|
|
Absolute deviation, 绝对离差
9 c3 s8 i0 `: ]Absolute number, 绝对数
4 \% X, Z ?# t9 R4 q3 ^Absolute residuals, 绝对残差3 i9 A- Q7 ` I3 @
Acceleration array, 加速度立体阵- K, S" k' r( C f0 K/ K
Acceleration in an arbitrary direction, 任意方向上的加速度
$ T, Y% ~1 `( s' V1 y' r" KAcceleration normal, 法向加速度0 E; C" z- |! X' `, w
Acceleration space dimension, 加速度空间的维数6 Y, w# [- D+ p# Z @
Acceleration tangential, 切向加速度0 A2 q% R6 M# X8 Q
Acceleration vector, 加速度向量
) j) |; K7 |; b) D; }* p1 {Acceptable hypothesis, 可接受假设
9 g1 S5 T4 d" kAccumulation, 累积% _. T# v% v/ N% o6 H
Accuracy, 准确度
1 X$ b/ C! g: u3 RActual frequency, 实际频数7 p6 _+ h7 ]8 |/ O/ I
Adaptive estimator, 自适应估计量5 ^. }# c( q |* K% b! [
Addition, 相加
1 c" ~0 m+ [4 e2 EAddition theorem, 加法定理5 r. x# y0 Y0 S, ^' \
Additivity, 可加性" u" \+ S+ Y+ G) D
Adjusted rate, 调整率
4 d+ E5 t4 u# z' a1 i8 ZAdjusted value, 校正值
0 c6 M% q: s+ b( NAdmissible error, 容许误差& O* @; ]' P5 p- F: j+ b6 Z
Aggregation, 聚集性7 U- y5 l0 z8 r, A e% l
Alternative hypothesis, 备择假设
% Q; X( J* w5 \4 m+ NAmong groups, 组间
; G! \+ S5 b$ Z, Y) X' z' h& wAmounts, 总量
$ @+ T, B( R# `6 uAnalysis of correlation, 相关分析# C: L+ Z( v5 u1 h a1 s
Analysis of covariance, 协方差分析
0 j( `4 b- ?) T9 D+ iAnalysis of regression, 回归分析' \1 D1 @! a% O; \& _
Analysis of time series, 时间序列分析
) Q y, {- O U' O. y! mAnalysis of variance, 方差分析* {. J1 U |" I& R
Angular transformation, 角转换/ q2 ~7 o; r; e8 }' n, I( X
ANOVA （analysis of variance）, 方差分析0 d* G( h7 Z& `$ H- D' M
ANOVA Models, 方差分析模型: Z1 ~" d6 [8 T$ i5 I9 a8 m
Arcing, 弧/弧旋7 t; K( a6 ~8 ]) t; n; i
Arcsine transformation, 反正弦变换
4 u4 B a6 @* kArea under the curve, 曲线面积
/ C* |! `. p6 L8 ]; X/ dAREG , 评估从一个时间点到下一个时间点回归相关时的误差 & D3 d/ h8 g0 n" d& M, O
ARIMA, 季节和非季节性单变量模型的极大似然估计
+ U' Q' k7 d# H- o" yArithmetic grid paper, 算术格纸
2 r7 e i* i4 C$ Z/ T- ?Arithmetic mean, 算术平均数
6 w: I" s* E) ?' B2 S% _4 TArrhenius relation, 艾恩尼斯关系3 J9 ?0 u/ g1 q2 \ w
Assessing fit, 拟合的评估* G/ z8 C/ ~+ B- D
Associative laws, 结合律
& L# d& |& W% n8 E6 Q6 G, _Asymmetric distribution, 非对称分布7 V# E) g# B& N1 D2 Z3 f
Asymptotic bias, 渐近偏倚
1 y$ U2 G7 F5 {0 `Asymptotic efficiency, 渐近效率+ V- l$ o$ K! {6 B
Asymptotic variance, 渐近方差 b8 J% G6 P4 M2 {: i
Attributable risk, 归因危险度9 }, Q% L3 F% x7 @
Attribute data, 属性资料
j* G" }3 a% ?; AAttribution, 属性
6 w+ i3 V. y2 e/ f# D/ a' dAutocorrelation, 自相关
/ R0 d, N8 P7 q3 Y2 VAutocorrelation of residuals, 残差的自相关+ }% ~8 X1 F" Z( d/ B: b# L
Average, 平均数+ Z4 `8 s3 t q9 I$ y
Average confidence interval length, 平均置信区间长度 @2 `1 `9 j y' i9 i% T) O
Average growth rate, 平均增长率
, Q+ o( p! z, ~1 n- ?Bar chart, 条形图% C+ Q. ^: y' [3 V! q
Bar graph, 条形图
8 K; j2 d! y( nBase period, 基期
9 N$ v) f! L3 mBayes' theorem , Bayes定理8 q5 E, i9 a5 B6 m6 E
Bell-shaped curve, 钟形曲线" u! ^, h. Z9 o& _* r+ `* [% X
Bernoulli distribution, 伯努力分布
: X# M* |% W5 ]% D) WBest-trim estimator, 最好切尾估计量
# a6 C( }- O( {- r) ?Bias, 偏性
/ L7 a0 {2 X7 V) L4 Q/ _: tBinary logistic regression, 二元逻辑斯蒂回归
- Z( }, b! C' D, f( \Binomial distribution, 二项分布1 }$ _; E( c/ Y6 n y; j" {
Bisquare, 双平方3 H4 S t/ @# C7 k! ^: W
Bivariate Correlate, 二变量相关: W! f/ |7 x/ k! a
Bivariate normal distribution, 双变量正态分布3 N/ o( K- v/ z# C
Bivariate normal population, 双变量正态总体
1 B5 E7 l* S8 HBiweight interval, 双权区间
' w2 f2 X9 N7 oBiweight M-estimator, 双权M估计量4 b a. V( c8 [. G
Block, 区组/配伍组: i& c+ g! }7 O, A! V
BMDP(Biomedical computer programs), BMDP统计软件包3 b9 Y& d, S) ~ \
Boxplots, 箱线图/箱尾图
4 t1 l% N# b. j& N$ E8 |; xBreakdown bound, 崩溃界/崩溃点; G* Z, {; k- z M5 {
Canonical correlation, 典型相关
- B% m/ |' f& k; u j+ h# MCaption, 纵标目" K5 y0 ]+ c3 e4 C& F; m
Case-control study, 病例对照研究5 s$ P/ c9 |' P' T4 H- X, W
Categorical variable, 分类变量
# h/ Y( k$ B6 m5 V. ~% ^2 [Catenary, 悬链线* V6 [0 B5 [0 m+ {9 k8 z
Cauchy distribution, 柯西分布
: I% y5 V; o# \. b4 HCause-and-effect relationship, 因果关系
2 l) I6 e# L9 d4 R. o3 E% fCell, 单元
; a# f( f: J) [Censoring, 终检; O# L0 V% {4 }4 h# }* V
Center of symmetry, 对称中心
$ R; ^& h0 `# M0 eCentering and scaling, 中心化和定标) Z; k% q# }( ]0 L/ D
Central tendency, 集中趋势& B. ?8 x8 |. u N$ i$ R
Central value, 中心值
0 L @7 Q: C! O5 d& SCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测2 B* }! H2 M- {! |$ i' m B
Chance, 机遇8 S' k4 _4 p- h! ]- [
Chance error, 随机误差
p) L. a" N' h+ _& c( [Chance variable, 随机变量
; V$ l( O! q/ L R/ OCharacteristic equation, 特征方程
% L: v. T! O( A4 B( GCharacteristic root, 特征根5 J1 ^8 q0 j4 Q
Characteristic vector, 特征向量
# T# A6 G H& Q, BChebshev criterion of fit, 拟合的切比雪夫准则
# s( a. c: I# p& SChernoff faces, 切尔诺夫脸谱图
9 @7 k$ e) q# I7 h- d0 `- `/ TChi-square test, 卡方检验/χ2检验
# c0 S9 h, z5 a) h- tCholeskey decomposition, 乔洛斯基分解6 W+ o( L7 Y! }5 f7 w2 ^7 Q* o) f
Circle chart, 圆图 + Z. {1 V' z3 X d# F5 |' k2 \; {( r A
Class interval, 组距2 j6 W5 Y. L" J7 z; S9 `
Class mid-value, 组中值/ h9 J$ L$ t7 _5 g) R' C
Class upper limit, 组上限7 K. P4 d+ G2 V! } c# y
Classified variable, 分类变量
! S' { K7 |8 `. B2 r [0 u/ SCluster analysis, 聚类分析 ]' l W* g3 g
Cluster sampling, 整群抽样
) c8 d2 N3 A+ B4 ?5 q7 nCode, 代码) X1 q. N+ q; o* E
Coded data, 编码数据
$ l: V) ~0 Q- q/ N- sCoding, 编码+ k- g+ W0 u9 E' T9 w) M
Coefficient of contingency, 列联系数$ U; F( W! n( }; P
Coefficient of determination, 决定系数
- }$ R" a9 b$ [( q; ACoefficient of multiple correlation, 多重相关系数* n: }! C5 t) ^; \& j0 x( V: U
Coefficient of partial correlation, 偏相关系数
/ N; Y" `+ `" ^9 `2 } {( H& P6 uCoefficient of production-moment correlation, 积差相关系数7 W7 J( S/ G7 T# b0 y
Coefficient of rank correlation, 等级相关系数' w. T& J) W) O4 M0 ~" r0 v# ~! |
Coefficient of regression, 回归系数" t4 ^/ N( P0 `3 T3 J% J) G$ o
Coefficient of skewness, 偏度系数& I. W/ g8 u/ [/ V! _; b& C
Coefficient of variation, 变异系数" g# B8 V5 ~) o6 N! n3 P: p+ Q6 N
Cohort study, 队列研究& i7 K6 R3 ` F: p1 e( G
Column, 列9 u8 f2 R8 M) M9 X9 A% f
Column effect, 列效应, {9 C: n( U: }1 o5 I
Column factor, 列因素
3 T' |5 j0 |$ m+ @. K* E9 BCombination pool, 合并
7 y3 @" l. z0 U0 t2 W. R6 b6 RCombinative table, 组合表
2 T5 @5 O3 a4 vCommon factor, 共性因子
3 y' y+ w1 K9 \ }9 jCommon regression coefficient, 公共回归系数1 U# ?- w# ^* h0 k7 J
Common value, 共同值8 L( g6 E+ c! V2 H2 u: h
Common variance, 公共方差# w, j, K$ ?6 r0 R; ^
Common variation, 公共变异' I9 i) g" F3 L+ _3 I7 I4 W
Communality variance, 共性方差: K D# n& w" C s
Comparability, 可比性
9 i2 ?- E$ M4 D& Q: \" a6 mComparison of bathes, 批比较7 d9 Z' P$ G$ j8 }& ~5 N7 N, L$ v. V( u
Comparison value, 比较值/ O) I* h* z6 e U n. K
Compartment model, 分部模型
% r# o* n3 d, n: D* {Compassion, 伸缩6 m0 |" _4 |9 H
Complement of an event, 补事件
: X0 \( H) ^3 T+ Y1 [Complete association, 完全正相关
' N' O4 L9 ? V3 @8 tComplete dissociation, 完全不相关
1 F1 N- U5 o# P- |. E0 q, }$ {Complete statistics, 完备统计量* V, P( S) t/ j1 X/ _
Completely randomized design, 完全随机化设计' j, ?( M5 S6 ^8 N( j. i
Composite event, 联合事件
. r" m# ~) v& C* s, k0 t& l: BComposite events, 复合事件
0 L' Z; o% m2 |8 A6 gConcavity, 凹性 S) c- `4 E3 K1 C" _
Conditional expectation, 条件期望
& r* H* g4 T# C! E! s* l, j& UConditional likelihood, 条件似然7 {2 [- T3 d& B( C
Conditional probability, 条件概率6 H$ ~. j: C1 E( _; t
Conditionally linear, 依条件线性' w' m9 J' ?4 O1 d
Confidence interval, 置信区间# y! z* C5 G' a0 K5 _
Confidence limit, 置信限
" X: K' C1 \# Y) _1 Z3 A0 jConfidence lower limit, 置信下限
. y1 R4 x, K/ ~; rConfidence upper limit, 置信上限0 n0 `7 H M! Q; J" X+ R
Confirmatory Factor Analysis , 验证性因子分析
O0 s4 ?1 g/ K5 R3 aConfirmatory research, 证实性实验研究
. y; X% G* u' T N. d0 LConfounding factor, 混杂因素
2 {9 Z& a' t* b& xConjoint, 联合分析$ e0 U7 |9 Q- R* e I4 V, b8 o$ p7 l, V
Consistency, 相合性4 V" I. p- R/ m$ U) t- g) Z
Consistency check, 一致性检验
8 `1 E) D1 q. H- o* [9 L+ ?! vConsistent asymptotically normal estimate, 相合渐近正态估计
4 B7 c( Q/ L4 ]) d4 PConsistent estimate, 相合估计+ m9 {8 R) z k0 N
Constrained nonlinear regression, 受约束非线性回归
' J7 h& X% d& y4 ^7 BConstraint, 约束
1 y, C; ?# w2 x' d) eContaminated distribution, 污染分布, ^$ J) F; ?7 J5 Z$ x
Contaminated Gausssian, 污染高斯分布: n3 q' c' b N) e7 E( w+ ]+ E
Contaminated normal distribution, 污染正态分布 ?) n, L8 r8 h+ x/ x s( {
Contamination, 污染7 w- b- p% ~* } O/ q F# d
Contamination model, 污染模型5 n B7 N# b) ]0 p) Y! _/ u1 M
Contingency table, 列联表
" G: E s$ s/ ?5 c* BContour, 边界线" w3 U; V! w8 u' `8 x
Contribution rate, 贡献率- {7 i. b8 q* y
Control, 对照
5 a# n2 K" o5 |$ _Controlled experiments, 对照实验
. K1 }- l" h. u6 D7 KConventional depth, 常规深度7 j+ _8 R, @) @! F
Convolution, 卷积: n7 g- }$ @+ m! Y9 d o# s
Corrected factor, 校正因子1 L% o( l. G: ?5 F1 {. M
Corrected mean, 校正均值3 Q, T2 C6 q0 `
Correction coefficient, 校正系数 m: ]2 ~7 a1 | d9 j
Correctness, 正确性! X+ S; C1 b: v1 V/ d0 r% J" G
Correlation coefficient, 相关系数
) [9 N) D# @* g3 ACorrelation index, 相关指数" U3 s2 f* i) a7 i3 k
Correspondence, 对应
3 U: a3 M% {$ C$ r( PCounting, 计数
' B q' e2 a; S/ P8 v- M2 ^4 M( FCounts, 计数/频数& T$ |6 j+ i- i" i; n
Covariance, 协方差& w% V+ z! k$ a$ w& L8 s' j
Covariant, 共变
3 A& j" ^! ~+ F& |& D% R7 G) f% vCox Regression, Cox回归. Z1 S" x- G" f6 r% [. B
Criteria for fitting, 拟合准则
! z2 @6 p) Q9 `2 s0 WCriteria of least squares, 最小二乘准则
: L5 O0 @8 A. d/ I& a5 pCritical ratio, 临界比
/ |. Z% X7 O8 lCritical region, 拒绝域: ?- S. s0 g8 g2 G. ~
Critical value, 临界值& _- V' q9 |2 n9 y2 L2 h6 G
Cross-over design, 交叉设计
) x; c- B7 C+ j0 P# tCross-section analysis, 横断面分析! G8 D V; Y5 `
Cross-section survey, 横断面调查, S* z. w. X0 p( G
Crosstabs , 交叉表 6 I/ P j6 b }2 |# l- S8 B
Cross-tabulation table, 复合表* h3 y" U* \& t: g8 J6 w
Cube root, 立方根
* l1 ^. B4 f* M! H- N; y* D7 YCumulative distribution function, 分布函数
4 ]! K" Y8 p ^Cumulative probability, 累计概率0 I9 x0 }, [" g$ T0 C
Curvature, 曲率/弯曲+ {" p9 m, g: [
Curvature, 曲率; V9 o$ ]- M% y- j
Curve fit , 曲线拟和
0 @8 f* }- a# q$ LCurve fitting, 曲线拟合. T' q6 X7 v( A5 \
Curvilinear regression, 曲线回归
2 R2 ?9 { Z8 K) t% u6 F3 X* H8 A- ICurvilinear relation, 曲线关系
2 S% T/ o8 ^: E O, [# ~% `; ECut-and-try method, 尝试法
1 @8 T* T, n8 H5 n- u& l6 B; l; S' ACycle, 周期
9 g6 G4 U k9 B0 j; }Cyclist, 周期性3 a @, ?, C1 ?! D& v
D test, D检验
+ V/ L K4 C% c9 h3 J% [Data acquisition, 资料收集* D- s: p% C7 w
Data bank, 数据库, u$ k9 w( k: c7 ^$ P( m
Data capacity, 数据容量
) Y! k- P5 Z* \/ P- [, nData deficiencies, 数据缺乏
" O! E$ F+ p' NData handling, 数据处理
0 v l3 w; l! F( wData manipulation, 数据处理
9 t/ F) J+ r. R( a: f& S/ Q# g$ d3 z2 tData processing, 数据处理3 E9 I3 ?- h9 ^8 ^/ Y
Data reduction, 数据缩减0 l. R( y- y# c! q7 d# R5 O
Data set, 数据集
# v) J0 g. n' \' ]0 g* E4 EData sources, 数据来源
# L) z$ k: ^7 o! }* K! AData transformation, 数据变换
- L9 h% N) D7 P& s y. pData validity, 数据有效性/ P0 Y" V, c/ n; }
Data-in, 数据输入) x- O4 Z8 Q9 f7 s
Data-out, 数据输出, d" N' J2 s; u* f7 N5 d& P6 [: R0 m
Dead time, 停滞期5 A4 G, R2 F4 d- m: B) k8 p
Degree of freedom, 自由度8 l E2 h3 `+ F( U; {# M. `
Degree of precision, 精密度
4 J1 e) g6 ^- M6 u& I& ~" FDegree of reliability, 可靠性程度2 M- s6 ?8 m+ }; K7 Q+ R
Degression, 递减
, I* I/ T* ]% f! Q6 Q( V7 o4 N+ YDensity function, 密度函数4 f5 ]( A u, }+ H& b0 |+ _* ~
Density of data points, 数据点的密度" Q" X' i) k# C
Dependent variable, 应变量/依变量/因变量. r$ b! N8 ^ Z# r' W6 b8 [
Dependent variable, 因变量
$ D% M+ h5 x/ l* O% I+ d; L% t; t2 IDepth, 深度
4 s c- v2 m, ] d8 hDerivative matrix, 导数矩阵8 X- O" w7 b1 p) U" ], Z
Derivative-free methods, 无导数方法1 \: H! X6 G4 h
Design, 设计
, u8 B( s+ L, B$ l' v/ O3 A7 gDeterminacy, 确定性. l4 R7 S+ K9 }- t' p# U& K ^
Determinant, 行列式
; I' z P% ^) F6 ?; Y* BDeterminant, 决定因素4 C- J0 O. W+ u7 l
Deviation, 离差
' A' X1 P0 o0 d% YDeviation from average, 离均差$ ~ X3 L7 U4 T' C$ H, ~% k! W
Diagnostic plot, 诊断图1 ]; H7 O+ j$ G6 N, X7 q# J( h
Dichotomous variable, 二分变量9 d3 ]7 A5 B0 H) C# N, [: D+ `
Differential equation, 微分方程
0 b$ l0 z7 \6 X" S0 H8 |$ N5 c! L8 FDirect standardization, 直接标准化法. X+ T% J( _% `' f6 P
Discrete variable, 离散型变量, O: m6 |7 s l; q
DISCRIMINANT, 判断
. k ]6 g# u7 t: ?4 g& eDiscriminant analysis, 判别分析) C/ z* [0 R2 F% V6 R5 j
Discriminant coefficient, 判别系数8 `5 m) k# w) g3 I
Discriminant function, 判别值 U ?; A+ B7 D, \6 N4 R c0 C9 r
Dispersion, 散布/分散度
( q! a, N. M. Z3 b! CDisproportional, 不成比例的
0 f: L# m/ e& b5 `: h# B+ `Disproportionate sub-class numbers, 不成比例次级组含量
2 y/ J! V1 Y; a+ Q) ]- vDistribution free, 分布无关性/免分布
4 W8 H( T" D! B( RDistribution shape, 分布形状
4 Q. y( a$ V, o0 |Distribution-free method, 任意分布法% e) ]5 w2 i' J8 q5 _# p9 ?
Distributive laws, 分配律
% |9 T# J( B0 q5 e4 U: EDisturbance, 随机扰动项
" \2 K, K3 s- ^6 w: ~& SDose response curve, 剂量反应曲线
& b, }4 q4 y; Q- _Double blind method, 双盲法' z- O2 |5 d8 g3 W. f
Double blind trial, 双盲试验) i8 H8 v" D! }" Z8 r0 l
Double exponential distribution, 双指数分布
' J; u( q7 ]+ u8 }Double logarithmic, 双对数6 i6 V5 t# Y+ l! [' M
Downward rank, 降秩5 W! ^0 H+ G3 ~; k' ^% N9 d5 W- J
Dual-space plot, 对偶空间图9 y8 e' m8 `. J8 u' a
DUD, 无导数方法
4 U8 S) D8 G" w" P- NDuncan's new multiple range method, 新复极差法/Duncan新法& \+ j6 J: I7 A5 m* q+ n1 _1 t0 {
Effect, 实验效应
) _ o' C' G. s! k9 SEigenvalue, 特征值
/ j, r c- j! A, i' \Eigenvector, 特征向量' k) z7 D. p$ d( R8 y- s
Ellipse, 椭圆2 J+ W& r6 A5 a# S
Empirical distribution, 经验分布( T3 n- r; b. L4 Q
Empirical probability, 经验概率单位
- H0 M7 z0 w9 |+ T9 ~5 S/ `, v3 GEnumeration data, 计数资料
; u8 B3 M% u/ i/ B$ S3 u9 Z E+ QEqual sun-class number, 相等次级组含量7 @& @& P4 @0 R& C
Equally likely, 等可能2 w+ a, I. d% Y, b
Equivariance, 同变性5 C4 q6 R0 ]5 ~0 r r
Error, 误差/错误
) g2 `: u+ M% n4 J) eError of estimate, 估计误差8 ~! O* h) [1 ~: g8 {
Error type I, 第一类错误: w. I9 U& z: d8 f: G4 D
Error type II, 第二类错误
" i1 v% [4 L B+ oEstimand, 被估量4 ?8 N" n r* z; @5 l$ i
Estimated error mean squares, 估计误差均方
3 f+ _8 a2 J* L/ J# N( o$ MEstimated error sum of squares, 估计误差平方和- g" n+ c0 x* P" Z9 C5 {# c
Euclidean distance, 欧式距离
2 d& H/ p$ R! I; ^9 LEvent, 事件+ Y& U, B0 V/ G$ N( }6 [
Event, 事件
: h1 R5 q. W1 g5 M4 W' VExceptional data point, 异常数据点1 h3 }9 W5 B, U; _
Expectation plane, 期望平面4 k2 y8 U; N" J! Q( S
Expectation surface, 期望曲面
( p- p# q7 @( q1 AExpected values, 期望值
! G" n4 a( o& H2 LExperiment, 实验
* G) S( B% u0 T9 [" X" MExperimental sampling, 试验抽样
) q* s2 L$ h/ Y* VExperimental unit, 试验单位
! G) _. p: P3 Y7 S5 a6 C8 iExplanatory variable, 说明变量( `1 ^3 _% [# ~& T' e0 f }
Exploratory data analysis, 探索性数据分析6 ?0 `5 z0 `& n
Explore Summarize, 探索-摘要
; H Z2 y2 x& F7 D9 H, o+ vExponential curve, 指数曲线
+ I4 K$ K4 U0 D. w9 c2 cExponential growth, 指数式增长
( Y% _: u5 v: w* t) }+ P) E5 [EXSMOOTH, 指数平滑方法
$ j* [' t0 D8 FExtended fit, 扩充拟合! Q7 K: Y" e5 B! k4 I8 e( C, v
Extra parameter, 附加参数! Q; V4 p& U) c. U }7 Z
Extrapolation, 外推法! c9 D' b/ k. S0 ]8 s. a3 b2 C
Extreme observation, 末端观测值
" i) l: {) j8 L/ @0 CExtremes, 极端值/极值' s$ U, x- j+ m
F distribution, F分布# `, z) ~! ^) {! ~
F test, F检验
; |5 E. O5 Y0 N9 B2 d' G% J [: WFactor, 因素/因子
! Z$ A+ Y J t6 M0 ^' D3 c8 IFactor analysis, 因子分析% s' P3 Q' i# A0 s0 l7 g
Factor Analysis, 因子分析
2 a3 W, E8 l: Z- ?8 X! lFactor score, 因子得分 ( l) H3 f$ s+ a& D) z
Factorial, 阶乘. f$ Y$ J/ T) M( R4 r
Factorial design, 析因试验设计) Z- e& h) D- \) j6 X
False negative, 假阴性9 t% h3 [' ^. s1 v% i" ]9 L6 V
False negative error, 假阴性错误
; s2 P. `+ t' v! f: NFamily of distributions, 分布族. {* ^) J0 h+ E! J9 t3 z4 ]
Family of estimators, 估计量族 l4 y' ^: ], p" _3 x
Fanning, 扇面) L, k# W" V) }
Fatality rate, 病死率
5 M4 p) a9 a+ O$ ]" BField investigation, 现场调查) K% G) {5 V+ A; Q7 j5 }
Field survey, 现场调查
7 Q! a2 {: e8 i K4 p# lFinite population, 有限总体; B6 z4 K l1 J% k$ u( x
Finite-sample, 有限样本2 \$ |% ?: h" B% [, p' a
First derivative, 一阶导数+ v7 j: \8 u5 s& ?7 D% @9 i
First principal component, 第一主成分. j# i2 z2 s" W
First quartile, 第一四分位数
3 M& R* }3 [1 @Fisher information, 费雪信息量
: W# w6 t4 ? w$ B+ eFitted value, 拟合值/ O- f- q/ _0 z7 ~, s
Fitting a curve, 曲线拟合/ P- r* u# E6 i2 L2 G7 t3 M5 l
Fixed base, 定基: c" i; l# @& O; a' z% y
Fluctuation, 随机起伏
! a; r' w( ?- k7 Q# e& ~/ m; x1 dForecast, 预测
' `2 \$ a/ ~, _4 a0 ~Four fold table, 四格表
3 a) a4 k" r2 E. b/ wFourth, 四分点
& t! O& O, }& ]+ V7 [ c( rFraction blow, 左侧比率
1 Z( W9 B U2 E; _Fractional error, 相对误差 w/ ^9 I2 q1 W' Q2 u
Frequency, 频率4 |& O2 T5 f1 y( t a
Frequency polygon, 频数多边图' s. v9 g" [/ h& N) c6 `& b
Frontier point, 界限点/ Y4 U; K7 V4 G* {0 @" N
Function relationship, 泛函关系- S" Z* c3 l8 r2 P; O5 A
Gamma distribution, 伽玛分布
& e, @+ n8 g8 g8 CGauss increment, 高斯增量& Y+ p. J r Y
Gaussian distribution, 高斯分布/正态分布
( `! j9 M5 T& O$ L7 J& r- N# ~8 RGauss-Newton increment, 高斯-牛顿增量
* t, d' p# p; T5 C, Q/ ]% G: z# G% ZGeneral census, 全面普查. u1 \% F. y7 Q! [0 M) J8 B
GENLOG (Generalized liner models), 广义线性模型 ' J# _$ E8 p; _7 y, Z" |
Geometric mean, 几何平均数. X( f( K; R# N( ~4 S8 P+ w1 q
Gini's mean difference, 基尼均差2 N% c& X- x; X2 z2 [+ c
GLM (General liner models), 一般线性模型
' C* a9 W. v# k8 g1 x& H( D" }Goodness of fit, 拟和优度/配合度
2 H$ _, _% h! V- Z) SGradient of determinant, 行列式的梯度
1 ?" _0 s8 b( Y9 yGraeco-Latin square, 希腊拉丁方
$ x( ~! G. w+ Y9 K0 xGrand mean, 总均值
. W1 J' F% j7 `* {" R, V- z4 ^Gross errors, 重大错误) C/ K3 D5 k' m) j1 i" V& n6 x
Gross-error sensitivity, 大错敏感度! S5 s' R! L" M8 ~( w, H
Group averages, 分组平均- E: m/ s7 h7 s7 S
Grouped data, 分组资料% J. R% E* C, C4 d- o8 `, z |8 o
Guessed mean, 假定平均数- y- r: \1 n" x. D$ u
Half-life, 半衰期
) j8 v: E" W7 @0 mHampel M-estimators, 汉佩尔M估计量
5 M/ l+ [& K& ]+ rHappenstance, 偶然事件
6 a* q# l4 e3 m2 [9 L) r! RHarmonic mean, 调和均数
$ \+ t8 o. D& j: b- w2 G6 THazard function, 风险均数, l Y$ [& ]! [0 o7 ^& }
Hazard rate, 风险率
8 h, _! ?- c p, FHeading, 标目
2 h% q% k1 k2 [' a0 ?Heavy-tailed distribution, 重尾分布, h+ W" X* y2 a; H/ J/ ]
Hessian array, 海森立体阵
5 n6 D8 M9 y7 CHeterogeneity, 不同质
, e5 f- L0 ~$ {Heterogeneity of variance, 方差不齐 : ^7 a+ i1 R% |
Hierarchical classification, 组内分组: o8 f" `% L% a% z0 t# x4 n% v
Hierarchical clustering method, 系统聚类法
8 B; L- E0 |9 b( J1 yHigh-leverage point, 高杠杆率点
J" y) a( ~8 C3 eHILOGLINEAR, 多维列联表的层次对数线性模型9 u1 _3 t3 Z$ B3 X# |7 m
Hinge, 折叶点8 H% \# W* ] L
Histogram, 直方图- F/ v G9 M6 G2 O1 L
Historical cohort study, 历史性队列研究 + r) C1 W+ V4 `9 k: f
Holes, 空洞1 N \" L. @$ Z) u5 h' X( D# X
HOMALS, 多重响应分析. G9 l7 P0 V! X
Homogeneity of variance, 方差齐性2 M. e+ e% A& w
Homogeneity test, 齐性检验7 F9 G- R% s2 w( { P4 _! R
Huber M-estimators, 休伯M估计量& z0 [' l2 P! n/ B1 X
Hyperbola, 双曲线: f O$ O+ R! N3 ?2 r- `8 x
Hypothesis testing, 假设检验8 Q4 [9 a; c9 O5 h
Hypothetical universe, 假设总体4 k8 z* f$ H4 t: v, g% z+ B% P1 W. X
Impossible event, 不可能事件7 ?3 p+ B5 V( Q+ Q
Independence, 独立性
5 `3 e% Z: ^# m$ sIndependent variable, 自变量. \$ O; J; P, L! o6 k5 x9 f9 y
Index, 指标/指数
0 z- f# j; {) b5 L, ?2 W8 CIndirect standardization, 间接标准化法; _# L. z% L1 A6 P% [
Individual, 个体
1 G$ n7 A. q N4 U/ hInference band, 推断带5 m/ o, H$ p* w+ U. y b. u" [
Infinite population, 无限总体4 W( U5 }. O" J, `. R( |, K
Infinitely great, 无穷大% A* Y4 ^' ]% R! ^" ?
Infinitely small, 无穷小4 B$ L6 q. I V7 H6 x# E
Influence curve, 影响曲线
) X& {" ^ a1 V, v; _$ OInformation capacity, 信息容量0 p# {: U5 O! G) E
Initial condition, 初始条件
# i$ p' `8 z) ]7 CInitial estimate, 初始估计值) s6 B" T4 [$ b3 y+ N" b
Initial level, 最初水平
& D% v. M$ F$ ]- W: A8 {Interaction, 交互作用
?' E1 a. m' }' B. Y+ I, oInteraction terms, 交互作用项
7 X, t6 H* E2 b( NIntercept, 截距7 E$ Y" Q0 s4 |# y5 Z# b9 R( e
Interpolation, 内插法# N; W& h, v) z; i9 e4 H1 {
Interquartile range, 四分位距. C* W. a' f/ S0 Z
Interval estimation, 区间估计
4 C3 [% I$ `- L) R8 v; h5 }7 yIntervals of equal probability, 等概率区间: i% }8 q) R( c0 i
Intrinsic curvature, 固有曲率) a* X( x( F: V( _; P- @/ Z* _
Invariance, 不变性* K E1 H6 M( G
Inverse matrix, 逆矩阵
) r# s. X% U8 F! Z% ?# L7 QInverse probability, 逆概率
9 E3 o' z2 D6 a' y/ R, @2 f( SInverse sine transformation, 反正弦变换
/ w6 ]" r, w3 A' AIteration, 迭代
2 Z% l2 g7 G0 P2 |4 DJacobian determinant, 雅可比行列式
% ?' W+ Z& i/ b$ p5 T: @Joint distribution function, 分布函数# J) M" l! M9 l' L7 y
Joint probability, 联合概率
4 v" L# ?$ p7 H% Y; {& e0 R4 YJoint probability distribution, 联合概率分布
. K3 `& E/ X- ]# WK means method, 逐步聚类法6 T, o$ U& F$ [% R
Kaplan-Meier, 评估事件的时间长度
3 D! E, I+ E) _. K) bKaplan-Merier chart, Kaplan-Merier图
2 \ A2 P3 g9 oKendall's rank correlation, Kendall等级相关3 R" p1 g& p7 D" m: {9 ]
Kinetic, 动力学
! B% o& U" s- @Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验% Y% f7 `9 G$ a
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
4 a9 Z" c$ ~: g' y Q# c$ iKurtosis, 峰度1 B3 B: _" V( J3 d
Lack of fit, 失拟. r+ I/ O5 g- c+ J) n4 c$ f7 m" `
Ladder of powers, 幂阶梯8 Q" P8 T* c: }# s P% ~* p) y
Lag, 滞后/ ~% H: q V) h Q- Y. n
Large sample, 大样本) U) k5 \* n$ T0 M# ]
Large sample test, 大样本检验( L5 x9 w# C# x; t6 V: v0 N
Latin square, 拉丁方& |# q& I; G. e2 a" | y
Latin square design, 拉丁方设计
! H e+ E! H2 `Leakage, 泄漏
: D9 M& U) q& x0 e8 \Least favorable configuration, 最不利构形
0 H, a4 M ~6 WLeast favorable distribution, 最不利分布
+ ^$ L* @8 @2 A) r% s; L8 s$ c9 @" CLeast significant difference, 最小显著差法
+ M, A5 V0 `+ u6 }Least square method, 最小二乘法' {6 x; m* {6 P n1 S+ S8 o
Least-absolute-residuals estimates, 最小绝对残差估计
6 n M c' _4 R8 C+ ?Least-absolute-residuals fit, 最小绝对残差拟合0 u5 T2 B. L" f0 |; p# l2 P
Least-absolute-residuals line, 最小绝对残差线/ O9 q1 K1 p. B) p, X3 F2 `: u
Legend, 图例8 Z' h m. e+ x) x/ {/ T- l
L-estimator, L估计量
9 \+ z9 Y9 e W @6 Y$ r$ X9 v- D/ IL-estimator of location, 位置L估计量/ `5 ~. O0 W8 x: X$ |# x. w; y: i
L-estimator of scale, 尺度L估计量3 _* V* Z+ ?( ]2 a$ E- N
Level, 水平
1 K/ Q8 X* ?8 \7 RLife expectance, 预期期望寿命
- m j! D3 v+ d. V0 aLife table, 寿命表
6 M k3 I7 `7 j6 v! Q* g, @ DLife table method, 生命表法
% e+ f ?% X0 o2 w+ h- { HLight-tailed distribution, 轻尾分布
: I; {- {9 H: t( N; Z( {+ {. }Likelihood function, 似然函数 ]3 S6 K; ]% t4 r
Likelihood ratio, 似然比
5 b8 Z; _( f* G' Z+ p8 Lline graph, 线图7 r' a+ I/ Y$ @4 Z
Linear correlation, 直线相关
/ U! H# o3 `0 I$ V7 l2 O/ w5 lLinear equation, 线性方程
3 r9 U5 G8 r5 U, A; `8 wLinear programming, 线性规划6 z0 L8 N3 q7 L
Linear regression, 直线回归7 u2 y" X: X, J
Linear Regression, 线性回归
5 K4 r. S" r7 c3 rLinear trend, 线性趋势/ j. f; F4 U9 t& }0 D" ?
Loading, 载荷
' {& Y( ?; }6 WLocation and scale equivariance, 位置尺度同变性
9 e! H M, |) yLocation equivariance, 位置同变性
+ U- O" k" c$ W3 XLocation invariance, 位置不变性1 a% Q* C f4 h( a
Location scale family, 位置尺度族
6 l- v5 L( n) t. S; `2 zLog rank test, 时序检验
8 C: ]$ {7 c0 ^% ^+ z1 tLogarithmic curve, 对数曲线9 D" J- v0 r! Y6 N1 L. a
Logarithmic normal distribution, 对数正态分布
" @9 r, [( H: d0 m! }Logarithmic scale, 对数尺度
. b6 j" x/ S6 u' @( u9 _Logarithmic transformation, 对数变换: K; t0 q2 ]; G( r: f7 e3 y+ {
Logic check, 逻辑检查* S" H: L0 g% e$ j$ ?
Logistic distribution, 逻辑斯特分布
# v/ [' Q4 U' u* GLogit transformation, Logit转换
9 o6 E X5 U) ?% K' QLOGLINEAR, 多维列联表通用模型
+ }7 ]# @9 d: ?0 }Lognormal distribution, 对数正态分布. ~% l) i2 X: M4 \* d) }) a# k
Lost function, 损失函数3 d2 }0 P1 U! t+ }4 R
Low correlation, 低度相关
) G7 s1 _) c( n: K R. ^Lower limit, 下限
$ x- M B( c% ]! b3 TLowest-attained variance, 最小可达方差
, w4 @/ v6 O- o( M3 z. qLSD, 最小显著差法的简称
3 K5 k' K% K1 k/ Q9 i/ tLurking variable, 潜在变量6 K; @0 a3 Z1 v9 R; q* G5 E3 e
Main effect, 主效应 z4 [' _7 ?, d
Major heading, 主辞标目
, d8 n2 g$ D) e3 \( S- r" AMarginal density function, 边缘密度函数
9 O+ \* r$ h) {: F$ CMarginal probability, 边缘概率
9 h8 r4 _" K+ t0 |% n$ o) @. K7 ~Marginal probability distribution, 边缘概率分布
8 D$ E* Q2 ^$ e0 iMatched data, 配对资料( \, X" Y0 o7 p' D) q
Matched distribution, 匹配过分布
3 d8 S/ W! x) ?* PMatching of distribution, 分布的匹配
! ~* e" z [8 e8 k! g3 S4 UMatching of transformation, 变换的匹配
3 ]; b* ~$ v8 k7 z) y3 ~% A4 |: ~Mathematical expectation, 数学期望
# J( Y- ~7 I- PMathematical model, 数学模型
$ D" o' {, d9 J+ OMaximum L-estimator, 极大极小L 估计量
( m* @9 P4 ~1 M7 ~Maximum likelihood method, 最大似然法 l; [2 [4 T6 m; v
Mean, 均数
' s* L' W5 h7 Q; ], F2 iMean squares between groups, 组间均方5 K0 Q( _, g9 _7 k- s4 W
Mean squares within group, 组内均方
7 S+ a) W6 a) B1 j7 E BMeans (Compare means), 均值-均值比较
- Z7 T; h; H6 a& O% LMedian, 中位数
; G5 r$ U- l- a7 Z; UMedian effective dose, 半数效量4 u0 p5 V3 \2 B# p) y' g$ W( Y3 ]- y
Median lethal dose, 半数致死量0 {% O0 O. Y. w: v
Median polish, 中位数平滑. t" y3 b2 j2 ~: u
Median test, 中位数检验
f: I, T% H4 { K2 \+ n3 q5 [Minimal sufficient statistic, 最小充分统计量+ H- m5 F3 {7 E, l) U
Minimum distance estimation, 最小距离估计
# @2 t0 @. V! D# j% g; C( S- o" _7 FMinimum effective dose, 最小有效量& l0 b5 q/ Z# P" r9 i2 E3 n2 m( i) L
Minimum lethal dose, 最小致死量
* A* ?4 v% C+ R( KMinimum variance estimator, 最小方差估计量' a& V( a# r8 G: \
MINITAB, 统计软件包2 j& `5 }- `+ H
Minor heading, 宾词标目 I P6 y3 x$ B( x9 Z
Missing data, 缺失值+ L+ A0 \7 Z6 ~- a) w
Model specification, 模型的确定* K& F9 r) Y* [% O" W! U& M2 |4 @
Modeling Statistics , 模型统计) l# n3 R- N" ^, Q8 U* S3 O5 D/ p
Models for outliers, 离群值模型( I& F/ s% b# X
Modifying the model, 模型的修正! n/ z$ Z6 z2 {0 }
Modulus of continuity, 连续性模
. I4 H' {7 H0 mMorbidity, 发病率 # P; w+ C! `7 Q+ b0 j h
Most favorable configuration, 最有利构形; I* |8 Y8 y9 M5 K
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
, a t" R4 a( ]Multinomial Logistic Regression , 多项逻辑斯蒂回归2 B/ q: W/ W, j3 ]2 n6 M
Multiple comparison, 多重比较
9 K7 J8 O$ O7 L1 N2 l- J7 xMultiple correlation , 复相关
# {' u( y+ l( v" I* YMultiple covariance, 多元协方差0 M( f! p% Z( P
Multiple linear regression, 多元线性回归
# r7 e6 R L$ x" h' B" S3 z7 bMultiple response , 多重选项1 O" f# Q- @: M
Multiple solutions, 多解8 z1 Y: l+ m4 ?, w1 e; G- |7 @
Multiplication theorem, 乘法定理
9 k" A. C. b: V4 SMultiresponse, 多元响应! U3 N; Q7 q+ w% e) z: o6 D9 J
Multi-stage sampling, 多阶段抽样+ g: L- I( }/ |9 Q2 z2 J! T: S0 K* I$ _
Multivariate T distribution, 多元T分布: E# w6 Y0 L, J
Mutual exclusive, 互不相容: R4 e2 Z/ t7 Z* f/ k- W
Mutual independence, 互相独立
9 s1 ?# ] Q; Z' a2 @; @6 s; QNatural boundary, 自然边界
# E2 P1 F- v& H! ?/ dNatural dead, 自然死亡$ P6 c- j9 o9 k9 ?# F9 Z
Natural zero, 自然零, d" F, V) I- z, K _- L6 _
Negative correlation, 负相关
, }) x7 N U/ J. b6 B& D; t6 V8 mNegative linear correlation, 负线性相关% V7 {0 P+ @6 s6 u
Negatively skewed, 负偏
, O/ b7 d/ h& {0 p- g8 S/ zNewman-Keuls method, q检验+ B) K) c# B' }* n: O5 v
NK method, q检验 ?9 a! {$ u( b, s3 y$ b0 A. h3 @
No statistical significance, 无统计意义/ M0 K K2 A2 z8 ^) O7 Y
Nominal variable, 名义变量6 P1 W" w. e$ K* ?
Nonconstancy of variability, 变异的非定常性* `/ ?( X; w2 G8 D! o' y# ^
Nonlinear regression, 非线性相关0 O; h: J+ `1 j
Nonparametric statistics, 非参数统计
: K7 y7 N# ^) |: fNonparametric test, 非参数检验
' ^/ c) X6 @; m- mNonparametric tests, 非参数检验
" Y. X9 M! p' v2 y7 o; ?7 W4 FNormal deviate, 正态离差2 s- W0 l' k/ L$ c7 k- t6 t
Normal distribution, 正态分布* @$ X+ N- E4 `0 N
Normal equation, 正规方程组
- V3 D a" E% m8 L0 |Normal ranges, 正常范围$ ~3 ^( v9 M9 L2 B5 O
Normal value, 正常值, K. `1 M: I l1 ^3 F6 ~. G" o
Nuisance parameter, 多余参数/讨厌参数
; C2 Q, Y; ^$ G0 lNull hypothesis, 无效假设
$ E& f, i, V, k4 e- Z, i5 DNumerical variable, 数值变量
$ E4 Q7 {% t* j/ |+ V$ JObjective function, 目标函数
3 S2 v, o+ e; h- r) V" Q$ O' F( QObservation unit, 观察单位
$ u& l% r& B& r$ B7 _5 t" W, R/ U! rObserved value, 观察值
d9 ]" K5 o+ T9 l% `+ k YOne sided test, 单侧检验
! q* h2 D' t6 p* TOne-way analysis of variance, 单因素方差分析
* V: F$ X. L- u" Y5 z7 w1 ^Oneway ANOVA , 单因素方差分析6 I5 K3 g! i8 i3 W: { A
Open sequential trial, 开放型序贯设计
1 M' ~2 h2 [9 z/ \; yOptrim, 优切尾
+ a+ i% {1 R. z2 \; [Optrim efficiency, 优切尾效率
) m( s9 Q5 N, j+ ~* ^5 gOrder statistics, 顺序统计量
# E: J4 V: P+ D4 k* COrdered categories, 有序分类) |% U/ T( R$ l
Ordinal logistic regression , 序数逻辑斯蒂回归
$ W4 \- b; l/ {8 }: {' UOrdinal variable, 有序变量
; Y% O3 N4 r8 O- DOrthogonal basis, 正交基8 i! N8 _& a1 |# s
Orthogonal design, 正交试验设计" _; F% z( R: E, C% B
Orthogonality conditions, 正交条件) ]- @: r% G5 e9 \ h
ORTHOPLAN, 正交设计 ( R" _+ f. Z* i& J
Outlier cutoffs, 离群值截断点
& Q; [7 G# Z# G2 g# s! A/ xOutliers, 极端值
; a6 d3 y4 w# d3 {7 o2 A' Y6 k6 FOVERALS , 多组变量的非线性正规相关
6 l' b) j9 G5 Q* T9 |4 ~& {Overshoot, 迭代过度( F6 W/ T# p% V2 X
Paired design, 配对设计% R4 h v/ ]- W# U3 a
Paired sample, 配对样本
8 N* D6 K% u" j& EPairwise slopes, 成对斜率$ o4 i+ O# e, a0 U% L& a
Parabola, 抛物线7 K. G9 h h' K+ ?
Parallel tests, 平行试验- V2 u& O9 z# [8 H% v, `9 L
Parameter, 参数. @( i q/ N; N6 L3 b4 ~
Parametric statistics, 参数统计
]) P% e" g- @; _Parametric test, 参数检验
3 Z. M; i/ f/ t# I+ MPartial correlation, 偏相关
$ e% M) K0 s- \4 l: |Partial regression, 偏回归' c( c) z% M! W- _
Partial sorting, 偏排序/ M) V7 p3 [$ A. L$ Y
Partials residuals, 偏残差
0 r# i, H$ m: J+ WPattern, 模式
4 W. G( p& N( _$ Q# n9 D8 RPearson curves, 皮尔逊曲线
- O9 w) ^! }3 T; {% gPeeling, 退层8 R; M7 r7 i* W8 \
Percent bar graph, 百分条形图
5 Y. a" H) [: LPercentage, 百分比
, m/ C. T; E" h1 p1 wPercentile, 百分位数
8 i* n# }4 I9 W9 W. b) QPercentile curves, 百分位曲线0 \/ H( R8 @. E. b, g
Periodicity, 周期性! X7 Q. c( r+ Z) ~% Q
Permutation, 排列
\0 j0 g, v# _/ g! [; CP-estimator, P估计量, D3 X: @2 d5 Q w# H# Y
Pie graph, 饼图
- F6 |$ n. ^( y, g- CPitman estimator, 皮特曼估计量% x# @2 A, `( A6 [- V7 \ ]
Pivot, 枢轴量# @' W( C7 ^$ g# m: x
Planar, 平坦, m5 V# F8 w! G+ b! [6 i1 J
Planar assumption, 平面的假设
$ b6 p X0 }" q/ { LPLANCARDS, 生成试验的计划卡' e; O t# G' l- c: ]& e0 @" v
Point estimation, 点估计
6 |6 z4 `. }, n' z3 Q2 a9 hPoisson distribution, 泊松分布' j* p3 l6 a' X+ P" T4 m
Polishing, 平滑" M2 c/ e3 @! D. b; f
Polled standard deviation, 合并标准差
* N/ x6 Y0 L ^6 V/ C9 f0 E( E! RPolled variance, 合并方差 g* v8 }" t; I3 ` T& A
Polygon, 多边图, R% t4 q- I: x3 g# Y& q
Polynomial, 多项式
6 u* m/ i3 _( X: F7 N" q& D3 z, HPolynomial curve, 多项式曲线
/ s3 G% ?( l0 f3 C9 o- {6 PPopulation, 总体
2 M+ Y5 C, }7 {1 d" l# h6 uPopulation attributable risk, 人群归因危险度
& m6 C7 {4 a: a( u( aPositive correlation, 正相关8 z! k7 x# ^# {8 L: \2 n
Positively skewed, 正偏
* c# m: z* f5 }3 }: Y5 V2 aPosterior distribution, 后验分布" l |: ]2 S8 j; v1 Z5 W% y
Power of a test, 检验效能/ p9 e. R2 v |' [4 z
Precision, 精密度8 [8 W/ ^5 x: b* i1 V
Predicted value, 预测值2 D8 E. {1 ]& H0 N- U: E
Preliminary analysis, 预备性分析
& R" C- G( b; K BPrincipal component analysis, 主成分分析3 `+ X8 m0 J' w8 Y0 a1 L
Prior distribution, 先验分布
, H, S% Y! B l% m4 c6 BPrior probability, 先验概率/ I: i4 g! v7 W! a6 r8 g; W$ s2 [
Probabilistic model, 概率模型- C# n/ Q" j; u; t( x: ~
probability, 概率' A1 M( T4 N8 h& j
Probability density, 概率密度
; h- m, Q6 o& ? H1 {; RProduct moment, 乘积矩/协方差& L' C6 ]/ P5 y4 o( ~" U$ P
Profile trace, 截面迹图5 l. U3 F2 W% w- ~0 X2 N
Proportion, 比/构成比
! R u, H8 r: P' |1 u9 |$ v# Q5 i" MProportion allocation in stratified random sampling, 按比例分层随机抽样4 Q+ p3 k8 {6 s
Proportionate, 成比例3 P; [# W* [! W+ G
Proportionate sub-class numbers, 成比例次级组含量1 g- y- P, c% V; L, m% \7 j4 w( A9 k
Prospective study, 前瞻性调查
2 t& C2 q' ~2 _Proximities, 亲近性
5 ?/ D3 u6 A% Z; W& ^, y# h2 |Pseudo F test, 近似F检验' J4 v' U% Q- } [& ~& |7 B8 d
Pseudo model, 近似模型
" a+ ~9 d% \ QPseudosigma, 伪标准差5 ]( Q& r' G8 V4 G/ u; I
Purposive sampling, 有目的抽样
, C& Z. W" |1 ?$ Y& RQR decomposition, QR分解# w" m }( n/ w7 {% G
Quadratic approximation, 二次近似; b2 b6 u8 y7 n7 c
Qualitative classification, 属性分类* Q1 Q, ?+ |3 A! ]4 L0 ^# H9 s
Qualitative method, 定性方法
8 i) J9 P6 V. g3 BQuantile-quantile plot, 分位数-分位数图/Q-Q图3 L/ M i: n8 w8 B
Quantitative analysis, 定量分析
* L1 |- \9 p3 ^3 O+ CQuartile, 四分位数
/ I* N. m- N" o/ j! w. t$ `2 m1 iQuick Cluster, 快速聚类
! P, o& I0 G" R" }Radix sort, 基数排序
: n+ o9 _' T- wRandom allocation, 随机化分组+ @& u9 k4 ~- Y' }' C$ V
Random blocks design, 随机区组设计; I4 z; I# z ^# _/ r+ H: v+ K
Random event, 随机事件
9 R& ]6 o" @! MRandomization, 随机化6 z1 W# d9 p( m* h: O9 A% n! |
Range, 极差/全距$ Q, d* m* [9 W! K6 @7 Y0 I! F( L
Rank correlation, 等级相关
4 C) Y/ a4 [: Z0 R6 c( _8 Z* PRank sum test, 秩和检验
9 K: P ~" e7 U6 j9 T1 D8 MRank test, 秩检验( Q9 k% D. D( W6 a# X) t, U* l
Ranked data, 等级资料
6 }1 z P; b* p5 z( f# E7 NRate, 比率1 l' c9 F( c& m8 D- H2 F" m* ^
Ratio, 比例
6 \- @8 a I% wRaw data, 原始资料
, r2 ~2 U! p7 Y! w' sRaw residual, 原始残差9 n. D+ R- U9 Q' W+ G
Rayleigh's test, 雷氏检验% e n4 ^0 {3 U2 K+ t7 l5 ]! b
Rayleigh's Z, 雷氏Z值 ! Z c0 R( c' g: S5 z! Y1 A
Reciprocal, 倒数4 Y3 L0 T+ B1 @) X a0 s
Reciprocal transformation, 倒数变换
: J1 `* z4 q0 j& tRecording, 记录
8 r% _9 f2 @* l3 ^Redescending estimators, 回降估计量
( v+ [ v% F3 q0 r; yReducing dimensions, 降维
" p* B3 n, d( g6 f0 T% V; F' z2 VRe-expression, 重新表达
0 h( o* j' V$ t+ ~% @ AReference set, 标准组
7 b4 a9 I( c" n" L; jRegion of acceptance, 接受域
7 T2 Q. d, o, y9 k& e oRegression coefficient, 回归系数3 J2 m, N) e. A% h" r+ G2 e
Regression sum of square, 回归平方和( _$ J" ^: j: V G$ |* {
Rejection point, 拒绝点! ^) V2 ~+ p4 j2 J* P% l
Relative dispersion, 相对离散度
; g, f% g C, h# G( g) URelative number, 相对数2 @, \4 F, u* G8 l3 \
Reliability, 可靠性
$ @4 ^6 W. n+ e: w. z1 K, M! vReparametrization, 重新设置参数
- `5 ^) a: ]/ P) @. aReplication, 重复
. B1 A, l$ N7 z' h6 u! G2 TReport Summaries, 报告摘要
8 k) C! Z9 Q8 c3 wResidual sum of square, 剩余平方和6 m( @* @6 u1 K( \$ v7 V
Resistance, 耐抗性
5 S3 c X* M7 C7 FResistant line, 耐抗线9 L2 {1 T! I! N7 O
Resistant technique, 耐抗技术
! ], [6 i% `. qR-estimator of location, 位置R估计量
- X% C+ z( @- j' E' k Q% aR-estimator of scale, 尺度R估计量
: M4 S2 u6 z& K3 |Retrospective study, 回顾性调查! ~9 u. D4 r9 K9 q# ]$ `
Ridge trace, 岭迹, `& X- e6 t8 Z7 E! r
Ridit analysis, Ridit分析
* Z' U' r- ?$ l8 R& P' _Rotation, 旋转
+ I; h' X9 c F4 k, RRounding, 舍入. R5 Y0 m2 M( T" t' e1 W2 W
Row, 行
+ c: V, N4 q$ p6 D, v; [3 Z {) J$ {Row effects, 行效应
7 J! T' F' [# d% k7 g( gRow factor, 行因素* _0 i5 C+ } s& I5 ~
RXC table, RXC表
. A" s# M2 Z/ q4 e' E$ [0 ^Sample, 样本- J# x0 G) c' r
Sample regression coefficient, 样本回归系数
4 j; T. F: K" @2 t' o3 n# z/ @0 `Sample size, 样本量. L' w$ P) I( g! s% c5 z9 I
Sample standard deviation, 样本标准差+ S: F, ^' _0 x% ~$ S
Sampling error, 抽样误差4 @$ F9 c9 S* }. T4 o7 G" F
SAS(Statistical analysis system ), SAS统计软件包2 R# Z! W( u9 B9 y
Scale, 尺度/量表* y) Z: | ^ I
Scatter diagram, 散点图: l* I$ h. _' z, r- l2 O
Schematic plot, 示意图/简图0 ?7 f: C$ Q: }% |& Z
Score test, 计分检验
& a# N1 M) |; Y$ g# GScreening, 筛检: _, J; { U- [. p7 U/ Y( P
SEASON, 季节分析
; @ G' j g* [& w! I0 KSecond derivative, 二阶导数
4 m- V$ J5 I8 I3 z, NSecond principal component, 第二主成分. i! e8 f+ V7 X0 u# W+ E
SEM (Structural equation modeling), 结构化方程模型 , p: K% v7 H# Z; [& I5 q+ Y1 m# K! n
Semi-logarithmic graph, 半对数图
4 Z/ u3 Q$ r* n2 CSemi-logarithmic paper, 半对数格纸
* z8 s$ [5 P1 V ~" U' T+ H* jSensitivity curve, 敏感度曲线
; [: h7 s" y) F% u8 ?Sequential analysis, 贯序分析
' t; ]- J/ l" u7 rSequential data set, 顺序数据集
: |2 Z7 N. M& }3 p7 ?" dSequential design, 贯序设计
L) ?4 j) B8 k1 v2 t }Sequential method, 贯序法
- A7 Z5 D9 u; W' Q8 n3 FSequential test, 贯序检验法9 S- T3 C* t. M% L3 H/ r
Serial tests, 系列试验" Z$ m% Z6 p/ q+ l
Short-cut method, 简捷法
; s& h1 f( t$ Z& j; }3 m# USigmoid curve, S形曲线2 W8 i( k- ? I7 V1 d
Sign function, 正负号函数
4 \& e. }' v7 K5 iSign test, 符号检验3 \# `8 \2 s) v0 Y: n* a
Signed rank, 符号秩
8 h: e l: r2 I. ZSignificance test, 显著性检验, J% }, X4 K! h2 y
Significant figure, 有效数字
- _1 x; ~1 F- ]. ~0 [' R2 w: b7 ]Simple cluster sampling, 简单整群抽样! G& p# x7 N* \
Simple correlation, 简单相关
9 u+ N- c! ?7 B5 uSimple random sampling, 简单随机抽样
2 R. F3 _% v0 J& v; T! `. pSimple regression, 简单回归
/ ]0 [) F& p. _+ v/ i7 _7 u4 d# C& Fsimple table, 简单表
: v6 l4 ]9 g9 m0 T$ a1 GSine estimator, 正弦估计量
7 f5 A; J& A$ e6 N; e2 [- eSingle-valued estimate, 单值估计; h- |/ j! w8 ?$ L0 r' ]! F
Singular matrix, 奇异矩阵
. {( m! {/ H2 h$ [9 a* |Skewed distribution, 偏斜分布; p* f9 _5 v- L; u9 B1 K! ?& u6 Z
Skewness, 偏度
; Q$ L( l% i- N1 R7 USlash distribution, 斜线分布- V% R$ R9 J7 I3 {0 ~) R/ q$ F) b
Slope, 斜率
1 q @; G7 r; W( ]2 BSmirnov test, 斯米尔诺夫检验
4 V. J9 N2 ?. g! s" Q' QSource of variation, 变异来源
, ?3 T3 \, j) d7 TSpearman rank correlation, 斯皮尔曼等级相关% [5 ]. ~1 ?+ [ U
Specific factor, 特殊因子
4 j( Z/ W$ j/ l# q& L4 S: ISpecific factor variance, 特殊因子方差
3 F Q& [# k% y- h+ `& c sSpectra , 频谱' Y y2 @( q9 v) q/ n# O9 e9 M
Spherical distribution, 球型正态分布0 d7 F9 _4 P, ]$ G; N- w; \5 j/ |
Spread, 展布
# c2 O7 E; O h% | QSPSS(Statistical package for the social science), SPSS统计软件包
5 Y& I4 ^2 n+ o) QSpurious correlation, 假性相关: t5 t; E! o8 {$ S
Square root transformation, 平方根变换
$ ]9 c" e8 G" T8 I4 ^0 \$ oStabilizing variance, 稳定方差# U0 z0 C# a. |# J! M- u( g( k4 I
Standard deviation, 标准差
$ b f8 l( g6 n& TStandard error, 标准误
5 c* C( V% h2 i6 }+ t; d* H% tStandard error of difference, 差别的标准误
: N: O1 Z* `! v+ p) T+ y4 NStandard error of estimate, 标准估计误差
# y5 N* G% p9 ]( OStandard error of rate, 率的标准误! Q1 [" f$ J. J* L* p
Standard normal distribution, 标准正态分布
. L- G) d) n0 p/ |* H/ [ [Standardization, 标准化1 }3 o; F8 i8 C3 {" Q; N& w
Starting value, 起始值$ F0 j7 E/ A2 m
Statistic, 统计量
4 N- V3 {5 j4 m( X; B sStatistical control, 统计控制5 A- b. S9 l& A& F. }
Statistical graph, 统计图
/ K3 x3 h! N F+ N' q; P! e* x& WStatistical inference, 统计推断
8 N1 \5 f+ y$ G3 JStatistical table, 统计表4 S( C' |" F) h2 d
Steepest descent, 最速下降法: g2 v$ o c, J4 w. y) ]
Stem and leaf display, 茎叶图
0 Z8 F/ `5 k) u$ [( p4 \2 u) W/ sStep factor, 步长因子, ]7 b7 A/ m& g7 o, z" D! S
Stepwise regression, 逐步回归
+ T+ P4 T! G E0 m7 r1 bStorage, 存; _+ v( @) t n: s1 ?6 Y3 X
Strata, 层（复数）
. ^/ O' V& F( N6 M( ]4 dStratified sampling, 分层抽样6 [% C8 `) a5 S$ i
Stratified sampling, 分层抽样* d* b$ u/ S# o2 y- j& a
Strength, 强度
+ `% r5 }" ~! AStringency, 严密性
3 z) ^9 g) @4 {" bStructural relationship, 结构关系
6 p! `' ] `2 W- E9 X* wStudentized residual, 学生化残差/t化残差
9 Z$ S+ w+ n0 V2 A* ^Sub-class numbers, 次级组含量
* Q. i+ H3 I5 ~( _$ g7 H- hSubdividing, 分割
$ q' ~/ h9 O( \% qSufficient statistic, 充分统计量- I$ n! w5 k' r% o* h
Sum of products, 积和
* _) V( S8 d2 z1 x H# `Sum of squares, 离差平方和+ e6 J+ P4 d/ ] R; {/ T0 ?# ^
Sum of squares about regression, 回归平方和
! O9 e: A$ ~4 N" u2 b5 BSum of squares between groups, 组间平方和( S* U( v6 I2 T5 J3 B
Sum of squares of partial regression, 偏回归平方和
) ]( p1 F8 f' O7 A2 E7 P2 Q2 r, xSure event, 必然事件
7 G1 _1 u( X3 E- GSurvey, 调查2 ?7 }9 p% d B3 k O
Survival, 生存分析- u+ s2 @3 A9 z! I$ \0 J
Survival rate, 生存率
7 {, A- U, k, Z$ hSuspended root gram, 悬吊根图
4 E1 ^: ~' L# Q6 `Symmetry, 对称4 d3 c; F5 B: b1 ]5 R# C
Systematic error, 系统误差
$ M2 D) u& a, lSystematic sampling, 系统抽样7 Z& _- c: M9 I6 ~) u: U
Tags, 标签 I. |) |9 F; }: z+ m3 f
Tail area, 尾部面积0 h- T' Q, }7 D8 N
Tail length, 尾长/ E" l: _4 T N3 M3 V. b
Tail weight, 尾重
+ F' M3 l4 Y# B+ _* R ^) K3 J- d. GTangent line, 切线
D$ u: X8 x, n; @" _$ S4 z$ [: C H& tTarget distribution, 目标分布
: U$ B0 Q# G+ v( P9 G! o) ~Taylor series, 泰勒级数
3 W; J9 G, g9 d( ITendency of dispersion, 离散趋势
; f# n4 m. w9 j3 f7 H& aTesting of hypotheses, 假设检验* n0 }- w/ i3 Q
Theoretical frequency, 理论频数& `: h7 B' c+ F% B/ f: }
Time series, 时间序列
; M6 Z) n' i. }: I8 VTolerance interval, 容忍区间$ y' h7 }5 e( Z3 {# [/ Y* B2 J
Tolerance lower limit, 容忍下限
8 o) I2 U- y9 W6 @# E# bTolerance upper limit, 容忍上限
8 I# J; E6 ]8 A0 _, m2 ^! N: o5 s, J/ ATorsion, 扰率
/ q) V9 i% U7 Z% V9 U6 b4 f4 fTotal sum of square, 总平方和0 s) {, A$ y; g4 H. J! X! F
Total variation, 总变异
2 G3 u! i* ?! l- ETransformation, 转换
, U/ H: Z3 O Y v% v& I$ uTreatment, 处理
- W& e& R* z2 n% K9 oTrend, 趋势
' O9 |2 k5 ]3 V. J p" oTrend of percentage, 百分比趋势+ Q% i, }2 N2 q
Trial, 试验& ~2 M: R& Z) B F6 o
Trial and error method, 试错法2 g6 O- J1 I! f! m( {
Tuning constant, 细调常数
, Y- C( H# L- h2 z# g! |Two sided test, 双向检验 m: v0 }) m8 C, w
Two-stage least squares, 二阶最小平方+ w( O, w) I- R- _, E
Two-stage sampling, 二阶段抽样7 J9 H2 I3 A" e
Two-tailed test, 双侧检验
$ c% t1 s& u. i* i# U/ dTwo-way analysis of variance, 双因素方差分析
* a3 v7 c7 p7 m, X! QTwo-way table, 双向表3 Y: H4 t" \' W# ~. S
Type I error, 一类错误/α错误/ p9 a7 ?. q5 L1 S9 M$ n1 G: b5 J' Q
Type II error, 二类错误/β错误
7 o9 S1 j5 ~; r1 MUMVU, 方差一致最小无偏估计简称( @ _, ^2 x. [0 p' j+ Q' i; E
Unbiased estimate, 无偏估计
& ~" F# Z7 e8 s, JUnconstrained nonlinear regression , 无约束非线性回归: \ [8 {9 a" s) l) s+ n' B) o
Unequal subclass number, 不等次级组含量2 a2 \/ V* G3 ]1 ^' j7 ^. q
Ungrouped data, 不分组资料
. R9 T ^% V8 c D4 _6 S9 t4 W4 MUniform coordinate, 均匀坐标
$ ~0 ^$ m1 q7 [Uniform distribution, 均匀分布
9 ?* O4 ]/ H! Z, |Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
7 j5 V$ Y9 l7 V2 A2 f3 _3 X! C% ]Unit, 单元6 U- a( E8 p, H( Q% y" ?# G2 W6 k7 ?7 k
Unordered categories, 无序分类
2 A, e) y2 k/ ^# A" MUpper limit, 上限
- w9 Y' b. X* i, O3 v& S( mUpward rank, 升秩1 q; ]$ T0 K' c& |, K/ n
Vague concept, 模糊概念
% |( N9 ^* |& f( Q8 F$ e! IValidity, 有效性7 r+ a9 M+ W. P% m
VARCOMP (Variance component estimation), 方差元素估计
# Z6 D/ P) |0 z+ u0 ^& h2 NVariability, 变异性
, s7 P' F6 f, ^8 n: \Variable, 变量
2 R) W5 V: Q1 W" KVariance, 方差* |) ?7 Z: b4 K' |: q% D
Variation, 变异. h F1 Z; g* A, n
Varimax orthogonal rotation, 方差最大正交旋转
& x4 S8 v! l' f' f6 t' WVolume of distribution, 容积5 n8 { H! q( q
W test, W检验3 D: J: \3 N( j! a, {) x. V
Weibull distribution, 威布尔分布
/ b4 V4 v. K- z# j8 CWeight, 权数
4 ~& B+ V6 z" l$ P* fWeighted Chi-square test, 加权卡方检验/Cochran检验. P6 v* f. T! N7 k! {
Weighted linear regression method, 加权直线回归
8 G% W5 J7 P8 ~Weighted mean, 加权平均数
( w1 J; z7 {8 `: ^7 ^2 n/ {Weighted mean square, 加权平均方差
0 [+ V: k: A% B+ {Weighted sum of square, 加权平方和
$ f* g9 ^) D/ _2 N0 SWeighting coefficient, 权重系数5 {9 q1 F. [, H4 ^: X5 D- i
Weighting method, 加权法 + X) [# k! P7 q# y; E3 c$ C1 H
W-estimation, W估计量0 o% u3 u% G& ?, c$ M, z
W-estimation of location, 位置W估计量& F4 X3 `$ e% d7 P4 ]4 P
Width, 宽度+ e1 g8 _0 ^/ n5 [& `
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验+ l$ H$ u7 g2 g1 d$ _' S
Wild point, 野点/狂点1 Q- j. |! n2 [' P+ A
Wild value, 野值/狂值
, ?) z o9 s. z8 y+ M; O7 m% [Winsorized mean, 缩尾均值& V) a, `6 }8 U( t
Withdraw, 失访
, a0 J9 ?; A6 n7 A& S6 mYouden's index, 尤登指数( d$ G: O6 [: X6 L( T
Z test, Z检验0 O6 |4 p' `0 ^0 R& V9 E
Zero correlation, 零相关
! E+ ]5 i: z: U" {! H' zZ-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看，没有账号？注册会员
x
|
|李越老师直播间|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
