|
|
Absolute deviation, 绝对离差
6 A$ A( J, U9 S" \! D6 MAbsolute number, 绝对数
; Z' o+ P7 \6 M; ]' t1 z- d# NAbsolute residuals, 绝对残差
$ G& S0 U* w4 x. o6 uAcceleration array, 加速度立体阵) d3 ]" T# U( e; L- E0 z2 E8 F2 O
Acceleration in an arbitrary direction, 任意方向上的加速度
' q6 Q' [" s1 ~- p# F( @- ?Acceleration normal, 法向加速度
/ T# T; |' h. E7 v! e GAcceleration space dimension, 加速度空间的维数
; q6 ~% K6 X1 L; x8 c+ EAcceleration tangential, 切向加速度
' d; X& `7 S! H' p' L( x" R) n+ fAcceleration vector, 加速度向量
# n: ]7 h0 j% r) E- y3 aAcceptable hypothesis, 可接受假设
* c/ B; r3 Y) A* p/ z/ MAccumulation, 累积
3 V. B0 [/ j' l! uAccuracy, 准确度9 a! U/ x' l6 }* v+ F: Q4 C0 R
Actual frequency, 实际频数
; _3 b9 B; j* O& }$ w& q* WAdaptive estimator, 自适应估计量) h# ~; i) ]. n B* ^+ E
Addition, 相加' o6 o$ _4 c# C8 q) V" A
Addition theorem, 加法定理
, k5 a) q/ [% ?# @/ ]+ N# OAdditivity, 可加性4 a- c) @2 e I" _" S1 j; I
Adjusted rate, 调整率) M g* ], w! N4 }1 O+ C5 w
Adjusted value, 校正值9 R: V# R0 E2 P
Admissible error, 容许误差
8 s, y; x, k+ ^3 C9 j! BAggregation, 聚集性
( v- }1 n& z ^9 @& K& wAlternative hypothesis, 备择假设
7 r" \* P7 y# v% g' NAmong groups, 组间
9 {* S8 ], e" M: c3 h5 i* ?2 ~Amounts, 总量
8 i6 R! H$ \, ?* w7 J' ZAnalysis of correlation, 相关分析
7 d; f4 B9 t( g( C! S5 I( r5 _) r7 ?Analysis of covariance, 协方差分析- Q; w9 V3 W0 t$ I2 j
Analysis of regression, 回归分析8 i, b( y! {& X& w
Analysis of time series, 时间序列分析
! }/ Y+ J7 I! I: M- D: nAnalysis of variance, 方差分析
& [) _0 M w1 ~5 Z' f( H& I A0 cAngular transformation, 角转换
/ o g2 b# G& l/ FANOVA (analysis of variance), 方差分析
2 i5 P$ h9 }2 E8 o t$ uANOVA Models, 方差分析模型9 Z b. C. P% |4 ~3 Z
Arcing, 弧/弧旋2 l% [, a; z+ N( \
Arcsine transformation, 反正弦变换
& L3 U( t; D2 z8 BArea under the curve, 曲线面积' Y# }3 X- z, T' l4 Y
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
7 a5 v. ~2 Y+ aARIMA, 季节和非季节性单变量模型的极大似然估计 [( |$ [9 K# G7 A* c. i7 C: a
Arithmetic grid paper, 算术格纸9 Z- j$ p+ X4 S) z
Arithmetic mean, 算术平均数
8 l- S9 ]# F3 |6 GArrhenius relation, 艾恩尼斯关系$ T7 w- \3 E" K( |* @
Assessing fit, 拟合的评估
3 I0 ]5 k- b4 P" L$ B6 `9 A; P! kAssociative laws, 结合律8 q5 W, }& L3 ]! b
Asymmetric distribution, 非对称分布
2 F2 G, b# l. T& nAsymptotic bias, 渐近偏倚
1 ~7 n6 _- x: B+ X1 K$ V! f- ?8 HAsymptotic efficiency, 渐近效率) N9 ]/ r1 s0 P n, U, b
Asymptotic variance, 渐近方差( E/ F1 }* j: G# w6 H7 s* N* \- u* s6 t
Attributable risk, 归因危险度' R; w8 |( g/ f9 C/ \2 _, x, H
Attribute data, 属性资料
5 t, y: Z3 i/ `2 @" M) T' nAttribution, 属性
& N+ T/ d( t: b1 yAutocorrelation, 自相关" E8 }! l3 B8 b6 }0 y7 X
Autocorrelation of residuals, 残差的自相关; }5 g$ W* i% Z
Average, 平均数+ A& V4 D" N3 k
Average confidence interval length, 平均置信区间长度
! G* F: Z2 R, t! W0 y0 E! K( Y$ hAverage growth rate, 平均增长率
8 G# u! ]4 \/ O2 C& [Bar chart, 条形图, f" l4 G8 U4 H4 G6 t* ^( _
Bar graph, 条形图
# e0 U3 n6 `0 G1 H/ rBase period, 基期
$ i R/ J p3 T7 b6 jBayes' theorem , Bayes定理8 q: n- S/ s) U( ]* i
Bell-shaped curve, 钟形曲线
% c6 ?* ]3 }0 e. H( a V# o3 ], ~1 zBernoulli distribution, 伯努力分布
1 I4 i" o/ H2 DBest-trim estimator, 最好切尾估计量
' |) y- ~. ^6 q1 C8 z0 c7 [6 ZBias, 偏性% u" I, Q4 ?/ O# e
Binary logistic regression, 二元逻辑斯蒂回归+ w+ O# o# K- G4 r& S$ v" m$ h$ w
Binomial distribution, 二项分布+ n3 s. G1 ~' @
Bisquare, 双平方9 T& k* z. e$ T* H; X- I# h. F
Bivariate Correlate, 二变量相关
5 k2 S) L6 P; WBivariate normal distribution, 双变量正态分布) ]2 J# X4 U/ N4 Q' d
Bivariate normal population, 双变量正态总体
$ I( [/ L% N! ]# @9 \6 _7 ]Biweight interval, 双权区间, y9 d1 j8 Y3 ^: D) v) i
Biweight M-estimator, 双权M估计量6 W. ]7 h5 R v9 U) q0 j* Z5 g
Block, 区组/配伍组9 i5 t6 B* @7 d+ u- E( x; M! G
BMDP(Biomedical computer programs), BMDP统计软件包
& e( ^3 C: @3 iBoxplots, 箱线图/箱尾图
' a5 {0 @0 |$ t$ kBreakdown bound, 崩溃界/崩溃点
, T; e" a4 E6 v! |Canonical correlation, 典型相关. f r' C* Y' ]9 E5 u5 N
Caption, 纵标目9 b8 e; z$ i" d, {
Case-control study, 病例对照研究& N) a+ j4 _ ~. [+ V
Categorical variable, 分类变量; E+ X7 x, @- K( r
Catenary, 悬链线
' C) X! g1 x, U+ uCauchy distribution, 柯西分布# k. _9 v, ]" ^# D
Cause-and-effect relationship, 因果关系4 ?/ h* |- L& Y' k! s ^
Cell, 单元8 J# W( c I1 C# j5 l* d
Censoring, 终检
$ s! I% |' M& s2 R4 h" \Center of symmetry, 对称中心9 q8 O' h% ^& T6 ?8 T9 _# m* Y: f
Centering and scaling, 中心化和定标
?( d/ ]& R( YCentral tendency, 集中趋势
* J! J' c% S- y0 m1 PCentral value, 中心值( i. O1 C; H1 F) x* z- I* N
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
9 a# q$ ?% y/ r; o7 e' Z& |Chance, 机遇, A$ K( {! x! q
Chance error, 随机误差' m, {# I5 l; k( Y% u; Q
Chance variable, 随机变量
% H5 R5 z' h% M# o5 B# u, PCharacteristic equation, 特征方程: o& s3 t; T4 i7 B/ o5 L. K
Characteristic root, 特征根
8 q- P1 l$ ^. B0 C2 _Characteristic vector, 特征向量7 ]) r2 e2 g% `0 n* ?! Z% N. z; p
Chebshev criterion of fit, 拟合的切比雪夫准则
, ^ o. |" X* i8 h7 V1 h& `9 qChernoff faces, 切尔诺夫脸谱图! R- r; ~* F; W8 L Z0 T, o5 h. d
Chi-square test, 卡方检验/χ2检验" z' A: N5 }0 i6 X3 i
Choleskey decomposition, 乔洛斯基分解7 C9 M7 Q2 B1 C
Circle chart, 圆图 , P. y( d, Z. o1 l: L7 L+ e
Class interval, 组距
/ o- K4 v- Q1 TClass mid-value, 组中值: G5 f- s ~# V( P" D
Class upper limit, 组上限, ]8 e5 O* H5 C
Classified variable, 分类变量* ~3 J( G, R, M- H( L/ v4 D O
Cluster analysis, 聚类分析
4 V: Z8 g! g3 N8 d: R; ^Cluster sampling, 整群抽样
# _% m* ?! a, b/ b. TCode, 代码& m/ k8 }, u/ b( X" a
Coded data, 编码数据3 u! G. h/ D" A+ M% ~0 g) \
Coding, 编码
* G( P6 k2 z1 I) @Coefficient of contingency, 列联系数 q: T/ o+ S! |. \0 c1 h
Coefficient of determination, 决定系数
& I5 {3 A2 _$ |2 Y- }Coefficient of multiple correlation, 多重相关系数) J s- e4 N! f! G/ b) x1 ~
Coefficient of partial correlation, 偏相关系数
- [5 v) G* Y1 z* m. _* S3 L! A; Z' z+ ACoefficient of production-moment correlation, 积差相关系数
; z5 g% w4 n D5 HCoefficient of rank correlation, 等级相关系数
+ }7 b& _- u9 a Z* O4 jCoefficient of regression, 回归系数
3 y, S( x2 j2 l' [) I( F3 H: dCoefficient of skewness, 偏度系数
1 J" _, R4 x' P* v1 I! _( E' s( iCoefficient of variation, 变异系数- X3 J7 ~7 ]% `/ I
Cohort study, 队列研究
5 d, k6 g! b9 G1 @& |Column, 列' F3 g: ]9 E& a* r' Z
Column effect, 列效应
- U) r( D; n: ]8 f+ BColumn factor, 列因素; q* J& q' w' N7 J
Combination pool, 合并
. U. \! ^% d7 O X( U+ w- n2 ACombinative table, 组合表
! z+ A# q) E" D+ r6 [0 o5 }Common factor, 共性因子
6 o, P$ x' R! a4 l* HCommon regression coefficient, 公共回归系数
V& D, `$ \' p5 [8 z0 TCommon value, 共同值
4 R, R' x$ t0 fCommon variance, 公共方差3 i c. l3 S. M, j c. ~
Common variation, 公共变异3 f! { u; _! X2 m2 |. u& {
Communality variance, 共性方差+ Y) J$ ]( E" c3 s4 _! ]/ q3 Z
Comparability, 可比性$ Z) N& O" [' p% d
Comparison of bathes, 批比较; U0 `0 f" Y/ g
Comparison value, 比较值: J6 s8 d E, O
Compartment model, 分部模型" B: y% j+ j1 t1 W3 Z
Compassion, 伸缩$ u( i) o3 G% Q/ l
Complement of an event, 补事件! D& O( f; A: \
Complete association, 完全正相关
: ~) h# I* G5 X7 QComplete dissociation, 完全不相关7 X. y! y# ?) g+ {" l3 w9 l
Complete statistics, 完备统计量8 s" c% i. E2 _
Completely randomized design, 完全随机化设计, n/ @! X& g, v" p' S1 T- r; E
Composite event, 联合事件
1 y7 B' g7 W# s5 U- f; v+ |Composite events, 复合事件5 ~7 s) J* Z8 C$ ?6 I
Concavity, 凹性) w7 a }6 E d9 |8 N R
Conditional expectation, 条件期望
7 m# R+ ~0 Q( G3 aConditional likelihood, 条件似然4 N7 p8 }/ _$ D% O# v t J. ~
Conditional probability, 条件概率
$ z$ p! Z$ z8 r- H& M4 SConditionally linear, 依条件线性; w% J) B& j! m& X
Confidence interval, 置信区间
) m/ j5 t! l6 I8 s1 `Confidence limit, 置信限
. u0 p" i* _( ^! _+ L5 D8 c( s0 aConfidence lower limit, 置信下限 ?5 C% H- g- ]6 V
Confidence upper limit, 置信上限
: W: x- F' _/ tConfirmatory Factor Analysis , 验证性因子分析
- ^5 X+ r% U$ I3 }3 @Confirmatory research, 证实性实验研究
1 o" M! `2 a# K a& tConfounding factor, 混杂因素4 ]1 @# ]* _/ o7 ]+ a' Y4 f0 T
Conjoint, 联合分析. K2 ]* f7 V1 j, {. u @8 G
Consistency, 相合性7 }8 t3 {7 J9 J& S
Consistency check, 一致性检验
! P& O; C4 r$ E+ PConsistent asymptotically normal estimate, 相合渐近正态估计
% n d, z+ k2 N) a" p/ }! t* zConsistent estimate, 相合估计- T+ a/ i0 {2 n6 O% u8 o- t
Constrained nonlinear regression, 受约束非线性回归
; E( g- ` ~3 {1 d+ M eConstraint, 约束% r5 `8 v" q5 f/ r9 y
Contaminated distribution, 污染分布
$ Q2 z2 \& t4 w3 f. DContaminated Gausssian, 污染高斯分布1 O& j. T9 h: t# ]
Contaminated normal distribution, 污染正态分布2 a' S! G' q7 t7 F3 f! @
Contamination, 污染; e+ Q8 I: O% M9 r8 {
Contamination model, 污染模型
' l8 p, L1 C" a/ j$ N% F. wContingency table, 列联表
6 t2 ~$ Z% `* ZContour, 边界线
. S) t& Z) u& i) ~2 \Contribution rate, 贡献率
& a8 l+ p8 D, W" v3 @6 N1 I/ cControl, 对照* A6 _5 g0 V: S/ e$ B
Controlled experiments, 对照实验
: b/ R8 C9 [, qConventional depth, 常规深度, n& Q, _1 j4 |: f4 N! H/ f
Convolution, 卷积" Y* z8 ]2 ?4 O5 S" U
Corrected factor, 校正因子
8 b% v+ O6 J9 |9 ?- W- ~5 ~0 s; QCorrected mean, 校正均值
; n" Q0 e* n8 m$ u1 A% xCorrection coefficient, 校正系数) w- {7 E9 P% ~- _5 _* z
Correctness, 正确性5 ]( L' g- ~4 L+ g6 H
Correlation coefficient, 相关系数# ]" F* z* U/ i; B7 w! B9 L
Correlation index, 相关指数
: v l8 i3 `3 \0 ]. OCorrespondence, 对应: f a5 q" q/ W2 L! W2 O4 ~* i
Counting, 计数" W/ G0 E/ i! W% T+ W9 w
Counts, 计数/频数; n9 [" C/ h+ F9 |5 B
Covariance, 协方差
" i C* k4 g: B" c8 ECovariant, 共变
. v- x7 `) e9 c2 M: }- G- c! f% `$ iCox Regression, Cox回归# `* ~+ z3 X; t
Criteria for fitting, 拟合准则
% w6 m" H5 ~, Y& c3 pCriteria of least squares, 最小二乘准则/ r3 j H \: C4 n6 N
Critical ratio, 临界比* L3 ^. [8 o( c+ S S5 q
Critical region, 拒绝域 D/ n# E2 x3 f1 m" q2 [
Critical value, 临界值, u$ j* ]* }( N& L. C5 {; R
Cross-over design, 交叉设计
! a c/ R( o7 y1 @Cross-section analysis, 横断面分析
I" W% y+ v; `; r* t& zCross-section survey, 横断面调查 U d4 x; g2 d! X2 Y
Crosstabs , 交叉表
2 G( H6 x0 P! G5 aCross-tabulation table, 复合表
3 I- [3 N) ` X1 ~. E$ yCube root, 立方根
7 i& c; s3 \- t* G3 LCumulative distribution function, 分布函数
8 @3 \7 j/ H4 f' J, hCumulative probability, 累计概率
8 G/ v6 j- p. ~ K( O. GCurvature, 曲率/弯曲6 r% N" c8 k" Q( ?# g) R
Curvature, 曲率
2 J; C+ u; O" O" A, ^& BCurve fit , 曲线拟和
2 m# D- W, ^% N! W6 N! j+ ^Curve fitting, 曲线拟合. H8 G1 Z7 V) z. x) U) h
Curvilinear regression, 曲线回归! a3 ?! e+ p) P
Curvilinear relation, 曲线关系! ?6 |( w' [+ s! k
Cut-and-try method, 尝试法
8 C; B, P; V! H9 dCycle, 周期
0 k1 F- B8 \, @ V. h0 E; w# D# J9 [Cyclist, 周期性) b4 X2 k9 @9 O0 q
D test, D检验
, Z2 q9 `( x/ {5 N" o: r5 xData acquisition, 资料收集) W* P! {! g9 n0 S2 e
Data bank, 数据库( B- n6 p, u. d2 N7 X$ F" {
Data capacity, 数据容量+ w' B7 [8 [' ?7 e0 \
Data deficiencies, 数据缺乏8 T, {+ X7 h5 I$ e* p* W: {, g
Data handling, 数据处理
H: w p* E7 c5 i3 T* M2 h6 [Data manipulation, 数据处理
% i8 z6 F) W4 v3 R6 m. FData processing, 数据处理
4 r2 G! M0 C. H* cData reduction, 数据缩减! v0 z' @9 M/ R+ t" }
Data set, 数据集4 x0 A6 n( T. {* m6 V$ u
Data sources, 数据来源$ r" s" U3 H; i% e- [
Data transformation, 数据变换
! T( r% V. |" X X7 x% m4 A3 bData validity, 数据有效性
6 C+ h' n* ^( U1 XData-in, 数据输入3 P! V# Y! n `; c. {
Data-out, 数据输出
1 w2 ]( h7 i- Y _9 U. u- ]Dead time, 停滞期
a8 G+ y9 y# G9 ~4 {Degree of freedom, 自由度
4 d: m9 ] |5 U& D9 {" eDegree of precision, 精密度, W+ N. X( \! v; G1 y, R" J7 s
Degree of reliability, 可靠性程度# k( O& u- @) O% ?) ^, p
Degression, 递减/ P- {% A4 [ f t
Density function, 密度函数) T$ F5 ^% x9 W3 p x
Density of data points, 数据点的密度; \1 N7 w( c, F' q
Dependent variable, 应变量/依变量/因变量
Z' k; N! F- |* t2 kDependent variable, 因变量
2 J a! N$ q. x; U9 }Depth, 深度
8 Q7 U0 V. }" t- Y$ j; VDerivative matrix, 导数矩阵
6 u, J% H( F( T$ dDerivative-free methods, 无导数方法, X6 T4 b( B- w, @! @- b
Design, 设计* ]* r! B2 z: |- g
Determinacy, 确定性9 m3 a) ~& }% a. A9 v F; x
Determinant, 行列式
; I, \: t. i7 C: [2 A; k4 |3 F7 h+ dDeterminant, 决定因素
, G0 u0 @/ g$ ]4 ?* _Deviation, 离差! `3 O3 t6 W; F& g8 c" A- C3 W
Deviation from average, 离均差
6 y9 j1 I# ]2 l/ z7 D' f2 vDiagnostic plot, 诊断图; D! N; m! v0 D2 J' c8 B! _, l1 }1 B
Dichotomous variable, 二分变量
: q/ t: U+ o* {& I1 Y8 kDifferential equation, 微分方程9 M) d F+ ?1 J! n n$ V
Direct standardization, 直接标准化法1 L$ m. a. s; z8 _
Discrete variable, 离散型变量
2 N5 g2 h3 G! xDISCRIMINANT, 判断
) I$ K6 o6 n6 a+ E( T+ kDiscriminant analysis, 判别分析
, r+ O; _4 G5 T0 B$ l$ e' l0 v* xDiscriminant coefficient, 判别系数! G7 F" X& i; t' d( t6 e
Discriminant function, 判别值/ b# v" @1 L7 `5 A" Y
Dispersion, 散布/分散度* `. O2 h3 e1 Y U* W/ j4 t* M$ y
Disproportional, 不成比例的8 _! W! L; h4 ~' }/ N% l8 }
Disproportionate sub-class numbers, 不成比例次级组含量
7 W4 |0 @4 @. B* e PDistribution free, 分布无关性/免分布: M5 E- P6 v' H" G* }0 w
Distribution shape, 分布形状2 |8 C# \8 h( {) P
Distribution-free method, 任意分布法- ~: W$ u' z+ O* S) S
Distributive laws, 分配律
5 a1 X3 u0 Q$ K3 y7 m* _# XDisturbance, 随机扰动项
, `$ I# Y8 {8 I" s" Y, RDose response curve, 剂量反应曲线
. W, m. X1 R* ]! {Double blind method, 双盲法7 p. Q% E& C0 P0 @
Double blind trial, 双盲试验5 G5 G: r* j; p4 e% t
Double exponential distribution, 双指数分布
4 R3 [! f' [6 x) ` |* T) u: FDouble logarithmic, 双对数" n' a& Q0 Q- I0 v( x) ^
Downward rank, 降秩1 p' T6 \0 B+ A' Z5 R4 y, y
Dual-space plot, 对偶空间图& w) ^4 q% `! H& T- C3 B
DUD, 无导数方法& R: d* [. b$ K$ o! d1 L
Duncan's new multiple range method, 新复极差法/Duncan新法 v' Y) W) `) a0 R: y U
Effect, 实验效应
0 e3 o- [, s0 p7 h, G) ]Eigenvalue, 特征值
- B2 N. ]* i: g' f, g; h9 a0 ZEigenvector, 特征向量
3 N, A% S- m& g" a* uEllipse, 椭圆
, D6 {0 w+ r" q; y3 o/ n+ A5 A5 sEmpirical distribution, 经验分布- K1 P; A1 T8 Q0 r! I0 }
Empirical probability, 经验概率单位7 g" ~/ ^. n/ i& v9 _
Enumeration data, 计数资料0 n# ^8 J- Y1 _. V
Equal sun-class number, 相等次级组含量! y% N" m _0 Q
Equally likely, 等可能
: X/ p: x0 z( J5 G0 { e- i6 AEquivariance, 同变性
, \6 l& _: G: m# X" }% ?7 g/ ^Error, 误差/错误
9 F; i# g3 {2 SError of estimate, 估计误差! B7 t7 O1 W, \9 S* y1 U. f
Error type I, 第一类错误4 C2 b0 ?7 @1 ]& G, N8 m
Error type II, 第二类错误
1 j) i; ]# S! k( n0 CEstimand, 被估量7 z3 V; `* W% D& ~, k* T: ]
Estimated error mean squares, 估计误差均方
3 E+ Z4 l4 i$ ]4 Q4 hEstimated error sum of squares, 估计误差平方和
& |0 W! D& p: y' L7 |* s1 dEuclidean distance, 欧式距离
* p* w# h6 t0 vEvent, 事件
+ }$ G2 V; [$ f/ n5 ^Event, 事件4 I8 [6 c" P8 J- I
Exceptional data point, 异常数据点
: q; U- K- Q% A) FExpectation plane, 期望平面6 m; U! L: U- }+ b* r( u
Expectation surface, 期望曲面
* e# {- b. Q3 j7 ~! DExpected values, 期望值2 v# v+ \5 N3 }# x
Experiment, 实验; \# S; r1 a6 L% @6 J3 p
Experimental sampling, 试验抽样
4 T, h: _# { RExperimental unit, 试验单位
& K: d0 T8 ~# ^+ v' Y0 I4 z% }6 ]Explanatory variable, 说明变量( @1 ]7 n. Y$ m9 B0 T# O
Exploratory data analysis, 探索性数据分析1 u' l8 i/ b, V3 z' ?
Explore Summarize, 探索-摘要$ S5 s" ~+ n) ]' c; g
Exponential curve, 指数曲线: c! U' z8 Q! ?, \3 ?
Exponential growth, 指数式增长
/ x/ z9 r7 |3 r- z+ vEXSMOOTH, 指数平滑方法 6 H7 S3 ]" J2 B! T; W
Extended fit, 扩充拟合6 J6 D6 M! L1 ?; Q3 M
Extra parameter, 附加参数8 O, Y) M1 m+ x0 U7 ^9 W- K% s6 J) n
Extrapolation, 外推法( P' c& D3 E. E$ O; U3 V
Extreme observation, 末端观测值: a& r' s5 O3 K9 T
Extremes, 极端值/极值
/ g, M( n# c6 q8 P' x- Y/ x7 vF distribution, F分布5 P( ~' G1 K4 O" b V
F test, F检验) Z+ s+ R/ ~! {# k6 w
Factor, 因素/因子
4 Z+ x) e$ h8 K; s! I0 g' AFactor analysis, 因子分析 f0 I, o ^# i1 Y1 d% H
Factor Analysis, 因子分析
7 Q( t* I( A2 ?( ^+ _Factor score, 因子得分
! Z+ e1 w ]" i6 h3 J0 V* gFactorial, 阶乘0 V$ r/ p4 Q. ~
Factorial design, 析因试验设计
- ~1 P) G1 S1 W. U1 [- DFalse negative, 假阴性# {) D2 f; b' x- m; e
False negative error, 假阴性错误4 O/ `5 x! W! g0 ?3 v
Family of distributions, 分布族
4 T1 ]$ g; |) z. d$ P! ^5 IFamily of estimators, 估计量族
% S9 I4 z- L! ^8 }1 G" ?4 c! m- D1 PFanning, 扇面0 Z% P4 O# t% S# e2 b) r
Fatality rate, 病死率0 E/ H" R i' ?5 X- c: w
Field investigation, 现场调查) i* V8 i9 d' I& p+ r! o
Field survey, 现场调查
* {7 S; M; v. o0 bFinite population, 有限总体
1 S1 e! p2 i- M5 _0 ?- G: iFinite-sample, 有限样本
; M6 t1 o; L+ z5 AFirst derivative, 一阶导数
. b* I% |/ c# p" l, B& H9 v- G1 [! fFirst principal component, 第一主成分
0 v1 w; p0 |9 H, |! z& F( kFirst quartile, 第一四分位数+ Z& M' t5 ~0 [. z' g
Fisher information, 费雪信息量
0 p$ M$ ^3 d& c% [2 s! }1 YFitted value, 拟合值
* d% Q* m: |, GFitting a curve, 曲线拟合8 _8 X4 F+ b5 X* d6 Y) l. f
Fixed base, 定基8 Z! D. X+ X% J; }# M
Fluctuation, 随机起伏& d% ~# C$ e1 J9 J
Forecast, 预测; p% T6 F* X7 D8 [
Four fold table, 四格表
/ i! K; U/ \2 ~/ M# F% fFourth, 四分点) U2 L& z9 @: w1 x8 G: U9 W' ]+ b
Fraction blow, 左侧比率
* k4 m4 M) z) Y! x2 @$ @! jFractional error, 相对误差
6 K. r) [5 ?' PFrequency, 频率" G0 d7 x; V! G$ a8 F; P
Frequency polygon, 频数多边图
; y8 P$ F+ H" B8 F+ l: F& uFrontier point, 界限点
% \, s. w9 C& [' j" ]; n7 t( H7 ]- bFunction relationship, 泛函关系
n t- L3 c# v' KGamma distribution, 伽玛分布. U& z4 K7 Q3 _2 r" s6 F
Gauss increment, 高斯增量! s! j. S5 v/ T9 k3 }
Gaussian distribution, 高斯分布/正态分布
; h* n: L1 _! N6 hGauss-Newton increment, 高斯-牛顿增量
* `5 ?, z9 ~8 CGeneral census, 全面普查
' y( `7 I2 B/ V' ^, ?GENLOG (Generalized liner models), 广义线性模型
1 g; J# ~# Z/ ~% wGeometric mean, 几何平均数
3 A+ {1 Y' J3 {9 SGini's mean difference, 基尼均差
; Z# D3 P2 \4 T7 IGLM (General liner models), 一般线性模型
5 Q+ m" [1 P2 F5 u; w% R; P9 tGoodness of fit, 拟和优度/配合度$ r3 e% u# i, d' {
Gradient of determinant, 行列式的梯度
! c* v# G) }0 p* R8 M, ^6 d! `- mGraeco-Latin square, 希腊拉丁方
# ~1 v! h( o# x- pGrand mean, 总均值& Z* H5 D u, j/ x& r2 M
Gross errors, 重大错误
) U3 m6 e' Q K! f0 y' E5 xGross-error sensitivity, 大错敏感度
7 r# W9 H8 R v- R& jGroup averages, 分组平均
- b1 h4 `9 F I8 ?Grouped data, 分组资料
' b7 Y7 Y3 M, s/ GGuessed mean, 假定平均数
" U% `* h' c/ W! FHalf-life, 半衰期
. n/ [* U& g$ q/ l" `' d8 eHampel M-estimators, 汉佩尔M估计量& I3 Q( D5 U9 e# v! t! d) h W
Happenstance, 偶然事件% A2 c4 W& Q. h9 k
Harmonic mean, 调和均数6 Z3 ^$ @5 @* o/ y$ W
Hazard function, 风险均数
; m: p, S3 [/ o: S! w0 E' bHazard rate, 风险率6 l: J+ r( k' j, ~( n+ v( S4 D2 W# h
Heading, 标目 ) e9 D: [& L% X0 A: X" v% e
Heavy-tailed distribution, 重尾分布7 W* t* z- ^' n( g
Hessian array, 海森立体阵
* r2 y5 d2 ?0 G& c. X( n- ]4 CHeterogeneity, 不同质
4 c" R* O. q/ QHeterogeneity of variance, 方差不齐 $ ?4 A1 }$ r: F4 k# _' X7 z0 d
Hierarchical classification, 组内分组" G: K+ b$ H; _
Hierarchical clustering method, 系统聚类法) G* U4 J2 [* |* a
High-leverage point, 高杠杆率点
! G- [4 A) E' `* v2 D$ ?' `, |HILOGLINEAR, 多维列联表的层次对数线性模型
0 [" s9 E% Z* ?* w( {Hinge, 折叶点1 U& y: r2 D; E! L9 _" ?9 t
Histogram, 直方图5 ?) t# G) g/ v5 N0 c' o# ?; H
Historical cohort study, 历史性队列研究
, ]; m+ O$ i7 K' g }! B oHoles, 空洞/ M8 @1 V! z1 X, {9 z3 Q* }2 V; X1 N
HOMALS, 多重响应分析
% \, x! L2 E, R8 Q1 A) BHomogeneity of variance, 方差齐性7 o7 k' U0 m: R! p! c# z. L% y, G9 J
Homogeneity test, 齐性检验) N# y/ w% ?# n3 X$ ]
Huber M-estimators, 休伯M估计量- Y/ ~3 G/ G* P4 G7 b
Hyperbola, 双曲线5 w% t5 K4 M" s
Hypothesis testing, 假设检验
: d5 Z! G9 \0 v0 g7 w0 LHypothetical universe, 假设总体
& M5 e4 U6 e: D0 I7 BImpossible event, 不可能事件
2 Z" `" R% ?& @$ P$ Q; _8 y9 `Independence, 独立性2 }& e: X/ f; m2 T3 g2 R
Independent variable, 自变量/ h; D0 \1 F$ Z. }5 S
Index, 指标/指数1 @7 T: {# b, T O4 C
Indirect standardization, 间接标准化法
4 N6 C% a" K% g8 } f% CIndividual, 个体
@& e4 l! q/ B8 X" j& l/ dInference band, 推断带" L: Y; K6 l F& @
Infinite population, 无限总体
, A4 b9 Q, H6 t' f9 AInfinitely great, 无穷大+ I+ a: ^8 ]2 I" C- S
Infinitely small, 无穷小( H$ P8 ] Z* K- |6 \% c: o
Influence curve, 影响曲线* K" V' d: n- ]0 ~4 M
Information capacity, 信息容量
- @7 j a0 `% ZInitial condition, 初始条件' W9 k! x' p, ]. ?0 C3 ~& }: y
Initial estimate, 初始估计值) x7 ^4 I* n3 P8 w" s/ e k8 a
Initial level, 最初水平
& L$ H% g$ E: Z# [. |; iInteraction, 交互作用
- Q. f+ y( O, C hInteraction terms, 交互作用项
3 A. e# F6 o$ `; \Intercept, 截距
5 A6 H; O1 e2 J( Y7 TInterpolation, 内插法* a2 _; N' A5 J3 \8 m; Q$ i6 s" _
Interquartile range, 四分位距
* N/ t7 G: v7 g( Q6 g8 W; A% t' L5 M, @Interval estimation, 区间估计
. G3 v! a+ }+ k& N. OIntervals of equal probability, 等概率区间0 q8 `. o; @9 j7 C3 ?
Intrinsic curvature, 固有曲率
$ H+ Z# X( e% Z. n: w3 w, }Invariance, 不变性6 K9 I8 r+ d- }) S8 c
Inverse matrix, 逆矩阵
" D( U2 x/ E X) lInverse probability, 逆概率
- O5 v4 d. u7 ^9 r/ x3 NInverse sine transformation, 反正弦变换# J' T* ~/ Y* d7 u, Z0 T) ?/ z
Iteration, 迭代 9 Q& U0 _. j2 L3 Z
Jacobian determinant, 雅可比行列式
' p$ `5 ~5 l3 Y [Joint distribution function, 分布函数0 y* A+ r7 G: ?; t; W+ J+ C# a
Joint probability, 联合概率
) Y: g8 X/ t) N3 M3 c7 sJoint probability distribution, 联合概率分布
, C7 f7 I' P2 b) K1 Z* K+ IK means method, 逐步聚类法 B# l/ W1 @8 A0 C4 Y' D$ s- y3 g
Kaplan-Meier, 评估事件的时间长度 : j" ?: l' h# e
Kaplan-Merier chart, Kaplan-Merier图+ r5 @" Q. ]7 {
Kendall's rank correlation, Kendall等级相关0 y' s5 | y- I9 N
Kinetic, 动力学; z- R; m, I ~7 ^, {- B
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
1 D7 K) U3 H4 i0 M0 \0 t, UKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
& t1 C+ V( d \1 G* r* [Kurtosis, 峰度& Y& B0 ^/ E; E
Lack of fit, 失拟
# \! O, ^! V8 M) G0 wLadder of powers, 幂阶梯
9 R5 j7 a" E% S% Z% |0 o9 [* ]Lag, 滞后- S8 ?- x. O4 q0 `
Large sample, 大样本
X) l7 I* D. [" u! dLarge sample test, 大样本检验
- O6 A$ A' h, z. {- m3 |. p& U! hLatin square, 拉丁方
; O3 E! H4 U+ G3 r n, lLatin square design, 拉丁方设计. p- W2 W8 v6 p/ X; ]' J
Leakage, 泄漏
2 H V* g7 J7 H/ |2 W! f* {Least favorable configuration, 最不利构形# [9 Q+ \4 m5 R
Least favorable distribution, 最不利分布6 c1 C# S8 c8 s. O/ P- X
Least significant difference, 最小显著差法
& B, j9 |/ `, q7 V) e3 K5 dLeast square method, 最小二乘法
4 P0 R% }; c$ P7 ?Least-absolute-residuals estimates, 最小绝对残差估计
& c$ w0 Y! {4 M7 {; c1 }. U6 V. {Least-absolute-residuals fit, 最小绝对残差拟合- R, L% A1 u7 {% g" I5 d* j
Least-absolute-residuals line, 最小绝对残差线; k5 \- p" ~5 a! |
Legend, 图例
( A* S5 v6 c) @' O6 d( { p+ D( s9 aL-estimator, L估计量/ Z' q* A& F, ~# s& x
L-estimator of location, 位置L估计量
; y# D4 T' P3 B$ C) `L-estimator of scale, 尺度L估计量( h: C9 F2 P* \! m# t4 L
Level, 水平
! u. k$ z) F, O4 uLife expectance, 预期期望寿命8 _6 o J8 a2 n
Life table, 寿命表
4 E0 v8 v& w( P8 ~9 Q% U) mLife table method, 生命表法6 b0 i9 R, }6 B# r* t6 V
Light-tailed distribution, 轻尾分布' w( }) q, y' c p, U
Likelihood function, 似然函数
/ V& o' d) |/ U ~Likelihood ratio, 似然比# H/ K. {- F1 L g8 [) Z. }. q
line graph, 线图
( ~1 i. S% V2 PLinear correlation, 直线相关% d8 W$ p! d3 X
Linear equation, 线性方程8 Y( n$ v) L7 a3 @9 q
Linear programming, 线性规划& Y7 k+ d0 j6 L- Y; J& x
Linear regression, 直线回归% x3 V9 d' h2 B- a0 j- |
Linear Regression, 线性回归
d0 C- d1 Y( n* w4 yLinear trend, 线性趋势1 d! a/ L( o6 j( q( y
Loading, 载荷
' c/ @3 I. X, q, XLocation and scale equivariance, 位置尺度同变性) |& {2 _; N: d0 J; E5 R; `- ~
Location equivariance, 位置同变性
, i0 T: G1 Y6 }! C- u9 g7 SLocation invariance, 位置不变性0 n# ?# w$ q5 x! Z, Q' B1 Q
Location scale family, 位置尺度族; `5 P; e! L; {. e% f
Log rank test, 时序检验
* ^4 ^3 c( v/ Q6 rLogarithmic curve, 对数曲线
! _' x8 v, x# w8 f: `0 {( }" r) gLogarithmic normal distribution, 对数正态分布8 D+ c9 h2 Z1 Y# b) z
Logarithmic scale, 对数尺度
* O4 B; M& `, G8 XLogarithmic transformation, 对数变换5 W$ t; e0 V, c% M; g/ M! C! K* W
Logic check, 逻辑检查# [+ X' S/ v% L, V
Logistic distribution, 逻辑斯特分布9 b! S; `% t) A; a! q+ _
Logit transformation, Logit转换1 h3 ~6 s, R6 {8 P2 Z
LOGLINEAR, 多维列联表通用模型 8 w& T6 o/ T! B4 m, t
Lognormal distribution, 对数正态分布
" G$ e9 R. O' Z2 vLost function, 损失函数6 [: D( f4 ]7 P
Low correlation, 低度相关
% d \2 O, r" G3 X& M" ?$ E' ]7 t0 QLower limit, 下限
( D( J$ N: V7 E3 g' I* G5 KLowest-attained variance, 最小可达方差
- D9 w& W9 j1 ?1 fLSD, 最小显著差法的简称6 m; `2 L* `( f) X v% N
Lurking variable, 潜在变量
% \ H( i. v4 `" W5 ~( n; mMain effect, 主效应5 e! n$ c6 p- Q6 \# Y8 _: K) y
Major heading, 主辞标目9 q& u! @% ?6 k, c5 q# T# @
Marginal density function, 边缘密度函数
5 T J5 T' v$ b( w& NMarginal probability, 边缘概率
( {! b9 d) O: Q: D) _' M* k: z7 LMarginal probability distribution, 边缘概率分布6 K: P, h$ ?8 d: \* K; \
Matched data, 配对资料
$ T$ z% b. ]1 fMatched distribution, 匹配过分布
- V: z d2 O# K/ C( j: D" T* IMatching of distribution, 分布的匹配% _$ W7 f, ?+ ~
Matching of transformation, 变换的匹配
, `' \4 o$ e/ F7 a. e. x2 ^Mathematical expectation, 数学期望' K5 ~7 k- T, X, f3 T& D7 A! \
Mathematical model, 数学模型
1 @7 k8 Q9 a; S" e' s' G7 HMaximum L-estimator, 极大极小L 估计量
" U. b4 q# Z4 S* W2 U) }1 T# oMaximum likelihood method, 最大似然法
1 K1 ]& K* r& F! V5 PMean, 均数. p; |4 p# I" B6 |- i* L; n
Mean squares between groups, 组间均方+ h, p1 A: l( y( a3 W' i4 M
Mean squares within group, 组内均方
9 I! ?" l. B# u5 [( `Means (Compare means), 均值-均值比较
% Z8 G9 v$ N1 Y; p$ _, Z4 `4 DMedian, 中位数
) Z$ S( w$ B- q! q0 Z7 Y. q- mMedian effective dose, 半数效量
& M. y9 q7 z6 n( V' i$ MMedian lethal dose, 半数致死量
# K& ^4 e* E2 m* B7 r+ FMedian polish, 中位数平滑$ y' {- a' B) C1 r
Median test, 中位数检验
/ p9 l: a- y. a# M: mMinimal sufficient statistic, 最小充分统计量- k9 l& I4 \( X% K1 J! A7 `1 t
Minimum distance estimation, 最小距离估计
; N- L$ Z/ S1 c# g' J j0 TMinimum effective dose, 最小有效量' f2 B- X) y) {% X0 n
Minimum lethal dose, 最小致死量9 F v* `* w1 F! v: }
Minimum variance estimator, 最小方差估计量
. P. U1 ? T. _. L/ AMINITAB, 统计软件包
* ]+ b5 U$ s# F; xMinor heading, 宾词标目9 M5 Z0 ?; o: H9 A. C# \+ Q
Missing data, 缺失值* X! q$ w+ I! l0 S
Model specification, 模型的确定
+ `; ?8 a: o8 \Modeling Statistics , 模型统计
( s# X) A+ A. a8 ~9 S9 hModels for outliers, 离群值模型
0 V1 N3 M& v: |6 t+ q& NModifying the model, 模型的修正
v N0 a+ S6 ~+ D8 F' @Modulus of continuity, 连续性模# k) h7 v$ [" U7 M9 {, L1 K
Morbidity, 发病率 ! D$ U. ~% |% r1 a1 ]7 o
Most favorable configuration, 最有利构形9 [+ b- k7 Q6 X+ t
Multidimensional Scaling (ASCAL), 多维尺度/多维标度& y$ \3 g1 B" P
Multinomial Logistic Regression , 多项逻辑斯蒂回归. c2 L0 n- ~7 @! r
Multiple comparison, 多重比较3 u/ N1 ?! b$ C; @! C1 U& Q
Multiple correlation , 复相关% C+ w* h/ M, q0 g( G+ _; J
Multiple covariance, 多元协方差9 ^; a8 ~; K) v. J1 l
Multiple linear regression, 多元线性回归7 e" h2 z: s8 n" a) @$ b
Multiple response , 多重选项2 R% f# k& n. N1 b* J/ ?! D6 R/ M
Multiple solutions, 多解' i+ e( I% H# R; P4 l4 W
Multiplication theorem, 乘法定理
9 A1 s0 S+ U. N' J1 N* AMultiresponse, 多元响应7 ^! \, _4 y0 `+ A' l7 _, G( W! q
Multi-stage sampling, 多阶段抽样- ^7 ^4 x) L2 E \% f5 d! O
Multivariate T distribution, 多元T分布" A0 A3 [* [8 h v3 z' ~
Mutual exclusive, 互不相容
1 h& F2 h, W4 e2 K1 J$ R! xMutual independence, 互相独立
& v4 R* ~* J/ B$ iNatural boundary, 自然边界( G, S7 V( t6 I
Natural dead, 自然死亡; y3 E6 ]6 C* Z3 ~" i" ?
Natural zero, 自然零# j, e6 j$ ?7 M+ W/ S
Negative correlation, 负相关
' {/ D3 o9 K. d6 INegative linear correlation, 负线性相关6 }+ ~/ F/ a! E6 D6 ^. ]$ |
Negatively skewed, 负偏
( @0 M+ x5 k. L4 e% M. T' r+ _Newman-Keuls method, q检验
( A6 {8 G* p* g; r( P) V' Y) L1 JNK method, q检验
- j5 i+ J8 B5 P: T( h% iNo statistical significance, 无统计意义3 T9 h# k1 z' r7 n* D# @$ _
Nominal variable, 名义变量
9 f, ^4 k# E7 {) F) ], e# }, I; mNonconstancy of variability, 变异的非定常性
. a4 I$ E4 @" e, oNonlinear regression, 非线性相关
' ^( i3 V, `8 `0 ?' [( ENonparametric statistics, 非参数统计7 H, g2 {& L& J% d* G6 S9 I3 y
Nonparametric test, 非参数检验
; o" q2 ?- t5 u+ ` [Nonparametric tests, 非参数检验
; Y A5 u3 c7 V$ u6 X+ INormal deviate, 正态离差5 G' c. u# E; t: O4 s6 s$ d$ v
Normal distribution, 正态分布9 Y; C6 C- h! O; l6 {7 V" v
Normal equation, 正规方程组2 D9 f" o$ W* m7 z
Normal ranges, 正常范围$ I2 [# Q1 H2 M$ F& _9 Q
Normal value, 正常值. R- u7 L% Z; h. c
Nuisance parameter, 多余参数/讨厌参数. Q/ i2 g$ s; D
Null hypothesis, 无效假设
$ h& v! f: d, G- r+ p6 t% dNumerical variable, 数值变量
, O& S6 w3 }2 L/ \; B4 GObjective function, 目标函数
2 u) _- Z4 J8 S7 ]Observation unit, 观察单位- t: H+ Z9 J$ V* Q+ V
Observed value, 观察值
( q% D- l' X+ M! G% ^' o8 \9 @9 l+ kOne sided test, 单侧检验2 o+ J/ j! @ h9 @. J4 D
One-way analysis of variance, 单因素方差分析
+ y% R9 b# s0 }7 ?7 [Oneway ANOVA , 单因素方差分析" x7 M. K) L) E, [7 @; P
Open sequential trial, 开放型序贯设计( m; U: \) @6 V/ @
Optrim, 优切尾
+ \$ }, D( f- gOptrim efficiency, 优切尾效率
2 r5 V% [/ w% ~- Y: J) i7 |7 {/ o8 S* EOrder statistics, 顺序统计量
! X" n% O" V, OOrdered categories, 有序分类
! ^$ @/ k# X: |Ordinal logistic regression , 序数逻辑斯蒂回归
; [: P( ?7 S& x' p& o( n6 p7 B8 {Ordinal variable, 有序变量* r1 F! a! l/ u, o
Orthogonal basis, 正交基! h# t/ ]5 ]" o2 w+ M: Q
Orthogonal design, 正交试验设计+ Q% [ v6 Y) ^- c" a! S
Orthogonality conditions, 正交条件# z( D, a$ B% q1 k4 q0 _# \% U
ORTHOPLAN, 正交设计
. z* u3 o9 l& \$ P' n. HOutlier cutoffs, 离群值截断点
+ O% w8 H" \' u' m& Z- n, LOutliers, 极端值
& x. A3 u' @ Z6 x1 \8 m- D$ TOVERALS , 多组变量的非线性正规相关
- w% p' b, x! [4 D/ gOvershoot, 迭代过度
! z- |* n; [8 S/ r' ^Paired design, 配对设计
, A1 T8 P% ^2 d2 ?8 cPaired sample, 配对样本/ r4 X; \7 |, C* ?+ f( ]+ @: W G
Pairwise slopes, 成对斜率
" C# ~+ b7 d/ O$ c6 {# nParabola, 抛物线% L8 }! }. E! f) c$ @8 C: K
Parallel tests, 平行试验
5 u8 T% R9 K+ ?6 T8 x E! b' X) a9 c% zParameter, 参数7 K8 f$ L8 J T3 y# S
Parametric statistics, 参数统计! \3 }; C% Q# M+ U/ S
Parametric test, 参数检验. o1 F( O- ~7 p- ]1 f# a
Partial correlation, 偏相关
7 k$ R# s7 J8 d8 G; e hPartial regression, 偏回归
5 c5 m% V" o# E0 {1 ?Partial sorting, 偏排序0 e5 ^$ h7 e2 {) A
Partials residuals, 偏残差
/ L- v) _6 L4 m4 T8 ?7 x( OPattern, 模式
8 C1 f' x" t: z. ZPearson curves, 皮尔逊曲线* Q: f, | ]1 B/ J+ K
Peeling, 退层
/ g/ j% X* @+ [/ N5 C6 XPercent bar graph, 百分条形图 R) i b7 p* j: o' D2 p$ G
Percentage, 百分比, R) y {& y, w7 D F7 c2 N$ Z
Percentile, 百分位数# p" l; l/ x) k1 |3 k
Percentile curves, 百分位曲线2 j! q+ i6 J! h& K
Periodicity, 周期性
% p* G, B- h1 @6 H- vPermutation, 排列
+ r% I. b7 ~0 ], H1 O$ f3 wP-estimator, P估计量
) _. E, v" Q9 H G' t YPie graph, 饼图& z$ u3 y. k% J
Pitman estimator, 皮特曼估计量7 V% [+ h* M9 T# {/ F6 V% W
Pivot, 枢轴量
: e% u8 C0 `+ IPlanar, 平坦3 R U6 ~5 B4 T' _' ^& U: D
Planar assumption, 平面的假设# `5 Y" h8 }7 Q0 D' Z# S5 [
PLANCARDS, 生成试验的计划卡
4 {* x% L" X5 A# SPoint estimation, 点估计
6 A6 ^( w9 \% w5 ~3 P( aPoisson distribution, 泊松分布
6 V! s. U" p$ a5 s4 t7 B- |9 j' pPolishing, 平滑
, e# \! N: b7 O6 |# ]4 RPolled standard deviation, 合并标准差
' M7 x5 v( o' a: Q. N# A" HPolled variance, 合并方差7 K/ }# b8 L4 n0 f1 Y
Polygon, 多边图
) | Q" K% a5 {: X" D* `Polynomial, 多项式
0 |& T8 s/ T$ D$ M k& f; w& z3 CPolynomial curve, 多项式曲线
8 o3 u0 k9 ^& j8 K5 @6 Y# _Population, 总体7 ^2 y N; G; N0 a6 ^/ g. D* |- T
Population attributable risk, 人群归因危险度' Q. Y o% x1 d2 G
Positive correlation, 正相关
: d J' | \6 s# Y2 IPositively skewed, 正偏
) @( F3 I5 l6 }+ E) u/ ^: |Posterior distribution, 后验分布6 q, S( n) w7 F) Z) }$ V
Power of a test, 检验效能( `4 u. ~, @$ z
Precision, 精密度
& k. k" H/ g% C, ^Predicted value, 预测值% c, p) o( W) f! O% S
Preliminary analysis, 预备性分析
$ \+ Y( B8 e7 J, iPrincipal component analysis, 主成分分析) J& D1 Q, q3 ?; @
Prior distribution, 先验分布6 T* w! g( o/ z6 G1 o
Prior probability, 先验概率
2 Y5 f# y! T% u+ O% g: I" }Probabilistic model, 概率模型
. \1 F' u' [( y+ Yprobability, 概率
; [$ x# `* R4 h- w, A. WProbability density, 概率密度
9 H/ f# F2 L/ e5 t3 ZProduct moment, 乘积矩/协方差
9 l- }5 T5 y% H5 p1 BProfile trace, 截面迹图
/ D& n+ R& c5 D1 hProportion, 比/构成比
, L5 D- x2 D# J2 G5 PProportion allocation in stratified random sampling, 按比例分层随机抽样; z2 f8 q8 t; F# G1 Z a
Proportionate, 成比例
- [* m, D; R7 q( T/ C/ t1 ZProportionate sub-class numbers, 成比例次级组含量- x- k, K$ D. ~8 ?" q: V* V4 w
Prospective study, 前瞻性调查
. N: _+ ^$ ?# v, L& \1 U4 G7 Y! YProximities, 亲近性
W; [5 X7 C2 f( ]8 Q7 B7 c6 K4 \4 ~Pseudo F test, 近似F检验 H7 t) e2 D; K. c% @
Pseudo model, 近似模型+ _- V* w5 {7 ]/ _+ p1 T
Pseudosigma, 伪标准差" m( \) y3 f: d) Y* e( n O
Purposive sampling, 有目的抽样: [7 D a- }- n( y5 p
QR decomposition, QR分解
, g2 ]) n/ X2 q% ~* C8 `Quadratic approximation, 二次近似. e5 J% Q9 w# E5 X) A8 w
Qualitative classification, 属性分类) [( E9 e: C+ _/ h- j8 f, B) S8 C
Qualitative method, 定性方法3 d' X3 [/ Q/ S6 Y. H" a9 ?
Quantile-quantile plot, 分位数-分位数图/Q-Q图
0 l& x2 X0 B& u3 C* z% k4 {8 ZQuantitative analysis, 定量分析
5 ~* o* O( h$ B* d# p. TQuartile, 四分位数
( e2 x& J7 @( j1 ~% M+ `8 ]Quick Cluster, 快速聚类
5 D1 n! @ J+ g% e- S1 U: ~Radix sort, 基数排序& V. m8 ^' t4 O) [. H
Random allocation, 随机化分组
, i6 p& I; @" ^9 k+ Y/ q7 YRandom blocks design, 随机区组设计
( _/ k% \3 s0 kRandom event, 随机事件
" M0 l/ c9 f4 T) z) `* XRandomization, 随机化 P& g' T+ w0 m/ I. D7 ]
Range, 极差/全距
' v: v' }. E- o# M7 y* m1 F$ a, B: I8 uRank correlation, 等级相关% M7 e. p2 U2 ]& H
Rank sum test, 秩和检验
1 i8 _0 q6 L' v* P( g6 P w. L3 G+ KRank test, 秩检验4 u6 Z0 }3 k7 T/ x
Ranked data, 等级资料' E# `( b. ?3 n$ c6 r! U- u3 w
Rate, 比率
% f- s* j( @% k. w4 `4 M/ r% dRatio, 比例
4 o z3 S0 B2 H8 k& d) t5 w; W3 DRaw data, 原始资料3 W" G" L; _8 m% B M5 o- a
Raw residual, 原始残差
$ q5 y! {! [5 n4 j) c- hRayleigh's test, 雷氏检验
0 t6 t! S6 u: N5 `Rayleigh's Z, 雷氏Z值 0 w; m1 k5 a$ U* i, ^3 d0 Q% |7 u% M
Reciprocal, 倒数% T$ d+ G4 _, ?- t7 p
Reciprocal transformation, 倒数变换
9 J) F7 n- U" A. b$ ZRecording, 记录
: r2 C4 o. b* E. ?; sRedescending estimators, 回降估计量$ x3 L# J9 G) ^, L Q. z; r
Reducing dimensions, 降维
5 k* a5 g- t, m1 O; r. ARe-expression, 重新表达1 f8 P- B$ Y) p1 Z
Reference set, 标准组3 r. _' r3 ]' w$ S$ M5 m
Region of acceptance, 接受域9 m, h9 r$ c1 y U. W" c
Regression coefficient, 回归系数. ]* p; J; W7 N1 w% G6 ~
Regression sum of square, 回归平方和
' P7 Q& T/ W% d1 r4 ~% N- ^Rejection point, 拒绝点
8 m; B1 q& U1 K2 i# |$ W7 P+ @! v: {Relative dispersion, 相对离散度. d* A, }( n! { w
Relative number, 相对数 G# q( u( X( o; W! {$ m. _& @3 w1 [9 C
Reliability, 可靠性. B5 k# H& u, q: P+ ?! j# ~
Reparametrization, 重新设置参数
; \5 ~# ^6 k4 ^% d6 G3 @" R9 M0 B# sReplication, 重复* g* Y, K& Q' u' ~: _4 F! M
Report Summaries, 报告摘要
% s8 `* q; l0 |Residual sum of square, 剩余平方和
, c! N0 c7 {( M" e, i; j3 kResistance, 耐抗性
% O7 D4 B9 i# F# Z$ V( ]Resistant line, 耐抗线" b9 ^) e) c a {
Resistant technique, 耐抗技术
. k! K4 q6 B3 IR-estimator of location, 位置R估计量8 ~5 m; s, y% h7 V5 A
R-estimator of scale, 尺度R估计量
6 B6 \' ~7 R4 Q9 h2 f2 n3 ^; lRetrospective study, 回顾性调查! x9 Y' F( Z5 ]8 A6 Z# e/ x3 Q
Ridge trace, 岭迹
6 s8 W# x7 [" i" ?# CRidit analysis, Ridit分析
3 R% W( |' E4 iRotation, 旋转) m) d9 @+ B3 w x* U2 X2 P
Rounding, 舍入
: z! B! U0 s' `- S! @& T; ?Row, 行
5 B) l: E! L4 HRow effects, 行效应
8 R- j9 b f! B6 F6 LRow factor, 行因素" C! I+ ]# Z% T& ]
RXC table, RXC表
0 U9 j; a" [ oSample, 样本
0 Y* L9 S5 H6 B. R( _1 nSample regression coefficient, 样本回归系数
+ m' W" _. s- O! fSample size, 样本量: k8 F9 N4 x0 }3 M | f/ p
Sample standard deviation, 样本标准差0 ?4 x) c/ ]% O5 _8 P
Sampling error, 抽样误差
5 A4 a9 u* K# ~& @6 W: q* B5 ?SAS(Statistical analysis system ), SAS统计软件包
& g. S. T- ?" LScale, 尺度/量表
2 R6 ~: Q9 F i0 EScatter diagram, 散点图. ]+ ^" ~: O6 [- f
Schematic plot, 示意图/简图3 ]! U% r* f2 O
Score test, 计分检验6 s H8 d9 K7 i+ L
Screening, 筛检
3 s8 C! z. O( H2 YSEASON, 季节分析 # U4 T" L0 M" Q/ w) _" [4 `
Second derivative, 二阶导数5 @# v' j: N" b0 K6 N) r
Second principal component, 第二主成分
2 n. `8 U: ]$ ?& A2 ^SEM (Structural equation modeling), 结构化方程模型 / e; }& W0 h/ u- A
Semi-logarithmic graph, 半对数图
0 d3 q/ b. J5 b. JSemi-logarithmic paper, 半对数格纸
; S& O* [1 U1 s% NSensitivity curve, 敏感度曲线+ m$ X, w' I; R4 D) u4 K- n
Sequential analysis, 贯序分析) y8 @ p. ~, d0 `
Sequential data set, 顺序数据集
2 ?! `) _- ^0 b# h, M8 V: d6 h5 C8 PSequential design, 贯序设计1 }3 E, {- u; d! E% `. `
Sequential method, 贯序法4 s, S) M* h6 G$ `& q% E
Sequential test, 贯序检验法 T* |( I. I: Q
Serial tests, 系列试验' Y+ n, w* z* u+ C, V% k
Short-cut method, 简捷法 ' T* x S: U3 F3 J7 l
Sigmoid curve, S形曲线
8 a3 \: J# Y7 h4 e1 {4 ISign function, 正负号函数
5 `4 `# H4 {9 h3 W# a; e% dSign test, 符号检验5 N+ e9 O b1 Q6 b( O2 O
Signed rank, 符号秩
8 V! {$ V2 H0 n1 g! o, Z. USignificance test, 显著性检验
. @$ d5 L( Q8 d1 ]Significant figure, 有效数字
( d3 @8 c( z# z: ]" [* N4 r$ x \Simple cluster sampling, 简单整群抽样5 `# I4 ?* v) n! m7 M
Simple correlation, 简单相关6 s5 ?9 c6 b" t5 u: D, I. U
Simple random sampling, 简单随机抽样
6 K1 q$ w5 }: j9 q- @Simple regression, 简单回归* C0 M, c% o# H
simple table, 简单表
( R* A. |; G6 v9 Y: D& f* h9 }Sine estimator, 正弦估计量$ _$ v, ^- q5 j. C3 Z
Single-valued estimate, 单值估计
+ v" d+ b. j2 o. Q4 oSingular matrix, 奇异矩阵, p8 V, q$ j5 P: d
Skewed distribution, 偏斜分布
! j. ]" I- P6 ^5 q7 X3 h7 dSkewness, 偏度, U4 N; }7 u4 J9 E0 _
Slash distribution, 斜线分布
; a9 { {2 N& U) V/ A4 h1 o8 N8 V) oSlope, 斜率5 ~* b3 [" s! j/ M4 u
Smirnov test, 斯米尔诺夫检验: ?8 K, z/ G- ~
Source of variation, 变异来源! h7 q0 J7 W2 m( t
Spearman rank correlation, 斯皮尔曼等级相关
: B9 R& K+ E+ ~; y$ G% B nSpecific factor, 特殊因子
5 M. R& b( K/ |Specific factor variance, 特殊因子方差6 G5 x9 e: z; O1 [5 s P/ P
Spectra , 频谱! f; B+ K2 ]3 _
Spherical distribution, 球型正态分布
6 j9 \ _" ~+ R2 V2 G: X( }Spread, 展布 o8 z& }9 ^$ b
SPSS(Statistical package for the social science), SPSS统计软件包
4 [2 F6 X$ Z4 w. i/ B* F& gSpurious correlation, 假性相关
1 O+ p% {! H" ~5 `' MSquare root transformation, 平方根变换' }' l# A0 @ c2 o) E7 _9 V* k4 s
Stabilizing variance, 稳定方差
: G* b8 b2 \1 [Standard deviation, 标准差+ Y; W8 s( C# s0 n
Standard error, 标准误0 g9 L4 B& v- |
Standard error of difference, 差别的标准误
9 H8 i. o. O! T$ J0 z# Z& {4 }: ?Standard error of estimate, 标准估计误差1 B5 z6 K! r, t# m& w3 d. Y
Standard error of rate, 率的标准误
( M! r* ?% ~3 b QStandard normal distribution, 标准正态分布
8 W6 y6 ]. O! H8 k2 N# c/ l4 m P1 }Standardization, 标准化
- U. U$ Q! {' R, q- `Starting value, 起始值1 s, Z# Z- ~1 o+ c+ p0 O; a9 b
Statistic, 统计量4 C" n: F2 w' `0 j( o# M
Statistical control, 统计控制. D7 a' i" l9 w& f" A
Statistical graph, 统计图
. D0 ^' ?; H5 o! Y: _6 C# vStatistical inference, 统计推断
4 P* u. ?% X7 r8 [% |& yStatistical table, 统计表. g" R3 A* i2 p
Steepest descent, 最速下降法3 Y+ |' g# h8 Y# y6 e4 W
Stem and leaf display, 茎叶图
% N. g) Z @* u T3 S) `# pStep factor, 步长因子
# C/ s8 O. C/ q, P, C* J) hStepwise regression, 逐步回归
( g% D& ~: J1 T- \1 ]Storage, 存' S7 P8 y) D5 [3 l. o* I
Strata, 层(复数)) c+ ^: T* D1 l
Stratified sampling, 分层抽样& V$ Z2 o1 e$ k7 Z( _# b, j( g" V
Stratified sampling, 分层抽样* `. Q3 W) I- G& U9 K! {" e
Strength, 强度
0 b, d7 F/ D% O2 z4 CStringency, 严密性
2 [6 X. x3 E$ |% [9 XStructural relationship, 结构关系- z! u3 `* {, H0 ?( ^- Y8 Q0 m
Studentized residual, 学生化残差/t化残差
3 n9 ^2 }$ F" L& c9 gSub-class numbers, 次级组含量. R) @* ~8 t* O, n7 E: f2 ]
Subdividing, 分割# ]8 n3 t$ N5 y% g
Sufficient statistic, 充分统计量9 X" G0 ]% ~# V# T1 F) a- T
Sum of products, 积和
, `% R% h [* tSum of squares, 离差平方和4 J4 T$ l2 v8 b& |: B9 e; {
Sum of squares about regression, 回归平方和' } W5 M1 q' k# x/ T3 ~( }
Sum of squares between groups, 组间平方和
+ H# L- x% Y, t5 K) I- M" SSum of squares of partial regression, 偏回归平方和
' N1 S7 I9 w. ?5 v( tSure event, 必然事件! @ R. L! y/ u
Survey, 调查
7 R g. V: m; s3 uSurvival, 生存分析5 Q4 u- T; D1 P+ O/ q6 y. b
Survival rate, 生存率& t- r! u v1 G7 E: `8 t
Suspended root gram, 悬吊根图- n4 t: w% j2 p0 q
Symmetry, 对称
, Q* t& b9 a% Y' a. Q0 T7 {Systematic error, 系统误差
& C; c1 I! Y8 g+ \+ [2 PSystematic sampling, 系统抽样0 A" `; @8 ?+ a+ t5 i' ~
Tags, 标签, B6 A; ^( ~: Z& C( H1 D) Y
Tail area, 尾部面积! q; W D9 C" n i* C7 i
Tail length, 尾长/ g( o" m+ q, p( h: U' g% D# j
Tail weight, 尾重
1 A3 G5 V+ X# wTangent line, 切线
. ^2 ]1 _. E1 Q1 O% m9 i0 I: STarget distribution, 目标分布
; E" A7 c$ l. @* C3 E8 B" E& m! LTaylor series, 泰勒级数
5 y4 I! u$ I) r3 Q. kTendency of dispersion, 离散趋势
. c) f+ c( `$ v! Q- \Testing of hypotheses, 假设检验' o, k! w; c- A5 K( w0 I; x" L
Theoretical frequency, 理论频数. ^# ? K4 x! @) d4 Y6 O; E: s2 ^
Time series, 时间序列. n3 }$ j6 H$ L9 X: A# D2 n R( |
Tolerance interval, 容忍区间" h; M# q: l: B2 \8 V8 ~
Tolerance lower limit, 容忍下限
d: ~( O. K: b' m; bTolerance upper limit, 容忍上限
+ r2 {# T! d5 Z% j& l* F+ GTorsion, 扰率
. H- E* M7 w" p# \+ v9 KTotal sum of square, 总平方和8 F8 ^6 } x; \' Y! C, O
Total variation, 总变异
& O- L" B4 ?3 A( \! B; T! tTransformation, 转换% U; g8 x4 x% ~' A7 \9 i
Treatment, 处理
) o! m- P4 n2 K' C6 E GTrend, 趋势+ q& s3 I/ ~" Z; w3 a8 @
Trend of percentage, 百分比趋势
' o. `+ `$ {3 t) K* bTrial, 试验
, J. {% `# ^+ @, T' \. uTrial and error method, 试错法; P7 {0 T# h$ O& n% L
Tuning constant, 细调常数; N; B9 U5 K! h; R! {- ^' U# _
Two sided test, 双向检验9 v: R# Z5 Q0 Z
Two-stage least squares, 二阶最小平方0 W% A, |0 q7 W4 i; ^: m
Two-stage sampling, 二阶段抽样
7 j% t- I! b5 x3 _Two-tailed test, 双侧检验
# m$ W9 c) m6 M1 q; eTwo-way analysis of variance, 双因素方差分析
% H: o- g6 h: J5 ^2 YTwo-way table, 双向表* C1 A" e7 p+ X( F, g
Type I error, 一类错误/α错误& [. _) U7 j! Y( c
Type II error, 二类错误/β错误
% K _- A. R, x: i6 TUMVU, 方差一致最小无偏估计简称
. f* B7 D& D! Q2 R# ~0 h9 VUnbiased estimate, 无偏估计
4 v8 O( s1 x+ V5 B1 l* sUnconstrained nonlinear regression , 无约束非线性回归
, t V, l4 |. F7 P pUnequal subclass number, 不等次级组含量
3 e5 R4 h' ^" i j* ^( FUngrouped data, 不分组资料8 c4 r; w4 m J x9 d
Uniform coordinate, 均匀坐标
$ E+ {! F& B: Y9 FUniform distribution, 均匀分布
: g# B' i, ^& L& R5 pUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
' E8 ?, w- l$ `1 s( k6 q! r# KUnit, 单元
5 x" ~, _, o5 J2 DUnordered categories, 无序分类
f+ s. L+ Z! G7 C a" W! nUpper limit, 上限- \, |; H- n6 n0 ~9 P0 l
Upward rank, 升秩
! l" f5 Y2 G) \) s/ [' P" O: EVague concept, 模糊概念
- |6 B! E4 e. wValidity, 有效性9 B" y1 J' L( D
VARCOMP (Variance component estimation), 方差元素估计* g, Q0 u4 P0 m# I5 w, T
Variability, 变异性, z# {8 @; d3 [ x6 `9 Z
Variable, 变量8 S* C( i5 q& |& a8 W7 i
Variance, 方差
/ M3 v: [* i$ ^9 b! U, AVariation, 变异
: ]: p4 Z0 P* S" O. O! w. QVarimax orthogonal rotation, 方差最大正交旋转, s; {% ]' f" z! D
Volume of distribution, 容积
' ?9 w: z5 u: Q3 S* g; z, {- k7 ZW test, W检验
+ W9 B4 n5 g) gWeibull distribution, 威布尔分布( q K3 g1 Z$ A6 l1 T
Weight, 权数
( P5 u+ q$ i9 r) _5 sWeighted Chi-square test, 加权卡方检验/Cochran检验- J1 d* S3 v0 q
Weighted linear regression method, 加权直线回归
5 Q5 v8 F) l/ m U2 I$ U6 HWeighted mean, 加权平均数
X+ J% l& l7 p7 nWeighted mean square, 加权平均方差
- j; g9 x" O9 B4 \+ |, w1 rWeighted sum of square, 加权平方和& r0 R' p! M4 _& b
Weighting coefficient, 权重系数
" y6 J! k8 D( R( G" }Weighting method, 加权法 [: ]7 n, B2 D
W-estimation, W估计量( O5 e! d/ ]. j* A1 Y1 g
W-estimation of location, 位置W估计量
$ D( @( T7 N7 I/ e3 s+ X; y) H3 uWidth, 宽度
7 X3 V5 v4 V2 ^3 u" F y6 ?Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验( I6 S8 ?, A `9 ^/ H
Wild point, 野点/狂点
7 Y# p+ V$ c w1 b" MWild value, 野值/狂值
2 t* o* B) U% T- Z {Winsorized mean, 缩尾均值
! b3 d- W* Z; G2 `; ^" MWithdraw, 失访
4 Z& o( N1 E' r0 I% v0 n5 ^+ |- pYouden's index, 尤登指数
5 G* _/ M; h& t6 lZ test, Z检验1 j2 F0 d Q' m1 _4 k* b
Zero correlation, 零相关
6 j0 [9 t+ F+ d; HZ-transformation, Z变换 |
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