|
|
Absolute deviation, 绝对离差
! X% {# ^+ ~0 U7 ?" f: YAbsolute number, 绝对数/ g; D# N7 e/ r/ C
Absolute residuals, 绝对残差* ]2 k! Z6 T9 a r
Acceleration array, 加速度立体阵) S1 ?. P) A( P' T
Acceleration in an arbitrary direction, 任意方向上的加速度
9 b$ a. K0 C4 Y* X8 l1 cAcceleration normal, 法向加速度) E/ t, z7 q) p. Q1 F; e6 |6 c
Acceleration space dimension, 加速度空间的维数8 C6 L7 |6 h9 `+ ~* s
Acceleration tangential, 切向加速度
7 R7 Q+ H% }- V1 M8 lAcceleration vector, 加速度向量
# [. L: s5 w; N) M; d4 Z, IAcceptable hypothesis, 可接受假设
1 Y4 R d+ x5 a0 @' WAccumulation, 累积
r; X6 B) g9 E2 zAccuracy, 准确度
+ D# w3 U0 m+ T3 Z# M4 qActual frequency, 实际频数
: m9 c) b- y2 {6 jAdaptive estimator, 自适应估计量
. I9 |3 E& T% a) |Addition, 相加
& W; \2 E7 L6 \9 g. _Addition theorem, 加法定理% _ z9 q' A7 V* z
Additivity, 可加性
* X1 J! @* O j" wAdjusted rate, 调整率
4 A4 N! v6 |, I0 VAdjusted value, 校正值0 K# \: g8 l P# t- H8 v8 E
Admissible error, 容许误差
! v3 Q, Y7 G+ xAggregation, 聚集性
- e, R- M9 j7 x5 b% f* E/ A5 Q& x% ]0 oAlternative hypothesis, 备择假设+ ^3 b: V0 ^$ B7 \# g
Among groups, 组间. Z3 T+ ^2 o/ E3 D! o6 a
Amounts, 总量
2 e y( V# N1 Q7 z9 _Analysis of correlation, 相关分析
2 e- t# W1 r s/ Z# B/ b1 \5 z% ~* UAnalysis of covariance, 协方差分析' t9 Y1 Q( F& O) _ U) {1 j
Analysis of regression, 回归分析
8 Z6 u4 C3 c& N9 m iAnalysis of time series, 时间序列分析3 {! X @5 W8 R0 K$ s. d
Analysis of variance, 方差分析
- S5 h2 @) D4 u. bAngular transformation, 角转换
6 J* S& ^& o# b- m: y" r* o; K, |) CANOVA （analysis of variance）, 方差分析5 ]0 E- _# U0 Y0 e5 r
ANOVA Models, 方差分析模型
2 g3 ~- y9 d; GArcing, 弧/弧旋1 j# D: s( L6 n: z& n0 u5 \& W# J
Arcsine transformation, 反正弦变换" p. n- n9 x; x* [; g( b
Area under the curve, 曲线面积
( ~& ?* ?+ s& w" M( mAREG , 评估从一个时间点到下一个时间点回归相关时的误差 3 B# T5 I4 X- }2 y
ARIMA, 季节和非季节性单变量模型的极大似然估计
) n' L0 z$ j3 U. u4 v D9 V5 zArithmetic grid paper, 算术格纸
% {' q. b1 G& p4 c3 jArithmetic mean, 算术平均数/ A% |5 ]- A5 @ E: D8 H, `
Arrhenius relation, 艾恩尼斯关系9 L2 ?6 Q, X7 K1 ~1 x! z, M9 l- a
Assessing fit, 拟合的评估
1 l( c# X0 j) Q% qAssociative laws, 结合律8 X X) _' K. p6 M! c" F
Asymmetric distribution, 非对称分布5 o# _. \% _) p1 O
Asymptotic bias, 渐近偏倚
! c( `8 Y6 C$ t: B& uAsymptotic efficiency, 渐近效率$ q$ ], \% `% s3 x7 r7 X
Asymptotic variance, 渐近方差* M+ Z7 ~1 o+ E7 `
Attributable risk, 归因危险度+ Y( B7 w* f) C; ]7 X8 l% A7 y! U
Attribute data, 属性资料3 J1 O1 w" }* A9 |! X9 m# M
Attribution, 属性1 j6 o) j: x; @5 S. J
Autocorrelation, 自相关
0 |0 G; M( }+ M5 q5 ~7 x- `Autocorrelation of residuals, 残差的自相关
* j, c6 N f) rAverage, 平均数( i0 B- M7 O* I: P; }
Average confidence interval length, 平均置信区间长度% y+ n- e' V4 G( I
Average growth rate, 平均增长率3 H2 {7 ^; S5 A) x: S
Bar chart, 条形图
+ h6 @6 f4 q: a, J% _Bar graph, 条形图, P% U! [* N" T2 w- y' {' k
Base period, 基期2 d0 o' E- v, F5 i
Bayes' theorem , Bayes定理' I( ^5 a F+ z8 f
Bell-shaped curve, 钟形曲线0 I" v a* T5 y
Bernoulli distribution, 伯努力分布 p9 s' H: E- @9 K# N( f+ h" D0 |
Best-trim estimator, 最好切尾估计量
5 Q4 `9 c. N: F: `/ V* J& q3 MBias, 偏性) e* g5 {1 H# t" u' t; S
Binary logistic regression, 二元逻辑斯蒂回归
0 X) k4 _5 x4 W- JBinomial distribution, 二项分布
8 U8 b5 y9 O5 [ V* @Bisquare, 双平方9 a' Q% B& R9 U* w
Bivariate Correlate, 二变量相关6 j: c9 B! c, O) g" ?1 ^
Bivariate normal distribution, 双变量正态分布7 ^/ n' M1 c( Y! A. L' d
Bivariate normal population, 双变量正态总体" X1 I$ W- |6 f% \7 c
Biweight interval, 双权区间
- z, M0 A: p- _# u+ rBiweight M-estimator, 双权M估计量+ K+ T' Y& S6 p' ^0 U
Block, 区组/配伍组5 g- I8 I7 ~% F* v
BMDP(Biomedical computer programs), BMDP统计软件包
/ T$ Z! ]' t) RBoxplots, 箱线图/箱尾图5 ?3 S$ v \5 [' |
Breakdown bound, 崩溃界/崩溃点
# I, j6 s# V/ y2 f B" ]Canonical correlation, 典型相关
5 N5 c9 x+ O4 t" Z w; P D Y2 MCaption, 纵标目3 t. Q. Q! A! ?2 j9 @
Case-control study, 病例对照研究+ ?( a. G- H/ U
Categorical variable, 分类变量
/ B$ Q9 Y# m3 aCatenary, 悬链线$ G* _, z/ G& d" ?
Cauchy distribution, 柯西分布
4 Q3 {% [) n, G6 i% [Cause-and-effect relationship, 因果关系: `; Z* c1 B+ U+ F7 z
Cell, 单元
1 K; l g, B7 d, [Censoring, 终检3 D' I3 v% L/ T& H
Center of symmetry, 对称中心' E( r" n @; b6 q" {
Centering and scaling, 中心化和定标& }3 i. W1 y! E8 M: h5 a+ e+ _
Central tendency, 集中趋势 b/ [9 \1 ?( q( p7 [' a3 }; A4 S; k
Central value, 中心值6 h! s6 @% w3 c9 W# s
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测) g' G& U i4 ^
Chance, 机遇
. P9 }9 S# f. D* S H0 ]Chance error, 随机误差- D. Z& }* k7 x7 Y5 e. h; L% _
Chance variable, 随机变量
+ y' w+ q1 J, ?. k0 E! tCharacteristic equation, 特征方程
1 A6 X. m; K! ] E3 NCharacteristic root, 特征根
. t. p2 n! w* }& }$ \6 \5 {Characteristic vector, 特征向量
0 Z' {. h; Y$ D+ H; a b) C. aChebshev criterion of fit, 拟合的切比雪夫准则
$ }4 x; a& L' X6 N% E% JChernoff faces, 切尔诺夫脸谱图
/ N$ C+ m2 s9 U/ y; ZChi-square test, 卡方检验/χ2检验
+ D7 H/ A# |- }5 ?& z' ~# YCholeskey decomposition, 乔洛斯基分解
3 Z- c$ }. A- A5 G' KCircle chart, 圆图
* L, e' ?6 D& Z2 r, T/ HClass interval, 组距
& O0 ^4 U- J* A$ T( n3 `/ vClass mid-value, 组中值
! Q9 @ l( U# Y3 u# T0 JClass upper limit, 组上限4 b3 r8 h" n! o- a
Classified variable, 分类变量9 Y" o' o; D/ k9 I" c( W
Cluster analysis, 聚类分析9 Q3 A! Q- I: c3 @
Cluster sampling, 整群抽样7 B; R7 h, @7 g
Code, 代码
: j5 j: n- e) ^Coded data, 编码数据
, J) j1 B, P& H* q; `/ ]Coding, 编码" [1 w8 |& l9 A+ T. I5 f# i" {
Coefficient of contingency, 列联系数; m9 S6 w+ n: K+ _. S7 L
Coefficient of determination, 决定系数* g# \4 ?/ E" N8 z5 J1 r3 N
Coefficient of multiple correlation, 多重相关系数& k) ]( |1 j- }5 C4 B9 I
Coefficient of partial correlation, 偏相关系数
. I: ~) v2 w# s. F4 k$ vCoefficient of production-moment correlation, 积差相关系数
. u" e' b: q9 _" SCoefficient of rank correlation, 等级相关系数
5 D# J; M9 V6 V. r' r1 R' q' t, kCoefficient of regression, 回归系数2 s& F8 i- k# V8 H [
Coefficient of skewness, 偏度系数9 ~' i Q1 [" L' E) J& |' Y
Coefficient of variation, 变异系数2 C* F% _4 z3 A
Cohort study, 队列研究5 T; f+ A: A$ M* {1 D
Column, 列* `+ p- b" Z" x8 P" D) W9 s
Column effect, 列效应
5 r) V; U7 I LColumn factor, 列因素
2 g7 `5 u# S* L7 MCombination pool, 合并
6 h1 V, P$ P4 Z7 l7 WCombinative table, 组合表 x, {# W) T5 }% Y% {
Common factor, 共性因子
3 b" J y& D' L, `0 cCommon regression coefficient, 公共回归系数
, P0 D! T9 ?. A9 L8 [Common value, 共同值9 _( C5 b2 M R! d N+ J
Common variance, 公共方差
1 D" R$ i1 [9 \& e* h0 f" RCommon variation, 公共变异2 J2 _' @( J( }8 V/ D: C- R
Communality variance, 共性方差' E, |" o9 k0 K0 i9 b
Comparability, 可比性 J$ y" `9 M: Z! z; }; Z5 p( W
Comparison of bathes, 批比较
5 |) s* P) I: c2 iComparison value, 比较值9 s5 i/ Z0 k0 ?% ]
Compartment model, 分部模型
. b- o; c- \# m5 FCompassion, 伸缩$ _+ t2 Q1 W8 s1 N7 i' Q+ ^
Complement of an event, 补事件& ?& U3 e" P0 E+ ^
Complete association, 完全正相关2 [: I3 b, w- F9 K
Complete dissociation, 完全不相关
: w9 Z5 ^$ ~7 M* BComplete statistics, 完备统计量
! s# o3 S% m7 [+ p) e. `) z; iCompletely randomized design, 完全随机化设计7 J9 R0 ~% r+ s0 ]/ u: W
Composite event, 联合事件2 ?' K, t5 q- Z4 A, ?
Composite events, 复合事件
3 r) `4 J7 n. r! M0 AConcavity, 凹性% y5 E1 y# H D
Conditional expectation, 条件期望% j7 K0 B/ a! m+ x4 r! p
Conditional likelihood, 条件似然
3 u- s4 g! F p2 v0 w4 J3 PConditional probability, 条件概率
; z4 g2 [( |/ p, v8 ?$ AConditionally linear, 依条件线性
5 I9 }6 J( c) XConfidence interval, 置信区间
% i3 P# W0 i' b/ X2 _Confidence limit, 置信限
( b$ t3 `% P* E/ d- @& f+ PConfidence lower limit, 置信下限1 @9 h. X3 l! |2 B4 x& s& K& x
Confidence upper limit, 置信上限, q6 d4 d- k5 u& |, P& P6 |: T
Confirmatory Factor Analysis , 验证性因子分析
9 [4 n$ Q5 T4 L# g3 U6 uConfirmatory research, 证实性实验研究
( E* u" G" z& c+ D2 r$ kConfounding factor, 混杂因素9 {3 T$ x5 V4 R; J2 z3 A0 [
Conjoint, 联合分析
9 ~% u6 C. R2 T9 \Consistency, 相合性
* G: @/ X* r. n% }, v3 ~) nConsistency check, 一致性检验5 `8 q2 g, O" [# x$ p. J
Consistent asymptotically normal estimate, 相合渐近正态估计: n9 v0 o6 A! c
Consistent estimate, 相合估计- q5 ]! g' t2 M; s0 [4 T
Constrained nonlinear regression, 受约束非线性回归3 M2 U* o0 M Z1 n
Constraint, 约束
' y d7 I* ^( T, M9 X. W1 O, X7 [Contaminated distribution, 污染分布( P, f9 S* }* @+ o6 G* C7 A- }
Contaminated Gausssian, 污染高斯分布
a& B$ j$ ? w0 k$ iContaminated normal distribution, 污染正态分布
* ^6 C% I9 m; o/ XContamination, 污染2 S/ X, [0 F/ ^ W
Contamination model, 污染模型* }9 p Q" V/ P5 Z; Q3 {. B# w% H
Contingency table, 列联表
3 }4 q! X1 H) z/ d4 ]Contour, 边界线
; }5 j# K u; Z! }7 S1 ~Contribution rate, 贡献率0 c4 P! V% U6 i
Control, 对照
0 q7 v8 S3 [* LControlled experiments, 对照实验
- o$ Z! g2 |7 a! q; `$ [6 tConventional depth, 常规深度: a6 z3 h6 y6 l" m; z8 u
Convolution, 卷积
" ^3 N" Z/ u2 H$ x GCorrected factor, 校正因子
" \8 |8 A6 B8 [8 n# w8 H* aCorrected mean, 校正均值
0 d* O: O- J; F5 xCorrection coefficient, 校正系数9 u7 J4 V0 T/ B; f' T
Correctness, 正确性4 s" H. i& Y6 Y& M
Correlation coefficient, 相关系数. _+ b/ t5 ]5 y2 w8 b. K
Correlation index, 相关指数
8 D: j: T$ c* d6 p" aCorrespondence, 对应
" @! a7 V' y2 j. lCounting, 计数* L* |$ f- s/ {1 i, A
Counts, 计数/频数# l7 ]1 m7 ~3 j2 J
Covariance, 协方差& I3 S5 d& S7 U$ W
Covariant, 共变 2 N4 l s6 A9 V
Cox Regression, Cox回归" ~9 h3 b( x( B: [; S* k$ @/ m- Y6 q
Criteria for fitting, 拟合准则+ H! @6 a2 S1 W7 p
Criteria of least squares, 最小二乘准则- G" k" h% L0 D
Critical ratio, 临界比 B7 p* f& l5 N
Critical region, 拒绝域
1 G9 `+ i& |' L, I- h; W/ JCritical value, 临界值2 g4 B# \5 u# m n( z
Cross-over design, 交叉设计# Y+ J1 K6 W* J
Cross-section analysis, 横断面分析0 Q, \5 \9 o* V3 \, o; w
Cross-section survey, 横断面调查7 L# g5 o; K D4 _( B S( q
Crosstabs , 交叉表
9 J( T; W8 c5 o( [4 ?! TCross-tabulation table, 复合表
! L' n* m( t) m0 G% c. Q; u$ jCube root, 立方根
2 B% ]; p% D! yCumulative distribution function, 分布函数 T2 @8 _% \: D
Cumulative probability, 累计概率6 z2 X v6 h9 N* Y7 J, v# X3 w, D( G
Curvature, 曲率/弯曲
7 d9 {1 C# S& W0 y6 S6 O% aCurvature, 曲率
/ F( Z, O0 }3 f: t7 lCurve fit , 曲线拟和 $ ~+ O7 [ P X% I4 i) g" v& {; y
Curve fitting, 曲线拟合
$ {$ d: {5 |1 ^Curvilinear regression, 曲线回归, E* N& J1 x+ V2 Q4 E9 g6 R" \% E
Curvilinear relation, 曲线关系
% ~4 e6 p1 Q" W/ N, l# F* n1 X2 @4 nCut-and-try method, 尝试法, G+ a0 t' ^9 `5 [
Cycle, 周期+ u6 s" V5 j' B: w- K& s+ a
Cyclist, 周期性 j: j! f& a2 d- V2 I
D test, D检验
; ]; _0 @$ m; ~% RData acquisition, 资料收集! H B5 b/ u8 t- Z* a
Data bank, 数据库
. e5 E% f9 Y* g4 O# ?& MData capacity, 数据容量
2 b" c! U2 R7 A. x2 PData deficiencies, 数据缺乏% l) E. G/ I( g% \5 y, V& X
Data handling, 数据处理
4 q( f4 k& O' o) b. L4 oData manipulation, 数据处理. \- W0 U- Y% Q/ p& E
Data processing, 数据处理( \, C3 Q4 a1 x4 {+ I
Data reduction, 数据缩减
& u. f1 c |' n/ X+ z& L& }Data set, 数据集
1 F! S% I- f7 Y7 w: R3 tData sources, 数据来源
: W: K( q( i5 n2 k0 fData transformation, 数据变换- H. P3 x4 l" @4 b. Q& K
Data validity, 数据有效性+ g* L7 b" r( d) c. J+ w
Data-in, 数据输入& `6 M8 v% c$ _4 ^; J3 ^6 ^+ P
Data-out, 数据输出
' M W1 N/ k7 @7 ^4 w' g/ UDead time, 停滞期2 m2 o6 h' A; V* J
Degree of freedom, 自由度
: ]8 K6 Y" G1 \$ {4 ^- J, pDegree of precision, 精密度
- d/ N; W W# r6 p! F8 pDegree of reliability, 可靠性程度
, _0 \' [1 E, `Degression, 递减, K# q7 l0 G: s$ \( Q2 c
Density function, 密度函数, ~- R Z3 \0 N- w/ |
Density of data points, 数据点的密度# X; o ^6 K; ? D4 a' b: v: v
Dependent variable, 应变量/依变量/因变量9 p. Y4 y; @/ s' W0 T
Dependent variable, 因变量 p2 u( |. H9 Q% o6 j
Depth, 深度
, n7 L5 ~% e6 gDerivative matrix, 导数矩阵
6 \5 a8 T1 j3 vDerivative-free methods, 无导数方法# |" V: R7 X0 y; w) B' C2 K8 x
Design, 设计
) z2 x+ u4 v( `1 s8 y! ADeterminacy, 确定性: q$ }4 U+ |" A( u: @
Determinant, 行列式
* \* k# d8 r3 o0 i5 ^4 ?5 @ |" X+ TDeterminant, 决定因素0 P7 c( u t0 f: j- F& ?
Deviation, 离差5 p& C+ G3 L/ y5 }! j1 `
Deviation from average, 离均差* f6 T5 V1 l l
Diagnostic plot, 诊断图- I4 H* D& }9 o+ a
Dichotomous variable, 二分变量 ~2 z* `9 K! @; ~7 m
Differential equation, 微分方程
3 z7 Z2 C2 [6 W5 w7 V$ qDirect standardization, 直接标准化法
2 l) C( q$ M4 l) V& }Discrete variable, 离散型变量" |3 r# ?# E, e0 r
DISCRIMINANT, 判断
! n4 ?* N% Q6 {% V1 KDiscriminant analysis, 判别分析
, `$ c* G! {3 _Discriminant coefficient, 判别系数# \, {9 o; u' m
Discriminant function, 判别值
. ^+ h) C' v! u% mDispersion, 散布/分散度2 H2 Y% x% H% D/ V4 O2 W
Disproportional, 不成比例的. J k8 b- s2 Z8 p. ?. |
Disproportionate sub-class numbers, 不成比例次级组含量4 X; H% G! r. \- s- r
Distribution free, 分布无关性/免分布: _* r l2 @2 C, z
Distribution shape, 分布形状
% X( x) {) \; f. n, M/ {Distribution-free method, 任意分布法
* K1 v @3 q; e' Y7 QDistributive laws, 分配律9 K, [* |6 R( j8 s8 ~5 C
Disturbance, 随机扰动项
( r( [+ b1 r* Q" K' g5 f8 r% d, NDose response curve, 剂量反应曲线' R0 e- A( G1 R W6 B5 m8 f/ k
Double blind method, 双盲法
`3 }8 f% I; ? j0 hDouble blind trial, 双盲试验: C5 u, p( q% u
Double exponential distribution, 双指数分布
) f1 D$ d4 N5 ^% y; NDouble logarithmic, 双对数- F, n$ i k& d$ ^& N K; z
Downward rank, 降秩- s7 x! ~$ s0 g" o2 P7 `0 G
Dual-space plot, 对偶空间图
2 O% n- t8 V5 QDUD, 无导数方法
6 C8 e2 y. \5 s$ tDuncan's new multiple range method, 新复极差法/Duncan新法" O1 u8 z5 Z9 n+ |" i
Effect, 实验效应
) @: J i8 u, A) T" X4 ]+ d( qEigenvalue, 特征值& O3 P: F( B% J
Eigenvector, 特征向量9 \5 a/ D! h+ z) T, t% h( F
Ellipse, 椭圆+ R( q; L& S! @& f( q' w
Empirical distribution, 经验分布7 V! t- o& v, ]/ M( i
Empirical probability, 经验概率单位3 P w) R4 \: H3 j
Enumeration data, 计数资料
7 b C' s* |2 `: M! }; PEqual sun-class number, 相等次级组含量
' d c4 }. x2 C& y, @1 a8 x: M: jEqually likely, 等可能
% A# Y# \ {% C) O* [5 zEquivariance, 同变性
" s' |- g& E: JError, 误差/错误
3 I# Y# c$ d% y) HError of estimate, 估计误差, F) m. l: W/ s: \3 I* I0 e
Error type I, 第一类错误
, o1 U% p3 l' S; T' @& V5 s: xError type II, 第二类错误
9 Q. M/ J6 n- M u- m/ IEstimand, 被估量
, l* I' p' `( I3 \9 dEstimated error mean squares, 估计误差均方
5 U& o$ e% T& L1 Q' a, _& P8 ?Estimated error sum of squares, 估计误差平方和
$ C. ^- Z# @0 X! h+ zEuclidean distance, 欧式距离
4 g# l, v5 l% G! bEvent, 事件
6 ?/ ]" d& O; D0 W! i' W% CEvent, 事件* S, e0 h* P/ ?0 e9 z& Q3 R& t" Y
Exceptional data point, 异常数据点
1 _1 A, \- i( l4 KExpectation plane, 期望平面
: Q) i: x8 E( t9 R; kExpectation surface, 期望曲面
' n* `- B3 ^$ p% M! FExpected values, 期望值
& _: M2 }; u# [6 w8 a$ C3 Y) @! \Experiment, 实验% x% [6 u. S& j5 R2 `- L" x6 ^ B
Experimental sampling, 试验抽样
" Z# d& W8 I- B8 f- VExperimental unit, 试验单位
n. z, \. t% TExplanatory variable, 说明变量
; M+ ^* T% n0 H: XExploratory data analysis, 探索性数据分析
$ }! A% U0 F! M8 b3 g3 N4 v2 v8 I5 ?Explore Summarize, 探索-摘要
0 q ?" ^" b' y9 K" r% |! B vExponential curve, 指数曲线
4 I- ^' c, W. U. O" VExponential growth, 指数式增长 O+ N* ~/ }5 a3 e. E$ P# O
EXSMOOTH, 指数平滑方法 . B5 U7 B) Q; b0 n8 Y) L
Extended fit, 扩充拟合
* Y* W8 O- D1 L% vExtra parameter, 附加参数
* Y5 f5 O' R \) \& h# hExtrapolation, 外推法
- H# K+ F ? g' SExtreme observation, 末端观测值8 R: X5 p3 K4 `! O4 y' m
Extremes, 极端值/极值
8 k+ }# f5 F* N& LF distribution, F分布8 \8 e, {9 c! h8 Z Y8 i6 T
F test, F检验! r5 T- i/ m; z- H5 d8 G$ |/ S1 ~% `* F5 z' Y
Factor, 因素/因子
8 r- d1 p0 n2 I% ?! t$ s; w4 ?3 rFactor analysis, 因子分析
, z: y; m' B. `1 i9 rFactor Analysis, 因子分析
( ^) O7 J. W7 w8 D$ m3 a. @% O* T/ mFactor score, 因子得分
1 k M+ e7 o5 oFactorial, 阶乘
. v: H8 g4 _, p9 {7 _: }Factorial design, 析因试验设计% |3 s' w6 c3 y6 P
False negative, 假阴性
) T' h3 R* n' N" m1 P6 n" o- m: ^False negative error, 假阴性错误1 a- h3 u* B9 W" F( O
Family of distributions, 分布族% U+ e1 X/ ]! x4 L4 ^/ m9 ]; A4 P
Family of estimators, 估计量族
5 D1 r$ X: o4 v+ w# q3 O0 p$ EFanning, 扇面
9 k/ t* F* I% `: i9 G: k; }2 SFatality rate, 病死率- I1 V! z$ z) {: @% y4 G
Field investigation, 现场调查
5 s# c/ B: T. ]. c' G8 A" QField survey, 现场调查1 f# _9 e3 K2 R1 B* G# U" c7 f" q
Finite population, 有限总体: g( V1 b+ |6 X6 a2 n4 x
Finite-sample, 有限样本
9 ]6 a4 e2 I/ b. hFirst derivative, 一阶导数
3 u8 z9 B" X. l' g3 Q6 |8 qFirst principal component, 第一主成分
9 k: V4 o/ s) q) WFirst quartile, 第一四分位数
0 J" x! H) F' A) k9 FFisher information, 费雪信息量
& H1 p+ y3 G: q! yFitted value, 拟合值
& S7 c- V0 P0 xFitting a curve, 曲线拟合5 B4 F t) ^8 `7 O Z
Fixed base, 定基* z3 r0 t+ `! c% y
Fluctuation, 随机起伏8 w" e. Y L, C' d
Forecast, 预测' u1 ?4 I- e0 }( ?
Four fold table, 四格表
$ d' ^# R& f `0 `& @) V0 R0 O1 aFourth, 四分点
7 z- V- M. k" U1 RFraction blow, 左侧比率
- H9 d6 d" G; w/ b3 i2 r2 R5 `3 lFractional error, 相对误差& V& B: R! u1 b L
Frequency, 频率
, M3 ?7 X# B# i$ aFrequency polygon, 频数多边图2 I3 D! ?: m! b* m7 s# p6 D
Frontier point, 界限点* z6 P) E2 n0 `7 ~
Function relationship, 泛函关系
. {% m) Q1 d$ mGamma distribution, 伽玛分布. J/ t% U) A* m \; e) `
Gauss increment, 高斯增量
8 k/ `; e4 x* y( Y# i$ C2 \Gaussian distribution, 高斯分布/正态分布
; z+ D) K0 f+ H4 nGauss-Newton increment, 高斯-牛顿增量
; t) i( N/ O$ {General census, 全面普查1 {/ Y" f% e; }7 b) o
GENLOG (Generalized liner models), 广义线性模型
% B3 u3 s1 q0 |( S- QGeometric mean, 几何平均数( R4 ~/ m& S* l
Gini's mean difference, 基尼均差
7 h0 M, X2 j# N4 P W: v' M, qGLM (General liner models), 一般线性模型 + w% @$ {" t- u$ K" o# y1 V
Goodness of fit, 拟和优度/配合度
- K7 j& H+ ^0 c& i! \/ \' yGradient of determinant, 行列式的梯度0 `1 D4 e W) u% Y( @; p
Graeco-Latin square, 希腊拉丁方7 J7 Y& q. P! D1 w
Grand mean, 总均值
3 ^5 t9 T! B# d9 U( _Gross errors, 重大错误4 |) @& g/ r: r' y/ h/ n
Gross-error sensitivity, 大错敏感度' k( H" @) P0 ]: U' R: r
Group averages, 分组平均7 S5 g+ X* c2 ~1 p, a; b
Grouped data, 分组资料
: ^) T8 G: X0 `( f* v( _* H9 eGuessed mean, 假定平均数
3 [# @$ g$ l9 UHalf-life, 半衰期 {2 f, Z- r) R7 J# A
Hampel M-estimators, 汉佩尔M估计量
3 e* g5 `5 B) h3 @Happenstance, 偶然事件
. F& E8 C, ~4 S( {/ [, l- y9 j) H1 l8 KHarmonic mean, 调和均数9 L$ {; ~ Q C2 @
Hazard function, 风险均数
1 h; n! C$ D% \1 PHazard rate, 风险率& t# n/ M5 C7 w; q: h
Heading, 标目
9 \6 h% ` {& f0 LHeavy-tailed distribution, 重尾分布( Q7 r* b+ \; F% v% _5 U, J
Hessian array, 海森立体阵: ^" e) b, f( H+ y ]
Heterogeneity, 不同质, r0 h6 `( h5 r9 i6 Q* b3 p- R9 O
Heterogeneity of variance, 方差不齐
' t" r" e& ^! D8 ?8 YHierarchical classification, 组内分组
/ M+ ?1 y$ b' F! THierarchical clustering method, 系统聚类法1 R: W! _: R; A' j, ^- x1 U, P. w2 Z6 N4 H
High-leverage point, 高杠杆率点
! h4 M5 O e* @' M& h! hHILOGLINEAR, 多维列联表的层次对数线性模型) M# S% v0 `1 }1 J" h
Hinge, 折叶点+ i; M& j0 |* Z3 h1 V7 R
Histogram, 直方图1 u1 E0 C' G; l# \6 g6 p s" ~
Historical cohort study, 历史性队列研究
$ q. T2 ?6 ]! a9 RHoles, 空洞* B. Y8 z7 i5 G- Q/ g9 ^
HOMALS, 多重响应分析
/ f( O. f; W. Q6 t1 a, q# jHomogeneity of variance, 方差齐性
. l8 \5 O! {) | VHomogeneity test, 齐性检验$ p! C& _: Q, V4 m" V
Huber M-estimators, 休伯M估计量" o1 |5 Y" F& ~
Hyperbola, 双曲线
5 S. p% Z! e: k/ n- n7 `) y1 u$ ~; DHypothesis testing, 假设检验
6 F; ^8 T8 K2 \* |. ^# \/ ]Hypothetical universe, 假设总体! \% k b! @1 b+ K
Impossible event, 不可能事件* y* V$ Q8 o" x% U! t# i s
Independence, 独立性
% D6 Q, ]5 b2 ~8 q5 c8 k% ]Independent variable, 自变量7 y, R3 w& Y: M$ _- A5 ^ X3 E
Index, 指标/指数% R% w! L" F6 P- {# r( U8 _
Indirect standardization, 间接标准化法3 s3 Z7 T, o0 G5 q" d" \7 ]; t0 w
Individual, 个体9 ~. F& Q$ @, t% j7 c* v
Inference band, 推断带
3 M- G$ v8 V* T) S7 ~- g0 cInfinite population, 无限总体8 I, m I" m* W% g; d
Infinitely great, 无穷大5 v8 D/ C$ N& [3 {
Infinitely small, 无穷小: n G: b5 C/ L3 y/ g9 U! l0 `
Influence curve, 影响曲线. R- Y: @- _0 s) D, D; I/ W
Information capacity, 信息容量7 Y0 `- S2 s% h: s
Initial condition, 初始条件" e( D' j6 x1 b8 H5 D( o
Initial estimate, 初始估计值# F2 ~+ c4 Y+ H4 a0 A
Initial level, 最初水平0 H1 L" G6 F$ K6 E5 b, k$ i9 D) [$ e3 L
Interaction, 交互作用0 X4 c7 Z# h& J+ H+ j( V: }
Interaction terms, 交互作用项- i: w& y d4 k# |6 K
Intercept, 截距
* V1 {5 _/ `) V6 ~% g3 @$ n$ sInterpolation, 内插法
- Q( K) J( A! D) k- h( UInterquartile range, 四分位距4 B* ~" i* c6 ~/ y/ b1 ~
Interval estimation, 区间估计. O( a- ~* E! X. R
Intervals of equal probability, 等概率区间& }9 }6 ~# D2 X% M4 g3 b
Intrinsic curvature, 固有曲率
: l; _& T1 {1 E) [# }5 ?+ {Invariance, 不变性
# @. T% i2 K9 N. {. R ~( s! aInverse matrix, 逆矩阵7 C4 i; y: G! L7 ?2 p# I3 \
Inverse probability, 逆概率
0 v* I+ _6 w6 EInverse sine transformation, 反正弦变换
7 P; N7 O- ~! V6 B0 v5 wIteration, 迭代 7 q; V9 |8 I/ @# n# R+ }0 U% a6 s
Jacobian determinant, 雅可比行列式9 T% t+ H& n5 N
Joint distribution function, 分布函数
( [; q4 |# N& t V/ YJoint probability, 联合概率; c" P/ z/ _) ]7 p
Joint probability distribution, 联合概率分布
* w) v! l6 p5 k. k8 ?6 l0 W+ z! oK means method, 逐步聚类法" ]3 T6 ~( @7 c6 n2 a2 p. N
Kaplan-Meier, 评估事件的时间长度 0 d+ F1 g, v0 D* O8 z
Kaplan-Merier chart, Kaplan-Merier图
' p1 M, Z( D! J+ }Kendall's rank correlation, Kendall等级相关, w. ^0 P5 W/ y
Kinetic, 动力学
6 z; y/ t$ z& O0 DKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
" ` `, }$ k. `: eKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
; d5 P/ k! d# F( l4 y! @1 S' I+ VKurtosis, 峰度
' ^2 q7 ?+ I! X2 U- u7 F0 `/ q9 vLack of fit, 失拟- G0 R) y( K v+ F
Ladder of powers, 幂阶梯* u. q7 G4 y& E( w
Lag, 滞后/ P3 d: Q& V* O! K: \
Large sample, 大样本
2 K1 f* Z( g7 p$ VLarge sample test, 大样本检验
4 E8 w9 h* p u5 u" @Latin square, 拉丁方
: k3 w4 ~0 E8 kLatin square design, 拉丁方设计
' i: X7 [% h0 m' H6 T% k, a- H- mLeakage, 泄漏 L. U$ s* K7 |; [
Least favorable configuration, 最不利构形+ m, d* [: Y ?; k. D6 Z! G
Least favorable distribution, 最不利分布
2 J0 F$ e2 M% X7 uLeast significant difference, 最小显著差法$ f' y" M- I) R9 b$ ]6 P- E. q0 }
Least square method, 最小二乘法
* t2 X* ]1 v" D& mLeast-absolute-residuals estimates, 最小绝对残差估计7 Y: H1 ^$ B( f. @' s
Least-absolute-residuals fit, 最小绝对残差拟合$ I I6 m% s4 ^4 A0 H/ I- @
Least-absolute-residuals line, 最小绝对残差线
+ h+ p9 \) x3 B QLegend, 图例" M3 g1 I' o+ _/ V0 c
L-estimator, L估计量9 U9 ~" Z0 F9 ?/ a9 d ^# ]
L-estimator of location, 位置L估计量
/ C k$ H J8 y1 ^* g7 W4 oL-estimator of scale, 尺度L估计量1 ^4 z; D- U/ G5 {7 X
Level, 水平
- D, N# ~$ |" Z# D9 l4 ] D7 BLife expectance, 预期期望寿命4 A/ F1 k8 L9 N; g( s: y/ [
Life table, 寿命表: O7 S) \0 }6 S7 w
Life table method, 生命表法/ U9 h& @& T1 z' L+ O6 L# Y7 S5 v7 s
Light-tailed distribution, 轻尾分布$ A( `7 M2 d5 c9 M& `
Likelihood function, 似然函数, l8 M5 N. ^2 L5 {
Likelihood ratio, 似然比7 |7 Q( o' E: Y9 a- s4 s. m
line graph, 线图
7 v# Z1 l/ L) S [Linear correlation, 直线相关9 W; O* B- k6 }+ I$ E3 s c6 x l+ x
Linear equation, 线性方程
$ V5 s! C; Z6 k/ r, VLinear programming, 线性规划+ G- K4 l8 A" `: \) C6 c
Linear regression, 直线回归7 [" w! y2 ~& L O% o' H
Linear Regression, 线性回归
$ P# b& }/ V: ]! [& Y x. t5 OLinear trend, 线性趋势
# C# n Z# O- m; X9 w) W" KLoading, 载荷
. S8 A9 J% C0 ]: |- ~ i; Y& iLocation and scale equivariance, 位置尺度同变性
4 p* \$ D2 Y6 M6 B. V6 k; nLocation equivariance, 位置同变性3 F9 ?7 y" A1 G8 `& o5 L6 n6 g, @
Location invariance, 位置不变性2 U6 v( N5 |+ Q5 e/ L
Location scale family, 位置尺度族
9 R% w0 y' C ~- h% rLog rank test, 时序检验 " [$ e$ W% z- e9 J
Logarithmic curve, 对数曲线
) _ z8 ] u0 s7 m0 lLogarithmic normal distribution, 对数正态分布& w6 @0 f; t5 D: f7 z8 ]0 s
Logarithmic scale, 对数尺度9 x1 Q/ }& \& _- d7 i* O; K6 s
Logarithmic transformation, 对数变换
9 F' H% }) j. O3 p+ p" bLogic check, 逻辑检查
6 d8 R( ]# ^, ~/ A" Z) }Logistic distribution, 逻辑斯特分布
0 ]. Y( o' M% u' i0 B3 GLogit transformation, Logit转换
& R. w$ |4 R& l; P9 }LOGLINEAR, 多维列联表通用模型 8 A% }2 O+ J& H! q) B0 I" u ~
Lognormal distribution, 对数正态分布
# E/ q5 U' @6 N/ M s6 M$ k/ ~* pLost function, 损失函数
U- ~: }5 O) }( g: KLow correlation, 低度相关5 ?/ ?" c6 L2 K8 b, B
Lower limit, 下限
% o8 ^' [" ^$ q% W4 HLowest-attained variance, 最小可达方差, ~8 s4 D! A9 n: H/ i$ n$ ?
LSD, 最小显著差法的简称
+ Z5 X! o7 Z9 ?! ^1 uLurking variable, 潜在变量- k& I3 k4 ~! K* U% K
Main effect, 主效应3 f4 g: c3 Y8 @4 S3 X, s4 w/ \
Major heading, 主辞标目
' s' `3 l( J7 L4 k n5 EMarginal density function, 边缘密度函数$ x, d$ |3 ]9 F" L6 k: r
Marginal probability, 边缘概率
# C% N' V. M- }. ^4 p% yMarginal probability distribution, 边缘概率分布
) U. ]- `% _' T+ n& aMatched data, 配对资料
7 m7 ? y) |. \Matched distribution, 匹配过分布8 h; v' @: {7 s9 w! E3 h+ ~
Matching of distribution, 分布的匹配% u" I$ I# A, h0 W& g- e* B+ |
Matching of transformation, 变换的匹配4 B! V( q4 Z. L3 ]1 I$ ?# h. [
Mathematical expectation, 数学期望+ L* H& _1 C5 B8 e4 M/ ?
Mathematical model, 数学模型1 H- W1 q/ S. w* m4 [9 E- d$ Z* I
Maximum L-estimator, 极大极小L 估计量" o8 P* D8 ~' H' v/ |! b
Maximum likelihood method, 最大似然法
. d2 i3 b+ Q7 Y; yMean, 均数
# ~2 {7 f. z) j; b" u: VMean squares between groups, 组间均方
" {8 b1 Q9 V2 C0 J0 u9 ]4 gMean squares within group, 组内均方8 W' i! t$ U9 {" j% k
Means (Compare means), 均值-均值比较/ D& s3 V/ Z4 A
Median, 中位数) A: p% D8 [( R
Median effective dose, 半数效量
* E" Q6 o( u/ t; `Median lethal dose, 半数致死量+ E3 M3 ^: m& f: o
Median polish, 中位数平滑5 B" e. A6 t( f8 l# \; _$ J
Median test, 中位数检验
. O/ q+ |7 y1 A* P$ lMinimal sufficient statistic, 最小充分统计量* ^8 c4 u) ~4 g- c6 _% C: [
Minimum distance estimation, 最小距离估计, l) j# A0 O. x/ e/ e
Minimum effective dose, 最小有效量- R% b! |" y+ n. v3 d
Minimum lethal dose, 最小致死量: d0 v0 x" W5 ~! F) @; V
Minimum variance estimator, 最小方差估计量; _+ ]8 O1 N" f/ i
MINITAB, 统计软件包( Y8 b3 ~, ~ Z) H7 c f1 C
Minor heading, 宾词标目, O% F) V" N4 R' h; j* w2 d
Missing data, 缺失值3 P: u8 w, U1 c) ~5 r
Model specification, 模型的确定# X: B& L$ z3 N6 g" H! m0 F
Modeling Statistics , 模型统计. f t% F* e! r" W5 x
Models for outliers, 离群值模型
# z, _. \/ M3 O' h& uModifying the model, 模型的修正
: M) [% `; R4 ]3 dModulus of continuity, 连续性模
8 R1 Q+ `9 T4 b1 x4 X) f. A- BMorbidity, 发病率 . d+ K* N' R2 k3 J( K
Most favorable configuration, 最有利构形
; m) O. `+ k$ Q7 V7 H, D" VMultidimensional Scaling (ASCAL), 多维尺度/多维标度
8 |- p: `: B: v( H# hMultinomial Logistic Regression , 多项逻辑斯蒂回归
& E8 k" `) M# N0 A9 k/ ?Multiple comparison, 多重比较* C# |* W4 o* o/ w; H' n0 L& _: p
Multiple correlation , 复相关: D2 f! r' W( q( n6 \6 Z, j2 k
Multiple covariance, 多元协方差
% w3 Q& I4 w+ ~3 h" B/ p9 [Multiple linear regression, 多元线性回归( |# v7 Y0 ]0 G2 Q1 O- \5 q
Multiple response , 多重选项
6 x" m a0 V% b0 J" l0 ^2 yMultiple solutions, 多解/ z! E: I: X! W3 S3 t
Multiplication theorem, 乘法定理
* V% q; V" L9 Q0 e, n" PMultiresponse, 多元响应( l/ H8 L0 ^# S) n- q
Multi-stage sampling, 多阶段抽样# [1 I* t. a8 f$ E$ M! g# s- Q
Multivariate T distribution, 多元T分布+ H" g/ H) ?# O9 U$ N5 F* ]
Mutual exclusive, 互不相容
; j4 \6 f$ a3 b7 x7 [% w+ \# i, o* kMutual independence, 互相独立
# I, a$ e% \1 h b7 ~- XNatural boundary, 自然边界( x l; w$ @7 m# @) N
Natural dead, 自然死亡
7 K! I0 Z: v# Y5 `Natural zero, 自然零
; |" z2 `1 C3 }Negative correlation, 负相关# a5 c: n. i) U$ N6 Z
Negative linear correlation, 负线性相关* Z$ \! O' T9 w# N
Negatively skewed, 负偏
# z% |9 ~; {# _% C. yNewman-Keuls method, q检验. E7 h+ ~" `, a/ q4 I+ h
NK method, q检验8 Q5 o: o6 |2 F8 o; X& O
No statistical significance, 无统计意义2 f) ?/ T0 v1 ^$ m
Nominal variable, 名义变量
$ `% |# J9 I1 [- l& TNonconstancy of variability, 变异的非定常性
% i4 v% [7 ~2 S& H8 x! v, iNonlinear regression, 非线性相关& s9 N( E" G& ~0 J# V. g
Nonparametric statistics, 非参数统计
! W) T4 \. \4 ?& a: JNonparametric test, 非参数检验8 m g( S$ O! U x% z
Nonparametric tests, 非参数检验* U+ D4 F; u1 H. f
Normal deviate, 正态离差
" D& G" j( A: h, o) t. m- R4 `8 ZNormal distribution, 正态分布
' c1 ^9 i9 c* `Normal equation, 正规方程组
& Z. ]6 k9 X ]! kNormal ranges, 正常范围
3 G s! C; p# s6 N, gNormal value, 正常值. ~3 [ P2 f3 {) [# V. k) |; l
Nuisance parameter, 多余参数/讨厌参数7 Z0 [4 x' s4 T( ?$ K' E G! z: B1 Q
Null hypothesis, 无效假设
# R( {7 J( F0 g* D7 _, ENumerical variable, 数值变量& J w4 T# U# e9 F/ \
Objective function, 目标函数
9 C( h. G% ?7 C+ k8 `8 y* `Observation unit, 观察单位
( L; d& M% A( A( oObserved value, 观察值
X% A9 @3 Q+ V# H8 A9 X6 ~One sided test, 单侧检验
! p6 Y7 ]! b0 yOne-way analysis of variance, 单因素方差分析
8 d) k9 c* x! n" r/ mOneway ANOVA , 单因素方差分析
, S3 ] _+ Q" A4 b. KOpen sequential trial, 开放型序贯设计- A1 @' S$ k# R9 k
Optrim, 优切尾! M/ F6 V( ?1 G6 j. z8 i
Optrim efficiency, 优切尾效率
0 G' \5 ]2 E1 J7 F6 D- r1 EOrder statistics, 顺序统计量' N6 o+ ~7 v" X0 \
Ordered categories, 有序分类# R7 d) D" ~$ R# ~9 \: u+ ]
Ordinal logistic regression , 序数逻辑斯蒂回归" ~0 {/ j! {" I8 T9 V
Ordinal variable, 有序变量
- Z J8 I0 C- o- FOrthogonal basis, 正交基
) E8 W5 g1 ^( `1 }% gOrthogonal design, 正交试验设计) @7 @6 B" i S$ T4 }1 Y" _' _
Orthogonality conditions, 正交条件7 z G$ C) a+ |/ l& Y; p
ORTHOPLAN, 正交设计
8 ^! T E/ F9 }Outlier cutoffs, 离群值截断点
0 ?: h3 {5 _: t, O# GOutliers, 极端值5 v4 k( e& m$ U7 _
OVERALS , 多组变量的非线性正规相关 % ]/ ?6 h5 H- u" `7 Y f
Overshoot, 迭代过度
. @1 Q5 y" p: r: | qPaired design, 配对设计
' M9 [" ~! b. k# }! |# RPaired sample, 配对样本* p% q0 u T5 V
Pairwise slopes, 成对斜率
0 f6 P" ?3 W$ L. M* `9 [Parabola, 抛物线
! m" @! {9 L8 J% jParallel tests, 平行试验
! P, l* _- D9 y$ dParameter, 参数9 @- \9 _% z+ P' }4 p* e, ~- W* Q
Parametric statistics, 参数统计* T. |2 {$ q9 ?
Parametric test, 参数检验
4 m. a% V0 z9 ]0 @7 VPartial correlation, 偏相关
* Z! ^8 v' {3 M# }3 I9 R0 V' KPartial regression, 偏回归* q. `+ P; E# h% U/ ^% j9 O
Partial sorting, 偏排序
4 Q% [# x9 o: hPartials residuals, 偏残差1 u- I! c' Z6 t% K% t; D* {+ ~% I
Pattern, 模式 B, }* C z* a/ e: Y% N# w
Pearson curves, 皮尔逊曲线, M0 V8 t; ?1 U) |) I# q$ |
Peeling, 退层
" B- ~7 ~$ a- g. f# C0 q: Q5 a5 YPercent bar graph, 百分条形图
5 @/ g; |$ W2 jPercentage, 百分比
; f. v8 F( T! @4 ^ d- f4 w9 f# l3 o! fPercentile, 百分位数
3 f& v& l' L, @0 }Percentile curves, 百分位曲线
6 M* c6 D; g: O {: A- BPeriodicity, 周期性) {8 ?9 x! C& x$ }6 d/ N9 B
Permutation, 排列
) b) \' M2 _7 [P-estimator, P估计量
6 p. H4 _5 s2 H0 t6 Q1 `Pie graph, 饼图
' j; K: K7 o( rPitman estimator, 皮特曼估计量
7 r" z- T+ h" _; y1 a" [: t- |Pivot, 枢轴量: i, K! b. o/ } e5 k
Planar, 平坦, V, H3 t& g L
Planar assumption, 平面的假设! t+ S( i: K/ T% U0 q% o S
PLANCARDS, 生成试验的计划卡" y& d2 Q# {; b8 ~( `1 ?7 S8 c, z
Point estimation, 点估计
3 w O" C# I3 ]Poisson distribution, 泊松分布7 o3 d! r; K0 U! I" e+ O
Polishing, 平滑
- K' S/ [/ m; P- S9 LPolled standard deviation, 合并标准差6 r! r! s' W2 e; |; B
Polled variance, 合并方差, x. w' u9 [5 r8 ]2 w) j8 k0 `8 N8 m
Polygon, 多边图3 Y7 X0 M8 n; t4 R8 D/ e* m4 ^; l
Polynomial, 多项式
3 |* V2 X0 k D) _Polynomial curve, 多项式曲线
5 w- A" N% v8 ]% t JPopulation, 总体
. |2 _4 x0 \. F( W1 XPopulation attributable risk, 人群归因危险度" E3 s: j" t) a6 ^% {
Positive correlation, 正相关
2 j9 q+ N% s8 k$ N8 IPositively skewed, 正偏* E; u W$ s) a, o' g# c
Posterior distribution, 后验分布
) w; t: `" g+ E+ l$ E% wPower of a test, 检验效能
0 J, Y5 @0 ?. [. h7 LPrecision, 精密度
/ I# K8 T, _6 SPredicted value, 预测值
5 |; M! Q/ @ P$ g, z: jPreliminary analysis, 预备性分析, p+ U# C' r5 f) k, _$ t
Principal component analysis, 主成分分析9 x+ d" z$ h' g7 I% ]2 w
Prior distribution, 先验分布
" ]8 M/ `4 \, v; qPrior probability, 先验概率! r2 u# U9 j; g
Probabilistic model, 概率模型. b9 g/ V6 W: r2 s* j3 u
probability, 概率. Y% J1 |: S8 C1 N, i; {, |
Probability density, 概率密度
9 ~2 N$ q t* q1 x9 {. K: c8 AProduct moment, 乘积矩/协方差$ y4 i) |2 [ h$ [9 ?
Profile trace, 截面迹图3 ]- d! L. I/ s
Proportion, 比/构成比
# {) ^( a5 E8 G! E% b7 P* FProportion allocation in stratified random sampling, 按比例分层随机抽样
# x6 j3 V$ t& p) K. MProportionate, 成比例
) t9 a( K! v& e0 qProportionate sub-class numbers, 成比例次级组含量& x+ G+ C8 U, B( Q2 A: R
Prospective study, 前瞻性调查
( b' K7 ~# O$ c& X: o5 |Proximities, 亲近性
3 }4 p! W9 e+ A+ ~9 M1 SPseudo F test, 近似F检验
2 B, l" ^# l) {Pseudo model, 近似模型0 B$ U4 o" L. a$ R4 U" ~
Pseudosigma, 伪标准差2 Y& f5 c) }1 f
Purposive sampling, 有目的抽样. l' x2 y4 r7 e" O. E
QR decomposition, QR分解
1 ?9 n X$ ]2 G, kQuadratic approximation, 二次近似
7 s( O1 k5 V+ F; uQualitative classification, 属性分类
) b: \: Q0 N D d. kQualitative method, 定性方法
3 l p) K& }$ t( ?5 q( b: u) iQuantile-quantile plot, 分位数-分位数图/Q-Q图8 F% J( I" k" O' I' d: k9 Q
Quantitative analysis, 定量分析
4 X/ i" s4 T# E. g! u6 w7 _Quartile, 四分位数
; ]: Q1 k& J( q [: BQuick Cluster, 快速聚类
# Y3 s1 L4 ~" |) p. f. Q0 YRadix sort, 基数排序2 j5 T% A! ?6 B& q5 K/ R
Random allocation, 随机化分组( m' F G; T+ L
Random blocks design, 随机区组设计
. A9 y* C" F" F1 D) O0 A2 Z+ ]Random event, 随机事件+ X/ d5 [0 R" J: E
Randomization, 随机化9 Q- H1 q& p5 B% {6 V0 r- b
Range, 极差/全距
! X5 Y8 J+ x" [; J! W+ a' ARank correlation, 等级相关
& k2 b/ Q6 J. c2 `Rank sum test, 秩和检验
& @, m. o) ^* @; [* d* W/ I* i6 {' HRank test, 秩检验
- a1 r! K! Z2 k$ c" C$ p, ZRanked data, 等级资料2 {0 e- i2 G# X6 G( d; o
Rate, 比率+ l# J3 Y: z: |/ ]. d1 C& D
Ratio, 比例! s$ [0 @8 t$ O' Q) D: P. q+ A
Raw data, 原始资料6 w/ Z, z$ @# q
Raw residual, 原始残差* O* I6 z. W M3 ~/ j+ M! D- l! `
Rayleigh's test, 雷氏检验$ X0 [1 j/ n$ f @5 v4 S
Rayleigh's Z, 雷氏Z值
: M9 k" j# U: z) A* P( m1 qReciprocal, 倒数
; |9 v& |. _, e3 k) J# PReciprocal transformation, 倒数变换$ G- K7 l5 A# `0 ?1 A
Recording, 记录
' a$ p. ], E ~ o" d# nRedescending estimators, 回降估计量
9 u. @6 N1 E" h9 a( \1 jReducing dimensions, 降维% N' u, p' g/ |0 T& {: r! n( }
Re-expression, 重新表达
% r. j3 ~6 {8 W7 g1 ]9 C7 O+ |3 sReference set, 标准组8 w, u% n" i% b! [) o/ H
Region of acceptance, 接受域6 `1 l$ w' z8 w, E! z4 X+ i! ]* t
Regression coefficient, 回归系数
" _ r& \) ~- `3 lRegression sum of square, 回归平方和& Y% X/ A6 m4 L% K( E6 o
Rejection point, 拒绝点: t: |" L7 l- k7 |; V- H8 J
Relative dispersion, 相对离散度
: I& {2 E, \/ A: U' U' kRelative number, 相对数
" G2 v* |/ |% ~/ I1 TReliability, 可靠性
: v/ w/ g; k; g9 E; {* IReparametrization, 重新设置参数5 b/ }% W! U% ?: \
Replication, 重复
4 B; a3 ~4 u% }* u! L, d- MReport Summaries, 报告摘要( w: G+ L( J& u% j
Residual sum of square, 剩余平方和
5 L5 V& G+ I' w/ @Resistance, 耐抗性
8 O$ e7 O6 j: j7 C5 c$ IResistant line, 耐抗线
E$ b: s( W( G, WResistant technique, 耐抗技术8 N( w$ C" U/ f, {+ J
R-estimator of location, 位置R估计量
0 Q# F2 L- z( D# ?R-estimator of scale, 尺度R估计量
8 C1 i1 F, W: m1 K* r# F1 z, i% rRetrospective study, 回顾性调查- `2 P/ p: T% f1 F3 @
Ridge trace, 岭迹
: u) A4 O& v+ E: I3 ARidit analysis, Ridit分析/ L/ u4 j* g0 s' R! C: |* Y. m
Rotation, 旋转, C s }1 H+ a0 K9 Q( n
Rounding, 舍入
5 A" M/ P, {# F, P' o8 sRow, 行' w/ l& d. l2 t! s& K. |
Row effects, 行效应% F H/ N" r: w q5 E$ y/ E
Row factor, 行因素2 M" B, R4 O, Z; x2 @/ w
RXC table, RXC表
. }7 b5 g7 r" ]$ fSample, 样本5 \2 w) u! @0 i
Sample regression coefficient, 样本回归系数
% E8 u1 i6 X1 P) v9 JSample size, 样本量$ N: l- u( b j& q1 R* c3 y
Sample standard deviation, 样本标准差
; |5 r4 x4 {* M1 J$ F5 _Sampling error, 抽样误差
2 x2 H! x( R# c% N* dSAS(Statistical analysis system ), SAS统计软件包$ R1 f; s2 C7 H2 S$ q& e, L
Scale, 尺度/量表2 _6 D& L, y2 V. w
Scatter diagram, 散点图6 q# p. g8 m0 t" L
Schematic plot, 示意图/简图
. L3 U9 y S7 ?6 Y/ b0 e5 X9 N) i9 AScore test, 计分检验2 j% W5 T3 W/ C1 c) V
Screening, 筛检- \& A) [/ k- Z
SEASON, 季节分析 : N4 T: n5 b0 t c) f) Z7 b% k5 J
Second derivative, 二阶导数. C2 P9 \3 f: u4 F- }- a
Second principal component, 第二主成分
4 Q7 O4 F. Q s" z0 J6 iSEM (Structural equation modeling), 结构化方程模型 ; c6 V8 D/ K! J& K& B
Semi-logarithmic graph, 半对数图& [/ r7 Y* J+ k9 X* |
Semi-logarithmic paper, 半对数格纸
2 `0 {$ x. i0 ?2 b, q# p; WSensitivity curve, 敏感度曲线
" B8 u7 {6 R) I2 l$ a& R6 KSequential analysis, 贯序分析
0 G/ y: W$ B+ C$ W& t7 Y$ qSequential data set, 顺序数据集
7 C; ~! [* x8 l; }9 L* u& }# kSequential design, 贯序设计
1 ^0 b" ?& G t2 k' `$ Q- i+ ESequential method, 贯序法
& }3 S1 w; m: U) eSequential test, 贯序检验法
+ G7 i0 S, c; v3 M: l4 LSerial tests, 系列试验
# s) F+ m0 W1 c/ n4 X3 M( Y( U" kShort-cut method, 简捷法 " E6 v2 E) j9 O1 l, ]( X6 Y5 e, k
Sigmoid curve, S形曲线
: i! a- B, B% d8 f9 zSign function, 正负号函数
: L3 g9 y( y) u! VSign test, 符号检验
! t7 C W% ^( L2 p! w( C, YSigned rank, 符号秩 K4 E# R; W) U5 e; a/ _' E0 j
Significance test, 显著性检验- I+ r- D8 J( h
Significant figure, 有效数字
k* z( @# P9 U" nSimple cluster sampling, 简单整群抽样9 ?+ ?; q! I4 \ j6 t' p3 q
Simple correlation, 简单相关# y6 F/ o+ f5 l, }/ U
Simple random sampling, 简单随机抽样* l/ _6 u; [& ^/ C8 f; a3 ^
Simple regression, 简单回归& q% A6 S; u. k; {
simple table, 简单表3 j! @1 x9 C" ~" V! l2 v& t! l
Sine estimator, 正弦估计量8 r2 Q0 [- a+ Q+ X$ x* H& }! I
Single-valued estimate, 单值估计
( M8 Z3 k+ _. i* z! Y/ q+ ySingular matrix, 奇异矩阵
" W9 s: D0 }% _& aSkewed distribution, 偏斜分布9 F% c$ \: b+ B: T" p
Skewness, 偏度
7 Q2 i, \0 w0 T1 e9 [8 f: d# j. CSlash distribution, 斜线分布
/ o$ @/ i% l) r- @" I6 S) u1 WSlope, 斜率' K1 P! V! E. D6 M2 \" _$ z
Smirnov test, 斯米尔诺夫检验
[# s- g/ c) _. @$ xSource of variation, 变异来源
9 r( _% O* x& @9 S, zSpearman rank correlation, 斯皮尔曼等级相关
, a+ W+ ^! Z2 Q) h! a) I0 h! q& o9 rSpecific factor, 特殊因子- F$ |8 E/ y( p& }0 G
Specific factor variance, 特殊因子方差
9 [: @5 @( p) ]9 H+ r+ ~Spectra , 频谱
. C5 C% D" F9 `. B: M' I7 wSpherical distribution, 球型正态分布; |7 E3 A/ J0 V" W; f# R( b
Spread, 展布! @. g( \ Q9 o2 {/ u6 \, m) @
SPSS(Statistical package for the social science), SPSS统计软件包
& m& N+ o' a- B, {& j' P% }Spurious correlation, 假性相关9 U/ o' O7 x( r
Square root transformation, 平方根变换9 @, x0 _! p0 I9 K2 O
Stabilizing variance, 稳定方差
* M; c; d' g `% CStandard deviation, 标准差0 D* k2 @, k6 [9 _! _! P
Standard error, 标准误9 G2 A. A( C3 ]( G
Standard error of difference, 差别的标准误
4 [6 `7 I8 W7 t; Z2 QStandard error of estimate, 标准估计误差+ [( M9 m: v) q3 C9 c
Standard error of rate, 率的标准误- H: a( r. D* h5 Q% D7 L) Y
Standard normal distribution, 标准正态分布
" D. S1 E& F+ _) vStandardization, 标准化9 E) g9 @* Z" L3 s! W5 ~
Starting value, 起始值6 S2 v1 ?* J' L( `4 j# B4 r
Statistic, 统计量+ S e$ F- |- J5 @1 R9 n2 N5 t
Statistical control, 统计控制' N% T7 p; F2 n' U
Statistical graph, 统计图
6 |: P) D+ {. E8 a8 p, D( _Statistical inference, 统计推断9 x. \5 A5 I) Y+ [# @! i
Statistical table, 统计表
0 S7 [4 u$ F+ d! L( z& c7 p0 tSteepest descent, 最速下降法
# _" J$ \4 d2 `. a3 n% F) yStem and leaf display, 茎叶图* a+ i) |( g8 y1 N0 U+ @4 e; J1 T
Step factor, 步长因子
* H7 b6 @8 O* M! CStepwise regression, 逐步回归8 }, ^5 n- ^; }
Storage, 存
8 O Q- W8 n v9 VStrata, 层（复数）
$ D1 B5 c; b$ {7 K% y; v( dStratified sampling, 分层抽样
) L) |9 o( P R& w2 GStratified sampling, 分层抽样
/ n h' |) b! I1 v5 KStrength, 强度% ~- F* z+ F) K6 J. a
Stringency, 严密性: @2 H. ^: l Y" `7 S. Q4 \" w
Structural relationship, 结构关系
6 t. y' g, S+ j5 M4 n5 C; RStudentized residual, 学生化残差/t化残差# K/ Z6 w+ X" B. g+ s
Sub-class numbers, 次级组含量
4 G% v' O0 P W3 L; ]1 }3 QSubdividing, 分割
/ M+ u+ j- a+ x cSufficient statistic, 充分统计量
' F2 k& q$ g3 dSum of products, 积和
8 B+ z9 L; u2 i$ u- ] ASum of squares, 离差平方和* I* d" v4 h- G
Sum of squares about regression, 回归平方和
! N: x( {2 E' D( e7 t @Sum of squares between groups, 组间平方和
# g5 K0 q( ]) [& { d* iSum of squares of partial regression, 偏回归平方和
2 K5 A5 Y* s8 ]4 dSure event, 必然事件3 k% _& [# W- s; W& V# ~# [' e) e0 X3 w4 G
Survey, 调查2 ^5 {# A' w5 ^; N2 S; T
Survival, 生存分析1 V$ P4 C$ t3 V7 Y8 C' f
Survival rate, 生存率7 H4 U, q2 y4 ]4 ^0 h7 c2 U
Suspended root gram, 悬吊根图* O1 I( X0 o9 J0 V9 e9 R1 H# B
Symmetry, 对称, F, z/ p7 A. o+ P
Systematic error, 系统误差
4 U% E4 s4 Y8 h# g/ t5 f3 xSystematic sampling, 系统抽样
! h# K& F5 s! B7 O" a$ H' f6 ]Tags, 标签1 [$ T* L( E6 |7 p
Tail area, 尾部面积* ?6 z4 q( n) m% u6 H1 c6 u
Tail length, 尾长
8 D8 q3 l/ e, pTail weight, 尾重) ^9 a+ t$ \% `! O- T
Tangent line, 切线& U* z) |# p) A6 o8 S
Target distribution, 目标分布. E9 c8 a' I/ J/ _' G
Taylor series, 泰勒级数, Z/ g% x. o8 {" C) V
Tendency of dispersion, 离散趋势
! l1 u) } [+ h- N) wTesting of hypotheses, 假设检验- V, f. f( Y: L7 W+ k3 N
Theoretical frequency, 理论频数
$ d# `) ? q$ w0 U4 TTime series, 时间序列
- W: @3 B. {0 Z$ D: vTolerance interval, 容忍区间
' _' R# o* ^3 tTolerance lower limit, 容忍下限 N- z* t5 F2 c; M# A( a( F1 M! F
Tolerance upper limit, 容忍上限" ~7 Q0 C N4 n' m1 v* ?2 I
Torsion, 扰率
" @: T- e5 I7 O+ @- ^. N8 TTotal sum of square, 总平方和
. Y% r! L6 P3 t2 {Total variation, 总变异7 _) y3 O9 H" @
Transformation, 转换
4 e: U7 t; N( s; \- hTreatment, 处理% D6 H* b4 t, z0 d9 ?, r- E2 M
Trend, 趋势+ I& e6 s' s, G, ^* H6 b
Trend of percentage, 百分比趋势. k! o9 w. ~& {$ s+ f; t3 K5 s
Trial, 试验5 b8 o: Q1 ~2 l
Trial and error method, 试错法7 ^7 n$ G$ ^0 b) b$ d* y
Tuning constant, 细调常数 c9 _0 ^% K7 L+ h* m0 j- ~
Two sided test, 双向检验' V* m9 Z5 G9 Q6 `
Two-stage least squares, 二阶最小平方' b3 z( C- D1 y% s- Q
Two-stage sampling, 二阶段抽样
3 x) U/ m; z: L4 T; [9 YTwo-tailed test, 双侧检验' p; \0 ^" I$ ?4 J# K; h5 J
Two-way analysis of variance, 双因素方差分析
- ^, h4 o8 T4 t8 ATwo-way table, 双向表) ]7 j! n5 R& O- \' k* m
Type I error, 一类错误/α错误4 S( R+ r" u. S W
Type II error, 二类错误/β错误
- P0 ^- a; q' X) w; o# D* pUMVU, 方差一致最小无偏估计简称/ h4 v K8 L7 o! h
Unbiased estimate, 无偏估计
$ { r" _* k$ z5 MUnconstrained nonlinear regression , 无约束非线性回归 ?$ R% {' Q3 S% K* I8 o
Unequal subclass number, 不等次级组含量* S& Y) O8 s' v( R9 \9 c
Ungrouped data, 不分组资料
4 k& ^- D9 s, s9 FUniform coordinate, 均匀坐标* F" u0 [6 s: g: x7 F$ u* ^' W
Uniform distribution, 均匀分布: H7 J, v4 y* M+ T6 _
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
' n1 d6 p4 d4 V1 J. T8 j+ p$ ^" c4 W1 oUnit, 单元
1 T# T) U h: b5 x& h: cUnordered categories, 无序分类! W9 o% E4 x( J
Upper limit, 上限
7 k4 x, g% w% gUpward rank, 升秩
9 w" y( W4 y% t5 s. [7 n; \* ZVague concept, 模糊概念+ [( i: g$ q! |$ b# q5 y3 q1 S
Validity, 有效性' a3 h( c K3 D" r8 I0 \3 i8 N
VARCOMP (Variance component estimation), 方差元素估计
0 H) j, c, g+ o% d+ E% q% kVariability, 变异性- o% K# N) {# B" C0 h& p
Variable, 变量& A4 K0 U, s% {
Variance, 方差% ^/ b' }4 s F
Variation, 变异9 D$ S. ^' |$ P. H# _: ?
Varimax orthogonal rotation, 方差最大正交旋转
0 s5 @( f/ s' o0 FVolume of distribution, 容积
! g5 O D& ?" s9 u0 E. wW test, W检验6 j+ ~! u1 |9 B) Q
Weibull distribution, 威布尔分布
1 ]: q9 S0 s, @; h1 MWeight, 权数5 V3 K- x' i5 q ?6 k% [4 @4 |
Weighted Chi-square test, 加权卡方检验/Cochran检验
8 U* h1 G2 q3 }! {6 ]! FWeighted linear regression method, 加权直线回归
6 |5 I' F* f7 }0 BWeighted mean, 加权平均数
0 o3 [+ O2 T7 p0 S' NWeighted mean square, 加权平均方差 n% z- T- K! v# c) k; O- w6 T/ _
Weighted sum of square, 加权平方和
( U5 {+ H8 H- f% E C9 p4 A, h, V% jWeighting coefficient, 权重系数+ P6 B, ^& ?; ]/ u! J
Weighting method, 加权法
2 ^ X$ R2 D- o; ~+ m9 E3 ~; I9 tW-estimation, W估计量- Y# e& x- o! _/ ]+ T
W-estimation of location, 位置W估计量& M2 S2 n g" q/ o6 W
Width, 宽度# n* C' E3 N& S7 @$ H9 l
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验2 o9 M9 H& } l& l. g* R% \
Wild point, 野点/狂点7 P4 Z% B# n6 K
Wild value, 野值/狂值
8 V4 J$ z3 \3 f+ HWinsorized mean, 缩尾均值
: [' V, U( i+ {) h& U s: TWithdraw, 失访 * w/ n/ v1 l' R8 Q' X I7 f! ~
Youden's index, 尤登指数4 ?) I/ ]1 P, b# u1 F, g1 S: G* ~
Z test, Z检验" s% q% M/ U+ m2 }" z% O
Zero correlation, 零相关9 ^' u( L% ?2 h
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
