* D# f: JHILOGLINEAR, 多维列联表的层次对数线性模型
# p0 ?1 K4 h0 M9 Q1 g& K0 CHinge, 折叶点5 |$ e- ~! g' B
Histogram, 直方图
. p/ [7 H" C5 P8 ~Historical cohort study, 历史性队列研究
7 x1 M( j, N( r% I+ o; iHoles, 空洞4 _8 _2 ^9 T2 C8 X5 b
HOMALS, 多重响应分析
; ` S; a4 E$ Q2 P% T% R$ g/ WHomogeneity of variance, 方差齐性
8 J3 `+ ^( [3 S$ I" \Homogeneity test, 齐性检验
2 w! K. J( k* @' e; t w: AHuber M-estimators, 休伯M估计量
- C. {9 w( ^! f0 z0 S8 J; c8 x2 eHyperbola, 双曲线# d; B0 v; m+ T+ H5 f: g0 P* f
Hypothesis testing, 假设检验3 S' {# z: M: U2 k* E
Hypothetical universe, 假设总体
$ [- W7 ?% R8 L6 |8 O4 H' kImpossible event, 不可能事件
/ b- ]+ ^! O8 T5 U! J- C3 tIndependence, 独立性" z5 k# G; `/ U
Independent variable, 自变量2 c& K3 c. A" a; G! G" i9 M
Index, 指标/指数
0 F0 r* H. U+ I# nIndirect standardization, 间接标准化法
1 S1 E1 j8 _/ k: MIndividual, 个体' F% M T* k4 m% i+ \; n
Inference band, 推断带
: L8 z* n* @( I% YInfinite population, 无限总体
3 D# O( h/ g+ y9 h* tInfinitely great, 无穷大2 Z* m: V$ v7 h. Q/ H+ R* F4 M
Infinitely small, 无穷小
; o( v) A/ Q8 ~Influence curve, 影响曲线2 S9 ]' c" ~4 b6 ?5 p5 H
Information capacity, 信息容量, k) z6 e) X. Z9 a* Y/ C
Initial condition, 初始条件
2 ~* N' @* a8 Z; @0 Z! k/ }2 z9 M2 XInitial estimate, 初始估计值: R! e/ I$ ~" f3 s# W8 E( J6 E
Initial level, 最初水平2 ]# I7 @2 {6 V+ L
Interaction, 交互作用7 ~, Q' P3 X( z. ^9 \2 P: {5 P& \ ~
Interaction terms, 交互作用项- I& u# a1 m" S }" w5 P, s7 Y! Y
Intercept, 截距
# O; q: E9 ?- s/ y CInterpolation, 内插法
2 N- C" @0 s, sInterquartile range, 四分位距3 I' A. k: ` q _3 n
Interval estimation, 区间估计. o5 j z& p* P
Intervals of equal probability, 等概率区间# v" g( o4 ^& A% P* r$ E% y: i4 v% t
Intrinsic curvature, 固有曲率9 B% O1 z; ~- {
Invariance, 不变性* }) f! b S3 B* n* F$ X: s0 _5 e
Inverse matrix, 逆矩阵) C9 r% h {8 }' u& Z
Inverse probability, 逆概率
+ T i: V, G' {; V. h8 LInverse sine transformation, 反正弦变换
* k6 T% P% y- GIteration, 迭代 # x- [9 B/ g+ l, P& @3 z7 N; d
Jacobian determinant, 雅可比行列式
$ F+ r6 [1 \2 g+ mJoint distribution function, 分布函数3 p2 z* O# M6 U( {) v
Joint probability, 联合概率) l# P" n$ q! b8 H, _2 e
Joint probability distribution, 联合概率分布 T9 R2 j' ~5 T6 e5 i6 @7 J2 J) m
K means method, 逐步聚类法/ \1 K! q. |$ c
Kaplan-Meier, 评估事件的时间长度
* b3 D! d+ c% H7 bKaplan-Merier chart, Kaplan-Merier图3 q7 n4 ^7 d T" G+ R0 J6 \2 P' `# T7 D
Kendall's rank correlation, Kendall等级相关
8 G' R+ \" V* H+ yKinetic, 动力学
2 b/ h% z: ]! ]& L0 n5 BKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验( O3 B4 }/ Z( Y) i% l( n+ \
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验7 A) u( [" ]0 c4 Y/ A3 M2 j
Kurtosis, 峰度! D$ o8 j$ i4 l
Lack of fit, 失拟: N9 v' P; m: B9 K$ B% I, ]
Ladder of powers, 幂阶梯
8 u" t" Q& R. O" ^$ ]% dLag, 滞后- ]8 H4 e7 x2 ~! r8 l) G/ P ?
Large sample, 大样本- ?* C& v# Z4 R5 T. x: y* z" ~
Large sample test, 大样本检验
( _2 `/ v* z2 Y t \8 {Latin square, 拉丁方
+ H# v1 r4 A* a, b% W9 M7 G, uLatin square design, 拉丁方设计
5 p& r5 j8 {% C- a: I5 n- R3 ?5 aLeakage, 泄漏
/ l5 H1 ~3 E$ }Least favorable configuration, 最不利构形
F, L5 ]+ o3 U$ RLeast favorable distribution, 最不利分布+ ~& r7 r3 D+ `5 v2 z- [
Least significant difference, 最小显著差法- d# D$ E+ h! O; t/ _* P# }! k
Least square method, 最小二乘法. m% J: C, S8 p( G
Least-absolute-residuals estimates, 最小绝对残差估计
3 Z/ l% `# {! m) ZLeast-absolute-residuals fit, 最小绝对残差拟合
$ g& G# [6 p6 d, W& Z; A0 iLeast-absolute-residuals line, 最小绝对残差线
. Z: k3 J, \. o- W; NLegend, 图例
1 j& R9 Q- W/ M7 E" r2 yL-estimator, L估计量
/ P6 n( b, ]+ B) ]3 nL-estimator of location, 位置L估计量7 T& l# w+ C( E
L-estimator of scale, 尺度L估计量
& l1 \5 @* d' Q# A8 ]! LLevel, 水平% Q% H0 T4 R' [, \1 [; g
Life expectance, 预期期望寿命
- Q; v [/ X& K$ S; u* k" K% aLife table, 寿命表
4 \2 @! m2 y/ eLife table method, 生命表法
9 y% \4 B' A: G" J4 QLight-tailed distribution, 轻尾分布
0 n3 i9 [( d/ ~ q" J% D+ `0 _Likelihood function, 似然函数7 w) K- F4 I3 Z3 Z: }/ H) k* i8 t
Likelihood ratio, 似然比7 ]0 M& X+ F* }. W- t. z# k o: g
line graph, 线图
6 b% |% q7 Y1 o' LLinear correlation, 直线相关
) R5 Z& O' ]2 z: ~/ O" A$ YLinear equation, 线性方程; M% j% W& T( F
Linear programming, 线性规划; U% ]: u) x& G _$ T
Linear regression, 直线回归8 W+ z3 g: l3 ^ p
Linear Regression, 线性回归
+ ~- ?2 O* l& c9 q* XLinear trend, 线性趋势' K5 ~/ [) R. j. e+ ^: }! M
Loading, 载荷
" v' i: [% a# K0 i1 RLocation and scale equivariance, 位置尺度同变性: H# R. c7 ^; o: |+ u
Location equivariance, 位置同变性/ u U4 n( E4 D9 O2 U% r
Location invariance, 位置不变性" @& @; B, f2 o* j* b9 R3 b9 r
Location scale family, 位置尺度族- |- v* b" R& ^0 J3 Y+ U0 N) ~3 z0 {1 l
Log rank test, 时序检验 % p5 Z& ]1 |! x/ P( A
Logarithmic curve, 对数曲线
- H9 Y0 i! i6 ? m+ uLogarithmic normal distribution, 对数正态分布* B- E- M) g4 c- L W
Logarithmic scale, 对数尺度# T$ P5 G1 @- l1 e
Logarithmic transformation, 对数变换' J7 U6 ]+ S4 c% _: ~
Logic check, 逻辑检查8 q) m) @0 N: A9 R/ R9 } ^
Logistic distribution, 逻辑斯特分布* i& `# i9 X3 f4 K/ w! x( D( t. V
Logit transformation, Logit转换
4 d. d+ P9 _% N2 c+ g, ILOGLINEAR, 多维列联表通用模型
' U! B3 w$ s# C3 o0 W& ~Lognormal distribution, 对数正态分布
7 G+ Z5 [; ?7 b& Y& ?# _: v) OLost function, 损失函数0 g% I" ], g: I/ I# S1 r% ~
Low correlation, 低度相关5 q; h4 }# `2 i& n1 j
Lower limit, 下限8 F! V0 g% H, @
Lowest-attained variance, 最小可达方差$ V1 `3 Y' T" _9 d2 e; f' R4 q
LSD, 最小显著差法的简称
. {/ M7 L) E$ T. ~Lurking variable, 潜在变量
! ^9 ^1 g' i4 ^. n8 w9 YMain effect, 主效应
; o) X0 J) V$ h, @% H1 N$ EMajor heading, 主辞标目
7 _$ Z7 U7 Y9 m3 w# UMarginal density function, 边缘密度函数
# a7 `' b6 j0 H* cMarginal probability, 边缘概率
9 U: q' p! X& d& RMarginal probability distribution, 边缘概率分布 H: x; S; N( }6 [6 Z1 Y
Matched data, 配对资料9 r& _$ Y; o5 H/ @# c+ j( W
Matched distribution, 匹配过分布! E7 t+ W2 U9 @, L- n `( P& u
Matching of distribution, 分布的匹配( s: R8 @8 p* V) l8 m
Matching of transformation, 变换的匹配) [7 k' F, d% b( {7 o- a
Mathematical expectation, 数学期望1 @/ M7 V4 R- x& M4 }& p3 D2 E
Mathematical model, 数学模型
+ C) U- {+ {) X' hMaximum L-estimator, 极大极小L 估计量# {1 k( ]# K5 e* J( u8 v
Maximum likelihood method, 最大似然法
6 |" n! x. F* C. fMean, 均数, \. k' N! Z8 Z
Mean squares between groups, 组间均方: Z: P7 \( ?2 D! k+ R P
Mean squares within group, 组内均方$ w! d9 w+ r1 o# i
Means (Compare means), 均值-均值比较; i+ _; \4 H( w$ ~# G7 Y; K
Median, 中位数
- ^- g4 [, A2 _ y4 y IMedian effective dose, 半数效量7 j2 I$ O4 N8 s1 @! }& x
Median lethal dose, 半数致死量% p( r+ B& b$ Q* z& _: @" r3 {0 D
Median polish, 中位数平滑
* e- Y- Z& n6 oMedian test, 中位数检验( L4 [; s0 k0 N/ }- M8 Q- w
Minimal sufficient statistic, 最小充分统计量! p. x- w% ?8 k; L* k# F# u5 A" W$ J
Minimum distance estimation, 最小距离估计
$ s$ {: ~: o- ^, bMinimum effective dose, 最小有效量, L5 e6 g4 k& ?+ i
Minimum lethal dose, 最小致死量0 B4 _' ~! o3 `5 b6 n) ]
Minimum variance estimator, 最小方差估计量
1 Q+ E3 Q3 [0 |: E6 \MINITAB, 统计软件包
! v: i/ k+ w( c, o2 g4 WMinor heading, 宾词标目
8 }! ]4 {" Q6 A% q: XMissing data, 缺失值; b& j( s& G0 X
Model specification, 模型的确定3 W# U* y$ p+ Z w
Modeling Statistics , 模型统计
$ ~, X: a8 e* z! ?/ h1 bModels for outliers, 离群值模型. c) X- I3 k& f( t3 o
Modifying the model, 模型的修正. u& O, \" g6 f* j$ K+ j" d6 _+ H
Modulus of continuity, 连续性模5 b$ ^% b. C4 V5 w. P# _; W( B
Morbidity, 发病率
9 J* @* t" ~6 I' M4 ~Most favorable configuration, 最有利构形. k# H5 O2 G: h" u6 x2 y" W
Multidimensional Scaling (ASCAL), 多维尺度/多维标度+ w! v9 B/ S( r3 X: r
Multinomial Logistic Regression , 多项逻辑斯蒂回归0 T. Z, f! v$ G1 F. [" v8 n8 [
Multiple comparison, 多重比较
7 @* X" E3 s8 W( e: O( tMultiple correlation , 复相关
5 @: G O9 y7 P% V: _) WMultiple covariance, 多元协方差) \9 d- B) `: a
Multiple linear regression, 多元线性回归7 {! a0 B( |# w" U9 V# D
Multiple response , 多重选项
0 w2 X- ^& X f" q; I& gMultiple solutions, 多解
: `5 A% L Z9 e hMultiplication theorem, 乘法定理
- M2 ?1 H; z# c2 L" OMultiresponse, 多元响应* d6 `7 C: W7 s, s P& k! |
Multi-stage sampling, 多阶段抽样* r" ?) e1 }5 k$ J+ v8 [5 i0 p
Multivariate T distribution, 多元T分布
6 u# p0 j8 @) s% y' H/ i7 Y' TMutual exclusive, 互不相容
) |8 c1 q# j) g8 qMutual independence, 互相独立
; ?) h" h$ Y, l6 z3 \Natural boundary, 自然边界# W0 `5 ]9 g9 L" W# e0 {6 Y
Natural dead, 自然死亡
3 {4 K. V1 M( v( _0 ^7 yNatural zero, 自然零+ ^/ \, N- h e& @+ v
Negative correlation, 负相关
. G% i4 }* G O) l" g* }! }Negative linear correlation, 负线性相关
6 R) `+ Z) @- G7 w8 W+ ~Negatively skewed, 负偏
% P1 r" }- `* o! ?$ C" Q9 \; bNewman-Keuls method, q检验
4 G4 U' j+ G6 M% _! dNK method, q检验
l; j( O6 U' KNo statistical significance, 无统计意义
6 x. f/ h2 h+ @! H- a3 B0 dNominal variable, 名义变量: b) D9 G9 \6 v7 A
Nonconstancy of variability, 变异的非定常性
: r8 o. e* n; t9 BNonlinear regression, 非线性相关
+ s1 w g5 k/ q d/ L8 G3 q+ hNonparametric statistics, 非参数统计" F- X: d( ]1 ^2 E0 o& ~& ?! ?1 V) v
Nonparametric test, 非参数检验! I% {. a7 G& i a. i
Nonparametric tests, 非参数检验
2 S0 h$ M& X, M: j% H0 O) p( HNormal deviate, 正态离差( S6 x. L, _' j) l X
Normal distribution, 正态分布$ M# b0 v3 i& \9 |1 y) e8 L8 L2 ?
Normal equation, 正规方程组
8 [2 _7 S6 R) C. h6 N3 l, CNormal ranges, 正常范围& i) n0 @1 L# @) H: D
Normal value, 正常值
: q* ~0 x( I" t. B3 X+ uNuisance parameter, 多余参数/讨厌参数; S' ]4 J* ^- k7 V! V3 d4 N
Null hypothesis, 无效假设
( q1 V0 G1 ^+ ?' MNumerical variable, 数值变量
2 a( p. v' Y/ H+ z. sObjective function, 目标函数
$ d$ @2 {+ v" c3 NObservation unit, 观察单位- h, M; T, S% Y4 A
Observed value, 观察值
9 a3 ?0 o% x1 n6 r yOne sided test, 单侧检验 b3 w1 m1 M' O. e7 w- [
One-way analysis of variance, 单因素方差分析
) C5 K2 L6 ]( ~5 \) R" ]+ HOneway ANOVA , 单因素方差分析
' L' Q6 L, J# c. D6 ~4 bOpen sequential trial, 开放型序贯设计' D+ |; d ]1 l5 w v
Optrim, 优切尾
# k! f2 j1 r5 C4 Z& zOptrim efficiency, 优切尾效率
+ @; L- L7 \7 }Order statistics, 顺序统计量. a# W; ?% U& @! X
Ordered categories, 有序分类
9 Z5 J; i4 v* p2 d& kOrdinal logistic regression , 序数逻辑斯蒂回归. {) F& h9 \ M+ ^( O* e Z4 }
Ordinal variable, 有序变量
7 }! G/ h* ^9 ~/ gOrthogonal basis, 正交基# c* _- A8 a7 q3 F% P; ~3 W
Orthogonal design, 正交试验设计5 X, u( f; w2 O7 i0 d
Orthogonality conditions, 正交条件6 m* J$ V) Y& c( m$ a9 S! j2 m
ORTHOPLAN, 正交设计
" u/ l* A3 |& x4 [2 g! [Outlier cutoffs, 离群值截断点
" G. o# M' j/ C" lOutliers, 极端值) S$ D* R7 g( t# H% \# `
OVERALS , 多组变量的非线性正规相关
4 c; `, Y" P. `8 m8 _Overshoot, 迭代过度
( w* R% v$ |- L2 L$ S; C) {. LPaired design, 配对设计 ]( y( t1 M+ w% v( F
Paired sample, 配对样本
' N \' B2 {4 u$ zPairwise slopes, 成对斜率) r) t- W& a# O: t
Parabola, 抛物线
" K7 C; h7 V: J, S. r' V; |3 CParallel tests, 平行试验
m3 t4 G+ _! t3 D, d# jParameter, 参数+ J# d1 B9 x0 G7 _$ r( a; d
Parametric statistics, 参数统计
/ x; _% J5 h. m7 @* h KParametric test, 参数检验
0 _4 {( ]3 ^, lPartial correlation, 偏相关
& R4 x4 Z$ t' y) R q, fPartial regression, 偏回归
: U9 n! v: O0 F" ~Partial sorting, 偏排序! n2 p7 U3 C2 Q, d
Partials residuals, 偏残差
; U- @ ~4 L6 i: l9 uPattern, 模式
9 n4 n) p( W0 w1 X+ Q* d/ s$ ?! [Pearson curves, 皮尔逊曲线1 D( ?2 ^" A6 k' n e
Peeling, 退层
& K5 |7 Z! {7 g" R; Z% L5 l' yPercent bar graph, 百分条形图7 G0 D1 v* D3 R' q/ \
Percentage, 百分比% q# w9 |# U. m! N: B' Y
Percentile, 百分位数 `0 K3 y0 x q* `: C. k
Percentile curves, 百分位曲线
/ R( {2 C; R5 I x! y8 {; [4 _Periodicity, 周期性
5 u" L: C! P: ^+ JPermutation, 排列3 r c( m+ n6 R- ]! Z
P-estimator, P估计量
J9 n: G/ R1 Y" t/ b; H4 z6 z! BPie graph, 饼图
% [1 T9 X. z4 n9 i' r4 q( U% ]$ tPitman estimator, 皮特曼估计量3 ~" N$ w0 e% g; g
Pivot, 枢轴量2 W9 ]- Y* ?9 [0 |' G
Planar, 平坦
% ?! h; y7 g. ^4 G& sPlanar assumption, 平面的假设8 `1 P- Y( L4 v: X6 H4 K
PLANCARDS, 生成试验的计划卡. x" s. w- p3 C& X. D |; G
Point estimation, 点估计3 r+ B) z1 Y! a5 g
Poisson distribution, 泊松分布
6 J- F; p$ ?. Z, o/ f8 X3 SPolishing, 平滑# M/ S$ E. C U$ `4 N, a; x5 D
Polled standard deviation, 合并标准差9 |$ j3 i2 o3 M9 k4 V8 Z
Polled variance, 合并方差# O9 H* b( T0 Z
Polygon, 多边图
. z/ K6 Z/ H7 _3 G" jPolynomial, 多项式
8 ?4 z- z; H3 |/ O; G- v7 PPolynomial curve, 多项式曲线
- h( A: L" g2 MPopulation, 总体
0 N. U* l' n8 {% j1 ZPopulation attributable risk, 人群归因危险度
: H+ D% J, r+ PPositive correlation, 正相关9 J3 l9 g) y5 l* L0 i7 ]: s
Positively skewed, 正偏6 ]; \. p) C" S) y# Y
Posterior distribution, 后验分布
% ]+ F& |6 x/ M ]8 I6 IPower of a test, 检验效能
# X2 Y6 f9 t4 Y f3 Z& q' y8 cPrecision, 精密度# a u7 r3 ~2 q' ]2 M
Predicted value, 预测值% U* C# Z8 {* D" U
Preliminary analysis, 预备性分析
5 T# F9 ^" G& Z6 I) ?2 q8 ?6 wPrincipal component analysis, 主成分分析( c X+ a0 ]6 g0 G, ?" o' |
Prior distribution, 先验分布
' W1 X/ x. x4 _/ I7 sPrior probability, 先验概率
0 R* Q5 Z5 t# N0 A8 M |" @Probabilistic model, 概率模型
2 ?$ p9 I' D) U3 qprobability, 概率5 ^$ ~8 Q1 K) E5 }% u! ~; B
Probability density, 概率密度
- ]9 s0 I, n: g' [. X2 H' q. X; NProduct moment, 乘积矩/协方差3 k2 ^3 N `, z0 c7 a
Profile trace, 截面迹图 h% ]1 R1 I0 K+ U I. T7 t
Proportion, 比/构成比
6 D# ~% D1 {( j8 C$ Y# i3 {1 {Proportion allocation in stratified random sampling, 按比例分层随机抽样, o+ k( ] M# C- X% k( w
Proportionate, 成比例( ]- _$ z! ]6 ]8 t6 c
Proportionate sub-class numbers, 成比例次级组含量: i8 T$ _- J" q( j" r, Q' f- P
Prospective study, 前瞻性调查2 b: \, d& P. ?. ^
Proximities, 亲近性
8 Z4 T" W* |4 [9 U# Z" XPseudo F test, 近似F检验
* ?8 ^% [3 y- |' {Pseudo model, 近似模型
# l( Y" B) A& U, G5 E% WPseudosigma, 伪标准差: g) k0 b* R4 j- D- V. s
Purposive sampling, 有目的抽样
1 ]8 z9 d" A0 ~& t* @2 w. H/ wQR decomposition, QR分解; q) E0 Z* I1 o; t! o. Z# }
Quadratic approximation, 二次近似! F& ^0 F6 H2 z9 q2 F& Q' W
Qualitative classification, 属性分类! h$ ?' ?$ M8 B( @, s' ^" z' _
Qualitative method, 定性方法
- b. c: u$ x( k* G, |: zQuantile-quantile plot, 分位数-分位数图/Q-Q图
! {5 C1 u. U2 E( A$ e$ y2 A3 RQuantitative analysis, 定量分析
6 t6 I( g+ u3 M3 [6 ?- ] I* g7 gQuartile, 四分位数! E) p& E9 m1 p: C+ v
Quick Cluster, 快速聚类
1 D$ ^2 t1 y* N" d3 I, e7 uRadix sort, 基数排序+ n7 X- @. f/ l0 S9 P
Random allocation, 随机化分组( s" {' o+ M, o& O1 |: Z! @. F
Random blocks design, 随机区组设计 ^2 C/ J. ?$ A1 E. T
Random event, 随机事件
1 U x8 `0 i) H# b6 ARandomization, 随机化" J1 O' m; @2 _. g- v# T, S" }
Range, 极差/全距
( n" T3 `/ p" k0 ~5 y2 k) A4 s9 ORank correlation, 等级相关4 c, V; t- Q& |, ^" M
Rank sum test, 秩和检验 q* o: m0 h8 {, a8 O ? u
Rank test, 秩检验
. j" u' [2 a9 p7 t( O0 p4 `3 @' ARanked data, 等级资料
. F: B$ E4 K& Z8 L, V( JRate, 比率 L- _) y- D& J+ u% o; d- d" ?
Ratio, 比例* X$ |. B" k9 p
Raw data, 原始资料
; Z7 K: h3 w. E' I$ I; j4 `9 V- bRaw residual, 原始残差
4 k( W8 E+ e5 r9 z% L4 `: eRayleigh's test, 雷氏检验- B. V; X8 e/ J
Rayleigh's Z, 雷氏Z值 ) r* W/ Q$ f& v; w3 P
Reciprocal, 倒数6 C( m9 U. {4 u
Reciprocal transformation, 倒数变换7 s. z* X O# {. z2 l/ M- n
Recording, 记录
, j4 k1 b0 t6 o- O$ O3 ERedescending estimators, 回降估计量8 u( X) W( q/ e/ D
Reducing dimensions, 降维
. U0 ?. i# x6 t I ORe-expression, 重新表达
2 C' Z5 |4 Y+ R; F* TReference set, 标准组9 D9 Y% W% T/ V3 \% J/ G/ ^
Region of acceptance, 接受域
- x, Q) e- A4 T3 Y# u1 NRegression coefficient, 回归系数
4 t* L% s9 r; w, ]Regression sum of square, 回归平方和7 X- I* l0 b0 R4 j
Rejection point, 拒绝点) v2 s( B6 } A: z- A% f* g
Relative dispersion, 相对离散度
" L- m- ?( y1 ~$ `Relative number, 相对数
5 j! ^$ `1 v; ]" x' BReliability, 可靠性. d, i0 X5 I$ r6 }$ ?( F0 ?. w& E
Reparametrization, 重新设置参数 W- ^. |6 t+ F" f& @! m8 M9 ~
Replication, 重复
+ [! p8 @ _+ K5 |- x& I* J* kReport Summaries, 报告摘要5 R1 x+ a3 h7 H% j
Residual sum of square, 剩余平方和, Y: s0 B+ [) I0 A, h7 l
Resistance, 耐抗性2 F* F8 k9 F+ c) \3 L
Resistant line, 耐抗线
- E D6 X0 E1 L: p {Resistant technique, 耐抗技术! X4 Z+ M( A% a9 \ q( |7 K+ W
R-estimator of location, 位置R估计量7 P$ R9 p: x# y
R-estimator of scale, 尺度R估计量4 b" \" T- o; q& [( G' y, d1 V
Retrospective study, 回顾性调查6 m# ~/ [, ]0 z% h6 G- r0 X& `, ^
Ridge trace, 岭迹: t4 l5 d3 q: e# q9 `
Ridit analysis, Ridit分析
0 S8 `; J7 \% \8 o# M$ jRotation, 旋转7 R. p% ]4 d, K- F+ y2 k0 \: y4 S
Rounding, 舍入
2 p2 ~5 s( P. C" {Row, 行7 u f1 @8 } R+ e% p9 l$ l
Row effects, 行效应8 V0 m7 j }: F3 o/ |, A
Row factor, 行因素/ }* Y1 b+ o3 q
RXC table, RXC表
% O3 x) i- D" M" A1 y1 O5 YSample, 样本- O* P! e" {3 b% H7 l7 ^ M
Sample regression coefficient, 样本回归系数
* c5 x. g4 J$ ]$ `: h" A8 Z" x, NSample size, 样本量
- K# X% ]6 y- [Sample standard deviation, 样本标准差
/ @5 S1 y( d4 E( `9 M. qSampling error, 抽样误差
7 L# Y$ ~9 b' V, W9 R9 y4 e5 USAS(Statistical analysis system ), SAS统计软件包1 m" a& g" |4 s. ~7 G7 E. {
Scale, 尺度/量表/ u* f0 R8 l! J& U& ^
Scatter diagram, 散点图
; b( y. s2 z* ?) m) @4 ^+ B3 \Schematic plot, 示意图/简图2 ?, ?% ~4 a/ C' P
Score test, 计分检验
x1 m2 z; i9 v% U# L. ~# D( PScreening, 筛检
0 d: b0 Y* p5 {# o! V2 \3 {+ sSEASON, 季节分析
' Q- z% v+ m( {8 [( h& x2 USecond derivative, 二阶导数
( ~. @0 W5 w* Q& W3 e* B, L4 JSecond principal component, 第二主成分
. w1 l+ K, o+ z) Y! J" vSEM (Structural equation modeling), 结构化方程模型
" S8 r" _9 m8 n2 }0 I5 NSemi-logarithmic graph, 半对数图, }/ Z+ T# v. O2 Z8 Q7 P2 x. j5 P+ b4 J
Semi-logarithmic paper, 半对数格纸( f8 n& h% M2 ?8 Z1 W
Sensitivity curve, 敏感度曲线( n3 [) s0 R# J$ x3 K
Sequential analysis, 贯序分析+ t( F' Y+ k5 L V0 V
Sequential data set, 顺序数据集$ n- @0 N8 o7 n8 Q) n
Sequential design, 贯序设计8 {; b& Y8 y$ |( J _7 k/ B9 I
Sequential method, 贯序法
( v4 H$ y9 P5 |/ A! h+ ~Sequential test, 贯序检验法
( t" _0 B3 h |/ D4 U/ o& CSerial tests, 系列试验
9 Q& ^ b4 V2 N6 Z7 s0 e" n: a6 P' `Short-cut method, 简捷法
% v6 C/ I4 D( e9 y5 tSigmoid curve, S形曲线; @+ T" X0 k( _& R) Z3 C- v" a
Sign function, 正负号函数4 G. |' M% j" d) o; Y4 n* m
Sign test, 符号检验
+ Y3 l+ k& W7 ~/ ~% W4 h* h9 |Signed rank, 符号秩1 _/ U2 g( P* q; s
Significance test, 显著性检验$ e% ^4 h! V9 C# j* J
Significant figure, 有效数字6 b& o) @- O7 i% D5 p
Simple cluster sampling, 简单整群抽样
$ P1 e2 u! @/ }. H5 e, C; a9 iSimple correlation, 简单相关5 w3 T( M. h$ q4 Y
Simple random sampling, 简单随机抽样: T5 _8 p8 j' @0 u: l
Simple regression, 简单回归
8 E% j, ~! @. N( d) P( ysimple table, 简单表
* O" a4 V/ T) l ?5 }Sine estimator, 正弦估计量
: I; m5 X6 ?! Y) v; ESingle-valued estimate, 单值估计
; z8 O$ X1 g8 R, {Singular matrix, 奇异矩阵8 ~/ d; j9 H. q0 S |6 l8 W/ P
Skewed distribution, 偏斜分布
" M3 p+ f- d1 {( L6 w# A5 `: sSkewness, 偏度
! ~+ L$ v2 {8 Q& C: V8 l. BSlash distribution, 斜线分布
7 ?, j5 q; ]6 ^. TSlope, 斜率
4 u# P# w* y, pSmirnov test, 斯米尔诺夫检验2 N2 ~) `% A0 e0 ^
Source of variation, 变异来源
) |8 |. F" V' \6 J( O5 j' mSpearman rank correlation, 斯皮尔曼等级相关 C* y$ x& A0 L; |5 I/ l5 N, n
Specific factor, 特殊因子. ]; ^# t% J- g& s$ @
Specific factor variance, 特殊因子方差
2 q& C, Z5 }# e7 HSpectra , 频谱
7 s# T: R8 H8 u4 w( \, USpherical distribution, 球型正态分布
- O F' C$ t9 l% D9 USpread, 展布8 A' S% |. {( w4 W& B# q, @
SPSS(Statistical package for the social science), SPSS统计软件包% s+ [+ S' q2 B1 ?5 T2 w+ ] h+ Q
Spurious correlation, 假性相关
Y1 n! K) t7 s6 mSquare root transformation, 平方根变换3 W: ]) V# q9 q) X( ]; w
Stabilizing variance, 稳定方差; Q& V4 s* z4 T5 {: ]- q
Standard deviation, 标准差 n0 A* Z# \; }8 | x' e
Standard error, 标准误& h& s7 ]! c* Q
Standard error of difference, 差别的标准误
5 C# d7 R& i8 g" ^Standard error of estimate, 标准估计误差
0 p! c+ {6 Q8 n" }+ J4 Z2 D+ `Standard error of rate, 率的标准误
" k0 M. u. A" S- F$ i9 iStandard normal distribution, 标准正态分布3 w% |$ Y @; G% I+ H! L" g( s
Standardization, 标准化
- P7 k8 T% _! C0 ^0 NStarting value, 起始值 N p# F' k' w3 U4 D( [; ~$ m
Statistic, 统计量2 J/ q, S: w# v) {
Statistical control, 统计控制# }+ q$ y1 Q* v, Y) P8 T; U$ {
Statistical graph, 统计图
" c$ ~7 J7 V9 q- L. u4 z0 _6 V8 X4 _Statistical inference, 统计推断
3 g+ f$ U* F5 EStatistical table, 统计表
9 r" K9 h9 J9 e; a6 t7 s* gSteepest descent, 最速下降法
3 U P- x$ M* E' eStem and leaf display, 茎叶图- W) k/ c( B* D% r" Q. a
Step factor, 步长因子) S4 `5 U8 f; p& D* \8 k- K
Stepwise regression, 逐步回归
) |1 R, P- x0 Y xStorage, 存7 _& e9 R% q/ X0 x* J8 ], [. b2 D, U
Strata, 层（复数）+ B' ^! B( j" S, S
Stratified sampling, 分层抽样
( C8 z) g$ N8 Y. m9 hStratified sampling, 分层抽样+ F& v& f s+ g. X) t3 d
Strength, 强度
+ g( G3 J4 ~; D& n+ p. E! D) R. ]# ?Stringency, 严密性/ `- G: _* B0 t5 p9 a, L
Structural relationship, 结构关系
5 {8 B$ D& n' G& b* d+ ]. KStudentized residual, 学生化残差/t化残差
6 c) _ U# M# F; B" k# G, ?Sub-class numbers, 次级组含量
; }5 }* [- O1 cSubdividing, 分割. @' C8 a' u- t- ]9 ?( s5 H8 S
Sufficient statistic, 充分统计量7 D2 s; ]# C( E! R1 O
Sum of products, 积和
: j* L x) u9 a6 K0 z3 O( BSum of squares, 离差平方和' E8 `- X' X9 n% w: D
Sum of squares about regression, 回归平方和- a I" a% T# c1 q* G: @0 U0 V; n1 |
Sum of squares between groups, 组间平方和
$ c( I) ]( M! ASum of squares of partial regression, 偏回归平方和, L' y0 m3 A0 M
Sure event, 必然事件7 d+ j4 `- k3 }7 X ~: C: _1 o) Q' w
Survey, 调查
" K$ |5 N# k- n, z% Q3 ISurvival, 生存分析
" M0 ^3 F! [' h4 D7 o3 U9 `Survival rate, 生存率
4 X/ {2 s1 x/ |# d0 I; q3 R# d7 F# v- ]Suspended root gram, 悬吊根图" I! A7 ~; `% q% o' j* P
Symmetry, 对称
7 y' n8 ^# a( N: X8 c' j) V) ?Systematic error, 系统误差7 @; }. T; ^6 w3 P) ^/ C
Systematic sampling, 系统抽样
! j* _0 t4 I( z, UTags, 标签
; `' J! U% V/ A4 B! R$ A2 m; d8 z6 UTail area, 尾部面积5 H. p8 P: J: r% M8 j! }
Tail length, 尾长) Y& V9 y3 N, U( H
Tail weight, 尾重
/ x( ?5 c0 a1 }1 HTangent line, 切线% N N4 e1 h4 O- {( w: I
Target distribution, 目标分布3 T) G1 B) r. W$ ? K; B d" Y
Taylor series, 泰勒级数
( W1 O. b! \ N1 \' Q( c+ iTendency of dispersion, 离散趋势3 T/ B, e: Y6 f! P/ a+ N, E% C
Testing of hypotheses, 假设检验! {4 t) [, h& n3 A% F8 [3 j! q! ?
Theoretical frequency, 理论频数- Z5 ?( Z, a$ _0 P& H0 R( x
Time series, 时间序列
) r, j* x, c. A4 u) jTolerance interval, 容忍区间5 d+ K" Z8 w4 u2 }
Tolerance lower limit, 容忍下限$ j c z! ^9 F4 c/ H( z; m
Tolerance upper limit, 容忍上限
1 @' n* X- P; O5 mTorsion, 扰率9 T B, {! {+ T1 l _' A0 ]$ N
Total sum of square, 总平方和& h/ o4 h* c! s: B5 B# R
Total variation, 总变异
# I' m( S2 j8 t0 x8 w" mTransformation, 转换+ s x$ e$ ~3 T% w
Treatment, 处理
' @/ Z( k( s& D: f! h6 ~4 |Trend, 趋势
$ x7 L2 d( Y+ L$ P! w! @4 c! nTrend of percentage, 百分比趋势 |4 ]+ ^$ L5 `/ z. H+ b5 o
Trial, 试验
7 {6 v ?7 S( B* C% f' aTrial and error method, 试错法/ Q- v7 a9 Y$ q% p% H* A: C2 H
Tuning constant, 细调常数2 H! L1 s, Y# q( m3 B8 @5 ?$ C
Two sided test, 双向检验
! s; f9 p) S; I& iTwo-stage least squares, 二阶最小平方9 V5 a% u' [2 w3 H9 c, u; G. ]
Two-stage sampling, 二阶段抽样
7 K/ O/ Q0 E" O I- CTwo-tailed test, 双侧检验
; X: |' F; [: Q( ?8 Y1 i' g, STwo-way analysis of variance, 双因素方差分析$ B' l3 S N4 ]; u
Two-way table, 双向表2 r- _" E$ |" F; L, v( z
Type I error, 一类错误/α错误
9 V: I3 ?1 W' L N; y- NType II error, 二类错误/β错误" \: S. s, @4 E
UMVU, 方差一致最小无偏估计简称2 q3 R* W' C" |$ ^$ t( e
Unbiased estimate, 无偏估计, E, }% B" e0 {6 t* b9 _; a
Unconstrained nonlinear regression , 无约束非线性回归7 G- p" h4 ?/ j2 W* [
Unequal subclass number, 不等次级组含量" O1 L! j8 I% d5 Y+ f
Ungrouped data, 不分组资料& H# R+ t" e& ~
Uniform coordinate, 均匀坐标
; z7 l. r T' ^. ]6 GUniform distribution, 均匀分布1 ]4 E4 U' C* D) [0 w) |; `; p! M# O) Z
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
4 w7 U0 T( B* w% B& E9 r$ iUnit, 单元* r! d- E- Y6 ?" w8 ^
Unordered categories, 无序分类% I# U( F" a0 ^/ i/ v- ^. X; q# L
Upper limit, 上限6 B5 @. p* [/ J- G% C
Upward rank, 升秩
" m* E$ f+ M ?/ M$ TVague concept, 模糊概念& ]% C* {1 A4 @+ t
Validity, 有效性& p$ B1 ~3 a, g2 N& I
VARCOMP (Variance component estimation), 方差元素估计/ D& S3 o" X2 E9 s$ K
Variability, 变异性8 q! w7 B- I' O! H8 f
Variable, 变量0 ?" W% E [5 J! A0 W
Variance, 方差- u6 d) l+ y1 D
Variation, 变异9 S7 R* O. o) X7 ~
Varimax orthogonal rotation, 方差最大正交旋转" k+ B. p9 b5 c* v$ {' b
Volume of distribution, 容积 j" S! x% e: s/ n; P6 p% C
W test, W检验9 M3 I, h1 f y5 `
Weibull distribution, 威布尔分布% w, X9 A! C, r( g
Weight, 权数
V$ c% o- u: h$ G5 ?Weighted Chi-square test, 加权卡方检验/Cochran检验
$ j: [: ~1 m7 ?* T4 f) C/ X, I1 pWeighted linear regression method, 加权直线回归2 n% w% ]* `5 V7 ?' S* X: z3 y
Weighted mean, 加权平均数, S b& @: r% q1 h
Weighted mean square, 加权平均方差6 O6 y5 d+ R- Q- p! h6 i7 \5 J
Weighted sum of square, 加权平方和8 h9 ?6 _6 L" p- \2 q1 ^
Weighting coefficient, 权重系数
0 C% @+ M% }& K) C* N9 h, l1 CWeighting method, 加权法 ' w8 [2 \5 t x( }% t% h
W-estimation, W估计量+ t( H5 `% }$ r' M4 W
W-estimation of location, 位置W估计量
+ q% B( [5 ]6 v" |7 t$ P% {3 a$ ]Width, 宽度) v; c( ^: B4 L. E
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验& R/ q& g+ Q. H% G! t
Wild point, 野点/狂点! I: R- j/ A7 S/ u
Wild value, 野值/狂值
9 g; H' R! S4 K6 k: pWinsorized mean, 缩尾均值
" j$ l9 N; K1 Q. LWithdraw, 失访 " ~/ t( `3 A0 E/ u0 `( D- |0 K, T
Youden's index, 尤登指数5 F ~* z0 a5 ~4 u
Z test, Z检验
5 v! |7 Z8 `( I0 A' l( K6 CZero correlation, 零相关8 j, |8 }# `( z: B: t
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
