|
|
Absolute deviation, 绝对离差
: `% n/ L6 _" Z& `Absolute number, 绝对数& O. |; l6 i/ w& i7 D
Absolute residuals, 绝对残差
, M- q @, {% @" R/ [. rAcceleration array, 加速度立体阵
% q. U1 d7 e5 R( b0 [8 EAcceleration in an arbitrary direction, 任意方向上的加速度* F! |8 T$ _( N, x; L
Acceleration normal, 法向加速度+ [+ [7 q/ T5 a5 y! B. s# `0 y$ l4 c
Acceleration space dimension, 加速度空间的维数) N7 w/ ]0 x7 S$ K8 D4 p
Acceleration tangential, 切向加速度
/ p' ?* ?% y0 O' {7 t) J/ t3 iAcceleration vector, 加速度向量
2 g( S2 ]$ X# Y% pAcceptable hypothesis, 可接受假设
, d- s1 g* p; r% z8 @Accumulation, 累积
( @7 v5 j& m: L$ ` v& a/ z9 P% ^Accuracy, 准确度 X: K" g5 ~& c e' p
Actual frequency, 实际频数
+ b8 e; G5 L/ r7 T" A/ \4 QAdaptive estimator, 自适应估计量
0 Q) {2 O$ c* h2 k5 FAddition, 相加# ?) x# j! y( r1 ?! ^
Addition theorem, 加法定理
6 m/ Y* A [/ A) z! k6 O( ^: `8 RAdditivity, 可加性) L" w8 u: _" @4 z' a0 a: J: ^
Adjusted rate, 调整率
7 q6 h, K5 c9 r, h! {1 |# nAdjusted value, 校正值 r7 c6 c! @6 P3 o/ L: u, v2 X% D
Admissible error, 容许误差, c0 Q9 d! K+ }# d
Aggregation, 聚集性
! [* p# H w3 v2 y- Y4 @, IAlternative hypothesis, 备择假设
7 ?# ?. V1 z1 q. i N+ N: y3 BAmong groups, 组间
) W: C* [# @, ~* O$ @Amounts, 总量
8 k1 a$ b$ }8 B1 fAnalysis of correlation, 相关分析
* N: @9 K; X7 Y: e; x$ G0 iAnalysis of covariance, 协方差分析
) u& Q2 u7 X' gAnalysis of regression, 回归分析2 p* S/ K- Z$ G1 g J
Analysis of time series, 时间序列分析
* }) T1 W+ U& D. V) o! `$ d/ v8 h4 m: iAnalysis of variance, 方差分析
8 T, }+ H, ^' o/ [" Y9 B& @7 fAngular transformation, 角转换* p9 o8 G/ x- f* k; O$ O
ANOVA (analysis of variance), 方差分析
@/ Y# Y/ F. n9 D) {9 ?8 zANOVA Models, 方差分析模型6 T9 f( C7 l* w+ h B1 V
Arcing, 弧/弧旋
" t, t) R4 d$ T+ n( QArcsine transformation, 反正弦变换2 K4 L2 I$ A5 s- {6 \
Area under the curve, 曲线面积, B+ ]1 A& ]8 \3 b# i) K
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 b2 b7 J& {( Q4 \+ a( R3 VARIMA, 季节和非季节性单变量模型的极大似然估计 & n# z! g3 b* x3 p x
Arithmetic grid paper, 算术格纸& c& Q1 F, B2 n
Arithmetic mean, 算术平均数1 o" P2 v2 h1 n8 p0 M
Arrhenius relation, 艾恩尼斯关系1 Y o7 W2 O7 G6 t4 M
Assessing fit, 拟合的评估! r* Z- f6 K: F( e# j; G
Associative laws, 结合律! B, z' c% d0 U# B
Asymmetric distribution, 非对称分布
0 [( m& i" H% D; K& aAsymptotic bias, 渐近偏倚
' e" Z |. A3 QAsymptotic efficiency, 渐近效率
9 v* K' R n) n* Q. eAsymptotic variance, 渐近方差# x+ m1 e: C$ x( ~9 X- i
Attributable risk, 归因危险度
) L) \* {/ ?: S: e& l( l5 N0 |Attribute data, 属性资料
. k/ K* b3 A& F# n$ p. |, IAttribution, 属性! W# O. I2 u4 w! M
Autocorrelation, 自相关/ v9 E: y6 x: s$ a
Autocorrelation of residuals, 残差的自相关
8 q0 Z/ P5 v; r9 j% A6 oAverage, 平均数$ w8 C9 z# ^& `2 X- e5 v" t2 T
Average confidence interval length, 平均置信区间长度
4 I( }3 z/ P+ m% JAverage growth rate, 平均增长率& X% S4 B- N( t: F2 I
Bar chart, 条形图1 z: u$ X! k$ G4 M7 M
Bar graph, 条形图/ X( l/ k: M) i
Base period, 基期
: f. P0 c* T$ W4 H9 r WBayes' theorem , Bayes定理 {+ Q# j( U- p% y
Bell-shaped curve, 钟形曲线
; S1 O, i$ q9 F5 V2 V4 WBernoulli distribution, 伯努力分布* Y$ w- `$ r! |- a0 U! m+ k
Best-trim estimator, 最好切尾估计量
" j3 U& C& H3 @$ s; g8 ?Bias, 偏性
6 e# x2 R# y2 l5 jBinary logistic regression, 二元逻辑斯蒂回归: ~- x9 y3 v/ g6 l& b
Binomial distribution, 二项分布
' x6 R9 z6 ~7 S) E0 BBisquare, 双平方& I6 x. K" u% a1 K6 w2 A
Bivariate Correlate, 二变量相关% F7 f" @ w; M* |- P4 v
Bivariate normal distribution, 双变量正态分布- n" O+ E3 d0 ]0 e: U
Bivariate normal population, 双变量正态总体3 q3 A& O1 R" Z5 Y& [
Biweight interval, 双权区间
1 U. Y* K( s5 ? r* S. h% Z' lBiweight M-estimator, 双权M估计量' T2 M2 C( @ k2 M1 T* T: F
Block, 区组/配伍组, j! [. l5 o7 t( S5 m7 ~- U
BMDP(Biomedical computer programs), BMDP统计软件包! v5 j$ H$ H: T7 ~! T" }) i5 S
Boxplots, 箱线图/箱尾图
t! Q2 b2 F" y) \! s( }+ nBreakdown bound, 崩溃界/崩溃点. b! d2 O4 ~0 x; E( ?
Canonical correlation, 典型相关- w0 n5 x" m, ?. J/ l0 E4 |
Caption, 纵标目9 K- K5 M7 f t9 o
Case-control study, 病例对照研究
( q, H: C' {! }. G. ECategorical variable, 分类变量
2 m! y$ h; L' x* ECatenary, 悬链线- d9 e/ y. _) U2 U
Cauchy distribution, 柯西分布
1 o1 {# `1 v3 j, i/ n# w/ \: U# j7 }Cause-and-effect relationship, 因果关系
' H7 h# `; f. B2 z! q7 pCell, 单元3 S, j0 r s4 X5 p* ^
Censoring, 终检
2 _, p4 H0 C/ z) J* b- `$ m, rCenter of symmetry, 对称中心
5 m7 l4 {; n; Z: e2 b% N) FCentering and scaling, 中心化和定标
6 o: w, R/ v6 b9 H2 J Q+ xCentral tendency, 集中趋势; h5 }0 ^+ L6 c% Z* t @
Central value, 中心值
' t) N! I Y! c% v0 ICHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
% \- ^% o4 O! d: `( ?& N( |Chance, 机遇
8 P4 S3 V% b- d0 R( ZChance error, 随机误差( E0 c# e( q( r. H5 Y2 W( i
Chance variable, 随机变量
: n5 t+ g& u6 nCharacteristic equation, 特征方程
) g% ?- P, @7 Y. J" iCharacteristic root, 特征根5 z. |% I; r5 q
Characteristic vector, 特征向量
3 V3 B, p+ j; c" V. ^& S% eChebshev criterion of fit, 拟合的切比雪夫准则
) Z/ ?6 E. p+ p. O' M4 u1 g# uChernoff faces, 切尔诺夫脸谱图0 A, b* g/ y( R1 p5 W2 a F Z) ?
Chi-square test, 卡方检验/χ2检验- l, _9 J1 Y0 M1 F
Choleskey decomposition, 乔洛斯基分解* F. [1 ?7 K4 E, x
Circle chart, 圆图 ) b! m. w3 A* z S# |
Class interval, 组距. S+ e; {- M3 e5 u6 Y y0 ?
Class mid-value, 组中值
6 @% [# [3 i+ W5 GClass upper limit, 组上限
3 _+ U+ ]9 A9 DClassified variable, 分类变量 Q% `5 F5 r: b1 m
Cluster analysis, 聚类分析
5 Y/ a! Y. J, c3 C( qCluster sampling, 整群抽样
- R, O& e: K1 d) c7 W+ Y& JCode, 代码' b3 o7 j: W, u" U! e9 A
Coded data, 编码数据
" _1 S; a) b4 I0 t+ iCoding, 编码- H+ j9 j5 J! |9 J- u
Coefficient of contingency, 列联系数
. `# H3 z" g' m# p' z0 ]. y P9 vCoefficient of determination, 决定系数
* g/ b% H2 A& Q" g6 aCoefficient of multiple correlation, 多重相关系数
1 N; z3 O: h I$ lCoefficient of partial correlation, 偏相关系数8 G: i1 \% q3 o) w: {
Coefficient of production-moment correlation, 积差相关系数
6 d4 X8 W6 Q9 @% V" GCoefficient of rank correlation, 等级相关系数+ Y+ u8 z4 \# x* R3 m* B8 I
Coefficient of regression, 回归系数7 }9 w3 V. w* H# t
Coefficient of skewness, 偏度系数
! f2 i! m6 K0 M& @8 m6 DCoefficient of variation, 变异系数3 O/ N0 }5 }1 ^1 o- |
Cohort study, 队列研究
. K$ z8 q+ U2 A: _5 R9 c2 q7 [Column, 列
2 d$ b8 [. V/ S6 E7 L/ a LColumn effect, 列效应7 @! X% j! \. l* P _
Column factor, 列因素7 K& }/ X1 N. Z6 S( x! ]3 _ l' s7 @
Combination pool, 合并
* ] S) F. L+ mCombinative table, 组合表( O+ H7 h0 ?% ~" J
Common factor, 共性因子
- E9 w2 K+ w- e& x( s1 F, O: mCommon regression coefficient, 公共回归系数
! Y( U- `5 |% S u5 S$ kCommon value, 共同值
, t0 X$ K) b' n" o# VCommon variance, 公共方差2 ]. V; d& P" l8 e7 ]' x
Common variation, 公共变异: Q3 P! y$ ~' l
Communality variance, 共性方差
! f1 o- r3 x, G z# d3 ^; NComparability, 可比性7 v- I$ \* V) ~. Z% [9 K
Comparison of bathes, 批比较
) p5 P* V" h/ s0 sComparison value, 比较值3 p$ V8 ]: m2 M) j
Compartment model, 分部模型" d- I# W# ?! a9 A$ j" {
Compassion, 伸缩, F) J2 P; [, G2 ?& O5 j
Complement of an event, 补事件
; g2 b. A1 q: M' b; ~6 AComplete association, 完全正相关; C' L/ K& F' b& Q G
Complete dissociation, 完全不相关
+ J% a/ f: _0 ~, U. W! \Complete statistics, 完备统计量3 [8 N' r h4 K; S
Completely randomized design, 完全随机化设计% o$ `# Y3 R* m5 ]6 p
Composite event, 联合事件
0 g) \# W" }0 s* dComposite events, 复合事件$ s0 Q& w; v; G2 l* F5 \
Concavity, 凹性
! r+ T6 E: @2 K2 M8 ~Conditional expectation, 条件期望1 H3 F( R8 D# u! ^! w% ~
Conditional likelihood, 条件似然
2 ?" _4 B" s- }4 p2 a1 J# b1 ~Conditional probability, 条件概率
0 M5 G4 _8 c, A) k, y6 e+ oConditionally linear, 依条件线性
& {& d; [# s% t# j9 kConfidence interval, 置信区间
! P0 c! R6 a; C( {Confidence limit, 置信限8 F1 p& {( l' j. `7 _
Confidence lower limit, 置信下限# M: x) b! R- x. y( Y& X
Confidence upper limit, 置信上限
$ N. R% K- i8 V0 D/ q3 x3 nConfirmatory Factor Analysis , 验证性因子分析
1 ~( @2 }! E! h5 m. a$ LConfirmatory research, 证实性实验研究- Y9 h, s4 V5 B1 f, G9 S7 j' P. Z; q2 j
Confounding factor, 混杂因素
9 ?! X" J2 @4 m; y; D5 V8 k( bConjoint, 联合分析' q' h2 u1 ~! Y+ V
Consistency, 相合性! M$ V x! K3 c3 o4 C+ K
Consistency check, 一致性检验/ W" G+ ~5 I1 G" o1 O
Consistent asymptotically normal estimate, 相合渐近正态估计
* g7 y' T% I9 u# gConsistent estimate, 相合估计4 P) V3 Y k0 ^( t: f4 I1 u
Constrained nonlinear regression, 受约束非线性回归
* i* `: ~/ J+ N, lConstraint, 约束
! Y: B1 T4 a4 E5 ]9 o }- m$ H% ]Contaminated distribution, 污染分布! @4 b" q" w. h/ p* v
Contaminated Gausssian, 污染高斯分布. T1 y5 W, R' p/ ?0 M; u. m( D
Contaminated normal distribution, 污染正态分布* ?0 c3 l' Z2 G
Contamination, 污染
* E: e! Y4 P' N+ H2 B' zContamination model, 污染模型9 y4 ~/ g: g s; T$ B$ Q% L
Contingency table, 列联表
- {8 O8 L, z' g& J* i% {: EContour, 边界线
- E* x! U0 V4 m% A- QContribution rate, 贡献率
* `% K& S* Q. B& L& ]Control, 对照
. G; w% h7 q- |7 RControlled experiments, 对照实验9 T4 o: H/ H" [& O; e Y/ S/ d
Conventional depth, 常规深度
: X3 K, O6 \6 A; \: ]Convolution, 卷积7 f) O4 E5 D6 J8 b; Y; \ y
Corrected factor, 校正因子
! u* h$ c* `: M# }8 @4 d0 `, w! SCorrected mean, 校正均值1 y! N/ N; X Z/ Z
Correction coefficient, 校正系数
2 V; s N. b, G* v: y, M' NCorrectness, 正确性7 P8 t* |- x3 H4 O; z' G3 B
Correlation coefficient, 相关系数
- x, O4 P/ d1 U% S4 b, w! yCorrelation index, 相关指数
. W! x: x! l$ j$ O6 ~Correspondence, 对应6 j) Z, R0 V$ W" S6 Z
Counting, 计数
8 N6 ~- `; G" M; Z5 W5 n- ICounts, 计数/频数! ]# r8 Y! j& q3 `
Covariance, 协方差( C3 D# i6 k% T7 r1 n' A
Covariant, 共变 , T* |: [8 D# Z8 ^1 z8 F
Cox Regression, Cox回归4 Q: \- j5 b F- x
Criteria for fitting, 拟合准则" T0 ?& Z; d+ E+ m8 I
Criteria of least squares, 最小二乘准则% k3 a% _; W$ w" @) j$ j8 C( E8 v9 p
Critical ratio, 临界比3 T" C0 d1 j. f$ B! a" `8 U: f9 v9 f
Critical region, 拒绝域+ B( @8 X1 q3 q6 l* }. A0 m
Critical value, 临界值* M: ]5 p7 v: ]
Cross-over design, 交叉设计
5 i: [; Q6 W6 w! jCross-section analysis, 横断面分析
+ _1 Z" e5 D [5 W1 fCross-section survey, 横断面调查
1 o1 k- {" F1 tCrosstabs , 交叉表
6 ?! |5 b5 [; i. n; {Cross-tabulation table, 复合表
/ K4 i4 P0 y$ T, l) U9 t! kCube root, 立方根4 T U- j/ _( e4 v b0 r
Cumulative distribution function, 分布函数
' c7 k0 b; E A! T& c6 V' O5 {Cumulative probability, 累计概率+ [6 q8 T- e& d6 U5 C
Curvature, 曲率/弯曲: `; l: B4 ?. E. U+ A
Curvature, 曲率
" ?* z g C" e0 vCurve fit , 曲线拟和
4 z c% v. g5 S+ m3 h/ s, N* ]Curve fitting, 曲线拟合$ p6 h! [/ L5 x/ B: y% @9 a4 ]' U
Curvilinear regression, 曲线回归
# r& s$ V, P. i: QCurvilinear relation, 曲线关系
; z# A* `( ?; z. r6 ZCut-and-try method, 尝试法
8 ^1 A8 O H: _* [Cycle, 周期
9 _! Z1 R) ?/ X1 w8 {. I# B$ {2 P' QCyclist, 周期性
6 [4 ^3 a1 q! w% G+ KD test, D检验6 x3 t1 k" F! z4 d" ~, ^1 i7 S3 K4 y2 n
Data acquisition, 资料收集
. ~, \8 a: q' a0 v0 QData bank, 数据库
! R! \! s/ c* sData capacity, 数据容量
+ X* k& {1 l. f5 p" H) r/ Y; VData deficiencies, 数据缺乏, J0 o; E( c0 O& e# o" l
Data handling, 数据处理
; U T+ `; _4 W. m1 lData manipulation, 数据处理8 \5 X# p6 O& _
Data processing, 数据处理 e% ]/ g; ?( _- C/ q' Z
Data reduction, 数据缩减- J& o2 b# k S# K6 n: t! a8 V
Data set, 数据集
2 z* x' `3 X2 g5 |9 {$ ^1 KData sources, 数据来源
$ M" Y9 | X7 c& NData transformation, 数据变换
- M) V, H0 h/ q' NData validity, 数据有效性
+ I1 V# J ?( W6 `/ uData-in, 数据输入
! [) d$ z' L) C+ V5 zData-out, 数据输出7 o3 [: _- a b& M% z6 T0 ^
Dead time, 停滞期
9 e$ m) |2 t, @ lDegree of freedom, 自由度2 b4 B4 ^ Y0 U" |% ]; Q: k- m7 [
Degree of precision, 精密度) p; L% U( B& l$ D& |
Degree of reliability, 可靠性程度6 o9 I& J; C9 G, u' Q
Degression, 递减/ U8 }# B; t0 ~* ^6 R& I* B u
Density function, 密度函数5 A9 _9 f( |, M, {" D
Density of data points, 数据点的密度
. ?- M$ b5 @9 I! f! T' fDependent variable, 应变量/依变量/因变量% s5 Z1 Z, B" N. ]; [
Dependent variable, 因变量
0 w) ~) [, j c& [2 s* vDepth, 深度9 v0 {9 U& S/ }: O
Derivative matrix, 导数矩阵7 r. V& B' v2 B0 l# _
Derivative-free methods, 无导数方法
3 X6 w* v4 G& @Design, 设计
* z; m5 P7 \. m; v* T/ TDeterminacy, 确定性
7 p, T, f% S9 i: |9 ^" I9 [Determinant, 行列式
& J8 q2 R/ |2 y! C. u8 N1 [Determinant, 决定因素( \# i: B, m* Q# S4 {) X4 @9 y% @
Deviation, 离差; a6 [ s- C9 ?8 E
Deviation from average, 离均差5 b3 _0 h9 ^0 Q4 P
Diagnostic plot, 诊断图# T0 q* E$ v: u. Z7 M
Dichotomous variable, 二分变量! @! ^3 _3 ~; x1 {, s/ W
Differential equation, 微分方程
2 H" E) s! T1 \5 PDirect standardization, 直接标准化法* G3 E3 {% `, e7 O: ]5 A, x
Discrete variable, 离散型变量
$ Y8 B n c1 {3 S+ qDISCRIMINANT, 判断
; b7 Q( e' ?9 @1 ~, H- J; m3 qDiscriminant analysis, 判别分析
; L+ B" O, N( a" G$ _Discriminant coefficient, 判别系数
9 O' ?+ B2 \, `- ?) ?Discriminant function, 判别值( b1 ^3 k0 q' z* `& U1 W
Dispersion, 散布/分散度' Y' q) Q& ~' Y8 m
Disproportional, 不成比例的4 a6 \) g! L* q% }3 O7 O, ] y6 V
Disproportionate sub-class numbers, 不成比例次级组含量9 B. T. ~0 V6 R" X7 M9 ~
Distribution free, 分布无关性/免分布
2 H8 p3 c) U5 q+ |! L5 `" tDistribution shape, 分布形状% }' ^, Y6 n* K! }# E
Distribution-free method, 任意分布法" }; ?; D9 _" v$ l1 I* R
Distributive laws, 分配律! E, T9 c/ S Q/ N# Q5 ]0 A* b5 a
Disturbance, 随机扰动项
1 R1 u' } ~% y' k9 w; ^Dose response curve, 剂量反应曲线" Y0 P# Z6 |0 n, k2 b% t, L
Double blind method, 双盲法
' B# M# u9 F7 x# ^Double blind trial, 双盲试验
/ V# S" Y# Q( fDouble exponential distribution, 双指数分布
0 d# r4 I! d4 Y* t8 MDouble logarithmic, 双对数
a# }4 W$ [2 T. F3 Z, EDownward rank, 降秩
; L5 ?* C$ j/ o6 t4 ? x0 a1 P. GDual-space plot, 对偶空间图
( q' i$ f( G% p3 VDUD, 无导数方法
- c$ r( G1 a% I5 n2 g, ~. h: E6 U( oDuncan's new multiple range method, 新复极差法/Duncan新法4 s8 j2 I, [. x) U: h3 t
Effect, 实验效应2 i1 k% B$ I6 K: k8 v& [
Eigenvalue, 特征值) H( M2 _& e: R5 b! k! g
Eigenvector, 特征向量8 I0 \1 N: l3 Q& ^8 w
Ellipse, 椭圆) d. `( O7 h0 m3 j/ w. U
Empirical distribution, 经验分布# K/ k% Y( g3 @1 z) ]) o! o
Empirical probability, 经验概率单位; {" ]/ Z3 [8 {) h
Enumeration data, 计数资料
* }. n$ D. a7 ]+ Z8 fEqual sun-class number, 相等次级组含量
9 Z s+ v/ u- g8 f) EEqually likely, 等可能$ x' P+ k0 @+ R: y8 Q. O# ]
Equivariance, 同变性2 _# f5 l. H! ^* \! l" ?) G+ O9 @
Error, 误差/错误
4 ?: ]% d* d" v$ FError of estimate, 估计误差
4 I, c/ t7 D4 w3 e/ WError type I, 第一类错误
+ C0 Z/ I! z iError type II, 第二类错误' U) g$ M: @ l9 ~ w+ s2 E
Estimand, 被估量
3 C1 a _8 B; |$ p; I3 FEstimated error mean squares, 估计误差均方% Y8 @6 z! f3 s: E
Estimated error sum of squares, 估计误差平方和( [- X8 n/ J, u. V0 ]
Euclidean distance, 欧式距离) J. `+ X% q# U1 D
Event, 事件
& x( V0 s* T2 `6 j3 T7 d( xEvent, 事件
H5 O3 b8 `. K! ]3 g) A% c) FExceptional data point, 异常数据点' m% e- F' f) J" ?+ Z' p1 v
Expectation plane, 期望平面* o2 `# ^. b# K( a c9 i e
Expectation surface, 期望曲面- t: w' m% ^7 n0 {5 ~' B- n
Expected values, 期望值
5 ]4 S5 y# m( WExperiment, 实验
6 E4 i7 A' y) ~4 `Experimental sampling, 试验抽样
) N$ }0 \5 v/ e8 @! aExperimental unit, 试验单位
0 t g, m N: GExplanatory variable, 说明变量5 f3 _+ h2 z- p' w1 {
Exploratory data analysis, 探索性数据分析7 C, ?8 a6 j) c, z! _' |
Explore Summarize, 探索-摘要: P k7 k0 ^7 i: \
Exponential curve, 指数曲线
; J! {0 p9 h8 NExponential growth, 指数式增长
8 b- ~, T$ b* T z4 VEXSMOOTH, 指数平滑方法 " j+ w' ^; X8 t: a/ h- l
Extended fit, 扩充拟合7 P" o/ ~5 a! V+ y' Q; u
Extra parameter, 附加参数
. m3 b( x8 R' r4 ~Extrapolation, 外推法/ [/ |& X, \, T, P' `( S
Extreme observation, 末端观测值2 r+ B( W0 C' Q- x1 ^2 f
Extremes, 极端值/极值% ~" r$ w* c1 b
F distribution, F分布
8 o; y4 I5 w' `4 ^( p" p+ i4 hF test, F检验
( S: g, _) ]- o; [4 GFactor, 因素/因子
& a+ S0 G( Q9 w, O- U. T: z8 s" mFactor analysis, 因子分析 f" O+ g* C C b3 z5 l
Factor Analysis, 因子分析/ i$ J+ r a }" Q# P
Factor score, 因子得分 . c7 \5 I- C* U @
Factorial, 阶乘
, ?6 T7 B* F& z+ v3 n' kFactorial design, 析因试验设计/ f" c8 o( B$ ~7 i6 E) d0 h/ K" j
False negative, 假阴性
1 ^# g4 z. x; L+ m u) ?: j' F0 BFalse negative error, 假阴性错误
- e. ?8 B" K% m" o ~% dFamily of distributions, 分布族
; I; }7 {* E: p# z- ZFamily of estimators, 估计量族
9 w0 U2 _- d* x+ K- i) B4 A) gFanning, 扇面+ [, S" ^) D/ t1 u3 R( S; x
Fatality rate, 病死率& @; _1 z n2 f0 I5 P
Field investigation, 现场调查
$ T; r* S) h5 GField survey, 现场调查
$ L6 m# v! x3 x$ }Finite population, 有限总体
5 z+ i. E6 v4 `/ \/ V) u6 J/ ^Finite-sample, 有限样本; G; N8 o( x* h; U
First derivative, 一阶导数
! L$ Z% |9 A) h& Q: d/ y' r: cFirst principal component, 第一主成分
6 i4 O. {! ]# W/ @' XFirst quartile, 第一四分位数+ O; U2 A- x/ A! q( R
Fisher information, 费雪信息量6 n. u& j/ h; {3 w, S
Fitted value, 拟合值
5 e( ~: `* ?7 D: m" u4 [9 rFitting a curve, 曲线拟合6 k8 X+ C9 A% {0 `" N& O
Fixed base, 定基) B9 D5 w6 q6 A5 D. Q
Fluctuation, 随机起伏
. d" s! j5 K1 B! QForecast, 预测
% Z* a1 C0 l' F+ b' U# gFour fold table, 四格表
; _+ _* M5 x! h, v! xFourth, 四分点
6 t$ J$ L, ]& J# o* x5 A CFraction blow, 左侧比率
1 d* O6 G" N, ~3 ^- ~Fractional error, 相对误差
x( |1 M9 d0 s+ tFrequency, 频率
+ l+ l- H M1 O+ f4 h1 P2 SFrequency polygon, 频数多边图
6 Z. d5 D. J/ E1 _# h' GFrontier point, 界限点" O: q8 S7 l* ?- O0 q
Function relationship, 泛函关系
# R2 w! L }( r3 ?. p: @Gamma distribution, 伽玛分布 Q, Q9 v5 W' R: S5 L. d$ P
Gauss increment, 高斯增量' ~' Y' J" c7 d1 h
Gaussian distribution, 高斯分布/正态分布
* ^; V6 ^2 R8 U: g* i9 k6 k' k& hGauss-Newton increment, 高斯-牛顿增量
# g2 {* Y3 q0 b: aGeneral census, 全面普查& ?, k$ b0 V9 \* C! n# U6 G
GENLOG (Generalized liner models), 广义线性模型
8 S6 o* i% l4 NGeometric mean, 几何平均数 ]* J, T) G4 d& h
Gini's mean difference, 基尼均差5 M" Q( x( _5 K- Z
GLM (General liner models), 一般线性模型 5 ]: _- E9 B, `" a5 V1 T
Goodness of fit, 拟和优度/配合度
& Z8 W' S @1 RGradient of determinant, 行列式的梯度
. {# D4 D& C. @2 t# s6 LGraeco-Latin square, 希腊拉丁方% A* f* E D) h+ h: \8 j, n
Grand mean, 总均值+ q% E+ d1 Y1 P) ^7 m
Gross errors, 重大错误1 m2 ~# I4 d4 g! `& K$ v
Gross-error sensitivity, 大错敏感度6 c! z7 S8 _1 {4 U
Group averages, 分组平均1 l+ m$ o% T5 N( ~9 S* a
Grouped data, 分组资料
5 u! e7 V+ P- qGuessed mean, 假定平均数
$ _" ?. [$ H; h5 k" V5 |Half-life, 半衰期1 S6 A# \: ?/ C; m
Hampel M-estimators, 汉佩尔M估计量: p+ J$ N7 g& a1 j
Happenstance, 偶然事件
* b$ @1 n+ Q: ]! FHarmonic mean, 调和均数
& K5 y* G* c" Z P& qHazard function, 风险均数. A! ]* k7 o+ o# s# o1 R+ s) o
Hazard rate, 风险率 I% m4 u% z1 W, x
Heading, 标目
# A* j; a a5 P& w7 IHeavy-tailed distribution, 重尾分布% Q2 l$ m; }2 ~4 Q
Hessian array, 海森立体阵" Q! l7 }# o5 T! V" o# M& m
Heterogeneity, 不同质
' ? R/ g4 o. b1 e) l9 iHeterogeneity of variance, 方差不齐 _/ e3 f" G% O4 @4 Q
Hierarchical classification, 组内分组
1 w7 f D$ n# C7 }2 nHierarchical clustering method, 系统聚类法5 s0 v4 M5 _8 g% ^( E
High-leverage point, 高杠杆率点% Q8 [4 w0 b" `& Q- z2 s8 P
HILOGLINEAR, 多维列联表的层次对数线性模型6 g! q) ?4 e! `
Hinge, 折叶点
; K5 C! c9 K2 t& r( c4 H2 FHistogram, 直方图
: H4 F. g& |* C0 S$ |$ [Historical cohort study, 历史性队列研究 ! t3 G9 d2 K0 P, I
Holes, 空洞
2 K3 m' {# r0 X8 |/ \HOMALS, 多重响应分析9 f# o+ T5 h1 r; u
Homogeneity of variance, 方差齐性
% \; e) _, r9 ^) I. z, c( |3 M- JHomogeneity test, 齐性检验
& Y, f4 C6 k5 d, o# ]Huber M-estimators, 休伯M估计量
) K( Z" Z2 k9 m2 U6 Y6 YHyperbola, 双曲线' j6 B9 c4 l/ V
Hypothesis testing, 假设检验
$ F, A. Y" f8 Y8 p/ KHypothetical universe, 假设总体
& }3 f- |& R* \Impossible event, 不可能事件5 v; L6 l3 l3 C/ c) `- e& F0 S8 _& f7 u
Independence, 独立性
; H7 s3 ~1 o5 dIndependent variable, 自变量 N7 Q! X; f% C
Index, 指标/指数
+ O( m) z# m# @Indirect standardization, 间接标准化法
7 T7 |) K" E9 @Individual, 个体/ L+ U# H. {% g& |" J" z& N
Inference band, 推断带& K7 |8 b1 L" t9 x# |- T, S
Infinite population, 无限总体
$ n# C: W1 N9 S3 x$ K9 R: OInfinitely great, 无穷大
5 O4 q, ?# P7 g7 _3 r9 {2 j5 R$ N5 t! BInfinitely small, 无穷小6 i8 _& k5 b- T( ^( r+ |! c
Influence curve, 影响曲线
2 Z8 `( a" m1 s" ZInformation capacity, 信息容量! V1 y2 J9 n+ y) ]+ h$ H
Initial condition, 初始条件. J' a$ T4 ~8 A) f; I8 Q/ s5 d+ v* B
Initial estimate, 初始估计值) O' a. O& d- X1 B9 S- W
Initial level, 最初水平
- I' E3 ]" l& l0 U5 {; QInteraction, 交互作用; J% L+ W: s4 f, C( o
Interaction terms, 交互作用项
p. q, L2 k; G+ T/ u$ PIntercept, 截距
$ K6 v" d. f7 W2 d9 jInterpolation, 内插法
" i+ @; R8 F, r( ?8 o, QInterquartile range, 四分位距) |) V' W+ S$ X( S
Interval estimation, 区间估计& x+ E2 G! q0 W$ b6 ?
Intervals of equal probability, 等概率区间* \& _9 S' u0 d$ v& [
Intrinsic curvature, 固有曲率
5 S' u, F E: ], }" MInvariance, 不变性
4 ?% ]- I4 i5 SInverse matrix, 逆矩阵4 ~7 {4 f! i+ u% J
Inverse probability, 逆概率
& q' r+ G2 [. A1 LInverse sine transformation, 反正弦变换/ c5 I6 N; }/ @
Iteration, 迭代
+ t' s: O0 W0 z* t3 aJacobian determinant, 雅可比行列式
+ [- r; u# ~) G1 R1 `1 EJoint distribution function, 分布函数
/ n! D6 z1 c0 M1 VJoint probability, 联合概率0 r) u& f( |7 z' }6 j
Joint probability distribution, 联合概率分布; @; L9 p; h3 ]- n* i% g/ H. S* ~
K means method, 逐步聚类法$ `* ]1 a3 \' |9 m5 X
Kaplan-Meier, 评估事件的时间长度
5 P& C) e- L5 v7 s7 B; XKaplan-Merier chart, Kaplan-Merier图! U4 b/ n; f/ I) \& H0 L( D" @$ U
Kendall's rank correlation, Kendall等级相关
2 M- X& j9 } _! X, C' E& XKinetic, 动力学
3 }/ o0 _ U Y. s0 u m, r4 v* E& rKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验 a F/ a0 v& [! Y4 t+ Q" K
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验. O+ ^1 @1 V% y- x( P
Kurtosis, 峰度
5 x0 b5 Y( y8 a5 V9 c1 w" ^0 yLack of fit, 失拟
' E ^+ I: [% jLadder of powers, 幂阶梯
; ]+ A( ~ x- wLag, 滞后/ `; `+ t0 o `. F% F
Large sample, 大样本) d* Z* c$ b0 F1 F$ T
Large sample test, 大样本检验* Y4 a+ j' d& A9 R1 J; h5 D
Latin square, 拉丁方
9 s3 U( f# n3 }6 eLatin square design, 拉丁方设计" V: {- p5 S+ K1 A1 ?' Z4 K
Leakage, 泄漏' P6 u) P8 H1 N& W- Q- O* R
Least favorable configuration, 最不利构形1 c$ A) F) U: {' g! L* C4 o+ b# N
Least favorable distribution, 最不利分布
* ]4 j, c' z5 F+ F- TLeast significant difference, 最小显著差法
3 r: P, M# v+ tLeast square method, 最小二乘法
5 P# \% j$ Q$ h% u/ L* G! ]Least-absolute-residuals estimates, 最小绝对残差估计8 D5 f8 y4 ?7 `: z' K2 _; x
Least-absolute-residuals fit, 最小绝对残差拟合" j- x6 r2 T$ z8 Q
Least-absolute-residuals line, 最小绝对残差线- [3 P8 T) T, I7 {
Legend, 图例
; [& V7 b/ [2 R: H( ?' DL-estimator, L估计量3 q i6 Q8 W8 N' k
L-estimator of location, 位置L估计量* Z/ b/ ?4 ~2 `. w9 [$ m
L-estimator of scale, 尺度L估计量5 e: P4 f+ k! k. _5 l2 E
Level, 水平
9 e8 e1 m) J1 a0 L. j6 w$ _Life expectance, 预期期望寿命
2 ]0 [0 C- Z2 `! l( _Life table, 寿命表
% l1 L0 H, `. tLife table method, 生命表法
( {0 ?& `% @3 v( [: K- P5 H; `Light-tailed distribution, 轻尾分布
0 L9 J4 R2 y- b: l$ [% w2 BLikelihood function, 似然函数( g7 t3 S' Q ]9 Z7 _+ q0 t
Likelihood ratio, 似然比3 S q& o7 o2 C* V( z4 d% K+ e4 t7 c
line graph, 线图
! T$ d$ T, R' \0 KLinear correlation, 直线相关
y8 [+ n& u4 jLinear equation, 线性方程" l0 C! t5 o7 y5 S3 t- d' d) ~
Linear programming, 线性规划6 X) S! o' D- \. u
Linear regression, 直线回归! L' G! ], ^3 ^# s" b1 R8 z
Linear Regression, 线性回归
2 H" M3 K( Q; A; FLinear trend, 线性趋势# @8 y' d3 C9 W; K. w# F
Loading, 载荷
) ^3 X$ Q+ x: Q5 R6 n/ BLocation and scale equivariance, 位置尺度同变性
7 \' e- D) h! C0 zLocation equivariance, 位置同变性
% |6 T& W. U0 I1 H6 H: XLocation invariance, 位置不变性
8 h" L, o- z& ^5 ?Location scale family, 位置尺度族% G0 c- L4 s+ ^% a1 f
Log rank test, 时序检验 % J4 E* J' f3 R# c
Logarithmic curve, 对数曲线& W" ]$ D6 J7 j9 N1 \. Z( X
Logarithmic normal distribution, 对数正态分布
; n! N8 E f" u% u( ~Logarithmic scale, 对数尺度
4 D+ l: r/ w2 h/ SLogarithmic transformation, 对数变换
! w7 }/ y( A9 Y* H5 k2 j/ ZLogic check, 逻辑检查0 W, z- Y8 U: @* W
Logistic distribution, 逻辑斯特分布 F0 C2 o4 w) l) ~
Logit transformation, Logit转换1 |: i5 q- e& r9 D" x, I g6 D6 d
LOGLINEAR, 多维列联表通用模型
$ S, h* F+ P: n% yLognormal distribution, 对数正态分布7 t8 S- j1 p* f3 ]* ^3 T g8 U
Lost function, 损失函数
$ O; l( S* p+ M# b* ZLow correlation, 低度相关2 q# r$ @9 n% O6 ]$ p
Lower limit, 下限2 J7 T' H$ j' @" s! V; u; f
Lowest-attained variance, 最小可达方差
) W2 U$ h/ u- y6 a' o, i& fLSD, 最小显著差法的简称
! B1 O7 j( F" ^' KLurking variable, 潜在变量
% Z' v, k8 V5 FMain effect, 主效应% Y( m9 p; b* M) x. ]
Major heading, 主辞标目/ y) A7 r' Q4 p3 f
Marginal density function, 边缘密度函数( z& g" D% _" ?. V0 _
Marginal probability, 边缘概率, Z- x- F# @- j/ _# m$ a4 w- [; ~
Marginal probability distribution, 边缘概率分布' H& j, Z# r2 `& N W4 L" n
Matched data, 配对资料/ C/ Q$ b8 ^2 Q. y2 P
Matched distribution, 匹配过分布, f0 | L d; w3 v! R4 A
Matching of distribution, 分布的匹配
- X' p/ C4 g/ ]7 V- a" Y, k) uMatching of transformation, 变换的匹配
9 E4 K9 G- n$ g6 r7 u# i: e9 ^. mMathematical expectation, 数学期望
6 `; V) ~( N& L1 U1 G/ v4 fMathematical model, 数学模型
( v3 |/ R$ {6 s( Q! _# rMaximum L-estimator, 极大极小L 估计量
* m8 N% I$ Z* Z) o2 l+ p( j: ~: X! w( fMaximum likelihood method, 最大似然法
$ Q# L9 W; U5 WMean, 均数6 U. ?: x0 f1 o3 u
Mean squares between groups, 组间均方 i1 M+ Z7 A2 u e5 e, R
Mean squares within group, 组内均方. G9 g) z% F; y* ? F! I
Means (Compare means), 均值-均值比较
8 k/ s! X i$ V3 l0 A: _7 kMedian, 中位数. N& i( `1 x- J3 a5 Q2 E4 M
Median effective dose, 半数效量6 V; B0 F6 E2 y1 |- h
Median lethal dose, 半数致死量
4 z. u# {( D1 Q7 V% n" T6 qMedian polish, 中位数平滑
( r2 y& f+ o6 V" I1 ^Median test, 中位数检验
7 j( E& w4 z8 EMinimal sufficient statistic, 最小充分统计量
& I# b0 M0 d' C6 JMinimum distance estimation, 最小距离估计& l' }6 N. v5 o7 A
Minimum effective dose, 最小有效量- i8 n- t; ]- d& n
Minimum lethal dose, 最小致死量
. e6 X6 E' R. u9 {4 i2 tMinimum variance estimator, 最小方差估计量1 i3 X, m- ?) j1 i8 b
MINITAB, 统计软件包
( k2 Z! R, g1 [, ~( p! |' T2 YMinor heading, 宾词标目
4 e! P. V0 e9 o' GMissing data, 缺失值
0 U: H, s( k2 E- _7 w/ wModel specification, 模型的确定4 b+ p0 s7 k. F. q
Modeling Statistics , 模型统计
) U( E; v, i2 S, lModels for outliers, 离群值模型$ I5 V; h3 E1 R* H
Modifying the model, 模型的修正
: S; H+ q6 M% ?4 b0 AModulus of continuity, 连续性模
( F7 e- J# }3 M' ^% P! nMorbidity, 发病率 ' }; t& g# j/ [: C0 t1 e
Most favorable configuration, 最有利构形
. h# v8 e$ b1 X- A) J* r$ jMultidimensional Scaling (ASCAL), 多维尺度/多维标度
# V y, N6 }! W- F. S' @Multinomial Logistic Regression , 多项逻辑斯蒂回归
+ f: v9 y& ^: I+ J4 Z9 U% T) m* \Multiple comparison, 多重比较6 m Z; \4 c) u7 _ @
Multiple correlation , 复相关
8 O- t: N8 G( WMultiple covariance, 多元协方差) e% J/ y1 B/ j) I* H( @ K$ |
Multiple linear regression, 多元线性回归
1 p, v8 a- d9 p, o8 V; LMultiple response , 多重选项
" L$ y! u- d. b/ AMultiple solutions, 多解
2 |# a5 ?# p" c1 Q- ?Multiplication theorem, 乘法定理& Y. d! K+ e, F4 r' Y
Multiresponse, 多元响应4 O( A( k5 p* J5 j3 G' N; O
Multi-stage sampling, 多阶段抽样7 X# |6 ~7 r' O I! O; J! o' X6 C
Multivariate T distribution, 多元T分布8 i, ]' Z5 X% Y
Mutual exclusive, 互不相容
4 T& r: q J. d; w6 J2 z3 kMutual independence, 互相独立
& f9 B8 Y8 J% M( w3 e* D3 p6 @Natural boundary, 自然边界3 n! e& [) q, U. B& w8 X% w z% J
Natural dead, 自然死亡2 G$ c8 b! e+ {" [! O! U5 n
Natural zero, 自然零
% |% j8 D. g0 \ ^5 X0 JNegative correlation, 负相关6 w5 c r7 e; e0 B
Negative linear correlation, 负线性相关2 J+ z& m4 M! ]! T1 {% |
Negatively skewed, 负偏
/ i5 I# _: h& k7 aNewman-Keuls method, q检验
- {4 K' [! U! @, ~: K- x( c* V6 KNK method, q检验3 O% g5 I3 [$ ]1 A1 g
No statistical significance, 无统计意义
- R4 e' X# D( f4 `$ b! RNominal variable, 名义变量. T$ ]- R, p5 o, f
Nonconstancy of variability, 变异的非定常性4 d0 ^1 i6 z/ d- |( q$ J' u
Nonlinear regression, 非线性相关
/ i* m- f- r4 Z" ?( V; u5 e: wNonparametric statistics, 非参数统计
2 y( R5 c% R6 s( f ]% GNonparametric test, 非参数检验
! S1 ?+ `3 [1 QNonparametric tests, 非参数检验) q n' {* s( k7 T; ~
Normal deviate, 正态离差
* h! U2 _, B0 R; a9 D, PNormal distribution, 正态分布
* O* s5 F% G8 {! m& ~Normal equation, 正规方程组& L+ L0 T. T9 B$ l
Normal ranges, 正常范围$ v: {$ m' [$ e
Normal value, 正常值
2 m+ W7 [+ Y7 n4 oNuisance parameter, 多余参数/讨厌参数- Z6 F' i4 `- R, n! b2 g
Null hypothesis, 无效假设 + G- B, } _. [. D9 t, V
Numerical variable, 数值变量
1 E1 e6 ~0 `& S: e: S0 ? e1 LObjective function, 目标函数; _$ `* I8 g+ c" s1 c
Observation unit, 观察单位7 [* G- n! j# d5 ], d' ^) y. k
Observed value, 观察值
. K7 k* u5 R( u) X1 V) M8 JOne sided test, 单侧检验( K/ v8 N9 E2 X& g1 g
One-way analysis of variance, 单因素方差分析7 Y- m% @$ g) ?" J$ I! ]
Oneway ANOVA , 单因素方差分析% T a& ^* t0 M& G4 K5 g
Open sequential trial, 开放型序贯设计9 M, u; J ?! S
Optrim, 优切尾$ Z, t# ^9 Y9 y- T2 u/ ?/ O" p
Optrim efficiency, 优切尾效率
2 ]# z) I$ ^% v) d' A! TOrder statistics, 顺序统计量
( u+ z7 N* R; v8 q9 DOrdered categories, 有序分类& C1 X( B' ^8 [9 W# P
Ordinal logistic regression , 序数逻辑斯蒂回归
' v5 M) j. T/ j+ ?: a$ _, ~Ordinal variable, 有序变量
! [; h4 G. @! G) dOrthogonal basis, 正交基
$ J9 v* A' H+ R; p! m8 _' uOrthogonal design, 正交试验设计( N. a' S t1 K( Z5 B, i( x' R8 [
Orthogonality conditions, 正交条件 J. u; \5 u% y! g9 ^5 g7 `6 H
ORTHOPLAN, 正交设计 3 X* T& e5 ]# g! W& q' \( J+ c
Outlier cutoffs, 离群值截断点
6 h" |4 _( S' x1 qOutliers, 极端值
+ j" G: A) P6 F9 sOVERALS , 多组变量的非线性正规相关
0 }! X5 s4 l1 N' ~Overshoot, 迭代过度* q( e6 J8 i" N9 n
Paired design, 配对设计
9 l& h; [% j( [( Q2 p% K, x3 s" ZPaired sample, 配对样本
1 ^8 v% N! z2 J xPairwise slopes, 成对斜率& [8 x5 @9 k9 ^
Parabola, 抛物线
) r! G: h1 {/ m' m# m8 PParallel tests, 平行试验
: F7 g: W b5 ~Parameter, 参数8 J \1 X" R9 B& N7 i; P, [
Parametric statistics, 参数统计/ w8 x/ M; R) I# k
Parametric test, 参数检验* U3 c* j0 F+ C
Partial correlation, 偏相关
8 l# f) k9 d$ i$ ]/ Y+ S' JPartial regression, 偏回归. p+ L" m/ P' y: m2 X" r1 ~0 P
Partial sorting, 偏排序
( o" f: x } l, q3 tPartials residuals, 偏残差
8 D0 T5 c, N i0 X8 wPattern, 模式7 f6 q% b9 E# {# H6 a4 a
Pearson curves, 皮尔逊曲线/ Z) Q. M" l5 i$ g
Peeling, 退层
: z8 C# L1 g5 R- R- D) _" Q5 oPercent bar graph, 百分条形图( `* G) B& t0 g, x$ F& Z2 d
Percentage, 百分比
' y' w: D# O* E- g' aPercentile, 百分位数- C5 n; O7 |8 L! Z% W2 X# d* i& d
Percentile curves, 百分位曲线
: Y3 e7 l% P5 ^Periodicity, 周期性
7 o0 p5 ]- z: e. x# a2 b5 ^' IPermutation, 排列7 D$ n* @# {+ _
P-estimator, P估计量% [( W- a" `; f( ]0 Q$ l
Pie graph, 饼图: a8 ^# J6 u0 D
Pitman estimator, 皮特曼估计量
9 n5 y6 h) `4 i2 {Pivot, 枢轴量
* s( O3 c2 z* UPlanar, 平坦
# l+ g: c0 j$ w1 S: BPlanar assumption, 平面的假设! f8 E5 r# c# P7 h9 @* y7 s
PLANCARDS, 生成试验的计划卡
! O) ]- f* W ]2 \/ SPoint estimation, 点估计
( ^' K, F2 z% y5 zPoisson distribution, 泊松分布
( C8 I, `7 y" j4 J! u- hPolishing, 平滑- ?: M7 x q- _0 c4 ?9 t
Polled standard deviation, 合并标准差
5 F3 V' s$ q) O+ H3 TPolled variance, 合并方差6 \2 y6 M5 T2 I
Polygon, 多边图
3 z* N" n) d7 iPolynomial, 多项式
1 V( L2 g. @' t6 K4 N! `Polynomial curve, 多项式曲线
) L f4 M7 x R( X/ T) q( iPopulation, 总体8 B/ {2 b- H! [8 [! [9 F
Population attributable risk, 人群归因危险度' \7 M+ V+ }# v( L/ R$ L6 d( w/ L
Positive correlation, 正相关
0 u5 M# Z, R' YPositively skewed, 正偏9 d0 @- V3 s6 ^! Q) O& o
Posterior distribution, 后验分布; \ ?8 Y+ o1 {5 ?8 W" `
Power of a test, 检验效能6 ~4 E# n& h. A; u2 ]4 M" H
Precision, 精密度: d# ^8 p' R) n) _
Predicted value, 预测值8 @- R7 v# e, P. P4 z* a
Preliminary analysis, 预备性分析
2 ~# {. C# I) b! sPrincipal component analysis, 主成分分析) ]. _0 }& d* [0 G; A
Prior distribution, 先验分布
- E7 L/ `9 A" N N& cPrior probability, 先验概率! x5 d5 D( g1 Y2 ^
Probabilistic model, 概率模型
Q/ M- Z; q/ ]2 a3 xprobability, 概率
. y& ?+ Y) X5 V9 U$ Y- dProbability density, 概率密度4 X1 v( g! c$ ?: ^2 c+ q- t
Product moment, 乘积矩/协方差
1 H- T4 `# V9 k5 I+ a# ^Profile trace, 截面迹图: w9 A( ^, f* L# F u6 s! V/ y, q" ^, p
Proportion, 比/构成比5 L% Q/ _ E9 S$ \
Proportion allocation in stratified random sampling, 按比例分层随机抽样5 e/ |0 R5 v4 W5 b. m6 q# \
Proportionate, 成比例% P7 d. Q, G/ ?* `8 w5 t
Proportionate sub-class numbers, 成比例次级组含量7 {! `( F/ K B! R; A9 ^
Prospective study, 前瞻性调查
; _$ l; n. K- QProximities, 亲近性 3 c4 P9 c' Y, O! l6 x7 b
Pseudo F test, 近似F检验
9 m3 v# o6 G6 l- @, nPseudo model, 近似模型, ~6 c: M7 X# k/ I; d+ y
Pseudosigma, 伪标准差
& r, x- S( @4 w+ l4 S: |4 ~4 `Purposive sampling, 有目的抽样: _! F" N4 I4 Z5 l/ ^% J
QR decomposition, QR分解 Z1 M. O5 g- _4 r, E6 `+ n
Quadratic approximation, 二次近似/ W! f o" i: a5 L& X- V( T
Qualitative classification, 属性分类
" n# e% H' ]9 o7 ]; M7 p* J nQualitative method, 定性方法+ B0 G* M. r5 F. f6 s
Quantile-quantile plot, 分位数-分位数图/Q-Q图
9 y# P6 ]6 l. c/ r. H6 sQuantitative analysis, 定量分析/ Z! h: L, h; z$ t" k5 B
Quartile, 四分位数; m' i2 Y' J" ?
Quick Cluster, 快速聚类* j5 R+ f$ y% ?. b8 o9 ^
Radix sort, 基数排序
" m a/ S0 E, @ oRandom allocation, 随机化分组
2 T% F0 |1 D9 \! gRandom blocks design, 随机区组设计
& Q7 N* C4 a: GRandom event, 随机事件
( {/ y9 |$ W) c2 l5 fRandomization, 随机化
# [* Z) C3 J. r3 K2 Z. JRange, 极差/全距8 x3 Z1 q# P" N
Rank correlation, 等级相关. W, G* l/ V; ]" |2 I- C
Rank sum test, 秩和检验1 k* S& ~- x$ k3 q
Rank test, 秩检验" J9 x1 \" p4 q6 q2 F) W, P% h* K" c
Ranked data, 等级资料
0 E# F" U6 I* y2 w) ZRate, 比率3 |4 a0 `( U8 }3 u+ r- U
Ratio, 比例
8 @, x6 {- u' |: FRaw data, 原始资料8 H i3 A! @3 R
Raw residual, 原始残差2 x' m2 P/ ^" C2 L4 M. R5 M
Rayleigh's test, 雷氏检验
n2 ]# o* n1 y5 uRayleigh's Z, 雷氏Z值 ! k9 |, e3 r( }1 k" b5 R
Reciprocal, 倒数
6 M) X, A, d+ Q8 d5 s8 yReciprocal transformation, 倒数变换2 l( ?' @9 k- U/ |3 u1 C
Recording, 记录
5 J4 P0 o' _9 ^; tRedescending estimators, 回降估计量
]! E) ]# ~* O2 Y0 i& n. ZReducing dimensions, 降维2 n, L# i5 C- A
Re-expression, 重新表达, m. G) h3 g6 i1 D m3 a. s' k
Reference set, 标准组# S; Y# y' n. `$ i, Q" v
Region of acceptance, 接受域
' O6 s, D" e! m H- r( ~0 B6 x4 u! KRegression coefficient, 回归系数
# s8 M3 u0 o3 O9 k3 v# a8 gRegression sum of square, 回归平方和
# v. [0 Q/ W' j) S K$ DRejection point, 拒绝点
/ @" g- T9 ~& c: ORelative dispersion, 相对离散度
5 v3 B- G. j( |- @- fRelative number, 相对数
9 r2 [" k2 x& ~6 t; ]/ E+ B. \( VReliability, 可靠性0 M4 [( Y0 l! I, D
Reparametrization, 重新设置参数8 m6 e( g! ^1 g( ~' o. [
Replication, 重复7 I, C$ c* v2 z
Report Summaries, 报告摘要. {" ~1 F: _5 t$ e
Residual sum of square, 剩余平方和
5 a( x& o. Q! s! _8 f- Z/ ]Resistance, 耐抗性. _. o5 @6 E1 `
Resistant line, 耐抗线
$ y) q7 b0 f. H! V3 JResistant technique, 耐抗技术' o9 b; K( Z% t/ W' a
R-estimator of location, 位置R估计量* R. N& i* a1 ~7 Y8 u
R-estimator of scale, 尺度R估计量 v W3 S9 U) t: }
Retrospective study, 回顾性调查
( }7 S- [ }0 `6 Y ?Ridge trace, 岭迹
' e2 Z ?" y2 ORidit analysis, Ridit分析5 G6 ^" O G: v6 u8 w5 f" w" V
Rotation, 旋转& I2 x) ]/ G* k: P7 c( t) m
Rounding, 舍入, C2 K" l3 U0 R& G1 ~9 w7 v' E
Row, 行
; \+ k& p$ _0 o% m0 fRow effects, 行效应
% l( C* Y0 i; B L/ jRow factor, 行因素
+ ^) i f8 ^, sRXC table, RXC表/ h' R+ L$ ?& o0 m- `& |
Sample, 样本: d* j+ `4 N- s& [' W
Sample regression coefficient, 样本回归系数
) _. S0 G+ |" O6 ?. b [Sample size, 样本量# D3 `* m5 R" I1 o& a
Sample standard deviation, 样本标准差+ ` D2 F0 i: M6 k% a3 K. g
Sampling error, 抽样误差
; m/ h J3 o( t7 cSAS(Statistical analysis system ), SAS统计软件包1 i- U+ `" M. ~ ]0 Z+ a
Scale, 尺度/量表# K% }4 M4 O7 }+ b- ^/ s8 t1 D6 n
Scatter diagram, 散点图
8 s* Q( T' r- [, KSchematic plot, 示意图/简图5 `; _ `" U6 Y( {" ]
Score test, 计分检验$ O# W, ~2 t" |1 k
Screening, 筛检
. O% U( g2 K' O# Z, [5 zSEASON, 季节分析
' e% n) r6 c- b. X8 fSecond derivative, 二阶导数
( B4 Q3 [6 ?( U, ?+ m) GSecond principal component, 第二主成分
- e% B7 Y2 ?- U5 n6 A* uSEM (Structural equation modeling), 结构化方程模型 5 a1 H- s' h8 C9 @
Semi-logarithmic graph, 半对数图
2 M: J$ A: y8 u6 b xSemi-logarithmic paper, 半对数格纸
! X M) S3 w1 T/ Q. P! F2 mSensitivity curve, 敏感度曲线
9 X* j4 |5 s. s4 w0 I" R2 LSequential analysis, 贯序分析
) A* Q4 x5 v. u! j" g9 [0 v3 JSequential data set, 顺序数据集
( x |* H, o6 R6 C, ESequential design, 贯序设计
# h n( t5 V. ]$ s3 {+ e- kSequential method, 贯序法
/ x8 W" ^( T4 ?# T& {+ gSequential test, 贯序检验法- a9 k+ E* \% p6 {
Serial tests, 系列试验8 g) g" K6 s1 e6 G
Short-cut method, 简捷法
; i5 f& i. {% L9 ESigmoid curve, S形曲线
v$ E9 w- J7 f, B& @Sign function, 正负号函数
, v! w3 V. Z) ?) p6 u; GSign test, 符号检验
" I* S* l+ |# hSigned rank, 符号秩7 m% I: a+ j P9 T- }/ L8 h% f- G
Significance test, 显著性检验
/ K, S F* c% r( i5 B0 E+ @, W# rSignificant figure, 有效数字" K; G$ X" W5 T* ^
Simple cluster sampling, 简单整群抽样! Q" b3 i. }1 W: u( F U
Simple correlation, 简单相关
8 R% y6 q# Q0 `! A2 Q! zSimple random sampling, 简单随机抽样
$ N& c8 `# N( }9 D2 e, VSimple regression, 简单回归4 W0 v" Q5 O" D1 D7 O
simple table, 简单表
: s2 ~' ]5 u5 R: V- A( ^8 e3 Z) [Sine estimator, 正弦估计量* ~& x+ C0 f( n4 y( c( I
Single-valued estimate, 单值估计
2 S" q1 [4 k. HSingular matrix, 奇异矩阵. e* M+ W7 a5 x4 I* [; G
Skewed distribution, 偏斜分布
7 s, Q% C. F( k4 e: Z( W: Q DSkewness, 偏度
m0 E8 t* V5 cSlash distribution, 斜线分布
4 ~# n- K9 p1 n5 A1 m/ N! ?/ JSlope, 斜率3 N1 G8 a# q9 T; l. V5 f% M5 k E4 n
Smirnov test, 斯米尔诺夫检验8 @( d3 {6 f! O
Source of variation, 变异来源2 C" e( A# t$ o1 i6 G1 l9 ]
Spearman rank correlation, 斯皮尔曼等级相关
( K- q9 D& K# S+ R% ]$ `6 qSpecific factor, 特殊因子6 j3 y( y6 R6 q1 ?
Specific factor variance, 特殊因子方差
; O$ a/ v: C5 [4 q1 YSpectra , 频谱
$ V& i+ f6 v. SSpherical distribution, 球型正态分布5 c* {: Q. a2 X2 \
Spread, 展布
& X* B/ P1 B: I2 T$ U# XSPSS(Statistical package for the social science), SPSS统计软件包
+ ], e* h E/ B* o$ L& L6 V9 B- ]" fSpurious correlation, 假性相关
4 s* O( W9 v# z* Q3 W. ]4 ]% J8 GSquare root transformation, 平方根变换! b% E! K" n. d6 o- E' [/ l
Stabilizing variance, 稳定方差. M5 @6 ?1 K$ H7 _
Standard deviation, 标准差( e$ n+ B6 u+ N( P* o# N9 d8 R
Standard error, 标准误
* P# z' X' V, RStandard error of difference, 差别的标准误& F& d6 d2 }$ G2 {" J2 {
Standard error of estimate, 标准估计误差8 `1 H, X y% n
Standard error of rate, 率的标准误) Y8 v7 m v( Y# m8 J! a. D6 S4 S
Standard normal distribution, 标准正态分布
* g$ f* a" X% G6 N& w' NStandardization, 标准化
% J, d! Y; ?# x8 m, zStarting value, 起始值, H7 f5 j0 J. R
Statistic, 统计量- V& V) {: R' I8 `+ H5 H
Statistical control, 统计控制8 f* f5 H& h6 X! P# _6 R; m0 R. _
Statistical graph, 统计图
4 S: A5 ?* G* lStatistical inference, 统计推断
9 m% G- T( ^! c' `: Q# eStatistical table, 统计表+ e5 Q+ I {9 @' s" g( P# Z
Steepest descent, 最速下降法
( ~6 ^- a- Y" `0 A+ H& b. {Stem and leaf display, 茎叶图$ g4 E& K7 [$ N
Step factor, 步长因子$ b2 v# [: s3 w& u
Stepwise regression, 逐步回归
% `% w" J( v) gStorage, 存
- d$ Y, d0 r4 }$ hStrata, 层(复数)
2 X5 L% g0 B6 fStratified sampling, 分层抽样
5 ]) i k% j" q$ g" u. ^Stratified sampling, 分层抽样) g) X b1 g' c: n- _
Strength, 强度
, T# C4 [+ q6 y* G$ CStringency, 严密性* g* [7 [, w q
Structural relationship, 结构关系
. ]# i- a5 D6 D" x2 aStudentized residual, 学生化残差/t化残差
/ d& z0 Q9 O8 a; X! c' N+ i" BSub-class numbers, 次级组含量5 y+ X. Q& x( m4 d( F$ O6 E# b2 d
Subdividing, 分割
1 }9 u1 G2 Y4 M% L: T8 Y3 j4 GSufficient statistic, 充分统计量$ }4 P9 @* L. i) _
Sum of products, 积和
n/ s) e2 ?9 Q, \6 rSum of squares, 离差平方和
: q2 X3 P3 j- K% |. ]Sum of squares about regression, 回归平方和6 T- q6 t* y3 r. C& z4 n5 P* a
Sum of squares between groups, 组间平方和& y+ i0 }' w' q; W" a) n, m, d% q* D
Sum of squares of partial regression, 偏回归平方和
6 V5 d1 ?9 B0 m- x( q. w' nSure event, 必然事件2 n$ \ `+ L9 d/ z
Survey, 调查
5 |3 w0 ?6 J+ ^( U) TSurvival, 生存分析
+ w4 t! A3 G5 p8 U/ fSurvival rate, 生存率. Y2 I( g2 v* _) w) }" f- ~5 P
Suspended root gram, 悬吊根图( m1 h1 i& B$ c! q- z: l
Symmetry, 对称
4 w" X9 v# ?3 B# y. _7 l* _4 CSystematic error, 系统误差& {4 n( t9 f4 F
Systematic sampling, 系统抽样* d. W2 }: _; N: w5 v- |
Tags, 标签. b4 a* g# v4 I, i. f1 o* k
Tail area, 尾部面积2 [4 H9 s2 p4 P9 t: x3 p
Tail length, 尾长 Q% s2 \) w; o3 `/ s$ k" d
Tail weight, 尾重0 \2 _4 e* j8 }- A
Tangent line, 切线
" [, t( c5 e) J# o- v% c) tTarget distribution, 目标分布* h- n. M( _. h% y, }4 Y
Taylor series, 泰勒级数
# J. T$ t+ J! R% A9 m5 xTendency of dispersion, 离散趋势
- D0 b7 j, Q: h$ L1 gTesting of hypotheses, 假设检验8 \# k7 N$ w( n/ o4 S: C" e
Theoretical frequency, 理论频数$ z1 {! A2 u" W5 _5 z, G0 {
Time series, 时间序列
y. @' o/ I7 w. w. X7 U; M5 BTolerance interval, 容忍区间" v K9 V# F) m0 q& Q$ x
Tolerance lower limit, 容忍下限! J/ |4 n5 M2 ^$ V. w: Y
Tolerance upper limit, 容忍上限
2 R# G* R0 j" \ I$ uTorsion, 扰率0 d( I0 V- F8 T
Total sum of square, 总平方和: Y8 Y$ U7 a( x
Total variation, 总变异
5 R7 `1 [+ Q# G% K, R* x! XTransformation, 转换
( ~- @ y& k5 ]2 wTreatment, 处理 {8 T# f: f7 C7 z' Y
Trend, 趋势" t0 [9 d8 z/ t/ _( b
Trend of percentage, 百分比趋势3 I% u7 ~& ~' G5 j8 Z5 X: S
Trial, 试验, [3 p3 D$ `* E% |; T
Trial and error method, 试错法
9 r$ y/ F3 [! ^# W3 GTuning constant, 细调常数0 t" E2 I4 Y: j6 T' M* m
Two sided test, 双向检验
9 ]8 ^5 M4 m l1 ~- \Two-stage least squares, 二阶最小平方
4 r8 K) o1 ?" [" z. z( k6 pTwo-stage sampling, 二阶段抽样! Z5 H* |" v, q% L7 a
Two-tailed test, 双侧检验( T8 B b! p1 a' a$ Q3 A9 l
Two-way analysis of variance, 双因素方差分析$ k# ?- |: X3 D) R5 I
Two-way table, 双向表
1 @' x2 ]8 P% f/ z; ~8 tType I error, 一类错误/α错误3 q1 `! v# d/ S8 G7 O8 x5 `8 D
Type II error, 二类错误/β错误
: B1 Y Z0 M: K% U- K5 E% NUMVU, 方差一致最小无偏估计简称% X5 Y' c d! `# h: W
Unbiased estimate, 无偏估计
9 t/ b2 @# ~3 r$ Q1 w# |& nUnconstrained nonlinear regression , 无约束非线性回归
5 ^; L1 ^' `9 O6 }' p7 O- MUnequal subclass number, 不等次级组含量
. M: A/ G& \+ e8 m, w: TUngrouped data, 不分组资料) Z1 s! n* j* r' q& Q* O/ z6 S
Uniform coordinate, 均匀坐标" f/ g6 N/ q7 |- s! R9 ?) z2 P
Uniform distribution, 均匀分布3 z9 h5 i$ E* f- o: C) Q
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
9 E) G4 @/ f0 _+ z" w2 T u+ KUnit, 单元
1 q3 v- L: i& Q, U; q TUnordered categories, 无序分类' y' N7 d6 C, _ T Y+ H e' p
Upper limit, 上限
+ z4 }) X+ t. o: c$ OUpward rank, 升秩3 H1 }4 r# z" Z) g; t) @% g
Vague concept, 模糊概念
% b, b* S+ N: O) e" m3 XValidity, 有效性* g% D. c: R. C" k" D- _
VARCOMP (Variance component estimation), 方差元素估计. T, `6 {1 m9 v: N# z' P! u: f1 K' k7 r
Variability, 变异性
$ Y, a6 Y |) E, YVariable, 变量
! ~' n( d# G- Q! g ?( PVariance, 方差2 h' p; M9 T+ s( f) t+ k
Variation, 变异
! `# I ^& D$ [, Z: k+ y w1 ^5 CVarimax orthogonal rotation, 方差最大正交旋转" C4 H' Y. O- l) T7 |" _
Volume of distribution, 容积
% W9 @" Z) R8 O: O ^8 rW test, W检验
! I% l4 ]3 a- X; C5 ]0 K1 MWeibull distribution, 威布尔分布. D. c. k) }, y- x; y
Weight, 权数
* \/ C8 p+ M- mWeighted Chi-square test, 加权卡方检验/Cochran检验& H$ p( e7 k3 F4 v
Weighted linear regression method, 加权直线回归
1 M- F$ ]* V8 Y: b! `! PWeighted mean, 加权平均数
. N8 {! U8 v" `# Q6 {Weighted mean square, 加权平均方差4 f$ B6 m* j9 f6 S/ v: X* ^7 U) ]0 ]
Weighted sum of square, 加权平方和( |8 E1 I. J/ z2 x& Q+ y. u$ q9 [
Weighting coefficient, 权重系数, j5 Z. p5 c& i; b( @) E) T' Z
Weighting method, 加权法
9 {( u3 f+ G; f! ]. K1 C, PW-estimation, W估计量1 }" x4 g& T7 x. w- P: h
W-estimation of location, 位置W估计量 A; l! F6 b; `2 L. P3 D' \
Width, 宽度' T2 c0 x. w! l- u. F+ `
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验9 d3 K1 }9 Z; \7 r, D# F+ Y
Wild point, 野点/狂点
j% V& D# c' ?1 t5 @" m E* cWild value, 野值/狂值( S/ Z' j c/ h5 l( C) B
Winsorized mean, 缩尾均值
# l& z0 v- J1 J- u7 TWithdraw, 失访
- X/ Z4 v# ]$ z5 p0 y& J% X4 [6 u0 eYouden's index, 尤登指数
: @9 g. b9 N8 q5 H5 J! p. tZ test, Z检验/ i. U9 j' B# e+ i2 h1 h- z8 N. C
Zero correlation, 零相关
; V5 a( ]+ H: o8 A# n( [9 lZ-transformation, Z变换 |
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