|
|
Absolute deviation, 绝对离差
; G& a' [% w3 O. R. u" V: UAbsolute number, 绝对数8 k9 `7 z5 V, X ^
Absolute residuals, 绝对残差
$ G1 ?, d2 P& U3 C. fAcceleration array, 加速度立体阵
$ T; [' o; G+ Q7 G* _Acceleration in an arbitrary direction, 任意方向上的加速度" P. D6 x9 t: @9 G; y+ r/ c& _
Acceleration normal, 法向加速度
1 h6 A6 e2 ]$ v d% a6 EAcceleration space dimension, 加速度空间的维数
7 D; G6 [4 D: }% QAcceleration tangential, 切向加速度# U6 K7 E# d9 b* Y. f- y
Acceleration vector, 加速度向量3 T- d6 u4 _8 E3 Y+ V! r
Acceptable hypothesis, 可接受假设5 T/ d# C6 n7 K- n. S
Accumulation, 累积
! R0 J0 a6 {$ a) `) ~Accuracy, 准确度7 `5 D# ~7 p7 ?( i( V, k; K
Actual frequency, 实际频数4 {) P: }5 P/ L8 H Y% n9 b* h
Adaptive estimator, 自适应估计量; x% F* b: _7 Y; {+ Z, I j9 m
Addition, 相加
- O# K3 |4 z( D( r( l) x OAddition theorem, 加法定理: J& ]2 s9 c1 X
Additivity, 可加性
, Y4 n$ |0 r( z0 e$ S1 q- TAdjusted rate, 调整率
0 \3 y- |+ X3 X( D/ X/ E5 nAdjusted value, 校正值( c% @2 n/ `! J: J( \) n( h
Admissible error, 容许误差
' F9 v! ~0 v E: B7 zAggregation, 聚集性
) O, g i# W( j- IAlternative hypothesis, 备择假设% X5 A9 i0 a7 U6 c% d
Among groups, 组间
( F3 g/ V; t0 _# u: i& K5 CAmounts, 总量& W t" |8 K7 m5 `( h: d# M
Analysis of correlation, 相关分析
3 u5 v) S! U' E! A& _( h1 G QAnalysis of covariance, 协方差分析" ?/ k0 f4 G8 {6 a/ L% G$ a( V
Analysis of regression, 回归分析
) M, R! i2 \$ W: Y1 S4 ?: {1 YAnalysis of time series, 时间序列分析7 B3 T H8 d8 h' E
Analysis of variance, 方差分析
; R$ l. v+ |/ f9 KAngular transformation, 角转换! S! K3 M v5 P( K/ y ^* U/ U
ANOVA （analysis of variance）, 方差分析+ i" r) m" [( f$ h9 d' z
ANOVA Models, 方差分析模型
( g" t+ s/ a3 B. n' g0 mArcing, 弧/弧旋
+ A( ~9 z, g$ X& |) d. s: xArcsine transformation, 反正弦变换9 g: r. B) w A# j. y/ ~
Area under the curve, 曲线面积
$ s7 X* I+ y' ~# cAREG , 评估从一个时间点到下一个时间点回归相关时的误差 . [ H" W: K2 f8 ~8 l
ARIMA, 季节和非季节性单变量模型的极大似然估计
+ q* B* n0 O3 u* o' ]Arithmetic grid paper, 算术格纸$ [# J1 ~. q" F/ Q8 m4 X! v
Arithmetic mean, 算术平均数9 M+ p$ R+ V- H
Arrhenius relation, 艾恩尼斯关系/ n7 k) ~/ K$ S9 Q5 m
Assessing fit, 拟合的评估9 h' Q& G0 u. c. L0 N6 Z
Associative laws, 结合律
' A* R2 B0 J% SAsymmetric distribution, 非对称分布 Z: C0 U3 Y' p, T8 ]
Asymptotic bias, 渐近偏倚, Q* l5 b9 h8 |5 ]$ s5 a
Asymptotic efficiency, 渐近效率
! |* m+ V& S& F2 K9 W: X7 hAsymptotic variance, 渐近方差
6 w2 E* E( e7 a7 a9 kAttributable risk, 归因危险度
% X @& `# s. z$ C# k' r& w, X5 G7 qAttribute data, 属性资料$ G* _) I5 C+ |" F' u$ f3 H
Attribution, 属性
7 j u' v. ^$ ~0 O5 B) o/ zAutocorrelation, 自相关* K1 F" E2 w4 o
Autocorrelation of residuals, 残差的自相关, F6 V/ ~" K, l; [" a
Average, 平均数
1 P* P2 T( @' v0 O GAverage confidence interval length, 平均置信区间长度
1 }) I8 _& I: N$ ]# O: qAverage growth rate, 平均增长率
* ~& x# V6 m3 d$ C1 b" L, ~1 u: o! UBar chart, 条形图
. F( k) {+ U( v3 r( G( h+ P; wBar graph, 条形图4 I8 i* O! F! I0 A" i: P
Base period, 基期, x( [! j" t! V3 j
Bayes' theorem , Bayes定理$ j: I- Q0 ?2 y- k' \
Bell-shaped curve, 钟形曲线% X# T# [/ k1 u$ R& a
Bernoulli distribution, 伯努力分布. [+ n$ f1 t& h, b
Best-trim estimator, 最好切尾估计量
$ r `' {5 S6 s5 [2 yBias, 偏性
- M1 ]" r$ Y, E1 a1 {Binary logistic regression, 二元逻辑斯蒂回归2 l& t# S6 m) u' E" s1 [9 a
Binomial distribution, 二项分布
% ^, v: \6 Q: |4 s$ Z5 UBisquare, 双平方8 v! [* Z, o8 h
Bivariate Correlate, 二变量相关
$ G2 V8 ]3 f; `5 L+ b1 x: NBivariate normal distribution, 双变量正态分布
0 ^2 i+ \9 n9 oBivariate normal population, 双变量正态总体9 \$ B' ^3 o' X, \, r2 [: Q- G2 o
Biweight interval, 双权区间
+ j/ R! {1 n4 @) g0 qBiweight M-estimator, 双权M估计量
% @0 K8 d9 E) e2 X3 p/ V" C( ?Block, 区组/配伍组
# |7 {( E) L8 d _BMDP(Biomedical computer programs), BMDP统计软件包
- a' H( `8 f3 f3 z% r C5 DBoxplots, 箱线图/箱尾图2 O+ u1 P' H8 r. S4 H2 B
Breakdown bound, 崩溃界/崩溃点% H* i# f5 v$ r3 T
Canonical correlation, 典型相关2 ] }1 [: g) X# s" U+ H8 o! S
Caption, 纵标目4 t- C$ d* L$ K( h+ \" i/ D
Case-control study, 病例对照研究+ F( R! R/ r6 k5 @
Categorical variable, 分类变量% s% b* G' o( p; U: k$ B* t
Catenary, 悬链线' o2 E" G* z3 I& A7 {+ i6 ]- @
Cauchy distribution, 柯西分布
. A% ]# i- X+ o* ^! j( ICause-and-effect relationship, 因果关系% n$ ?* B5 x: Q' W. y' x
Cell, 单元3 i i2 y5 \& g7 c0 _
Censoring, 终检
6 h( }2 a2 v# aCenter of symmetry, 对称中心
; m/ f; x# R1 ?" W* QCentering and scaling, 中心化和定标. V+ x2 P8 ]3 q+ `
Central tendency, 集中趋势8 k2 E8 f9 }' Z) f5 ]+ w, \* v+ D
Central value, 中心值
! E( ?* m! j, U7 u% p$ v; U0 kCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测$ M" \8 h E" Q4 K$ D$ F' G* _
Chance, 机遇
( d2 D( U d" U, A MChance error, 随机误差" Z$ R {% i$ w6 ]+ u& z: \
Chance variable, 随机变量
/ P) ^& V) [6 _5 F1 Z7 y4 s NCharacteristic equation, 特征方程" H2 }/ G# @: y3 i$ Z _: x
Characteristic root, 特征根
% f+ C* {& A) `: _3 j7 @Characteristic vector, 特征向量
2 d6 N/ h+ D" d4 G: C; c0 Q5 y: YChebshev criterion of fit, 拟合的切比雪夫准则
7 [8 _) h" H! F9 x5 J4 CChernoff faces, 切尔诺夫脸谱图
$ C: U% ?% y' vChi-square test, 卡方检验/χ2检验& T. z5 M# w' D7 V5 m. r+ ^
Choleskey decomposition, 乔洛斯基分解
" p: b3 Y x; h! o7 qCircle chart, 圆图 ; M3 i! I9 E6 @& j
Class interval, 组距3 \ Z* d# D1 p) G& l1 [& z: Z
Class mid-value, 组中值( ~* w4 F4 K( k
Class upper limit, 组上限
* a4 n6 r% g9 D, T& {, n7 G: Q$ QClassified variable, 分类变量
( M4 e/ |) X5 h! s- @Cluster analysis, 聚类分析. B* [: b0 R9 |5 [ C* q* I1 A
Cluster sampling, 整群抽样) A9 k. A- w: ^2 A' ?% [3 r
Code, 代码
' b: P& |1 p, F% KCoded data, 编码数据
% T. S" B6 J- y( r1 U: @5 a4 LCoding, 编码4 M5 o2 f5 F7 _! F
Coefficient of contingency, 列联系数+ i1 k' C @; {' m% T Z5 I
Coefficient of determination, 决定系数
2 q0 L- R, q' O) i3 N# D7 Y+ _Coefficient of multiple correlation, 多重相关系数' F& P. f' T5 d5 K& y: B# V
Coefficient of partial correlation, 偏相关系数
" X/ F4 d- w! k) [$ a6 vCoefficient of production-moment correlation, 积差相关系数$ X. Z I9 M7 p& H! E
Coefficient of rank correlation, 等级相关系数2 X. P: i# H; E
Coefficient of regression, 回归系数
( A7 |8 r2 B; H1 _Coefficient of skewness, 偏度系数
0 r# \+ @/ y$ v1 n: ]* tCoefficient of variation, 变异系数
5 q9 C( e+ w5 u- oCohort study, 队列研究. h: p$ m6 J" u/ K
Column, 列% ]8 B3 X& M2 r( H( i# ?
Column effect, 列效应
' t2 q q1 y" MColumn factor, 列因素
0 p. `! l4 Z A5 I2 Q! A% X" s- Q7 a) lCombination pool, 合并
" N( U' S1 x5 M3 z3 v) uCombinative table, 组合表
* I3 `- E1 ^$ s/ ]: E& W% F# ZCommon factor, 共性因子4 t/ Y' y3 i2 I2 P% M! k
Common regression coefficient, 公共回归系数( _7 Q7 O4 ]* s* ^
Common value, 共同值
" P5 k5 Z* k/ J* wCommon variance, 公共方差! V8 ]2 K4 L% u- a2 R
Common variation, 公共变异
8 _6 N6 K7 m6 G/ XCommunality variance, 共性方差. m5 r- ^, J* b6 v
Comparability, 可比性
. M7 t' [0 B7 m- NComparison of bathes, 批比较- b9 A* e" y0 k0 \" m/ b" n
Comparison value, 比较值8 l, j3 M8 J, U" l! }5 P6 Q
Compartment model, 分部模型9 D: e& A+ D$ m: ^# Q9 s1 J8 K9 N: x
Compassion, 伸缩% |# i/ u: e. r" x% }
Complement of an event, 补事件; ~' r1 o9 q8 N3 Z' O' m( J
Complete association, 完全正相关4 n2 \& O7 F6 I) e* ~' t* c4 ^* Z
Complete dissociation, 完全不相关 b6 O0 V" a( w. c
Complete statistics, 完备统计量( q7 V! w) X1 {9 n8 I; K& Q
Completely randomized design, 完全随机化设计! H d' I" w$ ]* ~
Composite event, 联合事件3 I4 R2 v$ m' r* t
Composite events, 复合事件' b% Y' G4 {4 o* q# U+ l+ q2 ]
Concavity, 凹性
& @+ S; Z) X% m6 lConditional expectation, 条件期望
+ U# f4 V* \' _* Z6 n$ q' i4 [Conditional likelihood, 条件似然
. i0 k3 ~1 d/ g" q) e: b( ]Conditional probability, 条件概率" p, N2 P% n' y3 K$ J
Conditionally linear, 依条件线性: N$ m* ?. D8 x% F0 k
Confidence interval, 置信区间3 @ h$ b3 X% \: s: `1 @' m- u S
Confidence limit, 置信限
! f W' U: T9 J0 p TConfidence lower limit, 置信下限
: k1 Y7 ?! @# z% o( ~) y6 K; t9 [Confidence upper limit, 置信上限
2 n# X% g0 d/ Z8 N3 FConfirmatory Factor Analysis , 验证性因子分析
w q* Z; y* y% ]$ F$ N& r, S XConfirmatory research, 证实性实验研究
* D0 j1 S& U( R$ q! Q0 K4 o* e; ~Confounding factor, 混杂因素0 d) a/ {! O' D2 |; R- Y
Conjoint, 联合分析: f' c$ a# T2 |$ O' h' {. `
Consistency, 相合性) h# J5 O3 L; C; ^! P$ w
Consistency check, 一致性检验) v- G. z/ ^- z' g: P) Q- j w* a
Consistent asymptotically normal estimate, 相合渐近正态估计
0 c2 e3 m5 t! W0 uConsistent estimate, 相合估计
, y0 ^' q/ s' |: B+ c w7 BConstrained nonlinear regression, 受约束非线性回归
. J3 P9 L" l. ~5 M9 X, YConstraint, 约束
8 ~$ P2 a+ L- e: X: N$ WContaminated distribution, 污染分布
1 m. M% W7 B( _) }! |' L8 \+ oContaminated Gausssian, 污染高斯分布
8 y. B" E' K3 \, |7 I) fContaminated normal distribution, 污染正态分布. t7 s3 y5 K4 @% B. ]
Contamination, 污染5 n) `- T/ [" O2 U* R6 o
Contamination model, 污染模型7 |% z6 x+ d; J9 f" b- q5 }. H
Contingency table, 列联表
4 z, Q- j' K4 O" x. }6 OContour, 边界线6 R: O7 _( B5 ?2 B1 i) ^1 O
Contribution rate, 贡献率9 S" i S8 _' d: S" _; x
Control, 对照
0 ~' J6 C& Y% ?& h' g- _3 G: X# aControlled experiments, 对照实验( r' ^4 W1 q. p7 m2 G/ a% x
Conventional depth, 常规深度$ U3 P8 N& d* d5 y; @5 z' v
Convolution, 卷积
9 P3 s3 g9 S% m8 sCorrected factor, 校正因子 [8 p4 r& P8 a8 `
Corrected mean, 校正均值1 c; h ~: }* @
Correction coefficient, 校正系数" {8 E8 c9 X" t, }1 @) \2 f3 l
Correctness, 正确性1 ]& x9 C, z8 N/ Y" N
Correlation coefficient, 相关系数
T+ \. Q: K L) }: A' S) p5 KCorrelation index, 相关指数
, |2 x/ j8 J% j f. E# tCorrespondence, 对应* C0 p6 a6 a! f# F5 j1 U
Counting, 计数
0 u5 Z5 _! U4 D: P$ q. H7 L- \Counts, 计数/频数5 U8 l& e! O$ u" g, Q
Covariance, 协方差. r6 a' J5 s5 o5 ?
Covariant, 共变 ! T- ?1 o0 Y C4 i5 f! H
Cox Regression, Cox回归) s8 P( `8 U6 J" Z7 y, Z: _9 }( g% t
Criteria for fitting, 拟合准则( F8 K) N+ b# N/ S- }
Criteria of least squares, 最小二乘准则
4 d* T2 D: O2 Q' L9 Q2 ^& U1 F, VCritical ratio, 临界比. N3 q' H, a* `' O. q B. `
Critical region, 拒绝域
% L, B4 L! b5 `: e# CCritical value, 临界值
' L( i9 ~. a3 |! V3 q) _Cross-over design, 交叉设计6 z2 ]8 y$ F( ?6 Q! |
Cross-section analysis, 横断面分析
: Y. v9 e) o1 V) J1 R$ vCross-section survey, 横断面调查$ c8 Z9 k, z9 i) a
Crosstabs , 交叉表
2 _) b, `2 J) H1 H! m4 mCross-tabulation table, 复合表' f R2 b1 v6 K, V8 J
Cube root, 立方根
% }% X4 i+ h& A+ ]9 D! tCumulative distribution function, 分布函数
) H' \$ Z" I. ^Cumulative probability, 累计概率
7 {& i' T9 h" b9 vCurvature, 曲率/弯曲; _% X) P# f( t
Curvature, 曲率
1 a4 V3 c! e! X: r$ K& ZCurve fit , 曲线拟和 3 q$ n" Z( v6 |/ A. N
Curve fitting, 曲线拟合 Z; U+ I6 ~! T' v, X/ r1 h
Curvilinear regression, 曲线回归
% H1 y" R P k# tCurvilinear relation, 曲线关系
8 A* g: h/ ]3 q" jCut-and-try method, 尝试法( {$ U/ W* D# Y/ F7 T& V
Cycle, 周期
0 `; [& w! C9 X! S: z! GCyclist, 周期性/ Y [/ a8 ?7 W7 e( A" k* F$ S! b
D test, D检验
9 V4 M1 ^2 \# L( b# n' tData acquisition, 资料收集+ n% ^2 a3 C" R0 ]$ @& A2 i6 H
Data bank, 数据库! t& V5 ^2 A* _: T4 ~- D
Data capacity, 数据容量7 ^; J8 H9 w) }8 f. k
Data deficiencies, 数据缺乏* o3 M: A2 B. K) t" z' e7 e
Data handling, 数据处理
0 l' L6 L% t; vData manipulation, 数据处理
# h! i1 d8 ~( h* K7 O0 X8 ^Data processing, 数据处理
! d' N' Q8 q' y" u$ c+ wData reduction, 数据缩减
& t2 }: O% b7 w. ` U J) ZData set, 数据集% R4 s6 g2 R) Q8 }
Data sources, 数据来源0 m) y' x( V0 d @
Data transformation, 数据变换+ b% F j1 V3 c- y1 f! Z1 l
Data validity, 数据有效性2 l0 k* E o. V9 s* W
Data-in, 数据输入& r% t' v0 ~7 y- l
Data-out, 数据输出
3 z/ N0 h! }5 s" ]Dead time, 停滞期6 z1 u$ h/ o3 E' Q0 ]- L5 n
Degree of freedom, 自由度+ I) \% Y: } \2 a# p
Degree of precision, 精密度
: D( ^1 R2 h, z$ [/ d9 XDegree of reliability, 可靠性程度: U& m) p& L# g! x' K, ^2 R( ~
Degression, 递减% L# I. N! Q! B5 Y
Density function, 密度函数
7 m" a; U2 D2 V, u* r# O4 }8 rDensity of data points, 数据点的密度
; {6 n( L* P$ P4 J, d- qDependent variable, 应变量/依变量/因变量) b2 d# P9 }7 n
Dependent variable, 因变量) Y0 \7 b* M6 j$ U6 L; F
Depth, 深度
5 T8 x6 ~6 S9 w4 K V+ Q0 L; ?Derivative matrix, 导数矩阵) a. l# i( _8 ` R+ w
Derivative-free methods, 无导数方法, J9 k+ K. C% p$ Z. ^. ~: A: y) i! O
Design, 设计+ O3 Y: g0 o* k p
Determinacy, 确定性7 O7 a) K, f! X: v/ L: e
Determinant, 行列式
J4 B) B5 ]* `2 WDeterminant, 决定因素% D& B! X0 y7 z6 U( a/ V
Deviation, 离差
! ], [ \( v; L) D* N y$ A5 ~Deviation from average, 离均差' N& B5 j+ C7 m/ y- f
Diagnostic plot, 诊断图
$ ?3 x2 p4 {$ l+ K" qDichotomous variable, 二分变量5 z. m' f- ?! r1 L) {
Differential equation, 微分方程7 K* U$ x( Y" t/ n2 L/ J. {
Direct standardization, 直接标准化法
3 ]3 O8 P$ p- EDiscrete variable, 离散型变量
0 u- k- O( K1 WDISCRIMINANT, 判断 9 W y& V" h& u! e
Discriminant analysis, 判别分析
% ?5 x- O$ E+ @- `1 oDiscriminant coefficient, 判别系数
5 [8 M* E$ e# C1 aDiscriminant function, 判别值+ ^3 ]9 X5 `# h; X. x( W4 I% @6 H# V
Dispersion, 散布/分散度
" W1 a4 m* U' z q. rDisproportional, 不成比例的
3 i( @2 y7 @4 Z3 fDisproportionate sub-class numbers, 不成比例次级组含量$ O. ^0 u1 q: g1 y9 D0 `- S2 B' f' [: G
Distribution free, 分布无关性/免分布
; q: e- H+ ?; YDistribution shape, 分布形状) Q( {4 w! J! u
Distribution-free method, 任意分布法
: }& f6 G4 v) HDistributive laws, 分配律
: V: g4 A# i9 H6 o: g' a; C K" Z5 w2 {# ]Disturbance, 随机扰动项
, V0 }( \. N* d' a/ J" F) K" u4 S N; XDose response curve, 剂量反应曲线1 u0 [; `6 h, c/ {
Double blind method, 双盲法
! R! X. C6 u( F# i& RDouble blind trial, 双盲试验
* j+ L& z. c. P2 HDouble exponential distribution, 双指数分布+ f4 ?& o+ A$ P6 A
Double logarithmic, 双对数
9 e! r8 `6 W. h* X2 z* v( oDownward rank, 降秩- [/ i6 q3 `# i; b0 i+ P
Dual-space plot, 对偶空间图; Y$ b- ~" c2 s, c; X# z- }
DUD, 无导数方法
/ a. d; N5 R* h3 ~Duncan's new multiple range method, 新复极差法/Duncan新法% n, J+ c9 A4 J: d7 q* I. M
Effect, 实验效应' m8 K; a. }! Y% x. l* Q- W
Eigenvalue, 特征值. ]2 j2 M1 E+ r& C5 D% v! L
Eigenvector, 特征向量
9 Q0 T5 F' h4 TEllipse, 椭圆+ I* Z7 u1 t1 `) \( c6 i+ m
Empirical distribution, 经验分布
! ^- {3 P6 W! ]9 F! ]Empirical probability, 经验概率单位
7 _! [( N) c7 X- K& kEnumeration data, 计数资料
0 f8 @' U4 w' ?1 t0 _' JEqual sun-class number, 相等次级组含量$ d& e# e n3 k, H: `
Equally likely, 等可能
. Q9 P9 O4 Z, ]" AEquivariance, 同变性( C* V) R0 B- o
Error, 误差/错误; q- L) p- e4 \8 }) ?/ A
Error of estimate, 估计误差
6 f9 T# o9 d( Y6 }* U. UError type I, 第一类错误& a2 i( x4 m6 ?( g
Error type II, 第二类错误; `2 S% [7 I' P/ P* b
Estimand, 被估量. O' Y- ^9 ?7 Y* A
Estimated error mean squares, 估计误差均方
2 p6 I* D q: M7 X+ T7 E" L) y0 ?Estimated error sum of squares, 估计误差平方和; n0 O+ e5 A/ F6 I2 z6 q' u1 I ^
Euclidean distance, 欧式距离4 F6 f* C9 d& a0 v5 M# k
Event, 事件; @8 V# R" ~: ^9 |0 d
Event, 事件
+ a2 L7 ~$ y! M* t7 O7 d; _Exceptional data point, 异常数据点
- X8 Y8 f( d8 J; p3 @' M" mExpectation plane, 期望平面4 a; i, s ~& J
Expectation surface, 期望曲面
3 X& \& @6 K( N% W `: qExpected values, 期望值
0 u9 P# p# [1 o. _. xExperiment, 实验
7 O, D$ C* a( ?2 @7 r) {Experimental sampling, 试验抽样( m: O4 |: e- m6 |# R( j* Y
Experimental unit, 试验单位
6 ]: y- I# k4 E8 @: P: p* xExplanatory variable, 说明变量1 j9 _, X+ W2 d6 h. f
Exploratory data analysis, 探索性数据分析
! {( a! B; Y- yExplore Summarize, 探索-摘要1 X& Z1 D+ }. ~! C; w1 n; S- {
Exponential curve, 指数曲线
' m5 K5 @: X9 F! j) b8 ^Exponential growth, 指数式增长8 C5 C7 s$ M+ I. b4 B$ I
EXSMOOTH, 指数平滑方法
* a. l% v/ V, @ q* VExtended fit, 扩充拟合
6 |' k5 {$ \: V9 N. o1 c1 eExtra parameter, 附加参数3 Z# {* X, x, r; i2 @5 o
Extrapolation, 外推法
, M; b/ p2 p1 s4 xExtreme observation, 末端观测值6 f8 g! W. }4 F8 p% v" N; y% X
Extremes, 极端值/极值
# g8 Q5 f( J7 m' XF distribution, F分布% \+ b" E9 t1 [; ~3 ]
F test, F检验( [) W. m: d. l; V8 z
Factor, 因素/因子/ w1 \4 O% q& |: v4 K
Factor analysis, 因子分析4 j5 O2 D( @: Z
Factor Analysis, 因子分析( U9 j/ K+ \8 S, W f: H: \: s" [
Factor score, 因子得分
0 M& ?! g0 s/ {9 y7 w& t; w) B6 gFactorial, 阶乘
. V7 g) ^. u2 g( ^Factorial design, 析因试验设计1 R) t3 I/ \; P" z: G( b
False negative, 假阴性1 X' X9 w9 u' Y( w9 M
False negative error, 假阴性错误/ w- u2 {( j" w1 v+ g* T+ S) j* X
Family of distributions, 分布族: X9 S' H4 r3 s. [9 }; u) K0 l
Family of estimators, 估计量族
( Y: r+ r* x# U# q% mFanning, 扇面
6 O1 t. w' |* }8 D" NFatality rate, 病死率
: C( n- j( t% W- a- v! qField investigation, 现场调查
f) I9 @0 O; T9 S4 M: e* \Field survey, 现场调查* g! J; e' i% G) E0 V, Q8 m1 L
Finite population, 有限总体: n% s0 E2 m4 y) [
Finite-sample, 有限样本; O5 G# A3 U% f: ]8 @
First derivative, 一阶导数$ u7 z5 T* m" |0 J8 V
First principal component, 第一主成分. l1 a( v: R2 j1 a9 l7 T
First quartile, 第一四分位数
& c, C; F! U: y& pFisher information, 费雪信息量
# X1 o1 M7 f( {! aFitted value, 拟合值 t; C. Z- ~$ M; @" q8 W
Fitting a curve, 曲线拟合
1 A6 p s/ q% T( r0 OFixed base, 定基
# g# a1 I8 U) @+ t2 [4 p8 PFluctuation, 随机起伏
8 S5 R4 _+ ^ S* w( B+ XForecast, 预测; T7 D B" E$ T9 ?7 t+ {) Y
Four fold table, 四格表, O# y1 m7 F( e0 ^5 ~; \6 m
Fourth, 四分点2 T" o3 ^8 C2 R7 C- f3 e" N
Fraction blow, 左侧比率
2 v. C @2 d+ u JFractional error, 相对误差
- u) T \4 U7 Z( f! c3 qFrequency, 频率* o6 H) l6 p2 G# a
Frequency polygon, 频数多边图9 O/ ~' ^$ n: q/ x" `) t, q" h
Frontier point, 界限点
: G8 h8 Q" D3 W" ~Function relationship, 泛函关系' U( Z. g, p1 ?4 {: h' h4 E
Gamma distribution, 伽玛分布# {; x- |! g# U+ p9 `6 ?4 }
Gauss increment, 高斯增量( ]6 g% f# u9 e% J
Gaussian distribution, 高斯分布/正态分布
B! i0 b- k9 a) _% }0 DGauss-Newton increment, 高斯-牛顿增量- C& z+ V8 S# o. z& C
General census, 全面普查0 @. g. v2 Y& I) E7 W
GENLOG (Generalized liner models), 广义线性模型 # R7 {9 @! s( @* O# `9 B( U$ }
Geometric mean, 几何平均数' {1 T8 ?) I! t* T. s* E' s5 E
Gini's mean difference, 基尼均差$ `% v1 Y" X' ~. C: b) O" P, Y. H
GLM (General liner models), 一般线性模型
' P- j1 i e( u* n% u# \; TGoodness of fit, 拟和优度/配合度
! h, g( {: z8 G1 u4 kGradient of determinant, 行列式的梯度" F5 G, C4 p( F, w- V; a% ^7 _8 K
Graeco-Latin square, 希腊拉丁方- W( s& Z) C L# B0 K3 S
Grand mean, 总均值
% H& S8 g4 V& i, D+ iGross errors, 重大错误4 h- p7 m7 K8 r6 T1 S l' c
Gross-error sensitivity, 大错敏感度* [1 F" N& N) H0 x/ S" k n9 x
Group averages, 分组平均
3 x+ e. u; g5 S, R+ `7 ?Grouped data, 分组资料4 i6 i; R1 m. H: G% g: E0 t
Guessed mean, 假定平均数3 ^( q' ]$ u9 }/ [
Half-life, 半衰期% T7 k7 ]$ p& b) ]. H1 z; F; i3 g
Hampel M-estimators, 汉佩尔M估计量0 V& I- Z, f' T6 c+ M4 p
Happenstance, 偶然事件
; T) X5 m% `$ b0 }6 x9 PHarmonic mean, 调和均数! ?) t: q0 {* P
Hazard function, 风险均数0 M( {: R3 e, o
Hazard rate, 风险率
0 _! u$ s0 J. `! q& \Heading, 标目 6 _# a* \2 }7 P4 Z4 B% j3 g( ~
Heavy-tailed distribution, 重尾分布
$ O7 X$ d, A# aHessian array, 海森立体阵
, i" T' A/ ^) H( \$ yHeterogeneity, 不同质
+ }: |: s R$ V( z1 RHeterogeneity of variance, 方差不齐 5 N g$ B2 K" {9 b9 m
Hierarchical classification, 组内分组
4 F& D+ u+ r+ S5 R7 n, KHierarchical clustering method, 系统聚类法1 e+ @6 `; }0 ]! R" \, X
High-leverage point, 高杠杆率点# m0 X5 a C- S& q, B
HILOGLINEAR, 多维列联表的层次对数线性模型
; k3 ~, G4 a! O+ s. THinge, 折叶点
# x& Z ^. |4 I fHistogram, 直方图
5 a2 r7 i: P, A# @* X4 zHistorical cohort study, 历史性队列研究 + p9 Q! c( j( T2 N$ `) b( ~0 A& G
Holes, 空洞
3 G( b) W/ s& S6 q" a! ZHOMALS, 多重响应分析
4 l( W2 y! C9 F" bHomogeneity of variance, 方差齐性
; N% R# J' o2 T1 i) DHomogeneity test, 齐性检验1 {6 V3 P V4 a; z3 Y6 M3 {
Huber M-estimators, 休伯M估计量0 r! T$ Q0 T) s" D
Hyperbola, 双曲线
( k0 ~% R/ s1 d! l6 I: k1 f# c/ [Hypothesis testing, 假设检验
% a8 p$ }) R4 S8 U( NHypothetical universe, 假设总体
, a3 Z6 X5 t1 d8 I8 v* [Impossible event, 不可能事件! u" B) X$ U! e2 K. J
Independence, 独立性2 P, V* @* s, M/ C$ N; n6 x( r4 n
Independent variable, 自变量! s: V5 P- C4 z
Index, 指标/指数$ {8 P/ P+ a4 B+ L6 A
Indirect standardization, 间接标准化法 {7 d1 s3 X; ^. R. |. N" g
Individual, 个体( [) p9 U+ ^0 W z9 B
Inference band, 推断带
, b) @' A& ~) R( a) wInfinite population, 无限总体- e, Q( e. G4 i0 O) O
Infinitely great, 无穷大
3 D2 u3 q$ T& G+ }( |) fInfinitely small, 无穷小
# V+ w$ W; V8 f: Q: y; z- _0 AInfluence curve, 影响曲线$ o% H( A4 s4 k) R, ]) z
Information capacity, 信息容量
7 g( ?# a; N/ b z) Q/ }. l+ _Initial condition, 初始条件" B3 J! p) D* r5 O
Initial estimate, 初始估计值, V( [1 M* i2 Z$ \' M' S
Initial level, 最初水平
X" Y$ N! e' i7 aInteraction, 交互作用
6 Z. |, h" ]& o! v2 r- k# zInteraction terms, 交互作用项
4 i5 o0 h# _' G4 n& aIntercept, 截距
$ C8 P6 x4 b4 }, GInterpolation, 内插法
# [. v* H; U8 ? L9 ZInterquartile range, 四分位距
/ ? X) \! g, e. s) n; p4 WInterval estimation, 区间估计
. c, b6 B8 u1 x% Y4 ?Intervals of equal probability, 等概率区间* b9 m7 s) N- y4 B, t1 L! @
Intrinsic curvature, 固有曲率 `3 `9 P% ?! {. \, K- z+ n5 L
Invariance, 不变性
9 S* k _7 c/ ?Inverse matrix, 逆矩阵9 o! i. u) {% f; z* S
Inverse probability, 逆概率+ d/ u q- Q0 {7 C( s, k! [! r
Inverse sine transformation, 反正弦变换4 \5 A9 R y( D' L, s1 P
Iteration, 迭代
- G6 q9 @0 }. [% `6 N2 LJacobian determinant, 雅可比行列式
# \+ @. `1 ^. l# s1 U W( }Joint distribution function, 分布函数0 T- T+ ]8 H# |- R1 u" U+ s# y
Joint probability, 联合概率
6 j- j8 W# b$ B$ B8 SJoint probability distribution, 联合概率分布" K5 e1 ]4 S, ?4 P% d8 D
K means method, 逐步聚类法
. C) [5 s9 b M3 \6 f: SKaplan-Meier, 评估事件的时间长度 3 ?8 ?; k3 S* [! {; {7 a5 y: }
Kaplan-Merier chart, Kaplan-Merier图
8 Y% _1 b; L0 b5 }( b/ w0 ~Kendall's rank correlation, Kendall等级相关
- k, Y# J/ S8 UKinetic, 动力学
* G" @0 n! V' jKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
( n9 o8 E% w$ d: fKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验% q4 n4 m& r+ j: V
Kurtosis, 峰度1 E6 }; d) O7 F) D
Lack of fit, 失拟( v2 R! t: F' N1 E
Ladder of powers, 幂阶梯; u3 c7 s' q/ h6 h0 q
Lag, 滞后
9 B( J: i% R$ d4 ~3 J) ?Large sample, 大样本* \7 g8 u. t/ \5 T
Large sample test, 大样本检验8 e. M4 L0 X. S5 e# w% A
Latin square, 拉丁方( P2 T9 u, B, W& D
Latin square design, 拉丁方设计
# p' A* e4 o: s: b$ XLeakage, 泄漏: O* W/ m' ?! L- D- R
Least favorable configuration, 最不利构形6 r$ c' `) U6 r7 p6 S
Least favorable distribution, 最不利分布" k& t& Y y, u" }
Least significant difference, 最小显著差法
1 H' l3 N' c$ s) ~. C% b+ \0 ]. e1 sLeast square method, 最小二乘法. K& w$ R& p% ]5 F$ X
Least-absolute-residuals estimates, 最小绝对残差估计. l. e$ d) s0 c0 _0 i4 Z r
Least-absolute-residuals fit, 最小绝对残差拟合
0 y8 {( B& Q' Z' x& GLeast-absolute-residuals line, 最小绝对残差线! n s& `* O, c( H( v
Legend, 图例
9 ^; E6 @3 B: C# X6 |# tL-estimator, L估计量
$ O7 V5 N; z- `; m" [; t) [L-estimator of location, 位置L估计量7 T# T1 S$ ` T* m
L-estimator of scale, 尺度L估计量4 F/ O: o! W8 | o6 k8 Q
Level, 水平
' V6 d5 e# y' ?+ f! E! {Life expectance, 预期期望寿命) z( n2 e' a. m. Y- c% c5 f( L' O
Life table, 寿命表' [. {6 U# S# ~. k! H
Life table method, 生命表法
L+ p f2 ~8 w; G% C- _3 vLight-tailed distribution, 轻尾分布. M6 k" r: ~, f$ }! A" V
Likelihood function, 似然函数6 N( |3 A1 M: A/ d: H" _$ N
Likelihood ratio, 似然比
7 W2 T' x; C+ s0 lline graph, 线图
" `+ g: L' L) y. A. d0 zLinear correlation, 直线相关
& @* ?: S# A4 y: eLinear equation, 线性方程
# k+ p$ B$ e* aLinear programming, 线性规划
+ p( X3 {' z& N% \9 H- C" jLinear regression, 直线回归/ Y" e- a8 P7 h0 ~
Linear Regression, 线性回归- I2 ^: N, ~2 W9 b. m; c1 R0 h! y. |
Linear trend, 线性趋势 }% l. |" z3 G }% F* L
Loading, 载荷 5 ^# m7 n- @+ }" }
Location and scale equivariance, 位置尺度同变性
3 r; V7 h) v) U! r; `) s! h% ELocation equivariance, 位置同变性2 S" i+ H8 W2 X# S: J0 g
Location invariance, 位置不变性
H7 v' L- ?+ b6 U2 mLocation scale family, 位置尺度族; l e" ]0 g; { G& o9 }
Log rank test, 时序检验
0 K" y% b# @3 e" {, Z9 X% R( vLogarithmic curve, 对数曲线1 K3 I% C& i9 t7 [& }" Z4 V7 @
Logarithmic normal distribution, 对数正态分布
6 [0 }1 W( O% v: K. t8 U8 b6 ^; N5 b$ TLogarithmic scale, 对数尺度
K# y# Y3 F4 S+ g tLogarithmic transformation, 对数变换
6 e5 v( p5 D5 P$ w2 }2 d- SLogic check, 逻辑检查1 q) x. v* p- Q/ {
Logistic distribution, 逻辑斯特分布; Z! Y5 g8 t4 E. p
Logit transformation, Logit转换! D$ g, |% H$ {6 H s6 o, E2 W
LOGLINEAR, 多维列联表通用模型
. e4 T. |! p) X3 p) r G- O+ k& T, S; MLognormal distribution, 对数正态分布
1 e, L( z( y+ X# e- A/ xLost function, 损失函数
. J; w2 v f# l0 e* {3 M( l3 x: y- zLow correlation, 低度相关
. m3 w) C9 ~9 U" ?* X2 fLower limit, 下限
" r# d* w) i. P* F- ULowest-attained variance, 最小可达方差8 }7 s8 G* m+ O) r0 ?
LSD, 最小显著差法的简称
* X, P9 s/ }8 [& {* Q# @Lurking variable, 潜在变量6 m& Y" I+ s E& ?
Main effect, 主效应" U* `& E6 z( j
Major heading, 主辞标目1 d4 @+ a. h6 Z6 s6 F/ J" w
Marginal density function, 边缘密度函数
9 X& d3 j6 l( o! KMarginal probability, 边缘概率1 a/ _7 B4 t) L8 X5 R5 r6 u7 d' T+ ~
Marginal probability distribution, 边缘概率分布: i2 L- q- Q4 W" k
Matched data, 配对资料
4 w3 O4 P/ ?/ |4 c8 V, RMatched distribution, 匹配过分布5 l" E5 J# \1 M b* Y5 G' u2 \
Matching of distribution, 分布的匹配7 Z- P' r7 |- t# M4 q
Matching of transformation, 变换的匹配
2 D7 b- z9 R, e- k5 U0 AMathematical expectation, 数学期望
, v5 g- O; i9 \9 e) y/ h9 `5 T: `Mathematical model, 数学模型
) B" f) X) t& j) A, X! yMaximum L-estimator, 极大极小L 估计量
; B/ w- r$ i2 C- S6 h! _Maximum likelihood method, 最大似然法
" J0 `4 s$ j" C$ O3 I3 ~; ]Mean, 均数4 c' T( A. n" z/ @& t
Mean squares between groups, 组间均方 V- I" u3 v- W+ \: l
Mean squares within group, 组内均方
- C$ i4 F/ y& h- qMeans (Compare means), 均值-均值比较$ v- h+ d+ r$ s ^3 P* _/ H: H' h
Median, 中位数
* V! S! |2 o t1 w' U' K! XMedian effective dose, 半数效量; t3 P1 h# W% x% | ?3 V7 F( y7 }
Median lethal dose, 半数致死量
9 s* U4 Q/ {4 Y8 oMedian polish, 中位数平滑
" ~% M e% P( t: {( H' J; \6 R- pMedian test, 中位数检验
' X4 z7 v4 P' i* e9 pMinimal sufficient statistic, 最小充分统计量
. A' Z, T5 e/ W" bMinimum distance estimation, 最小距离估计5 H, R2 D' Y9 Z' ]7 n$ f0 O# C; q
Minimum effective dose, 最小有效量
( d$ n; u7 z5 I8 c+ m+ b, E6 uMinimum lethal dose, 最小致死量
5 i K% q# [% ?& {' `7 c/ P0 _Minimum variance estimator, 最小方差估计量. l" N( k4 M7 w" l- A* v1 e/ o
MINITAB, 统计软件包
' W4 \$ q( i3 CMinor heading, 宾词标目
% y( ]* i) g* z" j6 YMissing data, 缺失值
0 L; U' m. e3 y% c7 EModel specification, 模型的确定: K8 r# [* t; f
Modeling Statistics , 模型统计
$ g: W8 R. \5 J( x' y# ~Models for outliers, 离群值模型) L# |" v/ N& X- H! R' R( |6 v
Modifying the model, 模型的修正7 O b" O" q8 W
Modulus of continuity, 连续性模1 E& X, p) V* ~$ z
Morbidity, 发病率 ' K7 |7 o( k4 z6 ~
Most favorable configuration, 最有利构形
% H+ J1 _ A3 dMultidimensional Scaling (ASCAL), 多维尺度/多维标度
( X1 Z! h2 \" E* v% }7 FMultinomial Logistic Regression , 多项逻辑斯蒂回归
' T+ f6 [+ A, ?6 E0 W- A" HMultiple comparison, 多重比较) M4 s/ A* F- N2 P
Multiple correlation , 复相关, ?$ R6 _0 v$ ]0 G" _2 k1 d
Multiple covariance, 多元协方差- M0 o5 o! F& H" K) ?( u4 \
Multiple linear regression, 多元线性回归% X: A" M2 _. W% ^: ^' s* `
Multiple response , 多重选项) P. \# e) Q' D: U/ T
Multiple solutions, 多解/ l" {% \+ O$ }2 {5 D
Multiplication theorem, 乘法定理
* v2 M& `; J7 PMultiresponse, 多元响应" s. J$ }- m% {& A0 n4 |# a0 ?- `
Multi-stage sampling, 多阶段抽样8 s" Y' r, S x, F4 u
Multivariate T distribution, 多元T分布; e( N# T# R, E1 O$ _: j6 G
Mutual exclusive, 互不相容
! \7 d& Z! P6 z# h, {# J3 bMutual independence, 互相独立; Y: p0 Z/ E5 r/ y( `
Natural boundary, 自然边界
* e* o/ ]1 R( o4 x2 L- f# R1 RNatural dead, 自然死亡( D( \" h$ `" g q. M, Z' c7 U4 ^
Natural zero, 自然零
/ X' r$ c0 t7 k1 {- MNegative correlation, 负相关0 x" b3 I- l1 S$ i' `$ m2 @! K
Negative linear correlation, 负线性相关
! }4 J* ]4 K* m |( tNegatively skewed, 负偏
. P; k% [5 |/ SNewman-Keuls method, q检验
" F% _" F3 K6 S- } [ sNK method, q检验
( F3 v5 t; X" o8 ^No statistical significance, 无统计意义. P$ e c$ d5 U' A$ \5 W; g4 }" N7 s; }
Nominal variable, 名义变量
9 S6 n* O1 i& }+ f# E8 HNonconstancy of variability, 变异的非定常性
' Q, ]6 F% G$ o3 n% [' BNonlinear regression, 非线性相关; J3 C* b/ A* d _5 O1 V0 X
Nonparametric statistics, 非参数统计2 R3 T2 {' P/ r! b0 x& k# D
Nonparametric test, 非参数检验- B) _; F' G! z) p
Nonparametric tests, 非参数检验" u! B8 @: ^- ~6 M" j
Normal deviate, 正态离差- }& f( y! ~5 x! J# G- S/ |0 Y; s
Normal distribution, 正态分布( y/ H% Y, z7 c) H& T, p6 {: v
Normal equation, 正规方程组$ |$ s3 Z/ q; O- A8 p
Normal ranges, 正常范围
1 q1 {% ~( i6 zNormal value, 正常值8 V+ D% e. a+ d2 _* T7 D6 J* b; C
Nuisance parameter, 多余参数/讨厌参数- Y$ f6 L% Q# U# b4 U! G
Null hypothesis, 无效假设
1 h \/ U0 V- L1 o1 p3 HNumerical variable, 数值变量
; r/ I) P' H+ _) mObjective function, 目标函数1 N9 Q- K6 t/ ]) f6 o
Observation unit, 观察单位
- a; i0 h* d. x4 Q3 }" ~Observed value, 观察值
2 s* v3 e! V; C& x5 }# @, VOne sided test, 单侧检验- v* G# g5 ?( n0 D2 k$ L
One-way analysis of variance, 单因素方差分析 r2 d3 e7 U4 @& w4 D
Oneway ANOVA , 单因素方差分析, p4 ]: I/ g3 p! T! `
Open sequential trial, 开放型序贯设计. N" m B/ M* K7 M% T5 U
Optrim, 优切尾- q& m% m$ B; Y5 a: j
Optrim efficiency, 优切尾效率' {: I* z4 Z+ u) s# N8 h1 `
Order statistics, 顺序统计量
- F2 } x6 E( Z. J+ g- `Ordered categories, 有序分类
- e) s1 U6 {- G8 v8 o9 E! R, KOrdinal logistic regression , 序数逻辑斯蒂回归
" F) D5 c) _8 |, h6 t* XOrdinal variable, 有序变量
3 J% ~. ^ ^9 Q/ \! HOrthogonal basis, 正交基/ x& w% x, N3 j/ G' N6 L
Orthogonal design, 正交试验设计
( J+ W1 {, {9 ^0 h' JOrthogonality conditions, 正交条件4 I& E1 m% O( X
ORTHOPLAN, 正交设计
, m1 z4 V' V ^ kOutlier cutoffs, 离群值截断点
$ w. M/ T! ]$ jOutliers, 极端值
5 y- s. b* O }2 V0 R5 E) ZOVERALS , 多组变量的非线性正规相关 % L2 O+ K( P/ m/ G6 {( h* b
Overshoot, 迭代过度
0 u- w' e' A) lPaired design, 配对设计: c# _4 k7 o# g5 z
Paired sample, 配对样本 b% Q/ o: ~5 W, g5 }- n( V0 |+ E
Pairwise slopes, 成对斜率
- l6 e: U) f, Q: l- P3 J* k! `" k( U) hParabola, 抛物线
7 r3 ]% I" ?9 h- @6 @Parallel tests, 平行试验
& b% M1 [) c% S- y/ j" l' IParameter, 参数7 x( y2 e# u/ ]. d
Parametric statistics, 参数统计
2 q5 N# i' ~* [1 A# l2 xParametric test, 参数检验
, \" C5 C; c/ L1 o7 g4 `Partial correlation, 偏相关! ~( b0 j/ y! c3 @* ^) j0 O7 D
Partial regression, 偏回归
! U, c0 `* Z& e S) M FPartial sorting, 偏排序
9 \: d! j5 v9 S7 {( g3 I7 ^& r. g: W3 }Partials residuals, 偏残差4 p. p2 z4 a/ g5 L% T
Pattern, 模式% Y1 a) V7 O( ?- I0 J% R# f
Pearson curves, 皮尔逊曲线% ^8 ?+ _; Q3 J1 x' `
Peeling, 退层+ }& z/ N$ Q# w( M( u: V
Percent bar graph, 百分条形图
3 d% r J! f t: EPercentage, 百分比+ g3 M7 i/ Z# n( N9 b0 P5 j, l: ~* C' B, _
Percentile, 百分位数& F2 ]+ a B& i+ L
Percentile curves, 百分位曲线
W7 j5 g) j' g& R0 gPeriodicity, 周期性6 s S1 N2 d. C3 |
Permutation, 排列% |+ I# e6 ^+ \4 W: }: A
P-estimator, P估计量 p, {& u% C( m2 j0 ~- }
Pie graph, 饼图
9 f2 j, n: T2 w) YPitman estimator, 皮特曼估计量# Z9 E# n' Q; q5 W0 g d) Q
Pivot, 枢轴量1 l9 R4 e: O& q5 z* [. k: C( _: m
Planar, 平坦
3 c0 Q1 j3 K9 _# x; |7 {" O1 ^5 O+ w/ NPlanar assumption, 平面的假设
. C c4 O' E1 G1 H* x3 g( ^: a9 LPLANCARDS, 生成试验的计划卡
+ v9 \: J( X9 q" \' {9 P' rPoint estimation, 点估计
5 V- J' F3 ~$ E3 QPoisson distribution, 泊松分布! z/ F4 V" w8 T
Polishing, 平滑
) h+ O; x! r4 p' ?- QPolled standard deviation, 合并标准差5 b: }6 L$ ^) M1 q
Polled variance, 合并方差
0 ^+ W1 k+ N& v0 a4 OPolygon, 多边图9 K2 H0 w6 E& ]
Polynomial, 多项式% b+ i$ _. L! v* }' Q; q6 k
Polynomial curve, 多项式曲线
2 e4 f( R8 ~+ j x4 dPopulation, 总体
- l3 \/ F( d- K6 q# lPopulation attributable risk, 人群归因危险度) n4 t+ Q4 p( [" b
Positive correlation, 正相关! H$ b2 g/ V. g% `" O3 [6 x
Positively skewed, 正偏3 e5 R6 Q5 Q0 J& e* i4 H
Posterior distribution, 后验分布
! \' J( |% ~' M7 i; L4 `Power of a test, 检验效能
6 a. I5 E: ?/ ^! W9 cPrecision, 精密度3 ~0 j& V; i3 S% p
Predicted value, 预测值, @ ]1 k; U* z% ~* {
Preliminary analysis, 预备性分析2 W" R9 P! J, D& s
Principal component analysis, 主成分分析
$ L2 M `- A2 S" ] WPrior distribution, 先验分布1 k( e, C u1 `* v3 F- `( P! [; h
Prior probability, 先验概率
* `! @! C- m1 Y, S0 h0 hProbabilistic model, 概率模型4 s6 z# C( h, |7 L+ f
probability, 概率
1 d0 b6 n% }3 Y7 J/ gProbability density, 概率密度( C5 ~+ U" n6 s- ?
Product moment, 乘积矩/协方差, \$ E5 \1 Y- D) l+ K
Profile trace, 截面迹图
7 c# I4 w3 m% T6 q5 s1 DProportion, 比/构成比
$ w2 Q; z6 u# d1 h1 PProportion allocation in stratified random sampling, 按比例分层随机抽样5 M2 n+ n% d( t
Proportionate, 成比例
4 N! g% e8 s: J" TProportionate sub-class numbers, 成比例次级组含量
& Z3 r+ ]* C( U6 z5 CProspective study, 前瞻性调查
' K$ W" J7 q/ ~9 jProximities, 亲近性
: ~6 I& {8 l6 F! O: k/ Z; }Pseudo F test, 近似F检验
4 [ E$ l+ g p: D1 Y# x/ A7 _Pseudo model, 近似模型7 s4 N# ]- g0 _' \
Pseudosigma, 伪标准差# J4 J7 T, x/ P& \4 U$ v
Purposive sampling, 有目的抽样, ]8 k/ G/ v5 ^1 q, S8 M2 X
QR decomposition, QR分解- B3 L# j7 I0 }
Quadratic approximation, 二次近似
7 E( {- g1 J5 Y7 Q& u) YQualitative classification, 属性分类# D% e8 _; L$ ~) R* z8 H
Qualitative method, 定性方法( O7 O; T- ^5 x5 c/ q0 H, f
Quantile-quantile plot, 分位数-分位数图/Q-Q图3 X P$ I9 v7 _7 P* D
Quantitative analysis, 定量分析
# O( j6 [7 ^5 _2 ~3 mQuartile, 四分位数
+ z# L" ]1 u, [; LQuick Cluster, 快速聚类
% I& W2 z$ ]+ S9 V: C, M8 SRadix sort, 基数排序
. f; k2 ]8 |6 R( B0 \# S! L/ {# sRandom allocation, 随机化分组
8 ^ W+ o! @/ ~' W7 KRandom blocks design, 随机区组设计
8 k, V d5 @$ c D: l1 }Random event, 随机事件9 h$ C u8 ?8 o6 W
Randomization, 随机化
% L" f$ P1 C& H! uRange, 极差/全距; L; I0 ]5 h5 x5 `- h5 @& T
Rank correlation, 等级相关& _% a, u% d, c1 V: U
Rank sum test, 秩和检验
- u# ?: ~' x% r2 M* aRank test, 秩检验- S& k/ \' v1 H8 K. d
Ranked data, 等级资料 P! F5 [3 K h& ~- h4 r% f8 y5 {
Rate, 比率/ W/ t) j5 ^3 d# n
Ratio, 比例$ Q- n% C R. m4 x! w" @9 e, z
Raw data, 原始资料% E6 O3 B- |) y% \
Raw residual, 原始残差
" X: r' a% A. [! n: d, Y0 N4 @* o* A' eRayleigh's test, 雷氏检验' z, h( r* ~: `
Rayleigh's Z, 雷氏Z值 6 J1 `6 f5 |' L$ c4 |: @7 |
Reciprocal, 倒数$ ]" b N. Q h" {3 p
Reciprocal transformation, 倒数变换6 `$ W3 g9 d- w$ V4 E5 i; `, \
Recording, 记录
0 _, _4 y% f/ W0 x. H u" nRedescending estimators, 回降估计量) F8 h4 m5 z6 V) g
Reducing dimensions, 降维6 G- _$ M$ |8 x+ G, ^
Re-expression, 重新表达
# Q/ ^5 y8 w/ t" _1 D. yReference set, 标准组. b1 c% l7 [; g: B
Region of acceptance, 接受域5 ~ N- i% r$ w1 b
Regression coefficient, 回归系数% |& i! A0 Z& N. z) q
Regression sum of square, 回归平方和
9 E% \# p# x$ r, A# t1 j) xRejection point, 拒绝点
; v8 ~0 a) x% s8 X% a# S$ qRelative dispersion, 相对离散度
/ P) a& \$ M; }, SRelative number, 相对数: Y, ^$ z; Q2 c/ Q3 Q
Reliability, 可靠性7 n5 t; Q/ q9 W1 Q9 ?8 Z
Reparametrization, 重新设置参数" @+ R+ I" t. { B2 ^0 C
Replication, 重复
! k. i4 {, }3 U+ f3 B" [6 \1 fReport Summaries, 报告摘要0 g- K8 }/ G9 |4 K: C5 t' j9 p
Residual sum of square, 剩余平方和
( E! C5 p/ f1 M+ P2 v2 xResistance, 耐抗性& @1 G$ N. g i! Q- Y
Resistant line, 耐抗线
+ \+ r6 z2 r. W( [Resistant technique, 耐抗技术
+ r$ H6 \) f# [R-estimator of location, 位置R估计量
% x( b' \+ T3 Q2 QR-estimator of scale, 尺度R估计量
( S5 J S Z4 a" j3 i* b4 ERetrospective study, 回顾性调查# t2 }3 d' K7 R. e- e
Ridge trace, 岭迹8 B# {& O) h" F/ |. C
Ridit analysis, Ridit分析% m' F+ G% M% p$ S
Rotation, 旋转
# w. ~, U3 a% c1 t# e: t3 aRounding, 舍入
- P% O& a6 `+ G( l: |2 { pRow, 行
. `* _! D" j3 ~& T" ?- ORow effects, 行效应
( Y: N( d, I1 j" eRow factor, 行因素
: i7 o+ [% s7 O" a6 P/ n6 k" V, u7 [RXC table, RXC表
3 B# V K# }+ G" d" ` y8 X* y( Y- I3 @Sample, 样本) V; N; _3 ` L# {) Y
Sample regression coefficient, 样本回归系数
. x( y) x4 V* [7 z4 d8 ]Sample size, 样本量
6 b `+ Q3 s5 `7 K$ RSample standard deviation, 样本标准差
# T+ K" W( ~* T! `, TSampling error, 抽样误差6 r1 v0 B) q! i# O& R
SAS(Statistical analysis system ), SAS统计软件包! o. w7 B V) I$ i8 G S5 V* ]
Scale, 尺度/量表
( @! L, R5 V+ a5 MScatter diagram, 散点图
9 Q: E: s. m! D/ F% f) o/ J9 k/ K/ B6 ySchematic plot, 示意图/简图& `1 v2 |. h$ O; Q/ \ \0 h! l1 G
Score test, 计分检验! t n- s/ G- y, c+ {7 n% K
Screening, 筛检9 w k& P2 x4 M4 u5 w! I* E
SEASON, 季节分析 : J8 v* x7 }. E+ {. H
Second derivative, 二阶导数
6 l* O' N0 G' |# h, P' hSecond principal component, 第二主成分# h3 O' t3 X: y
SEM (Structural equation modeling), 结构化方程模型 ; L8 V" N9 `; p- D. G
Semi-logarithmic graph, 半对数图4 R: z9 M$ d( k0 U
Semi-logarithmic paper, 半对数格纸8 j7 C+ B3 _9 f* }4 h. i
Sensitivity curve, 敏感度曲线; U. J7 l' ?6 s# M, p6 j' R( ^
Sequential analysis, 贯序分析0 L' v. _- k6 Z* C: w1 E% J( i
Sequential data set, 顺序数据集$ X; K5 ~$ p% Q4 n) h, K, b, J# H+ ?( r
Sequential design, 贯序设计
" o; @ W8 ^# [( Q9 _Sequential method, 贯序法- B4 m: J3 k/ o
Sequential test, 贯序检验法
6 v! P, k$ Q3 M) tSerial tests, 系列试验1 ]4 j) W7 o0 k( Z2 t
Short-cut method, 简捷法 . j7 C7 o$ _% q i5 D
Sigmoid curve, S形曲线
4 U$ B. `$ K% z. E7 `Sign function, 正负号函数
& K' z8 [. H: X/ j7 _Sign test, 符号检验
/ X) r" R0 X/ [4 j0 ESigned rank, 符号秩6 J, V k8 ^4 `" g6 P8 @% T1 _$ v
Significance test, 显著性检验5 J0 y2 o* K4 E8 l
Significant figure, 有效数字
. p0 a5 x" ?/ L2 ?Simple cluster sampling, 简单整群抽样+ W: o! W! Q) C
Simple correlation, 简单相关: O* l( d1 {- e. s. f
Simple random sampling, 简单随机抽样+ P8 L. [) M+ K; B& P9 Q2 ^( V& c
Simple regression, 简单回归) m7 X# h4 x: N- j: m& |
simple table, 简单表
$ |" K t. f) M/ ?Sine estimator, 正弦估计量8 W* ^4 }- Q h
Single-valued estimate, 单值估计1 H1 l$ K$ } f3 m" A/ k
Singular matrix, 奇异矩阵
% J% q$ m: e4 `. [& s8 i/ [- lSkewed distribution, 偏斜分布: T3 X9 L# d' ~ Z8 \' `% x( A
Skewness, 偏度
, V' i* z) |5 r" `) w9 Z9 kSlash distribution, 斜线分布/ Q g g) w& r' d7 p; G
Slope, 斜率
, r( L# P' b5 W+ T hSmirnov test, 斯米尔诺夫检验
' w6 \$ }! u1 ^1 W! mSource of variation, 变异来源 ]6 H% d, Z" S4 o! o+ P* X" O& Q0 |
Spearman rank correlation, 斯皮尔曼等级相关3 [3 D5 B7 |0 @" |' a* m) m
Specific factor, 特殊因子
" t1 m, z+ i6 ~) Z( nSpecific factor variance, 特殊因子方差3 _( Y% U' \" Z
Spectra , 频谱" E$ i) |0 c: D* V) j
Spherical distribution, 球型正态分布) G4 i5 e; f, X
Spread, 展布% a& R! p; v/ d3 I( J' ^8 {
SPSS(Statistical package for the social science), SPSS统计软件包
5 u9 i; p3 b. l' P- GSpurious correlation, 假性相关
: r9 a7 S8 O, t6 {6 rSquare root transformation, 平方根变换2 a$ t) K4 ]5 r2 @ q4 |& S1 n3 S% a
Stabilizing variance, 稳定方差
6 Q/ `% s. V0 t! _Standard deviation, 标准差
0 f4 U0 x, ^, `7 }9 q6 N! CStandard error, 标准误
; F& g; N3 T1 |7 N( `3 H5 Q( rStandard error of difference, 差别的标准误4 x1 ^: v* ~- f2 _/ F t
Standard error of estimate, 标准估计误差
6 g- r$ ]3 D: `) d; p/ j. @Standard error of rate, 率的标准误: r' Q: X8 B( t$ o5 w" U' v
Standard normal distribution, 标准正态分布
}2 z) T% R% Z2 S% d& S$ NStandardization, 标准化
$ Q' ?0 y. I/ _/ k6 [. L' sStarting value, 起始值 J( ~5 B& H; Q6 G. o
Statistic, 统计量) [4 X M3 ~6 R& D' n
Statistical control, 统计控制# J% \8 F* \7 @( u2 U( O
Statistical graph, 统计图9 s8 C3 n' D5 j; F8 J
Statistical inference, 统计推断/ [+ |9 [4 J% M
Statistical table, 统计表
4 c& }* v# P3 j# jSteepest descent, 最速下降法+ {: m$ r# z" Z9 }5 Z- f$ m( k
Stem and leaf display, 茎叶图
X |4 Z+ T4 k1 J x* z. \Step factor, 步长因子
9 x3 E& J) [& O! r. e9 e7 j5 ~0 y+ K8 ZStepwise regression, 逐步回归* y0 O& B; C7 J ?4 [+ E+ e4 s
Storage, 存
# i& P8 {, F. h- Z$ z( PStrata, 层（复数）, h; P1 S) B# r) X7 F2 q$ S
Stratified sampling, 分层抽样
2 x- t5 }4 \5 C {/ h- [Stratified sampling, 分层抽样
# P6 W4 I9 p& @. q. YStrength, 强度0 g, }+ Z7 F8 _ V9 q* Y% e
Stringency, 严密性
6 F! w; v+ g4 F7 I& uStructural relationship, 结构关系 D6 M& t: t8 A& Z) ^1 z
Studentized residual, 学生化残差/t化残差8 e5 m8 ]; e0 j- o! o( X6 T
Sub-class numbers, 次级组含量/ f0 n$ {5 T+ l! ^& x0 t
Subdividing, 分割
5 G3 Z( {6 U7 M! p' ]9 l& ?Sufficient statistic, 充分统计量
& a1 p) w7 V* x% {$ _; QSum of products, 积和
) P- l+ g7 e' |6 e' s8 jSum of squares, 离差平方和
9 T' M7 D! P+ g9 ~4 xSum of squares about regression, 回归平方和6 V" r6 v: |! R. k& }* y2 m
Sum of squares between groups, 组间平方和
" [( f7 s0 k+ q* D" USum of squares of partial regression, 偏回归平方和
/ ~+ _! g# n; [% wSure event, 必然事件. @/ H; y8 p) W) X ^' T8 u
Survey, 调查8 m1 z! v1 N2 s5 h. N2 c* W
Survival, 生存分析
5 n& o5 e6 o& h( J6 }! ?# a% R* {Survival rate, 生存率6 _" e5 p- s. f2 w3 o+ Q. u' G- S
Suspended root gram, 悬吊根图( r& K4 e* |1 q4 r+ `
Symmetry, 对称" c% V; b" G) \1 g
Systematic error, 系统误差
3 ~: H1 w# {+ {1 ]1 b4 s, G# A. jSystematic sampling, 系统抽样
- A- A% d0 T5 H5 OTags, 标签
1 ^( H# g% r l9 H! lTail area, 尾部面积
' l/ R- Q+ ]. [: a2 H3 S5 gTail length, 尾长- n2 {, T& a9 R
Tail weight, 尾重- A, V4 q4 F# ^' R4 I( e9 h; \2 h) r
Tangent line, 切线& h! W1 S! ?) e4 {
Target distribution, 目标分布
4 K8 R' x& c, z& ]: O; vTaylor series, 泰勒级数7 _. B' n2 i. p9 C
Tendency of dispersion, 离散趋势
, u* o. \. J# G( LTesting of hypotheses, 假设检验9 o2 {6 \; B3 T
Theoretical frequency, 理论频数' @1 n, [& ^; Q% k8 {
Time series, 时间序列
# E. }/ w/ C8 d# x/ s3 ~4 ETolerance interval, 容忍区间
4 f( S _9 S) y' yTolerance lower limit, 容忍下限# ]" S' D# t, A+ P2 ~! I" H
Tolerance upper limit, 容忍上限
% d$ z# s% w5 K% R& ]! KTorsion, 扰率% k2 f ~2 L. d4 a% M$ ?1 y5 ?
Total sum of square, 总平方和8 e( N% u8 v X# Y
Total variation, 总变异
2 G" G7 o/ d2 F) `Transformation, 转换
) v) Q! E# p) L, vTreatment, 处理
' _' l: H9 @$ `% B% f! R& ]/ bTrend, 趋势" s; c" x8 i9 N
Trend of percentage, 百分比趋势! N3 K- `$ ^* k
Trial, 试验
& r/ K9 R( t- K uTrial and error method, 试错法
) @! G% p4 S3 `9 hTuning constant, 细调常数
' K) x: ?3 S' v1 p' ^& R1 B* _# _' t7 yTwo sided test, 双向检验) S2 t/ ~& A- b
Two-stage least squares, 二阶最小平方( j9 S7 k& S( \0 i; P& m0 A
Two-stage sampling, 二阶段抽样. ^" X# z- Q) }0 S. w: X+ H; O
Two-tailed test, 双侧检验 j; y) N; ^4 G3 @# e9 e( d
Two-way analysis of variance, 双因素方差分析
5 H2 i9 z, y6 m1 [- x2 r# N2 _Two-way table, 双向表
. V2 Y* D1 ^0 b tType I error, 一类错误/α错误
, S* O6 e7 l5 u" t. \ R: u4 LType II error, 二类错误/β错误6 q% Y" o3 ^; n0 G2 x. J5 |
UMVU, 方差一致最小无偏估计简称/ l: o/ {9 k5 M. A' [; Q
Unbiased estimate, 无偏估计
4 q1 i+ S/ q9 ]! pUnconstrained nonlinear regression , 无约束非线性回归
5 ^4 h3 k/ h: N* y, S' JUnequal subclass number, 不等次级组含量
! o& d" c- z& Y* J# D- D7 uUngrouped data, 不分组资料; g: p( F1 K7 c, P# Y9 T6 _
Uniform coordinate, 均匀坐标* @1 b3 @2 N+ e$ i; T! w2 |% s
Uniform distribution, 均匀分布& ?1 m% S2 X, K ^
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计* h1 A8 q/ o, K* w4 D9 K: m
Unit, 单元5 b8 t C4 X# M1 P# ?
Unordered categories, 无序分类
) R' J: G& H0 R9 S5 m/ U- `Upper limit, 上限
) b9 n% |' j, A6 f' J* b) DUpward rank, 升秩
; f8 Y; \8 |' r$ B8 a+ C0 ZVague concept, 模糊概念
, D% p1 [1 I. e; T G; t- {4 }7 r9 \Validity, 有效性' N8 f2 g4 f. J0 W C: ?# R( ]1 J
VARCOMP (Variance component estimation), 方差元素估计/ p# y1 U; f+ }+ M; N
Variability, 变异性
d% |( {$ w# N" n0 L; bVariable, 变量9 L* i( A7 E. u0 K: |$ w5 `
Variance, 方差1 O! V' h2 h3 x: `+ ^7 j) l# j
Variation, 变异0 B7 Y& X- H S4 U: Y0 ?
Varimax orthogonal rotation, 方差最大正交旋转0 c8 v$ X4 H# F8 O) m' V
Volume of distribution, 容积
1 G. @; S/ u5 L5 o" HW test, W检验
* D: H7 g3 v A( r* H9 Y: LWeibull distribution, 威布尔分布
" ?, o! g1 z1 vWeight, 权数! O) g x E8 m# W
Weighted Chi-square test, 加权卡方检验/Cochran检验6 m# g( J; X+ f8 w* O
Weighted linear regression method, 加权直线回归
: A+ _) b8 r p0 j4 {% XWeighted mean, 加权平均数
3 ?) p, m: v# XWeighted mean square, 加权平均方差 Q8 K! H" `& V) {3 S/ v j
Weighted sum of square, 加权平方和+ B6 Y3 e+ I% z& |% \( j
Weighting coefficient, 权重系数' N$ J( p; i/ N, z- I3 G( g6 T( ]
Weighting method, 加权法 4 A/ M0 [, s8 L2 L! W( F% b
W-estimation, W估计量6 U2 e' @2 u& j( d
W-estimation of location, 位置W估计量* |- i, K+ |' t' X) l
Width, 宽度( U% R2 @4 B9 k$ P% H
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验7 |2 B# L, j0 @! M' a- E0 ^
Wild point, 野点/狂点
) M7 Q5 O* t; C, z; ]3 cWild value, 野值/狂值0 u, g7 }) n. s0 e# H7 N
Winsorized mean, 缩尾均值% l. J4 x, {, N! w, G
Withdraw, 失访 ' m( X8 k, A5 j4 o0 x3 D% y8 D1 ^
Youden's index, 尤登指数2 J6 U1 h3 ?# L* `6 Q8 W# o
Z test, Z检验- _0 \. }* i! V. n" D7 `. L) E, F" q: h
Zero correlation, 零相关) J" C& G. C( R
Z-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
