|
|
Absolute deviation, 绝对离差
$ n6 Z C. P, y3 \" QAbsolute number, 绝对数* d+ e4 O" j* n- }
Absolute residuals, 绝对残差
# t; f: q3 }) J B( eAcceleration array, 加速度立体阵
5 m! Y4 Q: n; g1 X" v" w: D9 Q8 hAcceleration in an arbitrary direction, 任意方向上的加速度
1 o3 a. g) Y& z/ I, V* t4 y4 z+ qAcceleration normal, 法向加速度: X; N# v! r: b% V: P3 J5 k
Acceleration space dimension, 加速度空间的维数& }- h- o7 N: K) [: I' I
Acceleration tangential, 切向加速度- z, |; W2 i5 Y
Acceleration vector, 加速度向量2 I: n$ j* y" E" H) c& a: y" B
Acceptable hypothesis, 可接受假设
# A0 v& _$ @0 S7 |* J. ^5 j# S% RAccumulation, 累积7 G. S& w3 u3 b
Accuracy, 准确度
) z- @! ~" c% \4 MActual frequency, 实际频数6 k, i8 j$ Z. g6 ?
Adaptive estimator, 自适应估计量! s1 E) v' A( z! q U6 U$ g/ d$ \
Addition, 相加
. Z: L4 ~ A+ @" V6 S2 M* l9 kAddition theorem, 加法定理& U5 f' m* T- x5 Q- V" b N
Additivity, 可加性
: j7 B% ]* G. `$ DAdjusted rate, 调整率. z1 r% z6 A1 u) _- B: }
Adjusted value, 校正值
) [" y7 m' j2 N" i# ^) }6 mAdmissible error, 容许误差
+ i" _; p" D B6 iAggregation, 聚集性 C s# e) q/ ^6 S
Alternative hypothesis, 备择假设6 L5 q( Z% N0 _# x: F c/ O J
Among groups, 组间
* G% {/ M* w+ r7 H# u4 zAmounts, 总量
# p( @4 j; N4 G, A4 C. jAnalysis of correlation, 相关分析 A, z) g4 R3 k4 M
Analysis of covariance, 协方差分析" ^4 }. M( O7 E/ d. J1 a
Analysis of regression, 回归分析
; P X7 { K+ U" GAnalysis of time series, 时间序列分析
: h" D) o0 g$ |! ^Analysis of variance, 方差分析2 ]. T8 X: [9 Q. `" g0 p
Angular transformation, 角转换
& l% T9 u, P, l' EANOVA （analysis of variance）, 方差分析
# j2 ?- i8 e' {; yANOVA Models, 方差分析模型+ }* V- z( o# E8 V V3 h; {+ c
Arcing, 弧/弧旋
3 f0 ]! E# v/ c' GArcsine transformation, 反正弦变换7 I0 X0 h( D; z/ ?7 o* }
Area under the curve, 曲线面积
3 k4 M1 d5 S& G/ b8 EAREG , 评估从一个时间点到下一个时间点回归相关时的误差
0 @; z& K% Z& o4 v3 UARIMA, 季节和非季节性单变量模型的极大似然估计 ( U. Z) |! n' B
Arithmetic grid paper, 算术格纸3 L# k# ^ d4 A# {
Arithmetic mean, 算术平均数& x0 X% _% ~$ | @# Z& j+ Q: m
Arrhenius relation, 艾恩尼斯关系( `2 X, b5 K1 c8 n
Assessing fit, 拟合的评估; U. e: O0 B& H8 G7 C/ ^7 y3 y
Associative laws, 结合律( ]$ T' n Q3 g- K
Asymmetric distribution, 非对称分布
1 Y5 X& n# c; N/ r* p5 x0 @2 ZAsymptotic bias, 渐近偏倚
% K# H7 t. _3 \9 u: v5 a9 uAsymptotic efficiency, 渐近效率
; z; z o$ M! yAsymptotic variance, 渐近方差7 I- ?/ R7 P$ Q6 `
Attributable risk, 归因危险度
% b+ |; w$ E( F% q9 |. NAttribute data, 属性资料
' F& ~9 d3 B9 O6 SAttribution, 属性* ?; P& m4 A8 d M
Autocorrelation, 自相关& v0 y1 {/ N- K; ^) `6 I- U
Autocorrelation of residuals, 残差的自相关
% e1 {- R: G) ~0 mAverage, 平均数
" D1 I7 I" A, C) `0 {3 D8 k) w6 j& rAverage confidence interval length, 平均置信区间长度' s& {5 a0 c* G ]2 V4 o8 J6 U
Average growth rate, 平均增长率
% O, S+ Z' d% z' W: x+ z# SBar chart, 条形图1 V5 w5 H1 d# K4 d
Bar graph, 条形图
) D: V) m& c7 f3 F: qBase period, 基期. `) f! f n2 F+ L* A0 `' a
Bayes' theorem , Bayes定理
z! y1 F, C6 z- [0 fBell-shaped curve, 钟形曲线* J, Y3 o L$ l" d8 |3 J t- Y
Bernoulli distribution, 伯努力分布
7 K' Z) O% Y i+ ^Best-trim estimator, 最好切尾估计量5 M* o3 G9 w! P3 `
Bias, 偏性
! ]* ^- i% W' n, B( TBinary logistic regression, 二元逻辑斯蒂回归% o9 ]" ^ T+ ^3 Z
Binomial distribution, 二项分布
' W! V0 d4 s, `: XBisquare, 双平方
& ^. g7 a* F2 c3 \Bivariate Correlate, 二变量相关# [) \4 p; m% n9 j8 O4 o
Bivariate normal distribution, 双变量正态分布6 I8 q' @3 }: q- { |2 N0 d9 X4 P
Bivariate normal population, 双变量正态总体
- z* g" o6 n, kBiweight interval, 双权区间+ ^4 p3 `) H/ C1 e5 V( U
Biweight M-estimator, 双权M估计量" g7 ~1 Y) J5 _
Block, 区组/配伍组
6 ]& W1 f5 n: g6 R5 sBMDP(Biomedical computer programs), BMDP统计软件包9 B' I5 K1 k2 E2 B( ^* v7 r
Boxplots, 箱线图/箱尾图3 T& ^! r h1 J/ R
Breakdown bound, 崩溃界/崩溃点7 o/ k# v: k/ R, c, v6 ?
Canonical correlation, 典型相关
3 f; ^) ]8 J$ `; WCaption, 纵标目
' m5 g6 K) f6 M6 bCase-control study, 病例对照研究
4 s5 Q6 }/ ^5 U" u. r+ RCategorical variable, 分类变量
' n6 m1 y6 I) @. mCatenary, 悬链线
( W" y) c9 d, |$ T' NCauchy distribution, 柯西分布$ ?6 ~0 n( c- F, ^( g1 D: R
Cause-and-effect relationship, 因果关系) `! e( H3 i2 [ S+ p
Cell, 单元
: L* ^ f+ K) J1 `( b+ d' hCensoring, 终检/ q+ |: t/ v5 o! b9 g6 E7 a
Center of symmetry, 对称中心' s: f7 O% a$ z* C
Centering and scaling, 中心化和定标
" t3 O1 k' R( c7 ]Central tendency, 集中趋势
' S7 A- k" x7 Q0 YCentral value, 中心值' `* K* U5 r( U# K# f, f) ]. j
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测; j& o4 C" b/ U. m# x) {
Chance, 机遇9 X, X# X! ~. ~5 r+ W* P! I
Chance error, 随机误差" O! X% z8 R+ p7 |+ C& l6 H- c
Chance variable, 随机变量( ?9 f7 F" Y9 T, O n; l
Characteristic equation, 特征方程; E, [) n8 Q7 `$ h" U, q. {
Characteristic root, 特征根
* m# a5 T2 P6 r8 \8 lCharacteristic vector, 特征向量
6 K9 x$ B$ t1 Z0 K( HChebshev criterion of fit, 拟合的切比雪夫准则# U5 h7 J. v% F; T" F
Chernoff faces, 切尔诺夫脸谱图
% O4 b; t% M8 A4 g; [" q7 KChi-square test, 卡方检验/χ2检验
7 [3 y+ H s8 t* k% |7 e& kCholeskey decomposition, 乔洛斯基分解8 l% h% ^. e v9 z+ u7 @( r5 l! v
Circle chart, 圆图
' a1 P- R& W: R, I; K* yClass interval, 组距
5 X& Z% l0 I s2 M* i& A% _+ s0 J- lClass mid-value, 组中值. S7 ~1 U! ?; Q2 \4 d6 D
Class upper limit, 组上限0 Z! w) x5 {4 Q7 l' i
Classified variable, 分类变量) b4 v, @: k* Z* `& B5 v: N
Cluster analysis, 聚类分析' j/ T) g$ _0 f6 M4 J, O' r, B: ~& ^; J# |
Cluster sampling, 整群抽样( W" G/ y, ]. @2 _3 g
Code, 代码
- X0 w2 t! W+ z' C3 {Coded data, 编码数据9 ~: X/ P2 t$ q: C* L- E" K3 k
Coding, 编码
. A) K2 k" {" LCoefficient of contingency, 列联系数" S/ o. i0 C3 A+ b
Coefficient of determination, 决定系数0 q0 Y4 h& r1 W. y
Coefficient of multiple correlation, 多重相关系数
! k% q- q: Z/ d, vCoefficient of partial correlation, 偏相关系数
7 t) X8 T1 }( s8 SCoefficient of production-moment correlation, 积差相关系数
& [; @: a, R' K) c/ s! f5 JCoefficient of rank correlation, 等级相关系数' p1 F9 ^7 q L& q
Coefficient of regression, 回归系数
/ n. b6 s% X6 o0 R4 D' R! |1 L8 GCoefficient of skewness, 偏度系数
# f# O0 R5 ^" s' b! E& GCoefficient of variation, 变异系数
3 [& G; G' W" Q7 U c0 S. q! ICohort study, 队列研究
& x' z% C- o( e VColumn, 列- o0 I& f1 e' z8 B9 _5 o6 `4 t7 }
Column effect, 列效应
. c5 e; I! Z* uColumn factor, 列因素" F6 }- s( u( w
Combination pool, 合并
( j8 X1 @! E6 p2 U& _9 ]Combinative table, 组合表. H% T, G6 Z3 t- R) U
Common factor, 共性因子' l% X# e G/ v5 O9 o9 c6 q7 p8 J
Common regression coefficient, 公共回归系数. I6 |3 V/ }. b5 R" S: W' ]9 `
Common value, 共同值5 r6 K+ {) Y$ T
Common variance, 公共方差* y) _0 A: P( n) Z/ T7 c* e
Common variation, 公共变异
6 @* [3 r R4 o! g6 f7 BCommunality variance, 共性方差3 p& a' n, w7 t( w+ g% t
Comparability, 可比性
+ z( h7 z& I4 TComparison of bathes, 批比较
3 w, l H. E; v- L, J" _% BComparison value, 比较值! ]$ X+ y e# [: K7 Q& s
Compartment model, 分部模型3 T- |6 M* T" j
Compassion, 伸缩 M2 d2 o. U3 |, R) _! @/ b8 D. K7 d
Complement of an event, 补事件
: i4 M- [9 }, k+ o8 d/ R/ xComplete association, 完全正相关: r! ~, ]9 R8 P. a. [5 w
Complete dissociation, 完全不相关) f5 j. o: f4 B9 i2 E1 {! }4 t
Complete statistics, 完备统计量
& z$ H# b6 ^, rCompletely randomized design, 完全随机化设计
; k' u5 Y8 T+ W! \% X# A, WComposite event, 联合事件# }& D, X$ D5 `4 Q3 }0 z4 M+ @
Composite events, 复合事件* e- X- J) f9 T" O, [7 P
Concavity, 凹性" ?7 C9 ?: I/ u P/ _* p
Conditional expectation, 条件期望+ `6 u+ h8 J) X W: w- {
Conditional likelihood, 条件似然. _- O1 k7 b/ I8 y) F+ Y
Conditional probability, 条件概率
% T4 U5 H" N$ G3 gConditionally linear, 依条件线性
; b+ o3 V# z+ Q) R$ YConfidence interval, 置信区间
* O. J8 q) n+ e4 m, @Confidence limit, 置信限
: q6 j6 U" t1 |3 Z; g/ @( A" J; DConfidence lower limit, 置信下限
' M1 q/ @/ @3 y* r- R8 wConfidence upper limit, 置信上限2 d5 s- w, [! O
Confirmatory Factor Analysis , 验证性因子分析* u, @& J% q: |
Confirmatory research, 证实性实验研究
4 s0 q) F# f; e/ l" n) B7 e4 ~& tConfounding factor, 混杂因素
. a3 t3 u0 `( M& g+ d$ _+ o- b8 pConjoint, 联合分析5 K& v- F* i/ M, e; c9 A* r3 |
Consistency, 相合性
* }8 n- V4 w$ }7 VConsistency check, 一致性检验
6 r+ {$ @9 Y' A* W. y+ B, P8 u# z! bConsistent asymptotically normal estimate, 相合渐近正态估计
+ p [" d6 ?2 V, j* C' A; z6 hConsistent estimate, 相合估计
* s7 v* c7 V) `; O2 S- f5 O4 j: ^Constrained nonlinear regression, 受约束非线性回归2 g% D. Z4 e j
Constraint, 约束4 \- r1 V4 A& {) t9 Q- l: F
Contaminated distribution, 污染分布
" F( F1 R2 p. G1 R0 {2 R# d. nContaminated Gausssian, 污染高斯分布
4 d% e7 e$ L! [ F: iContaminated normal distribution, 污染正态分布
3 C+ E! M b& lContamination, 污染
6 t# M- _; }- sContamination model, 污染模型6 }/ R) D! t" a2 [/ p" y0 L& y
Contingency table, 列联表! |. E: K) [( P* Z% P+ `
Contour, 边界线
" ~) a8 w2 q4 S# [Contribution rate, 贡献率
" Z l# U/ } t" zControl, 对照
" l- `0 A: ?1 Q kControlled experiments, 对照实验
( Y3 W& n7 E; ]5 hConventional depth, 常规深度
: z; y% B2 `0 ]0 {" v: s, `Convolution, 卷积; V0 R' P, x# d O8 j
Corrected factor, 校正因子3 G1 C2 C1 i7 h% _2 ?1 O
Corrected mean, 校正均值# P) w& Y# L1 ?2 ]+ N
Correction coefficient, 校正系数8 @8 n/ z1 g2 {$ U7 v( t. d9 z
Correctness, 正确性
6 E& u! u$ n5 ~" I# H' hCorrelation coefficient, 相关系数
- @# S e a8 L# H5 o G. RCorrelation index, 相关指数
/ j8 i! f4 H' v- v' |: mCorrespondence, 对应6 t0 V; Y/ s1 M) a, ~+ Y8 ]
Counting, 计数# d- `3 p# R. ~( [% D/ l% X
Counts, 计数/频数
. E0 M+ O5 ~0 b0 K$ k8 L* ZCovariance, 协方差
& m4 n* K: `4 D4 B. N1 {, ]' q) A# eCovariant, 共变
& Z1 A; A2 d/ a C, Q. BCox Regression, Cox回归7 n0 l. q6 ?9 m q% c
Criteria for fitting, 拟合准则
2 y) I, [4 U. |1 ?/ {. sCriteria of least squares, 最小二乘准则2 J# O' o) T: K* U! H! N
Critical ratio, 临界比) w0 W: h; t3 d1 u4 g
Critical region, 拒绝域
& e' j) l% S- ^7 k- x! L: Q$ g% F8 LCritical value, 临界值7 Y2 U3 d+ Q) v: `
Cross-over design, 交叉设计
4 I! M) a7 p, T& [Cross-section analysis, 横断面分析
4 F1 b" g* Y. Z3 HCross-section survey, 横断面调查
2 g% e6 J! _: s. b& W# D4 }6 \Crosstabs , 交叉表 6 w! U. ]1 m1 k: ~
Cross-tabulation table, 复合表
7 d) r/ Y. n8 [6 bCube root, 立方根
+ o2 ^/ M: ^( PCumulative distribution function, 分布函数
* s1 ~. C1 t0 T/ i3 L; e% vCumulative probability, 累计概率
: ?6 A* {. U, P1 \, [: p4 YCurvature, 曲率/弯曲9 s$ g$ n# g& {# D! z
Curvature, 曲率
3 b) u) x% w/ V) |" g, H& `! {Curve fit , 曲线拟和 % T4 u6 N& J6 r1 I0 p+ f% O
Curve fitting, 曲线拟合
& z1 k' ]& |' ?* P* S3 RCurvilinear regression, 曲线回归
) t$ y' \/ y; s' L+ d9 u, e+ @4 oCurvilinear relation, 曲线关系 y: K6 d* r1 b! K1 ~& j
Cut-and-try method, 尝试法
0 z) q! I" [& qCycle, 周期
& V( w. l$ s2 f* S4 |Cyclist, 周期性
+ a) s2 T% }, v- q$ M) oD test, D检验$ G7 c/ O, M& r b, E' t$ U
Data acquisition, 资料收集! N0 e' D9 P) T! C
Data bank, 数据库+ Y0 L [' G2 j0 b: u) p
Data capacity, 数据容量
- k/ j! f$ i7 Y3 xData deficiencies, 数据缺乏' P4 O2 @. o# c4 B) E
Data handling, 数据处理
4 B9 u( n# U: @' H; AData manipulation, 数据处理; f/ \+ d, y4 o; v$ o4 N/ w
Data processing, 数据处理
7 `: b, \5 Y9 AData reduction, 数据缩减
) h6 n& x( E# S: F ~" q* QData set, 数据集
& L8 [7 ~3 V$ [Data sources, 数据来源) i( c* v' w- U7 w
Data transformation, 数据变换
5 h4 N d) A3 T9 S1 b6 t' dData validity, 数据有效性0 I9 a4 B( H2 c9 x, ^: a
Data-in, 数据输入- [( ]' C! T4 Q1 r: ~
Data-out, 数据输出* l+ L$ ]7 [- R4 D
Dead time, 停滞期- ?% E8 X9 B' a, Y9 d4 T
Degree of freedom, 自由度. k# ~; P4 |7 X3 V
Degree of precision, 精密度, c6 z8 z2 |1 }' s% H6 ?$ ~( o
Degree of reliability, 可靠性程度
2 j) Z4 h' T: \' O. D" }$ yDegression, 递减
, X7 O- ~6 _) @+ q _& n$ @# FDensity function, 密度函数
3 ?4 q& O& I9 c( T6 w. O9 qDensity of data points, 数据点的密度& A2 R) C5 _2 o! t- i2 y
Dependent variable, 应变量/依变量/因变量% K2 l# s; f$ R' b% n
Dependent variable, 因变量
5 g# O/ w- w7 o" U. UDepth, 深度0 Y1 I6 E n$ P C
Derivative matrix, 导数矩阵
$ J/ B% W6 l& \+ |/ B2 K3 HDerivative-free methods, 无导数方法
: q+ A3 [: y% I: ~( N' v" MDesign, 设计
# h- y/ Z6 \0 C2 |2 }* S b% UDeterminacy, 确定性2 b; h/ B' S9 b1 Q7 y& f
Determinant, 行列式
% }# D. C5 P$ a8 W, O9 a$ bDeterminant, 决定因素- |9 ^8 g) D$ g! Z) U4 l
Deviation, 离差2 k- {) c! @& }
Deviation from average, 离均差4 \3 ]7 W8 Y/ q( K Y" v3 n7 \
Diagnostic plot, 诊断图
7 X3 k4 A) ~8 ~Dichotomous variable, 二分变量
0 s6 M9 V! j3 |- V$ pDifferential equation, 微分方程
; {4 {5 H: w3 Z5 c) b- nDirect standardization, 直接标准化法' L% n2 c$ S8 f7 `
Discrete variable, 离散型变量
) a; C$ _7 ?# ~DISCRIMINANT, 判断 7 r4 d* i( b3 n
Discriminant analysis, 判别分析2 z! j7 ~+ ]+ U. G0 k: u
Discriminant coefficient, 判别系数6 c8 q* a/ E, | k" X7 a
Discriminant function, 判别值
8 ?; X G# N, N% @+ i, p: O7 x8 ~Dispersion, 散布/分散度
( v( C1 k1 j p# {Disproportional, 不成比例的
, S/ q2 z h# `0 M6 ^/ |Disproportionate sub-class numbers, 不成比例次级组含量
% |) M$ E9 K+ w1 m C( V4 }Distribution free, 分布无关性/免分布/ e% d7 @! z3 I5 e
Distribution shape, 分布形状. c" Q* _/ d7 B& R$ F; I
Distribution-free method, 任意分布法
$ A; L! b; \$ q( s, ^Distributive laws, 分配律
$ g) C2 M' U8 G4 [1 p; D$ pDisturbance, 随机扰动项' c% c* }. X* I! f" M6 X
Dose response curve, 剂量反应曲线9 e% S$ q: u: \& _* `4 H% o
Double blind method, 双盲法0 v! c* ~$ f4 c/ a I% L
Double blind trial, 双盲试验3 ~ i' a$ `. ^9 J1 s; P
Double exponential distribution, 双指数分布
, y/ } Q: \9 E6 E6 K$ z9 S' ~Double logarithmic, 双对数' }* f( h2 n' q0 h9 h9 {
Downward rank, 降秩
: \- f9 O% B9 b+ o, a5 n* mDual-space plot, 对偶空间图+ n# P5 o! C5 L2 v( |$ {
DUD, 无导数方法: I7 H- t& S& q
Duncan's new multiple range method, 新复极差法/Duncan新法" O ]% l) v( Z2 a& c' Y
Effect, 实验效应
$ x. v' G8 e& ^+ ]$ N9 B" Z7 EEigenvalue, 特征值4 G6 T! h' c) O- B( K4 c
Eigenvector, 特征向量7 U! ^( C$ n/ j: Q* _. @
Ellipse, 椭圆
3 ?8 L+ ~4 W7 f! w5 sEmpirical distribution, 经验分布
3 d, q- \3 k" Z9 VEmpirical probability, 经验概率单位, r2 x5 H9 w4 R, K
Enumeration data, 计数资料0 [& C7 x+ l, P( K H, Q
Equal sun-class number, 相等次级组含量5 R# }) t9 ^5 t" B5 n/ {7 ]7 Q
Equally likely, 等可能 \- x5 X2 o$ E1 z. [
Equivariance, 同变性
2 q. c. a5 p4 p2 v) TError, 误差/错误, g' \1 F5 b6 { v
Error of estimate, 估计误差
" F, N) F+ V* W+ t) x4 C2 hError type I, 第一类错误
3 a# H5 a( T6 N* q7 b6 rError type II, 第二类错误' c/ {# S7 g+ N+ {: t
Estimand, 被估量5 B2 ~5 `2 F$ R9 H1 u1 W
Estimated error mean squares, 估计误差均方
; ^7 d z3 P& i: dEstimated error sum of squares, 估计误差平方和2 D* L+ j8 I" }; x$ r9 \, F
Euclidean distance, 欧式距离
, b" b+ }+ [: ^; D, P$ A. k5 XEvent, 事件' e0 [ J) r' C! L, x! C7 ^3 z7 I8 C
Event, 事件7 H6 k5 B+ U9 Y3 [
Exceptional data point, 异常数据点- d- O4 Z5 q( S* r' Z
Expectation plane, 期望平面
3 X3 }) J: ^! h: E# [* v+ d$ ]/ PExpectation surface, 期望曲面
+ X& @2 z) A& [# JExpected values, 期望值
! I7 N* ?! H. d, ]) R3 v. ~Experiment, 实验1 c1 u5 i. ]9 O" B" j+ `
Experimental sampling, 试验抽样
2 M" L4 M5 @. g* t- jExperimental unit, 试验单位
1 R6 b9 Y$ ~& g& y+ ~, e2 y( E/ y3 vExplanatory variable, 说明变量0 ^* W1 A7 d# j
Exploratory data analysis, 探索性数据分析
! ?' w, y7 j- yExplore Summarize, 探索-摘要8 N8 o% `3 J4 e0 @! X
Exponential curve, 指数曲线
7 Z) M; ^7 N1 a m3 A7 u* K3 RExponential growth, 指数式增长0 y; Z. b/ n, r3 o$ |4 G
EXSMOOTH, 指数平滑方法 5 ~: i" N% a, R% g6 s
Extended fit, 扩充拟合. a1 g$ Y. n# d( y5 E! W
Extra parameter, 附加参数1 x5 X% u* ~, V0 L* v
Extrapolation, 外推法
$ y( F9 `. b- H2 T6 \) I o7 nExtreme observation, 末端观测值
! W" A6 Z t" @2 HExtremes, 极端值/极值/ O2 V; C: o3 m9 A, @
F distribution, F分布" f/ n) v2 I9 C" i) e- \. C
F test, F检验& z- i5 Y/ C( e0 a" @2 T( c2 @) n. `4 a
Factor, 因素/因子
\& ^7 V7 s% m; P' b+ o* E! nFactor analysis, 因子分析: B8 d6 k) Y1 G! ?: A
Factor Analysis, 因子分析
: r1 c2 Q1 F5 lFactor score, 因子得分 ' {5 c, S4 `+ ~/ D) I
Factorial, 阶乘7 @& E) T' {. |$ `- ?% P3 l7 _
Factorial design, 析因试验设计8 k) g( t7 g- H, ?3 |
False negative, 假阴性3 g* T& L) K- ?
False negative error, 假阴性错误
9 b1 e% P/ s4 t- P% `# T$ xFamily of distributions, 分布族
5 ~5 D; j$ v# L5 eFamily of estimators, 估计量族
& B( E1 O9 N- d4 D" ?0 h% ]* SFanning, 扇面# q8 [( |. c1 }
Fatality rate, 病死率6 o. B* U1 v: C! c2 k* a; m& [
Field investigation, 现场调查
- t- T& ^8 L' xField survey, 现场调查
* O% Q2 x- z5 Q. J! DFinite population, 有限总体4 E/ p1 v/ o0 a# x, g+ Z: O" M4 `
Finite-sample, 有限样本
& j+ F- Y" M$ P/ |First derivative, 一阶导数
5 d5 @/ g" F: I; O. k6 n2 ]. aFirst principal component, 第一主成分6 W# O* L" ]8 s5 d/ b
First quartile, 第一四分位数: x+ l- J. r A5 u& R
Fisher information, 费雪信息量
0 m5 n h8 J0 z2 v$ @" D- ?, }Fitted value, 拟合值6 n- J7 G; M- Y; w
Fitting a curve, 曲线拟合
$ G2 w, q- k2 h; hFixed base, 定基2 D6 e) b8 X+ Z& }8 e7 S
Fluctuation, 随机起伏0 X/ J ]. B: ?% o5 I9 O( [0 B
Forecast, 预测
% o1 B$ ]8 Z- V6 ~. sFour fold table, 四格表
& d; L0 P5 e2 YFourth, 四分点3 N- B5 C) s, ^) P; t( G
Fraction blow, 左侧比率
& P1 r1 N- J5 J' \* `- X1 L3 Q1 UFractional error, 相对误差1 q# a$ G' \7 a% \* F
Frequency, 频率
, z% _) ^6 T U" K1 V$ G& B3 d E" WFrequency polygon, 频数多边图
7 E! T& R2 g* s* I8 m" QFrontier point, 界限点. m. a F4 x' Y7 ]
Function relationship, 泛函关系
# u2 ?+ A( z, l O: NGamma distribution, 伽玛分布# F% G' N& b; n. j. H/ ?: x
Gauss increment, 高斯增量, q3 m% @. \6 Z2 |
Gaussian distribution, 高斯分布/正态分布% X, x+ [. j: q. t
Gauss-Newton increment, 高斯-牛顿增量4 [: ^$ S: A' I) \$ L
General census, 全面普查
2 V+ R. g1 m0 |: G- Q) lGENLOG (Generalized liner models), 广义线性模型
5 }$ H: k' U* P6 IGeometric mean, 几何平均数
8 x, e5 Y$ r: e2 Z5 TGini's mean difference, 基尼均差
% N$ l W7 C" }- A/ A# k, n. e! U/ y% U0 iGLM (General liner models), 一般线性模型
- J5 M o+ o/ d5 h7 B, tGoodness of fit, 拟和优度/配合度
& |* L) u3 J" U) }+ r4 O/ k# I7 CGradient of determinant, 行列式的梯度
. x, R" W/ B1 H! P9 Z% z% eGraeco-Latin square, 希腊拉丁方8 D, N3 K1 \9 p5 ~1 ~
Grand mean, 总均值+ L% `+ K% ~) A$ x
Gross errors, 重大错误
% N ~8 o) r' n, k/ GGross-error sensitivity, 大错敏感度6 s4 b- F# l- [- J, C
Group averages, 分组平均
( N; l0 {- P: m+ A8 V6 ?5 Z! M+ ~Grouped data, 分组资料
3 O% z/ T: Z9 ^Guessed mean, 假定平均数
. d, q& M' s- e( rHalf-life, 半衰期9 \, r4 J% Q$ \; T+ c! w* s
Hampel M-estimators, 汉佩尔M估计量. }1 O9 Q1 d Q' s- `1 }
Happenstance, 偶然事件+ ]& h* t: I1 Q1 e3 M
Harmonic mean, 调和均数
. Q8 g3 i* J# T# I% r8 {Hazard function, 风险均数; _! r& @1 N: a& s9 p4 q
Hazard rate, 风险率' D6 V* q* f3 {( y
Heading, 标目 3 P$ U( B/ }6 X2 q
Heavy-tailed distribution, 重尾分布
7 E' f L1 x8 U' M2 I+ k% o# xHessian array, 海森立体阵
3 b+ [* ?- x {, X3 t5 QHeterogeneity, 不同质8 }* |2 i3 ?- p3 h& g5 ?9 W
Heterogeneity of variance, 方差不齐
6 p$ D7 i) X: A4 eHierarchical classification, 组内分组& ~1 K! c( S( J9 R1 N4 u
Hierarchical clustering method, 系统聚类法6 n9 H1 } @" v- N1 h0 B" W0 P- G
High-leverage point, 高杠杆率点/ m( `' B, E- _- h
HILOGLINEAR, 多维列联表的层次对数线性模型
" A1 S* {0 O* R4 o5 y; z8 |: \Hinge, 折叶点
Y+ n& x6 A. h* T1 ?: xHistogram, 直方图8 n2 V- U1 E% E2 S2 A) [
Historical cohort study, 历史性队列研究 * h k: Q) i. P4 f- V" y
Holes, 空洞
8 m% A# x$ F; Z. AHOMALS, 多重响应分析 L+ y0 X8 n7 J+ t8 e( H4 N) j2 J
Homogeneity of variance, 方差齐性" ^% e* C) Y2 W* s4 S, G
Homogeneity test, 齐性检验 |: K2 K% \/ Z7 D9 m5 @9 q
Huber M-estimators, 休伯M估计量3 R, {" o- @7 T4 V* a2 o7 D
Hyperbola, 双曲线
) I9 Y: S) H* ^+ QHypothesis testing, 假设检验6 {6 x: H& K3 l& q8 r* i
Hypothetical universe, 假设总体* s( g( ^6 ] [7 K& g* L M
Impossible event, 不可能事件# D2 t( r4 @# }9 q
Independence, 独立性
8 w6 c; z8 Z9 Q9 OIndependent variable, 自变量
5 U5 Z( ]5 w& [0 Q' ^6 H) F& ?Index, 指标/指数6 _3 a$ p2 o! ~7 O8 l, x$ P
Indirect standardization, 间接标准化法. n. A$ K# n- U
Individual, 个体
$ D3 T$ m. N" WInference band, 推断带7 i ^3 X( E0 `: `) Q" y
Infinite population, 无限总体
8 Y3 Q7 c; R- ]0 T* TInfinitely great, 无穷大
' e2 n8 u- i- }. V* U& R* f, _Infinitely small, 无穷小1 i7 p$ z( G8 ^
Influence curve, 影响曲线8 c8 ^ h) g8 p/ N% k
Information capacity, 信息容量8 D' C7 J1 h' O6 h" Y- W
Initial condition, 初始条件- o, S- K$ x5 P3 E Z" l
Initial estimate, 初始估计值
* Y, X7 Z. Q' fInitial level, 最初水平- ~: [# c# ~% r; o
Interaction, 交互作用* K9 ~' e2 g) R0 k) s! o! {
Interaction terms, 交互作用项' {" W% c7 p7 u% Q+ g) A( p7 P3 C( Q
Intercept, 截距& K) S' K- M7 O* \/ g. i7 U7 D
Interpolation, 内插法
* _7 d& X8 }% G! P/ FInterquartile range, 四分位距: g# a& j: v3 C5 b, s
Interval estimation, 区间估计$ Y! {8 b7 }$ ~5 g
Intervals of equal probability, 等概率区间, n7 H1 {3 A) k7 E6 d1 \ E$ W
Intrinsic curvature, 固有曲率4 j$ o. ^, v: D6 n
Invariance, 不变性3 d6 L/ o' A$ J: o# _; A# b2 W
Inverse matrix, 逆矩阵
% e7 \. Z y+ F6 ZInverse probability, 逆概率
5 O' h* u& u# F0 e# rInverse sine transformation, 反正弦变换
) [7 a# O( P* m0 @! `# ?( j, qIteration, 迭代 # k8 u% L5 S+ O7 R
Jacobian determinant, 雅可比行列式
2 {: X3 m" Z N0 G1 uJoint distribution function, 分布函数! e; ^% z( s# `7 p7 a0 N5 t
Joint probability, 联合概率" N N2 I, z# b
Joint probability distribution, 联合概率分布
. j8 ?( P) l! IK means method, 逐步聚类法
9 q# C! `, ]6 H6 l, jKaplan-Meier, 评估事件的时间长度
. y7 S% S5 `6 ~1 c' K! H* DKaplan-Merier chart, Kaplan-Merier图
/ f% A: x2 \2 l5 B' J1 [Kendall's rank correlation, Kendall等级相关( Z9 V8 @/ x# p) q" {( D
Kinetic, 动力学
7 K; M( h/ q* J' m/ yKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
; L/ q4 Y9 i- w; B7 IKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
6 q* a7 Y- p! u/ Z7 ^2 f5 z. ^+ uKurtosis, 峰度
; H: b% ^- q# J% _; a$ a% ALack of fit, 失拟; ^, k% r) u' k
Ladder of powers, 幂阶梯% e- L3 I2 J- u4 h
Lag, 滞后- a# I9 M' I: p, F
Large sample, 大样本! O! p6 Q$ M) W
Large sample test, 大样本检验
" `) w9 p* k4 i. yLatin square, 拉丁方1 F" P( u' } N" @
Latin square design, 拉丁方设计& @. a9 y+ E! S9 @) p
Leakage, 泄漏
9 o! n1 j, b" z+ @. T3 H a6 xLeast favorable configuration, 最不利构形5 W% A/ s- p2 k
Least favorable distribution, 最不利分布
: j2 g$ O1 B# n1 MLeast significant difference, 最小显著差法
$ R7 B/ Q' l4 R8 _Least square method, 最小二乘法
" D4 C5 p6 U4 KLeast-absolute-residuals estimates, 最小绝对残差估计
3 P: s- S5 w4 u9 a: ~Least-absolute-residuals fit, 最小绝对残差拟合
& A1 y: R8 g" X' m j4 ULeast-absolute-residuals line, 最小绝对残差线3 d$ q0 Q0 |% W: f
Legend, 图例2 p8 E2 T- B |# G- r
L-estimator, L估计量
7 j" m+ s( U8 t0 Q' K5 t3 NL-estimator of location, 位置L估计量& z; t. l. ]. z& e/ `7 S" ^' _8 ?
L-estimator of scale, 尺度L估计量8 q+ v4 s# e* C; }; L: r. r
Level, 水平; F% O5 `2 F' ?7 ]5 v
Life expectance, 预期期望寿命8 y' A h+ e+ N5 N
Life table, 寿命表1 n. W$ T; C6 ^
Life table method, 生命表法, i- r; V. N1 X4 T
Light-tailed distribution, 轻尾分布0 q# ~3 A' x0 \$ Q, y0 J
Likelihood function, 似然函数
/ r7 v; j7 t% R) O. U* A# H3 ALikelihood ratio, 似然比
$ R; W5 O1 n% u% rline graph, 线图' D8 _& K; C$ Z j8 B& v; T8 P
Linear correlation, 直线相关
3 a* l9 `8 `/ y0 {, bLinear equation, 线性方程, e- h7 m$ y7 k4 N$ m, Z. ]
Linear programming, 线性规划
& C8 D+ q; t+ ~* SLinear regression, 直线回归4 W/ i) X4 a6 x, c
Linear Regression, 线性回归
% t; O. r+ f J! J& j( ILinear trend, 线性趋势
* f* U; C: z( yLoading, 载荷 # t2 ^3 @, h; S
Location and scale equivariance, 位置尺度同变性# A, @; p+ b" }8 k, o& J
Location equivariance, 位置同变性
6 ~+ M4 d1 p2 t0 c7 h! B5 ]# m5 hLocation invariance, 位置不变性; v; p g* c$ ~4 b. O
Location scale family, 位置尺度族
+ \/ L; F* C+ \. @6 ^Log rank test, 时序检验 0 _$ V9 v2 ^! H' {
Logarithmic curve, 对数曲线- `! s1 W( R3 q9 z5 K) d
Logarithmic normal distribution, 对数正态分布
- g v4 _" K2 W" U/ A# H8 GLogarithmic scale, 对数尺度
1 A# |) _/ p/ g# r1 g* D1 [Logarithmic transformation, 对数变换
0 Z# i& R9 S( l* Q MLogic check, 逻辑检查2 A- {: K C* S' k/ {* B
Logistic distribution, 逻辑斯特分布& g0 Z, a# F2 F
Logit transformation, Logit转换- ^; D3 \! ~. H* [5 H c
LOGLINEAR, 多维列联表通用模型 ! Y) z, m' U7 a5 t* s C
Lognormal distribution, 对数正态分布. a; J6 Z" Z( j4 ~
Lost function, 损失函数; t" {! r( B. H$ k& Q% r1 r% S
Low correlation, 低度相关* i" R3 N% h, D) S# ^3 ]
Lower limit, 下限
, E3 E# S% G) _5 ~! }# W5 yLowest-attained variance, 最小可达方差
1 b7 a. a3 N1 ^& J' n. TLSD, 最小显著差法的简称
6 `( j1 [& ~' Q# C4 N; f+ I0 xLurking variable, 潜在变量
: e6 _' z9 f" G L$ PMain effect, 主效应' G1 {3 U! @0 p4 P9 ?! u# x/ F
Major heading, 主辞标目
9 ~6 `- o n( F3 N% rMarginal density function, 边缘密度函数
+ b- Z" S& B/ \1 n9 P& }Marginal probability, 边缘概率$ A: G4 F+ q9 a
Marginal probability distribution, 边缘概率分布- X8 R( b$ O a8 Z
Matched data, 配对资料
4 l& S# }. w3 Q# i- z; W/ {Matched distribution, 匹配过分布
' R( J2 u0 r0 _0 q! k! R- @Matching of distribution, 分布的匹配! o, q) r9 ^% D; Y* [- z
Matching of transformation, 变换的匹配
0 k3 \4 }, G7 t! x" oMathematical expectation, 数学期望8 o; q- ?: x" e
Mathematical model, 数学模型: F5 Q# m+ ]7 P+ G0 ]
Maximum L-estimator, 极大极小L 估计量3 ~; z3 ]) ~2 V
Maximum likelihood method, 最大似然法; ~! X; W; b! C
Mean, 均数
: |1 p$ f; e/ {+ ?Mean squares between groups, 组间均方2 Q. Z& E' K, k
Mean squares within group, 组内均方% X; L( x) O5 E% R: D$ u q
Means (Compare means), 均值-均值比较/ i, }# n" [4 {7 e5 N7 c# f# a
Median, 中位数0 ~6 Z4 a! I. v4 W- j2 ^' }
Median effective dose, 半数效量. s- m& K( N. I q
Median lethal dose, 半数致死量
& g- W' c) ~3 G0 @* ?1 ^) IMedian polish, 中位数平滑* |) S- I1 u+ n4 p C5 ]- U
Median test, 中位数检验3 }) B8 ?# ?, W" K
Minimal sufficient statistic, 最小充分统计量
, @( v. Y$ T/ a' HMinimum distance estimation, 最小距离估计: m' N* [+ p, R
Minimum effective dose, 最小有效量6 i; r" e# q3 b% ?' r* `" r
Minimum lethal dose, 最小致死量) R8 l5 W* V3 D; ]
Minimum variance estimator, 最小方差估计量" U3 `, N. g: X) g
MINITAB, 统计软件包- k" i0 d: S, b9 E5 @
Minor heading, 宾词标目! H7 y$ F; F, O! {9 z/ ?; f
Missing data, 缺失值( w" a2 e- v `4 V2 ]+ B
Model specification, 模型的确定. I+ K. g$ e( G, v3 h* t
Modeling Statistics , 模型统计: i3 p: n- n3 F: U
Models for outliers, 离群值模型
& ^1 G: a; n# [) xModifying the model, 模型的修正6 U3 ~! Y% Z: U: ?8 ]9 P; _- s
Modulus of continuity, 连续性模
/ U- b& G# R7 U! KMorbidity, 发病率
) n# k' y3 z) U- M- F+ nMost favorable configuration, 最有利构形
# A6 ~" Z4 M# C0 F' X3 fMultidimensional Scaling (ASCAL), 多维尺度/多维标度
+ ~) q4 `1 ]' k4 V0 e5 qMultinomial Logistic Regression , 多项逻辑斯蒂回归
: J! D5 e; \6 p. IMultiple comparison, 多重比较+ m: c, x: Y& B( M# c4 i
Multiple correlation , 复相关
, r4 ~6 b `1 y) i$ M( R8 GMultiple covariance, 多元协方差% R5 Q+ c) N% b& T) @
Multiple linear regression, 多元线性回归' H6 J3 U+ }" d# P; x
Multiple response , 多重选项
4 {0 j$ i, r# ^$ O1 b6 n4 eMultiple solutions, 多解. y6 ^7 A6 H5 n: q! }. F& ^" G' ~
Multiplication theorem, 乘法定理 k2 W7 r: q2 }0 E& @, p# n% l
Multiresponse, 多元响应/ q3 k% Y7 P7 D4 W
Multi-stage sampling, 多阶段抽样& n7 G" n( V# \5 o: R
Multivariate T distribution, 多元T分布
" z0 m$ b: c+ m5 _9 l' aMutual exclusive, 互不相容+ @. O" d! B" R4 j$ @" |. N
Mutual independence, 互相独立8 }1 J! h, k) |6 C& g
Natural boundary, 自然边界2 G) h+ H- I3 r; k7 o1 p6 r/ X' s
Natural dead, 自然死亡: W" f8 u" J! N1 s
Natural zero, 自然零
" x) ~+ c' r( `; t# [6 b' ?% D3 uNegative correlation, 负相关
' Z; E" B) j3 q: }1 p7 hNegative linear correlation, 负线性相关
' x, P- z% n$ k( e% P$ R) D6 F% FNegatively skewed, 负偏0 z6 r9 |7 C/ Y/ s
Newman-Keuls method, q检验
2 t: p$ _$ K2 g: H4 XNK method, q检验
- d0 L1 Q" a) L( iNo statistical significance, 无统计意义" |( m* N* {9 F1 B) d1 u6 r( M/ I
Nominal variable, 名义变量
* [ n) _9 q: x+ T% PNonconstancy of variability, 变异的非定常性& F. M: u |5 a* D2 u+ M. J, d1 D1 ~
Nonlinear regression, 非线性相关
8 T( I7 }+ ^# j/ @! _Nonparametric statistics, 非参数统计
' l; [0 f3 V7 L( qNonparametric test, 非参数检验$ k) _' S G6 N+ O% W0 A
Nonparametric tests, 非参数检验
9 z1 z8 b0 \+ RNormal deviate, 正态离差
) [0 o! ^: M! `' p/ ?Normal distribution, 正态分布
( K7 {$ K. l3 o8 x KNormal equation, 正规方程组# @% W4 i1 V- X C) [/ d
Normal ranges, 正常范围9 X; D/ ]! s+ d
Normal value, 正常值2 {2 D) ?5 h. j" M- s- n# w7 g9 d
Nuisance parameter, 多余参数/讨厌参数, N9 j/ \( z: X
Null hypothesis, 无效假设 . V c$ x6 D% Q# {( P8 g1 u2 r
Numerical variable, 数值变量
4 Y2 s/ [0 a8 T( P. aObjective function, 目标函数
8 t+ K$ s4 v9 e" I& k: I7 x. tObservation unit, 观察单位! m& u4 h2 e* q& S% Q. X0 @
Observed value, 观察值
' t0 J4 {: `7 t6 n) r: M7 _One sided test, 单侧检验
4 }/ i7 m8 U; TOne-way analysis of variance, 单因素方差分析
8 j$ ?1 O3 B! S" DOneway ANOVA , 单因素方差分析, V3 q. a0 i7 Z2 O5 ^
Open sequential trial, 开放型序贯设计; v+ ]! e8 S7 W% h3 b
Optrim, 优切尾
4 f9 r. a# f$ E6 i3 ~, c; AOptrim efficiency, 优切尾效率8 I9 I7 B* q9 y% B6 x
Order statistics, 顺序统计量
) n" n j: R' p* }( gOrdered categories, 有序分类4 B3 @, q& m2 `# Q8 I! b
Ordinal logistic regression , 序数逻辑斯蒂回归
1 N4 X' o, D" b& Y. z# FOrdinal variable, 有序变量% J" C8 E, \0 j6 _* L% k& Q
Orthogonal basis, 正交基1 b, |9 x) v, A, X- j
Orthogonal design, 正交试验设计
0 u/ u( ? O) p4 Z# ~Orthogonality conditions, 正交条件
# Q0 U1 ~8 E: q! ^ORTHOPLAN, 正交设计 $ m" O8 L5 U) ?! k$ A
Outlier cutoffs, 离群值截断点# k) i9 f( H/ e( B
Outliers, 极端值
& s, e1 j H D6 c, eOVERALS , 多组变量的非线性正规相关 5 j5 X* U1 i+ c
Overshoot, 迭代过度
9 `. \% W$ d5 J/ h) c8 J% x) HPaired design, 配对设计: q& S1 V$ N* F u% X- j, S* {
Paired sample, 配对样本
# S* c5 {) {5 w3 {# F# v2 q9 bPairwise slopes, 成对斜率
1 I7 e3 a u% G5 h3 x% d3 V; HParabola, 抛物线 _5 o& f2 p2 w: m6 c: ]- Q
Parallel tests, 平行试验
/ _' D6 G7 d- h. R4 T, yParameter, 参数4 ]* h+ x0 \, ]7 n+ R9 [ r* q
Parametric statistics, 参数统计
; I/ N; _4 ^2 @: W0 N9 A- _Parametric test, 参数检验
; ?% F' m q* h: GPartial correlation, 偏相关; {$ w9 d' R1 s( g1 n
Partial regression, 偏回归
2 j! u, ~; G( SPartial sorting, 偏排序4 K$ c. N& e2 ^$ c
Partials residuals, 偏残差
7 w1 x0 O' x3 t3 U KPattern, 模式9 g: T' Q6 m$ R) f! t, N
Pearson curves, 皮尔逊曲线* |. T% ~% n1 J2 @6 {! c+ W
Peeling, 退层& s# N7 S( n$ s1 y- n
Percent bar graph, 百分条形图
: g m# s2 v+ o. |! t+ G# w2 [+ bPercentage, 百分比" `; z7 B/ K5 e/ |! R
Percentile, 百分位数
0 Y5 c7 L' \0 P' `. OPercentile curves, 百分位曲线
% l5 P! l0 S9 I" j4 BPeriodicity, 周期性6 g( j% k D! }" s! \, l
Permutation, 排列5 j( g- }5 q% [# k8 g
P-estimator, P估计量
5 \4 Y' z2 g r7 D* N! hPie graph, 饼图2 t$ k/ u+ \3 ^% r
Pitman estimator, 皮特曼估计量1 l/ S, Y. q. u! H$ p
Pivot, 枢轴量- C: v' l0 Q' F. P# k; w% H6 Y
Planar, 平坦
: ^6 g i$ ]. M6 Q0 A, R) l0 w% ?Planar assumption, 平面的假设
. [8 s7 l1 _8 ^' XPLANCARDS, 生成试验的计划卡- i9 n# }9 [2 H+ }3 O
Point estimation, 点估计' G' A& |4 P/ h" z2 ~
Poisson distribution, 泊松分布; @6 l* ~4 _" w) M, P
Polishing, 平滑; R. T' J: y; C8 X
Polled standard deviation, 合并标准差, |2 I" L0 Y! `- E8 Q) L
Polled variance, 合并方差
' h% S- g* H5 h9 U# D) \" mPolygon, 多边图) N4 S$ ~6 m- F* V/ U! I
Polynomial, 多项式% v8 z; M3 B7 h; g1 u& X
Polynomial curve, 多项式曲线
2 C- o6 q7 Y3 a. z7 B* VPopulation, 总体
3 V# P5 g- h: |0 aPopulation attributable risk, 人群归因危险度$ B6 f- Y/ H9 {
Positive correlation, 正相关
/ a- D3 e) f, E0 S, @Positively skewed, 正偏
/ L" _6 U g4 `- Y2 n V; qPosterior distribution, 后验分布4 T8 t Z7 H! U
Power of a test, 检验效能0 Y, x+ d+ R0 k( ], i8 N& C* t
Precision, 精密度
2 }0 S Y0 U$ \' V, ?% ePredicted value, 预测值
; S" W* ?% U3 A$ E3 }7 b3 ZPreliminary analysis, 预备性分析
H8 Y/ {* b/ uPrincipal component analysis, 主成分分析
) {# O2 }0 N$ R1 GPrior distribution, 先验分布4 g: I; z5 d) a( H( g3 U
Prior probability, 先验概率
# l: s' v0 U) w& fProbabilistic model, 概率模型2 E2 @9 z0 t2 W. B" }3 h
probability, 概率
: k( [5 `4 u" _0 z3 @7 T! pProbability density, 概率密度
2 ^0 W r2 \5 n8 ~" `Product moment, 乘积矩/协方差
: N) [. r9 K0 m; nProfile trace, 截面迹图4 h- T# V& J8 B; i3 P5 n" n' F
Proportion, 比/构成比- y, D* @0 Q- k8 j7 Q' ~/ c1 B
Proportion allocation in stratified random sampling, 按比例分层随机抽样' S4 w) ?2 o6 \' {( y& X% |1 ~
Proportionate, 成比例
4 ?! J# l4 Z `9 uProportionate sub-class numbers, 成比例次级组含量/ H$ D" e; {( K2 q- M. l7 C
Prospective study, 前瞻性调查
/ f) I; l5 c4 ^) N' B' P" @5 IProximities, 亲近性 3 Q" S% C& ?2 Q' p
Pseudo F test, 近似F检验
9 ? X0 W1 [& E6 `9 |2 t5 MPseudo model, 近似模型! `' [: j! V8 W ~1 B) {
Pseudosigma, 伪标准差
- b' r4 S& S) K' P/ u8 C5 fPurposive sampling, 有目的抽样
* _2 D$ e- }. f- @QR decomposition, QR分解" D! O8 @1 q0 d6 J# A) t9 p$ P
Quadratic approximation, 二次近似
# B- K1 v! x) f. D/ QQualitative classification, 属性分类5 n H! F9 X9 W% v% \3 o' C
Qualitative method, 定性方法% L- ~. E) A! C- a( J
Quantile-quantile plot, 分位数-分位数图/Q-Q图
) O/ |$ `. S) v; T) Y2 pQuantitative analysis, 定量分析6 O- k" X2 u7 i6 b# Z; G% p
Quartile, 四分位数. [/ R+ \* D- l( I% f8 H/ F
Quick Cluster, 快速聚类
" P2 d7 o8 X. S! VRadix sort, 基数排序- ?; b9 B+ w/ g1 B
Random allocation, 随机化分组% x0 G' `, X& d% l; O
Random blocks design, 随机区组设计& ~' T" N( r) b* t
Random event, 随机事件
k! ?' f" I8 A1 c# VRandomization, 随机化: E* Q3 T7 ]( z) C6 M1 ?, K
Range, 极差/全距! Q* D3 C$ `! x
Rank correlation, 等级相关! p$ {6 | E3 F1 o. Q4 F
Rank sum test, 秩和检验
9 {2 p, p5 J4 i/ z' Q5 k! v0 pRank test, 秩检验
/ \! c, J5 `# u, ~* O+ ~Ranked data, 等级资料5 K' A) b; | ]& v$ k7 k
Rate, 比率
! W) z: B, }. HRatio, 比例; W2 j i0 s* K# L/ P2 h6 l: \
Raw data, 原始资料1 W$ D4 {0 z& ]5 V; P
Raw residual, 原始残差
7 R6 J* H9 e- e& M+ rRayleigh's test, 雷氏检验
4 i! R, U) ~+ S& `/ f- D& x8 b& w& _) IRayleigh's Z, 雷氏Z值
# f4 h' j, f% `7 yReciprocal, 倒数
# g3 b$ J' y, g8 VReciprocal transformation, 倒数变换
+ C/ ]8 R2 v' f$ O8 Q' FRecording, 记录0 T1 q# d4 C0 u: ]
Redescending estimators, 回降估计量' U0 ]* ?$ d! e2 g% n) o9 S
Reducing dimensions, 降维" P) j2 H: `' N# r+ s
Re-expression, 重新表达
2 {+ m+ X; g. }9 B8 O0 Z& x0 BReference set, 标准组
7 q/ M1 \4 `. k; pRegion of acceptance, 接受域
2 N [) S |: T7 x: [Regression coefficient, 回归系数
/ G+ X+ W. c7 t# s) O/ mRegression sum of square, 回归平方和
* z# Z, ^3 h/ m3 N& HRejection point, 拒绝点) e, ~' n; N9 W8 N$ s
Relative dispersion, 相对离散度
. J7 A) i# |% q( o' F, [" NRelative number, 相对数1 S2 U: I/ w$ x% a# O) r3 D
Reliability, 可靠性
1 `, R( b) g1 g; K+ tReparametrization, 重新设置参数. y' d9 u3 f8 z2 }
Replication, 重复% e+ ~$ Z# t% m& Y& o
Report Summaries, 报告摘要5 Q1 h4 G6 h3 | N0 t
Residual sum of square, 剩余平方和
0 `8 W4 E( {0 o+ F8 Q. ^' b# i) yResistance, 耐抗性+ m4 q/ s' B( f; d6 `% v6 v( v
Resistant line, 耐抗线
, m+ K# {' _5 ^; j8 D! L6 x0 Q. ?Resistant technique, 耐抗技术( ?6 N' @5 E$ |5 t P. j* [9 M( ?! P1 J. K
R-estimator of location, 位置R估计量
" ]7 Q( Y0 X0 B; S9 KR-estimator of scale, 尺度R估计量
4 f& M, b" n% k" jRetrospective study, 回顾性调查/ A! c. M6 Y5 f" N
Ridge trace, 岭迹1 Z7 _9 R0 y4 _2 ?
Ridit analysis, Ridit分析& c0 u/ o3 k O2 ?) W
Rotation, 旋转
# n4 N* i3 r4 sRounding, 舍入
~$ \( V$ U4 ?: X! H- HRow, 行
7 d5 U! u: d* {) ~+ [ _Row effects, 行效应
* J6 Y; w- ]/ N1 k- NRow factor, 行因素
0 y! {9 ~# P2 o" q: gRXC table, RXC表 [ h. z7 l1 g" T5 s
Sample, 样本, ~' i/ g, [* C7 z
Sample regression coefficient, 样本回归系数
+ g [/ w2 {" h: h" N; S3 @) |Sample size, 样本量! f1 m% l% f& h: H$ |+ v
Sample standard deviation, 样本标准差
; _& X9 n, t7 w: m# X5 u, e2 k+ nSampling error, 抽样误差
+ R7 |4 O3 _8 D2 e4 cSAS(Statistical analysis system ), SAS统计软件包5 H7 v* c! w) ~5 w; x& D
Scale, 尺度/量表
: E" K0 v; r8 w/ EScatter diagram, 散点图4 P. X. _( ~8 a' E: k( w
Schematic plot, 示意图/简图# v+ Z" z/ ? h1 M
Score test, 计分检验 I" S% r' x; G. d ]) ^
Screening, 筛检
$ t; ~1 u1 B: J1 x; g! J. j0 s5 h+ KSEASON, 季节分析 ( p; y8 Z+ Z# e; H0 n# m
Second derivative, 二阶导数& X8 ?5 ~6 {! R: b
Second principal component, 第二主成分8 J7 N$ U' n8 N! P( _' }2 [
SEM (Structural equation modeling), 结构化方程模型 - H7 x( W0 f! g. W. A) I( I' V$ M# M
Semi-logarithmic graph, 半对数图
2 {# |; h: ^4 `5 r D# bSemi-logarithmic paper, 半对数格纸6 _! G! [% s+ |& J( `
Sensitivity curve, 敏感度曲线. T% i' B0 c7 j# \# N
Sequential analysis, 贯序分析6 ~% F5 \9 ]# U; g$ R: m
Sequential data set, 顺序数据集
: w0 L0 Y7 F5 {7 b' ]2 XSequential design, 贯序设计
1 K/ `2 b2 s8 `4 y) F( r0 JSequential method, 贯序法" p0 M1 A6 Y/ w7 \
Sequential test, 贯序检验法
* ^% g% j' V, a4 J" m% gSerial tests, 系列试验1 d6 f& m' i; c. N# \* j9 y! J. f
Short-cut method, 简捷法
* e9 |- x7 |+ }9 {$ N. ASigmoid curve, S形曲线' J! ?0 `# D! p- p. w3 |# [9 C# m
Sign function, 正负号函数
, E3 B7 k0 A' X5 S% a$ g/ tSign test, 符号检验
- j; ]* c+ T! a! D: PSigned rank, 符号秩
9 ~9 W% i( E$ H0 j5 i* R+ OSignificance test, 显著性检验$ R" k% \$ D/ F$ h |# H. h
Significant figure, 有效数字
/ e- }7 m* g3 {, r. |( n5 y7 ]Simple cluster sampling, 简单整群抽样; m& W6 r6 s; d$ p ], d. z
Simple correlation, 简单相关
# g9 d7 \1 x6 s! i3 k' G7 _Simple random sampling, 简单随机抽样" r4 ^+ R6 F6 K$ Z& N! C
Simple regression, 简单回归
6 q: i4 y' A% w" vsimple table, 简单表
- }; x& }; U* j5 d x5 D+ YSine estimator, 正弦估计量
4 N) X0 g6 v( A$ O/ Z& VSingle-valued estimate, 单值估计1 z* z/ e5 }! ]/ I) W( |; O
Singular matrix, 奇异矩阵; b" @/ p! K# ?4 _- I
Skewed distribution, 偏斜分布
5 f- c# F3 h( j0 z& [! _Skewness, 偏度' S' K% A7 E. j
Slash distribution, 斜线分布* j1 i: i4 s0 U% \# \
Slope, 斜率
) f. I" l4 U6 E$ {9 U7 I: RSmirnov test, 斯米尔诺夫检验: ?' A8 C- }9 }) v0 `& X
Source of variation, 变异来源. |) a1 V8 a5 t1 F
Spearman rank correlation, 斯皮尔曼等级相关
6 o+ \ M ~% |- ]5 ]8 fSpecific factor, 特殊因子
: J* X' F8 M4 m# {9 @/ `2 bSpecific factor variance, 特殊因子方差
2 q/ ~: Z- \8 f ^Spectra , 频谱
1 B. _9 J! U* G! Q. s: ~5 oSpherical distribution, 球型正态分布- @# d6 ]! |; v3 l4 O6 K3 B2 C8 | y% S
Spread, 展布
% d- ^6 D- T8 x& y- ]) D$ KSPSS(Statistical package for the social science), SPSS统计软件包- m* M. B7 A: m
Spurious correlation, 假性相关
1 Z \, L! Z7 ?) P) |; XSquare root transformation, 平方根变换. a9 \0 g4 ?$ |1 o( |/ Z
Stabilizing variance, 稳定方差
6 d- C {- J7 o# c+ s6 N7 |0 VStandard deviation, 标准差( r& Y2 { ]) x
Standard error, 标准误, t3 U9 t$ d# r" O, S! r. J
Standard error of difference, 差别的标准误
( O+ A( {0 k& T2 @4 V. c, jStandard error of estimate, 标准估计误差5 f! x; s. j/ e
Standard error of rate, 率的标准误* H( M9 t# ^" X
Standard normal distribution, 标准正态分布
+ \6 K* M/ g! j; [" z8 nStandardization, 标准化) A+ J' j# [ J
Starting value, 起始值1 V! j2 Q" @* H& O
Statistic, 统计量6 f# V2 V6 c0 A: n5 R' H. [% g" e
Statistical control, 统计控制
2 v! f+ G" E# z( Z XStatistical graph, 统计图
0 c2 N: ~, [) c& [Statistical inference, 统计推断
% W5 ?, i+ O: QStatistical table, 统计表
$ @4 d9 d. K5 X; Q5 n) c+ {Steepest descent, 最速下降法
, p, g) M$ ?7 V. R' ^( _Stem and leaf display, 茎叶图
2 l6 i- O0 l5 Y' qStep factor, 步长因子
. v) Z2 w2 s5 B5 bStepwise regression, 逐步回归$ a( \, d4 ]0 g6 W9 {4 ^
Storage, 存
* [( o0 Y1 `" P9 pStrata, 层（复数）
7 W, n& Y& D4 C, RStratified sampling, 分层抽样6 ^6 ^1 b) s+ J; ^5 P
Stratified sampling, 分层抽样
0 M5 `$ P; Y( \" _8 Y6 S" @Strength, 强度' d: N9 y, t8 _1 R
Stringency, 严密性) H* O8 `' C% G( v# e0 q
Structural relationship, 结构关系
0 c+ X# {* S1 B* FStudentized residual, 学生化残差/t化残差3 }* m s6 z. ^! L" P8 q3 L
Sub-class numbers, 次级组含量6 _4 y* ]" Z* X# W
Subdividing, 分割- G4 P% \0 U) g% q( ?. G1 C8 x; s
Sufficient statistic, 充分统计量
6 [2 x: V6 ?. G; ^7 P' QSum of products, 积和- ?! s. g! \( e; {4 K
Sum of squares, 离差平方和2 H6 P! k3 R" R2 C
Sum of squares about regression, 回归平方和
' `! r1 p2 t* ~/ ^: {* z9 wSum of squares between groups, 组间平方和; _ [" [8 n6 m6 I
Sum of squares of partial regression, 偏回归平方和
; z& l% M0 l7 A( P) Y$ F+ P! j# x% CSure event, 必然事件
b0 o; B6 O& k& z+ U" GSurvey, 调查% q& W8 n8 q* d4 i! z2 D
Survival, 生存分析
& q( O/ q6 P* D. S/ I( R; sSurvival rate, 生存率: S9 U3 i* C" u2 Q; [
Suspended root gram, 悬吊根图! c9 d2 q# ^6 W+ R ?
Symmetry, 对称6 P9 Q0 K7 Y/ p$ c+ C" B- m2 ~
Systematic error, 系统误差
3 ~3 n0 V" [) K3 [4 rSystematic sampling, 系统抽样
/ W4 B0 b' X N1 c1 X2 r: hTags, 标签9 x& c4 w# Y" z
Tail area, 尾部面积4 g2 v! ]# \; P# n2 ?! `
Tail length, 尾长
7 h x7 d& ]; V3 J/ [" L& GTail weight, 尾重
% k: f1 s& v0 |7 A$ STangent line, 切线7 u) S3 H& i$ U Q3 P2 B, T, D
Target distribution, 目标分布
u% p, P; f9 @' q% p9 KTaylor series, 泰勒级数! V. i& h7 w( `6 x/ @
Tendency of dispersion, 离散趋势, v, v9 C9 A& Z
Testing of hypotheses, 假设检验
2 ~/ F( S& U: K1 l ~Theoretical frequency, 理论频数+ f4 N1 m4 D; Y) Y8 A
Time series, 时间序列2 G7 t& [# W5 d/ A0 b
Tolerance interval, 容忍区间2 j6 `& a K( ]9 R& ~- n F) i! Y
Tolerance lower limit, 容忍下限5 i$ o( N' S; ^- T1 i- ?
Tolerance upper limit, 容忍上限5 s8 J7 h" W5 \; ]' b0 Q/ |
Torsion, 扰率+ O. Y3 e! g2 W$ b! M2 e4 Z J; [
Total sum of square, 总平方和- y. X) o* C, }) `7 i0 ]
Total variation, 总变异: q; |+ N# U+ z6 t
Transformation, 转换* a8 k' |4 c8 |! g' M) U4 Y" t/ B
Treatment, 处理
- @' G9 q7 v$ C& W9 G5 f) P9 uTrend, 趋势
% T* s, K) Y( d cTrend of percentage, 百分比趋势
0 e' K" M N- s0 {% eTrial, 试验
( C3 G) E# f0 Y' Q0 Y" W3 {Trial and error method, 试错法
1 `) {+ i( y# |5 O! V7 lTuning constant, 细调常数+ _( k8 \& ?9 E1 U2 [2 s/ k( f
Two sided test, 双向检验# Q7 k/ p _9 @
Two-stage least squares, 二阶最小平方" Q8 U- ~. ~$ R: m; ^; R0 i' I- A8 L
Two-stage sampling, 二阶段抽样+ U0 ?7 k q2 n9 c, A
Two-tailed test, 双侧检验1 D: X/ K8 k5 d8 D# l1 |' Z+ t
Two-way analysis of variance, 双因素方差分析6 C1 z4 z8 z/ |& j
Two-way table, 双向表
- E9 A5 A6 s9 e0 E6 n. _: g0 SType I error, 一类错误/α错误+ H( N1 n1 _5 T, S
Type II error, 二类错误/β错误
0 j# h: J4 {: n& nUMVU, 方差一致最小无偏估计简称( H+ Y0 ]: d* e6 ]
Unbiased estimate, 无偏估计- C& m, G( h6 W8 g X+ {1 S
Unconstrained nonlinear regression , 无约束非线性回归
9 D6 `: C% U1 b* K8 X7 h# aUnequal subclass number, 不等次级组含量
# B" K2 n, { T7 e0 I& SUngrouped data, 不分组资料
' l# t1 i: `' r( ^7 I! M! |Uniform coordinate, 均匀坐标7 T) K1 _* y, n
Uniform distribution, 均匀分布9 T' s% H8 \! _- c
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
4 ~, X, U# T. D$ fUnit, 单元% Z f" A9 X1 @
Unordered categories, 无序分类
& \' S8 S$ M& Z& C% fUpper limit, 上限. U) S$ K+ E) F( n8 M' l
Upward rank, 升秩: Q' |" W: Y* W4 |- u' T7 ]0 o
Vague concept, 模糊概念# P( L: l" T# ~/ H: [ @( W9 J( @
Validity, 有效性
1 m& A2 I- L D& M* AVARCOMP (Variance component estimation), 方差元素估计
n3 g( K7 |& K' K1 q) M" }Variability, 变异性
; H7 V* V, [+ W9 tVariable, 变量/ V( B) m: H0 X' e+ ^7 ]+ [
Variance, 方差
- d4 E5 O) L8 h/ QVariation, 变异
% M- {4 Y5 K. D9 |! |$ n9 jVarimax orthogonal rotation, 方差最大正交旋转/ v! n0 R* U* S6 [# N+ |' {
Volume of distribution, 容积
% p' Y; ~1 F/ B' iW test, W检验
/ T& w2 R8 x r s- F2 m# h6 [Weibull distribution, 威布尔分布
9 b3 l1 A! K# V( XWeight, 权数
2 k: c( l5 n( n% W! B( k+ e: QWeighted Chi-square test, 加权卡方检验/Cochran检验1 |3 O# s: W* \- \7 j+ |; U4 I" \
Weighted linear regression method, 加权直线回归* e/ D# h$ i7 G4 v3 ^
Weighted mean, 加权平均数) U" z! v }" x( w. n% O8 H( b
Weighted mean square, 加权平均方差
' J0 _" h2 N t6 ]7 t5 u9 c4 j1 wWeighted sum of square, 加权平方和
$ K7 @1 w$ N9 M( D' N7 n4 OWeighting coefficient, 权重系数' |: E& h/ q' u Z( P( P
Weighting method, 加权法 " w& `: O2 g& N* l7 A
W-estimation, W估计量9 p: E$ ]) H g' I( q8 H: v- e" t
W-estimation of location, 位置W估计量/ S) H$ s) [( F: }$ }: x$ N3 N- k
Width, 宽度
V% z [( J! O: Q1 J% MWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
5 Y& @1 E8 u7 c4 J. H5 dWild point, 野点/狂点# }" O% N) z6 i
Wild value, 野值/狂值
- K X. i5 e( pWinsorized mean, 缩尾均值
& n; U; [6 f- d% e7 ]7 MWithdraw, 失访
# A) T2 b" F& b( gYouden's index, 尤登指数
5 K9 \) `2 m' |7 s+ _Z test, Z检验6 o/ m" t' ]& s
Zero correlation, 零相关: ?+ b2 w+ X5 h S* F* G
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
