|
|
Absolute deviation, 绝对离差" [- D& d- l# F0 ]: G
Absolute number, 绝对数; U$ F, v4 D7 M" n: f {
Absolute residuals, 绝对残差8 Q4 X8 h" |8 S% v1 c
Acceleration array, 加速度立体阵
8 R" e1 J; J6 Y0 s) J7 [9 iAcceleration in an arbitrary direction, 任意方向上的加速度; ~! W& U6 j* p5 @1 J
Acceleration normal, 法向加速度3 P* y9 j: S( X
Acceleration space dimension, 加速度空间的维数, \) d# U) |. S' u
Acceleration tangential, 切向加速度& A/ \! p+ S/ W c% {% y, c o
Acceleration vector, 加速度向量5 \# Y# o% g6 l5 i
Acceptable hypothesis, 可接受假设
: `) `# Q8 H# W+ c5 c$ CAccumulation, 累积- A0 }- Y9 \; L/ p+ V9 t
Accuracy, 准确度6 F2 U) `$ M6 S4 v; X
Actual frequency, 实际频数$ M6 k3 B1 n. i! h7 t
Adaptive estimator, 自适应估计量( E. X! Q- v( l0 [# N7 h
Addition, 相加! G. s& K6 E2 v
Addition theorem, 加法定理5 k G8 }* O# J" I
Additivity, 可加性6 C5 c& L" u1 x3 ]! r' S! x7 a9 a
Adjusted rate, 调整率" Q3 r5 Q9 u3 N- `; A* g% K
Adjusted value, 校正值
9 @5 C% @' l+ v+ s* G) X3 }Admissible error, 容许误差
. ~" [4 R) |' L6 w vAggregation, 聚集性1 j0 {8 o7 S6 Z1 X8 k) w' C M
Alternative hypothesis, 备择假设4 ~* i' T6 Q1 I; N% O- W- f
Among groups, 组间
7 M) ?4 r2 p4 P- CAmounts, 总量
7 V+ Q, J2 k; v) Z( x! AAnalysis of correlation, 相关分析
! ~1 G: l) e. }/ R" f b$ qAnalysis of covariance, 协方差分析: m+ ]" ~5 _' C% E
Analysis of regression, 回归分析1 }3 f0 F0 B% A
Analysis of time series, 时间序列分析3 d4 q, H, O" \0 c
Analysis of variance, 方差分析
4 i U7 ]* l( s6 ^7 ]4 AAngular transformation, 角转换
! b3 s! A, \/ d" V8 t6 u1 sANOVA （analysis of variance）, 方差分析1 |+ Q& f% ?# N
ANOVA Models, 方差分析模型
4 G: ]% g% V; qArcing, 弧/弧旋& H" ?4 S* a, o o6 {" G
Arcsine transformation, 反正弦变换
7 t6 W4 `) C" O. ^/ iArea under the curve, 曲线面积
" _9 m% p% p% o3 T4 ]AREG , 评估从一个时间点到下一个时间点回归相关时的误差
5 M! V( O u( v0 {' ]4 RARIMA, 季节和非季节性单变量模型的极大似然估计 9 t, p" f- {! m' |3 K
Arithmetic grid paper, 算术格纸9 `0 c9 ?- E3 c" B$ n. h4 \! b
Arithmetic mean, 算术平均数
- S+ s( [. U% n$ w0 F. X" `Arrhenius relation, 艾恩尼斯关系
' H$ [: d6 A. |, g2 p! xAssessing fit, 拟合的评估9 {; O0 i3 V2 K( D) H, N* {! J) d
Associative laws, 结合律
/ D7 `! F t9 N8 e, Z0 Y* E9 X1 [Asymmetric distribution, 非对称分布
$ d# Q. B1 E" t* H. yAsymptotic bias, 渐近偏倚1 r7 I \, i/ ^9 m0 D
Asymptotic efficiency, 渐近效率( D5 {) [# O3 N2 N, x
Asymptotic variance, 渐近方差
* Z) W4 U/ F4 T: r; r6 s7 fAttributable risk, 归因危险度
# J, v3 \5 ~! \+ c c0 n0 gAttribute data, 属性资料, _) I% z" B) g
Attribution, 属性
, g3 O% c% j, X* tAutocorrelation, 自相关9 X# Q; i# s: z* g- M$ L! Q
Autocorrelation of residuals, 残差的自相关) A3 e- _' |, S
Average, 平均数9 C. _& u! h& f4 M7 C4 n& s0 J5 G
Average confidence interval length, 平均置信区间长度
5 t" _# _# o: w* c' PAverage growth rate, 平均增长率2 e- @. H4 w) N3 Y$ f
Bar chart, 条形图- W2 f8 Q% F. E: _/ o' b# y
Bar graph, 条形图
M0 H/ T5 q$ Q8 l' bBase period, 基期" w! \5 H3 }* }7 Y
Bayes' theorem , Bayes定理
1 u- M) b0 _: b- [, V# g1 LBell-shaped curve, 钟形曲线
7 `7 p! r# ]9 M! xBernoulli distribution, 伯努力分布6 j/ d* I4 d2 S: t( d
Best-trim estimator, 最好切尾估计量
" U; x0 @7 u. D& q( k VBias, 偏性" w; ~6 R$ H& _. \$ Z1 ~6 G
Binary logistic regression, 二元逻辑斯蒂回归
/ ~2 M0 c9 V! h9 pBinomial distribution, 二项分布
i- A6 H7 [7 j4 b! YBisquare, 双平方2 l) h* N- R) I7 Z1 g5 P
Bivariate Correlate, 二变量相关
3 b6 K' p2 d5 g3 GBivariate normal distribution, 双变量正态分布
5 F T6 a% c% x; EBivariate normal population, 双变量正态总体3 x- P6 d" s. h6 ]% |! e
Biweight interval, 双权区间
1 ~: P" T R" h! v PBiweight M-estimator, 双权M估计量
. [/ U9 B, t$ P6 b. }6 fBlock, 区组/配伍组
/ @& g+ w$ g% s; G( W Z/ V2 p& KBMDP(Biomedical computer programs), BMDP统计软件包4 G% j6 e0 z0 q. s+ N0 ^, A$ j9 a
Boxplots, 箱线图/箱尾图2 {. y3 i( z o) d
Breakdown bound, 崩溃界/崩溃点) I3 ~0 H& H# c; k; l4 X, ^* I# N
Canonical correlation, 典型相关
2 e' g8 ?) t+ w% _& e r- [& S+ kCaption, 纵标目
9 p+ ^. m2 Y+ {& `2 FCase-control study, 病例对照研究$ I) Q/ V& W( |0 R- q5 A* C
Categorical variable, 分类变量
; j$ k8 o4 U. I9 u( `4 N3 n& HCatenary, 悬链线
# i2 L9 \! W: d; ~- q4 RCauchy distribution, 柯西分布
3 i! _8 V) {/ X! } H5 eCause-and-effect relationship, 因果关系# E' H+ \- }1 m" m3 G' T8 a$ Y( t
Cell, 单元
% D9 |3 `6 z g, b& }, c4 L- bCensoring, 终检
; n* [+ S! }! |4 F. KCenter of symmetry, 对称中心
0 p, F. ~7 [! X- j% ^Centering and scaling, 中心化和定标
0 H: B& X4 }. P$ S5 i: a% [+ z/ gCentral tendency, 集中趋势
$ G% b; N* _) g7 {4 t, ^. C2 p" YCentral value, 中心值
& Y! n4 _& P7 U- {CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测# W& ^0 T* Z- D! g# i
Chance, 机遇/ e& F) f( f% G& r U4 o8 j" v
Chance error, 随机误差
8 @! @ b3 K# T0 E! YChance variable, 随机变量
* Q; m- D8 @2 I0 WCharacteristic equation, 特征方程
$ e) O* F; G. U. P0 \Characteristic root, 特征根
+ k/ o0 ~9 Y4 mCharacteristic vector, 特征向量
# [/ U9 Y2 s8 t0 w" `" dChebshev criterion of fit, 拟合的切比雪夫准则$ f. O1 ?# \! _! _, c9 P8 ?
Chernoff faces, 切尔诺夫脸谱图
7 ?6 y& T s: {Chi-square test, 卡方检验/χ2检验
. Q C% [( y5 ACholeskey decomposition, 乔洛斯基分解
1 a3 T0 f( F- n& {Circle chart, 圆图
+ R* L: O4 O- X$ e+ [Class interval, 组距
1 i. j' X. |$ y; YClass mid-value, 组中值
9 X9 z1 D% y2 D% O: XClass upper limit, 组上限3 \8 Y& |, Q5 t3 a ?. Z/ r
Classified variable, 分类变量
7 a- h1 E# V1 WCluster analysis, 聚类分析
; X# m4 T" l# K2 A: |/ QCluster sampling, 整群抽样
( ^* ^* u/ o) x& s WCode, 代码
! J, p s: r! A: |- U: w9 _, H& SCoded data, 编码数据
) C5 _, C, {6 V. l j" U F! o) FCoding, 编码
: v( G* I% Z6 K2 w7 `Coefficient of contingency, 列联系数
6 h- C+ l) ~4 _3 iCoefficient of determination, 决定系数: {3 c, p5 D( f7 V0 n9 Z+ [, @
Coefficient of multiple correlation, 多重相关系数
. l& q4 e( k) m; I% ]Coefficient of partial correlation, 偏相关系数
" l. ?! x% x! o: a: OCoefficient of production-moment correlation, 积差相关系数7 b/ }' i% n0 ~9 z0 o
Coefficient of rank correlation, 等级相关系数
! M, y# U- L& U. V1 Z: GCoefficient of regression, 回归系数! z$ ~ ~! c6 [; w
Coefficient of skewness, 偏度系数" [' ^( u. M2 s+ p
Coefficient of variation, 变异系数
+ s$ }( ~" X8 Q# zCohort study, 队列研究! Z% ~# p2 H" p8 K0 ?3 r0 a& x8 J
Column, 列
: ?% X' j7 Q8 S- {3 @1 `Column effect, 列效应
$ p. h5 |9 {* V7 D5 j% _. t9 qColumn factor, 列因素
) v; E; g$ f* L) }: eCombination pool, 合并
* I3 E5 t6 w( M4 M/ O3 R& ?Combinative table, 组合表6 H- z4 Z1 p* J+ A: g
Common factor, 共性因子
! s6 h X/ S. E& iCommon regression coefficient, 公共回归系数4 B. f w% y- i7 V5 s
Common value, 共同值
5 U6 g S1 U/ M; c: F5 q# l8 tCommon variance, 公共方差
9 r7 E0 D* Y' \) j0 }9 E! SCommon variation, 公共变异
, D4 I3 p, ^: G: m7 P/ D9 l1 jCommunality variance, 共性方差 \# r% c- \4 w8 h8 F& a- M5 Z
Comparability, 可比性
# M$ e# a. I# F2 Y; jComparison of bathes, 批比较4 p- C) k% U! y. X) B0 I; s
Comparison value, 比较值
% z% m2 T. {" y9 G) ?7 `% HCompartment model, 分部模型0 L) t+ P$ {% j _; n. P5 S; N
Compassion, 伸缩" D, ~1 K; K2 i3 M
Complement of an event, 补事件/ B$ x* G$ ~) X& E! A: [2 r2 B9 F
Complete association, 完全正相关" e! O1 E7 l, i7 V7 \
Complete dissociation, 完全不相关- }2 t, e" K4 k0 c, x/ r" ^
Complete statistics, 完备统计量: j/ ^2 _5 M7 W6 R
Completely randomized design, 完全随机化设计
& v, J; r8 ~/ [" A6 E( j ?3 {: dComposite event, 联合事件* t9 U* ]# e ~" I1 M
Composite events, 复合事件
; g9 w5 f$ h* DConcavity, 凹性
% l5 p0 x t5 l& cConditional expectation, 条件期望
* S# }6 J# H7 O5 b" c9 k: bConditional likelihood, 条件似然
5 P z7 O( p$ FConditional probability, 条件概率5 B; s' L, _4 z" o
Conditionally linear, 依条件线性
- y7 R, c$ i3 S9 J+ Z0 WConfidence interval, 置信区间0 t- M6 D( ^$ y. ^- E6 m
Confidence limit, 置信限
) b4 l# a4 }4 D8 P4 cConfidence lower limit, 置信下限% J% a& s: b- X+ q/ N
Confidence upper limit, 置信上限# w& `5 _, P& {* T* f* X, n
Confirmatory Factor Analysis , 验证性因子分析# V, p$ ?: G( N5 O$ b E. m' u9 S. V2 v
Confirmatory research, 证实性实验研究2 I; @4 m" h; R+ K _. h5 D
Confounding factor, 混杂因素
$ O* J& B2 e9 F7 iConjoint, 联合分析
& X; I! U, H& @& D& _6 m( V, |Consistency, 相合性
0 I! ?1 o/ x# j+ _9 @2 YConsistency check, 一致性检验
" h- L% ^( P4 v6 ?Consistent asymptotically normal estimate, 相合渐近正态估计8 v7 E) t O2 [3 @+ X8 Y& Z
Consistent estimate, 相合估计- c! F3 T* s6 Q' x/ t) {
Constrained nonlinear regression, 受约束非线性回归9 P( A, o$ t* J# T
Constraint, 约束" }; o+ x3 \+ t& s% o
Contaminated distribution, 污染分布
( Y4 H: t% R# i3 m ?' \+ AContaminated Gausssian, 污染高斯分布( B3 K( P" t# o. `* X+ |
Contaminated normal distribution, 污染正态分布8 z& b; p( S/ u0 V7 c: q8 j
Contamination, 污染8 {9 {5 G: q3 J0 H5 C
Contamination model, 污染模型
, D& T. }& a8 gContingency table, 列联表
" z. {+ R' K z0 F$ NContour, 边界线* u3 Y$ C6 K, o
Contribution rate, 贡献率
0 y1 R* m- Q. e5 lControl, 对照+ Y: F* }4 a3 b
Controlled experiments, 对照实验
1 P" ~0 f; Y/ v7 ~$ t' Z. | L- MConventional depth, 常规深度$ @- j" A8 d, d
Convolution, 卷积# i. a- o1 Q, ]
Corrected factor, 校正因子* x$ i7 n+ e; ?( P
Corrected mean, 校正均值
3 l0 g6 M5 N& D: K* G# W# ?/ UCorrection coefficient, 校正系数
0 c2 ]4 b1 }3 A. H) l9 dCorrectness, 正确性+ W$ V7 ~, u8 E e( F
Correlation coefficient, 相关系数
) }& [) X9 P4 }5 F( L# j, `Correlation index, 相关指数
P H/ ~4 p, a4 U$ A+ BCorrespondence, 对应
- O5 ^/ \) g+ A. [, nCounting, 计数
" P ?( w2 x: F& V4 l; |Counts, 计数/频数
; b2 l3 o$ ^- L' s2 k% tCovariance, 协方差) T- L* `* C9 @
Covariant, 共变 ( n3 O" o" Q" j: p- l8 }7 k9 k
Cox Regression, Cox回归
, I/ o; a& f, q& J5 pCriteria for fitting, 拟合准则
$ I3 m @# [# K$ QCriteria of least squares, 最小二乘准则' n8 ~- h7 V2 a6 F$ X
Critical ratio, 临界比
2 P% K4 }7 s; R: W) s& YCritical region, 拒绝域
- c+ w! R! `: R/ ECritical value, 临界值0 m8 {' t6 K$ T
Cross-over design, 交叉设计
. N5 b! v# x& d2 {8 t+ jCross-section analysis, 横断面分析
3 x1 C2 M; f; e" ~Cross-section survey, 横断面调查 j6 ~, F* _9 u# k* R" }+ q/ N+ E
Crosstabs , 交叉表 ; F" ]9 ^9 Q+ D' S; }6 ?* c
Cross-tabulation table, 复合表
( z4 n/ ?3 W. l" d; M" A9 v& PCube root, 立方根. F: J- d! L; w% G$ e% Z$ x. z
Cumulative distribution function, 分布函数, v0 L! a7 Z* r2 K$ `/ l8 P r
Cumulative probability, 累计概率9 X* W/ F# @" f+ D4 C/ A Q, N9 r
Curvature, 曲率/弯曲
0 s0 J; T0 k: _* t; dCurvature, 曲率% j' e8 d; w. L
Curve fit , 曲线拟和 9 c8 F4 X9 v- T: e( ~# }
Curve fitting, 曲线拟合
1 c3 F ^2 Z- F7 G" FCurvilinear regression, 曲线回归
, @. ?- ^6 C* b' y! B6 o' q% cCurvilinear relation, 曲线关系
) b, y0 g. Z# J5 F# K1 @Cut-and-try method, 尝试法+ [+ i( f: b1 G& q2 y2 |) r+ a+ X
Cycle, 周期
& u: W; j4 [. L6 ECyclist, 周期性
6 Z1 w7 W3 } }; Q ^# {D test, D检验
3 S. @2 G1 C8 e' q) N9 gData acquisition, 资料收集% F; Q5 [& E, R7 Q% ^0 |
Data bank, 数据库% w# Q3 K" o" G/ S. _$ r
Data capacity, 数据容量! Q" a1 p3 O" v4 Q
Data deficiencies, 数据缺乏
% N, S- o+ R8 z4 d( bData handling, 数据处理
5 {6 ]; p1 i8 T5 i/ ]Data manipulation, 数据处理* Y" L. f% E* \5 D: i* c* P" [
Data processing, 数据处理4 n4 ~' _0 h1 k( U. }9 E' H: @7 M
Data reduction, 数据缩减. p* N. E; b5 }8 R$ g$ n; w
Data set, 数据集+ f9 s1 s* V- X' [+ o& {
Data sources, 数据来源
* B+ B0 V7 d- A5 k' HData transformation, 数据变换
; P6 X) z$ N* N4 H5 h! k& TData validity, 数据有效性
0 t& L% M; b/ g" o% p5 q" k% W# ]* nData-in, 数据输入
1 Y( N- l! }5 H" G$ v" P8 nData-out, 数据输出
+ c S; ?! E) k5 _. z7 WDead time, 停滞期; J4 e# z! M" z2 V0 x3 D1 s
Degree of freedom, 自由度
; N6 a) D5 l1 |4 LDegree of precision, 精密度
2 @* l" r+ Z; U) o! YDegree of reliability, 可靠性程度. y, L* \% M/ H; ~
Degression, 递减
1 ?9 f# F' f, ~5 C) pDensity function, 密度函数
L' c$ G& ?& o+ JDensity of data points, 数据点的密度* u1 I. s4 r& R g& q4 D
Dependent variable, 应变量/依变量/因变量
1 a4 P- }$ X4 y& oDependent variable, 因变量! f' N* s- R- \7 c- x3 f
Depth, 深度
! ?9 r3 G$ B# a$ I; b* tDerivative matrix, 导数矩阵
* c2 H- T7 n! v3 O4 CDerivative-free methods, 无导数方法
9 L9 {3 q1 M3 ~# f/ WDesign, 设计
1 W# q4 {' h* F- uDeterminacy, 确定性
0 k- [4 V M- ?) {Determinant, 行列式2 j: ?& N! h F$ ]# i; I
Determinant, 决定因素# g4 W- c% K6 d' x
Deviation, 离差/ X& q+ p! G4 t @+ L( H9 { @) R
Deviation from average, 离均差
' f0 {- d. D, |4 r! K3 xDiagnostic plot, 诊断图
* Z; ~* n8 g, M" |Dichotomous variable, 二分变量) j' J6 i/ t) X4 o
Differential equation, 微分方程& j; a7 a+ e& |, r" `4 p {0 e
Direct standardization, 直接标准化法1 n! }# a/ L" B8 @3 |
Discrete variable, 离散型变量7 `% |2 @9 m3 y5 v. }6 O" e
DISCRIMINANT, 判断
# Y! z4 Z9 H* h3 Q1 c: x3 {Discriminant analysis, 判别分析
! R7 [ @$ q$ `. }7 sDiscriminant coefficient, 判别系数# b! a# h* Q* _
Discriminant function, 判别值7 D$ R7 z. ]0 `* S; c$ K2 U4 b( i D
Dispersion, 散布/分散度
) n% W$ B' D9 Y9 u% a5 f! ]Disproportional, 不成比例的% k# t) ^4 E9 d S) g. l5 r( m8 S
Disproportionate sub-class numbers, 不成比例次级组含量" p. y; }) ]. ]5 P3 r
Distribution free, 分布无关性/免分布
, B5 s$ S9 M, \Distribution shape, 分布形状
8 q! T: @& Y) r$ FDistribution-free method, 任意分布法
7 o2 r5 b8 j0 I r# W5 w4 qDistributive laws, 分配律
# C/ k0 a7 _$ s: T+ O4 ~% _Disturbance, 随机扰动项
4 @" x7 q1 B% I+ J6 Q: zDose response curve, 剂量反应曲线8 J* k$ T' F* |. `/ v4 S
Double blind method, 双盲法8 |$ q" S+ y2 ^7 r
Double blind trial, 双盲试验
# |0 P3 @7 I( R! A. H3 c; @Double exponential distribution, 双指数分布! e$ N4 q4 _6 s ?. K9 j
Double logarithmic, 双对数
# B' I8 l( a: \. F# R( C* ~# GDownward rank, 降秩, M, {- C& K2 }/ y( ^* N
Dual-space plot, 对偶空间图
& z: E, c3 o( [DUD, 无导数方法 ~# {8 L8 V& w6 z/ e: o6 L
Duncan's new multiple range method, 新复极差法/Duncan新法
- N3 d; D/ ~# g3 S) r) \Effect, 实验效应3 w4 G+ I, W- p3 H' R5 P
Eigenvalue, 特征值, C+ y+ _7 Z; f+ v: H1 i0 \
Eigenvector, 特征向量- m5 T3 V3 V( X$ c/ I, V6 x
Ellipse, 椭圆
/ a" g: K) G' O2 D+ A" p" eEmpirical distribution, 经验分布) x$ ^; D$ V4 `+ t9 g0 I
Empirical probability, 经验概率单位2 N0 R. ^2 u' b, D% x! Z0 F/ j
Enumeration data, 计数资料# w1 ^: Q1 f( R* D t
Equal sun-class number, 相等次级组含量
0 w) f4 n$ t; L3 V; GEqually likely, 等可能0 [( d: E, Q: u1 F
Equivariance, 同变性
7 i% \; x# h! `- P4 qError, 误差/错误& U8 }2 \% {# r" l: |4 o$ A
Error of estimate, 估计误差
4 w% M) @- L9 f3 {Error type I, 第一类错误
E" D: Q! }: f. x% F/ _) G3 R/ dError type II, 第二类错误" t: ]' d8 m/ X. w& [
Estimand, 被估量
/ b6 H) z1 W6 y6 s! C7 Z( K8 EEstimated error mean squares, 估计误差均方
6 h! G' t# i9 ~; \/ H HEstimated error sum of squares, 估计误差平方和
' Z! b, S- w9 m4 @% REuclidean distance, 欧式距离: M: E5 w" P" ` p
Event, 事件
M. H1 K2 f q* f1 G$ g# eEvent, 事件
0 d/ ^' S- a0 n* W4 BExceptional data point, 异常数据点0 r0 ?8 E$ q& B' w- i# _
Expectation plane, 期望平面
. Q O- V& u8 k9 F5 iExpectation surface, 期望曲面8 F8 p. s5 _) W/ m
Expected values, 期望值
' _+ N+ d- S* b; `6 N& S8 MExperiment, 实验% s% f" y; e( z% L9 n
Experimental sampling, 试验抽样5 J; ^5 _% K1 n1 Y, l
Experimental unit, 试验单位0 o* O# g# F. Q8 V9 v* h5 b
Explanatory variable, 说明变量
- Q! F$ H; X1 BExploratory data analysis, 探索性数据分析8 L' ]" y% L0 v) U4 d) ~
Explore Summarize, 探索-摘要
, x& y6 i2 f7 s: Q8 [0 z/ H( O$ bExponential curve, 指数曲线% J/ O G. F6 ?4 V+ l, ~1 u
Exponential growth, 指数式增长
s/ V% O9 H0 I; t+ Z% mEXSMOOTH, 指数平滑方法 5 Z {+ ~. A- D7 x6 w2 Q3 C
Extended fit, 扩充拟合
5 c, `1 ~' A# y9 d' h5 RExtra parameter, 附加参数
1 W) t* T: O; |" sExtrapolation, 外推法9 {- h6 y5 T6 F. {) ^; K
Extreme observation, 末端观测值8 F; v/ T$ z: A, E8 C5 j, F
Extremes, 极端值/极值
9 }* _3 a" a8 B, G4 S% \F distribution, F分布7 i: w, S" Q& z P
F test, F检验! p* H) y* U, p% L. E( C- n
Factor, 因素/因子3 T# P, C" @ V* z! m3 W' |
Factor analysis, 因子分析
+ H1 y4 R' p3 B7 Y7 @& ~1 {; ZFactor Analysis, 因子分析
$ B8 R0 l3 l; G: W) L! m5 UFactor score, 因子得分
6 C3 u5 F3 u6 b7 P) @! ] }Factorial, 阶乘
5 D, N8 k9 K7 jFactorial design, 析因试验设计9 ^) F0 S; o+ i& p9 a
False negative, 假阴性% s& y- b8 P2 S5 h. }
False negative error, 假阴性错误! M: x. i! I7 Q- ~! E; q# t% n( R. N
Family of distributions, 分布族6 M+ b2 o M0 ^
Family of estimators, 估计量族
. n- \8 A4 R( G: M! IFanning, 扇面; L5 I/ X' m1 } Z
Fatality rate, 病死率
A. |! i8 k; @9 e0 DField investigation, 现场调查
7 C7 |' ]: m- L; \Field survey, 现场调查
0 c- W6 \3 a3 M6 R' f+ k0 uFinite population, 有限总体
- y3 f9 m( T' h1 K2 E; \( P) QFinite-sample, 有限样本9 d. ^8 \% p: R+ |! X( F3 f& x
First derivative, 一阶导数
0 _0 J& }- y K( Q' PFirst principal component, 第一主成分: s; h) e: C0 b3 @ m
First quartile, 第一四分位数
- ~: y: f, q9 P/ W0 d$ ? ~Fisher information, 费雪信息量
% R; s6 w4 s7 [; xFitted value, 拟合值8 m* W- ]3 _( o) p
Fitting a curve, 曲线拟合
( S& r" N/ {, S. WFixed base, 定基
9 J4 Q0 y- x2 xFluctuation, 随机起伏9 c3 v3 K3 \% ?* P& L4 r" k. r
Forecast, 预测
5 c0 s7 R4 W; o9 \6 v5 j4 WFour fold table, 四格表% |. ?8 U. U$ \& U( r
Fourth, 四分点: U! R! y* y2 ^; t
Fraction blow, 左侧比率
S0 f8 J, y- W% ~/ [+ @ xFractional error, 相对误差' c5 }" |1 b/ e% T
Frequency, 频率
0 D- S- \' N" E6 W4 x# H( YFrequency polygon, 频数多边图, q0 x( ~$ A& r* F# c
Frontier point, 界限点9 H5 A v' Z/ x$ w; F3 J* y
Function relationship, 泛函关系
- ], _/ ]3 H! W2 |Gamma distribution, 伽玛分布$ \ |/ h% z o/ y4 o& g0 J
Gauss increment, 高斯增量
# A' A$ Z4 E* qGaussian distribution, 高斯分布/正态分布
+ K, e- S& h s( {Gauss-Newton increment, 高斯-牛顿增量7 ?5 q' @( U* `) t6 p' v% f4 ~ I$ g! i
General census, 全面普查9 X8 m0 x: O/ d
GENLOG (Generalized liner models), 广义线性模型 . a4 V! ]+ R$ B- D
Geometric mean, 几何平均数
5 P4 L) B$ j ` k, c" J; BGini's mean difference, 基尼均差
4 U+ w* a5 I- `0 N. e1 H/ KGLM (General liner models), 一般线性模型 : X9 ^0 |# t3 M9 |, Q
Goodness of fit, 拟和优度/配合度$ ?% Q+ X! E) I! I# }6 M0 }
Gradient of determinant, 行列式的梯度# v5 ?2 ^8 \- R$ Y' M3 v
Graeco-Latin square, 希腊拉丁方 a( I% S0 N2 |+ G$ X
Grand mean, 总均值- d/ U: y4 n- B0 [# W
Gross errors, 重大错误; p/ A' Q2 i( t. H) y( s; J
Gross-error sensitivity, 大错敏感度
; @4 {5 Z8 E3 T! m) ]Group averages, 分组平均
$ l! F! a1 |3 wGrouped data, 分组资料8 A/ n$ c0 f. ?( V' @6 `+ U$ T3 G
Guessed mean, 假定平均数
5 ^5 O: }+ A' E0 z- d' p/ |5 eHalf-life, 半衰期
+ T+ }* _$ n. t; V% FHampel M-estimators, 汉佩尔M估计量
; [# R: s% t o& {6 WHappenstance, 偶然事件
! H- ]4 d3 r; {. T. L7 rHarmonic mean, 调和均数
3 @+ [6 z3 t6 R- U9 y! k2 d) K% ?; PHazard function, 风险均数) C$ N2 P! m) n9 b/ M. j J# q# Z
Hazard rate, 风险率' I' o: U0 W9 T5 c2 X5 ~- z4 E8 u8 u; ~" d
Heading, 标目 " t& L$ {0 _# ]7 b% T/ h0 H: y
Heavy-tailed distribution, 重尾分布
' q4 ?2 M8 }% V0 RHessian array, 海森立体阵9 m' Y0 a# P9 |/ X# A' r% g8 a1 w
Heterogeneity, 不同质( F3 I% J; p5 z# O- A# K
Heterogeneity of variance, 方差不齐 3 X9 W/ U9 B1 \$ I$ M6 H
Hierarchical classification, 组内分组
4 l, v" ^* Q9 U% p) k4 fHierarchical clustering method, 系统聚类法
) W2 L) a9 ?% G/ eHigh-leverage point, 高杠杆率点
! d! q j# \. M4 \9 K4 a2 DHILOGLINEAR, 多维列联表的层次对数线性模型6 n! I% e2 |+ S9 A
Hinge, 折叶点
0 A# d- n4 s9 `+ |Histogram, 直方图5 ?+ _- l3 O- H0 Y5 |1 A
Historical cohort study, 历史性队列研究 2 C* R* Z4 q, ` Q' k+ j: {4 Y
Holes, 空洞
" z2 h* Y" k; g& PHOMALS, 多重响应分析
3 p8 ^% b! b- w6 W+ @Homogeneity of variance, 方差齐性+ n$ H+ s" \: B5 \& d( g3 ]. ^
Homogeneity test, 齐性检验. O$ r! ]) w0 f7 Q
Huber M-estimators, 休伯M估计量" f9 m) u/ f! g* ?, e* O
Hyperbola, 双曲线2 H& G; }# N; h- R2 o. D
Hypothesis testing, 假设检验, h0 {5 q) a2 |. Z/ z# w
Hypothetical universe, 假设总体, I7 T7 H" E. Q& C% O1 p6 d
Impossible event, 不可能事件& l) {1 [4 ?& e- U& _
Independence, 独立性/ X7 {) e X2 c! m$ _8 o
Independent variable, 自变量5 t% O* D! W) t9 k9 F4 ~ a
Index, 指标/指数
: W( Q" S i9 }8 @8 GIndirect standardization, 间接标准化法
) @3 b& r( h1 x& s" P, iIndividual, 个体6 z( z* g. d* d! e7 H8 x
Inference band, 推断带" H X) d. x4 {, H) E- b/ V
Infinite population, 无限总体$ Y Y6 r0 w4 V) o; ^4 J' }
Infinitely great, 无穷大( D$ S; a+ j1 a. T% s0 h
Infinitely small, 无穷小
' w+ {( Y5 i1 c1 UInfluence curve, 影响曲线# [0 b* n# s M" X4 m
Information capacity, 信息容量" N: @$ N* l$ I4 l% {* E8 q
Initial condition, 初始条件
8 ]! X1 V1 c) pInitial estimate, 初始估计值: y& M$ U% N. V) }% [. X( h
Initial level, 最初水平
$ ^& d8 h, }$ L( J: D% oInteraction, 交互作用
/ |, ^0 U, g& N" a: x. TInteraction terms, 交互作用项7 S6 Y9 c7 P2 S r* r u4 p ?
Intercept, 截距
' C# B' U* D3 H$ d" N+ b7 Z- ZInterpolation, 内插法: W- y8 G, ^3 o6 Y( [
Interquartile range, 四分位距
3 o2 F! {. d0 \* `. j- g* E# wInterval estimation, 区间估计4 y3 x/ C. Y( q: |5 e _9 R
Intervals of equal probability, 等概率区间- `& z& f' s" e3 k3 W/ E
Intrinsic curvature, 固有曲率& Z& G% Q E' G) w6 u" J
Invariance, 不变性4 d+ r* b H4 m- @( H
Inverse matrix, 逆矩阵
! J3 V7 v- ^" v- J8 ~9 c lInverse probability, 逆概率- X* B" f& W( {! j5 }
Inverse sine transformation, 反正弦变换
( N9 L8 I% Z' Y1 A, n1 r+ gIteration, 迭代
: c5 i2 e3 Q" k6 LJacobian determinant, 雅可比行列式+ v. f4 D- A- }9 K
Joint distribution function, 分布函数7 e. b0 s1 m) l
Joint probability, 联合概率, W5 f4 T7 O Z% F" W( Z- [
Joint probability distribution, 联合概率分布
/ `6 ^5 U H, P- C" _& M4 hK means method, 逐步聚类法- X$ E7 e8 ]$ B: B. S- g
Kaplan-Meier, 评估事件的时间长度
5 M" b& H6 Y* j0 E4 hKaplan-Merier chart, Kaplan-Merier图
W- j/ r* @2 u9 `" g, wKendall's rank correlation, Kendall等级相关$ s! p( F2 y5 o
Kinetic, 动力学
4 ^. R+ a U# R# a% bKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验! I0 v4 t, z9 X4 ~' e+ ?5 d- w
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验. ^& z2 c% u! f
Kurtosis, 峰度
$ n( P# Z3 o& I* E4 ?7 o1 jLack of fit, 失拟* W) b' H. {0 r! n4 D
Ladder of powers, 幂阶梯. n/ X# E) W+ q% I/ @7 w/ L, S
Lag, 滞后
1 s" I8 g4 O4 k1 n, P2 n# GLarge sample, 大样本% j$ O! a- w' S3 i1 i& S8 v, Q
Large sample test, 大样本检验/ |" [% T/ K" I, b, T
Latin square, 拉丁方
0 h) ~# ^! H8 p5 p, F+ U% \Latin square design, 拉丁方设计
2 T, ?4 i, r- E) s) k; \Leakage, 泄漏& G% u4 {9 k% Y, O- @. S
Least favorable configuration, 最不利构形
# e( [8 `. K/ a8 `" y6 T% Y: DLeast favorable distribution, 最不利分布
( r9 l% }+ a f: Y# DLeast significant difference, 最小显著差法$ Y2 j! r: U7 f% C2 p+ A6 ~% J# \
Least square method, 最小二乘法
9 |$ f$ n3 Q# N, ], r5 i3 h6 [" \Least-absolute-residuals estimates, 最小绝对残差估计
+ ` \" v$ g$ s2 vLeast-absolute-residuals fit, 最小绝对残差拟合
0 m7 l% M# @! V+ a7 j' E6 |Least-absolute-residuals line, 最小绝对残差线
( _" F5 g8 ]2 aLegend, 图例
L6 Q3 C M! o0 C" O% y% }L-estimator, L估计量5 r. ~, u" j* c8 S
L-estimator of location, 位置L估计量
; R+ a( ~" h6 O8 OL-estimator of scale, 尺度L估计量! M0 D) r/ G- ]& S; h* f8 i5 a7 \
Level, 水平
' b8 r; F* t- xLife expectance, 预期期望寿命" {/ r2 J) K* j/ [
Life table, 寿命表
9 M$ z+ ^1 o. g- S! y( N" eLife table method, 生命表法/ z+ I! y3 G3 Y
Light-tailed distribution, 轻尾分布
( V8 Z/ v' p# H6 P& M# LLikelihood function, 似然函数
' q5 D/ |+ u+ TLikelihood ratio, 似然比, `5 m8 o2 F% L* t# n% a
line graph, 线图' h7 j1 d/ D, S/ }7 M
Linear correlation, 直线相关/ P, \+ A z. @6 l: q
Linear equation, 线性方程
, g! n r- S9 h) _0 H lLinear programming, 线性规划
" r3 U# l2 e. S$ Q! {$ X/ ]Linear regression, 直线回归
6 O7 ^9 p. E! P0 R$ U5 _Linear Regression, 线性回归1 w5 w* y7 O( G# Y" g" b
Linear trend, 线性趋势- x2 Q8 S* l- N8 L! `% N
Loading, 载荷 0 o Z2 y& u; A' j5 L& Z
Location and scale equivariance, 位置尺度同变性
2 b2 L$ i9 U( P7 ILocation equivariance, 位置同变性$ j! A4 e3 V& y4 X# I' K7 H/ p
Location invariance, 位置不变性$ |" C8 C5 N5 E
Location scale family, 位置尺度族
$ H! c& I# d7 P2 [+ v2 xLog rank test, 时序检验
8 _, z! Z& Q# W5 T$ L3 gLogarithmic curve, 对数曲线' G! x9 y0 a8 {
Logarithmic normal distribution, 对数正态分布
* ?- W8 h* O1 b' jLogarithmic scale, 对数尺度
& j, K- ^6 R$ E7 G& RLogarithmic transformation, 对数变换
" F2 I8 g, {9 S! [% a) r) y( ~Logic check, 逻辑检查
) ], v! l' ~# B. R% v9 @# J& n; }( ELogistic distribution, 逻辑斯特分布
c' x ^$ ^% O( j' GLogit transformation, Logit转换
- h" X4 O5 i5 M, K" K+ ?/ D7 H& MLOGLINEAR, 多维列联表通用模型 ) o! v9 e$ p) X4 u& k
Lognormal distribution, 对数正态分布
/ ^; J. K. u' {' HLost function, 损失函数
- ?8 u8 |; b5 x7 K# n0 XLow correlation, 低度相关
: I+ a7 Q( K0 T% V9 SLower limit, 下限6 n! U: l- A0 N1 V- |) G4 k' u7 S
Lowest-attained variance, 最小可达方差& k9 L* d9 s) R! F0 a, [" ]
LSD, 最小显著差法的简称* ~& [ p4 ]! A z1 ]4 [
Lurking variable, 潜在变量, Q$ u! k5 z( n
Main effect, 主效应
* M& J8 N, |; y3 c/ G- pMajor heading, 主辞标目
* Y+ x1 P/ b) ?Marginal density function, 边缘密度函数% l7 ^) Q( S: N2 \" P) ^
Marginal probability, 边缘概率
3 u! `, E( f. C0 P' IMarginal probability distribution, 边缘概率分布0 b5 Q* k( _1 H9 {$ t* i
Matched data, 配对资料
3 ]1 g \3 z" A2 _3 sMatched distribution, 匹配过分布' _5 l+ e/ C! Y% l' G/ |
Matching of distribution, 分布的匹配
j( r6 a1 h2 v/ AMatching of transformation, 变换的匹配
; u' k4 u" u, X: }Mathematical expectation, 数学期望
) ?$ Y2 b1 ?) e) F' ^ E& U9 @) EMathematical model, 数学模型- O- r4 F0 z2 Y1 U# D
Maximum L-estimator, 极大极小L 估计量
3 V! Y* d7 v. c5 S5 gMaximum likelihood method, 最大似然法
" r8 @$ U5 g% r# `; C" jMean, 均数8 \& N- F1 _, o3 x6 M3 G6 Y( v
Mean squares between groups, 组间均方! ?1 q+ ~# h1 g1 T
Mean squares within group, 组内均方 R; e5 o) I% t# A
Means (Compare means), 均值-均值比较9 x w7 j; b# S) ]2 f* j8 m! }# k
Median, 中位数
9 z% t' D/ ~6 e6 Z/ @$ i7 b0 A& UMedian effective dose, 半数效量) }$ I6 I+ \& c7 ?+ K! h
Median lethal dose, 半数致死量5 C! l2 o- v4 l1 g* k# C6 y
Median polish, 中位数平滑- v- S+ u8 V/ @& P: C6 Z
Median test, 中位数检验
% \; t4 J+ x* U% B5 L u5 [9 W$ bMinimal sufficient statistic, 最小充分统计量1 D( m0 `' M: Z
Minimum distance estimation, 最小距离估计
$ g: x/ B/ r& }% BMinimum effective dose, 最小有效量3 f$ |4 F; R5 P; \" r0 |
Minimum lethal dose, 最小致死量9 z0 ?) F. H' H' G
Minimum variance estimator, 最小方差估计量
- x6 Z4 _! P# b7 j! o: v. yMINITAB, 统计软件包4 V- ~3 M/ H% D j
Minor heading, 宾词标目. U$ m0 t1 ~+ N4 `0 F$ I( Y
Missing data, 缺失值, S J7 ~+ C, l) a1 B
Model specification, 模型的确定6 o/ w: X/ n3 o1 M: U
Modeling Statistics , 模型统计
/ @" ^0 Q3 J5 x! W7 YModels for outliers, 离群值模型+ P4 Z; f6 U6 I" r
Modifying the model, 模型的修正
9 {7 w, D5 w3 m+ ?+ [' t; ZModulus of continuity, 连续性模
; k2 N0 m+ D) `, A- K( t7 _2 qMorbidity, 发病率 % M: S3 `% `5 r/ _8 a5 {
Most favorable configuration, 最有利构形
, ?( a4 F- d5 i! K' n8 X7 l* SMultidimensional Scaling (ASCAL), 多维尺度/多维标度
0 A4 B9 p6 e7 Z) o4 W; Q- W, k" `Multinomial Logistic Regression , 多项逻辑斯蒂回归- ?6 E, C% T, `" ~# J: ~( j4 J G3 y
Multiple comparison, 多重比较
1 j, \ W1 ~/ L" K Z$ s$ q( ~: JMultiple correlation , 复相关
/ G' ]3 d" S5 `" E3 {1 a* [" d. BMultiple covariance, 多元协方差
; w4 i: m- j0 ]) CMultiple linear regression, 多元线性回归
9 e1 r5 c: |+ x: V' z. x3 x0 I) `Multiple response , 多重选项& S0 V, ? p7 c6 S Z2 A
Multiple solutions, 多解* [* ~, ?+ r. F5 c1 @2 k$ o
Multiplication theorem, 乘法定理
9 L1 z( J/ d( H, L8 NMultiresponse, 多元响应! X7 s; W2 H' `( B3 T- F3 r* K
Multi-stage sampling, 多阶段抽样
0 u, \+ Q9 @2 M5 xMultivariate T distribution, 多元T分布, n' @& s# g$ O! s- ]7 A
Mutual exclusive, 互不相容
& X% H( \- T5 g) \+ nMutual independence, 互相独立* }, {1 X( \& ]7 U4 p2 |9 U
Natural boundary, 自然边界
3 [5 C/ X1 T9 C1 rNatural dead, 自然死亡9 J A* S/ L% c% G
Natural zero, 自然零+ g$ T0 u# d" \9 B
Negative correlation, 负相关' _( g2 R$ N# X6 a
Negative linear correlation, 负线性相关
$ {2 z4 |. N6 u5 j3 y% _8 {Negatively skewed, 负偏
8 C' Q& u1 H% |5 y0 GNewman-Keuls method, q检验
- {# C7 _# t, b' U0 A! o% vNK method, q检验1 R: N' M+ H W* _. D# B' }; {
No statistical significance, 无统计意义
) q8 E) z# z' n: `Nominal variable, 名义变量
1 K9 Z& o0 Z* m; ^; DNonconstancy of variability, 变异的非定常性
( R+ J( I) A+ p O2 f" ONonlinear regression, 非线性相关! J2 k# v: ]9 G; a6 s2 l
Nonparametric statistics, 非参数统计- j% h! x! U" F6 a( F4 ]8 O" I
Nonparametric test, 非参数检验* H: a! q3 c; k( a
Nonparametric tests, 非参数检验, x5 y/ `8 ]+ {
Normal deviate, 正态离差
) D( B% c) d+ x7 l" \Normal distribution, 正态分布
5 d7 P( r' N/ R' y% ^5 V6 G2 pNormal equation, 正规方程组1 `9 @" b& \7 D
Normal ranges, 正常范围1 @: ]; L% P8 \* }
Normal value, 正常值' K: L% w- f. R1 n7 Z9 }
Nuisance parameter, 多余参数/讨厌参数( C2 E" `+ F* [/ Q/ O
Null hypothesis, 无效假设
8 S3 T4 H* g- ? p( E% oNumerical variable, 数值变量
6 r5 j; g" i+ x8 {Objective function, 目标函数/ \' B7 `# M3 w! P- K6 b) Z
Observation unit, 观察单位 M% ?* s& x3 e% U& [, G8 q
Observed value, 观察值
- w( }9 Y8 b8 y6 ~0 n" LOne sided test, 单侧检验
' l2 l- j: f _. Z% h, G) NOne-way analysis of variance, 单因素方差分析
' z# g# F5 z6 OOneway ANOVA , 单因素方差分析" x+ G) u/ b: E; ?) [( v
Open sequential trial, 开放型序贯设计! h0 j; N' b+ c' J
Optrim, 优切尾
# D" L8 l5 x g8 X, o, m1 @" uOptrim efficiency, 优切尾效率
9 N4 _1 F6 }7 p$ v" ^ dOrder statistics, 顺序统计量
: {) H2 J( h3 ?* X, x$ x W# wOrdered categories, 有序分类
8 a" x, @6 k/ XOrdinal logistic regression , 序数逻辑斯蒂回归
. g# S( N" Y; K, O1 [5 u0 YOrdinal variable, 有序变量 A0 |9 ^5 T# k. |' l" i
Orthogonal basis, 正交基
$ I6 c& D7 x8 z0 K+ _: V! nOrthogonal design, 正交试验设计- a( p" R5 V4 V3 i) B
Orthogonality conditions, 正交条件
) F' @ e" ?2 i. cORTHOPLAN, 正交设计
/ P1 a2 ^* m7 [$ I2 _Outlier cutoffs, 离群值截断点
; M3 x5 C8 ?0 Z: Q$ n; GOutliers, 极端值
! P6 Q5 m% G& ^" z9 N3 @OVERALS , 多组变量的非线性正规相关
- P8 b0 f4 e+ s+ AOvershoot, 迭代过度2 c- a4 ~; S$ W' ^1 h
Paired design, 配对设计
% ~; v1 f/ o- k! TPaired sample, 配对样本
6 ?: b$ ~) d7 O5 R5 S6 F% ^Pairwise slopes, 成对斜率: f7 I, ], P/ [3 `
Parabola, 抛物线% `! I/ w( }: r! E, I" J+ K( q
Parallel tests, 平行试验% E5 W( F# N% g O2 x d! {
Parameter, 参数/ I/ b: S6 a1 z- U0 S, ~1 q- ?) l
Parametric statistics, 参数统计: W( b3 ]# k' [8 H( ?8 Q: w
Parametric test, 参数检验* ~) I4 |+ D. v4 b) ~' e* o
Partial correlation, 偏相关
: e8 o, j. y0 O& Z) @Partial regression, 偏回归
% Q2 X( m' }% P/ F, w% |3 k+ Q5 DPartial sorting, 偏排序7 m# X' n0 R& `
Partials residuals, 偏残差$ W9 }' h- q9 R9 x, Y7 F
Pattern, 模式. i* l( w+ O% V% ?7 J
Pearson curves, 皮尔逊曲线
0 e' V% U( @. o6 x. r, LPeeling, 退层
2 `$ _# T# D/ W" j( zPercent bar graph, 百分条形图
- {3 X9 {# J; t- w/ S" M/ PPercentage, 百分比, L v' c0 ~/ e! y, _6 r, k9 l
Percentile, 百分位数* y1 Y) w- d) v' c2 H
Percentile curves, 百分位曲线- ~9 d& n5 D% y* {+ g0 x7 `2 D4 U
Periodicity, 周期性
1 Z& Q6 W; F) j# O( p/ m; ?Permutation, 排列* B1 X L7 \+ c8 x% ^# x
P-estimator, P估计量
" Q+ u; ?( S: {- r0 @4 u& D# YPie graph, 饼图5 }4 C8 S. R, O( g2 E
Pitman estimator, 皮特曼估计量
/ Q2 V' a4 N$ e. D4 r4 y6 FPivot, 枢轴量) r0 p% ~, ?# G+ ^5 f' W
Planar, 平坦
: q% o; l- B, Y: h% \Planar assumption, 平面的假设/ [6 {4 A P. g
PLANCARDS, 生成试验的计划卡( l! U! Z6 e# Y; \& d' k
Point estimation, 点估计$ W. q& C& ~: h$ J' ]4 E
Poisson distribution, 泊松分布
. {9 o3 p, O8 e7 I; Q2 OPolishing, 平滑
! y1 Y/ r* R8 @/ B- b NPolled standard deviation, 合并标准差
0 b5 Y6 V+ q" ] |6 @( MPolled variance, 合并方差! I* @# s" Z, G' T: w$ y( c
Polygon, 多边图
# q4 v @" g- J' [Polynomial, 多项式
0 m' g4 h' z+ a1 H) @8 b0 ZPolynomial curve, 多项式曲线
1 n; Y% N w: j8 _; I: N. K/ h5 @- {Population, 总体. h& [; s: [6 E% w& ]
Population attributable risk, 人群归因危险度+ m I6 u! x2 T+ I! Y8 ^% ^ U
Positive correlation, 正相关) g/ i' U' U; h; ]
Positively skewed, 正偏; `; A9 Y( q1 s9 k# `/ m+ E: e
Posterior distribution, 后验分布
5 Y& R: T9 r, A: G I! H- D8 JPower of a test, 检验效能" P) f# J; r% P" I" x, b
Precision, 精密度5 G W) h) R6 N- U% d8 A" {
Predicted value, 预测值
1 W2 N$ i3 b0 r, ?Preliminary analysis, 预备性分析
$ }& v0 ^$ ?, x' `( q0 UPrincipal component analysis, 主成分分析$ n( s; e7 h8 b9 [, T
Prior distribution, 先验分布
$ h. @9 ]9 N' \; V4 {' dPrior probability, 先验概率
. z3 T6 |. A% ~- {7 fProbabilistic model, 概率模型
& }5 {7 [0 y& l; _( Dprobability, 概率* @8 E8 D9 B! d8 J. R, J
Probability density, 概率密度$ S& Y; c$ @6 s5 _- I5 I
Product moment, 乘积矩/协方差
& L; W+ Y+ Y! J' qProfile trace, 截面迹图
7 o& J; W ?3 mProportion, 比/构成比
; ^, R N- S' {3 P" zProportion allocation in stratified random sampling, 按比例分层随机抽样
' T/ D0 Q2 Z; X$ Q/ b% SProportionate, 成比例
1 F2 O R. c/ m4 U" V5 wProportionate sub-class numbers, 成比例次级组含量
l9 \6 Q1 L' K& E! ? M4 pProspective study, 前瞻性调查
! K7 H6 J+ Y. Z6 J8 eProximities, 亲近性
! B: I# y$ J! V1 e, l& sPseudo F test, 近似F检验6 B8 l0 J7 q; }; H' C
Pseudo model, 近似模型& p' v1 G: h( o' I; [$ B7 D! J
Pseudosigma, 伪标准差
1 N3 q9 u/ w: `& iPurposive sampling, 有目的抽样. z$ x( s% j6 e% u7 k3 l) t' R
QR decomposition, QR分解7 n6 g, {, a; K
Quadratic approximation, 二次近似
) I5 x5 _& k% d Z6 N' q! aQualitative classification, 属性分类$ y8 T! E' n" W7 u& |
Qualitative method, 定性方法- Q( O! v( H2 C2 ] f
Quantile-quantile plot, 分位数-分位数图/Q-Q图; ?' j( e0 J B2 t5 f
Quantitative analysis, 定量分析 j+ @) g8 D* n" o: h
Quartile, 四分位数/ C/ ?3 `) E0 h. m
Quick Cluster, 快速聚类
N6 _& n1 J/ }" w0 ZRadix sort, 基数排序: t& e7 H. ^; C+ E0 n# G
Random allocation, 随机化分组
5 U% v7 L+ ~$ C! m+ GRandom blocks design, 随机区组设计, f5 d5 p( P' q+ y2 ]8 G
Random event, 随机事件7 k% E$ ]6 L/ m5 z% M4 n5 C3 b
Randomization, 随机化9 ]- ^3 \" O% W0 ~/ Q" Q
Range, 极差/全距
5 }/ l8 G9 b- h" u J. Y1 f! ARank correlation, 等级相关
( C4 d" i. w* A6 ~3 m( X5 zRank sum test, 秩和检验9 u, Y5 M; l+ P4 L& F
Rank test, 秩检验, l! n7 e2 k% N$ R9 R: G% q Y# @
Ranked data, 等级资料
: t; ~2 h( n3 C, j$ L7 ]& [Rate, 比率
; D6 T% p) H, u; F* CRatio, 比例& x5 j9 `/ `; i# W w5 A" A/ l
Raw data, 原始资料
5 C& a. s2 ]0 I1 ^, G: F0 X& ZRaw residual, 原始残差
: r! y4 J. I; {1 V2 ]Rayleigh's test, 雷氏检验& o( O( c: X. d F. ~
Rayleigh's Z, 雷氏Z值 3 i$ R; F, c) h6 h; @
Reciprocal, 倒数
# b( ]3 X: E' `9 O, X+ ZReciprocal transformation, 倒数变换1 Q- F3 D7 _/ ^. {# j
Recording, 记录
( M- w4 @& g& `- Z* @+ U3 ^Redescending estimators, 回降估计量
) s @0 b/ | a2 J+ WReducing dimensions, 降维( B* T" E1 R: n5 n P
Re-expression, 重新表达. D. G; G' r' z: w9 M4 m3 t) |& L
Reference set, 标准组
- L; F3 t; u: z2 J7 d) u) [; V# \Region of acceptance, 接受域$ E7 ] ~5 m0 _$ S% q7 T/ ~" Z. z
Regression coefficient, 回归系数8 M& t, B& |1 q, y3 O, j. `
Regression sum of square, 回归平方和
$ ~, r5 G! |7 r6 rRejection point, 拒绝点
2 S( O. A" ~; u" BRelative dispersion, 相对离散度
S" [, n. A3 ?Relative number, 相对数+ Q' d, p% e- X% Z
Reliability, 可靠性7 O6 e! f, Z; H$ W- c# @. d3 ^7 Q
Reparametrization, 重新设置参数
- Q" @5 S, J% R2 [Replication, 重复
1 T$ [$ \" l5 HReport Summaries, 报告摘要- m' s' a y* l# c ]6 v
Residual sum of square, 剩余平方和# w# ? C5 W9 O$ x" j3 a: f
Resistance, 耐抗性
. Z# L) P8 f" z0 F+ E! kResistant line, 耐抗线9 b' S# }1 s8 }& m
Resistant technique, 耐抗技术
[5 R. ], ?' @6 r4 ZR-estimator of location, 位置R估计量
% C* `$ p8 d3 Y0 x7 iR-estimator of scale, 尺度R估计量; P# _, H$ j8 `$ h) p
Retrospective study, 回顾性调查
+ U: T) i: @5 P2 \Ridge trace, 岭迹
6 I! X5 M* F1 q6 K4 QRidit analysis, Ridit分析
2 f3 H+ {+ G1 u" @5 \Rotation, 旋转
# p! F7 Q, K+ f6 p. c6 m8 nRounding, 舍入
1 Z- y% |: Y( i# \$ c$ B8 E3 sRow, 行
A4 m+ s7 m! X7 x* q1 m, g$ u. mRow effects, 行效应
& V0 B+ |- t5 ~2 E6 ^& p) p; qRow factor, 行因素
3 n8 ~6 }6 }. p9 HRXC table, RXC表2 ]9 u) V9 p* v6 k7 g8 U: G: N
Sample, 样本! h8 W7 z) b- }9 l# d: u+ F
Sample regression coefficient, 样本回归系数+ _0 l- |) H' E9 ]; B2 n" [2 P- X2 W4 E
Sample size, 样本量0 U5 [* m' i- p3 l) O
Sample standard deviation, 样本标准差& @ d n4 N9 O. g, Q
Sampling error, 抽样误差
; _# ~" d$ T. `$ y: `$ i2 JSAS(Statistical analysis system ), SAS统计软件包
/ s$ ?. {* Y% U, l B5 MScale, 尺度/量表! r" A( o5 p" h R" i" Y
Scatter diagram, 散点图
( }& u2 L4 U9 t& L8 tSchematic plot, 示意图/简图
6 t! f! t# w2 PScore test, 计分检验
% ]" y) Z% a- GScreening, 筛检
( s4 v' P# s q6 [3 T4 g' J) vSEASON, 季节分析 ( H, s( R! u2 [
Second derivative, 二阶导数
; Y" w! H1 ~% Q5 E% b1 T5 eSecond principal component, 第二主成分% M* ]9 p) j# _& i9 a: J
SEM (Structural equation modeling), 结构化方程模型 : I4 v8 Q/ U+ K/ N \6 F
Semi-logarithmic graph, 半对数图
, X- z- G) Y# ]3 iSemi-logarithmic paper, 半对数格纸$ H2 I% ?! ^" k4 q- T% T
Sensitivity curve, 敏感度曲线
1 i2 ~) O/ u) e' i6 DSequential analysis, 贯序分析
: c1 P" C# u( Q, X9 V+ E, a. _" p0 rSequential data set, 顺序数据集: @$ N: S: Y4 q$ }. W( U4 d
Sequential design, 贯序设计7 ~ p7 V: U P1 R( {
Sequential method, 贯序法
0 a- y( o @' {" A& J& |Sequential test, 贯序检验法; y$ [# k$ ~* w9 U/ s0 q
Serial tests, 系列试验
8 R& C8 q3 ] V: l" N" F' uShort-cut method, 简捷法
! h+ i/ v* J( X6 \4 a$ h5 nSigmoid curve, S形曲线% y/ _. q1 F+ Q
Sign function, 正负号函数4 {4 u5 Q+ D6 X! g
Sign test, 符号检验3 X! r; p3 r, @! x
Signed rank, 符号秩. u5 W( v6 L$ |' @
Significance test, 显著性检验
7 X/ x# B: x* U5 k9 \5 KSignificant figure, 有效数字
* P/ J2 i9 o! Q, G+ \Simple cluster sampling, 简单整群抽样3 s L. e2 L* D8 k z F4 ^/ U
Simple correlation, 简单相关
( O: w; J! C9 e7 ESimple random sampling, 简单随机抽样
% u+ l5 u3 U1 }0 C1 TSimple regression, 简单回归
3 E' ^" `1 O V5 T& xsimple table, 简单表) m2 S2 W4 T) L; W3 T
Sine estimator, 正弦估计量, q8 g$ j% C0 A1 m) Q- o( O6 t$ j1 R
Single-valued estimate, 单值估计
3 [. N5 d9 a5 b5 B5 _$ d6 hSingular matrix, 奇异矩阵+ Y5 @) u8 D3 \& W
Skewed distribution, 偏斜分布, N7 j2 @' E! s; H0 Z1 x: R' J
Skewness, 偏度4 J# {4 d) c. Z: I/ V: K2 j
Slash distribution, 斜线分布
+ q% [. u6 e$ ~& W* J3 d: }Slope, 斜率
: A5 J% |. E/ ]1 o) N2 SSmirnov test, 斯米尔诺夫检验1 \' ]3 j$ S+ ~$ ~1 Z
Source of variation, 变异来源
$ k. W; a. C p1 p, `5 z! @Spearman rank correlation, 斯皮尔曼等级相关
- x1 g: v+ A3 S5 mSpecific factor, 特殊因子; t& @& X6 v; J/ c0 B O& E p
Specific factor variance, 特殊因子方差
( }: g7 Z3 d2 k2 I/ b+ tSpectra , 频谱 \2 ?( A+ u# l+ [ x E
Spherical distribution, 球型正态分布
3 D$ M; _( _: M- l& I2 R* Z0 ~Spread, 展布
& c( o5 R& C0 j1 d! j4 ?SPSS(Statistical package for the social science), SPSS统计软件包5 i' }! H3 O6 {% n
Spurious correlation, 假性相关* j3 u0 a4 f; h0 e) T6 Y& c7 B
Square root transformation, 平方根变换3 G7 I( p5 F2 E( F
Stabilizing variance, 稳定方差
% c+ l. Y. A4 r! xStandard deviation, 标准差
4 a3 s9 J ^1 O, I2 p: j/ o! MStandard error, 标准误! ]2 G) h! @2 \1 M5 [9 Y. q6 I0 n
Standard error of difference, 差别的标准误
* S0 w* O3 q2 c: b. xStandard error of estimate, 标准估计误差
% L' U1 z/ l: o- C5 L9 NStandard error of rate, 率的标准误0 u/ y7 N! y' G( y- p
Standard normal distribution, 标准正态分布5 m! x6 R! t) r% e' D% u- Q
Standardization, 标准化
0 ^6 x! t- Q1 M( Q0 X" @: i V% PStarting value, 起始值3 e( K/ [9 q# h
Statistic, 统计量7 V! x8 N+ X* M3 O6 V
Statistical control, 统计控制
! @/ \0 G; d( h$ LStatistical graph, 统计图
* U: z3 [$ E# o; oStatistical inference, 统计推断
2 j- k% z: w2 {& g; u% ^Statistical table, 统计表& s# ?7 v. `0 N# ]' s- n
Steepest descent, 最速下降法
7 I$ R+ X+ G+ V' @* v7 wStem and leaf display, 茎叶图$ h" Z% ?2 r& N8 `/ l$ M
Step factor, 步长因子: f8 F+ a6 L: e5 z( Y; G3 q
Stepwise regression, 逐步回归) \! ]8 e/ t, ?3 P% b* W3 s
Storage, 存
7 F5 H& V6 ^0 I. YStrata, 层（复数）
: o7 D( {, p2 o3 l9 x( F/ W3 C' s8 y/ SStratified sampling, 分层抽样, r1 F) w2 K( h2 V6 m+ c! U6 G
Stratified sampling, 分层抽样! B) _' q1 i" I( B: _3 j
Strength, 强度) s+ ^7 M+ u7 i; M6 H, \, @! r
Stringency, 严密性
G7 n' R) \, A% P! v. l, E, \Structural relationship, 结构关系" G. Z, U( } g& t* b% C
Studentized residual, 学生化残差/t化残差
@' k3 y- P& u9 g5 d+ A& |/ v- DSub-class numbers, 次级组含量
& J5 l9 i- `1 z; t8 sSubdividing, 分割
, c" o( u) l* t3 F- VSufficient statistic, 充分统计量
O1 f& [( y% ?/ ~" Z/ |Sum of products, 积和
. ~. n3 V5 p* D8 K+ JSum of squares, 离差平方和7 d9 i) B! ~+ q8 X7 x
Sum of squares about regression, 回归平方和
: d! g+ i! v, [5 \$ rSum of squares between groups, 组间平方和4 v' f( ?7 Z4 D1 G
Sum of squares of partial regression, 偏回归平方和# f, B/ i9 A0 a# s. w8 e
Sure event, 必然事件. H# j: H f, f" l! y) _' W( ~
Survey, 调查
+ Y# F7 t$ F& {& Q- fSurvival, 生存分析5 ` l; h) L1 ~
Survival rate, 生存率# L' U4 W, g; B& R6 {3 t' |5 ]
Suspended root gram, 悬吊根图
: X: w: O1 |" g+ |$ bSymmetry, 对称
% f5 k( z/ w0 t4 j# ?/ D3 ]7 N+ OSystematic error, 系统误差! P9 h1 V: w( b* g* w
Systematic sampling, 系统抽样
9 l, E9 I( i( XTags, 标签5 }# i9 g. d& m; t6 m+ l
Tail area, 尾部面积5 e6 ^% m& g! _8 @5 \2 j
Tail length, 尾长9 K& ], ?5 \$ Q+ q" x j1 `- v
Tail weight, 尾重
. ]/ n& I+ d% S8 hTangent line, 切线- P3 |5 S4 R' W+ m+ p/ m+ ~7 ]
Target distribution, 目标分布6 N7 S3 V/ x- P
Taylor series, 泰勒级数$ i2 Y+ ~( G) X( G
Tendency of dispersion, 离散趋势
2 K( v6 W% X7 Z5 K7 }4 f9 jTesting of hypotheses, 假设检验8 `: n2 I7 I; `5 T
Theoretical frequency, 理论频数
# o; ?& W$ a5 c! {0 j0 M9 zTime series, 时间序列
, y0 G3 M# U2 ]' q* S7 GTolerance interval, 容忍区间
* I q! G$ e/ k) h2 N7 STolerance lower limit, 容忍下限+ h+ T6 G$ a* W7 s9 n
Tolerance upper limit, 容忍上限
# h7 ^& r2 p4 L% bTorsion, 扰率
0 Q( u9 t; d. T/ QTotal sum of square, 总平方和" @$ [% ~& p c7 } M" s# a) F* a# `
Total variation, 总变异
- m* {4 A% D% t% z; wTransformation, 转换
- }. {; u. Z" X9 I3 L5 g) |Treatment, 处理
4 E& h- n2 U+ aTrend, 趋势
& c6 E5 g' o' c3 j: OTrend of percentage, 百分比趋势
' e+ N, [5 e3 t. @Trial, 试验- c, y% ~- ]# K1 W
Trial and error method, 试错法$ @( f% }4 v0 y, A9 I0 j1 d# b
Tuning constant, 细调常数
( m: w5 G( b' s# S! {: \ j4 ?Two sided test, 双向检验. N4 Z, [# p7 q7 k& r* `! a
Two-stage least squares, 二阶最小平方! _! x( i$ B5 J: W+ O( u) @
Two-stage sampling, 二阶段抽样2 i0 ?! {" C! K* ~ [1 c
Two-tailed test, 双侧检验' o4 Y. b5 P' T; ] M
Two-way analysis of variance, 双因素方差分析" c+ }0 r7 ~# o* H
Two-way table, 双向表" }+ N3 Z: k$ t6 c' x& Q9 H! \# c
Type I error, 一类错误/α错误
8 y2 `7 T: @" s$ h( z5 l5 j+ }Type II error, 二类错误/β错误" ?4 h0 F' j1 U% r4 b4 u8 S1 }
UMVU, 方差一致最小无偏估计简称2 m, o2 W2 d2 ]# c
Unbiased estimate, 无偏估计9 U. n# p7 \3 Y* g: V b( G
Unconstrained nonlinear regression , 无约束非线性回归
% A% I6 S0 _5 u4 P* KUnequal subclass number, 不等次级组含量+ [7 \/ ?: _$ Z: K6 X5 L/ w
Ungrouped data, 不分组资料
; D/ Y" P5 d$ g) Z3 S% @1 O' `# VUniform coordinate, 均匀坐标* U! o; [+ R3 X6 }9 g4 |% X
Uniform distribution, 均匀分布/ G* R3 ?4 p, e+ ]8 F
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
( D# K% T9 z- Y9 z; kUnit, 单元* ~! X7 T8 {" K
Unordered categories, 无序分类* N. R' f. G2 M7 C
Upper limit, 上限9 @2 z1 P' A. B' q$ [% V
Upward rank, 升秩9 L* V( X+ A+ [( @4 l# N; R
Vague concept, 模糊概念
1 h8 L2 I0 W+ n* yValidity, 有效性 @$ @+ B( {) q
VARCOMP (Variance component estimation), 方差元素估计# V; A$ K( F5 X$ S( b6 n7 \
Variability, 变异性
; u/ W$ o) v. j9 `* u, NVariable, 变量
. v' P+ l6 h: q6 z* n2 |Variance, 方差% t; c, ^) ]2 |& ~ I7 z" i" t4 j
Variation, 变异0 K4 u+ h" n1 p4 u
Varimax orthogonal rotation, 方差最大正交旋转. p/ h% [, I; A
Volume of distribution, 容积! U& @5 b! @5 }2 Q& a; L3 v1 G
W test, W检验' ^0 N% ~5 P1 {6 A
Weibull distribution, 威布尔分布6 Y! Y6 {0 |! t/ Y
Weight, 权数
9 I# Z1 k. K3 g- Z: NWeighted Chi-square test, 加权卡方检验/Cochran检验
" Y! q: n0 Z! o6 D' R; OWeighted linear regression method, 加权直线回归
3 G& t) t$ T9 c* [Weighted mean, 加权平均数
* g) F" _# v7 q7 w# D. v# b TWeighted mean square, 加权平均方差- P$ N- { A1 q8 o
Weighted sum of square, 加权平方和
4 |+ n5 K& g8 v4 l, r- E: H; aWeighting coefficient, 权重系数( G2 H4 _! o( h+ p6 X# _& u
Weighting method, 加权法 ! h5 \# Y2 \, q' z& ] @9 D8 \6 ^
W-estimation, W估计量! v. Y8 b: H$ A- X# {* b( G
W-estimation of location, 位置W估计量$ b3 M. h {: A0 J
Width, 宽度
3 }) \) I: P8 R; hWilcoxon paired test, 威斯康星配对法/配对符号秩和检验& G$ l! I% j, p+ J" N& F
Wild point, 野点/狂点2 ]: q% k* m9 f* _. a+ ~$ }( D/ ]
Wild value, 野值/狂值
; U9 E3 i+ b3 q5 FWinsorized mean, 缩尾均值; v4 W3 h6 U8 h) _4 r2 g- ?+ p
Withdraw, 失访 : H, J7 C8 l8 U
Youden's index, 尤登指数4 l8 E" {* u$ H- i4 y
Z test, Z检验 {5 R% {- ?2 g& _* f% E
Zero correlation, 零相关
2 X; G9 I! K7 C/ ?1 z! lZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
