|
|
Absolute deviation, 绝对离差
. R& t5 T5 e. f6 fAbsolute number, 绝对数
! G% b5 b+ W+ a; XAbsolute residuals, 绝对残差 Q7 v, S' X' R2 t- R H
Acceleration array, 加速度立体阵
2 T( o( N$ i7 YAcceleration in an arbitrary direction, 任意方向上的加速度
/ ?9 q4 S. f9 K. w) U. y! T5 v7 PAcceleration normal, 法向加速度
7 h8 S& X8 u- Z& U5 w4 t; fAcceleration space dimension, 加速度空间的维数
|: U& K9 f7 X9 h% w9 sAcceleration tangential, 切向加速度: F1 ~7 w' O6 [- W% a, ~9 K D: O
Acceleration vector, 加速度向量3 l! \6 P9 d& ~0 b8 i. N6 R5 O
Acceptable hypothesis, 可接受假设% U# s% W2 E+ ~ E- X
Accumulation, 累积( t$ d, n- p& P# t, M7 ]- Y, Q; p7 C9 G
Accuracy, 准确度 I0 L" I7 z. Q, w4 C) b
Actual frequency, 实际频数3 \8 o& G* J9 B; Y) U9 _
Adaptive estimator, 自适应估计量
7 _: |, G! s, k+ C1 h0 SAddition, 相加+ u: j/ ?) t* i. [+ s
Addition theorem, 加法定理$ N) K& }" j t3 ], P
Additivity, 可加性8 ^ q1 d5 W- a. I, J6 {4 {5 M' ^
Adjusted rate, 调整率
1 g ?2 e0 C, h4 v# j6 j3 aAdjusted value, 校正值2 c8 e8 P1 U6 X8 | c" G( h
Admissible error, 容许误差7 q$ x% M" C. B. e. u" `
Aggregation, 聚集性
2 L5 c6 ?1 Q; cAlternative hypothesis, 备择假设
, D2 A# k, N2 c" |Among groups, 组间
. ~! s0 _& o: {* r' l* ^+ [. E& AAmounts, 总量$ e. B& E4 J' J% I' |& {
Analysis of correlation, 相关分析1 G( O2 n8 F B
Analysis of covariance, 协方差分析5 ]# r4 c4 ]1 A# D# ]! |
Analysis of regression, 回归分析 D) m i5 u- ^3 e
Analysis of time series, 时间序列分析
5 J, J# H( l5 t& r( `* w' N9 FAnalysis of variance, 方差分析7 H- j, ]+ D* M: z: l1 D3 e
Angular transformation, 角转换
) N0 Y; W! _) T: TANOVA （analysis of variance）, 方差分析, _! i! Y( N. C! h, P0 Z
ANOVA Models, 方差分析模型
/ I, a) u1 ~$ U4 ~Arcing, 弧/弧旋5 l+ p- H+ f7 _3 V
Arcsine transformation, 反正弦变换5 o0 {# }7 q3 M' h! j5 ]! A
Area under the curve, 曲线面积% v) U4 U. S9 z$ m/ @; J5 F0 B
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
- c0 Q; g- b5 `$ A% _1 a) p, xARIMA, 季节和非季节性单变量模型的极大似然估计
. c* t( y1 ?+ G" f: Z0 zArithmetic grid paper, 算术格纸# V) u$ Y+ _; p8 U' p5 _: R
Arithmetic mean, 算术平均数. D1 l# y: c& S0 }* g
Arrhenius relation, 艾恩尼斯关系8 L* l2 r: ~ q/ w4 a; j. x$ o
Assessing fit, 拟合的评估" Y( X0 V: p- x6 Q7 A t' j
Associative laws, 结合律
# R% M6 P3 t4 W, g; H5 BAsymmetric distribution, 非对称分布
7 P6 b& B, }1 l+ ]Asymptotic bias, 渐近偏倚; T' c/ b& r1 _, x7 h. p% D
Asymptotic efficiency, 渐近效率
4 b" N# S- ~, i) M& W1 r3 \Asymptotic variance, 渐近方差
( G1 E: q: @9 h( k9 m5 kAttributable risk, 归因危险度
, g$ @- x) h; r9 |Attribute data, 属性资料
- o8 G- U2 T+ A% N7 x. C1 mAttribution, 属性
! [! l- n5 l u6 \2 L( q0 SAutocorrelation, 自相关3 N; Y* i/ Z6 o- }1 Q
Autocorrelation of residuals, 残差的自相关
9 v( \7 C8 V! t& c+ [+ a4 W' g" [Average, 平均数) \2 M4 N9 f `" ~6 T/ j
Average confidence interval length, 平均置信区间长度: {4 s3 c; M p5 l; j
Average growth rate, 平均增长率" E+ }# z1 q- B1 E& |' B3 W0 [ ]7 e
Bar chart, 条形图% `9 H I4 n/ s( Y8 j4 u
Bar graph, 条形图6 }' D: Z: W5 r% P5 B! E$ p
Base period, 基期/ [: \( k6 f" i8 z, t
Bayes' theorem , Bayes定理
z+ l) J7 j! V- S1 }: N- MBell-shaped curve, 钟形曲线
% g3 Y, x* C* @2 ^2 eBernoulli distribution, 伯努力分布
. @& b) j- g4 tBest-trim estimator, 最好切尾估计量$ J. {# s6 z& M( {& l4 o4 W0 z" P
Bias, 偏性
6 E% \/ P6 ~) u. {1 F9 j. W3 OBinary logistic regression, 二元逻辑斯蒂回归
) p: [( Y+ O2 n' M: FBinomial distribution, 二项分布7 ] O8 ]" u/ B' `4 p
Bisquare, 双平方
5 J+ \+ {% f8 k& }3 X8 n" cBivariate Correlate, 二变量相关
9 c& H% Q; ^/ d5 X4 F) lBivariate normal distribution, 双变量正态分布
# C3 l5 ~3 ]; s1 ^$ X0 E1 K7 x0 C7 IBivariate normal population, 双变量正态总体
. T$ _& ]. l: _6 CBiweight interval, 双权区间
/ f( S4 f) G& a& [0 u ^% u: i6 A) e YBiweight M-estimator, 双权M估计量
3 j o; \ C k$ X0 ^( eBlock, 区组/配伍组# v( A: S. }8 M$ ]
BMDP(Biomedical computer programs), BMDP统计软件包
) N$ p3 J x# nBoxplots, 箱线图/箱尾图6 ?* Q F) B- h
Breakdown bound, 崩溃界/崩溃点
- a# k: }. j% C$ t4 d( FCanonical correlation, 典型相关; V$ S) Z3 e8 o
Caption, 纵标目
4 y1 j. E: x* e" T3 ICase-control study, 病例对照研究
, ~! i( f9 F' s" T8 |# N9 @Categorical variable, 分类变量( Q& f: J, a8 T# X
Catenary, 悬链线
# Y9 i% O* Q3 J4 hCauchy distribution, 柯西分布* e7 H3 U4 [) D$ W" }2 H/ |
Cause-and-effect relationship, 因果关系
9 j) R0 s" F# m ?/ s% iCell, 单元
1 r5 u4 ?0 W+ L9 lCensoring, 终检
4 y& Y- }7 g6 J$ E9 OCenter of symmetry, 对称中心! V6 ?0 L3 s" |0 n8 e/ \ M
Centering and scaling, 中心化和定标; z I: z4 u- F* A) e- S8 s
Central tendency, 集中趋势
1 @' [7 Y/ `( x0 nCentral value, 中心值
3 P9 s8 b% A3 X1 W+ q0 ~* F8 Q1 K, aCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
/ c+ C% m- E; d4 n$ K/ UChance, 机遇( L2 I3 L9 r% o/ L1 [
Chance error, 随机误差& w, f& e8 Z* h* J2 O
Chance variable, 随机变量
. ^8 E3 ^ p# gCharacteristic equation, 特征方程
: Q7 \/ z2 d* gCharacteristic root, 特征根2 d/ ?0 t* H" h: j
Characteristic vector, 特征向量- P) B% [( G3 m. z# N+ p" X, U
Chebshev criterion of fit, 拟合的切比雪夫准则" Z4 i) w1 R) U: O/ ?# X* h0 l
Chernoff faces, 切尔诺夫脸谱图! n# ]: k) J j2 A: P# }
Chi-square test, 卡方检验/χ2检验" t6 w" ^7 n$ U7 x7 x. d& K
Choleskey decomposition, 乔洛斯基分解
8 P, u' Q: s0 X% ECircle chart, 圆图 8 P0 j$ b1 Q2 u' X3 [% p' P$ m1 o* z
Class interval, 组距3 i: [/ P2 n: Y
Class mid-value, 组中值
5 @0 I/ [* G, d. Y4 JClass upper limit, 组上限
( o/ W0 G/ z% H3 cClassified variable, 分类变量
, m' d3 P% ?8 m" ^) q rCluster analysis, 聚类分析9 m9 ~6 ~) F$ E' Q: A
Cluster sampling, 整群抽样
3 m5 W, Y# X1 Q# l0 n' TCode, 代码3 `* [, y+ v! M+ M3 ~
Coded data, 编码数据) T2 D& x$ m% m' g/ Q
Coding, 编码2 [6 I1 v. A: y6 Z1 H6 g
Coefficient of contingency, 列联系数4 F8 R, I/ ]! {3 R9 P
Coefficient of determination, 决定系数6 V" ~1 R' X% W8 K9 B
Coefficient of multiple correlation, 多重相关系数$ {1 Y. r: t) Y# g/ J. w
Coefficient of partial correlation, 偏相关系数
5 s9 L% P0 E. y, n& e5 m+ wCoefficient of production-moment correlation, 积差相关系数
; z* w6 N, Z& ZCoefficient of rank correlation, 等级相关系数3 N& J' F! _5 S ?( Q6 u& z$ d
Coefficient of regression, 回归系数
- o3 J p; t7 ?5 r9 HCoefficient of skewness, 偏度系数
% a+ a* V1 `- p$ g) \; g1 NCoefficient of variation, 变异系数' [0 T y+ s8 Y: _, V) Z- F! } k
Cohort study, 队列研究# {8 }# c5 j0 ~4 E
Column, 列7 W, p- _0 e" J
Column effect, 列效应
( _6 p' ~' U3 B, d( o$ GColumn factor, 列因素
2 j9 e& `* k3 @% x7 X- LCombination pool, 合并
c! f/ s2 e+ C6 F& GCombinative table, 组合表
6 @( C0 H! b4 X* _Common factor, 共性因子
0 w; V, \7 ~3 `5 J6 K* c5 _! dCommon regression coefficient, 公共回归系数
2 S, ? h8 k& t+ nCommon value, 共同值 B& ]0 o0 F( |3 y
Common variance, 公共方差
+ ^* z, z( i+ Z8 {: N& I# `: o4 MCommon variation, 公共变异
, m: b8 X$ A% ?0 o7 k! wCommunality variance, 共性方差5 f% H! F5 Z" U0 D
Comparability, 可比性) B- x! O0 ~" O* V
Comparison of bathes, 批比较8 z- E! o9 }! y1 [; }
Comparison value, 比较值
3 m" L" s7 B& S; P3 ]- zCompartment model, 分部模型
, O7 J; R* z) g! nCompassion, 伸缩4 l- f& }# z2 T, X; f! {$ N
Complement of an event, 补事件
' C* T! n6 J7 ?- W" X* @Complete association, 完全正相关& b9 m b( m3 W2 w" T v" S
Complete dissociation, 完全不相关
9 j7 @ B4 r1 X: jComplete statistics, 完备统计量+ Y' T) H9 C5 X
Completely randomized design, 完全随机化设计
* y* F' Y" e* Y ]7 \, C5 M) AComposite event, 联合事件. h# y, @1 E. W, _
Composite events, 复合事件
9 A5 ~6 [. H0 C3 D: Q$ Q" y. cConcavity, 凹性
! m% L! Y9 `! N; R# @# _) O Y! QConditional expectation, 条件期望
& R: Q4 U a- J# [5 AConditional likelihood, 条件似然
- }% V! O& R& aConditional probability, 条件概率2 i- s! J6 @0 v, D* d4 n
Conditionally linear, 依条件线性1 H- C) o( S5 v* p
Confidence interval, 置信区间
4 O+ N: W9 r8 u9 f/ A6 GConfidence limit, 置信限
* b3 G, u+ K* C) _( J! B9 d9 O, ^. PConfidence lower limit, 置信下限
- |1 x! k- ]4 o6 ?# TConfidence upper limit, 置信上限( S0 z. u! }# Z( N. V4 ^7 i
Confirmatory Factor Analysis , 验证性因子分析
* h2 Y$ J. h! F4 bConfirmatory research, 证实性实验研究8 o! R8 p3 L# U) k8 d
Confounding factor, 混杂因素
3 _% w/ x0 D o& W# {Conjoint, 联合分析: X. ^" Z. S! [+ e# @
Consistency, 相合性
8 ], B, [1 y% L; E2 g* MConsistency check, 一致性检验
8 q d& E, L+ Y9 E6 D: T: ^Consistent asymptotically normal estimate, 相合渐近正态估计" W% m" J& L; U9 J7 P! p; n3 u3 _" ^
Consistent estimate, 相合估计( o( O, ^& E5 I, F+ y5 L
Constrained nonlinear regression, 受约束非线性回归1 `; v( ^! G% U: g) M
Constraint, 约束
* Z( B- L% A; U E, Z! b8 yContaminated distribution, 污染分布" m0 o* T' B7 m
Contaminated Gausssian, 污染高斯分布
% b2 o N3 u+ {5 `6 P; F# G; f PContaminated normal distribution, 污染正态分布
4 y% e9 _8 h# J" n- @Contamination, 污染
7 I" y, S, t3 O- R, l# ^Contamination model, 污染模型& j5 @3 h. J1 S, T" P( I. }7 p, ]% \
Contingency table, 列联表6 ^) M) {0 w1 B a+ j
Contour, 边界线
. F5 E5 Z/ e& K1 L3 ]* A, h7 EContribution rate, 贡献率
) Q+ m, @5 Q0 V8 }* q2 rControl, 对照2 v* b! R0 j/ p5 c. m$ U/ I
Controlled experiments, 对照实验$ R! ~6 g8 w5 @. {3 n r
Conventional depth, 常规深度" c+ c; r; L9 F
Convolution, 卷积5 B- D) |# g/ O7 U4 s/ h. \
Corrected factor, 校正因子/ _: D& _* P7 c. B1 }3 \
Corrected mean, 校正均值; A7 _1 B3 o/ e \- {
Correction coefficient, 校正系数2 w2 E! S7 Y( f% N; @
Correctness, 正确性
+ \& i- f: R! \$ X& J2 h& s1 tCorrelation coefficient, 相关系数
) C" n: c4 j7 C: b/ c7 F. @Correlation index, 相关指数4 W" H$ I0 |" ]1 W( g; u7 X
Correspondence, 对应
) \, w# L. O, B2 ?# SCounting, 计数
# n0 H2 o4 U. N7 Q+ Y v; Q( a3 rCounts, 计数/频数
8 ^) @$ B) T8 F4 S, C& ICovariance, 协方差& `$ W% i K7 Y
Covariant, 共变
2 v( V F! e2 Q6 Z8 l$ j; yCox Regression, Cox回归: U- V8 \1 o1 z) j, c ]) p9 a& Y
Criteria for fitting, 拟合准则
8 V8 u( C: E8 x0 d6 BCriteria of least squares, 最小二乘准则) ?. s6 Y( V' P+ R' e. [* U! ^
Critical ratio, 临界比8 h @. U8 X. I8 T# P; v, \+ z, n
Critical region, 拒绝域
9 B x& j$ H/ g" t: gCritical value, 临界值+ I6 f9 O0 g. g$ j
Cross-over design, 交叉设计
1 _& v" H) b6 Y. Y( F' y8 J7 aCross-section analysis, 横断面分析0 D$ S! @4 }! A V$ i/ K5 ~! F
Cross-section survey, 横断面调查/ D7 z. ?& @8 g# `! E: {
Crosstabs , 交叉表
; M& ]( t" H3 ?4 M6 S2 ?5 \- S& d8 QCross-tabulation table, 复合表
7 p- T+ s! U+ z$ BCube root, 立方根
+ `! J; V' v* T+ ]0 _! oCumulative distribution function, 分布函数1 l/ l3 ]; h$ r2 K
Cumulative probability, 累计概率9 j" {1 K* _% O( y* X
Curvature, 曲率/弯曲
9 m4 b m) r- m1 i) |Curvature, 曲率
# a+ L" B3 j) u# p2 t u N, J, {* XCurve fit , 曲线拟和 & y3 }6 q7 Y4 O% G+ h |
Curve fitting, 曲线拟合6 ?7 Y0 ~# X! V& C+ [4 O
Curvilinear regression, 曲线回归+ |. b) B5 o2 [+ v, v
Curvilinear relation, 曲线关系7 }4 b3 v0 u" q; t# _. _3 V
Cut-and-try method, 尝试法2 T' E7 p. A. ^5 O
Cycle, 周期
. F5 ?9 ]& w" CCyclist, 周期性
6 K1 n! c* d0 O; [+ l0 aD test, D检验
8 Q4 L& x) ], `# {, G# k9 PData acquisition, 资料收集
+ i( O7 ~2 e4 i) n8 G4 J2 oData bank, 数据库
' k4 `2 h9 c& P/ I4 zData capacity, 数据容量
4 y+ C( u8 T' J( P0 _2 fData deficiencies, 数据缺乏
3 i2 s/ @4 O, d6 H7 a: WData handling, 数据处理
2 E# L; I) e9 m/ UData manipulation, 数据处理3 l: z% o3 h: J' O1 ]: i
Data processing, 数据处理7 W I& o% N d
Data reduction, 数据缩减* X$ n f2 `4 u! }+ i6 Q
Data set, 数据集
! Z/ b. O( R. G' S1 [ f' wData sources, 数据来源( M( a! B! p( K2 [
Data transformation, 数据变换
. u8 |) Z6 J: c2 m0 z3 f0 uData validity, 数据有效性7 \! O) u7 B% G/ H
Data-in, 数据输入
9 I+ H* n6 a+ N- Z, lData-out, 数据输出
8 ` i( H) W! G z+ r+ I% P9 BDead time, 停滞期
' s4 Y; j/ P; q! J; aDegree of freedom, 自由度0 ^0 I1 |4 z5 I* c* \$ h
Degree of precision, 精密度% ~( E# h3 t+ ? J
Degree of reliability, 可靠性程度2 d1 ?+ @3 V" B# q
Degression, 递减" k8 I7 n" V, C+ ~* X7 S) t: i
Density function, 密度函数
5 B% [0 H$ e# s1 R' x+ gDensity of data points, 数据点的密度
x1 u& d& Y U8 X4 CDependent variable, 应变量/依变量/因变量
2 r" }" u' m+ ^ N1 W0 X) f& VDependent variable, 因变量& `( _9 Q$ ~/ E: ?* t- S4 M
Depth, 深度 P0 P( q P6 Q! ?# M3 y6 q
Derivative matrix, 导数矩阵 r" E8 H1 [4 D- Y7 h
Derivative-free methods, 无导数方法
% ?1 W4 M# ?; o$ q* J* S- LDesign, 设计
) L8 f! o4 _7 t/ a% K: ^: rDeterminacy, 确定性
8 Z/ n0 c X- M' B, GDeterminant, 行列式
# @+ B" G B: D+ d( `Determinant, 决定因素
* c2 \2 a7 b( o3 A/ t* I, VDeviation, 离差 F/ [# k6 [3 @/ {5 c
Deviation from average, 离均差" h+ ~9 X* ?8 U) u D0 x
Diagnostic plot, 诊断图
0 i0 C8 P" P4 C$ }5 G" q; [) a& NDichotomous variable, 二分变量% ~1 O) L5 H6 B! O% }: j9 y$ [
Differential equation, 微分方程; |3 J& _) n. W0 p
Direct standardization, 直接标准化法
: f$ I, B! _( S" {' lDiscrete variable, 离散型变量
4 _+ @" q7 O: v+ w6 CDISCRIMINANT, 判断 ) D \! B- p& l% [ | B/ g
Discriminant analysis, 判别分析
4 ^4 e8 s; j% }$ p- lDiscriminant coefficient, 判别系数- j# b& a e4 s
Discriminant function, 判别值
: z* S; [; D) I' I+ t z3 uDispersion, 散布/分散度
! v5 {. `8 T* RDisproportional, 不成比例的$ R- g- i2 W; t# z1 F( J
Disproportionate sub-class numbers, 不成比例次级组含量
6 j, v9 E o) W- _! @3 ~ oDistribution free, 分布无关性/免分布0 U! W$ p/ W' L( E' R, G
Distribution shape, 分布形状/ I' {- q1 T0 z2 i
Distribution-free method, 任意分布法* O8 t2 r/ U4 \7 O5 K4 Z2 p
Distributive laws, 分配律
$ S \$ T5 h( A7 c! _Disturbance, 随机扰动项% B' `7 A4 }1 m( f9 j
Dose response curve, 剂量反应曲线7 i! {# R. h; y* O* U
Double blind method, 双盲法% \$ P1 @3 C* _, d M" w7 O& L
Double blind trial, 双盲试验
. g$ G0 E4 t2 |1 c! C# t$ yDouble exponential distribution, 双指数分布8 P5 L4 }7 x. n
Double logarithmic, 双对数- t# Q4 n1 {% a: v" v1 o
Downward rank, 降秩6 K2 @" @, }/ I: }
Dual-space plot, 对偶空间图$ [9 k6 v: k) F
DUD, 无导数方法
- H4 f4 c" Z$ l# F) EDuncan's new multiple range method, 新复极差法/Duncan新法
4 {; t7 p' P) ~. kEffect, 实验效应
& @' v$ F) x6 \9 r! OEigenvalue, 特征值
) F) M4 V) W, D: I1 O8 P/ gEigenvector, 特征向量$ J# o! q: [, m% ~ l2 _0 F
Ellipse, 椭圆! K6 m. I6 ?0 k- x4 K
Empirical distribution, 经验分布& H% |% j0 ^ v; l1 \
Empirical probability, 经验概率单位
: g, f. ?, r- I" ~! VEnumeration data, 计数资料
% v$ E$ y. B/ x% Q. x9 z# N; wEqual sun-class number, 相等次级组含量' i0 i# V/ ]2 f
Equally likely, 等可能
. X: B! T1 W/ J) x# c+ |5 w$ yEquivariance, 同变性
7 @& x. F3 \- p& M8 t+ lError, 误差/错误* H# a0 m% c; I
Error of estimate, 估计误差
- p& l% p4 y8 Z9 r) qError type I, 第一类错误; g5 N+ V% A2 f" [8 m) _) u
Error type II, 第二类错误
* [+ s9 k9 K, f$ q- DEstimand, 被估量# [( [* x. d. k# Q0 u9 s
Estimated error mean squares, 估计误差均方
- s( g" }9 T$ |' e0 [Estimated error sum of squares, 估计误差平方和
, p8 i) h" R+ P- S5 _- o7 r) |Euclidean distance, 欧式距离
; c1 W0 m; {) e9 LEvent, 事件
+ s5 ?4 f4 j5 U3 WEvent, 事件 H% g" C2 j5 \% p+ b) Q5 `
Exceptional data point, 异常数据点' T5 u) Z5 C3 Z# J6 i
Expectation plane, 期望平面& o8 j& K( |/ g3 i. ^& V1 c+ z" o: |
Expectation surface, 期望曲面
3 L2 c8 \; P2 LExpected values, 期望值
$ ]4 n+ K- F% i+ T dExperiment, 实验
# i/ R7 L4 o$ O# p7 U6 NExperimental sampling, 试验抽样
8 l8 n: N2 B9 h* pExperimental unit, 试验单位
& N" Q6 }0 Z; @+ aExplanatory variable, 说明变量
. {3 O* D* k1 U, y7 yExploratory data analysis, 探索性数据分析. A& Q9 X1 P, v+ {) x! G
Explore Summarize, 探索-摘要7 e' }8 z2 J1 Z2 F. p6 Y1 U3 s5 X
Exponential curve, 指数曲线
7 v" i) K. G6 p; I. ?Exponential growth, 指数式增长
2 i1 B" _: O: B, T7 TEXSMOOTH, 指数平滑方法
( U& x8 a+ Z$ v Q0 @* }Extended fit, 扩充拟合" u, j7 U$ h6 E i- C5 ~5 o
Extra parameter, 附加参数
5 P+ o, J$ o* u9 G5 m5 r; pExtrapolation, 外推法
1 b k, X5 {9 C2 e9 L$ DExtreme observation, 末端观测值& f! c# ]( I1 M& x6 J. A
Extremes, 极端值/极值
1 E+ |+ Q* k) p X0 uF distribution, F分布
8 U4 R$ v6 P. o. iF test, F检验0 ^' f7 k$ t% I! Q) X
Factor, 因素/因子. x- K/ t& M) g2 ^
Factor analysis, 因子分析
7 H3 a8 R }: r- m5 s- MFactor Analysis, 因子分析$ J9 z0 M4 X2 D, d3 E) c
Factor score, 因子得分
/ S, n6 I2 a1 N/ A+ zFactorial, 阶乘
! K) H' ^& C5 d( VFactorial design, 析因试验设计
& z) Y( o2 W" X; ?False negative, 假阴性% }/ z3 y, B( r( T1 O
False negative error, 假阴性错误
8 h, c3 p H, iFamily of distributions, 分布族: _0 f2 `0 T" ~- [9 C* ^
Family of estimators, 估计量族
! Q, G3 j2 v1 [5 h9 ~# xFanning, 扇面
+ C0 Y+ k2 M! B( i4 UFatality rate, 病死率
; G, B% n. H9 WField investigation, 现场调查
4 k' }, h4 ?- ^$ N7 n" [" |' c5 S. oField survey, 现场调查) p! Q" H& V9 ~ B; j8 ~4 k( B7 o: P3 @
Finite population, 有限总体! L, y. |0 c! a- O J# E: l' S8 l* |5 l
Finite-sample, 有限样本8 D$ K' e$ f" ?
First derivative, 一阶导数1 o- q' _( I0 o3 q
First principal component, 第一主成分& w8 @& B. H9 E9 B! p
First quartile, 第一四分位数
: @. y2 u" N1 j: [; `3 p2 vFisher information, 费雪信息量
, G c2 b6 }, O; G8 N TFitted value, 拟合值& _# k+ k, a8 c( j
Fitting a curve, 曲线拟合
( q" |( s$ Z" |/ y5 eFixed base, 定基
4 F0 y- |* x3 f! g( NFluctuation, 随机起伏
: K4 u# d1 g+ F0 XForecast, 预测1 D8 R5 K2 I0 I6 T3 C z
Four fold table, 四格表4 L; L/ t$ K4 A8 Z
Fourth, 四分点, R) x. c( U8 T2 b: a4 z" Z$ O
Fraction blow, 左侧比率9 I+ a8 k8 @2 s. G
Fractional error, 相对误差7 k1 i0 `4 {9 f0 j
Frequency, 频率
2 M6 {0 O: W+ u' p9 E U) JFrequency polygon, 频数多边图
1 J# U( m* L& Y3 x4 bFrontier point, 界限点/ ^0 u3 q9 E: A$ c
Function relationship, 泛函关系
" W4 ?3 l, `/ l, q+ yGamma distribution, 伽玛分布8 `" t, n& ]9 n; t7 Q( D F
Gauss increment, 高斯增量% h% h9 _1 X/ I3 ]
Gaussian distribution, 高斯分布/正态分布" k$ o2 O! d$ V
Gauss-Newton increment, 高斯-牛顿增量5 \- k: W& n2 M& J% `* J& Y. X, C
General census, 全面普查4 v k, @$ n- p, w. L) G
GENLOG (Generalized liner models), 广义线性模型
6 p& O/ U/ f# M- `Geometric mean, 几何平均数
- |1 o- o# O2 R" ^/ Y. h( h/ O! `Gini's mean difference, 基尼均差
) G6 v8 R! r6 q( K; y' j1 A {GLM (General liner models), 一般线性模型
3 v9 T9 b+ T: Z& m. N" v/ LGoodness of fit, 拟和优度/配合度5 i# C) B" n# B
Gradient of determinant, 行列式的梯度
5 U) k) {( I; HGraeco-Latin square, 希腊拉丁方
- {/ F+ x) C: Z9 G+ ~# c# gGrand mean, 总均值
, s: Q' q- c# ^# _+ J& f6 M9 iGross errors, 重大错误
/ u$ B# G0 H% _3 B* wGross-error sensitivity, 大错敏感度
3 g' n3 o7 w ~5 }' }6 D+ zGroup averages, 分组平均6 k. Z# o; X) d a- ?6 w! P
Grouped data, 分组资料
/ \( x7 u' \- R& g( MGuessed mean, 假定平均数
+ i" r0 `4 h1 F$ U+ \4 {Half-life, 半衰期
5 w' i) @7 U/ c4 m- ~Hampel M-estimators, 汉佩尔M估计量
; p& u8 w# z: K% uHappenstance, 偶然事件4 r. v' h6 f8 `& h" J. k
Harmonic mean, 调和均数
! ?9 |9 k! N0 o4 pHazard function, 风险均数
* @9 _! {4 t" g! q4 h' I) E( R$ iHazard rate, 风险率; i# k% s: V2 Q- P0 r
Heading, 标目 ' f6 ?! t& ^: K
Heavy-tailed distribution, 重尾分布
+ |0 @' x( a3 y+ n$ E. kHessian array, 海森立体阵5 r" I {0 p0 h2 s: l! x
Heterogeneity, 不同质* E5 [9 m7 [3 J/ `, J7 O0 I
Heterogeneity of variance, 方差不齐
1 v0 N9 U" I2 ]2 V, dHierarchical classification, 组内分组) L, z) A6 Z2 e3 b+ o% ^
Hierarchical clustering method, 系统聚类法6 s! L6 J9 e8 D9 K6 q7 g
High-leverage point, 高杠杆率点/ @3 w# W. w* L. @
HILOGLINEAR, 多维列联表的层次对数线性模型, A# T9 s" K" C, ~6 v$ }7 M4 v
Hinge, 折叶点
7 a0 P8 ^' b; _, Z, g0 j( k/ b% s8 ]Histogram, 直方图1 l! e/ T' w( q' p2 f
Historical cohort study, 历史性队列研究
( c! _, Y5 Q5 k, J3 DHoles, 空洞
; @3 E" S& g pHOMALS, 多重响应分析$ R4 y: \0 v7 D. H3 }9 `! F* Q
Homogeneity of variance, 方差齐性8 C. k! g6 G* K8 g
Homogeneity test, 齐性检验1 c- y6 s0 \: o% p. X! q( q
Huber M-estimators, 休伯M估计量
9 y, U7 T- f9 R. I8 o+ qHyperbola, 双曲线
# e: a1 U& v. k% R$ ~& {. B8 N3 h8 \Hypothesis testing, 假设检验0 ]5 q7 ^; k, Q9 W
Hypothetical universe, 假设总体
- g% k. `2 A. C8 O6 i0 u0 L- RImpossible event, 不可能事件9 d8 e# R# x1 `4 j3 \1 m8 H
Independence, 独立性) j0 ?, Q4 l, ]/ S/ a
Independent variable, 自变量1 g3 d- [* [, \0 V P0 S
Index, 指标/指数' t. v( X, {* R# v) Z$ H b
Indirect standardization, 间接标准化法
" t* y7 j( P/ Z5 ?0 YIndividual, 个体2 l. t5 d; @$ X" v. G6 s6 W" {
Inference band, 推断带
2 @, m: c9 y' c+ Y8 v" cInfinite population, 无限总体9 b* C3 ^ I1 C5 q6 H/ L2 `0 O
Infinitely great, 无穷大+ F% i, w `; u
Infinitely small, 无穷小
0 ]" M! F6 D8 R: R9 V( S5 {Influence curve, 影响曲线
" S9 `$ M' ^7 ?3 U0 S+ UInformation capacity, 信息容量
u' h1 D3 m4 ~Initial condition, 初始条件
$ E4 F, c E9 r9 ^9 b/ uInitial estimate, 初始估计值
+ a. ~- Q* ~8 E/ s7 FInitial level, 最初水平$ C! v) }, x$ B* K9 r' \
Interaction, 交互作用' B3 A5 w# J& P( [
Interaction terms, 交互作用项, V3 A( T5 B$ n$ [+ F$ `- c
Intercept, 截距
& x8 W2 \) b- M/ P4 \Interpolation, 内插法
5 \: ?0 D: f( N' G1 v0 \* IInterquartile range, 四分位距4 @5 ^5 q O# J7 i7 g5 G# [; @
Interval estimation, 区间估计
5 q9 r6 h, j8 }% o+ KIntervals of equal probability, 等概率区间( {) N- q2 b; B9 w2 E- o6 y
Intrinsic curvature, 固有曲率
" v% h/ g5 x W! Q# o+ k0 GInvariance, 不变性- `8 I% p; `$ B; g4 n/ o8 l- M
Inverse matrix, 逆矩阵- |. c& s8 [$ d. v9 f
Inverse probability, 逆概率. u) u* N# X1 @/ |% U8 Q' g: d
Inverse sine transformation, 反正弦变换9 C* U9 u! J& I6 o: v
Iteration, 迭代 , g# s8 Q2 R% J1 e$ X
Jacobian determinant, 雅可比行列式6 t8 I2 F _9 N5 m7 B/ [9 m$ n
Joint distribution function, 分布函数" I5 \. b) g8 x$ ~5 V3 x0 J j
Joint probability, 联合概率& v: T. E8 t1 R$ M3 ?4 Z
Joint probability distribution, 联合概率分布# }5 M) v7 p7 ~) s
K means method, 逐步聚类法
1 J; F$ s' }0 p- x0 Q9 FKaplan-Meier, 评估事件的时间长度
& n' _" b& i) @- P! _Kaplan-Merier chart, Kaplan-Merier图
. l# d" [: g. i6 RKendall's rank correlation, Kendall等级相关
+ h8 T7 ]/ x: \; q& A) E0 B0 VKinetic, 动力学% C4 o0 \ o2 h- n; v
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
4 p1 o" n2 B1 D+ n9 KKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验# X: U K1 u1 i% S; @, `: A' f
Kurtosis, 峰度" }: P. Q. ~ m
Lack of fit, 失拟5 \7 |! V4 |( ~% C3 y6 a2 P
Ladder of powers, 幂阶梯
9 q) c, Z1 t( [# A& f F9 n# [Lag, 滞后
* Y: {# v7 w) N6 g3 I; ]+ F% zLarge sample, 大样本* U; T) @/ T+ q! W3 ?+ A/ a
Large sample test, 大样本检验# a+ X$ R7 j* P# x
Latin square, 拉丁方
; t5 G2 _# m. V' z( I1 {" `; ]2 ~% sLatin square design, 拉丁方设计
, e( S8 E* r) j) d; V* _5 q; gLeakage, 泄漏
0 v! p) `: b; m( W9 o6 E- N0 fLeast favorable configuration, 最不利构形" x* v7 T* n. G( q3 l, [
Least favorable distribution, 最不利分布( F8 Z8 h7 f/ B9 }/ y/ t* h# H/ b+ l
Least significant difference, 最小显著差法
* S) [# j! _% ?4 F2 jLeast square method, 最小二乘法5 B, C$ _! ^5 ~, B: N- i$ q7 t
Least-absolute-residuals estimates, 最小绝对残差估计& W& E* g O8 J9 Q% k( @) `
Least-absolute-residuals fit, 最小绝对残差拟合
) b+ s+ }9 ~" R* {: `Least-absolute-residuals line, 最小绝对残差线
7 |: I% F( A+ }7 N+ R+ NLegend, 图例, m E2 \) D6 D( t+ f e/ d
L-estimator, L估计量$ f# h- f: k: X/ B& {
L-estimator of location, 位置L估计量
* m+ z0 v! t, j+ q2 `L-estimator of scale, 尺度L估计量+ y2 j/ Y/ [5 Q# q) L/ D
Level, 水平3 _6 f* Y1 j( H4 n
Life expectance, 预期期望寿命: o4 [* p8 B4 c' f; }4 I
Life table, 寿命表8 ~% D6 r* h/ u' t3 s ^
Life table method, 生命表法
) }- z! R$ R9 I8 ]5 Y' `$ yLight-tailed distribution, 轻尾分布
% ] Y, C. G' C$ L$ ]6 BLikelihood function, 似然函数
. b/ k7 U+ i3 `) l1 ~: {. g0 r1 NLikelihood ratio, 似然比7 I' g; w6 g& ?' H8 _! w
line graph, 线图
m E8 n4 S, ~Linear correlation, 直线相关( y& P+ C( ^; J8 z/ \
Linear equation, 线性方程
1 \& r+ _" T4 F8 H% }Linear programming, 线性规划
: v% O& c9 `& ]/ p# PLinear regression, 直线回归5 N) O5 T; l5 Y
Linear Regression, 线性回归
% H5 E$ Y' X3 M0 g LLinear trend, 线性趋势7 O) t: ]" {5 w. k3 {$ y. S
Loading, 载荷 2 U! R0 f9 P- \% F: \* D( ~
Location and scale equivariance, 位置尺度同变性# V* e: Z5 d: {* C7 a5 `( @+ C
Location equivariance, 位置同变性+ ]9 V. C7 @( o! B) i
Location invariance, 位置不变性
0 W" g, A8 P1 \: C+ E1 V0 PLocation scale family, 位置尺度族
& n' K) z1 g2 Z' O6 `: y4 SLog rank test, 时序检验
: ?) n% d* w* y7 O: K3 U- `Logarithmic curve, 对数曲线; }/ r' Q5 Y4 ^* o
Logarithmic normal distribution, 对数正态分布$ h0 U5 D9 ?3 @8 W& @6 a/ [
Logarithmic scale, 对数尺度
' l( c( C m: w7 }/ K5 k8 l' y }Logarithmic transformation, 对数变换, }4 Z" n% S% d: e# x' ~' ?
Logic check, 逻辑检查
& I* Q( y# T: }9 }6 @( ILogistic distribution, 逻辑斯特分布- O( F: t2 c- H- f
Logit transformation, Logit转换
/ O0 G& T' Q2 d1 SLOGLINEAR, 多维列联表通用模型
$ _3 H# H" g5 f0 A2 k7 pLognormal distribution, 对数正态分布- {" k, J" k; b" v
Lost function, 损失函数. R% J. r; }5 b2 v/ j
Low correlation, 低度相关
- l5 T! O7 r) J, vLower limit, 下限. s! r9 z8 V/ P" F0 a# J9 d
Lowest-attained variance, 最小可达方差4 G5 M( ]5 n T
LSD, 最小显著差法的简称/ Q- v% [% E7 W* ?: e+ z' L
Lurking variable, 潜在变量
$ g3 ?1 U$ Z/ u$ L0 lMain effect, 主效应3 P4 Z7 e, e5 e; N; D6 Y
Major heading, 主辞标目
' S9 Z, t4 g6 N0 N4 W8 EMarginal density function, 边缘密度函数: ~! M6 H5 L! f8 H- Z
Marginal probability, 边缘概率- F, f# T; C1 [+ { Y1 U C0 p
Marginal probability distribution, 边缘概率分布
. W6 G4 Z( k* t7 @; X& F1 b" c( v9 AMatched data, 配对资料% l) q4 R2 N6 w7 m) U: c2 x
Matched distribution, 匹配过分布; U2 F8 C$ M3 r* }% f$ _
Matching of distribution, 分布的匹配+ x0 E, U' n3 W: ]" t* z
Matching of transformation, 变换的匹配
! X( }% T' g" _' f( @Mathematical expectation, 数学期望
& x c# A3 ^4 B A( T- AMathematical model, 数学模型
* j, D7 ~- {2 q4 _Maximum L-estimator, 极大极小L 估计量
+ h; J0 l5 n2 P+ _: |1 oMaximum likelihood method, 最大似然法
( G1 [4 L! p+ n% g, sMean, 均数2 {% x5 d3 V' p8 J
Mean squares between groups, 组间均方
; v' J/ } f9 S8 E7 n' mMean squares within group, 组内均方
: H* A. D7 y7 E' D' G; S- i" ?Means (Compare means), 均值-均值比较3 {5 r: ^- q* K, _! Z. l9 {/ i
Median, 中位数# N/ `2 U* s( {. z* A: R3 l) s
Median effective dose, 半数效量9 _$ _" d- g# S7 W; a
Median lethal dose, 半数致死量
# M2 q& ^+ M. H( i. w& A T1 e% C4 u9 MMedian polish, 中位数平滑
+ d0 X5 X* u+ I. WMedian test, 中位数检验
/ h' q2 w6 m" C: e) t1 ]* R, CMinimal sufficient statistic, 最小充分统计量
: o7 P- M& j( V6 g6 C! @5 y* h# t! ~Minimum distance estimation, 最小距离估计6 u( c. v6 }7 [2 f) g! x
Minimum effective dose, 最小有效量5 X* u5 R3 ?; s
Minimum lethal dose, 最小致死量
* `; T3 } j- Z3 h9 P( \! `& jMinimum variance estimator, 最小方差估计量
8 {# M5 f2 y; K3 y" n. J; T+ ZMINITAB, 统计软件包
3 c3 q8 u6 v4 L) l% IMinor heading, 宾词标目
7 b8 @$ ^) D( n+ g! B+ jMissing data, 缺失值
9 x& k( M# ?/ SModel specification, 模型的确定# \+ S0 {, W* j: B4 S2 w
Modeling Statistics , 模型统计
$ D6 }5 @0 i8 a. Z; t& q9 ~# kModels for outliers, 离群值模型
# |) u; I. D4 a* Z( {Modifying the model, 模型的修正
9 ?/ a# [+ l$ J# s' g. F% y' iModulus of continuity, 连续性模
0 x: `, ]" }' B& N$ kMorbidity, 发病率
4 {1 m! B- ^0 u8 S9 FMost favorable configuration, 最有利构形
! G6 W9 P% K! J3 cMultidimensional Scaling (ASCAL), 多维尺度/多维标度; s2 \! n) _4 d4 u! C
Multinomial Logistic Regression , 多项逻辑斯蒂回归" h4 ?, ^$ C0 j
Multiple comparison, 多重比较8 a6 J: ], d! U4 v9 W' L
Multiple correlation , 复相关- s6 k9 T1 c/ n% E5 B3 ^2 ~ Y
Multiple covariance, 多元协方差& W) E {3 r; q* T: ?6 [
Multiple linear regression, 多元线性回归
# U$ y0 O# m7 {# n2 \9 KMultiple response , 多重选项
0 J+ Y }; ^) n Y9 A0 {Multiple solutions, 多解. w" V* p# [: E1 g
Multiplication theorem, 乘法定理( k5 f6 `( Q* v9 e# `* _3 K' V# J
Multiresponse, 多元响应
5 E0 J' b1 [" U, Y1 T' w7 PMulti-stage sampling, 多阶段抽样* t0 h) h1 r3 J( z1 ?5 p7 v, p
Multivariate T distribution, 多元T分布
j; e3 n9 F8 l( l0 _Mutual exclusive, 互不相容 M( Y L/ C2 F& n# P
Mutual independence, 互相独立
$ P* z4 h m+ Q" n' a1 v+ FNatural boundary, 自然边界3 K# S$ ^7 M7 ^; \4 L' h# A, Q
Natural dead, 自然死亡( Z( R+ l& t$ N* {5 I8 y2 H
Natural zero, 自然零2 M% x, o/ @+ O$ c+ J( Y
Negative correlation, 负相关/ C# y9 [& a1 m- {* j* a
Negative linear correlation, 负线性相关! d" c' ]" d+ w9 z
Negatively skewed, 负偏
- t+ ?7 o& r; I4 y7 ]" R4 e9 aNewman-Keuls method, q检验3 V3 U7 S' ~- t9 ^" R/ W9 V
NK method, q检验
n# z4 o! z% B p3 u% TNo statistical significance, 无统计意义, V1 i- L3 X2 {! H( a6 K2 P
Nominal variable, 名义变量
/ Z6 _2 e& c% ]9 R6 c$ yNonconstancy of variability, 变异的非定常性
) ~/ D, B7 y, ^" {4 z2 nNonlinear regression, 非线性相关
7 _4 W3 F, j2 q* oNonparametric statistics, 非参数统计
, |2 U5 ?3 z, b! }9 X, B1 ?Nonparametric test, 非参数检验
4 a: w0 k7 B2 N/ v, k/ o" U( JNonparametric tests, 非参数检验# o' ~: f( B, y4 Q: h& L
Normal deviate, 正态离差
! R0 Y2 l" j4 f: D/ z1 U" tNormal distribution, 正态分布
; C1 V( c5 ^ dNormal equation, 正规方程组' ~8 `6 O* t' t- d7 r0 G( s$ N
Normal ranges, 正常范围
" ], l K3 ?+ x m: z7 r8 VNormal value, 正常值2 A5 a! e, q( y: A# e3 v% w) J
Nuisance parameter, 多余参数/讨厌参数/ x: w! W% Z" f3 j/ h
Null hypothesis, 无效假设
+ E- a! v8 p1 L' ]5 O3 ENumerical variable, 数值变量5 `5 p3 R. e8 J2 t0 H
Objective function, 目标函数
: E9 l4 R1 C$ f4 IObservation unit, 观察单位* g2 |. v% P, E
Observed value, 观察值* r3 L' @7 f' |* w8 u
One sided test, 单侧检验3 t+ M3 I7 ~! e- c- Q& l/ G$ \
One-way analysis of variance, 单因素方差分析. d+ W6 ~7 G" Q
Oneway ANOVA , 单因素方差分析' I4 c! W2 Z% P" E# x
Open sequential trial, 开放型序贯设计& H0 [$ X% @- O
Optrim, 优切尾8 D, z$ Z: v1 Q
Optrim efficiency, 优切尾效率* v" B( o9 q. }$ K8 B( I! j7 E& F( t
Order statistics, 顺序统计量8 L* @5 d5 q# P, R" c; x1 X3 b" \
Ordered categories, 有序分类
! U1 f9 e( ~& c. A- f% K3 fOrdinal logistic regression , 序数逻辑斯蒂回归- y: t) d* J; q p3 k
Ordinal variable, 有序变量" ?4 T- U6 Z6 D, p/ x6 k |
Orthogonal basis, 正交基
6 R7 W$ {6 m! YOrthogonal design, 正交试验设计4 x- L! V' U" v7 N
Orthogonality conditions, 正交条件
" e; v' p3 b+ ]1 h2 Z2 |ORTHOPLAN, 正交设计
$ [ i' k* T, b }% @" u7 \Outlier cutoffs, 离群值截断点! Z# E( v4 Z) j* o6 S
Outliers, 极端值+ _5 R/ t& [! h. q F/ m) {* [
OVERALS , 多组变量的非线性正规相关 # B- Y. ~+ F: g3 L- m% n7 i7 [
Overshoot, 迭代过度* e0 M% V$ J, K( ~4 h3 L
Paired design, 配对设计7 U$ ?; R3 X* C3 r3 v) ]
Paired sample, 配对样本
6 |9 ~, A# W) U6 X7 {Pairwise slopes, 成对斜率3 O- l( k" [* Q2 g2 j2 G
Parabola, 抛物线
, d- I3 {4 I6 ]# r, Q( tParallel tests, 平行试验
- ^+ h& r+ t5 N( j7 I5 ^Parameter, 参数7 H' `7 u( A0 D: T* K
Parametric statistics, 参数统计$ Z5 N) d7 R; ]0 x3 r7 _; c
Parametric test, 参数检验9 ^5 u" j& d1 }: y8 Q
Partial correlation, 偏相关: S* s# [/ o7 B" e5 b" z
Partial regression, 偏回归: Z2 l1 t& g$ w: b4 J1 ^
Partial sorting, 偏排序
* { k8 z7 x xPartials residuals, 偏残差
/ S/ u9 r# J3 b4 ?# Y. c' \2 _: Y5 APattern, 模式
, G) U) p* L/ z# pPearson curves, 皮尔逊曲线0 n( _' z! h; p2 i3 L
Peeling, 退层. P5 e' Q* ?% A+ S& z5 \- ? M3 |
Percent bar graph, 百分条形图) ]8 H+ X1 u& ^- Y$ b$ W
Percentage, 百分比$ M8 d6 d$ {& y. U0 J( R- F
Percentile, 百分位数- }9 ?9 p, V0 k: w# }
Percentile curves, 百分位曲线4 w7 b* [4 o& s+ W
Periodicity, 周期性/ g" R: D$ w G3 ^
Permutation, 排列
0 a& G9 k% [2 f+ mP-estimator, P估计量 n: a) h2 Q1 b3 N8 `% t1 j' n
Pie graph, 饼图: a1 n" a B% Z7 l
Pitman estimator, 皮特曼估计量
1 u- S- v: ]8 Y9 o; d$ JPivot, 枢轴量
' ?; x. n3 m, s( ]Planar, 平坦3 o& }: M3 g( K6 x+ e4 t2 z/ r2 f
Planar assumption, 平面的假设! R* q8 x9 i1 _+ J$ P( W
PLANCARDS, 生成试验的计划卡7 Y% ~7 }3 \! g. m+ k- l) q' W8 S+ W
Point estimation, 点估计
/ T @- e" q$ T: yPoisson distribution, 泊松分布
: @) I9 k& T- ~* A' W" bPolishing, 平滑
9 x" a0 K; n2 n+ l) H& l7 RPolled standard deviation, 合并标准差
( R9 s, a& d. j+ i* c) kPolled variance, 合并方差
5 y" l6 y- {( ?3 U4 A9 K7 \Polygon, 多边图$ v! k6 ~- }9 s7 P
Polynomial, 多项式
& B& C% }3 B/ T7 Z1 m7 M- D6 Z3 PPolynomial curve, 多项式曲线
0 I! @3 c& B+ R; MPopulation, 总体
* J" k3 c. g! WPopulation attributable risk, 人群归因危险度: \# u/ _9 g( F2 |! U7 I; c
Positive correlation, 正相关
8 f9 B3 g, g2 W/ K, \3 CPositively skewed, 正偏
6 {& f( U5 [+ @9 n7 h3 D+ gPosterior distribution, 后验分布2 s+ Z. I- @2 @2 @
Power of a test, 检验效能
+ R E0 Z% F% z; X6 X. U I h) wPrecision, 精密度
0 N+ o0 n1 c: H/ sPredicted value, 预测值
$ d5 H+ P7 l2 i) E N* PPreliminary analysis, 预备性分析& p0 t. u8 C! \2 u2 P7 L9 n
Principal component analysis, 主成分分析
, Z' j+ r1 p' c/ B# m2 H0 R" ^" vPrior distribution, 先验分布
: o( C* _' D5 y6 wPrior probability, 先验概率
4 K K/ e- M+ ^8 ~" k: UProbabilistic model, 概率模型
7 s7 q7 K1 i! }" Z+ tprobability, 概率
- M% z9 a8 L( z/ s: ^0 w9 M6 sProbability density, 概率密度
$ O: J: g2 p5 U+ E' d( Q' q( eProduct moment, 乘积矩/协方差; b( |* N& s# [0 ^: v
Profile trace, 截面迹图
" i O/ {6 `' h# f! G- c. ^Proportion, 比/构成比% S& e9 u; ~8 J2 I
Proportion allocation in stratified random sampling, 按比例分层随机抽样
8 I' b, a: b2 p0 J8 [7 I, IProportionate, 成比例1 I: m/ ]6 @) M* _( Z. q7 e2 x
Proportionate sub-class numbers, 成比例次级组含量
2 J! J/ }4 F9 }; I, \. @Prospective study, 前瞻性调查9 Q+ `! k" t, Y4 x( z5 p0 ^
Proximities, 亲近性
" K/ J- b% @" s4 c$ N- L: ?Pseudo F test, 近似F检验
! {9 ~% B- \/ N3 M) j( nPseudo model, 近似模型
6 Q! P6 B" A$ }" D+ c, WPseudosigma, 伪标准差
% Y) t' o ~7 u( h5 }0 n5 w iPurposive sampling, 有目的抽样
# Q% ]" K R0 ~0 H: Q3 H3 K+ @2 zQR decomposition, QR分解
% T: p6 P5 X# z( \- x2 D! i) IQuadratic approximation, 二次近似
8 a2 S7 a+ G! _: p1 u. T3 dQualitative classification, 属性分类1 q8 z* F" o- `" |1 @- l4 Z
Qualitative method, 定性方法
0 i p* P' p1 Q7 z# LQuantile-quantile plot, 分位数-分位数图/Q-Q图 `: U6 e9 r2 [5 G3 d2 g
Quantitative analysis, 定量分析6 P/ @) D1 r8 n6 G9 u
Quartile, 四分位数4 C" Z0 J( @, m* `- N3 ` }5 M
Quick Cluster, 快速聚类
+ @, S$ p* _/ v: ]; L3 ARadix sort, 基数排序5 X; v n4 I% N" X' x
Random allocation, 随机化分组6 S$ S$ j' ~ ]; B3 L2 r: l! Q
Random blocks design, 随机区组设计
( e' F- U u0 m2 b5 vRandom event, 随机事件
; k! I1 K& }# Z3 e1 [- y; XRandomization, 随机化/ h; f: F5 ]4 `9 i; T
Range, 极差/全距( Q; [2 S. a/ i$ t4 d" |2 S
Rank correlation, 等级相关4 X( Y# S" b2 ~% N
Rank sum test, 秩和检验
! v) N; k, \# p# A Z9 ?6 Q* TRank test, 秩检验
1 D/ U1 @4 k- Q1 s1 cRanked data, 等级资料
9 g0 G6 g6 {* yRate, 比率, O, n X1 l' k2 o( \1 p6 P# _
Ratio, 比例
1 W- M" [/ }6 T$ M XRaw data, 原始资料
0 [' J4 q C$ K& D0 R0 [+ CRaw residual, 原始残差
: y# d; Z6 W- ]$ B6 A9 {Rayleigh's test, 雷氏检验' r1 Z( Q. D9 `, {- o; P! ?
Rayleigh's Z, 雷氏Z值 4 M- ?! J' S$ H; s: J$ y* O! f
Reciprocal, 倒数
7 E& V {, {" H/ PReciprocal transformation, 倒数变换% c! X* \5 i" b& S2 u" m
Recording, 记录
8 w* z+ A+ ~9 C0 S+ iRedescending estimators, 回降估计量
0 j Q+ A2 M% N- Y0 k* \7 A o; dReducing dimensions, 降维
+ B4 p B% f0 L3 c% R$ i% \Re-expression, 重新表达
* n3 K$ ^* ~: |# t: n& x* @Reference set, 标准组" U! b4 }! A4 y: _ P6 u( `3 H4 r
Region of acceptance, 接受域# g: G# N) m- R, b5 l( u- w
Regression coefficient, 回归系数5 I- v, r0 l9 e2 V/ C
Regression sum of square, 回归平方和5 ]: d7 Q) p! ~$ l
Rejection point, 拒绝点9 {4 y' k" e: O" `
Relative dispersion, 相对离散度
6 U: J7 }0 k/ A4 r# J% fRelative number, 相对数3 r( V" h" F. m' C" S
Reliability, 可靠性$ S7 O7 G; A* `) y$ V) Q* p$ M) G
Reparametrization, 重新设置参数
2 ~ e/ J9 D$ ?. n: D8 l( m J$ @Replication, 重复
+ x7 {7 W6 S1 F, u& o8 x0 t7 m1 ~Report Summaries, 报告摘要, _5 F' M, A- J! g" k
Residual sum of square, 剩余平方和$ u; K$ G7 y0 h& H. p/ E* F
Resistance, 耐抗性
. `# P- n) Q# f* D! W' k1 MResistant line, 耐抗线$ s9 B# V" u1 w8 D# a" M
Resistant technique, 耐抗技术+ u8 W& @7 }6 Q$ I8 g
R-estimator of location, 位置R估计量
9 c) p" }1 O- h) {* t3 c& fR-estimator of scale, 尺度R估计量
- G1 v, t1 O+ q* X+ }* O1 IRetrospective study, 回顾性调查- P4 }7 L, u' N) e5 E( ]) e/ o* e: o
Ridge trace, 岭迹
! U) U; M( O ?) p' b5 ?Ridit analysis, Ridit分析
- R1 x/ u. k4 ?9 lRotation, 旋转
: b& v( u% m8 k- Q2 {) K+ LRounding, 舍入$ O) S- R* q& N5 k, p; {
Row, 行 g5 q( ?: b) g* P
Row effects, 行效应
' q$ {+ N! [3 ?4 wRow factor, 行因素# H& B& [; I* q( i
RXC table, RXC表3 L* h. A. r) U5 }1 c9 {
Sample, 样本
5 w1 ?4 h, C3 N: X& dSample regression coefficient, 样本回归系数+ k# i0 H8 v+ ^1 E, [- w5 j$ L1 A3 k
Sample size, 样本量) ~4 E( |( N5 ]
Sample standard deviation, 样本标准差, F+ \$ `, o' Y& O! n
Sampling error, 抽样误差
- l' n) _* h9 R" _. T# ?3 I" h; K5 S/ JSAS(Statistical analysis system ), SAS统计软件包6 f% t& D. Y# T5 {
Scale, 尺度/量表
! T2 q2 x t5 Q% I& l/ yScatter diagram, 散点图
3 q7 C* ^) o& ?4 J ~5 l( I& cSchematic plot, 示意图/简图1 t7 Y' j( X9 s' L, s
Score test, 计分检验: k" c& Q0 ?/ R2 i& n1 T
Screening, 筛检1 S6 W, L8 }$ B! ] s9 A
SEASON, 季节分析 * K5 _! l* q g Z& w
Second derivative, 二阶导数
8 [( p; j6 A% o' O0 OSecond principal component, 第二主成分# u1 l& _9 ~, M" Z' o/ E
SEM (Structural equation modeling), 结构化方程模型
2 |# U& F4 i5 Q. L8 qSemi-logarithmic graph, 半对数图, E) c3 k8 D* l
Semi-logarithmic paper, 半对数格纸
: B3 z- n! v4 t% J5 H1 ESensitivity curve, 敏感度曲线/ \, S; H5 I% Y7 E% w# b5 a# u
Sequential analysis, 贯序分析' {0 C( r. ~; [5 E
Sequential data set, 顺序数据集# S6 y, n7 ~* [2 v
Sequential design, 贯序设计8 Q& y" i* U- N: ~/ e. j) j
Sequential method, 贯序法
3 e. i* A' ^& r+ fSequential test, 贯序检验法
* C9 t6 j i1 E( u+ o3 k2 ^Serial tests, 系列试验2 p& i6 y! |7 I8 \- R7 H" w' r& I
Short-cut method, 简捷法
& ?0 @9 B4 T% F0 c7 X. }) b5 }Sigmoid curve, S形曲线
9 e! P9 B$ p9 D3 K# tSign function, 正负号函数0 L4 a" O/ g! `; ^- Q; R* T% f
Sign test, 符号检验5 v% ^( x# t! S2 u
Signed rank, 符号秩
* m6 |4 H* n; E2 i0 N2 Q: ?! }8 G, CSignificance test, 显著性检验
1 P7 ]! l1 C1 O8 k+ b qSignificant figure, 有效数字0 E! U$ ~7 _ u# |) A
Simple cluster sampling, 简单整群抽样
" L) D8 v1 R( _: G# @' J4 k0 WSimple correlation, 简单相关" X; D' y' [, Y% a1 X
Simple random sampling, 简单随机抽样! U- S8 k! w* c$ |2 \
Simple regression, 简单回归
3 X% q7 f; C3 isimple table, 简单表
# G# }; R; s# n; }6 ^: Q" ESine estimator, 正弦估计量
/ F; G& r% r& N9 m" ]& {Single-valued estimate, 单值估计2 _) `9 s! K( Z6 j- o9 S
Singular matrix, 奇异矩阵* c" _# c+ F( g' T8 m
Skewed distribution, 偏斜分布
1 M/ K6 `8 R& K$ {" j+ J8 BSkewness, 偏度
& q; n* k- y! _! x/ fSlash distribution, 斜线分布
- Q9 E' {" b% }7 j s; Z' C/ |2 u- FSlope, 斜率& J8 X0 S+ @$ G% R2 `
Smirnov test, 斯米尔诺夫检验. S( w& b; V9 q2 V
Source of variation, 变异来源4 _ l# O. z9 p; N2 R
Spearman rank correlation, 斯皮尔曼等级相关% B! ?0 p$ O8 }" s4 k
Specific factor, 特殊因子% R, v9 m; c9 z" C" ]0 Z. ~1 J5 x9 @
Specific factor variance, 特殊因子方差2 m) A' t: z# Z& B
Spectra , 频谱, U6 v" k+ N: i( K& j2 R
Spherical distribution, 球型正态分布
& ?6 n: Y$ O7 OSpread, 展布1 t/ C' ^8 Q5 x3 C8 a
SPSS(Statistical package for the social science), SPSS统计软件包
' Y% n5 x; g, p# v7 ZSpurious correlation, 假性相关
( l# i3 z; j& J5 z( JSquare root transformation, 平方根变换
1 g6 W! J8 F% U7 [Stabilizing variance, 稳定方差
) W5 |7 k2 U XStandard deviation, 标准差
- y; t' ?! ~, e# J) b1 `/ t9 k5 aStandard error, 标准误
# `# }) D4 N5 E* A; U$ Y% |Standard error of difference, 差别的标准误6 P d) i" e% y: Z1 Y
Standard error of estimate, 标准估计误差0 a# p9 Z5 J5 G! \ V1 F' a
Standard error of rate, 率的标准误
# w O0 p+ [ ^' g6 z+ }Standard normal distribution, 标准正态分布9 c4 ~) h: e% i3 e! i) a
Standardization, 标准化
8 F- h# F) Z" Y* {% O5 oStarting value, 起始值
- V* f; f9 z9 f* |4 pStatistic, 统计量% O9 L& u1 z! @
Statistical control, 统计控制
5 h! W; g- q" a, UStatistical graph, 统计图) Q1 c7 @. Q8 W2 s* E; l
Statistical inference, 统计推断
8 t4 R8 e c. _ G$ z' S' rStatistical table, 统计表
% h* N; S8 y5 ]% g# LSteepest descent, 最速下降法0 U! u; d/ N( ~7 g& A# P
Stem and leaf display, 茎叶图
& `$ a5 p% c" l6 ^$ {) {" J. DStep factor, 步长因子+ u; q; _4 S' {' U5 Z0 F9 q& ]
Stepwise regression, 逐步回归7 l, k1 m# S( g, z- l* T! }) M
Storage, 存
0 G. y7 _( F3 T( {8 C, Q: L7 ~( U OStrata, 层（复数）" J A9 y6 Q0 L$ m3 q' m# `# X
Stratified sampling, 分层抽样: v) ]! h) C' S- o2 U7 I
Stratified sampling, 分层抽样
1 g, _3 A; b4 ^9 Y3 {6 IStrength, 强度
6 y7 t; a/ t; z& xStringency, 严密性( r/ z# p$ P! O! r* j) q
Structural relationship, 结构关系
5 v, |/ `4 N( T, y; sStudentized residual, 学生化残差/t化残差
0 M! e+ r& l$ MSub-class numbers, 次级组含量
- H6 S9 E+ t7 h2 I' zSubdividing, 分割
9 d5 _7 @5 Q' f5 |# uSufficient statistic, 充分统计量
: H0 y$ ~ N4 D& }( u1 k4 k+ `" ~Sum of products, 积和
( }! M9 m! n. q. q) a* ASum of squares, 离差平方和
9 }' r6 O% v q' D" a5 p6 g2 C! xSum of squares about regression, 回归平方和 F* x$ U- o2 e& X
Sum of squares between groups, 组间平方和4 y+ |* C( p" B
Sum of squares of partial regression, 偏回归平方和* G. p6 y1 l" L4 y2 E/ ?3 Q% X: i7 j
Sure event, 必然事件
6 c$ i+ c9 y, `! eSurvey, 调查6 ]) Z9 a" J1 Z3 n h) m) G
Survival, 生存分析2 R# n, n9 H" ?& r
Survival rate, 生存率
9 e# A. h+ T( T' A0 k3 A4 qSuspended root gram, 悬吊根图
! l% |) U, T% @* ~& o# T% GSymmetry, 对称# J y% d; D8 G) T. N, ]6 s1 R
Systematic error, 系统误差
8 t" Z5 m5 t4 w, w6 F: sSystematic sampling, 系统抽样5 q: M) q1 i" `3 _* o
Tags, 标签
* Q& u& ], A) M! gTail area, 尾部面积
/ [( ] z" o+ Q8 _6 sTail length, 尾长
0 A* p$ }. P0 _2 ^Tail weight, 尾重
; J" s& X9 T+ H( R4 mTangent line, 切线
; `1 M; X U8 H$ N% s- D- rTarget distribution, 目标分布) _ I: H+ I6 a! g
Taylor series, 泰勒级数
2 D5 D [) V( b o5 sTendency of dispersion, 离散趋势
8 f. x' N! `8 l8 L' JTesting of hypotheses, 假设检验1 q% G/ x) [, v* G
Theoretical frequency, 理论频数
1 [# K# r# @- @: r+ `% hTime series, 时间序列1 ~ l7 I/ t7 x8 M
Tolerance interval, 容忍区间
; m. T v' z8 | d( r1 ^4 oTolerance lower limit, 容忍下限+ v, Y; S3 ]* n, B7 a( e
Tolerance upper limit, 容忍上限
% K. q* t9 A3 _Torsion, 扰率
9 L- X; u. B/ ]+ I) wTotal sum of square, 总平方和
/ ~, ` k" x3 n7 \Total variation, 总变异6 g5 G' V3 Z3 p! }
Transformation, 转换, l* J( P& t; [+ F. R& X { W
Treatment, 处理
; K$ Y6 f. F) [6 \, oTrend, 趋势
+ ?- F# g- V4 uTrend of percentage, 百分比趋势
; H; I" x! D1 v% RTrial, 试验( f; `9 L0 b; V' H
Trial and error method, 试错法8 o% w0 A8 Q6 ?# l' C
Tuning constant, 细调常数
* a5 S+ C& W4 W; g9 F$ D) XTwo sided test, 双向检验. j6 J( `8 m, t
Two-stage least squares, 二阶最小平方
3 x& ?3 G; |5 o! I5 ^Two-stage sampling, 二阶段抽样
# m$ X. y/ z: P; I6 s+ e/ UTwo-tailed test, 双侧检验! g( J7 K( E( P0 F
Two-way analysis of variance, 双因素方差分析
3 F) n+ c8 ^0 C1 ~Two-way table, 双向表
) {, L+ F% S, V& i4 L' E# sType I error, 一类错误/α错误
1 L" c! v! u# ~; H B0 bType II error, 二类错误/β错误
\2 G6 Z9 s( eUMVU, 方差一致最小无偏估计简称. ~+ i$ I( L( J1 I5 @) ?- e5 r
Unbiased estimate, 无偏估计: W1 o2 A/ h0 p) l% Z- r
Unconstrained nonlinear regression , 无约束非线性回归% P" x- c+ }. Q
Unequal subclass number, 不等次级组含量* P& z7 K: }+ p& e
Ungrouped data, 不分组资料3 [8 e3 T0 a4 L( Y2 {3 R% d
Uniform coordinate, 均匀坐标
, X" g/ d( K( r* u! {* P4 b$ A' lUniform distribution, 均匀分布
9 O; c' z {0 OUniformly minimum variance unbiased estimate, 方差一致最小无偏估计3 Y$ A. ~: X0 J- Y- w) ]! e7 K
Unit, 单元
3 T3 E) I8 [1 O3 U" V$ `Unordered categories, 无序分类
& d8 T f9 L/ D3 D6 OUpper limit, 上限
% N8 y9 i" }4 q) v# ~Upward rank, 升秩
* h9 F! C* J' BVague concept, 模糊概念6 s% e, e3 K1 [) j# l
Validity, 有效性
4 w! H' l! f9 w. ?; C2 l' cVARCOMP (Variance component estimation), 方差元素估计! _7 m' ~7 @+ p- T
Variability, 变异性8 R! h. l+ x& T% p& s H% w3 Y
Variable, 变量
6 v5 k ^* S0 Q2 ~% OVariance, 方差) {) h5 z' y- S
Variation, 变异6 d, V, N9 M* X
Varimax orthogonal rotation, 方差最大正交旋转% F5 G" Z% A! T3 J" N6 f( y( m
Volume of distribution, 容积7 `9 O& K2 s1 Q6 s7 u: P
W test, W检验7 u) D5 _+ ?# V! c$ D5 ^" t- n: A+ B
Weibull distribution, 威布尔分布& |% @8 y: I+ _% r; n
Weight, 权数- @* m; j* |+ m+ L; C. Z: P
Weighted Chi-square test, 加权卡方检验/Cochran检验! W' ~1 z$ G$ |3 k' W, A
Weighted linear regression method, 加权直线回归% d) W! n0 H0 S) F/ x
Weighted mean, 加权平均数
: W' B1 I& Q T% Y8 X3 [' lWeighted mean square, 加权平均方差
$ x3 z9 u) f7 c: q3 A8 s" OWeighted sum of square, 加权平方和7 I$ z% J; x" `; t! d1 {. b# @
Weighting coefficient, 权重系数
) u% z3 P; z; T6 U/ F" }5 t0 cWeighting method, 加权法 8 i# n. I9 V1 _5 j- j% }
W-estimation, W估计量( H1 L+ P* S' P! A8 V
W-estimation of location, 位置W估计量$ s3 z; B& ^' q8 V+ W2 I
Width, 宽度/ J7 I" v+ H1 W k* v
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验3 o" D2 H; L7 O, g/ ~
Wild point, 野点/狂点
! } \: v) B& d2 `8 c6 p# P1 eWild value, 野值/狂值! j# Q) i+ C7 }( y3 z
Winsorized mean, 缩尾均值$ j3 T* U; _7 l5 D; Z! B( Z+ ^: I
Withdraw, 失访
; x& ^2 \' |) T6 XYouden's index, 尤登指数, j5 w2 o' \5 Z o/ [# D0 r
Z test, Z检验
- U. L/ |1 O+ ]Zero correlation, 零相关
) F' I& B5 |2 ]# OZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
