|
|
Absolute deviation, 绝对离差. i2 J- b8 L0 X; y1 g- Q3 ?: R
Absolute number, 绝对数' w5 Z: w6 e- [* G* e5 i# W
Absolute residuals, 绝对残差" Z' r% K# v8 x2 i; b+ C; D6 O
Acceleration array, 加速度立体阵4 H5 c( o! j0 z) ]( C6 h
Acceleration in an arbitrary direction, 任意方向上的加速度
9 ~2 }! O$ s6 }6 `- D1 JAcceleration normal, 法向加速度
. Q- G; i4 Y& D2 _# r$ k- F8 wAcceleration space dimension, 加速度空间的维数
5 f. o4 o4 l) _# wAcceleration tangential, 切向加速度
1 |4 O8 e- H$ E e6 U; j0 _Acceleration vector, 加速度向量
0 O; J" V0 G- yAcceptable hypothesis, 可接受假设5 `! Y1 E% k2 l: q2 ]
Accumulation, 累积9 ^" A$ I+ |2 U) N
Accuracy, 准确度5 e. G2 B6 n; D" a) O, T
Actual frequency, 实际频数6 @9 T4 h% e7 z
Adaptive estimator, 自适应估计量
' O& V+ G# _5 b. m* {Addition, 相加! b& m' E4 w8 n/ \
Addition theorem, 加法定理
; O$ S) Q% m7 W8 ^- qAdditivity, 可加性
7 d9 x; H7 r1 U0 C7 D6 h; m3 mAdjusted rate, 调整率. F; J+ E! v' M. R! s( {
Adjusted value, 校正值
: X3 z1 Y8 X$ H& ? e: eAdmissible error, 容许误差
, Q5 e8 v' A7 {1 y4 z; M uAggregation, 聚集性; q' ^6 N: D/ c U9 w
Alternative hypothesis, 备择假设& R% o( j- v* V b5 m5 _
Among groups, 组间0 \% e* W+ j. L2 `5 v, q
Amounts, 总量. K- V& a8 \% K7 N" I0 \) a& A6 L3 P
Analysis of correlation, 相关分析
4 R }. R8 _; `/ uAnalysis of covariance, 协方差分析6 t- V& L$ T$ K3 N$ O
Analysis of regression, 回归分析# [/ ]+ M) N: D" L" K# y
Analysis of time series, 时间序列分析
X4 s" w7 X0 r1 @) |- sAnalysis of variance, 方差分析
; E# h I4 a7 yAngular transformation, 角转换
! D) }8 y4 m- o8 Y# ?$ G! xANOVA （analysis of variance）, 方差分析0 u, i7 y1 P" c- A! p8 n3 ]- o( l) M
ANOVA Models, 方差分析模型7 D( `: j% m. q9 ?1 r- x
Arcing, 弧/弧旋
: Z- |" V K, d& J m: EArcsine transformation, 反正弦变换
4 N0 n9 g5 ]; tArea under the curve, 曲线面积
5 q" S; {0 b$ N6 P8 M7 e2 @3 rAREG , 评估从一个时间点到下一个时间点回归相关时的误差
5 j: V' k1 N/ a! l- C9 f1 I- V. RARIMA, 季节和非季节性单变量模型的极大似然估计 $ H* e" y6 m4 d" d
Arithmetic grid paper, 算术格纸
$ e5 z8 J* D& @( |2 W" @Arithmetic mean, 算术平均数
+ j4 n. {. Z7 dArrhenius relation, 艾恩尼斯关系
/ t/ r) ~: H1 f; f: _, H: YAssessing fit, 拟合的评估# v+ y9 L+ z1 Q6 v; I. k
Associative laws, 结合律
6 d/ g# v% G: rAsymmetric distribution, 非对称分布0 ^* G, ^# g* R1 D6 l
Asymptotic bias, 渐近偏倚
; W* S- H! Y& f1 a. yAsymptotic efficiency, 渐近效率$ ]3 K+ i" _, h( k* q
Asymptotic variance, 渐近方差
3 U2 _. N/ @ R; r4 w5 |+ UAttributable risk, 归因危险度% ]. T D, I" N- a
Attribute data, 属性资料
% z& Z' s( n5 \+ T8 Z8 \Attribution, 属性
" e, J# }# x3 h9 EAutocorrelation, 自相关
2 g- l2 e3 Q2 |8 {: pAutocorrelation of residuals, 残差的自相关
4 E. e) [. v; T4 C+ I# NAverage, 平均数, [5 [2 R+ V# N5 t9 r& |# F( k. N
Average confidence interval length, 平均置信区间长度
- k& i, y# t! p; ?& v4 WAverage growth rate, 平均增长率
: T* x8 I9 J% N. n$ G! aBar chart, 条形图$ G' M: O6 \" x4 f4 _: S
Bar graph, 条形图
" {) \! `- c0 ~5 EBase period, 基期) ^% a2 B4 ^. `: B1 K
Bayes' theorem , Bayes定理% _, C9 O* m$ \* v, K* C. W @
Bell-shaped curve, 钟形曲线0 L& i1 N. D/ ^! \
Bernoulli distribution, 伯努力分布
4 e" A! j% i8 e# ]Best-trim estimator, 最好切尾估计量& r9 ]% T8 j4 E
Bias, 偏性" j0 s6 J- d5 s- G# H
Binary logistic regression, 二元逻辑斯蒂回归
+ K/ ]4 D- I: C, l& T. n8 H mBinomial distribution, 二项分布0 L$ y* s% M! b5 o/ |( h
Bisquare, 双平方' J* S$ }3 o( b# P
Bivariate Correlate, 二变量相关$ E, D$ L/ F. Y7 v
Bivariate normal distribution, 双变量正态分布4 k( q# [( Y% s3 K E6 U$ X7 n
Bivariate normal population, 双变量正态总体
5 H# U' I( b) vBiweight interval, 双权区间
+ q B( R x% w2 h( SBiweight M-estimator, 双权M估计量
+ e$ C: e6 |: LBlock, 区组/配伍组
* E$ t: e8 `9 L7 \ ~+ vBMDP(Biomedical computer programs), BMDP统计软件包. L0 x( a% S( e( ~
Boxplots, 箱线图/箱尾图: E+ y4 \1 p- A* J3 U, \0 U
Breakdown bound, 崩溃界/崩溃点
0 k; z/ w3 u' r& k/ [3 UCanonical correlation, 典型相关
, _4 x4 y% K- ~+ D. g: n6 `Caption, 纵标目
# O/ g1 F# f q; J. cCase-control study, 病例对照研究
% A: f7 s w. u/ Q; \ MCategorical variable, 分类变量' L! y) J( e# W* s0 o* G
Catenary, 悬链线
; F" K% |3 v# I- h- ECauchy distribution, 柯西分布
5 `: `: }, N* u% u7 ?Cause-and-effect relationship, 因果关系2 h5 ^! I9 @( U0 A9 C, @1 w
Cell, 单元
" Y+ T9 }2 x6 @: q$ dCensoring, 终检8 }% E2 _8 Y% o1 W
Center of symmetry, 对称中心/ K6 p' |1 l. _
Centering and scaling, 中心化和定标. y6 H2 ^( d# u m) a. n: y2 e& J2 d( c
Central tendency, 集中趋势; |' r9 {/ ~. A3 ^
Central value, 中心值
- [; z5 ~, N% j" s* A# i' |CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测3 a$ F/ H# {$ C
Chance, 机遇
- q( |" y. e( \9 d. L4 hChance error, 随机误差. V7 P. K+ Q' l4 p( p3 W
Chance variable, 随机变量
$ O7 @: K- ~/ S$ q' Y! N Q4 y: W: OCharacteristic equation, 特征方程
~ t" W% ^, Z$ ~" n( }6 Q! XCharacteristic root, 特征根6 }8 @/ D5 u9 A/ W2 t
Characteristic vector, 特征向量3 ^% A/ G# ^' M/ r9 F& d9 q
Chebshev criterion of fit, 拟合的切比雪夫准则: C$ l/ r6 F, T/ k6 N
Chernoff faces, 切尔诺夫脸谱图- @% U5 _5 z0 `* a
Chi-square test, 卡方检验/χ2检验
% H/ ~: q8 M+ s0 g5 T- GCholeskey decomposition, 乔洛斯基分解
2 L, R* i. I' W% W3 tCircle chart, 圆图 L+ d5 d; y, g/ A" W
Class interval, 组距2 Z, ?5 m0 C/ y/ k) h: w
Class mid-value, 组中值
% j/ a: s4 x6 e; z1 j8 y' wClass upper limit, 组上限
, k$ a5 F3 A' b+ }7 k5 Y; N/ T VClassified variable, 分类变量
. r8 g/ V; ?$ \0 [. UCluster analysis, 聚类分析
1 c/ [0 {' m# B1 W8 H, v/ g* E# aCluster sampling, 整群抽样! r( H& V8 ]' z1 o; K
Code, 代码$ c6 C: ~$ W) G2 H6 I' g- N
Coded data, 编码数据! i4 k, N# V7 P. q* V" p
Coding, 编码7 P+ g% R2 ?2 V3 t1 h. S
Coefficient of contingency, 列联系数' D& e) W' R% z8 c
Coefficient of determination, 决定系数. ~0 p" S9 x8 P) _! {
Coefficient of multiple correlation, 多重相关系数
/ p- v3 v9 v: X! fCoefficient of partial correlation, 偏相关系数
% L" M3 a8 B& n" _$ dCoefficient of production-moment correlation, 积差相关系数4 D% T' c5 o7 x
Coefficient of rank correlation, 等级相关系数2 c# G5 }/ a2 @5 D* {" l( a$ u
Coefficient of regression, 回归系数
' H9 d; T( _7 K! c; ], u8 xCoefficient of skewness, 偏度系数- V8 W9 i/ W" H& |' E: h& @5 N' \+ J
Coefficient of variation, 变异系数# {9 L/ m+ a1 {- Y" q7 m, N
Cohort study, 队列研究( A& _+ x- {6 a* {" p! H& Q& y! U
Column, 列) e* `9 i/ }" t! V6 J2 A9 ~. r! W
Column effect, 列效应! [' ~; {# W; {4 |2 E! P
Column factor, 列因素2 Q1 y' I/ j. v
Combination pool, 合并
! _" h [" P# W# ~Combinative table, 组合表2 ], Z( c( @: Y9 ]* [6 d
Common factor, 共性因子
6 J* y/ r- w1 }; y' v8 `0 kCommon regression coefficient, 公共回归系数! M! {: x3 S; e, O `! O
Common value, 共同值/ A1 _ F% _/ F
Common variance, 公共方差- ~, E0 N9 X3 c C2 S
Common variation, 公共变异
) Z1 W$ x2 [. T5 w0 W! D* XCommunality variance, 共性方差
$ t3 y l6 p0 V! T# o+ ]Comparability, 可比性3 T! Y& |- ^! e
Comparison of bathes, 批比较2 j5 j( m8 d. A9 T
Comparison value, 比较值2 T2 j9 L4 a$ x: X
Compartment model, 分部模型
X0 w$ J6 J& K2 r2 tCompassion, 伸缩
* ?2 p4 e/ R" {Complement of an event, 补事件
0 n/ ~* o. }9 B; T) V% n% mComplete association, 完全正相关
6 d* j& l0 w5 m9 R( h6 YComplete dissociation, 完全不相关
6 q' O/ o5 U) u* A: W8 QComplete statistics, 完备统计量
9 M7 x1 h1 x7 G: ^6 P( t1 MCompletely randomized design, 完全随机化设计! Z- `0 w" F8 v
Composite event, 联合事件! z8 }6 d# p' f* H. R6 i
Composite events, 复合事件
, H/ p8 H9 e& I4 IConcavity, 凹性
$ h5 b! o* n% L$ q' P/ z+ X5 G$ TConditional expectation, 条件期望
9 O% J1 K( g0 U( ]. a: `Conditional likelihood, 条件似然5 P9 a; ? v. X1 g M' ?5 F
Conditional probability, 条件概率
% o9 m7 n+ o! s+ u: O, j0 ~! g PConditionally linear, 依条件线性( {6 \+ s* Y6 {0 o8 a; @
Confidence interval, 置信区间: R+ j& Q6 [+ P" l
Confidence limit, 置信限8 N6 I( l, k3 P! |! N5 t
Confidence lower limit, 置信下限( g+ Z1 \+ q# b- y- [( V4 V3 J
Confidence upper limit, 置信上限! E) j+ H S/ }5 v
Confirmatory Factor Analysis , 验证性因子分析
% o4 @& Q2 F1 {8 U8 t& s; QConfirmatory research, 证实性实验研究
: T6 t* p4 T9 {' t5 z) QConfounding factor, 混杂因素
- S8 @) A H0 S1 |8 b5 ]' z4 _- X4 jConjoint, 联合分析
$ K! q0 q: N9 N' p% \9 b$ K0 gConsistency, 相合性
$ \: r5 d1 B3 o7 |Consistency check, 一致性检验
: K" L: e; I* g% S* F% C1 U. w" fConsistent asymptotically normal estimate, 相合渐近正态估计
3 ~6 p! ~/ `, U) {% nConsistent estimate, 相合估计
/ a+ ?: k& S; F5 z4 _ oConstrained nonlinear regression, 受约束非线性回归0 b& O, \0 ^1 q7 q5 J/ x3 H
Constraint, 约束; U0 T5 c- I/ u$ S7 M, T* B% m X
Contaminated distribution, 污染分布
; L; ~# M% `1 G+ X! m: aContaminated Gausssian, 污染高斯分布
! A% n! P6 r' l6 _+ j' U( IContaminated normal distribution, 污染正态分布
6 |) Y4 d' b. Y1 W# x1 uContamination, 污染
) h' u y& `3 q8 bContamination model, 污染模型* d, O! c/ y6 t2 u. z o* w
Contingency table, 列联表) Y+ q. V2 O2 W- e- t
Contour, 边界线1 J$ m2 a8 y# J6 M/ `8 D8 a9 `3 j, V4 p
Contribution rate, 贡献率; n, }$ U. k" |/ n9 l7 y
Control, 对照
- S+ }* ?! z1 x$ ~: a6 \Controlled experiments, 对照实验( @8 b* {8 N% }( f2 j! p, c# a
Conventional depth, 常规深度. n* Y) o+ b% B, }
Convolution, 卷积
z' B9 R t8 ~) DCorrected factor, 校正因子$ V7 Z h$ B7 x5 y
Corrected mean, 校正均值4 K! b: y. `# y, D: b! w' ?
Correction coefficient, 校正系数) j/ z2 [6 b E6 n7 V6 V
Correctness, 正确性( K5 X! e' R2 a/ f, V+ c2 Z4 A8 ?
Correlation coefficient, 相关系数- `- x. W. b, ]5 D# {
Correlation index, 相关指数
+ M. n( C! u Y4 X$ G) R3 k) U( s- rCorrespondence, 对应" L6 I1 }+ P) i# q# Q- h" H$ |
Counting, 计数) {8 F* }6 ^) M% ~
Counts, 计数/频数* ?5 v) w ^1 G
Covariance, 协方差* @+ l' u- j& I6 c* h' l
Covariant, 共变 . ^' }5 B0 v) m- a0 P. v! z
Cox Regression, Cox回归" |) |$ F) `- e3 u$ E+ @5 X8 Z8 L
Criteria for fitting, 拟合准则8 ]% S9 n- P8 D! f- q* d! T$ u
Criteria of least squares, 最小二乘准则
( @' B( q1 f0 F WCritical ratio, 临界比
' j) w8 w$ w8 r2 S" vCritical region, 拒绝域7 W9 U* M0 f3 z. K) g& `
Critical value, 临界值/ w# L4 q& G: K, _0 {' p5 N
Cross-over design, 交叉设计1 F0 o& \5 q/ A6 n
Cross-section analysis, 横断面分析
+ K, V2 h6 F' X/ F2 n4 q) _' D" aCross-section survey, 横断面调查
6 ?+ N7 i# t% o% Z# jCrosstabs , 交叉表
( O2 _4 u& v0 d9 K4 Q% M3 ^& \Cross-tabulation table, 复合表
& ?$ [! w+ R. lCube root, 立方根
u- O# U* q; F/ FCumulative distribution function, 分布函数4 g( Y) U+ @4 q$ N
Cumulative probability, 累计概率
$ [& @4 ^( s/ N) h8 m1 @' m* X3 ACurvature, 曲率/弯曲
) k+ l! F: r1 G9 ECurvature, 曲率
. R: ~: U- i* H9 ICurve fit , 曲线拟和
0 w# M( Z0 f, v' i8 F6 a( kCurve fitting, 曲线拟合
: G1 R: B& z$ d4 @& U: MCurvilinear regression, 曲线回归
4 r9 ]) v/ x- j4 c# Y6 s0 Z' h0 C8 ]Curvilinear relation, 曲线关系0 G9 x x; w2 n* C" m9 i8 R
Cut-and-try method, 尝试法7 ?' `+ I# Q( l
Cycle, 周期
6 [( }( u! ]/ v- |8 PCyclist, 周期性7 ^6 i- {" E) S O1 R
D test, D检验
0 Q$ \& Q7 u% X7 WData acquisition, 资料收集
5 z# H" w1 T4 \8 R$ ?: K5 EData bank, 数据库
0 ~. k0 j1 v/ O* MData capacity, 数据容量
/ A5 J: v- C' k8 S) _/ hData deficiencies, 数据缺乏
m% `: L0 {+ ], Y+ N. KData handling, 数据处理
( r3 M7 L8 E, l2 S+ j7 lData manipulation, 数据处理2 C6 p j+ g4 I/ ^6 `6 w. s2 j% A
Data processing, 数据处理
1 \- r: u- u9 E% @9 Q' ?/ K1 x' {Data reduction, 数据缩减0 ?+ |; V B9 p i4 V
Data set, 数据集$ o% [! } O/ y) T7 w5 N
Data sources, 数据来源; U5 j4 y8 p2 I* ~/ F/ d
Data transformation, 数据变换
: X; v4 H2 g' EData validity, 数据有效性' ?1 g! u' c0 J2 [7 o
Data-in, 数据输入' z8 i9 L) K" b9 q
Data-out, 数据输出
3 ^: A- I5 m; u/ _Dead time, 停滞期6 j8 s* y+ `9 a+ M. a/ F7 a0 z
Degree of freedom, 自由度
- B" y& t- x: M' _( v2 SDegree of precision, 精密度
/ {1 P# _6 X, ]$ d- DDegree of reliability, 可靠性程度- ~# ]' B" q7 y) F) o4 b) z' \
Degression, 递减
& A L. Y2 A! O* b+ A4 K& oDensity function, 密度函数
$ P% X' L; [1 l" F* o* `8 W" QDensity of data points, 数据点的密度- z: a t' H4 a/ k
Dependent variable, 应变量/依变量/因变量
/ c/ Y5 q3 r: y9 L( o0 @) L4 _Dependent variable, 因变量; q9 w7 T1 J: {# M7 z! F
Depth, 深度
+ B& Y' B% P1 FDerivative matrix, 导数矩阵
$ e7 W% g0 t T5 H- [Derivative-free methods, 无导数方法
" [/ S4 _5 q1 z- c Q4 q7 }& zDesign, 设计. f& D( e4 b, O( J5 t8 L2 a f
Determinacy, 确定性7 P9 B# A- |9 F& B; W% O( w) Q
Determinant, 行列式
' a- { e! E: i1 m, yDeterminant, 决定因素' N% Q* h+ T! V. w* ]
Deviation, 离差' ]$ y# O+ u; z( j {( z0 h3 P
Deviation from average, 离均差/ k2 H4 }$ c2 H# x& n1 E; h6 E
Diagnostic plot, 诊断图3 G8 b$ X a1 G2 [# U
Dichotomous variable, 二分变量
5 ~ |2 H7 H2 {. x( UDifferential equation, 微分方程- A9 c# S) q4 }/ I! D
Direct standardization, 直接标准化法
v& I/ d4 k3 c, X' oDiscrete variable, 离散型变量
3 Z: }$ {" Z9 s& X; wDISCRIMINANT, 判断
c# v( j+ S4 nDiscriminant analysis, 判别分析
2 V# p( N/ g* @3 N+ u5 \Discriminant coefficient, 判别系数; o9 a$ k9 z% U; k7 z
Discriminant function, 判别值0 |# g3 r- [: |' ~. \- |& o- q
Dispersion, 散布/分散度
# `% @7 I3 Q: |- q: SDisproportional, 不成比例的
) J3 B2 T7 f4 \8 k. T, }# i$ QDisproportionate sub-class numbers, 不成比例次级组含量
4 g9 R7 i: U6 ~6 e6 zDistribution free, 分布无关性/免分布* r0 A$ y, ?$ K( R3 N f
Distribution shape, 分布形状# Q+ \* b2 }# x+ t# B# _
Distribution-free method, 任意分布法5 L/ y' n6 d) f* e z
Distributive laws, 分配律, `2 t9 c+ b! Z
Disturbance, 随机扰动项. j0 s7 Q. S& Y
Dose response curve, 剂量反应曲线
0 y Z2 J+ v) XDouble blind method, 双盲法
# S6 M1 J' T' j' wDouble blind trial, 双盲试验
. i! a) l8 B% E) }, q# WDouble exponential distribution, 双指数分布1 ?6 }/ P1 `% T! ]/ D @
Double logarithmic, 双对数8 J- [% g8 u$ B3 y! C* N1 g: \
Downward rank, 降秩. {2 j/ ?! z5 [2 p
Dual-space plot, 对偶空间图
+ Q- A9 @/ K/ @- G8 f4 H1 s0 x+ RDUD, 无导数方法
. \+ v3 G: k, N# q r6 h; [Duncan's new multiple range method, 新复极差法/Duncan新法
7 K4 T8 b- E9 n& VEffect, 实验效应( F: a% ~# r1 Y4 \# }, l
Eigenvalue, 特征值
$ s) \- ?4 M" \+ I( V6 OEigenvector, 特征向量
4 f" F5 X; v @5 H$ J. ~Ellipse, 椭圆
* @" H9 u9 J8 A0 b, S$ E# _9 \" zEmpirical distribution, 经验分布
/ a6 |! ^2 B+ y8 X" t5 ]; vEmpirical probability, 经验概率单位" M7 k& `' {: n, c0 H& Z9 u; ^
Enumeration data, 计数资料
_$ `; F. _0 u. U! ?+ DEqual sun-class number, 相等次级组含量/ a1 }, l- ]) Y7 d( @
Equally likely, 等可能! i# Q3 T3 |0 T- _8 F) g9 D" J' w# _) ^
Equivariance, 同变性
. g/ Z i4 R# h1 b6 IError, 误差/错误
2 a1 l3 U1 |9 ^& p1 k1 T" YError of estimate, 估计误差+ X" |8 s4 B2 I7 D
Error type I, 第一类错误1 N j8 G6 m$ p3 [9 ^
Error type II, 第二类错误
+ T; l; S$ a, @7 ^3 d, E( BEstimand, 被估量2 T T! j# K. N& C+ F
Estimated error mean squares, 估计误差均方1 j- O4 K% I7 Q/ j g
Estimated error sum of squares, 估计误差平方和* S- |2 ]' J- m0 b3 p0 s
Euclidean distance, 欧式距离1 `+ U" @+ |' m! j8 ?2 T
Event, 事件/ e) V2 S9 H5 z. h
Event, 事件* ]0 S7 |. s. A3 G \3 X- }, ?
Exceptional data point, 异常数据点* N9 h$ Q, V# Z2 l5 F
Expectation plane, 期望平面1 {/ N$ _" N( ^
Expectation surface, 期望曲面/ i. T& s3 o. Y" V
Expected values, 期望值
" L5 J. H% E: u. y d A# f9 ~4 MExperiment, 实验* b5 m8 ?- \2 Q0 `
Experimental sampling, 试验抽样
3 w' y7 \$ |4 iExperimental unit, 试验单位$ s3 U8 O8 o: J+ U* a6 K5 M4 o
Explanatory variable, 说明变量
. o. w7 ~0 i# H; ]* |# l) wExploratory data analysis, 探索性数据分析
8 } d4 G2 c" h& f# m+ PExplore Summarize, 探索-摘要/ G' X# S: U2 E# T( i _4 Z
Exponential curve, 指数曲线& j) |. E6 z+ q8 v/ ^& ?, T* O" t/ D0 O
Exponential growth, 指数式增长
$ t7 g ?: t# c/ ZEXSMOOTH, 指数平滑方法
% w8 M9 D6 m1 N, v8 O dExtended fit, 扩充拟合
* T% Q5 m+ c0 {4 s. cExtra parameter, 附加参数7 E( C: b& b! [; ~' R- w
Extrapolation, 外推法, o; V, U7 ]2 L
Extreme observation, 末端观测值' B R' `! ?, |: @3 u- E( n/ J
Extremes, 极端值/极值: J* s+ P9 E# O. i$ f6 J! j
F distribution, F分布
# i3 }% h8 t, T5 jF test, F检验8 g" F0 I s1 P
Factor, 因素/因子
r; E4 {" M5 S# _' ^Factor analysis, 因子分析) D" p5 A( y4 G# } g4 y, ]$ Y+ ~
Factor Analysis, 因子分析' r5 s1 s0 @6 t. `8 G
Factor score, 因子得分
$ { @9 X- | I% Z% |% W0 XFactorial, 阶乘
$ N7 u9 D- B) ~Factorial design, 析因试验设计
3 g( t, H3 x0 [; b h" VFalse negative, 假阴性 d3 g, x6 j$ H* q- d7 x7 `/ B3 l! q
False negative error, 假阴性错误
( j( O8 v7 j" ~Family of distributions, 分布族
+ `/ c/ {" i. h, iFamily of estimators, 估计量族
^! g- [$ D/ h' iFanning, 扇面& _3 {* B) p0 W0 i6 g
Fatality rate, 病死率
. V& q, c1 ?8 z% ~- @0 S* b7 V5 dField investigation, 现场调查7 J0 g; s& ~! }% t0 p; Z
Field survey, 现场调查
; C3 P5 P# w4 v3 L: a MFinite population, 有限总体8 I% g$ U: o9 a+ U# W/ `" J: [1 T
Finite-sample, 有限样本: V$ y: e5 [1 ~( m$ n
First derivative, 一阶导数
2 i$ f* R# ?% N: f Q8 OFirst principal component, 第一主成分
" d4 P e/ l; PFirst quartile, 第一四分位数( i3 \9 L, |, P* \. a" p* N* h
Fisher information, 费雪信息量# Z& X) N1 U) l! n
Fitted value, 拟合值
) E# Q- w- \1 o4 u/ V! ]Fitting a curve, 曲线拟合8 n( X5 ~* i Z
Fixed base, 定基
- r; A+ i" x) x2 m3 [ {* U+ T; \Fluctuation, 随机起伏 Z# {2 |0 ^7 Z' \4 U3 z
Forecast, 预测
5 S {" K! W6 ~4 ^+ L4 aFour fold table, 四格表
6 c5 W# Q* D lFourth, 四分点, D9 x/ P6 y1 d
Fraction blow, 左侧比率6 v- l# A/ B2 [, t; F- }1 Q
Fractional error, 相对误差8 x6 j( b6 ?& A4 o
Frequency, 频率+ d5 a0 L. }8 ~7 s" Q
Frequency polygon, 频数多边图+ C8 H( b0 e+ O1 ]$ h
Frontier point, 界限点
+ W$ u% g! Y8 i9 P/ V/ L: QFunction relationship, 泛函关系$ R! Q$ ^: X W5 P- A
Gamma distribution, 伽玛分布
- b4 F6 Q$ p5 vGauss increment, 高斯增量/ I& e) Z7 z, F" T2 Q$ C3 m; V8 r
Gaussian distribution, 高斯分布/正态分布
! ?* h: s( h) @$ x! j8 KGauss-Newton increment, 高斯-牛顿增量) C# \2 o$ M8 ?/ F% G$ O
General census, 全面普查- v& x' }! P# ~; @8 o$ O. {9 P
GENLOG (Generalized liner models), 广义线性模型
+ y4 G, E7 Q# D4 R# ~Geometric mean, 几何平均数; i8 L3 \8 Z- P- f/ K0 S
Gini's mean difference, 基尼均差3 [+ j6 b# f" i% b5 q$ y! E
GLM (General liner models), 一般线性模型
Z: X0 z( k, M9 [Goodness of fit, 拟和优度/配合度
+ ^$ @5 G$ ?1 S# z' u5 M- nGradient of determinant, 行列式的梯度* k, I( @/ h8 B) j; E/ k3 S
Graeco-Latin square, 希腊拉丁方
) ^1 Y. ^# D( `" K+ g2 CGrand mean, 总均值
0 f; r3 M" @& e( T6 xGross errors, 重大错误
+ F6 c" }, m+ B1 ^- T$ H8 \Gross-error sensitivity, 大错敏感度
7 z! l1 q" K- P( h* I8 O0 zGroup averages, 分组平均1 w9 z3 ^9 a! m& D1 \
Grouped data, 分组资料3 k! R) a' H( a3 b0 D
Guessed mean, 假定平均数8 J I d4 R: Y$ Q Z9 K9 C4 l
Half-life, 半衰期 @1 k0 K& H. L& q+ G+ H# [% u1 J
Hampel M-estimators, 汉佩尔M估计量
4 Y, ?" Q! H) J% |Happenstance, 偶然事件$ c0 y1 J8 S; W* D8 y4 a
Harmonic mean, 调和均数* Z8 B0 i4 v+ y# A
Hazard function, 风险均数
. b" j/ ?0 K. G+ I( ?5 _2 k# v$ EHazard rate, 风险率2 C7 s7 l2 F, u% t
Heading, 标目 ) l) N8 X- @$ _- s" b9 M9 Y
Heavy-tailed distribution, 重尾分布
k4 e7 B% N8 j: w1 d; ]Hessian array, 海森立体阵
. K$ s' A7 T- M7 m$ Q$ j1 d5 DHeterogeneity, 不同质
) o" R3 c! h9 W, Y2 ?/ V# HHeterogeneity of variance, 方差不齐
4 i( @. B6 u; i2 N V1 EHierarchical classification, 组内分组
: y$ Z) P* t7 s% [1 i4 kHierarchical clustering method, 系统聚类法
8 {, X; {6 u& B3 w# ]3 bHigh-leverage point, 高杠杆率点
8 `1 Z, b1 x! K- ?' s$ c$ UHILOGLINEAR, 多维列联表的层次对数线性模型
) O: j/ a. G. P) t, U2 ?Hinge, 折叶点- y: |3 j! m& d" v w; y8 j- ]8 J% ?; {
Histogram, 直方图
4 b1 Q7 H& f1 j( u# G+ A6 k% |Historical cohort study, 历史性队列研究
6 ]7 w v/ V( z- y' C ~8 N" CHoles, 空洞; B; @/ \ k1 Z: H
HOMALS, 多重响应分析. o: a' x/ M, h2 W: x" g
Homogeneity of variance, 方差齐性) t9 f3 D2 T0 k3 W" O# H* e/ H1 R! z
Homogeneity test, 齐性检验( F n- r4 ~( I) D7 s
Huber M-estimators, 休伯M估计量, O. p* t6 ~( F6 d7 D3 q
Hyperbola, 双曲线3 t0 k% C1 P) f% p$ r
Hypothesis testing, 假设检验6 W! Z( r/ A9 v* u) s
Hypothetical universe, 假设总体3 G- `$ y4 G# D& o9 N5 q) U' c
Impossible event, 不可能事件 w5 }) E9 ^8 O4 K: L, b
Independence, 独立性
$ z* y% ^/ Q! D! G3 {( JIndependent variable, 自变量
1 I6 V8 z) l/ j2 U9 O, _% s3 w J. ]Index, 指标/指数* [4 H: o' A0 D
Indirect standardization, 间接标准化法5 K& W; R! y9 w2 i$ A6 i) @
Individual, 个体
9 b8 W) M* G( n0 k7 M6 m/ AInference band, 推断带
: \5 Z8 r. t8 Q7 q5 oInfinite population, 无限总体
! i* H+ @) M g9 WInfinitely great, 无穷大
+ f' V* ~# r! b+ J. y/ x, g+ U+ cInfinitely small, 无穷小8 I0 r9 @. q8 t: l2 j
Influence curve, 影响曲线; p) k; c* k) a, e3 |3 b$ l
Information capacity, 信息容量4 C( t1 p# U3 Q0 h! l3 J2 a; D: E
Initial condition, 初始条件
0 Y( q7 }1 v% ~3 nInitial estimate, 初始估计值
; U/ W# }8 J: O/ j; u! ]9 j; uInitial level, 最初水平5 g+ ^; A5 U- W$ A5 x# }0 O
Interaction, 交互作用
4 x+ J' Y1 N \4 ?/ L, _1 O# d+ TInteraction terms, 交互作用项% K- Y) c2 A% V, p6 _) l( G
Intercept, 截距
& H5 U2 o5 |1 t3 nInterpolation, 内插法8 {. n# o" Q9 e5 }2 ~6 ]- R2 i* P
Interquartile range, 四分位距
. X- b9 Y5 k+ N1 o. f4 p1 nInterval estimation, 区间估计% A: s* b0 g$ V" N) a6 q
Intervals of equal probability, 等概率区间
: Y1 i9 \) H( l+ S: a: \4 |4 IIntrinsic curvature, 固有曲率
: p% p) u0 `' L9 r; k7 p. iInvariance, 不变性! r7 t d+ ^0 U* N$ P1 n; P
Inverse matrix, 逆矩阵
$ P) h' M7 F) y3 m) AInverse probability, 逆概率
( b/ V1 i. R8 C2 d* oInverse sine transformation, 反正弦变换6 w2 M8 C+ Q5 A' k$ ~
Iteration, 迭代
4 _( j+ N- n! Y% RJacobian determinant, 雅可比行列式) s; H+ v! d6 V# r9 L( p
Joint distribution function, 分布函数. S, l7 u4 f% ?7 |# S" ?' W
Joint probability, 联合概率6 o2 \8 k; R8 l. N0 m
Joint probability distribution, 联合概率分布
' @0 \1 X* r! {0 t+ ]K means method, 逐步聚类法
# u4 g5 M3 r$ o! bKaplan-Meier, 评估事件的时间长度 - v% @% C; g Z( u4 M" d4 q
Kaplan-Merier chart, Kaplan-Merier图/ `4 C! `9 m, c% _
Kendall's rank correlation, Kendall等级相关
% U/ H8 q& @5 U6 ?2 RKinetic, 动力学* L8 K; ]5 n! U' p# I$ \
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验: Z8 e) j' A5 i1 [
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
! V8 [) m$ S: S3 a8 H: O/ kKurtosis, 峰度' h" O8 p; U' w1 v
Lack of fit, 失拟
& x, R6 v& n; v7 qLadder of powers, 幂阶梯% W- i$ }1 z! Z7 A: X- B
Lag, 滞后
p3 W$ A" F& |$ {7 ~Large sample, 大样本2 E8 v. A0 P0 G% U/ t0 x2 C
Large sample test, 大样本检验# E; r: o' U( y8 F: V7 y* `2 C
Latin square, 拉丁方. ]7 i8 W3 b! t2 T9 O8 i. \# j4 a
Latin square design, 拉丁方设计# O1 ]* t; j, d- i
Leakage, 泄漏* P1 a1 H/ ?2 u# a1 k8 D: R
Least favorable configuration, 最不利构形2 V) P5 C/ l0 Q
Least favorable distribution, 最不利分布
^- Y" \* q' S; [0 _Least significant difference, 最小显著差法# A; H" M( j0 x9 r8 v6 b- h
Least square method, 最小二乘法
8 m' \# n3 w+ ]* x" ~Least-absolute-residuals estimates, 最小绝对残差估计
, X1 U, m" G& b, jLeast-absolute-residuals fit, 最小绝对残差拟合
. t7 O5 _7 T- ~& ^$ H0 {( FLeast-absolute-residuals line, 最小绝对残差线
, {) a( W, H! l l& ], }% P6 qLegend, 图例
: a3 z+ Z( p4 c! |* l5 ^L-estimator, L估计量
6 A2 e1 F4 N) d [1 m4 QL-estimator of location, 位置L估计量# f( c; c) v5 }3 a3 z! A7 Y5 Q
L-estimator of scale, 尺度L估计量
! u4 w. E! j1 U0 ?& uLevel, 水平& U m% [# y3 B/ m: l/ H3 ^) b
Life expectance, 预期期望寿命* A( r; x' ~# |$ @$ F5 K6 c f
Life table, 寿命表
; l6 Q! h) t0 `+ z8 xLife table method, 生命表法5 w5 N& f" B4 K& }( y0 s8 i) X
Light-tailed distribution, 轻尾分布; `9 O" ^; d/ {; \; [% L; O. _+ `
Likelihood function, 似然函数6 A' ~) ?- L8 L- n3 q0 F
Likelihood ratio, 似然比
+ t/ M) t/ E7 N" `6 Hline graph, 线图
3 w2 D* Z k% ?Linear correlation, 直线相关( G' ?: H+ \2 ~: p! g2 m) ]
Linear equation, 线性方程
) s& \6 D3 }- @0 ALinear programming, 线性规划5 l3 S2 \' Z- ]: \9 L, U! `. P
Linear regression, 直线回归
* b8 x2 S: v7 c7 ULinear Regression, 线性回归
0 z3 ]- Q0 Y- N* u* b j& uLinear trend, 线性趋势
( r5 ]5 S& j6 ULoading, 载荷
J% I! J: ]8 ]8 R, ^9 A3 ULocation and scale equivariance, 位置尺度同变性
5 }% e- a* T3 L% U# J) bLocation equivariance, 位置同变性
1 G/ \2 v- |# x. ^3 YLocation invariance, 位置不变性
- }4 j7 B7 `$ p7 Z& aLocation scale family, 位置尺度族3 _- \$ W. e% q+ j% h& h4 \
Log rank test, 时序检验
& w2 q- l. k* m5 ^9 i5 ]Logarithmic curve, 对数曲线# R7 r8 K3 r9 Z, G& c
Logarithmic normal distribution, 对数正态分布
$ o2 g# L0 e1 K/ m" A3 T: e! z+ G c' OLogarithmic scale, 对数尺度1 R, d% t& q( V* y
Logarithmic transformation, 对数变换
+ s8 c4 E$ V, N! ~: O% oLogic check, 逻辑检查
1 c9 G/ Q) g/ {) r6 ]Logistic distribution, 逻辑斯特分布
. R0 U5 v& J3 S- `4 g: P" _2 bLogit transformation, Logit转换5 j8 H' i. O( Y
LOGLINEAR, 多维列联表通用模型 * o$ T5 d/ v; S
Lognormal distribution, 对数正态分布
! D- F$ _) R% E% G6 N CLost function, 损失函数' C" N( t+ u3 t! E
Low correlation, 低度相关
+ M8 {; D- d ~ N4 J) Q" k. yLower limit, 下限
4 F5 B1 x- b+ QLowest-attained variance, 最小可达方差& b. p" R% P3 {& V0 Q
LSD, 最小显著差法的简称 m( _! e- T& [9 _- i% K
Lurking variable, 潜在变量
. P" v; f f: L3 n$ K" RMain effect, 主效应: \. N/ h6 {" t6 ]
Major heading, 主辞标目
m4 C+ H! p7 E3 m, e: w% lMarginal density function, 边缘密度函数( S# ~7 M% I P: }5 a
Marginal probability, 边缘概率: J! c! l4 I5 }, W) d! d
Marginal probability distribution, 边缘概率分布0 }9 o0 }! p" ^6 A! X
Matched data, 配对资料
. S0 i6 q& U: U" TMatched distribution, 匹配过分布
% S( ~2 Q- M+ V$ H- p5 eMatching of distribution, 分布的匹配) O, D! m0 q% |; ]( F& i; @2 J
Matching of transformation, 变换的匹配; u! n0 L- \% l
Mathematical expectation, 数学期望; Z) Y' j8 m& C
Mathematical model, 数学模型% r* N1 C" T; S0 A; @
Maximum L-estimator, 极大极小L 估计量7 G' k5 T. E2 A" q& @4 K
Maximum likelihood method, 最大似然法" L: q# X4 r' ]( A
Mean, 均数
6 L9 W3 G8 c$ s- g8 Y, F- rMean squares between groups, 组间均方
7 d$ Z5 R4 s, Q( k' N' PMean squares within group, 组内均方( M2 h( r3 z* j _
Means (Compare means), 均值-均值比较
/ R _3 o! X7 D! w! hMedian, 中位数# B/ d E% _3 C. k" s6 q7 q9 d
Median effective dose, 半数效量
0 Q! }$ i' E0 B; t Q) n) }Median lethal dose, 半数致死量1 p9 h/ H N& H9 |
Median polish, 中位数平滑! C; [* L2 P2 p3 {7 R
Median test, 中位数检验
- V5 |6 S- I# v) m: K3 k: _Minimal sufficient statistic, 最小充分统计量# ^( P9 S: R1 W' i
Minimum distance estimation, 最小距离估计! e$ L2 Y. ~4 S* s& d i3 M
Minimum effective dose, 最小有效量& j4 {" c' R6 x( C4 L
Minimum lethal dose, 最小致死量
% } O% \) a8 o' T AMinimum variance estimator, 最小方差估计量
8 ~2 K& T5 H& s# L' KMINITAB, 统计软件包. O2 w% t5 w, k
Minor heading, 宾词标目9 d/ t2 [/ N9 F! u6 a1 L
Missing data, 缺失值7 h8 [9 @) |+ d+ i
Model specification, 模型的确定
; U5 Y* p/ {% t1 v# ^6 E: |8 ^, W! WModeling Statistics , 模型统计, G, n7 M8 d! r0 j( O: K2 L
Models for outliers, 离群值模型' P- a- G2 m5 W' h+ ]
Modifying the model, 模型的修正/ L& @" \; y8 S; M K. e" f# q0 N
Modulus of continuity, 连续性模. ~1 R! R6 Q0 M! S: i! Q! d
Morbidity, 发病率
6 L. y# e8 N" G- o4 ^8 R: ]& _Most favorable configuration, 最有利构形
+ x, h* Q) q+ r4 R: oMultidimensional Scaling (ASCAL), 多维尺度/多维标度) Z; {) ?7 o0 o" t: h
Multinomial Logistic Regression , 多项逻辑斯蒂回归
) m0 @) M# D* B- O4 mMultiple comparison, 多重比较
2 d9 f7 O0 [& M, I1 Y" Q4 LMultiple correlation , 复相关
/ o; i. A% `( W b9 F8 z% k7 Z* HMultiple covariance, 多元协方差
8 T$ f) o7 j0 `" DMultiple linear regression, 多元线性回归
9 q/ }8 \3 \( g% eMultiple response , 多重选项1 t) O1 p, d5 T/ T+ s
Multiple solutions, 多解' W' q# t" f6 e% ~% Q. `
Multiplication theorem, 乘法定理! t. F. q$ c* d' O, q
Multiresponse, 多元响应
2 Q$ z5 e' O$ v9 F) @Multi-stage sampling, 多阶段抽样' { b* s' w1 T8 v% l" a
Multivariate T distribution, 多元T分布
2 ^2 P) r- i# w0 J- a9 S( H+ `& DMutual exclusive, 互不相容
+ K7 a0 f" ^6 {! PMutual independence, 互相独立
" G* _6 w6 x: [( m/ h; o/ B0 \Natural boundary, 自然边界
. u2 p) j0 L v4 {Natural dead, 自然死亡
- }/ Y1 M# q; h7 dNatural zero, 自然零
- e7 G' j' A: t" R: C0 aNegative correlation, 负相关
* o7 A9 U' E; K+ L9 @Negative linear correlation, 负线性相关
. f6 Q# O( N. }( N; l* PNegatively skewed, 负偏
. D: _8 F, I7 P3 n# b9 _Newman-Keuls method, q检验- [; W4 d, c! x, p% P7 @
NK method, q检验
+ w4 @; x, Z8 d1 i" R$ k4 MNo statistical significance, 无统计意义
4 ^: B' e" t8 d; z3 a gNominal variable, 名义变量7 u3 l. J% K, o e# q
Nonconstancy of variability, 变异的非定常性
# U% B6 y4 } X( z, |Nonlinear regression, 非线性相关
( n6 p7 n; Y; x+ A1 U! c! t, _# qNonparametric statistics, 非参数统计
( h- Y/ J8 \; Y9 w0 h$ X6 ^3 nNonparametric test, 非参数检验
2 g5 \5 D# r- D i" iNonparametric tests, 非参数检验
! D' b7 d0 F1 Q( O0 bNormal deviate, 正态离差
' I0 q2 F0 D' K3 y3 }& ]Normal distribution, 正态分布; o" u3 T; h- l. M9 @7 b+ R( L
Normal equation, 正规方程组
3 C% z$ ^& g6 NNormal ranges, 正常范围
+ N3 q2 z. s5 q, x$ `+ v* MNormal value, 正常值* l' j+ a" f d5 q5 b: V4 U
Nuisance parameter, 多余参数/讨厌参数
* [8 k6 c' a0 Q) WNull hypothesis, 无效假设 ; J7 R/ t1 ] R& U, ?2 t
Numerical variable, 数值变量
9 \1 }% m v4 W3 YObjective function, 目标函数( X0 {1 A! F2 b& n- K
Observation unit, 观察单位
$ G/ O8 u) Q0 }& IObserved value, 观察值9 O2 ?# e; g9 v3 v
One sided test, 单侧检验
, o6 l2 z! o$ E) X/ cOne-way analysis of variance, 单因素方差分析
4 s. k k' m" J- nOneway ANOVA , 单因素方差分析; O C9 R: t) K4 v& s' y; b
Open sequential trial, 开放型序贯设计
- m4 I2 [8 @+ }, h$ XOptrim, 优切尾
" M5 |: [! n6 COptrim efficiency, 优切尾效率# W1 w) d+ U2 f! D. e8 \# e8 w
Order statistics, 顺序统计量; l5 Y6 _( q- J9 K
Ordered categories, 有序分类
6 I$ _, m' F! k5 _Ordinal logistic regression , 序数逻辑斯蒂回归9 O4 h; @/ Z+ E
Ordinal variable, 有序变量
/ T* M( @. p' U2 @2 w1 q( ]- L, bOrthogonal basis, 正交基
. t! N- J2 I" K2 W* i% C) r5 M8 w$ yOrthogonal design, 正交试验设计7 T5 z1 g0 ?1 r$ T9 Q: u7 M6 |
Orthogonality conditions, 正交条件
S7 P- H2 Y* b, z& L1 @3 hORTHOPLAN, 正交设计
' u9 N& o/ }) P6 Z* t6 ]Outlier cutoffs, 离群值截断点3 \ [8 p- [$ v8 N1 _
Outliers, 极端值
3 |$ o; V3 J `# k1 c! l/ sOVERALS , 多组变量的非线性正规相关 5 W4 U# t- N" o! u1 b U5 d6 P
Overshoot, 迭代过度9 @1 C+ k6 p4 l7 |9 p
Paired design, 配对设计
3 Y, N% I( O, W" }5 PPaired sample, 配对样本
7 l* @( \6 ^3 j2 k1 r) N4 sPairwise slopes, 成对斜率7 W( i5 e& O4 v! V$ D5 t% y
Parabola, 抛物线
1 P1 C3 e2 G$ R8 B) H# q& fParallel tests, 平行试验
4 N" |2 ^% {" kParameter, 参数! @: K; c: z% i0 [8 S3 V% a
Parametric statistics, 参数统计
' b! R' z/ X- {: G7 B0 uParametric test, 参数检验
! p& @9 J! J6 R2 M. W( lPartial correlation, 偏相关
. H/ c: b. U- v# ~4 h) nPartial regression, 偏回归
% Z% b, ]8 k y7 l% d1 r$ Z2 P4 Y( CPartial sorting, 偏排序
* K7 f% Q$ d7 J, zPartials residuals, 偏残差
7 g" E; L3 u' r, e: _Pattern, 模式- A; r& ]& ? f
Pearson curves, 皮尔逊曲线' [0 y0 S$ ]3 Y9 z
Peeling, 退层- H, L* L- R4 k+ G; {3 n
Percent bar graph, 百分条形图
! @- C/ G+ @4 D& n4 A* ~, [4 D# i D! mPercentage, 百分比. E5 m8 _# D+ l9 i, r3 [
Percentile, 百分位数5 ? Q- y" ^2 a3 T8 ?/ B
Percentile curves, 百分位曲线
0 f, @4 t6 B; u, c4 YPeriodicity, 周期性
2 Q% }% Q+ A* v. @7 lPermutation, 排列' g8 s. t2 D# |0 Y' @
P-estimator, P估计量, H6 q a0 ~! I W$ w% v
Pie graph, 饼图& g( K3 j7 f6 e1 P* e
Pitman estimator, 皮特曼估计量
1 r7 C' e9 s tPivot, 枢轴量
2 s( s: I) q( \/ e& v: X' W0 U9 NPlanar, 平坦
5 P' e5 b( u3 H! j5 HPlanar assumption, 平面的假设$ {1 C! `: `/ o9 J( i: s$ z5 h
PLANCARDS, 生成试验的计划卡# H1 J, x2 G7 U5 T
Point estimation, 点估计( B& c2 o# v. ?* b
Poisson distribution, 泊松分布
( o" K* ?& y7 p% | A, tPolishing, 平滑& Q+ j( T0 j! O3 i) ^5 n
Polled standard deviation, 合并标准差7 E7 c) w1 L9 k: e+ P% Q/ d
Polled variance, 合并方差
7 d$ x! p! m1 z i: @& M1 \Polygon, 多边图2 k1 N. V0 W$ x% p
Polynomial, 多项式
8 N) R. L1 r; l! _9 pPolynomial curve, 多项式曲线
9 J3 Z( N6 ~7 i3 u/ v8 `4 E5 fPopulation, 总体
A3 i Z( L1 W$ g* u& x- mPopulation attributable risk, 人群归因危险度
4 l ^+ Z4 r- WPositive correlation, 正相关
/ s, q4 V9 q, d9 {# APositively skewed, 正偏! C6 o$ t* \. R0 L
Posterior distribution, 后验分布( e5 G4 g) O6 t# ?5 D3 w
Power of a test, 检验效能
3 \9 X2 l0 a( v! ~/ R* aPrecision, 精密度7 o6 R; H+ ?; b! n; a! j6 x) G
Predicted value, 预测值0 _$ u: W* v8 @9 g. {$ r
Preliminary analysis, 预备性分析
1 m1 a1 J' p6 A6 p0 F5 D" gPrincipal component analysis, 主成分分析
2 L& |) \* E9 N' }Prior distribution, 先验分布
% f0 `" P+ d6 }9 b( }3 L5 l1 `8 H' wPrior probability, 先验概率
6 ^0 d/ K- N% U" }8 u+ NProbabilistic model, 概率模型
M+ l! B# ?& Cprobability, 概率
- {9 y5 V0 S) [Probability density, 概率密度
+ ]3 ]$ N( V. \% l+ N# r: NProduct moment, 乘积矩/协方差
' u8 o& e# K# |/ t# ^; B2 iProfile trace, 截面迹图
2 z2 }5 q4 m2 x u( v8 dProportion, 比/构成比; F# H" |7 W4 [/ T7 T7 x& c
Proportion allocation in stratified random sampling, 按比例分层随机抽样
7 U3 P& P/ c2 b) A mProportionate, 成比例) U+ y+ f- i: f/ r8 S9 U4 o7 P' u
Proportionate sub-class numbers, 成比例次级组含量
1 {9 d) S( [, Q( q+ y1 y" sProspective study, 前瞻性调查
- [$ L% l# h4 g9 KProximities, 亲近性 5 u# f+ V# _0 X& J) Q4 f# h
Pseudo F test, 近似F检验
+ W" J, L8 L+ NPseudo model, 近似模型2 T/ q! o6 e( o6 J
Pseudosigma, 伪标准差
2 A3 v" {9 L6 [" VPurposive sampling, 有目的抽样4 Q. \& W4 G+ ~7 e; s
QR decomposition, QR分解
0 b4 G" W3 l3 j" lQuadratic approximation, 二次近似8 S d: M0 Q- |$ c8 G( d- A" z
Qualitative classification, 属性分类
& G2 |" y' p2 x v5 y+ ~& }Qualitative method, 定性方法
5 \/ G; S, B# d/ F* {Quantile-quantile plot, 分位数-分位数图/Q-Q图
+ d. U, Y% e2 o. p' p+ x3 d* tQuantitative analysis, 定量分析) b6 D9 a9 K5 o
Quartile, 四分位数
; e9 H7 y! N* \Quick Cluster, 快速聚类/ Z s1 P0 A" N4 h3 Y7 F* E3 n: l
Radix sort, 基数排序
2 x) W2 O- N9 a1 _6 E+ rRandom allocation, 随机化分组
; h. q6 A3 J& L' dRandom blocks design, 随机区组设计
& `/ C6 L1 n- G3 X# P7 T4 H0 w# v1 bRandom event, 随机事件+ h; {5 Z. m5 ?+ N$ Z( ?
Randomization, 随机化
0 G6 r* c' q+ f: l5 y5 F8 W/ I" V4 GRange, 极差/全距
% q" u2 y4 r$ I4 LRank correlation, 等级相关' V3 N7 W, J1 ^, V2 K* d. t
Rank sum test, 秩和检验( x R5 ~0 Y6 ?4 u( s* R7 ~
Rank test, 秩检验, d/ v# L6 }& g/ u
Ranked data, 等级资料
3 Y% A0 t/ |" c" BRate, 比率
( ~( P& i$ c7 {Ratio, 比例
/ s3 ], N9 s% s! L& ~Raw data, 原始资料8 C" i/ E. ~! D( I
Raw residual, 原始残差
3 e' D, m+ E& U9 n# u3 W+ BRayleigh's test, 雷氏检验
7 ?5 @& E* q" k( J' B/ |& fRayleigh's Z, 雷氏Z值 # z+ y! S- ?: T+ e A
Reciprocal, 倒数; y& {' h1 Q0 x6 v. _
Reciprocal transformation, 倒数变换3 _! ~: j* C: D8 Q
Recording, 记录
5 A& h& l; X) K. aRedescending estimators, 回降估计量# `/ F9 j6 l0 q1 {6 @" b) g# n. D
Reducing dimensions, 降维
* c" a) c$ J$ n9 R2 B8 M- pRe-expression, 重新表达9 `0 k: y! Z' M5 K* w* s
Reference set, 标准组1 Y5 C9 ^1 `3 |2 I1 R8 L7 H* {
Region of acceptance, 接受域% V0 x: |- q# J( U; N/ C
Regression coefficient, 回归系数
% [' D3 g1 U( m f; _6 GRegression sum of square, 回归平方和/ t0 a5 e6 o7 q% x
Rejection point, 拒绝点+ @ M$ U2 u) }8 K" k3 W
Relative dispersion, 相对离散度) `' ]% |; A% M- V5 ] c9 E
Relative number, 相对数
, m8 y2 d- Q2 ]5 P+ V" }$ L% h8 FReliability, 可靠性( ~ @8 C8 k( q( w3 d) f+ J) C$ {
Reparametrization, 重新设置参数- m/ B, e, T! m9 t$ J: c2 P5 i
Replication, 重复 Z8 Y8 m; J8 C; u
Report Summaries, 报告摘要+ J6 C9 y* v: a5 T/ y
Residual sum of square, 剩余平方和$ W5 B& |& t. P8 f9 P5 F
Resistance, 耐抗性 N5 T- t% ]7 x- D! U7 t
Resistant line, 耐抗线
4 K( f. I# P' n: y) x# b7 bResistant technique, 耐抗技术
; E# J& Q* J. A8 M# u" qR-estimator of location, 位置R估计量% w1 A0 c1 a1 Q" }0 h3 g' k
R-estimator of scale, 尺度R估计量
- q4 n" `1 F4 R# fRetrospective study, 回顾性调查
4 _. |: p0 {0 }: }( J6 hRidge trace, 岭迹$ K6 b U' w" R
Ridit analysis, Ridit分析' z+ b! T9 P$ Y
Rotation, 旋转+ }" C) N: z' J6 O4 o+ v
Rounding, 舍入
- F! {' k. F. o8 a. WRow, 行
+ v, X! {( x- { y# @' HRow effects, 行效应
' P! ]+ j& y7 L5 t9 u C& URow factor, 行因素, D2 t- M* S, q" f$ I- |
RXC table, RXC表. n b) x7 t/ W5 O, k
Sample, 样本6 @& a2 [! Z$ o7 d
Sample regression coefficient, 样本回归系数' o) u$ \! o$ ^, w! g5 u8 o' M
Sample size, 样本量7 k6 X6 t6 M3 f& l, T& q9 A8 T
Sample standard deviation, 样本标准差3 r0 E$ _. a7 _8 _: ?
Sampling error, 抽样误差
2 v1 D. D# b: ZSAS(Statistical analysis system ), SAS统计软件包
?' H# D7 k0 uScale, 尺度/量表* b* o: s D4 X3 r3 ~0 U5 R
Scatter diagram, 散点图
' e( Q) p7 M' Q1 Q0 WSchematic plot, 示意图/简图
; f1 ~+ d6 ?; c& j6 ^: gScore test, 计分检验
0 u+ |8 C* f; b# x7 h/ kScreening, 筛检, }$ `5 o/ o; }8 X" _
SEASON, 季节分析 9 f. x8 H, y" s' g( Y, f
Second derivative, 二阶导数: P( f# \9 \1 K+ D5 d: a9 V0 }0 w
Second principal component, 第二主成分. L7 L" { G3 n/ I. a2 z
SEM (Structural equation modeling), 结构化方程模型
/ ^) b& G, @/ P [* e0 ZSemi-logarithmic graph, 半对数图
+ l2 E9 [1 p2 d. ?6 i hSemi-logarithmic paper, 半对数格纸
: q) O5 N+ p+ c. Q* Y( sSensitivity curve, 敏感度曲线5 l6 R7 }6 N8 }4 G4 _' q2 D1 b! i
Sequential analysis, 贯序分析
% _8 Z: l' l: @Sequential data set, 顺序数据集
/ _$ Z+ F0 e! e- d. `Sequential design, 贯序设计
7 ?: g7 v/ T% R% v. VSequential method, 贯序法0 D8 L9 i8 o5 {
Sequential test, 贯序检验法
5 o0 K+ V; I+ a& iSerial tests, 系列试验
7 [; d( h& y3 HShort-cut method, 简捷法
& z& o/ m" A% jSigmoid curve, S形曲线
; c1 i! f1 K2 R; M1 s, pSign function, 正负号函数% F0 W& M! X9 N# X
Sign test, 符号检验
* F) l/ u! j S: ^+ L# R8 h( dSigned rank, 符号秩
. U7 u4 @( a7 Y8 A6 S/ b) ?9 VSignificance test, 显著性检验, g$ S/ y2 c$ _% Z) {4 I7 p" g. c
Significant figure, 有效数字$ n+ a" g$ W6 I/ i% o9 z
Simple cluster sampling, 简单整群抽样0 X& }9 s( c* D* C9 N
Simple correlation, 简单相关
7 n# z. ^9 F/ OSimple random sampling, 简单随机抽样8 T, F8 G0 f+ S
Simple regression, 简单回归
2 U: J" E+ }& x4 Z& Psimple table, 简单表
) r, r8 c$ ?8 k3 ~Sine estimator, 正弦估计量
* |6 ]7 E6 S* |( Q6 I* I( ^- I; w& uSingle-valued estimate, 单值估计% n) h( v/ ^& j$ |3 q C
Singular matrix, 奇异矩阵
) q! D2 D+ U1 V, b" ]Skewed distribution, 偏斜分布' J6 v8 p0 U5 e$ g8 _
Skewness, 偏度
3 Z! y0 g( C" E1 V9 i bSlash distribution, 斜线分布. V3 G" _' w* D; s3 Y9 u& i- I: j& w
Slope, 斜率6 }) u( V8 \* `0 J: P
Smirnov test, 斯米尔诺夫检验
2 Z' \; z! I& ^9 g+ [Source of variation, 变异来源
0 T9 S2 g/ B) A) j6 t8 F6 }Spearman rank correlation, 斯皮尔曼等级相关' c3 v9 O( Z; q
Specific factor, 特殊因子. K5 A+ |! J& M ]- ?
Specific factor variance, 特殊因子方差6 v& v& G# v' A3 O
Spectra , 频谱
! b3 U0 F' M1 ]6 _; o' ]Spherical distribution, 球型正态分布; E7 n& U2 ^2 ~6 a5 O7 h% y
Spread, 展布( u' I" s1 [" q6 @* ~: n7 V
SPSS(Statistical package for the social science), SPSS统计软件包
9 {/ Y0 U$ g& E- K1 {; wSpurious correlation, 假性相关
1 a* w! C& F8 m J; [& ^Square root transformation, 平方根变换; i% C O5 M' [* w
Stabilizing variance, 稳定方差
' G' H7 I3 U: R, G: fStandard deviation, 标准差
, C$ ]$ D- ^( EStandard error, 标准误5 j6 @2 n0 V. ~
Standard error of difference, 差别的标准误
( z8 I2 E6 F8 T- e* u; I) L+ iStandard error of estimate, 标准估计误差
- Y, f1 O% G c8 y6 C% j9 t: lStandard error of rate, 率的标准误
. h; \; A9 O e: j0 y! F3 n% A& ?Standard normal distribution, 标准正态分布+ I& \7 @# n# W" E) b: ~
Standardization, 标准化
# v7 B, V+ \ jStarting value, 起始值- q: c, j/ W8 A: y& U/ M
Statistic, 统计量+ G1 t* B& G3 Z+ p) r( @
Statistical control, 统计控制
) {8 M- ` [& j' Z9 mStatistical graph, 统计图& E/ p+ c* E) g4 D+ w6 S3 u
Statistical inference, 统计推断8 S( P# R) Z9 x0 I6 ?+ Z
Statistical table, 统计表9 t3 I' a1 r1 V9 m
Steepest descent, 最速下降法& G1 _: `5 W$ |
Stem and leaf display, 茎叶图% L& W {. h' q4 S! w/ E
Step factor, 步长因子
/ V7 y/ A; p8 A7 YStepwise regression, 逐步回归/ Q7 L+ s+ k: C$ q9 A( L' }, m
Storage, 存: S' i8 I, i' R# B+ s
Strata, 层（复数）4 ^% {& b9 ~* D) f# @* u. A
Stratified sampling, 分层抽样
, _/ P! x* \6 k5 hStratified sampling, 分层抽样
' K% T3 n; p$ D; C. G2 cStrength, 强度. |& ^2 i+ e" X4 h* s- a; M3 B- M
Stringency, 严密性2 l" p* K6 s$ U& ^0 w
Structural relationship, 结构关系, y7 ^" J g0 t6 M7 [9 f
Studentized residual, 学生化残差/t化残差2 f5 A! ~ C, x, g& o
Sub-class numbers, 次级组含量
) r* n3 t" W/ SSubdividing, 分割
) ]$ X0 s7 p/ a6 F' Z7 JSufficient statistic, 充分统计量: O5 S8 D3 ?4 T6 R
Sum of products, 积和
, R9 ~( ~* @0 S. g# P3 XSum of squares, 离差平方和
2 r* D$ t$ m4 I3 z* WSum of squares about regression, 回归平方和
$ \$ z! W8 `4 XSum of squares between groups, 组间平方和) n; W: @! b2 s4 g4 `& l
Sum of squares of partial regression, 偏回归平方和
" r& b* C: _& c1 ?( N! QSure event, 必然事件0 u- p7 i: J/ \& c
Survey, 调查
/ _) p. p/ { @; B4 lSurvival, 生存分析) J+ V- Z! ^5 T# E' G# x
Survival rate, 生存率
& i& e. c) V* f. FSuspended root gram, 悬吊根图+ a$ v& A4 B* n
Symmetry, 对称
5 I; c4 g# T$ [9 R8 T) ISystematic error, 系统误差# U. g3 A, u7 P0 X9 Q: D
Systematic sampling, 系统抽样" E- Q. O0 a. I: n4 k4 Z
Tags, 标签
. C4 t; K5 T) R6 X+ q: g% P" V+ YTail area, 尾部面积/ T+ x( r: a: _0 g0 r5 B
Tail length, 尾长
: h- Y, |" R1 i& ITail weight, 尾重
2 q) G! \! V+ W. a' DTangent line, 切线$ }, N" t* J H( Q2 w8 J f
Target distribution, 目标分布) L1 J6 |; T1 a# ^/ ]: K9 E
Taylor series, 泰勒级数* Y, k; p% {0 p; g& M* Y
Tendency of dispersion, 离散趋势
- s! q" d$ Q! e' S. b6 X; gTesting of hypotheses, 假设检验
: w* Z' \) q; a$ T) \$ c9 z/ C) CTheoretical frequency, 理论频数
5 R# \# v# J, ^1 r+ gTime series, 时间序列
+ e9 [* M2 h1 M O1 `* A! v* ?Tolerance interval, 容忍区间- W$ \6 W6 Z; y/ N/ X$ E0 L7 \1 Z
Tolerance lower limit, 容忍下限$ A6 X0 R; o- {3 Q0 S' C
Tolerance upper limit, 容忍上限
+ y% [7 j3 C) d$ M8 P$ BTorsion, 扰率
+ z5 L v1 v7 u0 W: ?6 ITotal sum of square, 总平方和4 Z- A$ G/ @0 d' G6 h8 g5 i+ y
Total variation, 总变异
- w( S. E+ g$ x( t. N2 @$ pTransformation, 转换
2 g" v5 U6 Y7 q% r, l* sTreatment, 处理
3 v) n+ \4 p/ N; s+ E. ATrend, 趋势
' b- v( I% W( N* `" n4 u8 I, @& S7 ~Trend of percentage, 百分比趋势) w. L+ s' M8 {2 S8 C
Trial, 试验* U: _. P. P6 M' l- R
Trial and error method, 试错法3 T7 v' Q/ p- K9 X! m* |
Tuning constant, 细调常数! u6 Y: y1 y7 `/ P
Two sided test, 双向检验
6 s w( E. Q, CTwo-stage least squares, 二阶最小平方8 P4 ~. a$ i/ n' u- I' k5 C% p
Two-stage sampling, 二阶段抽样9 w* |, j4 o) ~* F% Y* U8 s( j
Two-tailed test, 双侧检验: w+ m- u s y# R6 ~
Two-way analysis of variance, 双因素方差分析3 h' W! d i0 g. ~2 `
Two-way table, 双向表
6 j* ~4 h$ `5 c, A1 E. ZType I error, 一类错误/α错误 H$ H m! {, c/ \1 n
Type II error, 二类错误/β错误; p; I: I$ F6 ~. J6 i& S
UMVU, 方差一致最小无偏估计简称$ v2 [0 w# U9 W) K4 S; u) z2 ]
Unbiased estimate, 无偏估计1 K* D' f) O, n5 Y$ b* ?
Unconstrained nonlinear regression , 无约束非线性回归
6 l) Q9 H- X6 _$ G" E3 KUnequal subclass number, 不等次级组含量
5 E8 Y- y3 ]: _' L( u6 y. vUngrouped data, 不分组资料" \ O4 r9 L4 l6 [
Uniform coordinate, 均匀坐标
% [8 C) Y( L0 P. N J) k9 [2 ?* F. wUniform distribution, 均匀分布
6 @2 d4 c/ r, a" U `' J$ O0 E# jUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
- ^' O& o) y! i1 r6 KUnit, 单元& E3 W6 u0 H6 m/ D
Unordered categories, 无序分类
) m6 U2 M4 J# z! W' |) XUpper limit, 上限5 L+ V+ S0 z. k% H! K
Upward rank, 升秩
0 a4 M1 F, q4 C: s( ~4 w& E z" dVague concept, 模糊概念
' k( `9 ]. i1 x* Q4 K* tValidity, 有效性
- w! y8 g1 L- S9 TVARCOMP (Variance component estimation), 方差元素估计
' J9 Q# d, W, d2 x6 oVariability, 变异性/ q' y% A) ^% h e
Variable, 变量
% x+ Q- N7 \" sVariance, 方差3 D1 N+ L+ [! ]" L8 B# w# z% W' d t
Variation, 变异7 H! E, \$ g6 {9 F( P/ x9 k6 K
Varimax orthogonal rotation, 方差最大正交旋转
7 t6 F. T; _! D- ?( D1 \2 a8 a# JVolume of distribution, 容积
G, e. i0 U& @% f0 |( t# NW test, W检验5 L$ F5 Z' ` O
Weibull distribution, 威布尔分布
F9 N5 d. \; D0 V( {- cWeight, 权数
2 }7 G* y; e; i1 t( M% ?- lWeighted Chi-square test, 加权卡方检验/Cochran检验, v j- ~! M" X3 X6 g7 Y- j6 T
Weighted linear regression method, 加权直线回归
0 q- y3 ^+ o# s! F; N+ \+ AWeighted mean, 加权平均数# u% S0 E; P' G- T$ S, t
Weighted mean square, 加权平均方差
. l3 H' T* l2 bWeighted sum of square, 加权平方和# b7 g6 P# i5 z5 Q; \4 s, [
Weighting coefficient, 权重系数
9 N r# {7 X! A2 Z$ sWeighting method, 加权法 2 X% ` `( G" n2 z( \ ]
W-estimation, W估计量0 Y- R2 p( n3 `* d" i8 K# J ?) U* x
W-estimation of location, 位置W估计量
{% }* K" M2 u/ W0 mWidth, 宽度
( B. e) K) G& b4 _7 ~ ]Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
* J+ [& ], R( T1 sWild point, 野点/狂点+ |- y" q" E) T" `! p4 s" c
Wild value, 野值/狂值
# i+ h% z: _4 @; [8 J z6 kWinsorized mean, 缩尾均值
5 O: a7 I' a% [: w$ oWithdraw, 失访
4 E& t, |, g9 D+ ]: GYouden's index, 尤登指数
! ]/ i# @: q1 X, _" T$ VZ test, Z检验
- p6 k5 y3 q; v E! O' z0 EZero correlation, 零相关
7 D# |, b [; AZ-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
