|
|
Absolute deviation, 绝对离差3 ]6 b: G( \2 E+ b' ~# I
Absolute number, 绝对数
; u) k- j. E4 I- OAbsolute residuals, 绝对残差% h- ]4 w3 Z) S0 \
Acceleration array, 加速度立体阵
* }4 ~; I6 G- n1 {' T- ~" zAcceleration in an arbitrary direction, 任意方向上的加速度
) S2 M/ E0 [* P. u8 fAcceleration normal, 法向加速度% Y% P% r% o1 H$ d- T- Q0 d
Acceleration space dimension, 加速度空间的维数
+ b7 Q0 \9 ^1 b m; @ xAcceleration tangential, 切向加速度/ i4 P8 p& n1 [2 h- k" F4 {4 Z$ i
Acceleration vector, 加速度向量& {6 _/ u1 o$ _4 v: D) o- y
Acceptable hypothesis, 可接受假设
5 x1 n3 d: b& n3 X/ w" N9 k" E* G; sAccumulation, 累积
6 E( C" e! @' YAccuracy, 准确度
9 d1 o0 c2 U! E6 _Actual frequency, 实际频数
8 v$ b, m8 v7 z g# }0 @% R% MAdaptive estimator, 自适应估计量
0 _& x! z" I1 }$ K3 u$ QAddition, 相加
a8 X+ v" L4 `- U, ]/ {$ k& g0 [Addition theorem, 加法定理
* f. ~" x1 {' w: T3 NAdditivity, 可加性
. `. t. C4 ^0 m- ]: E. b- SAdjusted rate, 调整率, X' H+ _$ b/ X
Adjusted value, 校正值
$ m# ^( ^! H- B8 g/ {& BAdmissible error, 容许误差
( |2 d/ W5 L: c) yAggregation, 聚集性+ W9 E' e8 [' u* E
Alternative hypothesis, 备择假设, ?# R6 y* {) N7 k# z8 S, [5 i# \
Among groups, 组间* ]% P2 K* U! U
Amounts, 总量
" G, V- l9 G) }; c; r8 M" DAnalysis of correlation, 相关分析
3 n" j8 G; O8 b' J% xAnalysis of covariance, 协方差分析
. V' S) F# L. q4 {* xAnalysis of regression, 回归分析- @1 c+ N( h1 S: Z& j
Analysis of time series, 时间序列分析
# Z n( ]0 p2 F0 yAnalysis of variance, 方差分析: E2 O" ^" D. |7 ]5 Y
Angular transformation, 角转换/ f. G6 j& N9 l) J! a" w
ANOVA （analysis of variance）, 方差分析8 a' w. J W% ~0 l7 K. _4 b2 h
ANOVA Models, 方差分析模型 [. U6 H1 G2 `
Arcing, 弧/弧旋
& s K+ n% W) n3 ?8 |: U. VArcsine transformation, 反正弦变换
% B- K' W5 l7 W8 U1 C. n# ]Area under the curve, 曲线面积
# f7 l, S( D7 ]' p- hAREG , 评估从一个时间点到下一个时间点回归相关时的误差
' G( z; v0 Z; u) ~6 ZARIMA, 季节和非季节性单变量模型的极大似然估计
: w+ C+ { N" s* ^0 a4 DArithmetic grid paper, 算术格纸7 q9 q! v5 D, {& O g
Arithmetic mean, 算术平均数+ Q. M% B( N6 m; o$ r% E
Arrhenius relation, 艾恩尼斯关系
) z: a0 L D( o/ G0 ^. a# B' fAssessing fit, 拟合的评估
9 L$ {; ?% Q. p: JAssociative laws, 结合律, q; @9 q; Z) W3 w- L" ^
Asymmetric distribution, 非对称分布
7 I2 y# Y; f) N/ \, V- W+ KAsymptotic bias, 渐近偏倚* X" o h. w; v
Asymptotic efficiency, 渐近效率+ ?! e0 R8 t4 i
Asymptotic variance, 渐近方差, Z; c/ @7 `3 f' L. W0 y0 ]
Attributable risk, 归因危险度% q6 a6 k: R: `8 R* [% w
Attribute data, 属性资料
3 p1 H y. |! J& n. D* XAttribution, 属性/ S k$ U3 |$ b3 v& z2 |2 Y- q
Autocorrelation, 自相关
# o* q+ ]% _4 n9 [7 `! z5 }; eAutocorrelation of residuals, 残差的自相关5 z- `# ?7 p5 ^; F" H1 Z
Average, 平均数9 D6 j' n, w! o
Average confidence interval length, 平均置信区间长度
" u5 L; w! K$ V2 T, NAverage growth rate, 平均增长率; M8 [' c; G: Q$ G2 Y% F
Bar chart, 条形图
! h6 N% z% f" X7 \" `, j" h) m& C) FBar graph, 条形图
, ]4 }1 T1 R" \$ h2 V3 t/ yBase period, 基期
8 ?/ }) v' M4 @# [Bayes' theorem , Bayes定理5 I! f' n4 A: e' {$ H, [/ @
Bell-shaped curve, 钟形曲线
) h# r0 ^" K% ~2 L: r9 x5 z. BBernoulli distribution, 伯努力分布
4 |( i3 t8 g m( p( I+ ZBest-trim estimator, 最好切尾估计量2 }3 q+ T. ?3 V4 f- m- {$ e& n' N3 ~
Bias, 偏性% @1 j6 A0 V/ L; \
Binary logistic regression, 二元逻辑斯蒂回归. d9 b( W3 z$ K( A
Binomial distribution, 二项分布; }8 z( L' ]3 _+ x
Bisquare, 双平方. b, d8 U# J: h; b
Bivariate Correlate, 二变量相关) f7 w& Z2 [5 q0 {* [! F5 M
Bivariate normal distribution, 双变量正态分布
% g. G0 E4 c, u9 k. J; JBivariate normal population, 双变量正态总体
- t8 e' x- Y# W$ y; d& l0 gBiweight interval, 双权区间; H% X5 y, O" k* t- R0 z( H3 J
Biweight M-estimator, 双权M估计量
! y1 s' k+ k, D+ C1 c: wBlock, 区组/配伍组
/ g+ U; G: O. iBMDP(Biomedical computer programs), BMDP统计软件包
& e4 z. ~ Z. }Boxplots, 箱线图/箱尾图
8 S: j+ J6 b+ ]7 mBreakdown bound, 崩溃界/崩溃点5 a) ]' _/ m2 b
Canonical correlation, 典型相关% k( w3 P$ ^6 x7 P
Caption, 纵标目
' V9 n+ a6 y$ I' zCase-control study, 病例对照研究' g. _- _! e: `' D* O% d
Categorical variable, 分类变量3 I+ b2 k8 ?5 b( y1 [
Catenary, 悬链线2 O. h5 ^5 I: Q( o
Cauchy distribution, 柯西分布4 R r% ]; }8 D4 ?( w' r
Cause-and-effect relationship, 因果关系
# [# X& e, }/ d+ OCell, 单元( N, V$ }7 v! a4 q1 [
Censoring, 终检" T7 n/ g; }+ O0 U
Center of symmetry, 对称中心
# K( S, G0 y. `# K9 zCentering and scaling, 中心化和定标
; ?4 I" q6 s$ Q; \6 J% W+ mCentral tendency, 集中趋势
1 u- O! x$ v c. nCentral value, 中心值2 _/ q4 Y; S( T! H9 P; b! Q
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
* L8 ]6 u' A+ \4 k8 v+ dChance, 机遇4 A" a5 ~* R1 d6 h. y
Chance error, 随机误差% w4 P( a2 Z4 G R9 o
Chance variable, 随机变量
# u) p8 o, u, ]: J+ aCharacteristic equation, 特征方程 c( \3 W$ v6 U$ t0 X! ~6 F) |1 f; w
Characteristic root, 特征根
0 }8 R& K+ e5 {! g, i& l7 |Characteristic vector, 特征向量
9 V+ C* N- {' g- {6 }5 Y$ qChebshev criterion of fit, 拟合的切比雪夫准则( h* Q/ X* h. u0 Z: }
Chernoff faces, 切尔诺夫脸谱图 s. P/ [/ n* }6 |/ D5 H
Chi-square test, 卡方检验/χ2检验1 F. q& T. S6 A! ^( C A! U
Choleskey decomposition, 乔洛斯基分解( R- \3 M/ @. Z) y j" a/ y5 G8 m
Circle chart, 圆图 % ^9 R5 W, D3 }+ l
Class interval, 组距
( S& k y% C1 iClass mid-value, 组中值
( T; {8 Y4 x' ^3 _' UClass upper limit, 组上限
7 V& ^. A5 B: i$ h* m# D- y; [" }Classified variable, 分类变量9 d/ s j7 r- s9 b5 r" q8 q
Cluster analysis, 聚类分析! Q, }( C: s7 _( ?5 x1 d
Cluster sampling, 整群抽样
' q* {, P4 v. h; R y* _6 OCode, 代码
9 ]( q; B+ I: d$ v+ G/ wCoded data, 编码数据
' w R$ r/ C; y. {4 |Coding, 编码8 ~) R# Y6 U) F3 R9 K/ x) Z% A
Coefficient of contingency, 列联系数
- t/ l' _* n, ^" t! s6 XCoefficient of determination, 决定系数" d7 J D8 a) y4 @3 X$ k- O
Coefficient of multiple correlation, 多重相关系数 N! _. {4 ~7 ?% N/ U6 ~5 a6 R
Coefficient of partial correlation, 偏相关系数$ A: q+ g+ a3 S4 E
Coefficient of production-moment correlation, 积差相关系数
7 K! l4 e% ]2 U0 {+ k! p; LCoefficient of rank correlation, 等级相关系数 z+ c/ r+ R0 Q& T+ v7 R; u
Coefficient of regression, 回归系数 K$ o+ z; Z! [+ _# `: ?
Coefficient of skewness, 偏度系数
6 {4 J" t+ A; F. r: f5 k9 vCoefficient of variation, 变异系数) t+ G% D2 I2 m' L/ ]) g
Cohort study, 队列研究
/ r; {! _1 b o1 m. E$ c3 v/ m4 _5 OColumn, 列0 S+ Y7 M; d; ?0 j
Column effect, 列效应+ l. _0 g+ @7 G) D) \, n5 g# W
Column factor, 列因素
6 O1 O! L* Y# T6 [3 W3 LCombination pool, 合并
5 a. }; i; O2 @: `4 t c+ ^Combinative table, 组合表
3 Y5 L; V- Z. pCommon factor, 共性因子8 ^, B6 S5 e: Q3 ~# s: @
Common regression coefficient, 公共回归系数) V, X# |+ P, a1 [
Common value, 共同值5 W; }& {. o0 M ]$ w
Common variance, 公共方差 V: l, ^7 s$ F5 k/ j6 r7 x! `
Common variation, 公共变异
1 f3 ~& d2 X5 Q" {) QCommunality variance, 共性方差
9 S1 l: o4 }5 eComparability, 可比性
4 A0 n# v/ p/ f* |6 t1 |9 iComparison of bathes, 批比较5 h4 W% d% S) b D1 G+ f8 c L% G }
Comparison value, 比较值
3 o- n0 t$ D+ S: t* x, z! ]Compartment model, 分部模型' `# O0 G/ T3 E: G
Compassion, 伸缩
) g" w# R1 _0 q1 I+ Y- H% ?Complement of an event, 补事件% p4 A. ^! j) h I8 j' W/ J
Complete association, 完全正相关# A8 _7 A1 c( c* u
Complete dissociation, 完全不相关
0 M2 m$ n! o* L- ?- r) B: qComplete statistics, 完备统计量
$ x7 ?9 O9 f) n/ M9 zCompletely randomized design, 完全随机化设计
8 P0 c2 L& v2 J5 f. ], R+ n* RComposite event, 联合事件
0 m3 f4 w% }) B8 }3 s) u. qComposite events, 复合事件
5 C2 } A' a9 Z' w) n- L. VConcavity, 凹性
! k; r, F( `* n8 \0 {Conditional expectation, 条件期望
/ k7 T" p) f r$ P. EConditional likelihood, 条件似然
' u! P% H P Y k1 c) [- qConditional probability, 条件概率4 m& c u+ o& ^1 _
Conditionally linear, 依条件线性8 I) N5 }( K5 y7 i% r
Confidence interval, 置信区间
& `$ M/ ^+ q$ WConfidence limit, 置信限
! ^9 V5 X8 d) |" F S' WConfidence lower limit, 置信下限
b5 ?# d, h5 @" F" EConfidence upper limit, 置信上限3 b7 K% L& \" O/ f6 _: W+ U
Confirmatory Factor Analysis , 验证性因子分析# ~9 n9 i6 k& @( s+ K3 _7 {
Confirmatory research, 证实性实验研究
U% m/ }$ K. `& q5 a4 mConfounding factor, 混杂因素/ S9 l. C, V' ?) V! K* {
Conjoint, 联合分析$ n4 e; W! I( Q5 Y9 [% T; G/ ]
Consistency, 相合性
! X0 } T& ]$ y0 aConsistency check, 一致性检验
( V5 u1 Z8 N3 y+ |2 _Consistent asymptotically normal estimate, 相合渐近正态估计: @" [. y% A8 L: O
Consistent estimate, 相合估计
1 K, p2 C# o$ L9 V+ GConstrained nonlinear regression, 受约束非线性回归; G9 m+ I _. Q$ @1 W5 I
Constraint, 约束
* N+ V$ n. z0 @# O; eContaminated distribution, 污染分布
( }$ W: ~5 V# I- o3 J/ Z3 u8 KContaminated Gausssian, 污染高斯分布
" P0 k+ O0 g! t. ^* ]! s; J) nContaminated normal distribution, 污染正态分布8 H8 |# h+ U+ A# L9 a
Contamination, 污染 L) Z& o' @2 h$ A
Contamination model, 污染模型
7 A, K( Q" X) M/ \7 m4 _! S6 X+ s. uContingency table, 列联表
" q: E! s. Q% V1 ^- v5 L% @Contour, 边界线2 q6 ?( B5 M! a
Contribution rate, 贡献率
& W0 {3 ]' Q. j7 f" P2 W$ A8 eControl, 对照
1 o! T& Q" K, I& u. g& q2 HControlled experiments, 对照实验
; Q0 S( v7 b4 ?' j2 l- Q; ^Conventional depth, 常规深度4 n; q; t/ T$ Y9 B4 y6 Q
Convolution, 卷积6 u' ~) E) {9 |- l+ z
Corrected factor, 校正因子. m7 E: Y! c' {& r) c- u
Corrected mean, 校正均值 W2 E: h# Z# C9 r- X3 J
Correction coefficient, 校正系数
5 W7 M2 k3 Z! {- R. H% W5 qCorrectness, 正确性1 L8 h2 H; p0 u' a, D" g) _
Correlation coefficient, 相关系数
" I6 d" P N! M1 m( HCorrelation index, 相关指数
\1 m' p# O- }$ g* JCorrespondence, 对应) _( O, i4 q: c9 {, u* M
Counting, 计数
% e2 G. \# ~& n# Z* N% n- D8 zCounts, 计数/频数$ h- {' F$ s e% k
Covariance, 协方差
$ {: ?3 n/ S- W9 r8 UCovariant, 共变
9 l7 w" [- v wCox Regression, Cox回归+ r; U( P1 U7 [- y: l/ d! A
Criteria for fitting, 拟合准则
: {. I8 W( c3 b; JCriteria of least squares, 最小二乘准则$ h! X. v, ?+ ~* K
Critical ratio, 临界比
7 G) l: o8 c2 E8 L/ @Critical region, 拒绝域
1 ]* E4 t; C* w! j; JCritical value, 临界值* i; }6 n, r. ^2 T& {( ~
Cross-over design, 交叉设计
! [9 `/ b6 ]3 b) yCross-section analysis, 横断面分析7 G5 _) v9 T( x) ?, j4 p
Cross-section survey, 横断面调查
* q/ [) M2 e. jCrosstabs , 交叉表
+ O. g7 d( `- u, x- S0 P0 ]Cross-tabulation table, 复合表
( b# A) v1 Y6 Y0 j$ I) \Cube root, 立方根/ r( }3 x. e1 n" n
Cumulative distribution function, 分布函数
4 M$ d! R r. a3 i1 ZCumulative probability, 累计概率
% F8 b* ]/ ~# Q' k3 q% kCurvature, 曲率/弯曲8 V" e) g2 y4 G9 B
Curvature, 曲率0 m1 M3 x6 H! m" T$ l
Curve fit , 曲线拟和 0 E- }# w! P2 y4 z4 a
Curve fitting, 曲线拟合' K) i+ _. g; G: _* [% M2 |* {
Curvilinear regression, 曲线回归 ~1 o4 N5 y3 {1 R% h
Curvilinear relation, 曲线关系
8 Q$ Q2 [# b( S" o$ ^% M* oCut-and-try method, 尝试法
u+ a9 Z, s) J6 T+ Q0 lCycle, 周期
) S9 H$ C" Y z2 `Cyclist, 周期性
) C: A+ D. {$ LD test, D检验7 R& g$ @( |2 ` O8 \" _& m
Data acquisition, 资料收集4 {! X7 k4 k; [& N6 D4 X. z- }
Data bank, 数据库
# N; _# q) @1 fData capacity, 数据容量! K; G. D, N* U- U' [' ^
Data deficiencies, 数据缺乏
9 ]0 h |3 E5 a d, VData handling, 数据处理
7 C Q5 S( G# r, K% p8 z- XData manipulation, 数据处理
! q4 ]9 f8 }. v# ^9 K* HData processing, 数据处理
$ G9 V1 X8 E" |, E9 a, vData reduction, 数据缩减
# u4 ^ M) p: p& XData set, 数据集' U5 h2 Q* ]8 s6 Q2 A
Data sources, 数据来源
4 E5 N; h! a# o6 w- I. mData transformation, 数据变换
& b# Y8 u( s) T& A6 MData validity, 数据有效性
s4 p8 |0 g5 K" n; ~" z3 zData-in, 数据输入% r4 ?9 I, \* h( B
Data-out, 数据输出5 V7 e; W9 ?% C% h2 h+ ?# `, E
Dead time, 停滞期
; p7 p3 z6 ~2 e8 Z2 Z! k& r' x/ lDegree of freedom, 自由度
- S8 v) D F8 LDegree of precision, 精密度
: b: X$ Z5 b: W# p+ i% y8 qDegree of reliability, 可靠性程度. j ?5 V ~4 m; u
Degression, 递减' c2 B% o e, q, S0 a J
Density function, 密度函数
: a. d. R z: ]& J) m3 D) Y$ x! ^Density of data points, 数据点的密度
, v& l0 e6 }" V# s BDependent variable, 应变量/依变量/因变量
: L" y! u8 @1 a3 d9 yDependent variable, 因变量3 _1 m! I& e" Q: e' s# k/ m9 z
Depth, 深度/ @ K/ [4 I8 J+ `5 E
Derivative matrix, 导数矩阵- ? ~# Y0 {' n
Derivative-free methods, 无导数方法
' G8 ?1 E- Q3 R1 ~+ M0 F# ?Design, 设计- D4 w$ {7 E# B' _5 O2 _2 a
Determinacy, 确定性1 B& j% D9 I8 B* B. d4 e
Determinant, 行列式
3 p. a' H& q. {3 lDeterminant, 决定因素
; x3 \ W0 v3 ~& W4 w1 ZDeviation, 离差 D6 q5 m- A' t9 [7 z
Deviation from average, 离均差2 [; O7 {' b, X! A2 G' n
Diagnostic plot, 诊断图
! [8 J M4 c& D/ r6 M: ^Dichotomous variable, 二分变量
, ]3 W P# ]7 ?3 V: qDifferential equation, 微分方程$ c' |6 Y" p s4 m
Direct standardization, 直接标准化法
% C, m3 o2 o! O: @9 DDiscrete variable, 离散型变量2 s& L) Z. q- l4 B6 M
DISCRIMINANT, 判断 : i: s; ]' f+ f* \4 V$ W4 D8 I+ Z
Discriminant analysis, 判别分析
) h% b' n+ s x8 \. d& eDiscriminant coefficient, 判别系数
l" g o" d$ W) N9 s+ Q5 hDiscriminant function, 判别值1 d5 `3 y" A/ D. g% n' o
Dispersion, 散布/分散度7 h1 X- A: x% F8 s, ^. p
Disproportional, 不成比例的
1 d' a3 C+ M8 \/ D' h% DDisproportionate sub-class numbers, 不成比例次级组含量
* p! \5 i% [( l( n% Q7 J" p3 SDistribution free, 分布无关性/免分布
8 d/ f. c* P* K kDistribution shape, 分布形状
, A; j! [" U3 J+ g. C3 P' J# _& kDistribution-free method, 任意分布法. g) q$ R$ G! f) Z6 O
Distributive laws, 分配律# D# d: Z6 L( m4 a, E, V v
Disturbance, 随机扰动项8 o0 l0 \, A$ k( G: P
Dose response curve, 剂量反应曲线
0 ^+ W( m+ \8 `8 y8 D5 \Double blind method, 双盲法/ k3 b; _& {' P" Y3 n$ e1 }+ Y
Double blind trial, 双盲试验; Z4 j. R/ |* a! m" x' S) ^
Double exponential distribution, 双指数分布2 V8 G E0 n1 P& h r
Double logarithmic, 双对数
& t1 x% P: P: IDownward rank, 降秩
1 n1 i) g9 j' S6 oDual-space plot, 对偶空间图, Q( y" q+ o' ]; k. v
DUD, 无导数方法
8 E" Q2 ^! J4 [Duncan's new multiple range method, 新复极差法/Duncan新法8 V' ^& S1 |' L. M. V
Effect, 实验效应/ X+ ~3 M; _1 Y; u7 ^
Eigenvalue, 特征值
& ~( |, ^7 v1 E+ S4 I2 V' M" p* mEigenvector, 特征向量- N# @( R' o; ^7 {) }2 G% O" R! |
Ellipse, 椭圆; h- t% t" P2 G3 S6 G/ X* M, Y
Empirical distribution, 经验分布; {" J% {3 \2 I4 N- a) I
Empirical probability, 经验概率单位% W4 U/ T" f& @
Enumeration data, 计数资料
Q" q8 k2 e) S$ b: YEqual sun-class number, 相等次级组含量
+ o7 n' }' K; lEqually likely, 等可能' B; w' O/ t# ^# ~, }. \' X# k
Equivariance, 同变性 f H! c" g( V0 ~+ X' ~/ ?
Error, 误差/错误7 w' |8 ~8 r: O5 A; ^
Error of estimate, 估计误差" ^2 |0 `/ J, c
Error type I, 第一类错误6 f7 Q1 B$ e ^
Error type II, 第二类错误
& p# r/ P2 j* PEstimand, 被估量
9 i+ M3 `0 z+ j Z& }! T/ w* N* rEstimated error mean squares, 估计误差均方, |7 O0 G2 P6 b* M$ M: F" z
Estimated error sum of squares, 估计误差平方和
, o! P/ }! A$ @4 m) XEuclidean distance, 欧式距离8 ^/ P2 R& l. m y
Event, 事件
, f) i* G% o' s% i1 S: dEvent, 事件( z( Q( R9 Q8 J& M, v" Y. e' T
Exceptional data point, 异常数据点
2 h4 ~% Y5 G1 ?Expectation plane, 期望平面
" Z( H% q4 C8 d( y& o+ QExpectation surface, 期望曲面
& Y) |: [2 @! {2 x: R& X! |- jExpected values, 期望值9 n- v" K# |/ b l
Experiment, 实验0 j4 k2 M1 \5 ~' `
Experimental sampling, 试验抽样
4 ^* X) Q: G. A( n+ H" w8 vExperimental unit, 试验单位2 {( a, u0 n3 b4 N
Explanatory variable, 说明变量6 j/ [6 B3 Z; X3 I8 i
Exploratory data analysis, 探索性数据分析
1 B# h; ^6 Y$ a8 o3 HExplore Summarize, 探索-摘要6 v$ W' S2 q9 g7 n8 X
Exponential curve, 指数曲线
; o! q0 o; v7 [8 e; w2 eExponential growth, 指数式增长
]! r2 O! D* e+ {EXSMOOTH, 指数平滑方法 % w, V4 g. ?0 q- M
Extended fit, 扩充拟合
/ `0 E+ m0 G- C* N& d8 RExtra parameter, 附加参数8 Y0 B3 U+ R# g; [
Extrapolation, 外推法/ I8 _1 F/ ?# g2 {+ x0 a7 _
Extreme observation, 末端观测值
+ e! c& q% n) j7 R, nExtremes, 极端值/极值, H6 K" _' R4 j9 i$ _8 l
F distribution, F分布+ _+ Q A7 I) P8 n4 b3 p5 s4 j
F test, F检验
; H+ J; _4 W' r, v0 g7 E- }Factor, 因素/因子8 q" s. D6 ~5 e K0 o
Factor analysis, 因子分析
9 g4 j& M8 @' ]: H2 M% K, m" j) WFactor Analysis, 因子分析
; ?2 @4 D% m f/ h) U3 M. R5 m% aFactor score, 因子得分 - w6 \' k W% f' B) ] c1 |! Y
Factorial, 阶乘7 q. R# v% }6 `& ~- t: `
Factorial design, 析因试验设计2 [, i, \3 u5 v1 f$ E4 B- O
False negative, 假阴性
5 i9 A2 A; k6 k% c0 @9 F. f5 VFalse negative error, 假阴性错误
8 e9 i1 }+ c5 J# t9 SFamily of distributions, 分布族
/ X& v7 J! U# i2 T1 w, O* _Family of estimators, 估计量族
1 n: h+ P8 T+ AFanning, 扇面. I' c7 h; ?2 Z+ E* Z+ f8 l
Fatality rate, 病死率; r$ m7 _) T/ {5 o6 z; P$ q0 \
Field investigation, 现场调查8 E' l$ ~9 R1 b/ v* z5 z5 W
Field survey, 现场调查
' g* t9 c3 v9 w( q+ W# @5 `Finite population, 有限总体
9 `8 i! x$ M3 n, X6 C8 sFinite-sample, 有限样本/ k7 U z2 e& }# S
First derivative, 一阶导数
9 n v" \6 s2 n' O, |First principal component, 第一主成分( e# e) n# J" O. ^
First quartile, 第一四分位数/ J* [% O5 T' \2 r% p
Fisher information, 费雪信息量
+ R3 X/ t1 u2 Y4 [* w7 NFitted value, 拟合值) r: K6 e' } o# l! [+ \8 T$ C X
Fitting a curve, 曲线拟合8 E: y2 X" c: ]% Y
Fixed base, 定基0 Y) K. l. Y( u; E0 q. K
Fluctuation, 随机起伏: J" o: E& V9 J7 w$ c6 d
Forecast, 预测6 ~' m' T) K, o: a* i. f( G- h# e
Four fold table, 四格表8 G( L( N3 K4 I
Fourth, 四分点
) t j4 N W8 b+ v8 B; \Fraction blow, 左侧比率; A8 e- j! \7 Z5 t
Fractional error, 相对误差$ i4 C3 F/ |. F& Q5 }
Frequency, 频率- z7 I5 P: n9 n% |4 n
Frequency polygon, 频数多边图
4 n* X, ?- l' A. g1 gFrontier point, 界限点
) F4 ^4 p9 O- q A4 t1 J* GFunction relationship, 泛函关系) K# M, t/ K" e7 {
Gamma distribution, 伽玛分布3 U# o5 b# S9 Q
Gauss increment, 高斯增量
4 ?* t+ x( @0 P; l/ _Gaussian distribution, 高斯分布/正态分布4 P) i9 I1 F/ ~* l' L% J
Gauss-Newton increment, 高斯-牛顿增量
5 {# _" j$ J) {; BGeneral census, 全面普查
: |. j( m: M$ F! k3 L4 YGENLOG (Generalized liner models), 广义线性模型
( f$ I) \0 {+ M; LGeometric mean, 几何平均数5 q5 G# q1 _# q$ E8 g3 c& P: t
Gini's mean difference, 基尼均差; O& G! g* a2 R' a
GLM (General liner models), 一般线性模型
& z" L* P- Q7 ]' iGoodness of fit, 拟和优度/配合度) J2 E# I4 ]8 M' @9 I
Gradient of determinant, 行列式的梯度4 a( J& x/ Q. U! M* |4 d2 i
Graeco-Latin square, 希腊拉丁方
# I. T3 S0 z6 lGrand mean, 总均值
3 j) b u) P6 EGross errors, 重大错误8 z0 X: t! A( a E7 D9 ~
Gross-error sensitivity, 大错敏感度
6 G; \7 b2 N8 n+ G/ R: O% @7 {" e6 `Group averages, 分组平均& N* U# ~- _) P$ l2 X
Grouped data, 分组资料" \, I( B$ f2 |( h/ K U
Guessed mean, 假定平均数
5 S$ e1 e0 d: u+ _# z, E1 j0 THalf-life, 半衰期
6 {4 K! X8 S) g; ^! R6 f* ]Hampel M-estimators, 汉佩尔M估计量
- J5 j2 N4 ~3 V9 S. GHappenstance, 偶然事件
( O% D0 h$ P& h. C. P6 |! ?7 I% @Harmonic mean, 调和均数
( T$ e2 F! o0 V/ ^: N2 W/ v P$ T, SHazard function, 风险均数
7 C6 n/ k" n, m% a6 EHazard rate, 风险率/ [! T) c# w' d6 e' \4 a9 \
Heading, 标目
/ |! I/ F" U c* Q; X0 }Heavy-tailed distribution, 重尾分布
& @" U8 j& m) V7 L' \Hessian array, 海森立体阵
6 M# a1 t ^7 k0 RHeterogeneity, 不同质0 Y& O* a/ n9 a# x
Heterogeneity of variance, 方差不齐 ) ?. Y+ Z. u& F* r
Hierarchical classification, 组内分组
4 ]1 C3 u& ~4 k" V! e+ N% i2 GHierarchical clustering method, 系统聚类法. a$ m7 i7 D5 r7 @% k0 ?" U8 \# s
High-leverage point, 高杠杆率点" |( ]) V; C( k
HILOGLINEAR, 多维列联表的层次对数线性模型" V' W/ R1 ]+ H5 s- i, I
Hinge, 折叶点6 ^6 f; a! E& i/ V0 M+ ]
Histogram, 直方图
" N; \ A Z) Y- q/ fHistorical cohort study, 历史性队列研究 ' Z# f4 f: X6 Y( n8 l+ E
Holes, 空洞( t% i& N* z7 h2 N( a r
HOMALS, 多重响应分析! U6 J; ?; K/ @3 C" @
Homogeneity of variance, 方差齐性
3 L% ^+ T! L2 O: AHomogeneity test, 齐性检验2 D. V5 g, w+ Z$ l( b
Huber M-estimators, 休伯M估计量8 }5 s& H! ~- c1 }; l+ t
Hyperbola, 双曲线
' F3 D# S+ P# B1 I4 y! rHypothesis testing, 假设检验
! r+ ^/ w* i& v; i8 b+ }( w" P6 qHypothetical universe, 假设总体4 u, r6 C$ s' v0 f
Impossible event, 不可能事件, I$ d! x0 J R3 j: q+ g
Independence, 独立性
( |. I: ^8 u/ M8 c" b; f3 X1 ~Independent variable, 自变量& r$ m9 g: E# A
Index, 指标/指数
$ A- Q) l' z9 R# I$ }) u# o$ H7 A, lIndirect standardization, 间接标准化法
# a' I: X4 ?& U) l4 |+ S! tIndividual, 个体
# X2 ?" N8 P& EInference band, 推断带# q) p, N- Q) Z6 q' U( t" I" z: W
Infinite population, 无限总体
, B$ T1 e. |0 {8 J# w6 G' r3 Q' gInfinitely great, 无穷大
* I0 Z2 b4 I6 D4 n* l* gInfinitely small, 无穷小
+ A6 @9 q0 h0 }- S( Y" j1 x. g' KInfluence curve, 影响曲线, F4 \+ B2 A" U& F2 m0 F/ a
Information capacity, 信息容量. z" n* ]3 k- I' C
Initial condition, 初始条件- Q& s/ n1 `8 B5 h
Initial estimate, 初始估计值% R. S- b! b1 Z; t! c
Initial level, 最初水平
# B2 d; y+ P5 c- ~% A& }6 Z0 oInteraction, 交互作用$ g+ ], \# A) ^
Interaction terms, 交互作用项
4 f1 F3 N, K' zIntercept, 截距
( s5 t$ N( v; D8 |' w# v: YInterpolation, 内插法
$ c; o6 X4 X7 O [# ZInterquartile range, 四分位距, _5 c, Q1 ?/ ^# B; H
Interval estimation, 区间估计 B6 P- i- U9 Y/ R
Intervals of equal probability, 等概率区间
" l( e6 {# a; i- wIntrinsic curvature, 固有曲率1 W4 T4 I& Q- n- ]% D' ~
Invariance, 不变性, p$ {' G2 P7 x% [ h# C, c* q
Inverse matrix, 逆矩阵
. ]1 L& _0 S4 N; S7 L& p2 z; eInverse probability, 逆概率 X( |) d- _$ s+ r8 u/ b& W$ p0 }
Inverse sine transformation, 反正弦变换- m: s( t( B3 y
Iteration, 迭代 8 e* x9 I# L# h7 J
Jacobian determinant, 雅可比行列式
; ^, ]# ^- h. hJoint distribution function, 分布函数
4 }: J, V$ |% ~# t. wJoint probability, 联合概率3 [/ \+ h$ I0 o( m4 j( u
Joint probability distribution, 联合概率分布
2 q- @4 j1 u# n' B* TK means method, 逐步聚类法
7 V- Q4 R- f/ P! L/ B" b% F% fKaplan-Meier, 评估事件的时间长度 , t# I. Y) d8 E
Kaplan-Merier chart, Kaplan-Merier图( P0 H" v" l: h' A6 b
Kendall's rank correlation, Kendall等级相关
5 r/ E- H# }3 g2 P; GKinetic, 动力学
9 H2 i2 d' L4 X+ _& X) QKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验& Z! K. H0 |$ I1 T. P
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验8 q" l! c9 [+ G c
Kurtosis, 峰度
0 j# r" N* q1 V; @. {Lack of fit, 失拟! N* q9 x O5 A/ g" H
Ladder of powers, 幂阶梯9 z _- u/ s$ k- ]- G; E M" u1 y ?0 o
Lag, 滞后/ I8 |0 q! E7 I5 S0 x D1 [
Large sample, 大样本
8 u+ c) ~6 i/ P) SLarge sample test, 大样本检验9 Y) P: p$ e. A9 v0 D2 ]
Latin square, 拉丁方& `8 t9 D) t9 ^7 P0 {$ C
Latin square design, 拉丁方设计
x Z: R; I* s+ A1 j7 f5 L9 LLeakage, 泄漏7 P- a* M) Q" H; H7 D) s
Least favorable configuration, 最不利构形- f0 s5 b- c/ o. y/ W1 J6 A2 E
Least favorable distribution, 最不利分布: x+ v4 f2 P' e, _8 Q' G, P( r9 D& J* H2 E
Least significant difference, 最小显著差法
1 |5 L6 U( \2 u% C1 X- J, PLeast square method, 最小二乘法
0 {: n4 X+ U- B8 {6 ~3 ^- BLeast-absolute-residuals estimates, 最小绝对残差估计 s* M8 s9 L3 X
Least-absolute-residuals fit, 最小绝对残差拟合
% c7 I/ a/ s: f+ Q0 v9 W1 VLeast-absolute-residuals line, 最小绝对残差线
' V0 A' o/ X- Q, Y+ ]Legend, 图例
& d' v, _- }! BL-estimator, L估计量
& W! {: ?( s. hL-estimator of location, 位置L估计量4 p0 c+ g8 l; P& J c
L-estimator of scale, 尺度L估计量
( x/ r9 J5 Z9 U* b$ c- ?# U! w! R1 y0 dLevel, 水平
( ~9 ^5 B! ?% k% lLife expectance, 预期期望寿命
* d& A8 Y. y u' Y$ {' Z& \Life table, 寿命表
; [ `6 H, C7 |6 Z' M! sLife table method, 生命表法( J4 h7 Y w& F! `: `
Light-tailed distribution, 轻尾分布
: k- E7 `- X6 a9 J! G9 E$ QLikelihood function, 似然函数- Z- j. F8 J( l1 ~2 ~3 G E8 e3 ]
Likelihood ratio, 似然比
* B: z! y0 M0 s* f l) y! yline graph, 线图) i; Y5 K1 {& K2 t3 M- _- Z
Linear correlation, 直线相关
/ Y. y1 R* }9 k& j% W1 F+ ]( V7 HLinear equation, 线性方程) j c6 d) e, P: \& n5 L h
Linear programming, 线性规划
" i7 f" S5 N, KLinear regression, 直线回归& }+ D n4 Q6 }) z
Linear Regression, 线性回归9 C7 I4 J2 \1 Z, L, [# A# }
Linear trend, 线性趋势1 K/ Q# d8 q, B4 }: W/ d, ^6 B5 z
Loading, 载荷 8 r/ ]% ?# t" w) }6 I
Location and scale equivariance, 位置尺度同变性5 y& E/ U6 _- `. o2 e
Location equivariance, 位置同变性
4 n0 L1 l Y/ N6 E6 M" pLocation invariance, 位置不变性
; ~- H" f: D; a8 {7 ]Location scale family, 位置尺度族) l. i8 o/ ~ b- T9 @8 F* e/ V
Log rank test, 时序检验 " R8 |3 x7 F; A0 c U
Logarithmic curve, 对数曲线
4 ]0 `' v% O( z9 A6 i" aLogarithmic normal distribution, 对数正态分布
" h' k6 d* q8 g( ~3 ULogarithmic scale, 对数尺度2 j- _+ S E% M' J- ?+ G8 u
Logarithmic transformation, 对数变换
: \( H6 T7 o; t4 fLogic check, 逻辑检查- x+ x! x! D' M# {
Logistic distribution, 逻辑斯特分布# ?" w; |+ c) d5 n' C. {
Logit transformation, Logit转换
5 i1 x# [( u- d- i) e1 H& L5 B2 zLOGLINEAR, 多维列联表通用模型
8 r. [& P4 t. U0 J9 y8 TLognormal distribution, 对数正态分布
+ i' `9 v/ J3 B k @Lost function, 损失函数
2 F! R9 X1 Y+ l* Y( @4 |9 ?; m- iLow correlation, 低度相关1 b5 j8 x9 }; y2 [+ k) x0 q+ r% t
Lower limit, 下限
9 x1 E' L) H) ^ d* ^Lowest-attained variance, 最小可达方差6 z$ z6 s4 x- R. ], k
LSD, 最小显著差法的简称
) y9 ^; m3 n6 BLurking variable, 潜在变量
. q4 ?0 V9 K4 aMain effect, 主效应, H% F0 D2 |1 h0 I
Major heading, 主辞标目* F" q: X3 h- U$ t( R3 y
Marginal density function, 边缘密度函数
6 f# a, {/ q6 }! a+ x( ?! L5 @Marginal probability, 边缘概率- o3 y) S4 d1 \" B ~/ a
Marginal probability distribution, 边缘概率分布% b/ f9 q( \# ^& ~$ b; h1 h* Y
Matched data, 配对资料
: g% D9 V/ q: i- wMatched distribution, 匹配过分布9 U7 Q" f5 o* t `% _; \% z
Matching of distribution, 分布的匹配
+ Z j0 v3 `4 g" RMatching of transformation, 变换的匹配
6 a/ A3 ` a( G4 `9 T+ F3 I" yMathematical expectation, 数学期望$ I' l3 F. d( X% j: N% H7 x$ |
Mathematical model, 数学模型& @. H+ @8 N3 [6 c& b( ]0 M% D
Maximum L-estimator, 极大极小L 估计量) }* _" M0 O$ W4 e5 b# Y# d+ M
Maximum likelihood method, 最大似然法/ k0 n. x) @2 y
Mean, 均数
" `1 I6 W0 o3 b5 h8 | K2 SMean squares between groups, 组间均方
$ ~" s* X6 _7 E+ A; A! T; RMean squares within group, 组内均方
! A6 @: {. _+ f- ]Means (Compare means), 均值-均值比较
% G) Q. S ?+ X( E# z2 ?Median, 中位数
8 |& E% m& Q9 YMedian effective dose, 半数效量
! L: p0 ]; ]7 M' V- UMedian lethal dose, 半数致死量" X' V: K2 o8 X3 U0 V
Median polish, 中位数平滑
4 n# E$ D' v7 A% Z; X' a( YMedian test, 中位数检验
5 A8 N/ C( d$ _8 ]: j) uMinimal sufficient statistic, 最小充分统计量" R( r! ^- j6 e5 Z p) C
Minimum distance estimation, 最小距离估计8 z2 J+ a( R( Y* K
Minimum effective dose, 最小有效量
( P& F9 `4 d& o& o$ m0 ]Minimum lethal dose, 最小致死量) z$ l& O# L) B+ Y6 i
Minimum variance estimator, 最小方差估计量' |0 N- w8 X/ I$ Q
MINITAB, 统计软件包 k! R6 H2 M+ ?1 K% ~; z5 W$ h, [
Minor heading, 宾词标目
( B9 M5 i# q. A0 |) H, CMissing data, 缺失值% j3 M) u% C4 ?8 w
Model specification, 模型的确定
0 K G' S l4 _7 oModeling Statistics , 模型统计( m; }/ X: z( A
Models for outliers, 离群值模型2 ]6 G; \7 t/ _
Modifying the model, 模型的修正
- y% p6 o5 ~5 }7 A1 rModulus of continuity, 连续性模5 h1 g$ e7 p6 l& H
Morbidity, 发病率
2 i+ X+ Z8 r9 Y/ D8 o$ H! NMost favorable configuration, 最有利构形
! H" x: K" c/ h- J1 ?: u9 ?Multidimensional Scaling (ASCAL), 多维尺度/多维标度1 E" W4 m3 @& t
Multinomial Logistic Regression , 多项逻辑斯蒂回归
% L. R2 {0 l& i' x. XMultiple comparison, 多重比较0 i& U3 o) u8 D0 m
Multiple correlation , 复相关
" y. ^- K2 J- R) d, y5 dMultiple covariance, 多元协方差
" L1 r d0 q( S& M8 X# uMultiple linear regression, 多元线性回归% C& `2 S/ Q- h
Multiple response , 多重选项0 l1 z4 s3 u5 o" L3 D. R* h b6 b
Multiple solutions, 多解7 G. T# w! q+ j2 N% J# B8 d. y
Multiplication theorem, 乘法定理
# A! v+ Y! g+ Z/ \& Z; CMultiresponse, 多元响应- }2 R2 _% P, [: M( u
Multi-stage sampling, 多阶段抽样: ?3 B6 w( w9 u# D2 D# S
Multivariate T distribution, 多元T分布# K# J! t. ~* {! o* M `
Mutual exclusive, 互不相容
4 e& S$ ]7 c9 C9 q5 tMutual independence, 互相独立
+ a4 q6 I& i4 F! e0 rNatural boundary, 自然边界5 A' h8 j8 q' m
Natural dead, 自然死亡1 V2 t7 S* Q4 X" Y" N* h5 Q) Y& E
Natural zero, 自然零
" T U! H2 A9 J8 s, @. [Negative correlation, 负相关
8 r, T, q, k( K3 [0 `2 mNegative linear correlation, 负线性相关) `3 P0 A* g+ N6 {, w2 _
Negatively skewed, 负偏+ F. ^- s( A2 [/ ]0 f6 G
Newman-Keuls method, q检验& m$ J; w- e* c
NK method, q检验1 d: Y7 D0 S |2 C
No statistical significance, 无统计意义
9 I. c+ x3 ^/ l e$ J! HNominal variable, 名义变量4 N0 D4 j, E4 ^! E N$ h
Nonconstancy of variability, 变异的非定常性8 g. X/ q$ J% t1 s
Nonlinear regression, 非线性相关3 w+ P+ I% b, p. z
Nonparametric statistics, 非参数统计/ j8 X; T9 f8 p2 _+ i C- N
Nonparametric test, 非参数检验! z) h( y: z6 P4 _+ t
Nonparametric tests, 非参数检验
% o$ E/ k1 i0 G+ K! w9 R! bNormal deviate, 正态离差
3 ?* W; w7 h4 H9 Z6 x& q, p' FNormal distribution, 正态分布
! B8 O1 U& G* W& i+ iNormal equation, 正规方程组
- y: j' ^7 w! \, z* ?& @Normal ranges, 正常范围, z' }% v N! @" e
Normal value, 正常值$ {; g# b- O$ Y9 |: V
Nuisance parameter, 多余参数/讨厌参数" d! C0 S4 f, n; ^& x
Null hypothesis, 无效假设
B4 W4 x( z2 F& r R- dNumerical variable, 数值变量1 x; S+ t2 @4 `2 g1 r% e9 j2 G. H
Objective function, 目标函数
" i9 \& ?0 f! S, W2 |9 Z0 SObservation unit, 观察单位
7 W- J1 m: ?$ F5 d+ k/ M8 P* W! wObserved value, 观察值
0 D: L" p7 r+ b4 o1 @+ cOne sided test, 单侧检验* Y5 Q: y0 K0 R" E) {3 w2 h
One-way analysis of variance, 单因素方差分析
/ h0 @+ C6 r, eOneway ANOVA , 单因素方差分析
5 N; J( |1 Z# F3 s0 q' r9 a5 TOpen sequential trial, 开放型序贯设计; t, W- x- s! S$ q
Optrim, 优切尾
7 E4 r! a+ Y0 f9 O$ MOptrim efficiency, 优切尾效率
7 \/ w9 Q0 v5 @Order statistics, 顺序统计量' S2 t1 H9 H' q* \
Ordered categories, 有序分类4 \) \3 G$ V! b, _- s, O+ L
Ordinal logistic regression , 序数逻辑斯蒂回归* [1 N# N, I( ^ n5 M; U8 N/ D
Ordinal variable, 有序变量
# R5 o' m `+ _( `2 j8 XOrthogonal basis, 正交基9 \9 Q! p" g$ @. V# k6 O% S
Orthogonal design, 正交试验设计6 b# \8 ]3 I C+ S/ X% a. N3 ]
Orthogonality conditions, 正交条件, i1 @8 \2 V3 p' ^, j
ORTHOPLAN, 正交设计
; s, {2 Q- f5 F/ I; M# B& jOutlier cutoffs, 离群值截断点
+ M3 K0 ~* Z2 S9 iOutliers, 极端值! O6 t: p. x& l8 v( b* x
OVERALS , 多组变量的非线性正规相关 : V) B6 t& c& c
Overshoot, 迭代过度
( b+ E4 ]4 y; E! u* JPaired design, 配对设计
& H# ]. ^0 a' I; DPaired sample, 配对样本; ?, S* \" q, I0 p% k
Pairwise slopes, 成对斜率5 E- b% W) j' M, Z1 Y- L' [
Parabola, 抛物线4 ]) _) |3 ]& K
Parallel tests, 平行试验4 l' |- O" p2 T& x/ f$ P
Parameter, 参数
! c- A( b" r8 w+ V$ l8 y+ ]Parametric statistics, 参数统计( @6 S! h( h9 s( v& a8 ]
Parametric test, 参数检验9 D& l& q) o6 o+ ?3 C
Partial correlation, 偏相关
) ` r. m6 P% G( a2 sPartial regression, 偏回归
8 i7 |- @( C$ p0 Q7 K9 p; uPartial sorting, 偏排序
6 s- w3 M5 k$ j! l6 APartials residuals, 偏残差. [& W. ]& e, Q& V! W' ]
Pattern, 模式 b! I% T8 X* ]# X: q( a1 S
Pearson curves, 皮尔逊曲线
. z! p; Q1 U, R4 {Peeling, 退层
6 ~ G: b0 {% X7 W& FPercent bar graph, 百分条形图4 X: e" L. S% ]& i: C. V' b" T2 F1 M
Percentage, 百分比, x+ _; ^" Z0 V3 C5 J& A H
Percentile, 百分位数
4 x- g; W. y& I7 `5 F. jPercentile curves, 百分位曲线, F6 @0 z% ?4 E4 Q( l( m& K& j
Periodicity, 周期性2 l* `; \+ K3 T! P8 S' O7 H" w
Permutation, 排列: M. _# h% ]5 j0 r5 U, P) `: x. v
P-estimator, P估计量
" c6 z. J1 o; R" IPie graph, 饼图2 m1 c9 \- J a- Q6 m- f
Pitman estimator, 皮特曼估计量 Q& u; D- c" W$ K* A5 D# \
Pivot, 枢轴量
. j% Y8 `0 d! r# ]/ k4 i" BPlanar, 平坦) h; C8 T. q# ]
Planar assumption, 平面的假设7 n# ?9 U) P5 s, x4 a; I$ z4 A9 f
PLANCARDS, 生成试验的计划卡
9 ]* H8 A7 \# _" YPoint estimation, 点估计9 G1 k |. F: F7 J; p- N0 a
Poisson distribution, 泊松分布$ S r, ?9 }; F, Z5 Z
Polishing, 平滑2 |5 M9 c/ w$ S/ E# j7 ?6 m$ N- G
Polled standard deviation, 合并标准差" b7 K; t+ \; }4 l% F! q' B- o
Polled variance, 合并方差
0 b6 ~$ j% r8 d: o; uPolygon, 多边图8 U( w9 w5 z6 b7 p
Polynomial, 多项式6 I" B+ m8 f! I4 {: {( Y7 |, V7 Z
Polynomial curve, 多项式曲线2 }1 Y7 \, ^4 i+ S! k3 G; a# F2 C) v
Population, 总体
1 v3 P8 @) I. K! K( @5 v9 WPopulation attributable risk, 人群归因危险度; G; z" n4 D2 ~
Positive correlation, 正相关8 T: b- v( A2 ]5 Y) {8 V4 G
Positively skewed, 正偏
3 k# d/ S& Q$ D6 _( \Posterior distribution, 后验分布
6 g. ^# z, K7 B2 WPower of a test, 检验效能& k; Y! R# \( y0 G) d9 c! P( l
Precision, 精密度
1 G/ @$ R8 a! [ D% DPredicted value, 预测值
, E1 y* @7 m m7 B3 |; \; ~Preliminary analysis, 预备性分析
' K% Z/ Y. K! sPrincipal component analysis, 主成分分析( `0 j F' D' H
Prior distribution, 先验分布; K- X) ^- M* a$ b' ?* s
Prior probability, 先验概率
d* F: g" S" NProbabilistic model, 概率模型! j0 u* e( j3 y$ I
probability, 概率& z2 |4 n$ p) b4 w: v! |( S/ |
Probability density, 概率密度, C( ^) y) M% H4 s c8 R/ |/ D" v
Product moment, 乘积矩/协方差
1 t7 x; K" ~+ L9 O+ WProfile trace, 截面迹图
2 p' P: `# C, \0 q, C* IProportion, 比/构成比3 H5 v2 v: G, C7 ?: @9 W5 S. ]% F+ H
Proportion allocation in stratified random sampling, 按比例分层随机抽样( C, L# z: I) v1 C' I4 {# J
Proportionate, 成比例6 `0 B" k# I; V5 P
Proportionate sub-class numbers, 成比例次级组含量
! L, Y! T# K H- M2 c4 Q3 eProspective study, 前瞻性调查2 M3 H/ v" @; x# W; z. u m9 e
Proximities, 亲近性 # T" d9 j- @- J( r3 P
Pseudo F test, 近似F检验
! f0 [1 o3 A$ h/ r+ `Pseudo model, 近似模型 e# x n) t# l, [7 h/ u, O
Pseudosigma, 伪标准差
K( J* L) m9 K, v% |$ E3 oPurposive sampling, 有目的抽样. d" k E6 y8 F+ U- \1 I% W
QR decomposition, QR分解
0 }" J1 q" h% FQuadratic approximation, 二次近似1 k+ K$ E; U& x! W7 m, y4 r9 o
Qualitative classification, 属性分类7 |2 [, @+ C5 o# m2 F
Qualitative method, 定性方法
$ d9 i# i5 q/ w7 EQuantile-quantile plot, 分位数-分位数图/Q-Q图 c2 l: O+ q0 b' n
Quantitative analysis, 定量分析+ a9 ? g; J8 q9 I( w9 o& C
Quartile, 四分位数. o% t/ Q$ Z7 ]2 ~& a$ Z: D
Quick Cluster, 快速聚类2 D* E E- K( f% a7 A
Radix sort, 基数排序: y, I, D4 \- I0 w$ l, n
Random allocation, 随机化分组6 I+ K$ ^: {) h
Random blocks design, 随机区组设计
4 x- |! D& D5 i- f: {8 j* hRandom event, 随机事件
0 C3 m3 N3 \; A, D! R9 k, P# f$ ?Randomization, 随机化
- t) }% D* O1 c9 P2 [3 cRange, 极差/全距+ [7 N3 {5 f, d
Rank correlation, 等级相关6 [$ ]+ r/ o1 j5 R2 w o7 E" F2 Y
Rank sum test, 秩和检验 d% y) U. u3 W, F2 k+ a6 w5 p; U
Rank test, 秩检验
* k* E" p# o/ J* O5 [Ranked data, 等级资料
7 q$ M% K6 q( l, O8 ?Rate, 比率: h9 {6 f2 d4 d! y: E/ s/ }) f
Ratio, 比例7 Q" Y# {' k6 m- u8 _% x& C
Raw data, 原始资料3 i" M+ u$ F ?, |9 W. I
Raw residual, 原始残差9 r+ _$ ^" V& ] w7 w4 n, @
Rayleigh's test, 雷氏检验9 _+ ?) Q9 {9 U" A
Rayleigh's Z, 雷氏Z值 0 ], H, D2 k0 `
Reciprocal, 倒数- n- R$ ?' w7 Y5 @6 n
Reciprocal transformation, 倒数变换
& T7 v9 @& [( o ^1 {Recording, 记录
. ?0 ]0 p* g! s! |" LRedescending estimators, 回降估计量' f- p" F$ q: f1 K
Reducing dimensions, 降维
3 r+ V& R8 E: k; \* Q( a" ]1 WRe-expression, 重新表达
, ~0 J" C0 i5 q, M/ H4 ]Reference set, 标准组
3 z! r) f4 E, M4 e/ V% |. O( YRegion of acceptance, 接受域
8 e1 r0 m4 Z' j, O+ z; d, fRegression coefficient, 回归系数0 Z9 j; W& |3 _9 i! A
Regression sum of square, 回归平方和7 b8 C# p. t; U" K/ M
Rejection point, 拒绝点 r, Z1 u0 S- p' s- Z
Relative dispersion, 相对离散度
( }* U: f V) MRelative number, 相对数
2 V9 L1 y& P* s2 FReliability, 可靠性. K7 W7 X! E3 M
Reparametrization, 重新设置参数
8 M W5 k3 Y. N5 ^8 `2 sReplication, 重复
# i2 s; ?$ c& [/ f: S9 a+ w/ dReport Summaries, 报告摘要
[8 Z0 X8 L; L8 MResidual sum of square, 剩余平方和6 D1 Q+ B- J- a- ^
Resistance, 耐抗性
# N2 b, t+ V h+ o* G5 @Resistant line, 耐抗线
" V7 S5 ?$ ^" Z, D+ A: ]6 IResistant technique, 耐抗技术+ P) P9 t/ t% n5 {
R-estimator of location, 位置R估计量% Y/ R8 A! b- V5 s O
R-estimator of scale, 尺度R估计量
( @6 `+ H' ` S# y& R# IRetrospective study, 回顾性调查
! T; T" ? b3 W, sRidge trace, 岭迹0 M M; ~# S# t* A2 \8 T
Ridit analysis, Ridit分析1 K0 v# G9 z5 x, B5 c# o ^
Rotation, 旋转) U. z; y$ ]) D1 S
Rounding, 舍入
b) w& K( }3 N% @& j) ^Row, 行' P$ T8 @0 G( Y9 Z$ e& H3 V* G7 @2 }
Row effects, 行效应
0 Y, K( Q. d; {- B* Q1 |: p0 SRow factor, 行因素* t5 l; z; E2 o8 M, w
RXC table, RXC表) N8 d* o& _' d5 \, _ K0 {/ e
Sample, 样本
2 Q v. l7 l. [7 C. LSample regression coefficient, 样本回归系数
$ S2 M! n0 U7 \: p- p& nSample size, 样本量
. Q* N* }2 B! }+ Z5 Z0 T3 S* [- N) p) E8 ESample standard deviation, 样本标准差+ ~& Y& L3 V7 `2 G/ f
Sampling error, 抽样误差
7 O/ F( s2 c' a, f: VSAS(Statistical analysis system ), SAS统计软件包
6 n% C- `' h6 ?$ |4 k" n" ?Scale, 尺度/量表
0 q6 g8 D8 ^7 vScatter diagram, 散点图: A/ }7 [" X. W7 H4 m0 U
Schematic plot, 示意图/简图
( B/ a! r6 ~7 s( O+ v$ ]0 WScore test, 计分检验
3 q6 ]* M6 Y7 f- qScreening, 筛检
+ a' E7 r7 G+ g# N. @( W6 YSEASON, 季节分析
* C, y/ Y- _! GSecond derivative, 二阶导数
1 o; \" j) v; A9 \9 kSecond principal component, 第二主成分* o$ s4 D+ P* f( y3 B
SEM (Structural equation modeling), 结构化方程模型 4 _$ a5 g: W O; n
Semi-logarithmic graph, 半对数图
3 R1 p8 n9 p5 N% h) YSemi-logarithmic paper, 半对数格纸
1 k; d: }. N" p6 a. w3 ~( H6 nSensitivity curve, 敏感度曲线" ?- ^% K, W! X6 ]6 w+ b! N4 b
Sequential analysis, 贯序分析
3 E1 I# o4 v8 R; O! o8 P) ESequential data set, 顺序数据集
+ z! a5 @* p* P5 }& [+ q$ y' ASequential design, 贯序设计
2 O1 j; U1 v8 w" b% w8 bSequential method, 贯序法
. ]% t2 y5 a. ^. U& V2 O6 g' DSequential test, 贯序检验法
3 D) x9 Q( z% `2 q6 `' pSerial tests, 系列试验
: M, J( y+ ]5 q7 w$ LShort-cut method, 简捷法
* c* K3 r* J5 H* h( Z/ p2 n" zSigmoid curve, S形曲线5 r( I% C) M0 I/ }9 {1 v' a! y$ g
Sign function, 正负号函数
9 U8 i: `' q& N+ YSign test, 符号检验
) u3 P6 j6 H% Z% BSigned rank, 符号秩
/ d1 t& u- Z9 l4 ]Significance test, 显著性检验0 v6 \3 m2 k) ?+ F" C4 k: f. x
Significant figure, 有效数字) b7 F8 G& P* S* I; U2 J( l
Simple cluster sampling, 简单整群抽样
1 O* T/ G: z3 E8 z# l8 ]$ iSimple correlation, 简单相关
! t0 P8 k7 J8 p& g2 CSimple random sampling, 简单随机抽样
- U/ V+ @, S; f* f' S% `/ M) _Simple regression, 简单回归: Q& F7 N! t) Y$ a x/ z
simple table, 简单表
$ u* A: p( I% u, S* Q4 b* M. |Sine estimator, 正弦估计量
3 x4 }+ E" q6 z+ hSingle-valued estimate, 单值估计
4 F, c6 C( t* [* g0 xSingular matrix, 奇异矩阵1 O3 G) b% I( K: l6 C( z# l
Skewed distribution, 偏斜分布
$ H7 O$ a* f# |+ o% E y2 ?Skewness, 偏度0 t# b, c2 o- Q" _0 |
Slash distribution, 斜线分布6 v8 T( q! h6 _ Z) Z, r7 r
Slope, 斜率
) v' D/ n' i, ?' I$ X9 n! mSmirnov test, 斯米尔诺夫检验1 W1 _/ }/ p# r( z* q
Source of variation, 变异来源
5 c) e5 K, x) f7 K: l, A- c! _Spearman rank correlation, 斯皮尔曼等级相关
. v8 S, G4 J: c/ Q9 c2 i) K/ ?7 KSpecific factor, 特殊因子; b9 I/ o2 M3 _# B/ O! C1 R) m
Specific factor variance, 特殊因子方差; U. f) a- n/ L* ^) y+ T
Spectra , 频谱
* M( Z% p' N9 ^, b4 `+ CSpherical distribution, 球型正态分布, @% L7 }( O0 I
Spread, 展布
" k7 Q3 i% T1 m7 b I. uSPSS(Statistical package for the social science), SPSS统计软件包
! u/ K9 A L& q7 C% nSpurious correlation, 假性相关# R4 G! d4 w8 D& m6 R. ~: {
Square root transformation, 平方根变换3 p: T) n: v3 T0 B
Stabilizing variance, 稳定方差
0 b- c/ B" N" }, b( S1 hStandard deviation, 标准差, c0 a1 d2 o- o7 ^% h* Y( g4 j
Standard error, 标准误9 x8 S( q& ?" D% D
Standard error of difference, 差别的标准误
) B/ N1 Y9 S/ l# SStandard error of estimate, 标准估计误差
! d* a, {& `, z+ E8 R0 TStandard error of rate, 率的标准误5 n- S8 H1 A) d8 q% l
Standard normal distribution, 标准正态分布
k; e: L8 y3 {& qStandardization, 标准化
$ r# ^. g. P4 l0 ^8 xStarting value, 起始值$ v* ]9 I' ]) W4 X6 l% X. c
Statistic, 统计量
/ r$ Q0 X4 q0 z9 yStatistical control, 统计控制" \" p! f" r u" {/ _0 y9 w
Statistical graph, 统计图
+ g% z3 ^" s* F$ T, R4 GStatistical inference, 统计推断
; q. [ a8 r2 IStatistical table, 统计表* @+ I" B0 I3 f5 I
Steepest descent, 最速下降法9 ]( T2 m. Q2 H1 q
Stem and leaf display, 茎叶图
/ s8 I: U* C* c6 e2 Z2 @. yStep factor, 步长因子
% R$ n9 d1 e# W( g0 EStepwise regression, 逐步回归% N8 N! o, F9 P
Storage, 存
0 p X/ a( e( A" Y; XStrata, 层（复数）
# D0 T$ i4 ^+ EStratified sampling, 分层抽样
. n: V z( K3 R/ {9 [' g" cStratified sampling, 分层抽样
; A) _7 f0 s2 s$ K6 E$ [Strength, 强度% ^6 o; J$ r3 ^7 S" `" Z. j P u
Stringency, 严密性- U$ E) `1 ?, k- K
Structural relationship, 结构关系
G3 P6 P) {$ c5 O( ]4 k, CStudentized residual, 学生化残差/t化残差- [8 B5 I+ G# `# K( ~. G! F
Sub-class numbers, 次级组含量2 r; h( }( v* C4 O, i
Subdividing, 分割9 s( K. H7 a& ?/ H, w( z
Sufficient statistic, 充分统计量5 s' \' |4 Z! h" u
Sum of products, 积和% v/ A7 D% S) E# O
Sum of squares, 离差平方和. y, e! U/ i# m7 o
Sum of squares about regression, 回归平方和1 ] D$ u% M0 Y' n- e7 `
Sum of squares between groups, 组间平方和
5 p. x. K3 k0 PSum of squares of partial regression, 偏回归平方和; Z$ [( G1 g& [( d
Sure event, 必然事件
, j: u; V+ O& |3 X/ A' l% kSurvey, 调查
& b2 _: L6 m8 Z9 n9 U6 y5 wSurvival, 生存分析. ~! K- q, V* ~4 A. q
Survival rate, 生存率& ^& F0 v( ^. h! Z9 D# S
Suspended root gram, 悬吊根图
$ {; l* v4 j! X. CSymmetry, 对称( j/ [6 {8 K. T! K+ L+ U! {
Systematic error, 系统误差- Y4 A4 U8 x* M7 V
Systematic sampling, 系统抽样
4 [' ~* [0 D( H$ Y# [+ DTags, 标签
9 f0 i+ s9 \. b* ITail area, 尾部面积( ~: r' f# Z# Q
Tail length, 尾长
" M, z& N- h* `! b( r; |* oTail weight, 尾重
" \7 O* a, | p3 ^* |Tangent line, 切线
$ D8 ?/ q6 }/ N# I! J4 ^* TTarget distribution, 目标分布
G/ N) j6 |$ Y6 gTaylor series, 泰勒级数. v) D( Y% ]; a" H9 Y# b0 g
Tendency of dispersion, 离散趋势
) `9 G, a" {( A" v4 }2 I9 e) O4 {. G7 fTesting of hypotheses, 假设检验
0 }- G) g" f3 ]7 E& FTheoretical frequency, 理论频数" L9 c/ ?7 S g+ I7 M; V5 F
Time series, 时间序列
3 k$ m1 G$ B: g9 B' C' ]; V$ FTolerance interval, 容忍区间" d+ H) u. S3 P' r
Tolerance lower limit, 容忍下限( ?! d0 Z: m9 R& _% \
Tolerance upper limit, 容忍上限
, x1 R9 B' L% a* @; [; T9 b5 k' BTorsion, 扰率
& T, V7 Z( O5 [0 R4 jTotal sum of square, 总平方和5 O" w, m0 A/ d8 e$ A, D: ~
Total variation, 总变异9 p# ^+ \& f! q6 {$ W
Transformation, 转换
- I4 h1 O1 M9 A6 m$ l& TTreatment, 处理
/ x! F. L5 k, O I2 ^8 Z# ]Trend, 趋势; V5 `! [; ?6 t) k
Trend of percentage, 百分比趋势
3 R5 v* C, s' Y/ e# ITrial, 试验
+ h2 c2 [ f) `' c; [Trial and error method, 试错法% ?0 z* ?& I M8 k2 m
Tuning constant, 细调常数' m( X6 p2 ~) M+ ^5 c9 F
Two sided test, 双向检验- {* Z% ^4 [ N) ^4 ^
Two-stage least squares, 二阶最小平方
* W- H5 |5 W1 y: _/ l: d6 b5 zTwo-stage sampling, 二阶段抽样
+ n2 u( a4 n- k s( M8 @8 lTwo-tailed test, 双侧检验/ [( |8 l1 @) b- p4 g# k' l( v
Two-way analysis of variance, 双因素方差分析" A6 l5 N* Q6 j1 z1 Z: y. M
Two-way table, 双向表6 d" d# l1 M, D( c
Type I error, 一类错误/α错误
" J1 e& u4 B5 U. A5 HType II error, 二类错误/β错误* [ D5 U. A/ n* f5 |1 L6 C
UMVU, 方差一致最小无偏估计简称/ F# l' Y2 N& B2 T* u6 K
Unbiased estimate, 无偏估计" E r( Z( Z: s. b* N$ O" V* D7 M
Unconstrained nonlinear regression , 无约束非线性回归$ Z6 V3 ]" ~9 j) W8 k' j
Unequal subclass number, 不等次级组含量
& _3 |6 S9 G% Y @. W* a4 v& L& ~Ungrouped data, 不分组资料
( z, A( {; t# z$ VUniform coordinate, 均匀坐标- }3 [3 a- e M1 M4 k7 P
Uniform distribution, 均匀分布3 t$ |& f, b$ k) D7 g5 c
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
+ ?5 C# m( b5 ~; u- n4 KUnit, 单元" Q- d4 T9 B7 \. `
Unordered categories, 无序分类5 A! `. v$ r2 t# O& P) U0 c
Upper limit, 上限
6 [. _2 B" @0 `# l* S- ]& E( |$ uUpward rank, 升秩! G" b2 ?, P6 W9 d- j! T# M
Vague concept, 模糊概念0 e% Z3 f' t- L4 u6 m0 ~& F
Validity, 有效性
1 C. Y+ b; [/ ?" Q) g( E& {VARCOMP (Variance component estimation), 方差元素估计
& p& U' n! e+ B9 a. Y9 u, v7 tVariability, 变异性. @' z4 c" G, i. O& p
Variable, 变量8 M C+ ~% }& J' H4 h0 x
Variance, 方差; e% f6 f( Y: A9 [: z3 |8 R
Variation, 变异. T. J7 [9 t+ Q% A8 h4 D
Varimax orthogonal rotation, 方差最大正交旋转3 [3 |' X: p; \/ Z% S) C q% C; H' z
Volume of distribution, 容积% E x5 q7 {8 S$ p" J2 g: m
W test, W检验5 k7 ^1 r) Q2 ^" P& ?
Weibull distribution, 威布尔分布
" o* K7 z) f, K. DWeight, 权数! b7 ?7 f/ g; `2 J3 n4 E, v
Weighted Chi-square test, 加权卡方检验/Cochran检验0 W6 j- S# p) P" }, M: J3 k9 T9 d4 K" u
Weighted linear regression method, 加权直线回归
; Q7 M5 Y X/ k8 |: gWeighted mean, 加权平均数: N. {$ b5 u* m5 ]# ^' Y, `6 U
Weighted mean square, 加权平均方差$ @1 O$ N4 I! G) ^$ r, g2 M* K
Weighted sum of square, 加权平方和; V1 i; V: `( I- Z) B, y
Weighting coefficient, 权重系数
; v% X4 E( t4 x9 {( @Weighting method, 加权法 ; s: k0 [, i) t3 M8 [
W-estimation, W估计量# C9 Z$ B9 S2 _, V
W-estimation of location, 位置W估计量# i3 O; w! c* F) R
Width, 宽度7 ~3 @& {% S9 f" q6 Y7 h2 ~
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验* L+ x8 Q4 j7 ?( W* k9 S' J$ B
Wild point, 野点/狂点
/ o7 L0 W* m5 z6 J* LWild value, 野值/狂值
% f/ A& t- L1 w- w0 XWinsorized mean, 缩尾均值
, r% J. D+ f2 N& P9 g( SWithdraw, 失访
z- P/ ~ w2 ^% }Youden's index, 尤登指数
1 d4 [. {8 |, k3 b/ |# x8 C0 wZ test, Z检验
2 M6 W4 {% `5 D% LZero correlation, 零相关1 _) a" O2 G1 r* s8 k
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
