|
|
Absolute deviation, 绝对离差; N6 d9 @) J$ a1 n, @
Absolute number, 绝对数+ b) F6 b, j1 R1 |% C8 V4 `
Absolute residuals, 绝对残差& b/ S/ K* x& L( ^6 v9 B9 \( Q
Acceleration array, 加速度立体阵- i" ^0 C! @- x2 f* g
Acceleration in an arbitrary direction, 任意方向上的加速度
; U# T7 q6 J/ d# UAcceleration normal, 法向加速度- P F% M m9 g: a- f2 Q2 C! J
Acceleration space dimension, 加速度空间的维数6 Q# J. Y1 J' H4 L: f, ^) l' R
Acceleration tangential, 切向加速度
- r+ n, v( z4 {- [* A3 eAcceleration vector, 加速度向量2 A0 v0 ]/ K) I. i
Acceptable hypothesis, 可接受假设4 B3 n1 o5 Z V# H9 I# {" w
Accumulation, 累积( J! ]% }1 o7 y- [4 _3 H, L
Accuracy, 准确度# U ~2 w. t/ W! d* P+ w* Z5 c; @* ?3 ?
Actual frequency, 实际频数3 m/ s( d7 [; D* U7 @0 {, w6 y# j
Adaptive estimator, 自适应估计量4 Q9 ^$ a3 l. r' X0 i2 q
Addition, 相加
7 t/ i' a# q, l3 v) e# NAddition theorem, 加法定理$ `5 t# y9 _9 G* Y, g1 X
Additivity, 可加性6 O9 S! w, {0 T- X3 X
Adjusted rate, 调整率
- W0 V7 P4 z0 D, YAdjusted value, 校正值
# W9 M) r6 u+ G' Z4 LAdmissible error, 容许误差) v) |9 F0 p0 t: M. B
Aggregation, 聚集性5 Z5 d: H# I3 r% O3 c
Alternative hypothesis, 备择假设
8 q+ U$ S' O, c4 S$ Y0 LAmong groups, 组间- i# X! X k Y- B0 T
Amounts, 总量
5 U$ E) x; M5 S$ `% d, v; M/ }; E# wAnalysis of correlation, 相关分析1 g2 U( v5 {4 O! c
Analysis of covariance, 协方差分析
" X" \; G' _* i s$ bAnalysis of regression, 回归分析
4 a L( Z7 Z$ D4 ~Analysis of time series, 时间序列分析
$ J$ z, L) X- hAnalysis of variance, 方差分析( p# x7 d$ g4 L! x4 n& ^% m
Angular transformation, 角转换/ p; M6 U2 N% `% A
ANOVA （analysis of variance）, 方差分析
* h4 c5 A' p" L; l5 G4 G; I/ HANOVA Models, 方差分析模型, S6 ~' U2 n4 U/ Y
Arcing, 弧/弧旋
" K, r" o$ k7 q# `: P) {( K, _Arcsine transformation, 反正弦变换3 }) V: p% U3 {1 D
Area under the curve, 曲线面积' _9 m" D, x H# P0 ^, q# _, E
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
8 l5 G# \3 n4 k. N0 x7 M1 M2 N3 oARIMA, 季节和非季节性单变量模型的极大似然估计
! W0 `. T5 l. h" GArithmetic grid paper, 算术格纸: ?: F0 o \% O6 V) d% r& t
Arithmetic mean, 算术平均数
1 Y+ C: N' ]" i6 m& y5 a+ P0 n/ AArrhenius relation, 艾恩尼斯关系; o7 n8 F7 n% K* m. ?
Assessing fit, 拟合的评估4 I/ X! o x1 O5 P
Associative laws, 结合律* K5 J3 Y$ H! |" M# D X
Asymmetric distribution, 非对称分布/ x: ]# u8 @( \# K
Asymptotic bias, 渐近偏倚0 G+ i# l3 D: f
Asymptotic efficiency, 渐近效率! }( ^# Z7 u% z4 X3 c( T
Asymptotic variance, 渐近方差
& k% h% v/ `% }# i- c2 AAttributable risk, 归因危险度
I% G7 W" z7 ?6 K0 w. e; Y. ]Attribute data, 属性资料4 T+ L( N. `& T& b5 J0 |8 l, \
Attribution, 属性
3 g8 |7 M% I7 J$ J& V( OAutocorrelation, 自相关1 O- h$ M) `8 ]. i& o4 B! m
Autocorrelation of residuals, 残差的自相关
$ @, @/ S e- i% y7 y; {- `6 V2 iAverage, 平均数' ~& b- Y8 R B
Average confidence interval length, 平均置信区间长度
, n X' t, ]% C: E: b# zAverage growth rate, 平均增长率6 A4 \% X6 q- b9 |
Bar chart, 条形图6 M: Y. w% A& o" i% N# ~/ o) W
Bar graph, 条形图
2 W7 Q. R# m- E( CBase period, 基期- t+ Q3 l! H8 _% P4 M
Bayes' theorem , Bayes定理
K& p. e. d' G( r3 \1 Q& T# }1 TBell-shaped curve, 钟形曲线
. d" r# V, ?- p* T; @Bernoulli distribution, 伯努力分布, A& x+ a" G; K
Best-trim estimator, 最好切尾估计量! h0 f8 J; u% w' O" s+ w
Bias, 偏性! I0 W6 A: T& x
Binary logistic regression, 二元逻辑斯蒂回归
1 Z) i1 W8 n/ C- T3 P# k" lBinomial distribution, 二项分布
1 t, B9 e& p9 [& SBisquare, 双平方; I# l2 T3 b: q$ ~
Bivariate Correlate, 二变量相关
. [5 v! c3 p" g/ _: e& mBivariate normal distribution, 双变量正态分布
2 \. e. k K, M; sBivariate normal population, 双变量正态总体
4 q, _9 B7 B- W, q. y m5 f. gBiweight interval, 双权区间9 i7 P! H. X# E m$ g7 L( `$ E- B
Biweight M-estimator, 双权M估计量
5 X. Y* s4 A7 g% \Block, 区组/配伍组
7 k4 Y! P+ o( J, a( c1 ]BMDP(Biomedical computer programs), BMDP统计软件包1 t) G; B' B2 g$ a. v `6 T) O
Boxplots, 箱线图/箱尾图; f: J. a& Y2 p m% T
Breakdown bound, 崩溃界/崩溃点
7 m( z' b1 w; |9 LCanonical correlation, 典型相关% O9 Y; H* E% x0 m1 ~/ W( i
Caption, 纵标目+ B8 R2 {* S# T$ n9 A# X3 \
Case-control study, 病例对照研究! R) F) W9 p, z
Categorical variable, 分类变量
m. e: g3 U, K+ |: m' n4 u- T- L; OCatenary, 悬链线- P* w9 ]7 J9 S$ k' b7 f
Cauchy distribution, 柯西分布
& Q1 E% n7 e( {Cause-and-effect relationship, 因果关系- q! m Q6 |9 h; e9 Q8 {3 t6 \
Cell, 单元
3 E5 |& X- ]( lCensoring, 终检2 a* z+ e/ l. [. T8 X$ ^7 ~: E
Center of symmetry, 对称中心
4 e/ [6 w( I" b6 D5 BCentering and scaling, 中心化和定标
4 n7 H9 m, P) q# a5 W8 kCentral tendency, 集中趋势2 |' ]8 b+ m9 X) Q5 ~3 V2 z5 P
Central value, 中心值" b3 S J7 E) ?+ q, r' u
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测3 W$ N8 i# B" G
Chance, 机遇
4 d# c4 t# d7 t* Y; w5 ZChance error, 随机误差( o) e1 K2 [ g0 P
Chance variable, 随机变量- L( S3 @+ |8 H3 b
Characteristic equation, 特征方程
4 Q) y* `) a6 O& W8 A6 \1 _Characteristic root, 特征根
3 R/ i) v2 G2 M4 W% uCharacteristic vector, 特征向量, G9 g; m4 [5 A1 v$ }
Chebshev criterion of fit, 拟合的切比雪夫准则
" J% `& A; A1 q2 D8 s2 eChernoff faces, 切尔诺夫脸谱图3 L+ j/ Y9 S3 N7 h
Chi-square test, 卡方检验/χ2检验
0 o6 a7 D" x: oCholeskey decomposition, 乔洛斯基分解
( X; @" X2 f4 D8 N, A, H. s$ |Circle chart, 圆图
7 t5 \+ x( R0 Q0 d- P! nClass interval, 组距
8 r$ c; Q& T' u, B% OClass mid-value, 组中值8 J$ \$ ~% n/ h7 c1 Z8 o
Class upper limit, 组上限
* |0 s+ E0 M; `/ ^* t7 Y1 U, ^Classified variable, 分类变量
& r. k+ h* K# E- o9 hCluster analysis, 聚类分析
; E) o% U) F! O1 S3 YCluster sampling, 整群抽样
6 H4 R. g, d& {) F+ dCode, 代码5 e% E8 F2 w" ~; d1 ~; R* E7 q2 X
Coded data, 编码数据2 G1 t4 [; w: q+ t
Coding, 编码: F9 A1 i% Z& T
Coefficient of contingency, 列联系数& `/ G/ j$ [$ s! T, C) j
Coefficient of determination, 决定系数
/ A- i4 n/ f: ]! C8 a2 _- kCoefficient of multiple correlation, 多重相关系数
9 D4 U5 f3 p8 I, KCoefficient of partial correlation, 偏相关系数6 J. b6 X2 T q h% d
Coefficient of production-moment correlation, 积差相关系数
1 @" q, Z6 ~$ Y4 [0 S9 j$ qCoefficient of rank correlation, 等级相关系数7 w' H' U$ v G( U+ |7 o
Coefficient of regression, 回归系数' V& W, P6 |5 W
Coefficient of skewness, 偏度系数0 A2 t4 `' H6 z" D/ s# X: B$ I& L
Coefficient of variation, 变异系数, K, e$ C; m( n% j5 ?, W# ~- x7 f: G7 q
Cohort study, 队列研究4 Y* x$ K2 ]$ t2 w9 C: W% U
Column, 列) I3 }6 I" {8 j" r; w0 a/ X
Column effect, 列效应7 i/ ~5 j' }* q7 G( D
Column factor, 列因素) D! W) ~! Y5 v0 Z+ f, M
Combination pool, 合并
, g4 v( S- a& {Combinative table, 组合表2 R ` p( _, G5 i* A
Common factor, 共性因子, q9 r C: R/ p* N2 A
Common regression coefficient, 公共回归系数$ ]4 T* q& X7 [0 T
Common value, 共同值
|2 h2 O8 G7 U$ L) SCommon variance, 公共方差" H6 q6 C7 q) C' Q) H4 [9 w8 a1 }
Common variation, 公共变异
+ ^7 b1 \1 C4 u3 G( Y5 XCommunality variance, 共性方差# m# T- \8 t1 L# Y
Comparability, 可比性
; I( Q5 X* N8 X- ?, b! MComparison of bathes, 批比较! d$ J. x8 A5 g- V
Comparison value, 比较值
# a. b0 x1 N- O2 [- V9 F2 LCompartment model, 分部模型
! w6 `* X& R( OCompassion, 伸缩
6 P) t) s7 }9 `0 n3 qComplement of an event, 补事件7 l& W( O1 a# Z9 l
Complete association, 完全正相关
6 P+ K4 ?4 J& t6 O# |# SComplete dissociation, 完全不相关
: n2 E: w+ q B( b' S; {3 jComplete statistics, 完备统计量
7 w" `" Q; n7 R2 V8 e2 @: `Completely randomized design, 完全随机化设计% F+ H! Q: @* h/ c' b, a: O
Composite event, 联合事件
- ?* v3 Y& i" j. q7 `& kComposite events, 复合事件
$ |# F a9 r( M0 w: WConcavity, 凹性
+ d' J+ U' f0 {Conditional expectation, 条件期望( i# v, h/ @3 ?7 ?* G e
Conditional likelihood, 条件似然
& u& q7 j: }' B1 KConditional probability, 条件概率
! {2 j* d- E0 @0 TConditionally linear, 依条件线性
: D2 l( C+ Y0 q2 {# l' f$ s3 {Confidence interval, 置信区间
; t9 G- G/ E. y' V% vConfidence limit, 置信限/ M- e2 Q& f6 u6 H: ]) @
Confidence lower limit, 置信下限: u% q1 M6 [- l
Confidence upper limit, 置信上限) l, n8 \$ w- F7 D/ Q( B
Confirmatory Factor Analysis , 验证性因子分析8 b' `" m! k( a: x6 n& j6 `; y' p
Confirmatory research, 证实性实验研究
s1 {- U: \ k. w# s! T9 wConfounding factor, 混杂因素* _: }+ O9 Q' s% w* F! t+ q
Conjoint, 联合分析2 z3 `6 a r8 ^
Consistency, 相合性2 K: @5 f% H3 q) t w
Consistency check, 一致性检验# O5 H) Q1 \' [( T! t3 a
Consistent asymptotically normal estimate, 相合渐近正态估计: q6 R ?- h0 v
Consistent estimate, 相合估计
8 ~+ l+ |" U* b" c. \ rConstrained nonlinear regression, 受约束非线性回归
+ Q2 Y( C5 |* N8 D; b" LConstraint, 约束 |. h& F% F. T9 ?: \8 I* P
Contaminated distribution, 污染分布
! S' a2 ~; u# k' w! gContaminated Gausssian, 污染高斯分布
W: N! T: [9 {9 A4 _6 m# r% Q# ?Contaminated normal distribution, 污染正态分布' r) k# v! ^ {% u
Contamination, 污染3 V6 |5 u7 j' P7 |. U
Contamination model, 污染模型
' e, y3 k& V" E2 @Contingency table, 列联表+ ^8 E% [4 @) }7 ]8 m9 N
Contour, 边界线$ ^6 b0 g" X/ z3 o3 J
Contribution rate, 贡献率
) Z9 Z' B6 F/ nControl, 对照( I% p0 Q5 o; a
Controlled experiments, 对照实验
9 G/ L; f* |8 { {/ U( E' ]4 wConventional depth, 常规深度( B) j" H. {- W4 I R) |5 i
Convolution, 卷积
6 [+ x" x( z) z# V0 ECorrected factor, 校正因子
- J( z0 F5 L2 u( q5 zCorrected mean, 校正均值* F: K. ^, u8 T+ g& g" i+ u5 M
Correction coefficient, 校正系数
; x4 _# V3 A: w) s& CCorrectness, 正确性
9 m6 E5 Z- C( A. v! ?Correlation coefficient, 相关系数' g- _% c% m& R, P' T
Correlation index, 相关指数, Y5 H. Q$ k8 i
Correspondence, 对应% I; A9 j( }: k& ^+ m* S; \
Counting, 计数
) L+ B" P4 i0 fCounts, 计数/频数/ B! p: {7 _+ {7 |. ]
Covariance, 协方差
8 ]* C3 i, P" @8 a6 b7 V7 fCovariant, 共变
( Y) p& d/ h4 O( E* lCox Regression, Cox回归2 J f2 E5 n: ` j/ _
Criteria for fitting, 拟合准则5 m( N! L% K) _- J2 Z" U% [
Criteria of least squares, 最小二乘准则0 U5 ? H# g, N1 R/ P$ {/ o
Critical ratio, 临界比
- J/ x& G p+ g1 K1 |; b# N3 ACritical region, 拒绝域, P1 U; T# w% w' [% Q1 v
Critical value, 临界值
9 p9 v! X, M+ J+ d4 y5 hCross-over design, 交叉设计
7 y! X* C* z3 ?; k7 f( d& y8 rCross-section analysis, 横断面分析
! ]0 h3 Y, O: s, u: WCross-section survey, 横断面调查$ j* h# b' R6 ]( x5 _
Crosstabs , 交叉表
# o& p: g; o+ ]( B' uCross-tabulation table, 复合表
, `4 z7 H9 k+ z7 V. I( D9 wCube root, 立方根
( ?# Q6 r3 [$ _1 F. SCumulative distribution function, 分布函数
6 c2 p0 N# `* @+ X/ iCumulative probability, 累计概率6 Q: ]9 n; B n4 g D0 ]
Curvature, 曲率/弯曲
" @, q5 D$ c; f2 bCurvature, 曲率# s7 e @' [- ?# c" c
Curve fit , 曲线拟和
, ?4 ^, w$ t% K w2 L$ }Curve fitting, 曲线拟合
( ~5 H6 k! \% R3 j- h6 W3 LCurvilinear regression, 曲线回归6 s0 G- v) c% H( T5 \% W
Curvilinear relation, 曲线关系# Q- L& `4 f U5 ^$ W" Q
Cut-and-try method, 尝试法
, U* V, c# U- G0 ^: R. K8 eCycle, 周期, m9 r1 G1 J3 ?- }
Cyclist, 周期性( \' S8 ?# z1 @2 b
D test, D检验
6 ?' X& K! l3 s( v1 h2 iData acquisition, 资料收集
9 C, j5 b2 p+ _1 pData bank, 数据库( P: h9 ~: _3 h; c$ o) |
Data capacity, 数据容量
% y, P) B% ]8 y4 Q6 HData deficiencies, 数据缺乏
4 [0 [- C9 l' G3 e) \. e AData handling, 数据处理
9 ^/ v' A- h% Q. LData manipulation, 数据处理
- t1 J Y1 i- B$ e) [Data processing, 数据处理9 Z |+ U. y" G* e7 T, Q0 l4 X
Data reduction, 数据缩减
! F0 d% R0 Z7 G3 P! [2 LData set, 数据集! Y. W1 V$ p& d: Z, g
Data sources, 数据来源
7 ~* z* _1 s' O5 _2 U9 K y8 lData transformation, 数据变换: d# v8 x4 a9 G( A
Data validity, 数据有效性4 Y& r5 R) t# {- W
Data-in, 数据输入/ b$ ?0 v8 o. l% G. E# I
Data-out, 数据输出; `8 [1 {4 k4 x+ u) ~5 d" z
Dead time, 停滞期& t5 ^- [& i& q2 K' p! s
Degree of freedom, 自由度
4 V6 M/ X0 f6 C4 e7 cDegree of precision, 精密度
4 j* Q6 E# j! O3 j. o. z& XDegree of reliability, 可靠性程度. f* ?( u! S; w% C' i% Q% y
Degression, 递减
3 [; b! j4 S, p% T/ l+ H; ZDensity function, 密度函数9 | s! i- C8 Q k5 I" s
Density of data points, 数据点的密度
+ [* P( {6 n# o8 J* u3 f7 tDependent variable, 应变量/依变量/因变量
/ a. L9 r0 m- k. {( SDependent variable, 因变量+ ~7 ~# f: d# P+ @1 K1 t
Depth, 深度2 q4 p& H8 o3 R. x7 i/ [) t* D8 T* v
Derivative matrix, 导数矩阵) e7 ?2 a7 B7 \3 e7 V3 M; o
Derivative-free methods, 无导数方法
" r6 `; K/ Y- G5 K6 b4 kDesign, 设计
& j& T" g; P9 L: t) {% TDeterminacy, 确定性
0 w! L: c l# I; G/ |. UDeterminant, 行列式
) j) p- z5 T, r# D5 iDeterminant, 决定因素) Y0 I8 p0 o5 u5 X' o. i
Deviation, 离差
8 \; I. e) G/ H" a5 r4 |/ {Deviation from average, 离均差' B) l, _3 V7 I. ]1 d% W1 H
Diagnostic plot, 诊断图
2 X, k7 p( u1 g( jDichotomous variable, 二分变量8 r# a- y m. f
Differential equation, 微分方程8 G7 }- t C! Z6 p& r, Z# j7 p) e
Direct standardization, 直接标准化法
# q, [. W8 Y4 q. k8 o* EDiscrete variable, 离散型变量; S/ [; N3 @/ l4 e- P7 `) F
DISCRIMINANT, 判断
4 K8 W/ n9 b0 x2 ]. s, T5 FDiscriminant analysis, 判别分析9 j7 K$ l, v. `: L$ g7 q
Discriminant coefficient, 判别系数
* e: \; c5 Q" a9 |$ `2 f# PDiscriminant function, 判别值7 r7 T/ ?8 ~/ N
Dispersion, 散布/分散度
. z% J& Z& _6 v5 x( ^ L- D! W6 h0 `7 [. KDisproportional, 不成比例的
. ?8 a6 x! e! v+ mDisproportionate sub-class numbers, 不成比例次级组含量0 H7 O5 w& Q, ~: V9 b8 R
Distribution free, 分布无关性/免分布
3 u, \0 c* ^% P% e9 ^$ PDistribution shape, 分布形状$ V. F; i( Q1 o9 D [8 i- u
Distribution-free method, 任意分布法
% `% l( }5 I* z+ UDistributive laws, 分配律
! A6 _" Q% A( h( ^% F$ rDisturbance, 随机扰动项/ R. W. ]( [/ I2 V0 P* }& T- W
Dose response curve, 剂量反应曲线, Q6 x6 D. b# s, A# u# C) }
Double blind method, 双盲法
# Z+ S. f* U! H2 c8 H! }Double blind trial, 双盲试验$ p* A" O D( p. }9 m0 q2 Z; C; `
Double exponential distribution, 双指数分布, q; _* b' y4 c! R
Double logarithmic, 双对数4 X C$ E+ f* {' T) H: E4 x
Downward rank, 降秩/ D. J m5 T7 J+ K" ]
Dual-space plot, 对偶空间图
0 n P \6 A$ G/ d2 |DUD, 无导数方法! ~2 q6 |6 B6 c5 o: v+ r
Duncan's new multiple range method, 新复极差法/Duncan新法
* L+ I* V: @9 L6 q, K7 T8 Q0 |. sEffect, 实验效应& w7 s, R8 ^/ S3 H% _0 p- c0 m
Eigenvalue, 特征值) b1 @) g! e: h. k- ?9 {& e
Eigenvector, 特征向量1 Y# e& b! Q# c/ W: l! y9 n
Ellipse, 椭圆
# v% O5 {9 M/ K ~' L2 kEmpirical distribution, 经验分布# ?6 I6 v# A" R. G
Empirical probability, 经验概率单位) P4 i( T! d5 M1 W
Enumeration data, 计数资料/ n# h8 G. X+ L; c+ | ?- l
Equal sun-class number, 相等次级组含量
7 `: ^( P8 l+ y# A$ XEqually likely, 等可能# t4 t+ S8 `% O2 E/ c
Equivariance, 同变性
3 u+ x1 x- g* i. v9 oError, 误差/错误: I9 u7 \) g- n9 t7 ^( E
Error of estimate, 估计误差: B8 g' d! R Q: Q# c
Error type I, 第一类错误& J- Y, X6 u, A/ I+ E; O/ G i
Error type II, 第二类错误
3 Y" X" J2 x8 @( d/ \" k# n' _! gEstimand, 被估量: F0 }' d8 X1 n! a
Estimated error mean squares, 估计误差均方
+ ~# |6 I# s6 Q A. ?8 S6 R) h% WEstimated error sum of squares, 估计误差平方和
4 V5 Y7 N7 _7 f' g) gEuclidean distance, 欧式距离
) b! i. A# x5 m& D9 s) O! r kEvent, 事件; A) r' \4 t* y3 w' g
Event, 事件0 S7 ]1 j) f' k3 u
Exceptional data point, 异常数据点
! f5 P# c Q" z6 V9 ?9 AExpectation plane, 期望平面
" W$ {- |5 s9 b) t/ FExpectation surface, 期望曲面( Q) ?: r- X5 \" t u( O
Expected values, 期望值/ A# m3 E7 Q: q
Experiment, 实验, ^& n& F1 I3 a+ C+ W2 m) {1 n
Experimental sampling, 试验抽样
( l4 L) a% Y* xExperimental unit, 试验单位8 n$ |: M3 A0 D% Q
Explanatory variable, 说明变量+ i0 D( e1 c g5 v
Exploratory data analysis, 探索性数据分析$ ~5 _# m5 t3 Q9 B, y E
Explore Summarize, 探索-摘要6 t% D% W; G& s. C
Exponential curve, 指数曲线
4 k; P0 ~* t7 M4 {" Y" X+ \Exponential growth, 指数式增长: Q7 O. o$ U# S5 G" n# y
EXSMOOTH, 指数平滑方法
: y5 S+ g; _' V/ ?: f( A& S) PExtended fit, 扩充拟合
- m+ k2 L" _! k" D. C. [8 _Extra parameter, 附加参数
& t/ N9 ]9 ]/ n, c- J @9 BExtrapolation, 外推法
5 S# K' \ r# g9 ~3 {2 i$ v2 ~7 PExtreme observation, 末端观测值$ e1 G' Y2 ?( r5 S3 }1 ?
Extremes, 极端值/极值! Z& Q& e% {$ A
F distribution, F分布
/ x0 ^' t, L2 o7 @. Q& D2 q$ bF test, F检验: q! j+ c8 k5 M( n* \
Factor, 因素/因子
: x2 e9 R9 ~& R" M, Q2 ], MFactor analysis, 因子分析
. X/ k9 K$ r7 t" MFactor Analysis, 因子分析) Y" A% K2 u2 U: ]" P; o7 b7 K( d* b! G
Factor score, 因子得分 5 ^% _# G4 q0 _) T9 u& M
Factorial, 阶乘4 {4 d$ T' m+ d( o `
Factorial design, 析因试验设计
& H7 f' J4 q; b7 l/ i$ r( g( xFalse negative, 假阴性& _ @: ?* Z% M9 o
False negative error, 假阴性错误
* N5 Z7 R& z+ Y+ |9 N$ o' [. {Family of distributions, 分布族& M9 ]# o$ r% B0 K& ~4 V/ r
Family of estimators, 估计量族
) s/ E v$ e9 kFanning, 扇面
9 ?: ~% c3 g; s; w- g% }/ BFatality rate, 病死率* {; b5 k# Y. H& }
Field investigation, 现场调查
' \4 K) Z4 O; s5 F( TField survey, 现场调查# M) w: ?: {7 t
Finite population, 有限总体( D. c! L3 K" ^, I5 q; L
Finite-sample, 有限样本
4 Y' T; B' z8 H9 ]2 ]* W" S( n: |First derivative, 一阶导数
& j2 H! W5 ?' ]First principal component, 第一主成分8 b9 S8 Y$ X* Q2 a; Z
First quartile, 第一四分位数
1 Y! |1 g" o! }- hFisher information, 费雪信息量
& w6 T$ h6 g% B! g- F: F- \Fitted value, 拟合值2 k4 d3 P% ~ X
Fitting a curve, 曲线拟合9 C2 O) N) E! w1 R1 [; n2 V7 O8 D
Fixed base, 定基, G, ?: c1 K' \) ] _/ X$ O5 @
Fluctuation, 随机起伏& `5 m$ ~) Y5 p; p. H% d
Forecast, 预测, y, V, \ a7 ?+ r7 @
Four fold table, 四格表2 l! {( {6 x( ]4 o8 f+ A* K; j* ?
Fourth, 四分点
+ i/ b: f" v: q4 M; n# fFraction blow, 左侧比率6 s E" f& u6 ~2 W$ L4 N5 I- V
Fractional error, 相对误差% L# U7 {5 E5 R! w* t7 d* M, y0 i
Frequency, 频率1 e5 d5 l+ r: ~* d
Frequency polygon, 频数多边图
' g# F$ [# A( ]+ s5 j1 XFrontier point, 界限点
$ B5 \/ e, j1 ?5 C% |Function relationship, 泛函关系. l% x) C& D* {
Gamma distribution, 伽玛分布
- M/ b" j. o% N3 rGauss increment, 高斯增量
9 F* b! C$ ?6 Y4 g: {* [5 gGaussian distribution, 高斯分布/正态分布% R' y8 f) G6 a$ M( O8 B1 H
Gauss-Newton increment, 高斯-牛顿增量# p+ a2 Z! T+ M7 P
General census, 全面普查4 ~' ~7 v% A4 y4 D! R4 t% _
GENLOG (Generalized liner models), 广义线性模型
+ r: v/ p+ p* h& m$ C' p4 F8 HGeometric mean, 几何平均数
, u: e, k% c. p1 M8 r6 GGini's mean difference, 基尼均差8 d$ h# [$ r) ^7 x2 u, e
GLM (General liner models), 一般线性模型
- a, C( Z6 n# l x ?Goodness of fit, 拟和优度/配合度
6 t: d& y6 z6 U. uGradient of determinant, 行列式的梯度/ Z/ S+ L+ s- g# t
Graeco-Latin square, 希腊拉丁方+ G8 i; { G6 p2 L/ P) S
Grand mean, 总均值
& s% U5 ]9 F/ `, B3 G5 GGross errors, 重大错误
% O+ W* k8 F8 o2 _+ @+ JGross-error sensitivity, 大错敏感度
& e7 k+ M& l4 A# O/ @8 `Group averages, 分组平均( F( `. p/ z" Z: t4 P; ` d8 |
Grouped data, 分组资料
) w2 q! ?9 C$ o0 m {Guessed mean, 假定平均数
. v. {& e6 ^8 ]% K- V2 r: E u3 s0 UHalf-life, 半衰期0 u O+ d( ^9 g/ h& w: y5 ^+ o
Hampel M-estimators, 汉佩尔M估计量) X) E4 o( i5 s, f; {
Happenstance, 偶然事件8 q3 k. s* W+ m5 r
Harmonic mean, 调和均数" C# n" S' f$ u
Hazard function, 风险均数
) p9 ]' i; W: t( |, E, OHazard rate, 风险率
K" F" K. }6 t6 R, q1 H0 @Heading, 标目 9 M6 [2 }, w7 }6 Z
Heavy-tailed distribution, 重尾分布
2 f$ t2 v) o% J5 Y* a3 t" f: n" {Hessian array, 海森立体阵
3 Z" b: \$ B0 {* D& gHeterogeneity, 不同质
6 ^( Z j: X# o; d r, p" r: ~Heterogeneity of variance, 方差不齐
8 e. u% h0 S/ B! L6 ^/ f# |; F& NHierarchical classification, 组内分组
' r8 o8 f- _: k5 q$ FHierarchical clustering method, 系统聚类法
! W! p; z2 g9 ] ]) ?, tHigh-leverage point, 高杠杆率点; k6 t* Q0 ?: h
HILOGLINEAR, 多维列联表的层次对数线性模型
4 z! G1 j5 i/ @. ^+ R6 A, DHinge, 折叶点* ~* _& H! \% B2 p9 \* W
Histogram, 直方图1 |# ?8 m+ C v0 B% R% R
Historical cohort study, 历史性队列研究 + ]' b- F; g h ?% ]) }
Holes, 空洞" {6 W3 q" v4 t, M& S
HOMALS, 多重响应分析
7 B$ g V% ~) h; ~Homogeneity of variance, 方差齐性( g8 _# X( P9 X4 J, @
Homogeneity test, 齐性检验1 Z6 i4 _! D: [4 P& U
Huber M-estimators, 休伯M估计量% W/ r3 ?* B, r
Hyperbola, 双曲线
- L4 a8 ^% F0 p" oHypothesis testing, 假设检验
; h5 f5 Q1 e+ @ R& o( ?Hypothetical universe, 假设总体
" D& w" a2 V1 g3 X$ ?Impossible event, 不可能事件! A0 d' v# ~6 B2 l3 p
Independence, 独立性0 M. n: [4 g! F0 j4 U% O( S' s* n3 `
Independent variable, 自变量( F B4 k' N) M# t- A7 F. i3 L7 y6 B
Index, 指标/指数
8 L' \: i8 N9 zIndirect standardization, 间接标准化法
( F8 ?! X/ N, Z! u1 d6 aIndividual, 个体2 D( L" c9 q$ Q3 G& I0 i" N* A
Inference band, 推断带
. z' H" X" o1 [% ^* p a, AInfinite population, 无限总体
+ k9 Q; m. ?/ Z: i; UInfinitely great, 无穷大
# i2 x0 ? l5 UInfinitely small, 无穷小# [% W' B9 D5 [
Influence curve, 影响曲线
3 B: r& h3 y" y! oInformation capacity, 信息容量
) D( @. ]4 A! }; V/ j VInitial condition, 初始条件; X# ~+ K- b. J
Initial estimate, 初始估计值- n+ V. t( M. S% _8 F$ L j }; `
Initial level, 最初水平5 G& X. }/ d2 F* l1 }
Interaction, 交互作用: K7 H6 Q2 `. Q: i, v Q* T
Interaction terms, 交互作用项
. J: l- O, |# t2 s$ `, {: [Intercept, 截距
" r% j7 E( V gInterpolation, 内插法
& L, I# Z x4 T& d0 C* W, A, YInterquartile range, 四分位距
3 r9 @9 W9 x% A9 ]0 oInterval estimation, 区间估计
4 I1 t( `4 f- I- qIntervals of equal probability, 等概率区间, c+ a, J1 ]4 r
Intrinsic curvature, 固有曲率0 H6 D/ m! ]' |. e
Invariance, 不变性
- D4 w5 } W( c/ ]4 z5 dInverse matrix, 逆矩阵+ @# E; [2 Z( @2 |
Inverse probability, 逆概率
" t+ o! c4 r' A7 b( r5 d+ U! wInverse sine transformation, 反正弦变换
3 ^9 e, E" l6 {' p% nIteration, 迭代
1 V: M' G4 v1 u4 p9 Q& jJacobian determinant, 雅可比行列式$ `1 E. o( a$ ]8 D9 N
Joint distribution function, 分布函数
5 J& V* B4 a* F1 K4 o* UJoint probability, 联合概率
+ u, @/ _6 f' C$ b9 _5 T4 WJoint probability distribution, 联合概率分布
. U1 t# ?3 }! v3 g Z4 J$ UK means method, 逐步聚类法
0 E1 P! V7 F7 D* lKaplan-Meier, 评估事件的时间长度 . G$ r H1 Q7 A
Kaplan-Merier chart, Kaplan-Merier图
8 R3 D5 T1 f" K' o CKendall's rank correlation, Kendall等级相关
2 K, D! s8 y1 l8 c! [9 |Kinetic, 动力学
) L' K9 i. d2 {" `" N xKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
" |6 t$ d" e* n, r! _ n6 vKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验0 X* ~! C9 ]5 p+ y# V9 r
Kurtosis, 峰度" z- i. o# | O; \1 |
Lack of fit, 失拟; _2 g% z: S+ _$ ^" G$ n: s& e$ U3 A
Ladder of powers, 幂阶梯1 h* t, Z) C! K' |8 K( R
Lag, 滞后
' C! d8 C- Z3 b% HLarge sample, 大样本
8 b# E5 C. U2 ]* c9 rLarge sample test, 大样本检验5 l' C w( J4 \0 {- a* O+ {6 @8 c
Latin square, 拉丁方
, e7 P# L7 s f1 D+ vLatin square design, 拉丁方设计
9 ~' p; l! ^: `0 t/ l$ X0 n; VLeakage, 泄漏) ?( l! ^8 D @7 J! R- ]
Least favorable configuration, 最不利构形
# M$ @& O6 g6 t% Q7 y, J9 |3 [Least favorable distribution, 最不利分布$ j' L% R: U4 }) b5 C& f- N
Least significant difference, 最小显著差法
9 ?) r4 |$ G( f2 v# FLeast square method, 最小二乘法
/ O: q- C! A [: a. f2 H( T/ ]Least-absolute-residuals estimates, 最小绝对残差估计& p& t2 J0 ]6 G W0 ]) v4 o- {
Least-absolute-residuals fit, 最小绝对残差拟合, W* W$ p8 M! l4 M( H6 C; M
Least-absolute-residuals line, 最小绝对残差线
! Q( t. Z/ y) [) ]/ |1 ^) e# Q0 F% ]: iLegend, 图例
( w6 Z' s9 C, ^' N. u6 uL-estimator, L估计量) ^) b, i; O/ Q% `4 I- |1 j' \
L-estimator of location, 位置L估计量- @9 D s2 R% Z( c) d' q
L-estimator of scale, 尺度L估计量" B r1 ^( }9 P
Level, 水平
8 U; {* h- y! }8 pLife expectance, 预期期望寿命
9 }( R- N! v. F/ N& u2 [0 `! n/ CLife table, 寿命表, F6 V+ `3 b" T- C7 K
Life table method, 生命表法3 Z0 O: U. H* P4 j! f7 @2 H7 k5 h
Light-tailed distribution, 轻尾分布! @/ `1 K- n: B; v7 L( o, x
Likelihood function, 似然函数 e4 o# O6 {% p- N* m: V3 S/ A
Likelihood ratio, 似然比
- }0 t! j. y1 M# zline graph, 线图! z% T5 D& M( H1 A( w
Linear correlation, 直线相关" ]3 s* C# J% L2 @% q
Linear equation, 线性方程' |" V7 q! f0 K* ^
Linear programming, 线性规划
" P) D4 k5 p! A: ELinear regression, 直线回归
9 v9 t F0 Y4 `7 k- e6 vLinear Regression, 线性回归
, B* _2 z1 y( ]! k/ kLinear trend, 线性趋势
% Z0 N7 Y& `7 G$ e: Q8 ^7 KLoading, 载荷
9 |7 t7 }9 F7 a# F T2 X6 A7 xLocation and scale equivariance, 位置尺度同变性
0 @ h4 [$ R8 r" t7 k6 wLocation equivariance, 位置同变性
: b, q2 n8 C QLocation invariance, 位置不变性
+ |+ C" J. B* O0 Q) oLocation scale family, 位置尺度族
9 ~, E3 U% O$ DLog rank test, 时序检验
, |0 S1 B4 W9 U' ZLogarithmic curve, 对数曲线
0 }5 }# e( m" y: g3 u+ l3 C& ]Logarithmic normal distribution, 对数正态分布
) N% ^0 ~9 `* q3 X, I( _" A/ o+ rLogarithmic scale, 对数尺度! s' e: q+ m5 Q6 g3 W
Logarithmic transformation, 对数变换
0 s# d" r) w4 M/ L# d1 @& h2 [! T5 jLogic check, 逻辑检查+ c) Q$ F+ V4 y. h5 n8 U6 T' v
Logistic distribution, 逻辑斯特分布
, R" E u# |: K) ?1 YLogit transformation, Logit转换
# d; v0 x" h2 V+ Z4 y. x" h6 _ bLOGLINEAR, 多维列联表通用模型 # c8 I( g0 x* A2 j- j
Lognormal distribution, 对数正态分布! h7 m2 c% v6 }7 r$ O
Lost function, 损失函数
4 o. h& w5 `; ]Low correlation, 低度相关1 E; N* O) G3 g) a6 W
Lower limit, 下限
$ }, j; t: T' P8 b; a/ H3 eLowest-attained variance, 最小可达方差. n3 R9 {. g* o& L/ G
LSD, 最小显著差法的简称* c( g5 p* O( Q! L" D X5 } U
Lurking variable, 潜在变量
: w6 {2 \* V: Q8 F; K$ [Main effect, 主效应8 t/ _* K8 \3 b$ S
Major heading, 主辞标目5 Q" \. g0 g# C7 H
Marginal density function, 边缘密度函数
4 z- T$ `! t! n# a \+ G6 ^Marginal probability, 边缘概率9 _7 T5 |: y' p j5 `, Z5 A
Marginal probability distribution, 边缘概率分布
6 ~- H- w' C2 z- g: I; zMatched data, 配对资料
3 T6 f7 K! N! F0 PMatched distribution, 匹配过分布
7 I3 P, v" u# @1 z% [. g4 HMatching of distribution, 分布的匹配! {6 |, U/ ?$ b5 k! L' k" ~- M( `
Matching of transformation, 变换的匹配
. w( \1 Y' I6 bMathematical expectation, 数学期望0 m) n) ?& i. t- P5 j0 M5 C, ]; k
Mathematical model, 数学模型
3 g" L( G- E& X$ ?) v, b6 E' WMaximum L-estimator, 极大极小L 估计量
6 W$ ^5 s" Y; gMaximum likelihood method, 最大似然法
! ]! A1 i9 u. _( n8 C! n0 yMean, 均数3 }( ]: T/ ^7 }
Mean squares between groups, 组间均方) j. `2 \) I$ s: D. g; r$ f) P, @
Mean squares within group, 组内均方. s8 n. I; x9 M) c5 {/ w, z
Means (Compare means), 均值-均值比较# L5 M/ S: } k! c
Median, 中位数$ e2 E/ d- A8 V6 \
Median effective dose, 半数效量: @! f( H3 h. {# a; w
Median lethal dose, 半数致死量
- |1 m9 w* ^0 b r" {Median polish, 中位数平滑
9 N: `2 {! o! C; wMedian test, 中位数检验5 N( I0 D( P7 X* J$ q
Minimal sufficient statistic, 最小充分统计量4 p* H. j m$ l
Minimum distance estimation, 最小距离估计2 i, N$ V* s0 A8 s* ]
Minimum effective dose, 最小有效量
) P0 J7 Y o+ {, s8 _; g, [Minimum lethal dose, 最小致死量
: h' w- w5 E% p7 g" ^Minimum variance estimator, 最小方差估计量' L( [+ p1 E% J2 N: Q
MINITAB, 统计软件包& V- J3 W2 b& A9 a2 l8 N0 F
Minor heading, 宾词标目8 _4 m/ h6 W! K9 l4 e
Missing data, 缺失值
- y% l0 i6 B4 @& c" f- ~+ @Model specification, 模型的确定
3 q- h% r$ r/ P9 K6 ZModeling Statistics , 模型统计: B8 B, S4 Q m& P+ q
Models for outliers, 离群值模型% A8 a5 n3 n3 i5 t+ o3 E+ a
Modifying the model, 模型的修正- t0 _' D( H! [, j- U a! z
Modulus of continuity, 连续性模
8 ]: h+ z9 `3 D& c0 ^2 x& |# UMorbidity, 发病率
4 ~* O; |$ G: }" W1 v0 t8 ?Most favorable configuration, 最有利构形. u! N+ S% d- R7 S# G
Multidimensional Scaling (ASCAL), 多维尺度/多维标度% _- ~! \( E) x- F4 F7 \9 }
Multinomial Logistic Regression , 多项逻辑斯蒂回归8 z' L3 o, i! Y9 {
Multiple comparison, 多重比较8 U- N/ j0 t! Q0 k# Z" S
Multiple correlation , 复相关& U- F Z/ i+ {5 c
Multiple covariance, 多元协方差9 ~+ u% P( i; L; _ J3 y. Z3 p1 M
Multiple linear regression, 多元线性回归5 w( {# `, R! b' D2 I" R) z
Multiple response , 多重选项
( o8 f1 w* T" m. c1 s! s7 iMultiple solutions, 多解
% Y G& \( N0 P9 zMultiplication theorem, 乘法定理
7 { E/ }4 Y1 s0 m9 Z4 }0 QMultiresponse, 多元响应9 Q2 n! u$ h. @5 ~( X
Multi-stage sampling, 多阶段抽样( E. a, H4 d9 @
Multivariate T distribution, 多元T分布6 W* f/ O3 m4 ~% h. T- v6 C
Mutual exclusive, 互不相容" c9 m0 |' A9 a$ x4 o% r
Mutual independence, 互相独立" e9 i* O" d T; a5 g
Natural boundary, 自然边界& c5 r" `# M0 ]
Natural dead, 自然死亡. F2 U2 B& l/ D" Z' O! J' Z
Natural zero, 自然零
, l. ^- a" L- U2 y2 E' Q wNegative correlation, 负相关
: b6 a& B; K7 oNegative linear correlation, 负线性相关
1 A! x; M) [ x( n% u5 H4 SNegatively skewed, 负偏
0 p, V0 P1 p) {( V' D! X. o3 pNewman-Keuls method, q检验6 Y Y7 \/ M( X& E
NK method, q检验
. Z7 o+ B r5 Z% \2 GNo statistical significance, 无统计意义( l2 {& _0 o$ P: j7 `" c6 ^
Nominal variable, 名义变量2 N1 K4 y/ ]9 L; E# U3 N
Nonconstancy of variability, 变异的非定常性
2 u$ e* D3 N& |$ p1 i2 ZNonlinear regression, 非线性相关
- H- e8 q! w8 ^% |* ~' h$ G2 l; JNonparametric statistics, 非参数统计
. y5 a/ ^$ s% j5 kNonparametric test, 非参数检验0 d5 E3 N) [6 o& f8 s; k/ B
Nonparametric tests, 非参数检验
; O- d$ ?8 J# vNormal deviate, 正态离差
2 ]* a, O1 Q( c4 LNormal distribution, 正态分布
1 j- A( P; }7 B6 f A9 C# T2 ?Normal equation, 正规方程组2 {7 Q# l; G" f4 J8 p6 H4 z
Normal ranges, 正常范围
: G/ k* j: U- o) {# f9 s. yNormal value, 正常值
" h: p. g; C: w! Q1 W5 uNuisance parameter, 多余参数/讨厌参数
! ?! j; R X8 I; }0 j; UNull hypothesis, 无效假设 9 V9 @7 I& w5 G5 O& ]; l7 O
Numerical variable, 数值变量$ D( t) P+ L0 |1 c: K E: |
Objective function, 目标函数
7 B" n. F7 m2 V$ w3 q6 C/ d& xObservation unit, 观察单位- X% y! Z0 F( ]9 |- r# K( Q
Observed value, 观察值
8 G6 c- d! T* a% `/ Q0 ^) ^2 K" tOne sided test, 单侧检验& S) z6 E3 @4 o+ h8 l
One-way analysis of variance, 单因素方差分析/ U% h$ }8 e p2 E0 W$ C% _
Oneway ANOVA , 单因素方差分析
+ L4 L8 a T& T$ {0 Y0 q* OOpen sequential trial, 开放型序贯设计! m$ E! g4 _: u3 B" ~& U
Optrim, 优切尾
1 J7 T/ u: W6 ~) a% s+ {Optrim efficiency, 优切尾效率
( V! I6 U5 L" T( o% ]1 X& f# S/ yOrder statistics, 顺序统计量
1 T$ I$ q1 }5 P! V: cOrdered categories, 有序分类
) M( {. U, T. ]. }9 m9 XOrdinal logistic regression , 序数逻辑斯蒂回归2 O) }! p% w/ f6 ~
Ordinal variable, 有序变量* Z M* }. p7 B5 `- r' f8 t
Orthogonal basis, 正交基4 _+ b) B! q8 H! s7 Z/ w5 t
Orthogonal design, 正交试验设计! p! w: a' }! B0 I* F/ N# B8 h- N8 R- [* w
Orthogonality conditions, 正交条件
# F% m$ ~2 I' C) ]8 |ORTHOPLAN, 正交设计
* b7 L% V. ^6 U8 L! hOutlier cutoffs, 离群值截断点
7 D- c" q* u* k" j* W. YOutliers, 极端值
; j6 \$ K9 o7 q7 |- u6 @" ?2 YOVERALS , 多组变量的非线性正规相关
1 W' h, P; x+ W5 F3 tOvershoot, 迭代过度
! w3 Q+ {6 D: }& }; h- cPaired design, 配对设计0 ?9 @9 E" L G0 V; X& {# d
Paired sample, 配对样本4 ^ ~# [3 [$ k' I
Pairwise slopes, 成对斜率2 ]5 q { K1 I9 M
Parabola, 抛物线) f$ _% U. k# d1 g T( L. {
Parallel tests, 平行试验
4 z; S* u0 T/ q+ LParameter, 参数( b$ ^. Q2 O, Z3 ^3 n9 _
Parametric statistics, 参数统计0 h. o9 j7 N, n& f
Parametric test, 参数检验 U5 ]4 T3 y9 b9 u
Partial correlation, 偏相关
3 {0 B9 F: X7 N) Y; ]% F2 }Partial regression, 偏回归( b3 \2 W5 L. H* u
Partial sorting, 偏排序
" p+ m. G) [/ G+ |: P: ?Partials residuals, 偏残差
/ T$ h6 B5 C7 i3 u" x, b- pPattern, 模式
9 [1 \9 {# A* r/ R) _& y2 G& dPearson curves, 皮尔逊曲线
; x( }; c" ~; \Peeling, 退层
9 V% s- n# S5 |1 v5 a2 b h9 jPercent bar graph, 百分条形图* |% x+ T, A1 ?/ J7 e0 y
Percentage, 百分比
1 Q& N; c% N$ D1 yPercentile, 百分位数, i/ M F8 e1 w* ~* W
Percentile curves, 百分位曲线
* Z* t4 a0 t7 `5 aPeriodicity, 周期性; P* ]: W# `" v0 D4 C: O
Permutation, 排列
, W4 M8 q8 Q1 T2 a1 g4 XP-estimator, P估计量) j2 N. H& m, y5 n1 p* g
Pie graph, 饼图. k& Y* m4 W2 v' P$ @ e
Pitman estimator, 皮特曼估计量
- I' C1 K$ i+ o# q9 oPivot, 枢轴量. H: P7 X* r& {0 g) Z8 I9 y6 _& }( s5 \
Planar, 平坦
, E) c' n$ k P: rPlanar assumption, 平面的假设
; r: {& i9 o& X" n1 YPLANCARDS, 生成试验的计划卡
% L) @1 M" l' L D3 X& YPoint estimation, 点估计
& h- B0 T- V7 aPoisson distribution, 泊松分布- o0 ?( ?5 ?/ f T# f8 M* q: p% i
Polishing, 平滑( n: ^* q3 y2 d, @4 ^- D
Polled standard deviation, 合并标准差
6 j% J F( T7 A" B$ jPolled variance, 合并方差1 E7 v4 T) [- \9 k. ^5 Y
Polygon, 多边图3 u4 e$ @+ e1 _% R7 E; X
Polynomial, 多项式
( M) ?$ I1 Z. I. @& _Polynomial curve, 多项式曲线4 t: B0 l0 _( e6 d* ?
Population, 总体
9 v" o# U: m; cPopulation attributable risk, 人群归因危险度7 } W3 x1 j& B3 T/ x3 T
Positive correlation, 正相关
/ G' y8 O* T! w: [, RPositively skewed, 正偏6 _! n" C+ r% F3 \
Posterior distribution, 后验分布: [( `/ I" S J# y4 b l: H$ C+ t
Power of a test, 检验效能- E& Q, K3 S' W$ i3 i
Precision, 精密度
Q5 y4 t% L* e* Y, W9 t0 j( P3 JPredicted value, 预测值! d) s1 J s$ {" m4 w% a
Preliminary analysis, 预备性分析4 X W' Z5 h7 {6 B; {
Principal component analysis, 主成分分析1 {1 P( [- v& k: R F
Prior distribution, 先验分布
7 P3 ^& J0 |( {4 V9 @2 c8 f8 e' W FPrior probability, 先验概率9 j2 U ~1 Z) g5 g% F7 L
Probabilistic model, 概率模型% S% x, _/ @ u' f# t, {7 M- D
probability, 概率
$ Y2 }9 z# o$ K! [4 E: i% }. T8 L* pProbability density, 概率密度
, }4 m* z0 b6 b' P& v lProduct moment, 乘积矩/协方差! n g* @4 X! {+ j0 O$ a
Profile trace, 截面迹图* H9 l- h. v' j3 C5 n! d/ `
Proportion, 比/构成比: V/ w9 n2 i; ~. Q
Proportion allocation in stratified random sampling, 按比例分层随机抽样
% q3 j5 i3 `7 N( w8 y& T0 z3 [Proportionate, 成比例
5 O) F' F8 c% [3 I) tProportionate sub-class numbers, 成比例次级组含量
0 Z: @ r+ `" F; |Prospective study, 前瞻性调查
a6 e* V8 ~: v1 h ], I4 ]Proximities, 亲近性
" Z8 K6 O7 U, f% hPseudo F test, 近似F检验
( D' p" U1 y+ B/ }, c& ?Pseudo model, 近似模型9 H- Q1 [: q6 l- h1 m$ F
Pseudosigma, 伪标准差
7 n# F" U* X3 S3 {Purposive sampling, 有目的抽样
6 i7 Y: Q$ T5 H* s+ T! qQR decomposition, QR分解! r0 P# X% A% E: m; p/ ^
Quadratic approximation, 二次近似& E# y* ?. W/ w" w
Qualitative classification, 属性分类
$ R! V: r* t6 |5 QQualitative method, 定性方法
4 s' e7 B0 C% QQuantile-quantile plot, 分位数-分位数图/Q-Q图
0 ?9 \% e, F: F# c; J) a) a# vQuantitative analysis, 定量分析
4 E ~8 r! t; o! P1 ?! BQuartile, 四分位数
% \2 X& C3 D4 ]; p% g2 ]Quick Cluster, 快速聚类
$ V! V' v* U5 H1 s+ bRadix sort, 基数排序
/ b4 q6 H! e6 e% j! gRandom allocation, 随机化分组- e: @ }. L" R4 f1 T
Random blocks design, 随机区组设计( g" t. ~7 y/ {
Random event, 随机事件
" `& \+ m$ Z, `6 L8 h! ~Randomization, 随机化
( H: l( q' P2 C/ J% I4 }/ MRange, 极差/全距$ N! @* A8 a/ p" j, O% j* h
Rank correlation, 等级相关. O5 g: {" L* V% S
Rank sum test, 秩和检验) G+ s! N& K% G3 k& |7 B
Rank test, 秩检验: b* k& b+ t, Z/ _+ g" U
Ranked data, 等级资料9 M, i- k1 K" N2 T( O
Rate, 比率
/ R4 p% _' i" G ~, Z, T; mRatio, 比例
0 O2 x! Q! M; LRaw data, 原始资料
s! s$ Z E% x8 DRaw residual, 原始残差
( Q4 u ~9 X" B6 F* \Rayleigh's test, 雷氏检验$ k- o) A2 {! Z' j, A- x
Rayleigh's Z, 雷氏Z值 * l5 W5 V9 {# m S) @' P
Reciprocal, 倒数
* m7 m8 Q3 b2 g/ M2 h" g/ t3 XReciprocal transformation, 倒数变换
2 j: \' @; B1 qRecording, 记录 B# I& `) n0 ^! K; S/ B4 h1 l
Redescending estimators, 回降估计量! I9 r* ?; |! T. [- L, a1 A( C5 ?
Reducing dimensions, 降维9 g4 X; h# t, G( `& E- K
Re-expression, 重新表达9 j/ V9 k" R/ j+ J4 n5 _
Reference set, 标准组) [+ A, f8 v$ W# Z7 P4 U6 C& e( Y
Region of acceptance, 接受域# T6 J; ?, V, J- X& [; `
Regression coefficient, 回归系数
1 P6 J2 D, ?% O8 e! I% @$ f1 ^Regression sum of square, 回归平方和
. S5 G6 I8 w* q9 }Rejection point, 拒绝点
Q: Q- v: n& URelative dispersion, 相对离散度
A! T+ Q' K/ h. W: ?" eRelative number, 相对数
2 X5 s: H( {) _5 P/ ~Reliability, 可靠性6 x, ~" }0 X# ^7 ]6 x1 Y& v) z
Reparametrization, 重新设置参数/ U, H4 C- x/ W D
Replication, 重复
3 N0 }1 |1 _2 [. i/ A8 m! GReport Summaries, 报告摘要7 k# O9 Y* A1 X" F! ^
Residual sum of square, 剩余平方和
/ `( D' [$ r1 |: ?8 uResistance, 耐抗性
8 c. K- _" Z W, dResistant line, 耐抗线; P- \3 m# Q0 }/ H9 ?
Resistant technique, 耐抗技术
# p3 @* y0 L7 |R-estimator of location, 位置R估计量7 K4 n2 b \# M1 }
R-estimator of scale, 尺度R估计量
% R$ M4 \& W, Z, ^( k% ?Retrospective study, 回顾性调查
3 J! j% Q0 t8 _( e- lRidge trace, 岭迹4 A; W5 S" p; O `
Ridit analysis, Ridit分析
7 i7 t3 } a; `Rotation, 旋转* p; D5 r: [# e' G( k
Rounding, 舍入8 m+ p, ]' P9 S; m4 L. C+ N
Row, 行) C7 Y5 Y$ y# |) U6 l6 Y1 e
Row effects, 行效应; \9 {4 b9 P* \. v
Row factor, 行因素
, r1 C; s) u7 eRXC table, RXC表
2 ?" C8 o/ j* |$ Y5 W ?Sample, 样本) z0 j% x$ f0 m% r I/ v/ q
Sample regression coefficient, 样本回归系数, G* B+ Q3 j: J: t) z: {
Sample size, 样本量
8 `; u: s D: C6 c2 W* ZSample standard deviation, 样本标准差, p; U+ R5 k2 T- ^9 C m
Sampling error, 抽样误差
+ H+ |( z( ~8 dSAS(Statistical analysis system ), SAS统计软件包
1 F- b$ S& h( ]) vScale, 尺度/量表
( ^' W8 I9 n* R9 q# WScatter diagram, 散点图
- v/ C& X9 e2 [3 D) uSchematic plot, 示意图/简图
9 g) i3 y9 Y# b$ @' L# T2 OScore test, 计分检验& u! O* i* L- r! N* Y
Screening, 筛检% B; q+ c4 n$ T' M$ E) N
SEASON, 季节分析
2 a4 ~# H2 M- {3 H4 W/ P! mSecond derivative, 二阶导数
; a* k y- |1 F+ r: ZSecond principal component, 第二主成分
^: S% `* Q) |SEM (Structural equation modeling), 结构化方程模型 ; Z4 c [- Q! {' K, I
Semi-logarithmic graph, 半对数图
8 W& J3 B3 \5 h* C7 S" y& A! mSemi-logarithmic paper, 半对数格纸/ x+ I5 i0 @6 N' c
Sensitivity curve, 敏感度曲线( ?) ?, |1 E. q$ k/ h1 p i
Sequential analysis, 贯序分析
! E! z5 R, {4 p+ |& v% s+ _' zSequential data set, 顺序数据集9 T: ]% ~, w5 {% }0 v! W
Sequential design, 贯序设计
/ H0 a% x( f8 [ J2 NSequential method, 贯序法
0 |1 D# K) ^7 o$ zSequential test, 贯序检验法. F& w% a6 ?0 w/ z6 _
Serial tests, 系列试验) ^- }2 e" f6 N+ e+ f; M+ ]
Short-cut method, 简捷法 8 d6 r$ Z1 V, a5 `
Sigmoid curve, S形曲线' i0 v ^& x8 D
Sign function, 正负号函数* X$ E3 b1 ~! y. }2 Z
Sign test, 符号检验
% g" O N1 B$ h+ l& v5 P& ?Signed rank, 符号秩' [; F1 P* {- r+ |! d& j) {1 w8 X
Significance test, 显著性检验4 n7 n+ @1 l6 y8 ]2 i; N, z
Significant figure, 有效数字4 A' k! V5 n6 X* {& X# A- {2 Z
Simple cluster sampling, 简单整群抽样1 L) p" D; E2 [ a
Simple correlation, 简单相关4 b. c% c+ m' ^
Simple random sampling, 简单随机抽样6 G' `* \$ b. l" U
Simple regression, 简单回归3 S* O* T5 Y W+ Z N. T7 A
simple table, 简单表7 q0 J% ~" @9 l
Sine estimator, 正弦估计量
% m+ n: p& i8 V2 y( j5 jSingle-valued estimate, 单值估计
( u) n P# F: l4 BSingular matrix, 奇异矩阵
" t9 E! B/ c' @1 v3 U+ [. b6 K( iSkewed distribution, 偏斜分布5 b7 ~+ k1 s6 T! v& o; x
Skewness, 偏度
5 ?, V# O# b a+ ~, MSlash distribution, 斜线分布
/ `* q( A) J9 j% vSlope, 斜率) E4 Y. V& e( x. `. I, y# l+ ?, R6 Y
Smirnov test, 斯米尔诺夫检验
[$ I( w- A; l# e4 tSource of variation, 变异来源
( N8 N, L* ?5 R; q/ a+ ]Spearman rank correlation, 斯皮尔曼等级相关" p$ G2 o4 N# w7 r0 ^
Specific factor, 特殊因子, m, b( {6 N5 g( \0 F6 I
Specific factor variance, 特殊因子方差
1 x# p) S% B4 m" SSpectra , 频谱. @3 f3 E% \) B% p: @8 v
Spherical distribution, 球型正态分布* X8 t, o( P$ i# O2 x1 f' _# E
Spread, 展布' H) \1 P. L& k# @
SPSS(Statistical package for the social science), SPSS统计软件包/ ~* i+ L4 ~4 G# L k& ?
Spurious correlation, 假性相关
9 x# v2 a9 Q4 q3 X$ cSquare root transformation, 平方根变换8 b# x& {: ]. P& G, |
Stabilizing variance, 稳定方差1 k) u$ X. Z( N, z% z8 @
Standard deviation, 标准差) W- A S- R' [4 p" l
Standard error, 标准误
" f. u- s, _- d; C. d) N' rStandard error of difference, 差别的标准误4 j, h1 V9 _: [$ ^+ Z8 y
Standard error of estimate, 标准估计误差
9 g' c' O) c; _$ {+ U$ FStandard error of rate, 率的标准误
, e7 W7 U; v5 r5 T2 W- vStandard normal distribution, 标准正态分布2 x( r; W! Y5 n$ A0 f) N: W
Standardization, 标准化
" H. \% ?" _6 r' W' tStarting value, 起始值
r( j4 s" T) v2 tStatistic, 统计量
7 @. a/ {. b4 Y, a2 {6 k$ K0 m* hStatistical control, 统计控制+ k- J: H: g- q9 C/ ~# O- c
Statistical graph, 统计图9 d5 E4 Q- Q0 Q0 S$ Q8 ]% d
Statistical inference, 统计推断
- P7 h7 C' r! N- p3 yStatistical table, 统计表; N; u' `% K4 i- _5 x! e
Steepest descent, 最速下降法; y, ^: k R. d4 G! B5 d$ T
Stem and leaf display, 茎叶图
1 j9 h4 n( Z( ~6 r# ?6 t# VStep factor, 步长因子2 Q. q& V1 @' z0 s
Stepwise regression, 逐步回归
- J5 F) i1 k F5 i B" k8 j) wStorage, 存) T) Y) w5 o3 c* D. X2 z8 z
Strata, 层（复数）9 Q. ~# w' r6 f' N' z. K" f
Stratified sampling, 分层抽样! R5 A7 Z& m; c, s- W% f+ ~
Stratified sampling, 分层抽样* F" c, a5 x; K, m6 n( o4 k
Strength, 强度
1 K( K& U' |1 \1 f4 iStringency, 严密性" g C& R: `* h& f6 \2 ^
Structural relationship, 结构关系
" W* A6 n, o+ H% ?Studentized residual, 学生化残差/t化残差 W1 G7 ]# h6 x ^
Sub-class numbers, 次级组含量
" z: n0 k3 g RSubdividing, 分割; o+ R9 Y5 f1 ^3 ?& }/ z; T
Sufficient statistic, 充分统计量* m4 z; n. l. j9 i4 }& p
Sum of products, 积和' d5 u3 |' ?+ c" w$ q& h
Sum of squares, 离差平方和
" ^" s% s6 D( w4 vSum of squares about regression, 回归平方和
) i7 j2 b; B) c6 w/ J! _) ^3 B' L9 }Sum of squares between groups, 组间平方和; ? k/ T+ @- S _
Sum of squares of partial regression, 偏回归平方和
* @9 E3 Q& H- ~! NSure event, 必然事件
3 x3 h8 O- P' N. X$ kSurvey, 调查# n, w) N5 y5 ^8 u4 n
Survival, 生存分析* A: @' r# t" f8 r0 h7 A
Survival rate, 生存率
$ `- V6 z- o; e5 ?4 n2 R oSuspended root gram, 悬吊根图; @- A& L0 _: O4 [8 A9 [& U' F
Symmetry, 对称2 H# V1 N6 F6 o* s. K" [
Systematic error, 系统误差# l& q. V, [, R# Y2 I/ g
Systematic sampling, 系统抽样
% D" B, H$ |( n& i) OTags, 标签
7 I m& a: t y7 z$ HTail area, 尾部面积
+ s* B! V6 o1 G6 `; Q& kTail length, 尾长: m+ S- P1 [: [3 w
Tail weight, 尾重7 l2 b8 V( X" L( z3 @
Tangent line, 切线8 i) R0 }# C; z$ G& U% B* Q i" z
Target distribution, 目标分布
& B* `0 z j: d' D& @8 u9 LTaylor series, 泰勒级数
* L- p* ~3 i; \" F6 F9 V* N, h$ hTendency of dispersion, 离散趋势. s {5 N/ u; @
Testing of hypotheses, 假设检验1 X$ q4 h4 x/ b# E( e
Theoretical frequency, 理论频数& |. o1 G) O/ X& j
Time series, 时间序列
{+ o- q, T H( kTolerance interval, 容忍区间
2 d! Z) r, z& g7 K! I- _3 n6 P8 @Tolerance lower limit, 容忍下限4 u" p% A/ y- [! o q
Tolerance upper limit, 容忍上限
' E4 t+ y, B' U. }* c( HTorsion, 扰率- U# A: Q. V9 v, R9 _5 C
Total sum of square, 总平方和
( T' X2 ^6 F% Y. P1 {9 a/ eTotal variation, 总变异; w. N: @! [. E& K: O
Transformation, 转换
8 d, b; P* z0 i8 uTreatment, 处理' D0 y2 f! q9 h6 q7 C) C0 Q
Trend, 趋势
b' b2 h* N( n$ mTrend of percentage, 百分比趋势
" U/ E8 I, b& l. k: A' Z1 u# zTrial, 试验9 m6 U# \% w3 I6 W+ a
Trial and error method, 试错法* [# H* z$ n4 k3 X& i
Tuning constant, 细调常数6 z J) Q/ `# s t0 S
Two sided test, 双向检验$ J7 E, I* C& j+ h, V
Two-stage least squares, 二阶最小平方
% W. P3 O6 d9 U3 u. B9 [Two-stage sampling, 二阶段抽样
. m0 X5 x- J& u$ V: ?! [: ]% A( eTwo-tailed test, 双侧检验2 u' d+ G9 x# z* ]
Two-way analysis of variance, 双因素方差分析
% r! n- |4 ?7 M0 i9 qTwo-way table, 双向表
+ W. f" q6 R J' JType I error, 一类错误/α错误
' W: K* f2 z/ G' GType II error, 二类错误/β错误
) A; y7 n/ g x7 ^" GUMVU, 方差一致最小无偏估计简称
2 ^( D) S1 \1 F" M: s' D! _8 H# LUnbiased estimate, 无偏估计7 o% l5 {* Y# H ^5 ^- s3 {
Unconstrained nonlinear regression , 无约束非线性回归
4 a" p$ O' b6 ~Unequal subclass number, 不等次级组含量/ D2 V/ v3 g* P; V3 W. g, S" \1 d
Ungrouped data, 不分组资料
3 @7 |0 J3 S# l kUniform coordinate, 均匀坐标
" ]( e: V, T1 ?9 @Uniform distribution, 均匀分布
' F u( s6 p6 J- V1 d5 T4 `0 `7 `Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计7 d/ L$ Q6 Y/ _1 c! F" n
Unit, 单元# r; v) Y. B( N y2 |4 Z& z
Unordered categories, 无序分类
2 e" e$ R) T, O; [: iUpper limit, 上限
! |) V: T/ _- q" g, D7 x: mUpward rank, 升秩
; T" t) j3 s$ WVague concept, 模糊概念/ _, v$ t/ R8 C; Z: \
Validity, 有效性
; F5 ?; o7 O# mVARCOMP (Variance component estimation), 方差元素估计
6 q) ^& q5 a# U1 m t7 i1 BVariability, 变异性
* |) o: c1 |4 ]. m4 a; b& x8 X6 rVariable, 变量
3 }9 A( H6 }, r5 O2 iVariance, 方差
0 g @+ P2 I5 W# V+ EVariation, 变异/ L' H4 H+ l4 u- F
Varimax orthogonal rotation, 方差最大正交旋转
! F& K4 t9 _3 U( r0 JVolume of distribution, 容积
0 V7 D7 ~9 ~: n1 YW test, W检验+ a1 V8 A( [9 V2 Y5 V
Weibull distribution, 威布尔分布+ H: k4 E6 a1 k* y/ c/ f8 R$ l. N
Weight, 权数$ U( W2 k0 C) A5 I" y( C
Weighted Chi-square test, 加权卡方检验/Cochran检验+ F# A5 e7 c9 J2 ]& H
Weighted linear regression method, 加权直线回归) B$ G7 g+ w4 E7 c9 q
Weighted mean, 加权平均数
+ s X3 B) }4 s1 U. g, VWeighted mean square, 加权平均方差& }' m6 r" x; V$ m! x' [2 V
Weighted sum of square, 加权平方和8 |2 b: L |/ \" D& e% k( s
Weighting coefficient, 权重系数# I' A" b9 U+ X5 x2 y1 ~ h
Weighting method, 加权法 * R+ O N, p9 z
W-estimation, W估计量
5 m" A# x5 B$ c4 j7 {W-estimation of location, 位置W估计量
2 n6 O+ m% j# O" G0 M7 r( F8 rWidth, 宽度
$ \5 k' _1 ?# Q. n5 p. G' v" ~1 e$ iWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
9 d" S G1 b8 @1 n* aWild point, 野点/狂点
: Y3 h$ v# k+ b0 M$ kWild value, 野值/狂值
" n7 z, p% P* a6 V2 M' Z' w: U8 SWinsorized mean, 缩尾均值( n. B( Y" h$ m; c- r
Withdraw, 失访 ' u: v o( p5 n+ T3 P* k
Youden's index, 尤登指数
. p. L) M1 M7 T" |- C1 h4 TZ test, Z检验
8 [" T9 R1 E3 W, |. q. Y% g# OZero correlation, 零相关
$ s, L6 A9 c+ B; r$ SZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
