|
|
Absolute deviation, 绝对离差2 b* f# \( ~, F" Z1 K
Absolute number, 绝对数
: z( U2 t3 X( X6 {0 {3 {$ N( U9 `8 QAbsolute residuals, 绝对残差
1 o$ {$ X8 H. V. Z% ~2 pAcceleration array, 加速度立体阵0 q, t: Q- A+ s% `
Acceleration in an arbitrary direction, 任意方向上的加速度
1 U. L+ v9 r6 G @3 I) dAcceleration normal, 法向加速度* V6 J$ L4 g% O( B5 n) q s8 M
Acceleration space dimension, 加速度空间的维数
; T6 w3 H6 R% a. }. X. Z4 mAcceleration tangential, 切向加速度
- [- A# k/ j, P8 @5 @! }Acceleration vector, 加速度向量
4 o3 h. y1 b% b3 E1 dAcceptable hypothesis, 可接受假设
9 D( g5 n, ]5 O8 bAccumulation, 累积
, z/ K/ n7 x2 F. y+ CAccuracy, 准确度
4 K% b$ m) L/ @/ eActual frequency, 实际频数8 y7 v: C/ x- u* O
Adaptive estimator, 自适应估计量+ c. E9 K3 k/ w! k. X
Addition, 相加. t a. ~' [7 b
Addition theorem, 加法定理. ^5 D, R0 I+ N4 ^/ L
Additivity, 可加性4 m0 A- r( I/ |# C
Adjusted rate, 调整率
' t! ~4 F( b) v! KAdjusted value, 校正值
d, { V7 y; |Admissible error, 容许误差' o1 }' Y6 N. r+ X1 ~) ]; H) {
Aggregation, 聚集性4 ?% H! ]- e- H8 n
Alternative hypothesis, 备择假设
! S2 B' n; H* X" d! p- l8 N& WAmong groups, 组间% Y `1 Q/ p( Y$ F: l6 X$ G6 E
Amounts, 总量
: C( H! H& N- ?- tAnalysis of correlation, 相关分析- D" D! ^8 D# {" B2 g% H0 {4 W) C
Analysis of covariance, 协方差分析
$ |: y1 a* E! R) ?9 eAnalysis of regression, 回归分析4 Z7 i8 {4 o, Q) }& d
Analysis of time series, 时间序列分析
" `; d1 c4 p9 O h' l: s! TAnalysis of variance, 方差分析
/ r4 G% N0 }( MAngular transformation, 角转换
6 P& r2 [1 d, z& {, OANOVA （analysis of variance）, 方差分析
+ A! Y; S' \- {9 \ANOVA Models, 方差分析模型
8 [+ {1 x0 I6 z1 c- u" g8 y& IArcing, 弧/弧旋) q! c' a" U* j/ B* _% C5 e. M7 W
Arcsine transformation, 反正弦变换
; E9 S9 U- ~, U- _ n: y; i! `' mArea under the curve, 曲线面积; i7 |: v/ I1 z! x
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 + p! j. e9 L( r# {6 N# r9 |, x- j
ARIMA, 季节和非季节性单变量模型的极大似然估计
( ]8 _; Z+ K2 [9 d l+ U$ ~% lArithmetic grid paper, 算术格纸% o& W; A! j0 ]/ b2 p" Z! _( E# U4 N+ M
Arithmetic mean, 算术平均数& v4 B( c m4 s7 w z8 F
Arrhenius relation, 艾恩尼斯关系2 @/ C6 k& S& A: A- _+ `. G
Assessing fit, 拟合的评估* @' G8 q- a3 f: H' G) [0 J! d
Associative laws, 结合律
. B% {) T3 A7 b4 T! AAsymmetric distribution, 非对称分布5 v+ p8 a: u+ O6 K9 i V
Asymptotic bias, 渐近偏倚
- e" w- h) u ^+ n/ o* aAsymptotic efficiency, 渐近效率
6 z" z8 S' x/ {6 d8 @Asymptotic variance, 渐近方差
& A# \5 x& ]3 I7 S8 m ~3 o2 cAttributable risk, 归因危险度! G( B$ I3 t8 Q9 I" q8 I
Attribute data, 属性资料
! M% d' P. Y4 y& n! C5 u% {- k6 G. CAttribution, 属性
* O- v3 R" ?. s- }Autocorrelation, 自相关
, X& U4 J7 W) e& F1 L2 u1 pAutocorrelation of residuals, 残差的自相关/ L7 C; [. Z1 j' {5 X; c2 Z
Average, 平均数" @4 e, c2 h8 n6 X! Z6 V4 \/ r g& [
Average confidence interval length, 平均置信区间长度
M" P* M1 J: |5 e. F% N1 NAverage growth rate, 平均增长率8 Q) I+ J$ t$ Y$ k$ A$ @" e' B
Bar chart, 条形图* G9 Y; O4 U" p1 u U/ {! P
Bar graph, 条形图
. F- m$ L2 E# I. _( G8 @" X# B( UBase period, 基期
6 J% X* `) L' o% V2 QBayes' theorem , Bayes定理6 Q. T$ f; f9 T/ }! L
Bell-shaped curve, 钟形曲线' Z5 E6 e. K3 m0 `7 \
Bernoulli distribution, 伯努力分布6 _* ~ E$ P+ P& d+ H
Best-trim estimator, 最好切尾估计量/ f( d% \' Y% X8 y' V
Bias, 偏性! S9 D7 x0 b% O- M j" ]6 o
Binary logistic regression, 二元逻辑斯蒂回归& F$ [9 l( Z( l8 L$ b
Binomial distribution, 二项分布
" p4 p6 Z! O$ O* Q3 J8 s3 [. h/ mBisquare, 双平方
) C; a3 Q% L$ [: Q# f7 {1 vBivariate Correlate, 二变量相关
_) G" F: l( e3 iBivariate normal distribution, 双变量正态分布; d& D! k- Y9 B0 D: U z H2 n' g& n
Bivariate normal population, 双变量正态总体
. q* j. |1 m9 h; z, _; W9 @" r/ dBiweight interval, 双权区间3 R4 b2 Z3 e3 P1 |* E) w8 S4 Y
Biweight M-estimator, 双权M估计量
+ V! a% }& q N4 F) SBlock, 区组/配伍组$ g$ @; i/ ?- _- R
BMDP(Biomedical computer programs), BMDP统计软件包2 [7 c( i9 i5 P, |
Boxplots, 箱线图/箱尾图
0 N% o) C6 u+ p8 b( y. SBreakdown bound, 崩溃界/崩溃点: t1 H" d% l" A8 h# {& M i7 _0 ~% C
Canonical correlation, 典型相关* q' V5 ^! H8 T$ v$ j
Caption, 纵标目
1 y) `) @( {" l1 DCase-control study, 病例对照研究
) I1 V5 x7 K+ K+ t/ pCategorical variable, 分类变量
" e! A: W( N6 ~9 `Catenary, 悬链线
8 y1 q" I r- A3 N3 g3 `8 ACauchy distribution, 柯西分布, L2 B8 @+ r/ S; p" h8 t
Cause-and-effect relationship, 因果关系
& J% ^2 M% w- I* s# pCell, 单元
+ A* C4 x5 p* g( \6 S& fCensoring, 终检9 f' g. |% z8 @, b) C" t* q* H
Center of symmetry, 对称中心
( O- h" k2 ?! j/ p! ?' ^3 ^8 _Centering and scaling, 中心化和定标$ b+ j2 K# z% \' n, B+ v
Central tendency, 集中趋势% t3 @2 }; _- h0 m! h! u
Central value, 中心值
6 L' g: I+ E$ jCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
1 Z3 W: u( U1 b' ~Chance, 机遇
. d- N; E# X$ A) ~8 L! p; w8 @Chance error, 随机误差
: p# }% i. l2 R9 I. E7 w1 bChance variable, 随机变量
% N7 k+ x0 g) ?0 j5 s. z$ tCharacteristic equation, 特征方程7 ?6 p1 b0 v2 T* h F! k
Characteristic root, 特征根4 \ y0 _5 ^/ [
Characteristic vector, 特征向量) e) |$ b) K/ N) O8 ]1 A ~) c
Chebshev criterion of fit, 拟合的切比雪夫准则( N! {/ B2 a: r. R! u
Chernoff faces, 切尔诺夫脸谱图
) G5 E+ f# q* u' R) C* ^Chi-square test, 卡方检验/χ2检验
1 n3 u9 @7 f" {Choleskey decomposition, 乔洛斯基分解( @6 |& V9 K( G/ q5 X8 D& x
Circle chart, 圆图 5 Y# g8 w* k8 o% |% B7 c# |
Class interval, 组距
8 R2 ~, B& {( V$ e4 d9 _2 h+ w) S$ D2 IClass mid-value, 组中值
8 J! u: ]' ~# D1 E5 b5 tClass upper limit, 组上限
& |+ y r( _. H+ O& yClassified variable, 分类变量
1 B! B. D6 D. @+ i7 ~Cluster analysis, 聚类分析& J n7 ?! C; J: v& H' w
Cluster sampling, 整群抽样' G) l2 _( G, ~) o2 y8 C7 w1 G; k
Code, 代码2 _2 _( D, g1 B0 |0 ?1 v1 j
Coded data, 编码数据
' `, g" p$ k, M5 @& M8 MCoding, 编码' y) s, Z0 A6 L6 n
Coefficient of contingency, 列联系数* g/ n) T. S6 M8 P# |$ }
Coefficient of determination, 决定系数
+ b0 k0 a% L, s" t8 t, J3 `: q% yCoefficient of multiple correlation, 多重相关系数& `5 R. H; n' \5 G# A, p
Coefficient of partial correlation, 偏相关系数- D: o, e$ A$ i6 ^' A/ H
Coefficient of production-moment correlation, 积差相关系数
, F: q) m. C, b: Y2 l! ACoefficient of rank correlation, 等级相关系数
9 g c$ g4 W/ j1 R# `3 L& ?; }Coefficient of regression, 回归系数
- ^ H$ M- }( m# j: S/ i- {, a; U( J6 mCoefficient of skewness, 偏度系数; T. R8 H5 a( z. Z
Coefficient of variation, 变异系数
3 }2 V& s' ]5 s7 T, T$ P" ]6 q$ ]Cohort study, 队列研究
m2 h- s1 m# S8 G' zColumn, 列1 L/ V! j8 J: k* e+ H
Column effect, 列效应1 j0 r- P' Y7 F4 w' U. [& _
Column factor, 列因素& `9 I0 i S, h W
Combination pool, 合并
, H d& R* b+ H# x1 QCombinative table, 组合表
; g7 `+ T7 Q; q4 {; ^3 z+ O7 P* GCommon factor, 共性因子, x2 e: X6 I* r8 t
Common regression coefficient, 公共回归系数
t0 k0 a5 Q( [; I* N; R2 {Common value, 共同值
3 p) h+ y0 v$ q( |Common variance, 公共方差& r4 w" `5 \1 W( H. a
Common variation, 公共变异0 T; o6 O3 J6 `$ Y* w: K1 T. }4 e
Communality variance, 共性方差
" [' O: C; x! i+ E2 sComparability, 可比性
9 T" t$ R5 G U" @- U7 K7 PComparison of bathes, 批比较# Q' E) E% h/ f ]
Comparison value, 比较值" P5 P2 K1 b3 y5 [, }0 ^
Compartment model, 分部模型
( q; ?: R& O, W4 Q8 f+ X+ ~: [6 tCompassion, 伸缩+ m" _1 o5 H# S6 Y
Complement of an event, 补事件2 ^0 P. b4 p) u8 n
Complete association, 完全正相关
& {1 N! P8 r7 B1 y8 r- p; J: C9 qComplete dissociation, 完全不相关$ h7 h# c# S% G w8 r
Complete statistics, 完备统计量
! d @9 r% P: N! @Completely randomized design, 完全随机化设计# O. @4 B6 k, M# k9 d
Composite event, 联合事件
0 v9 Z$ p( ^2 MComposite events, 复合事件
' L" o1 S- i/ sConcavity, 凹性
. y2 g9 ]7 d: ?$ Z9 n3 V/ DConditional expectation, 条件期望
# O/ u8 R3 |6 b/ S+ z. u2 \Conditional likelihood, 条件似然2 A- R8 q) w1 p J3 q6 @
Conditional probability, 条件概率4 y- ~# Y w' o; s4 W% X0 b& l0 A
Conditionally linear, 依条件线性, W4 l) _% t( R7 T: ^& n Q
Confidence interval, 置信区间
) k5 t9 M; ^' M3 z. \; k4 t) I) w& jConfidence limit, 置信限5 `/ X( n& p# P4 {3 ?
Confidence lower limit, 置信下限
3 ~: @/ E9 ~3 nConfidence upper limit, 置信上限5 _8 M( J8 p/ f$ r" M: g# R; ]% }
Confirmatory Factor Analysis , 验证性因子分析
% i+ Y+ ^- W% f4 V, `. |( m6 |Confirmatory research, 证实性实验研究) }9 {& x1 B! i" e% l
Confounding factor, 混杂因素
6 ~' G& U7 {: KConjoint, 联合分析
: T3 a" A0 ~+ d% J+ |# M6 wConsistency, 相合性+ O8 t( A% z9 j
Consistency check, 一致性检验 S9 f6 |6 D: \, o7 c
Consistent asymptotically normal estimate, 相合渐近正态估计4 E7 l) w5 w1 \
Consistent estimate, 相合估计
`0 i& `( A" ?3 `% WConstrained nonlinear regression, 受约束非线性回归( X) y' v7 f/ T
Constraint, 约束0 P) U1 z( @* f" b
Contaminated distribution, 污染分布
% _1 J- Q- C. X& J& ~) d6 |, XContaminated Gausssian, 污染高斯分布
& w5 B8 U3 x! RContaminated normal distribution, 污染正态分布
) M8 D7 v4 e( _- k# PContamination, 污染' {! o' }" Q( E1 u# O
Contamination model, 污染模型
8 Q: b* y- ]. m q- OContingency table, 列联表
. O. T- @6 I4 V+ u0 f% l3 X" eContour, 边界线
& Q3 j- X+ j+ F6 t1 @# DContribution rate, 贡献率 y2 ?& l8 _' Q4 x3 C$ d
Control, 对照) [2 J( |2 y- @$ e- N* E4 V1 x( |" [
Controlled experiments, 对照实验9 k. q( _8 r1 v" q( O% K' Z
Conventional depth, 常规深度
7 |1 P% ~+ p1 P4 UConvolution, 卷积; t9 [" l D' C+ u$ ^; |
Corrected factor, 校正因子
1 @8 i. [3 \' ?1 vCorrected mean, 校正均值7 q) x1 W& c7 f' n0 |+ W0 B. T
Correction coefficient, 校正系数
) g( J9 h7 L0 V" T5 R, QCorrectness, 正确性
. C+ H g) `+ \( |# S6 B3 ZCorrelation coefficient, 相关系数
% ]! A2 }" b0 j3 B7 {$ ~& @Correlation index, 相关指数& ~$ @- Y( ?! Z! e5 y, Z, Y
Correspondence, 对应6 [1 _9 d# v0 n0 ?: [$ Z6 W$ w5 s
Counting, 计数+ d1 L& p: ]8 W$ J8 \
Counts, 计数/频数" v& _4 u8 c; r/ J# Z/ Z/ c
Covariance, 协方差6 ^4 f& ]* g3 ~ J4 a
Covariant, 共变 5 n5 Z/ C, J& E, ]5 S. L
Cox Regression, Cox回归% q( O4 F, K: _# `; H8 m
Criteria for fitting, 拟合准则
& v' Q# i& m$ XCriteria of least squares, 最小二乘准则
7 O4 J q: F' y6 A/ KCritical ratio, 临界比
; b2 N4 x: z4 q6 c8 J3 U! u+ XCritical region, 拒绝域; C/ A- |: v4 A5 [( S+ ~' ] I
Critical value, 临界值, u: d' X& X1 y
Cross-over design, 交叉设计# X( d# f" s6 q2 f$ E2 G
Cross-section analysis, 横断面分析
! E9 o: k. K/ H; @5 `4 r E* V, wCross-section survey, 横断面调查
1 O5 u) ~9 H4 N1 p7 O a4 w& _% mCrosstabs , 交叉表 2 N+ b' Z" ]" [7 Y; h
Cross-tabulation table, 复合表- c9 L0 `3 i8 A
Cube root, 立方根: h7 H' {) l8 g1 ~- p. Q
Cumulative distribution function, 分布函数
6 ?; t: \- C; vCumulative probability, 累计概率& s1 b: Y4 C$ _2 l3 i a
Curvature, 曲率/弯曲
. x" T% q! e( `- LCurvature, 曲率
& B9 D% E" t6 k8 R, U/ Q4 O7 vCurve fit , 曲线拟和
0 L9 t: |0 t4 P" g3 Z8 j! YCurve fitting, 曲线拟合9 Z: Q2 w! P- H: {* J7 K
Curvilinear regression, 曲线回归% F& d6 X- g7 {5 E9 g
Curvilinear relation, 曲线关系0 B2 M% R( ~; f3 R2 O$ B, Z. _" n
Cut-and-try method, 尝试法! e$ v7 H" a8 J! ~7 h7 z" A b
Cycle, 周期0 A& s2 M" F6 z8 X9 U& b# r" T
Cyclist, 周期性
% T8 S1 Y* ?- ~D test, D检验, j3 g: {( @* Q6 d7 A. G
Data acquisition, 资料收集
/ t% i0 p$ S" T) f) e' i. ]Data bank, 数据库 R+ ~: n8 n, H
Data capacity, 数据容量9 [# Y0 R$ X' L9 z- ]% b
Data deficiencies, 数据缺乏* _% S$ Y0 f# s4 b8 F' }8 }0 t$ k: t
Data handling, 数据处理
, J6 k5 N3 U$ a3 A- pData manipulation, 数据处理
) r) _6 v q( q4 S; [- `% eData processing, 数据处理- G3 }. L2 e- u/ L9 u
Data reduction, 数据缩减
* ?0 M8 E9 D. o G' e9 TData set, 数据集
/ _0 r! P- T8 W- K& bData sources, 数据来源
' O' a0 ~9 h4 N: |Data transformation, 数据变换
: P E( }2 ~7 g* x3 D6 gData validity, 数据有效性
( A; _3 ]7 Y( A! C) EData-in, 数据输入
( E. r" z; M# Y; CData-out, 数据输出
7 L/ v% ^( x* y2 P5 A5 X* {1 N/ }- vDead time, 停滞期
/ A, S; ?6 |) Y' ?Degree of freedom, 自由度: N% m ?1 U5 t: v* x/ m" e. U/ x
Degree of precision, 精密度% E( j$ Q' o! B! H3 f
Degree of reliability, 可靠性程度
* N' p% r _7 N1 ~6 R, D/ YDegression, 递减+ @* e" m. t7 d; d7 U3 U
Density function, 密度函数
* e" ~# H" |$ h6 p! D6 EDensity of data points, 数据点的密度
H$ ?9 l8 u% ODependent variable, 应变量/依变量/因变量; x/ [2 a' v M9 r
Dependent variable, 因变量
, `" Y: m- y$ G5 fDepth, 深度( c! I: v! q+ v! R$ C9 S
Derivative matrix, 导数矩阵
- P Y% O A* uDerivative-free methods, 无导数方法
; e j' ]1 R, hDesign, 设计
* S5 O# |( p6 d- i( |$ x' FDeterminacy, 确定性
# ^0 b4 D; T- r9 k1 yDeterminant, 行列式/ R. ?$ r4 P( x
Determinant, 决定因素" }) k2 h+ p. j
Deviation, 离差
% Y! z, S. C$ q7 l/ C5 nDeviation from average, 离均差# \; p+ A6 L* h9 v7 n) c8 e
Diagnostic plot, 诊断图- ?) }" P7 q0 q' x- ?6 Y4 {
Dichotomous variable, 二分变量
, M3 k- x% i& i! l8 mDifferential equation, 微分方程1 \3 A2 @/ h( V, ~6 V+ G# Y, g1 r( w( a
Direct standardization, 直接标准化法
4 @+ \" U/ X2 Q; H8 xDiscrete variable, 离散型变量$ j6 S& x2 V, l% R
DISCRIMINANT, 判断 9 o0 U0 L8 w$ P& Z% k; Y7 K
Discriminant analysis, 判别分析$ q5 D5 O2 m% X
Discriminant coefficient, 判别系数
8 E1 Y5 g% q! p& M. \! z5 EDiscriminant function, 判别值
: E' w! D$ [4 ^# R( M7 cDispersion, 散布/分散度, ~1 W4 W5 Z$ }) t' K' T: m
Disproportional, 不成比例的; P# D; I) B1 X% w& x( }" n/ h
Disproportionate sub-class numbers, 不成比例次级组含量/ [" Y Y4 l/ C
Distribution free, 分布无关性/免分布' b3 y& t' z$ f! _/ q# t- j
Distribution shape, 分布形状
& ~- H; Z0 K* A& y# QDistribution-free method, 任意分布法
`( Z& W- z0 Y5 `Distributive laws, 分配律
8 l0 g! Z' ~5 {. z7 o/ J" qDisturbance, 随机扰动项5 e+ F4 M) c. e" ]
Dose response curve, 剂量反应曲线5 D9 V/ C9 M5 A& u. F$ y
Double blind method, 双盲法( d! c' _3 d+ E: I* S
Double blind trial, 双盲试验" w+ Y! ]2 Q A# a: p
Double exponential distribution, 双指数分布
7 K& O6 A4 K+ T, W/ v+ L+ ?Double logarithmic, 双对数
, v& _' ]7 c3 bDownward rank, 降秩
; g) E& w% K' \9 x0 ]Dual-space plot, 对偶空间图5 a0 [+ F, u* f0 w
DUD, 无导数方法/ P) }7 h4 B2 Y' A. Q7 Y
Duncan's new multiple range method, 新复极差法/Duncan新法1 R& u) }' s4 i8 K4 }4 K8 T. A! V! l
Effect, 实验效应! E8 C- M \8 k( K
Eigenvalue, 特征值* \" Z5 c0 q( o" B, f
Eigenvector, 特征向量
( `8 e4 }8 G6 W( ?" `' h7 y# JEllipse, 椭圆, Y, o) l# P u* `5 M. t
Empirical distribution, 经验分布3 a6 e3 k [/ F% i, @, S
Empirical probability, 经验概率单位
1 v4 k5 d( [: z0 I$ ~Enumeration data, 计数资料4 Y0 v7 p; s8 z
Equal sun-class number, 相等次级组含量
9 R+ L1 \+ I# n0 Q" QEqually likely, 等可能
( V4 k8 j, S; V3 fEquivariance, 同变性5 p' U' J( C3 X" J: R3 O
Error, 误差/错误
, a- A+ ~& g- fError of estimate, 估计误差. i& G; I( W8 C
Error type I, 第一类错误
# G3 I6 d; |6 SError type II, 第二类错误
( t5 ~- ^! e. S. q @) D( ?Estimand, 被估量
/ B) q8 U6 }$ w% q5 y+ l9 V( yEstimated error mean squares, 估计误差均方1 ?# [, o% T9 d" f" Y
Estimated error sum of squares, 估计误差平方和
3 E' E" R% t0 K+ h4 d8 F) C: w5 [Euclidean distance, 欧式距离! {: E0 I$ G) @$ L( E0 U
Event, 事件
+ T7 C' [8 B2 D: iEvent, 事件( {7 j: i- j7 V) n- y* r
Exceptional data point, 异常数据点. D5 l: n( y. n6 V
Expectation plane, 期望平面5 s( x. m. _8 m2 M$ ^$ G
Expectation surface, 期望曲面
$ b" L: L7 J6 U9 N4 O6 q6 N- g+ FExpected values, 期望值
9 ]8 J' i* f+ z5 J9 F$ M, QExperiment, 实验
# F5 R% x6 [- R& f0 YExperimental sampling, 试验抽样& s) Q* t, O* @8 O* B
Experimental unit, 试验单位
& x. H& [/ Y" ]- e& l6 A8 o. @Explanatory variable, 说明变量
. ^6 q1 j4 t# U( P8 E$ N' W7 ZExploratory data analysis, 探索性数据分析+ k D; f+ h" P- V3 B/ K* K
Explore Summarize, 探索-摘要
, e" {0 e7 T+ p# qExponential curve, 指数曲线, Y- N; f; u8 L, d2 e% o3 ]
Exponential growth, 指数式增长
1 T% l( \; ?; @- EEXSMOOTH, 指数平滑方法
5 D4 S, F3 d0 I9 iExtended fit, 扩充拟合
: S7 v+ ]: G6 O% u7 w% rExtra parameter, 附加参数: o" J( l3 ?- h9 \5 u, K5 m+ c
Extrapolation, 外推法
8 ^$ @. e; ~1 A( ^ y0 y& XExtreme observation, 末端观测值# l( Z+ `0 G8 M2 N6 v
Extremes, 极端值/极值
" v* X8 W# I4 o9 M+ a5 r, UF distribution, F分布4 A- t2 Q: _5 W. ^
F test, F检验, J2 e, n- p# T6 F& J; s+ k+ D6 _4 q
Factor, 因素/因子
z% N2 B3 o2 }+ k- r. u: t( V3 RFactor analysis, 因子分析
F- @" ?* a/ h: ? PFactor Analysis, 因子分析
' H. f0 g2 G _' f, ~7 \) OFactor score, 因子得分 6 d( \+ G( \) p [) [- n6 r& L
Factorial, 阶乘
7 x3 ]' [, O" R' eFactorial design, 析因试验设计
9 X* T) r) m+ p0 t' CFalse negative, 假阴性
5 [* A r' k+ G- g$ z4 Q1 d# sFalse negative error, 假阴性错误3 B: P9 X0 Y3 Z; l' O5 O
Family of distributions, 分布族
( X) \0 @% {! C$ J* LFamily of estimators, 估计量族
- g6 p4 K. F5 ^6 q Q3 TFanning, 扇面
/ w: A4 Q/ W$ r, \Fatality rate, 病死率
4 Q' M" H- @" E' o1 mField investigation, 现场调查
! ]! L) h9 w/ {% nField survey, 现场调查! J( ~: k6 E! y6 U& T
Finite population, 有限总体" w( E+ O3 \ j9 S* F
Finite-sample, 有限样本, v' |7 a# p+ ?, y+ T9 d+ n
First derivative, 一阶导数% D$ {- C' V7 C$ q, | y
First principal component, 第一主成分7 ]; G ~- D1 n* c/ ?& G
First quartile, 第一四分位数
6 w# B! x+ g! e# W& }/ M3 g' rFisher information, 费雪信息量 P$ C; n; y, S3 ]4 S+ V+ P& K
Fitted value, 拟合值% [( u1 {2 ~7 K0 l# G/ V
Fitting a curve, 曲线拟合' d8 F/ H% X5 y# Z8 v' e5 f7 P! K
Fixed base, 定基' w5 M5 K- P: u. k, E* w3 F
Fluctuation, 随机起伏4 T& ~7 H( W4 }) v: x
Forecast, 预测
& s8 }' }+ u7 i! t; rFour fold table, 四格表
& c, j/ ^7 ?. b% c6 f5 }7 IFourth, 四分点
C! l) e3 f7 Y9 n+ |/ L3 eFraction blow, 左侧比率
; d4 F( o6 |7 f2 UFractional error, 相对误差
# m3 y$ y6 g8 E( C- L; n9 ]2 GFrequency, 频率
' K, Y K4 r, \) S5 j3 M3 O( YFrequency polygon, 频数多边图
" N! R9 R, |* R2 D6 J! j# `Frontier point, 界限点# o$ I W9 k: {- S$ i
Function relationship, 泛函关系+ O$ q5 U+ A6 F- R( W9 ~. R
Gamma distribution, 伽玛分布
3 z5 T6 l+ e7 G( K3 ?4 o/ O; xGauss increment, 高斯增量/ }. c: Q/ E) a7 v' n
Gaussian distribution, 高斯分布/正态分布0 c6 E. I( R9 n- p+ q
Gauss-Newton increment, 高斯-牛顿增量
a- ~' O$ D) L( J3 m0 H2 _+ ?General census, 全面普查
- m# Q, m: O3 YGENLOG (Generalized liner models), 广义线性模型 / v/ b& D5 P! U, X0 k9 U
Geometric mean, 几何平均数" k% E" V% b6 E. V: T$ G
Gini's mean difference, 基尼均差
( v* u6 `2 Z" [* Q) h0 TGLM (General liner models), 一般线性模型 ! ?+ _7 O4 G' l/ W& M' T
Goodness of fit, 拟和优度/配合度
9 P3 `7 }9 ]) L. ZGradient of determinant, 行列式的梯度 ? H8 x6 v1 q8 E) W
Graeco-Latin square, 希腊拉丁方
5 V$ K+ F5 G& N; t; }8 [- VGrand mean, 总均值6 F1 {. B- c2 |* v q! q; E$ G
Gross errors, 重大错误
# J; u0 R3 O+ M% HGross-error sensitivity, 大错敏感度
' \; N/ k# W3 y9 A+ M4 W& EGroup averages, 分组平均$ B9 n1 U, E& ^" H& w q1 i5 ^0 V
Grouped data, 分组资料, k1 r% ]8 }' F" D6 V1 [% m* R
Guessed mean, 假定平均数
& ?- Z* }' ]8 W# V& W; Q1 X1 YHalf-life, 半衰期
- b9 M7 r( m. Y0 \( q& `6 DHampel M-estimators, 汉佩尔M估计量9 {* M I/ e3 _$ P- [, O' }
Happenstance, 偶然事件
( x; r8 ?+ b7 G. QHarmonic mean, 调和均数
6 g% R7 v; d1 P) B5 wHazard function, 风险均数
3 M* Y4 v: L4 u" E3 gHazard rate, 风险率
; `4 f @$ A+ N, c) w, @" U5 JHeading, 标目
8 F" m& e2 A5 {9 I; ?0 d$ BHeavy-tailed distribution, 重尾分布$ W% m+ {2 f* x% q+ u" }
Hessian array, 海森立体阵) E3 h% b: O' p3 P) I1 ]- W6 j
Heterogeneity, 不同质$ y2 d9 x, U4 C
Heterogeneity of variance, 方差不齐 % D2 T, U, b4 q. g: w
Hierarchical classification, 组内分组
$ Y: \) @! w( `Hierarchical clustering method, 系统聚类法; b& S, {$ v& _* B0 S
High-leverage point, 高杠杆率点' n8 m% I& r1 s5 b' m5 F
HILOGLINEAR, 多维列联表的层次对数线性模型
* r& \* g2 C- e Y' D. X* `3 |1 MHinge, 折叶点
6 N9 b9 c; T" u2 wHistogram, 直方图' ?- g" M, ]" Q1 V, e: B+ h) C' Y1 k
Historical cohort study, 历史性队列研究 5 ^6 \/ b, T; y# r$ z0 I
Holes, 空洞
" S" t! I$ N/ A; z0 kHOMALS, 多重响应分析
9 c! L0 @% l9 |& W) }2 VHomogeneity of variance, 方差齐性
7 E2 p4 g0 R/ w8 CHomogeneity test, 齐性检验
' Z9 l( P. d5 K8 b! YHuber M-estimators, 休伯M估计量+ \3 ~; ~& Q& g5 @ x) H( y
Hyperbola, 双曲线) K& {% R$ ?# R, ] K
Hypothesis testing, 假设检验
: M% i' Y- t4 A$ V7 ^Hypothetical universe, 假设总体
% r7 l. p T5 ]7 Q; F/ v' RImpossible event, 不可能事件
% X- ^" i( a- T- D& pIndependence, 独立性6 _" I; T4 j0 z3 {4 ]& B7 l
Independent variable, 自变量: P& S7 r$ d5 S k7 _/ o
Index, 指标/指数) H. y; ^9 q: Y, t
Indirect standardization, 间接标准化法0 u: l( M5 x5 Y9 O
Individual, 个体 t6 q: Y# V }! A% _8 w: ~
Inference band, 推断带3 `) X- k- U" B7 ~
Infinite population, 无限总体: o% @8 X& ?4 b* h1 O$ d; M3 b* }
Infinitely great, 无穷大
0 K1 t. Y# v( |% i( qInfinitely small, 无穷小( h$ K- A& g: H5 x6 P9 d: v
Influence curve, 影响曲线$ G. R( V; |* h0 O
Information capacity, 信息容量. U8 U+ M- B# M @9 ~
Initial condition, 初始条件
1 s4 L. N2 }4 U* Y7 |Initial estimate, 初始估计值
/ ?# l5 [1 Y% r; t+ R4 N+ b0 g* GInitial level, 最初水平" d8 y) q5 x6 N/ d
Interaction, 交互作用
: _$ ~ E9 Y* \8 ^" a1 dInteraction terms, 交互作用项
, S3 R. X9 Q4 h6 m; QIntercept, 截距5 K6 A. M7 x; t$ _
Interpolation, 内插法
. a3 v) n/ D/ U8 A4 A! pInterquartile range, 四分位距0 E9 z/ Y5 ]) A6 A7 v6 F( Y) H; V
Interval estimation, 区间估计1 g5 p( _1 m0 ~0 H7 u
Intervals of equal probability, 等概率区间
# N8 U, B& D% L" j# \* [3 P) QIntrinsic curvature, 固有曲率1 R2 h, ^$ R2 h/ Z
Invariance, 不变性( K% S, l7 o% v6 U1 b
Inverse matrix, 逆矩阵( m; U* r# ]+ O; s, z
Inverse probability, 逆概率
7 S* z! ^# c) J) Q! [Inverse sine transformation, 反正弦变换! @' D# M: N% |4 n" r- @& X' i
Iteration, 迭代
2 {( W& w+ P3 g0 A7 CJacobian determinant, 雅可比行列式
) @2 G7 J) K% A; A$ E: |Joint distribution function, 分布函数; V3 I* m( F* f: f- X8 B6 r
Joint probability, 联合概率
- k' ^4 K% _: x3 O3 W* B U2 J* VJoint probability distribution, 联合概率分布7 J8 b( V ?0 C. [/ h/ `( j0 L/ E
K means method, 逐步聚类法2 q! v* o) v% O2 T* t
Kaplan-Meier, 评估事件的时间长度
4 G/ X7 ~2 U, D+ q4 KKaplan-Merier chart, Kaplan-Merier图
! x/ q4 C/ `- z% I0 n: UKendall's rank correlation, Kendall等级相关+ R d1 c$ Q! K
Kinetic, 动力学
! f# L: R" G% y$ v) v: QKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
' ?2 a9 Y8 d0 e' \Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验- K' I/ m, L' A5 A6 ~2 V
Kurtosis, 峰度" z; m6 m( |. O6 @
Lack of fit, 失拟
1 f( Q, W0 C' n; L% A: _2 GLadder of powers, 幂阶梯/ [6 c6 C# `$ i" C" C) r
Lag, 滞后
0 r' V0 Q0 c) w4 ]5 iLarge sample, 大样本
) p# `' G3 L- {2 ULarge sample test, 大样本检验, U& F1 x8 k3 I7 X0 t6 ^- Y
Latin square, 拉丁方0 x# j8 v% N& d- [2 w, c# k
Latin square design, 拉丁方设计: W$ I3 Z8 L1 }: }0 c9 w2 r9 l
Leakage, 泄漏% b5 V2 X: r* `
Least favorable configuration, 最不利构形& {% I; Q, D( w4 `' H
Least favorable distribution, 最不利分布: d: U0 x* q$ ?$ L
Least significant difference, 最小显著差法
' c+ E6 _ r2 k- ^5 mLeast square method, 最小二乘法
* I3 M) b3 i4 [- D3 sLeast-absolute-residuals estimates, 最小绝对残差估计
% _( `: {) E" M9 W. ]" SLeast-absolute-residuals fit, 最小绝对残差拟合* S( |# K0 S4 T) R- \# q
Least-absolute-residuals line, 最小绝对残差线/ {5 h% g; C- W- `' X
Legend, 图例
6 f7 j3 {+ R4 F( Z7 TL-estimator, L估计量
w; O7 o0 g; q3 }1 @# m. O, QL-estimator of location, 位置L估计量) l; |) y5 @* k: {& z) u4 k9 B$ ?
L-estimator of scale, 尺度L估计量
* C- E3 b7 v$ |% h$ VLevel, 水平8 T# v& c' g5 n( |
Life expectance, 预期期望寿命( \4 b, z! Y* C
Life table, 寿命表" r) T2 l1 s" e# R- J% `2 R
Life table method, 生命表法' b, ~- V S: t9 U
Light-tailed distribution, 轻尾分布
8 ^# F$ g7 k0 Q! o ?. N' d* P& eLikelihood function, 似然函数
' U! ?: Z3 V- e& R! }, @Likelihood ratio, 似然比1 Y5 p+ z8 }- ]( j4 N% @! n& `$ }
line graph, 线图2 y: F6 _2 f. D' i: x
Linear correlation, 直线相关' x, R2 H3 M' c ?- N) }
Linear equation, 线性方程
: K K; B& z0 Y- A7 I7 yLinear programming, 线性规划: E4 g9 z {* A' u+ W3 H
Linear regression, 直线回归
) f, K1 H, L0 K' s$ p/ g; [" yLinear Regression, 线性回归
8 X; B% e9 x4 _Linear trend, 线性趋势6 j) {, [2 V y, j* l& C9 H
Loading, 载荷 5 \* S; p$ Y7 Y* e4 `( A
Location and scale equivariance, 位置尺度同变性: \6 Z" ?9 y; e4 F7 |: |
Location equivariance, 位置同变性
6 C' k+ D+ M* o1 aLocation invariance, 位置不变性
/ f# B! S$ Q; s* w2 I8 Q- cLocation scale family, 位置尺度族4 r% }7 l W/ l; @- a1 {+ Q
Log rank test, 时序检验 4 T' v: O3 H1 ]. n( e
Logarithmic curve, 对数曲线3 Y/ S# H3 H% w1 ?1 x. k" L% T
Logarithmic normal distribution, 对数正态分布
2 \; M% h$ X/ jLogarithmic scale, 对数尺度& T& D! X' n' ]& q6 ~
Logarithmic transformation, 对数变换 ^# I a/ L: q/ f; Q+ f% v
Logic check, 逻辑检查' }: i4 t& q8 T4 i% a% [
Logistic distribution, 逻辑斯特分布* g9 }. p* p' J W% ]" t
Logit transformation, Logit转换
$ k- U3 _% B% \7 e8 ?LOGLINEAR, 多维列联表通用模型 : U4 L8 j5 o$ T! O J
Lognormal distribution, 对数正态分布
* ]: T+ `, J/ U, U. lLost function, 损失函数6 \1 x) }7 x! o* w
Low correlation, 低度相关$ w9 |- I/ Y/ h
Lower limit, 下限
/ r4 \& {4 m! G& C, mLowest-attained variance, 最小可达方差' q5 j' f4 N. @0 A7 S" W' P- d
LSD, 最小显著差法的简称- m* C3 ~: B; x8 R8 [" d0 \7 {0 R
Lurking variable, 潜在变量; s% I9 k _- {% o
Main effect, 主效应. e: R' H, P, m9 n
Major heading, 主辞标目. W' G n: k7 }# A
Marginal density function, 边缘密度函数
) g# [+ y3 r: z, W& o7 _( gMarginal probability, 边缘概率: @6 ~+ I$ f) q+ m r5 ]5 q% y, d# h
Marginal probability distribution, 边缘概率分布
6 g9 g- E2 F5 F, g5 m3 dMatched data, 配对资料 }5 ?$ u3 S9 F
Matched distribution, 匹配过分布
+ \9 z. n4 R; h. {1 s( KMatching of distribution, 分布的匹配6 ]0 D; q3 p+ O4 x: J3 U9 z
Matching of transformation, 变换的匹配% u( f t l( {7 [
Mathematical expectation, 数学期望9 ]6 @$ f' u8 r5 L7 j) W7 K
Mathematical model, 数学模型
4 l3 [: R/ f( g* v& HMaximum L-estimator, 极大极小L 估计量
6 j9 W7 R+ u" _+ o$ g& R" qMaximum likelihood method, 最大似然法) e, {6 @" {, N7 h
Mean, 均数. M4 R8 D4 c& z* X5 B0 T. j: s
Mean squares between groups, 组间均方
. t4 | [, P; w% @5 s5 C6 ^Mean squares within group, 组内均方2 ~, B) [" [3 d
Means (Compare means), 均值-均值比较! j% q4 t1 R$ e/ V0 Y2 i5 G+ m
Median, 中位数
0 G+ [, H& N( c2 v9 M; e7 S& |1 cMedian effective dose, 半数效量3 J4 U1 z# D6 {. ^0 W
Median lethal dose, 半数致死量
& a! U# I! C0 H- O7 Q$ GMedian polish, 中位数平滑
8 \. L2 g6 P1 N; L# w3 {Median test, 中位数检验
6 x1 r; r+ o# K$ y% v5 GMinimal sufficient statistic, 最小充分统计量. i ]- f+ D- O! d/ ?. F/ ]
Minimum distance estimation, 最小距离估计
8 t8 t5 J4 B4 G7 X. e# E' xMinimum effective dose, 最小有效量- l/ Q1 t! J) O
Minimum lethal dose, 最小致死量
! l7 V. I. [" J7 G+ CMinimum variance estimator, 最小方差估计量
- F# ?) f' \1 O$ `- a5 e" XMINITAB, 统计软件包" v/ ~! u4 a9 h, `+ `- [
Minor heading, 宾词标目
9 [1 ]% u3 w0 r% @Missing data, 缺失值
" U( l3 i/ q4 |* q4 ZModel specification, 模型的确定
. n B4 s, Q+ Z5 C7 j8 mModeling Statistics , 模型统计" h+ \ S D3 ^, z
Models for outliers, 离群值模型
7 w: r6 G/ U1 J: M2 dModifying the model, 模型的修正
; E! Q, x4 F0 h: A% ^( ^Modulus of continuity, 连续性模
: V s4 H7 c% t+ bMorbidity, 发病率 & u4 z* U; J c1 |+ t. g- j
Most favorable configuration, 最有利构形$ d) z# K+ G& e
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
+ `' f) y( J$ \3 j% dMultinomial Logistic Regression , 多项逻辑斯蒂回归
5 u, u: _2 w1 N2 Z, z" H7 rMultiple comparison, 多重比较1 f. t: U( ?8 G+ I, o# O+ \
Multiple correlation , 复相关% a% y" x) }$ D
Multiple covariance, 多元协方差
5 Q( v! {! J* b( l, EMultiple linear regression, 多元线性回归, V+ m8 s/ C) l: M* _
Multiple response , 多重选项3 m3 X1 f" g& o" q, i+ P
Multiple solutions, 多解
) k9 X) V& t( H# [, WMultiplication theorem, 乘法定理
( m9 I3 B2 c% R7 m& x0 ~Multiresponse, 多元响应
7 K/ {% k3 v% m ~" K* S6 GMulti-stage sampling, 多阶段抽样
7 _0 c- t& e+ R8 {9 V6 Y$ OMultivariate T distribution, 多元T分布
; Q/ b2 G- t% i( c; SMutual exclusive, 互不相容
4 s& n- o5 k0 k' s9 l# ^, eMutual independence, 互相独立8 `6 p2 C' y- d& I i& d1 ^1 D9 [8 u
Natural boundary, 自然边界* P! Q$ H+ L5 j- _2 r. k3 x4 x
Natural dead, 自然死亡4 Y' c: q( X4 U, [) R6 b; r) f
Natural zero, 自然零4 C% ~6 q# J K& n# ^
Negative correlation, 负相关
/ T9 ^0 V5 S. Y6 j0 nNegative linear correlation, 负线性相关+ }6 V$ M6 u; Z; C/ D6 V
Negatively skewed, 负偏3 R% c; ^9 y# G' }+ T
Newman-Keuls method, q检验8 A$ x2 v9 l$ I* |+ a
NK method, q检验. w! O. v. Z8 h3 L- u' ^$ X8 U) S
No statistical significance, 无统计意义
$ b: X1 o9 a/ E' I1 W+ D$ h6 ANominal variable, 名义变量
& k& Y0 b i9 I% Q" F$ c: UNonconstancy of variability, 变异的非定常性, |+ @( g4 f7 i+ X3 e
Nonlinear regression, 非线性相关
' s. a- d5 g7 H% _: @ F- uNonparametric statistics, 非参数统计0 L: m$ b! k4 C5 E$ T/ q
Nonparametric test, 非参数检验
: F L8 I' E7 G, M& |Nonparametric tests, 非参数检验- `2 y- c9 S% s5 p! R b
Normal deviate, 正态离差
5 s. N g. V; b$ [0 {4 k4 W5 YNormal distribution, 正态分布
1 x% C; M% J- y* U; ^# x8 S3 E `6 MNormal equation, 正规方程组
6 M6 u) `% y4 B8 s" G. q$ Z& fNormal ranges, 正常范围' L; @3 h* g0 I$ ~3 g( y5 D
Normal value, 正常值
$ [, Y7 A0 x& JNuisance parameter, 多余参数/讨厌参数( I. E& j3 Q! M- `
Null hypothesis, 无效假设
$ x2 W; X0 Z" m! w& z# T# LNumerical variable, 数值变量" b! i$ e: n6 O8 x- O# [4 n5 S' F$ N
Objective function, 目标函数8 e3 R# d( f! @1 o2 J% | w: o
Observation unit, 观察单位. }) ]( e$ y- o; m* b1 w, O. j9 Y
Observed value, 观察值% q( }9 x4 R4 Y7 }9 Q
One sided test, 单侧检验5 c, W9 ^! z2 I1 h- s+ j# I9 j& I
One-way analysis of variance, 单因素方差分析
3 y) {. g1 B' IOneway ANOVA , 单因素方差分析& z/ I6 h; I6 i; {% n
Open sequential trial, 开放型序贯设计1 ]1 W# `3 m2 l5 c$ B* Q2 V
Optrim, 优切尾2 o( Y* _$ R. I7 I. M
Optrim efficiency, 优切尾效率
# j8 v& s' A* W4 x2 WOrder statistics, 顺序统计量 B- b4 G7 M q: m" l7 b
Ordered categories, 有序分类
2 e3 M' k9 T0 v f7 n0 }6 tOrdinal logistic regression , 序数逻辑斯蒂回归) e8 D E2 M! f2 S
Ordinal variable, 有序变量9 F2 `8 b7 `+ m
Orthogonal basis, 正交基8 ] {( L' ^+ N8 ~
Orthogonal design, 正交试验设计
" Z6 ?6 k) V( i/ }8 N4 K8 eOrthogonality conditions, 正交条件
# Q5 @, |% d; b0 L0 P2 T3 zORTHOPLAN, 正交设计 4 J1 _+ _! s2 N7 J. {
Outlier cutoffs, 离群值截断点% X( }/ @. f8 I- B; E! y
Outliers, 极端值
, b2 m0 u% F3 U; C) QOVERALS , 多组变量的非线性正规相关
9 I# ^, f6 m: p5 f5 X! e4 MOvershoot, 迭代过度
% _6 a7 a0 T/ F x) ~, e. N5 bPaired design, 配对设计! g2 S6 b8 G% Y/ T
Paired sample, 配对样本5 P4 S! {5 `- q& ^& U8 @0 }. K; b- q
Pairwise slopes, 成对斜率- f7 l" [( H! k9 J
Parabola, 抛物线
% D' h/ R& d8 I- D; C# N* ?Parallel tests, 平行试验, q+ F" h! |' h# M. [+ ?# k
Parameter, 参数3 m9 S% F6 ~+ l, e: w5 I Q
Parametric statistics, 参数统计! r: ]! r1 O! p. Z7 f8 X, F+ Z
Parametric test, 参数检验. V, v4 c o2 T$ ]- F7 r3 D
Partial correlation, 偏相关- g* n0 k% Z- K
Partial regression, 偏回归
8 U( ^! k+ d1 K7 ~Partial sorting, 偏排序
/ P$ p& A( ]" I9 o% h+ GPartials residuals, 偏残差$ ^6 B' e K, x
Pattern, 模式
8 O" m5 S# d7 L" W, fPearson curves, 皮尔逊曲线1 @/ [/ J. x9 [, T N
Peeling, 退层
, ?! ]9 ]1 c3 W8 c* GPercent bar graph, 百分条形图
( \% _! A3 E1 f& R8 fPercentage, 百分比2 m# ?3 x. R) [& v: Y% Q0 R) C) k
Percentile, 百分位数% A$ D' u) l3 [$ {* b) ?
Percentile curves, 百分位曲线
% j6 o" S( M" [% n2 EPeriodicity, 周期性( G+ m5 s q+ ^ w: V
Permutation, 排列 N; \+ D! j" N+ Q
P-estimator, P估计量0 h9 U1 [" f( p" A2 y; P0 D$ T& b7 u
Pie graph, 饼图: c: X3 d9 Q( _, d5 t5 M3 I
Pitman estimator, 皮特曼估计量; Z" {! w: t& V7 k: c7 S
Pivot, 枢轴量7 J, |7 A6 {; v+ E
Planar, 平坦
( o9 p" \9 \1 A4 ~$ v; zPlanar assumption, 平面的假设5 Z! _" V* n0 |8 R9 q) `
PLANCARDS, 生成试验的计划卡
7 U: u7 t9 P% p5 z# ? E* M+ oPoint estimation, 点估计
1 n. p v! o; a9 ]8 APoisson distribution, 泊松分布1 ?- M+ R5 O; K2 i+ s" h
Polishing, 平滑+ s- ` Z" o9 _/ v4 E
Polled standard deviation, 合并标准差
! q" O5 G! g8 h* `3 ~' mPolled variance, 合并方差
# Q; W1 @: }1 c A6 Y/ _9 o) rPolygon, 多边图
1 n: a& e7 C% D# W7 O6 hPolynomial, 多项式; Z0 S# I& q7 h, R5 `! Z6 D7 A
Polynomial curve, 多项式曲线1 K+ ^& E2 k* X5 F/ V D- f
Population, 总体
1 w" D- i* h& G& FPopulation attributable risk, 人群归因危险度8 N8 u* `* A6 L$ [' m
Positive correlation, 正相关
/ D9 N' X9 L# V: p3 ?: Y& @" xPositively skewed, 正偏8 `/ o, R/ }4 p- u
Posterior distribution, 后验分布5 b9 ]& i/ j# E( M" M+ u' I( y
Power of a test, 检验效能
z7 \* C6 ^# M( K) D7 oPrecision, 精密度+ a9 H) I2 S* K' d( i( }$ I
Predicted value, 预测值0 R* ?# X5 x0 Y2 f3 b% |, x5 F
Preliminary analysis, 预备性分析
4 A8 t J+ y/ }% {* NPrincipal component analysis, 主成分分析: F% y' n: C( {
Prior distribution, 先验分布, ?% }' v$ p/ m5 o: S9 y
Prior probability, 先验概率" T& e. D3 v2 P; t6 w& A
Probabilistic model, 概率模型
: d n) i* R) a. H- Qprobability, 概率
. F X/ L) Y5 W6 Q0 N; CProbability density, 概率密度
4 N5 a8 x3 X* i- G7 @' {2 S7 QProduct moment, 乘积矩/协方差: }! Q9 k0 ]. H% ^
Profile trace, 截面迹图5 G6 l$ T0 C) ^ [
Proportion, 比/构成比5 ? E; d+ i# o
Proportion allocation in stratified random sampling, 按比例分层随机抽样
- p. u9 u; s0 W0 L; DProportionate, 成比例
6 C. @+ l. \! K3 E" B9 v! h5 ZProportionate sub-class numbers, 成比例次级组含量
+ T8 e1 D2 v3 t( LProspective study, 前瞻性调查
& ?0 X; r; D, j7 F: P* U! ?4 M$ FProximities, 亲近性
" D2 F/ w. j* I# b* M+ YPseudo F test, 近似F检验
5 ]5 ^! |# X' n6 DPseudo model, 近似模型
; X: |: x% ?6 G4 s# E' S& C0 OPseudosigma, 伪标准差
8 L0 |9 W1 y. yPurposive sampling, 有目的抽样
v- K: n6 `" i" LQR decomposition, QR分解8 G0 T4 @: r% ~9 q: E4 l
Quadratic approximation, 二次近似! |% F2 P! c4 a& C+ x
Qualitative classification, 属性分类
0 D J& s% w# Q" p) H; t+ g1 {Qualitative method, 定性方法
) }' [1 C2 a) U/ {Quantile-quantile plot, 分位数-分位数图/Q-Q图+ @3 F- A5 a; n4 J2 J& r% e
Quantitative analysis, 定量分析
4 j* s9 v0 U6 EQuartile, 四分位数
; k2 l( X. [3 pQuick Cluster, 快速聚类* O( D7 E6 x) [3 Y: x/ o
Radix sort, 基数排序
1 B% T( Z# y% }4 ?* H @Random allocation, 随机化分组: ?8 g# P# b# M" N+ t6 ~
Random blocks design, 随机区组设计
" t n, ]8 s. e$ E$ B( gRandom event, 随机事件
, u1 c* L i6 Q M; j$ wRandomization, 随机化
6 x- ^) ~3 h5 ^- a$ `Range, 极差/全距
( n, V6 S/ c" e: mRank correlation, 等级相关
9 r' l$ D2 A) ]; A3 E3 F7 IRank sum test, 秩和检验. i7 q' m; b! ?. l d+ G' ?: J O2 }
Rank test, 秩检验' E4 F5 F6 Y$ L% \4 i' I
Ranked data, 等级资料
2 X/ y4 [ O9 w& }0 rRate, 比率* z4 T5 X+ I& h4 D4 o% \
Ratio, 比例5 c, _, n3 F; Y" ]
Raw data, 原始资料! M( E4 X9 z8 ]2 y( ~/ p
Raw residual, 原始残差
- v: T7 n' n# ~* t! Y! F* CRayleigh's test, 雷氏检验; W2 W B4 v; X0 W* l
Rayleigh's Z, 雷氏Z值 : f6 o9 i( o T3 A/ y+ {
Reciprocal, 倒数
) C$ I' k2 T" ] `& @* lReciprocal transformation, 倒数变换
" z) `9 r3 _/ `# {! kRecording, 记录( }( f& S7 ~7 c$ a, n1 K. N
Redescending estimators, 回降估计量
) i8 W3 H0 Q3 X. oReducing dimensions, 降维4 V4 G. M) w; X& p& U
Re-expression, 重新表达& |, R: h! p9 R2 Z5 z
Reference set, 标准组
1 ]( d* m: s5 XRegion of acceptance, 接受域
" c; f- N; D" C4 [' _7 VRegression coefficient, 回归系数
) a" u, T+ @5 k# q" CRegression sum of square, 回归平方和
, ~- y0 \! c7 u% iRejection point, 拒绝点
6 }3 i9 y3 J) v2 t1 _Relative dispersion, 相对离散度
' Q$ L k4 b# S$ F+ i1 M- b- hRelative number, 相对数
: [8 B, J _. x0 B' R* ^+ ]$ W9 TReliability, 可靠性
2 b: v0 d1 p7 v6 r8 [Reparametrization, 重新设置参数, \7 H8 [- z/ H1 Q+ S0 ]# A- j- e! b
Replication, 重复
$ V1 e% h) [$ G7 G3 rReport Summaries, 报告摘要
# c$ c/ h1 z9 {" BResidual sum of square, 剩余平方和. f/ u& z6 O, M
Resistance, 耐抗性% u3 f! S; ]8 S7 q- Y4 ?2 a
Resistant line, 耐抗线
2 z6 T- O, y; H, o& ?Resistant technique, 耐抗技术% k0 ]: a3 r; F: p
R-estimator of location, 位置R估计量
4 D P" e0 |9 I' OR-estimator of scale, 尺度R估计量
3 U' a1 I" U: n$ p$ SRetrospective study, 回顾性调查
3 z9 q2 H, O. b! k4 R# PRidge trace, 岭迹; W K: {/ i1 k- ]# {) G3 t* |. o
Ridit analysis, Ridit分析0 I/ k6 ^5 i+ D$ f% c1 A
Rotation, 旋转
- ~; U( O& J1 _) V1 PRounding, 舍入. ~' K4 l& f- N; e7 ^6 b
Row, 行: b8 B0 l, o# \( I" P/ Z+ l% g
Row effects, 行效应/ R" R# n" l4 R( F% i; y
Row factor, 行因素. q4 c+ Y$ D" A# U
RXC table, RXC表
* B8 p m5 e7 d. O& M4 A ISample, 样本
4 T9 R$ I% b/ ^8 A" tSample regression coefficient, 样本回归系数8 g2 {. s. x: O" m" f! Q' g5 d) S6 p! k
Sample size, 样本量
3 Z9 l3 P$ r: d: L/ M- W% F8 sSample standard deviation, 样本标准差$ p# v: E* b# i# n/ F
Sampling error, 抽样误差8 ~. Q% N! J3 I
SAS(Statistical analysis system ), SAS统计软件包
3 M0 b4 C4 r) wScale, 尺度/量表 C) r l1 }! Y" Y
Scatter diagram, 散点图
- V# A! G! v/ m, y* |8 [Schematic plot, 示意图/简图) T5 t1 g$ i2 x7 `2 v
Score test, 计分检验$ J3 O$ r3 _2 s2 a6 y4 K
Screening, 筛检7 Y |! {& o u1 L0 o; l
SEASON, 季节分析 8 m5 ~9 r3 |" X" [ H6 b1 Y
Second derivative, 二阶导数% \. f: `! x m% Q( g
Second principal component, 第二主成分 ~" A: u K8 k9 W
SEM (Structural equation modeling), 结构化方程模型 ; B$ X9 ?$ q$ U* G# }( N
Semi-logarithmic graph, 半对数图
% B; p- j& S: k* W- ? O9 sSemi-logarithmic paper, 半对数格纸
" r" D9 w9 q! c( p+ b9 k4 V" C1 W) \5 fSensitivity curve, 敏感度曲线" t& {8 q% r/ D% V" B
Sequential analysis, 贯序分析
9 u& M5 s8 g1 }/ @Sequential data set, 顺序数据集: M0 d/ P2 t) ~
Sequential design, 贯序设计3 J) m W. t! B9 ~! r
Sequential method, 贯序法. M" c g! L( u. Z
Sequential test, 贯序检验法% l8 Q& P; s7 j' y2 }/ H' S
Serial tests, 系列试验
* B8 U% W/ z, Q* r: \Short-cut method, 简捷法
/ @5 D. x4 A/ |( X! J7 uSigmoid curve, S形曲线) H1 R; |+ \0 O/ N9 t
Sign function, 正负号函数
2 @; a+ @$ s KSign test, 符号检验
: y; ~0 s& M; T d9 }: KSigned rank, 符号秩
' X" x$ `, v5 U; M2 P0 i, ~Significance test, 显著性检验) F2 @0 L' u1 k9 ~" v
Significant figure, 有效数字 U+ R6 e' b n9 t$ ?
Simple cluster sampling, 简单整群抽样
- o& p, m" [7 K0 V1 y9 r) w6 PSimple correlation, 简单相关
9 f5 C! p, p- O" j$ b( }6 ZSimple random sampling, 简单随机抽样8 i( F. a- e2 I" [& H3 i# Z, s
Simple regression, 简单回归
# e; X: X: C6 X" [$ \' Wsimple table, 简单表
+ }$ R9 \! E5 J5 k! |Sine estimator, 正弦估计量' I1 P8 \0 r$ J5 f1 A
Single-valued estimate, 单值估计1 @! S$ J& y6 ^1 Q/ s
Singular matrix, 奇异矩阵0 k$ O2 g, Z2 J* S7 k" X
Skewed distribution, 偏斜分布
# }, V8 Q7 ?4 n, jSkewness, 偏度
* ~& K/ b# R' v) S+ S6 u6 }Slash distribution, 斜线分布* Y0 N! d& Q" @7 ]5 c
Slope, 斜率8 I8 {! O4 |- V) Y8 t( B
Smirnov test, 斯米尔诺夫检验! d/ H+ w! R ^0 u$ u
Source of variation, 变异来源
* z' ?8 B' P( d5 N9 Y* MSpearman rank correlation, 斯皮尔曼等级相关
2 B% z: p( \4 i$ n3 J eSpecific factor, 特殊因子
; n2 \6 U, M l" P5 U4 K' ~& H. d( QSpecific factor variance, 特殊因子方差
* B4 Y K+ e: F; D' k9 pSpectra , 频谱, t9 j% E8 L' }. v+ O8 I. r4 c0 i! ^
Spherical distribution, 球型正态分布- [/ j* X( G' }9 l6 q
Spread, 展布
7 Z) d" P& [3 }0 Z1 ]( SSPSS(Statistical package for the social science), SPSS统计软件包9 E3 s9 u* j: e( u* T
Spurious correlation, 假性相关
+ p% x) h5 t9 ~- |! p2 P. pSquare root transformation, 平方根变换
0 g! T2 m& H" {9 Z \Stabilizing variance, 稳定方差4 V i( w& _5 m! Z
Standard deviation, 标准差
) e- d D2 L. y$ hStandard error, 标准误
% e, Q0 Q& o1 D% wStandard error of difference, 差别的标准误0 U: Q, ^- P$ z: R- i9 x) X6 D5 h/ a
Standard error of estimate, 标准估计误差4 N. e+ Z1 |2 @! U! i! i
Standard error of rate, 率的标准误
+ r& o0 ]' I3 x9 mStandard normal distribution, 标准正态分布
4 m& }2 H% m# X/ N. W$ M4 Y1 ^Standardization, 标准化& \3 x; P+ `% B: [
Starting value, 起始值
?, p5 g8 u1 a, P& ~Statistic, 统计量
& h" o8 M. C G( c3 w- M3 xStatistical control, 统计控制
/ }6 P* H# C' D: ` R5 i# G- L/ J2 n6 lStatistical graph, 统计图* P' ] V6 b# z7 ]6 H
Statistical inference, 统计推断) S$ `* H- e! j5 z- a$ w
Statistical table, 统计表7 I6 j1 D/ I) @! u. p) t
Steepest descent, 最速下降法( h! N+ l2 {7 v
Stem and leaf display, 茎叶图' E! n7 b" ^ z
Step factor, 步长因子
9 U* v( ~" @3 ~$ R+ r% d" VStepwise regression, 逐步回归
+ D7 Q: i9 `7 EStorage, 存
* }8 C) s$ L! i2 oStrata, 层（复数）
# G2 Y Y% I1 O7 L6 `Stratified sampling, 分层抽样% j+ f/ r& N2 N x7 I
Stratified sampling, 分层抽样
7 [7 x, w* z" C7 D$ j$ x6 W, {Strength, 强度
4 I* @$ ~# m- @$ nStringency, 严密性
# `% D( p% m1 Q6 g/ gStructural relationship, 结构关系8 H1 c# J; k3 ~
Studentized residual, 学生化残差/t化残差. p3 V/ K% _/ D/ _+ t7 P( Y1 V
Sub-class numbers, 次级组含量; J6 `6 W9 g3 F8 c) a: u% n
Subdividing, 分割9 @ v& Z- ]( U9 U) t" J* }% [
Sufficient statistic, 充分统计量
9 n) w" l' C1 Q/ t; w0 }Sum of products, 积和
2 q+ e9 q7 f. c/ F" c7 [: _. YSum of squares, 离差平方和% W' y3 b' D2 P4 m
Sum of squares about regression, 回归平方和
/ Y! C9 Y4 T4 g) H8 ^1 E _Sum of squares between groups, 组间平方和9 D a# i; G @: H A6 y
Sum of squares of partial regression, 偏回归平方和: u$ W$ `4 b: W" W; f
Sure event, 必然事件
: B) D7 g; q" f5 M5 `: |Survey, 调查
( N) w* e; C7 e% U3 wSurvival, 生存分析
* p! R0 e6 z) O* h9 R* j! nSurvival rate, 生存率8 S* f0 F1 |+ \/ M/ K" y$ T) t
Suspended root gram, 悬吊根图
8 n8 V+ |4 |' U1 l4 I( DSymmetry, 对称
# A$ @$ _, |9 |Systematic error, 系统误差
5 @8 |- v, t/ x% B! Z; WSystematic sampling, 系统抽样
7 @9 O' |! [4 r. W5 y. C$ ^% wTags, 标签
/ O+ f* A- k. W2 E' eTail area, 尾部面积" j1 D, G, w# g8 T
Tail length, 尾长
$ D3 Y9 [1 ?) v: `Tail weight, 尾重2 \) J9 ]5 w7 S5 G
Tangent line, 切线
! P" a0 q/ x% F* L/ MTarget distribution, 目标分布
( b% f9 B$ H' m0 m; t, zTaylor series, 泰勒级数. Z1 c, m6 O, H
Tendency of dispersion, 离散趋势( u# Z5 a9 z# e; F- z
Testing of hypotheses, 假设检验
% ^5 Y9 l* X' U8 c6 mTheoretical frequency, 理论频数
}0 ? ]) G- J8 ?! y. `1 XTime series, 时间序列
4 ^. l! ?; j: i/ j s `Tolerance interval, 容忍区间9 v q4 e9 I0 G+ s
Tolerance lower limit, 容忍下限
5 b, z8 u c3 i! |8 q5 e2 yTolerance upper limit, 容忍上限
: I8 o- D, H- L- vTorsion, 扰率4 ?: V4 \$ g* [# X+ W, |) U# w
Total sum of square, 总平方和6 R% u7 q+ o0 x2 E' {0 e
Total variation, 总变异7 g" e/ l9 `, `, i
Transformation, 转换# ]; M# T2 V6 ?& ?1 N
Treatment, 处理
/ z7 O6 [* Y( m0 D$ zTrend, 趋势" G; v- Y4 E+ r& G$ y- S. F
Trend of percentage, 百分比趋势" Q2 W* g! E. D5 c8 D
Trial, 试验
1 P0 P* A( Q5 C# MTrial and error method, 试错法 D# [7 b. q( B5 j' G& ]' p1 u( Q$ d
Tuning constant, 细调常数7 r7 m; r+ \- W. b6 J G1 W5 I6 B
Two sided test, 双向检验
1 F* c3 i, ~0 Q, s7 o6 fTwo-stage least squares, 二阶最小平方9 r$ `- z$ P5 N4 p5 a5 n& a
Two-stage sampling, 二阶段抽样
. Y+ O# Y/ p8 h. m: hTwo-tailed test, 双侧检验
! ~; ~3 ~. D% WTwo-way analysis of variance, 双因素方差分析# N5 U3 g- C, C& V8 i
Two-way table, 双向表$ c( p- w9 i$ K. M$ Z' C6 u
Type I error, 一类错误/α错误9 G8 {# }8 I4 A- L2 n
Type II error, 二类错误/β错误
+ E8 N, `, ?5 M d! F4 AUMVU, 方差一致最小无偏估计简称
) W Q- i. ^/ j# W K7 ^Unbiased estimate, 无偏估计
; O. o& c' x0 _( @1 e+ hUnconstrained nonlinear regression , 无约束非线性回归/ v$ j, r/ p+ M1 r: ?0 T# A
Unequal subclass number, 不等次级组含量" ?3 Z& P% _& P3 o5 G0 ]* [- Z3 q. ?4 s
Ungrouped data, 不分组资料: w' n. b6 d8 S4 q
Uniform coordinate, 均匀坐标
, h( W7 R0 R3 B- D/ HUniform distribution, 均匀分布
1 a# t4 {, L9 B- i# } N4 e0 FUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
1 y9 A) S" o) r3 ?$ `Unit, 单元9 F' P5 F- b# i! a
Unordered categories, 无序分类
9 `2 t) ~) `9 ^/ CUpper limit, 上限
: e2 R. X: k. k( }+ a+ l- K& j, a4 \Upward rank, 升秩
L- b" h; b# ~- l7 Q" UVague concept, 模糊概念
4 A5 S, z2 U" b8 L uValidity, 有效性2 Z! \ N) V' H5 ?
VARCOMP (Variance component estimation), 方差元素估计' U O4 W- ?$ a/ [+ G) Y U. F3 p
Variability, 变异性
3 [+ A9 M5 p- _) NVariable, 变量
( n) @! [" h+ [) O: f: t: W, G' }Variance, 方差! S* S- Z3 c- Y- K3 ?' f' f. Y
Variation, 变异+ e' o1 o5 A& V
Varimax orthogonal rotation, 方差最大正交旋转* X+ t* x. G# t( |: V
Volume of distribution, 容积
0 `- {* j6 G9 G; qW test, W检验: w/ O6 I5 s" }1 R, Q8 z
Weibull distribution, 威布尔分布
: d% J% C4 a1 a1 c( f! d5 f, ZWeight, 权数7 s t. ^8 O' s' B Q
Weighted Chi-square test, 加权卡方检验/Cochran检验( n H) z7 u* G* h
Weighted linear regression method, 加权直线回归
* A) e1 p- h+ d5 yWeighted mean, 加权平均数
C }' F& Z' y% x4 e# NWeighted mean square, 加权平均方差% | s2 d. C- K1 C+ P% n; c
Weighted sum of square, 加权平方和
5 x: w# t# Y; L N, k1 dWeighting coefficient, 权重系数/ q. t; O0 q- r4 j, H. R
Weighting method, 加权法 ( D/ x6 O# h2 {
W-estimation, W估计量
0 n8 T0 P6 K+ S$ pW-estimation of location, 位置W估计量. h0 T- @; P0 \' e; w
Width, 宽度
4 J/ ~ T+ f9 L. b7 v" `& c; WWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
) ]' H5 g7 d& t1 \Wild point, 野点/狂点1 E6 _# V$ b: I2 F9 i: {+ t1 e- s3 I
Wild value, 野值/狂值; P4 v0 W+ H+ M
Winsorized mean, 缩尾均值4 i3 i/ \ e; E7 \& w3 ^
Withdraw, 失访 " f/ b9 V+ j) I, Y
Youden's index, 尤登指数' S7 A( ?/ s# v7 S1 l' l
Z test, Z检验
+ E4 f8 d! f4 Z$ ^8 {, IZero correlation, 零相关' M: `/ [6 f* z: p+ b
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
