|
|
Absolute deviation, 绝对离差
5 m, Y! ~1 I4 K' _0 E1 L: |Absolute number, 绝对数
: }1 S2 b1 q9 i4 L4 \( ]5 Q- T% d4 bAbsolute residuals, 绝对残差
& z" a9 M# }. D7 G* YAcceleration array, 加速度立体阵5 E p# W3 U$ B" _+ |7 w* i
Acceleration in an arbitrary direction, 任意方向上的加速度" B, L m2 ~5 Y) F
Acceleration normal, 法向加速度
0 v5 v& B, S6 k6 B9 T$ c0 iAcceleration space dimension, 加速度空间的维数; j0 T% B( |: t1 @+ n/ e& }
Acceleration tangential, 切向加速度4 H/ `; j# \3 E# q1 M# t, i
Acceleration vector, 加速度向量
7 ] ~9 Z) V8 Y& j' ?. X- tAcceptable hypothesis, 可接受假设
. K/ \9 C9 O: k0 K) [* g( BAccumulation, 累积! W/ _6 h P+ \5 P+ H' r$ s, a' q
Accuracy, 准确度
1 } i1 q3 U1 ?0 @5 PActual frequency, 实际频数
$ b" r4 N" j# X+ q) s0 IAdaptive estimator, 自适应估计量, r+ c' a5 U/ A) D9 x6 L6 `; o
Addition, 相加
0 ~9 s' N! Y7 g5 L) LAddition theorem, 加法定理
- W, w/ J* `4 F3 bAdditivity, 可加性8 e3 j0 ~" J d% h' `: @
Adjusted rate, 调整率) C2 K) }2 c: @! H3 y1 E
Adjusted value, 校正值) m: T/ x5 `. n* M. Z2 _: ~
Admissible error, 容许误差+ X: c) l9 d, e; K: \
Aggregation, 聚集性
9 C+ O$ _9 c2 o6 y) p9 S; MAlternative hypothesis, 备择假设 h4 e5 I, _! I* s
Among groups, 组间* `5 q3 ?7 F: Y$ p3 ?* V$ X# r; y+ v
Amounts, 总量
1 g5 C; Z; u& c; W7 u% D+ z, ^Analysis of correlation, 相关分析. e2 w6 c) Y8 M" l5 l+ W; {
Analysis of covariance, 协方差分析' e4 h4 {8 s0 V( K: W
Analysis of regression, 回归分析
. T9 T/ q! g$ g# |1 [ CAnalysis of time series, 时间序列分析
8 a5 x; u4 j1 l% d2 y3 zAnalysis of variance, 方差分析' w' h+ t1 t" g. w) N/ U$ G
Angular transformation, 角转换
, Q% s8 ]( I0 D, J. }# ^" zANOVA （analysis of variance）, 方差分析
1 \. X8 O" f/ f G# M# b4 qANOVA Models, 方差分析模型
9 \8 }, K$ T1 w) {Arcing, 弧/弧旋1 | I9 T: k+ N) R/ x) Z2 }- k
Arcsine transformation, 反正弦变换
0 H( W z+ M- a+ d% r6 B8 UArea under the curve, 曲线面积7 b8 d' f' O7 {* M
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 3 R" _$ Z6 @2 L* t3 |# e
ARIMA, 季节和非季节性单变量模型的极大似然估计
" b7 ], r1 E% G o& BArithmetic grid paper, 算术格纸; ]' z& D& i# E, C2 K e( Q
Arithmetic mean, 算术平均数
& G: A! r$ m% U) z2 d, I: MArrhenius relation, 艾恩尼斯关系2 G {% d3 x. N8 ]8 c: s3 Y# I( N! s
Assessing fit, 拟合的评估/ x1 \ b' t0 m) w7 D
Associative laws, 结合律
" g0 K3 m3 M$ [0 J6 X) {/ dAsymmetric distribution, 非对称分布4 x1 e* B5 S: b) z) f4 X3 l$ E+ O
Asymptotic bias, 渐近偏倚% Z d8 P4 w, R5 X7 F7 E
Asymptotic efficiency, 渐近效率
7 Q. j4 `" {# }, ?: W% kAsymptotic variance, 渐近方差4 u( Q2 A9 N; F! ^4 m
Attributable risk, 归因危险度
* U$ N$ j) U9 f" U& QAttribute data, 属性资料
( R5 P2 F- S8 F$ H& ~Attribution, 属性
$ ^% x+ Q6 P9 `* h; QAutocorrelation, 自相关
9 B0 s8 z+ B$ _8 |. A8 _" F/ F; YAutocorrelation of residuals, 残差的自相关
+ S1 B/ C' ]- \, F+ W9 FAverage, 平均数
9 v: L( l. y7 tAverage confidence interval length, 平均置信区间长度
3 r0 V0 o& J5 ]5 { ]: {% s( dAverage growth rate, 平均增长率( i) U# f8 v; T) b
Bar chart, 条形图, r" g1 M6 G: i' M
Bar graph, 条形图% k$ h& w$ [- c/ @- v
Base period, 基期
* M! X3 ?( i' g v8 sBayes' theorem , Bayes定理1 ^! p8 v, W& `
Bell-shaped curve, 钟形曲线
+ j: ]8 B( S5 R0 @/ q4 B4 uBernoulli distribution, 伯努力分布' ^% h* [8 b4 N; m- V: h- U2 s
Best-trim estimator, 最好切尾估计量
3 p: k P" o$ v# W. Q* ?8 EBias, 偏性9 Q$ M7 d4 B- o) M
Binary logistic regression, 二元逻辑斯蒂回归
7 U7 x1 o" o( m! D( v) q& l3 EBinomial distribution, 二项分布 U9 B) n& D% V) ~/ l
Bisquare, 双平方
8 ~& ^1 |/ z8 P/ P8 F5 YBivariate Correlate, 二变量相关" s- ?( T: ^5 k7 W) T
Bivariate normal distribution, 双变量正态分布: L+ G5 A2 o5 r' Z
Bivariate normal population, 双变量正态总体
7 s5 j& a6 Z1 \2 q! Z) f6 VBiweight interval, 双权区间/ G! A, O! c7 a5 `9 C- @
Biweight M-estimator, 双权M估计量
! o; L ~ h, N& N8 yBlock, 区组/配伍组
0 Z, u* s% x. }; e' e9 g* |BMDP(Biomedical computer programs), BMDP统计软件包
( y' n6 H `2 e0 ]2 q; G1 zBoxplots, 箱线图/箱尾图
; s; H q0 u- d* `" \Breakdown bound, 崩溃界/崩溃点" }" h# {: n0 D$ P
Canonical correlation, 典型相关# K* S. c* p( w; ?
Caption, 纵标目4 c7 m6 f2 V$ ]7 b! _
Case-control study, 病例对照研究
* q8 Z% c. ]. u" H8 ~" f( bCategorical variable, 分类变量
0 {& Y, m( v: C& m& K# g( zCatenary, 悬链线& s& M& ?/ t7 o: k0 T; |
Cauchy distribution, 柯西分布
. t! P% z% [7 e; yCause-and-effect relationship, 因果关系
$ w4 o& I" ~7 T. C: l [Cell, 单元3 f5 h& v5 Z" l% b
Censoring, 终检
) ]1 A( ] Q: ?8 q* P/ _Center of symmetry, 对称中心
* ?8 R0 ^3 }5 g# m& j6 E: ?Centering and scaling, 中心化和定标
' c; i# H4 ~) E3 Y% r0 G0 eCentral tendency, 集中趋势 n# c1 j- r7 u- b" S4 i
Central value, 中心值+ \ f; P% d; D0 d% J. F
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测4 D5 c% {# j' ~
Chance, 机遇
; p1 s M) Q' o+ WChance error, 随机误差
, b4 m8 g; @0 F. @3 J* R9 n* P0 i7 yChance variable, 随机变量* c9 ~7 z& k! Y/ O
Characteristic equation, 特征方程- r8 X# \+ w* T- v6 e: C4 l
Characteristic root, 特征根4 S4 p1 ~, D- ^
Characteristic vector, 特征向量
' [6 ?% v8 i0 \8 [$ C5 m4 v6 q5 YChebshev criterion of fit, 拟合的切比雪夫准则
. x; r Q; j3 X: G0 WChernoff faces, 切尔诺夫脸谱图
, N; u$ \# H5 G' E6 w! hChi-square test, 卡方检验/χ2检验
5 f& R. C' j) M' y3 x1 z6 b$ LCholeskey decomposition, 乔洛斯基分解
3 `4 Z! I! d" G3 A& U# oCircle chart, 圆图
, o/ B. e8 ^5 \- X3 r7 L1 _+ r$ j+ \: {Class interval, 组距$ n5 @. e; u7 r6 A2 F
Class mid-value, 组中值
2 |: h* e1 y- [% ]+ e+ xClass upper limit, 组上限* u: e5 ], b- {8 o
Classified variable, 分类变量 v& Z/ ~0 H) M) Z0 W# b% O* z
Cluster analysis, 聚类分析+ K! m6 j( m' y9 w3 L
Cluster sampling, 整群抽样8 X" O" I, B+ y
Code, 代码5 T: o# W$ E! {' M0 A" z
Coded data, 编码数据
( O9 ~" l* f! G/ L. vCoding, 编码
5 V" F9 X# R5 ?% r' b/ OCoefficient of contingency, 列联系数
) n" o* S! c! g4 O5 tCoefficient of determination, 决定系数
$ \! h+ V) C Y! {Coefficient of multiple correlation, 多重相关系数
+ |: ~0 Q- ^7 s/ M2 j% o. [) hCoefficient of partial correlation, 偏相关系数8 h! L7 g# z ~: A K
Coefficient of production-moment correlation, 积差相关系数
5 j& @% M3 Z$ a1 d7 Z! F mCoefficient of rank correlation, 等级相关系数( i0 X w0 i2 o k* G
Coefficient of regression, 回归系数
. ]$ ]+ M# G( }3 R$ [Coefficient of skewness, 偏度系数
9 P, V: z9 y; ]$ \% D2 N# G5 }2 I9 SCoefficient of variation, 变异系数
6 v8 S: A" G' L: |% Q4 {Cohort study, 队列研究! v- h2 @5 S* A6 l" [( B
Column, 列. I! @4 q) v0 ]2 Y
Column effect, 列效应
; G4 \1 n; ?+ ?+ S GColumn factor, 列因素- T1 b% u& @9 }
Combination pool, 合并" L2 t- [$ c( O2 H
Combinative table, 组合表
* h$ Z0 ~4 v1 G; x! A% HCommon factor, 共性因子8 [# J" h& c9 R. ^: A2 [
Common regression coefficient, 公共回归系数, }) {8 n, ?4 G+ E3 b5 G' E8 g
Common value, 共同值9 K1 v4 _& t& B+ s* q& ^
Common variance, 公共方差
% _6 K( W# _+ e) }Common variation, 公共变异6 v9 l* g8 z+ I9 L
Communality variance, 共性方差1 |' |2 t9 W5 w }5 z/ _
Comparability, 可比性
$ O8 ~- H* f$ [0 t; L# y4 @Comparison of bathes, 批比较9 Q* }, L3 y+ s' R" h* s9 n% {
Comparison value, 比较值
$ c& E. k$ N& G: jCompartment model, 分部模型
5 ?' R' u7 }2 ^0 _Compassion, 伸缩6 `' i: @4 n8 Y! s
Complement of an event, 补事件: X( k! g, L+ N) Z4 r1 ^. g
Complete association, 完全正相关, U3 n) [ @" R4 [( ~
Complete dissociation, 完全不相关1 V( U6 G5 H* v# ?" A
Complete statistics, 完备统计量( d* Q$ a/ l+ C
Completely randomized design, 完全随机化设计2 ]; o- l9 p% u% @3 r# w
Composite event, 联合事件
* m/ k7 |# ~$ |) f" m6 HComposite events, 复合事件5 T6 ]- `/ M; S7 H6 h9 Y9 N7 P
Concavity, 凹性- @" C& U7 G Y$ H$ h1 `) G9 Y) y
Conditional expectation, 条件期望' o( x) J8 @# O$ f- n- s
Conditional likelihood, 条件似然
. U/ l7 a9 Y: y tConditional probability, 条件概率, V. U5 R/ {+ E3 T
Conditionally linear, 依条件线性% ^) i8 J! |. W) s( h' [
Confidence interval, 置信区间
/ e. y) M; U( _" S( j# eConfidence limit, 置信限' U6 m! w5 V. t
Confidence lower limit, 置信下限 K' F! F# {1 d
Confidence upper limit, 置信上限
& W+ v2 @4 O* ^Confirmatory Factor Analysis , 验证性因子分析& M% O5 S1 W0 e5 V. w
Confirmatory research, 证实性实验研究+ W; X0 C# x+ i S2 K4 Q
Confounding factor, 混杂因素
9 a4 V3 v2 b- TConjoint, 联合分析2 b1 M( k9 N0 C9 o/ a l
Consistency, 相合性8 q( C# M- @2 X. X) |
Consistency check, 一致性检验4 x8 r- d/ R- z8 |
Consistent asymptotically normal estimate, 相合渐近正态估计
. `0 z5 g8 B7 W7 u" B8 tConsistent estimate, 相合估计
8 N/ X ]. ?6 Y. ^, n1 g. PConstrained nonlinear regression, 受约束非线性回归2 m" Z, ~3 d9 W6 a" |& I5 |
Constraint, 约束: N2 x6 o$ a& |& O2 ?; V+ s
Contaminated distribution, 污染分布
1 Q! T" d$ D' D t0 SContaminated Gausssian, 污染高斯分布
! Y* L' {* `; y, yContaminated normal distribution, 污染正态分布
4 L- o* D4 ]9 j) p4 X* C: XContamination, 污染, S/ y1 @# o; C- e& p! X
Contamination model, 污染模型4 {: V+ o- C h5 h. p
Contingency table, 列联表2 Z f& ?4 e" [; s0 \% ?9 Z0 X+ ~
Contour, 边界线, x3 h* n! Y* D
Contribution rate, 贡献率2 @; P8 H2 ]. n# B! k
Control, 对照7 H8 I; D$ U. Z
Controlled experiments, 对照实验
3 F) Z! r0 C4 l' ?) q% N7 MConventional depth, 常规深度
' @1 S! l0 f8 V* pConvolution, 卷积
; _% f/ s1 T# g% H7 l8 i2 `5 LCorrected factor, 校正因子! B1 Z- g6 |" K+ N, z1 \8 t. B! y
Corrected mean, 校正均值
/ |" v2 k' Z q! V1 ~Correction coefficient, 校正系数
" Y. f2 |1 E- _6 u* d$ mCorrectness, 正确性
% G* a/ J" }3 }+ I/ D9 ZCorrelation coefficient, 相关系数
8 h1 v! r9 U, a( ]Correlation index, 相关指数
3 `6 \4 ] J% v2 {Correspondence, 对应
& B5 Q+ i0 p+ [Counting, 计数
& b7 U& W x/ L# JCounts, 计数/频数/ @% I# J/ y" x& v/ z
Covariance, 协方差
" M6 L# Z0 k' r9 q J" a# K# lCovariant, 共变 3 L! M7 o; S. p- Q+ |
Cox Regression, Cox回归
$ G+ F+ v5 L5 ^7 mCriteria for fitting, 拟合准则1 t+ y9 u) B" F" R! v, b
Criteria of least squares, 最小二乘准则
" } n1 q$ t6 mCritical ratio, 临界比
o. |0 A: T4 f' u. c" m$ iCritical region, 拒绝域7 x8 \' g% c4 w9 }: O! E( N7 |
Critical value, 临界值8 \3 M1 [9 R- b/ \0 b# _
Cross-over design, 交叉设计
# R8 e9 z6 }4 \ `% r) WCross-section analysis, 横断面分析" a6 m9 `7 \) W! H+ D2 l
Cross-section survey, 横断面调查
) y/ _' _* ^5 K0 [0 [Crosstabs , 交叉表 ; P7 n- d# b% ^
Cross-tabulation table, 复合表$ |# s: X, i4 A
Cube root, 立方根
- Q% C- X O: N) O3 L& I- ^Cumulative distribution function, 分布函数/ n8 I! Y5 u1 J5 J
Cumulative probability, 累计概率$ v, O. L. T+ m: a* M- R0 E+ W7 X% K! ^
Curvature, 曲率/弯曲
% N! p+ M2 p9 N9 FCurvature, 曲率
Z9 [: `. [9 ZCurve fit , 曲线拟和 4 K0 i* M! ~/ P+ ~4 S* X
Curve fitting, 曲线拟合
5 Y2 U a, ~# N9 d: e" L) e8 XCurvilinear regression, 曲线回归, Z1 z9 Q; }8 p' W" b* [7 m! o% t
Curvilinear relation, 曲线关系: @/ X7 X" ~* }- v
Cut-and-try method, 尝试法" ]% ? g6 U1 d+ s" c+ Q4 G* A( b* C
Cycle, 周期; A. b! Z+ z& r" J* T f D* c/ P
Cyclist, 周期性
6 f$ E; j+ x" G* P$ t% s( oD test, D检验
9 W/ f4 u/ o7 r, _/ Z1 X+ T* o0 ?Data acquisition, 资料收集# O6 N7 c% W5 X7 U/ N7 k
Data bank, 数据库2 P H- t. Q6 m4 H: n2 r! y$ k
Data capacity, 数据容量
. f9 R' `8 N3 u, jData deficiencies, 数据缺乏
+ F" ?0 h+ s9 ?: C' w2 k# V% EData handling, 数据处理
) C+ B* |! a- v# |1 e9 vData manipulation, 数据处理
, Y- i; V3 }% [4 L4 RData processing, 数据处理
/ m* p- N: T- d4 k" v `7 U1 aData reduction, 数据缩减) ]* Z6 [# N9 f$ d; m% U4 `8 Q
Data set, 数据集
9 S! J* b- o& j4 ^2 wData sources, 数据来源- _4 t; k; X1 d0 ]. j X. I
Data transformation, 数据变换
, ~0 G( X# m& ?0 D, |: AData validity, 数据有效性
/ ~9 S& N& ^: e# Q7 k. dData-in, 数据输入
; H2 o. r- W% L' v1 @Data-out, 数据输出; ?) u2 _% ]% ?. _' X
Dead time, 停滞期3 {$ ?6 T' I: O! U$ @8 d. B
Degree of freedom, 自由度
/ i" n& e8 m9 s% q, uDegree of precision, 精密度' `% K8 d D# J' r( ]
Degree of reliability, 可靠性程度; K0 U9 J4 w1 e
Degression, 递减9 o" o. Y' A T8 X2 A C9 v
Density function, 密度函数6 @/ \* I3 z2 `1 I
Density of data points, 数据点的密度' M _+ {! u% t9 B' W! o' e
Dependent variable, 应变量/依变量/因变量( s& N$ e5 U ?5 U; m
Dependent variable, 因变量
9 q) {- h! H9 V! Y6 Q8 D; TDepth, 深度2 h" i5 E/ U# b1 \
Derivative matrix, 导数矩阵5 z9 p; {$ r' v% c$ v5 L" `
Derivative-free methods, 无导数方法+ f7 g0 [7 D1 z6 ]& Z |( C, b0 ?: L
Design, 设计/ z2 a0 {+ d. B( x
Determinacy, 确定性
8 e/ @# ~. g* v6 ]Determinant, 行列式; c) P5 r1 Q" @( R3 I
Determinant, 决定因素
) G' g8 \& S7 vDeviation, 离差6 s7 I6 p; k$ m" w, H* o$ c: O; n
Deviation from average, 离均差
. D( \/ f6 w4 a7 p$ q' FDiagnostic plot, 诊断图- Q* h( }, f2 [" C5 P
Dichotomous variable, 二分变量' F- l# U+ P0 T' p
Differential equation, 微分方程% q; S% d# i1 y% C4 A, Q7 w
Direct standardization, 直接标准化法4 }7 s& a+ K! O2 C1 M7 Y3 }3 n! S
Discrete variable, 离散型变量
, S4 k) ?! e% c8 DDISCRIMINANT, 判断
" k+ W: I7 g1 T' K vDiscriminant analysis, 判别分析' |# {' I# x3 R5 ?0 g. z
Discriminant coefficient, 判别系数
" k% Q P; C& w8 ~' o* g QDiscriminant function, 判别值% _/ n+ @2 k2 J
Dispersion, 散布/分散度. N. A8 W! Q2 |7 g2 I. }+ [
Disproportional, 不成比例的
8 R. B! q' o. I4 u8 a# ODisproportionate sub-class numbers, 不成比例次级组含量
0 r3 B% L' o1 n* w/ o' Q7 XDistribution free, 分布无关性/免分布3 x1 b+ s1 s( Q" y- t
Distribution shape, 分布形状
% [5 I# N! G! g; o% ~/ }Distribution-free method, 任意分布法* w+ T: O) F; A
Distributive laws, 分配律! L5 U5 @$ s# W+ Q9 G
Disturbance, 随机扰动项+ [" b$ \1 W R2 ^
Dose response curve, 剂量反应曲线
& h8 d% T, ^$ M- W2 m7 uDouble blind method, 双盲法1 c; M, J8 j+ k; v4 j
Double blind trial, 双盲试验
0 J9 D/ [4 E/ ^5 q ?0 i* s1 dDouble exponential distribution, 双指数分布
3 R+ L! x9 y2 x; Y( Z& VDouble logarithmic, 双对数
* g4 D' ^4 u. C: E- ?7 H: LDownward rank, 降秩# b' K& T# f6 k5 q* y! i# U
Dual-space plot, 对偶空间图) B8 J1 j. s4 Q+ e
DUD, 无导数方法8 K+ r$ U$ \& ]; c% Q
Duncan's new multiple range method, 新复极差法/Duncan新法; i; Y: Z, a1 m, R1 c0 g
Effect, 实验效应) }6 ^1 a& r/ O
Eigenvalue, 特征值0 o4 U" p- L. X8 m; A
Eigenvector, 特征向量
% {/ ]) V3 _, |6 a* N) nEllipse, 椭圆/ V0 W! F& }# G2 d0 s/ O/ |
Empirical distribution, 经验分布
# D4 G( d K" A5 K1 l) e+ n5 O; UEmpirical probability, 经验概率单位3 v, T, g% p# }' v: _2 f- d
Enumeration data, 计数资料, ^+ t' H6 T/ B2 P6 d& P+ D
Equal sun-class number, 相等次级组含量
6 A+ [( c. c8 R. OEqually likely, 等可能
% S4 q" t: P! Y, b2 z" j1 F n0 o7 YEquivariance, 同变性* E- }" ~# Z6 L: d6 m( g" K
Error, 误差/错误8 {+ F4 H1 V0 A& Q. N2 c2 |; q5 R. P
Error of estimate, 估计误差1 c( b2 q1 E9 A/ [8 H8 ~% ]
Error type I, 第一类错误( ]8 p. e3 r: a$ e+ w$ r
Error type II, 第二类错误! e4 R+ ~4 R" c/ p" L. E3 a6 M6 I
Estimand, 被估量6 D9 L/ m E7 e
Estimated error mean squares, 估计误差均方
4 H- u2 N* Z+ Q& b% ^# v3 k8 |Estimated error sum of squares, 估计误差平方和) H! ~3 q; s" e: h
Euclidean distance, 欧式距离
1 S( l: S6 y( H+ k" P, Y2 u2 JEvent, 事件+ K- l# Q4 e2 [" R1 p3 \$ ]3 z
Event, 事件
9 C* `- v) f# v; R2 OExceptional data point, 异常数据点
~1 r5 o% d$ V- p& ^: \+ YExpectation plane, 期望平面3 ^" O# m$ {; i: i3 y, M( g2 x1 L
Expectation surface, 期望曲面( K4 ?' {2 M1 |& U
Expected values, 期望值, @1 ?- l* n; s- I) G
Experiment, 实验
* U$ X: \2 a0 k8 P. @- h6 f( oExperimental sampling, 试验抽样
1 B0 i, }7 E) ?: LExperimental unit, 试验单位
3 f* ?5 \! Y/ K4 vExplanatory variable, 说明变量
; R1 y9 Z2 ^& M# hExploratory data analysis, 探索性数据分析- U% E: e, e2 j0 p3 W
Explore Summarize, 探索-摘要
1 Z# C/ l2 a2 O" p# MExponential curve, 指数曲线
+ N6 _7 u4 L7 m, f. G' t1 L+ A& yExponential growth, 指数式增长
& R9 X1 H! F3 E) d: ~! XEXSMOOTH, 指数平滑方法 ; G2 x& y9 ~& `' Q, q1 d# K
Extended fit, 扩充拟合7 Z, F) q1 a* o+ ~1 `3 z
Extra parameter, 附加参数
: ~% n M5 B- U4 z" e* Q4 PExtrapolation, 外推法
; `8 k$ Y& V9 c; I9 J! u R; XExtreme observation, 末端观测值
) r8 U. ^- |. F, R( A! KExtremes, 极端值/极值
9 l5 ?+ O- V- x9 VF distribution, F分布
+ m4 V7 n' f9 f0 F/ c: EF test, F检验
8 G/ C Z1 y+ n5 ~0 v$ ]' E& x pFactor, 因素/因子* g. H l! c: o6 L1 ?7 x0 N
Factor analysis, 因子分析
% y! Y1 g- a: K5 l. zFactor Analysis, 因子分析
$ r1 v; X$ \4 w2 WFactor score, 因子得分
! z- A2 p! g- e, |' cFactorial, 阶乘" P' ?: \( x @3 V, K/ I R
Factorial design, 析因试验设计4 V2 y0 i/ b& N" [6 g% W
False negative, 假阴性9 x7 C0 A: ~, ?% B7 k2 Y
False negative error, 假阴性错误
" C- @# I2 ?& y+ zFamily of distributions, 分布族( Q1 J! q+ O6 K
Family of estimators, 估计量族2 B5 Z. K1 b! X' n( u
Fanning, 扇面
3 D2 ?$ N: G) vFatality rate, 病死率
r* X; o% [! I$ D4 X3 u) DField investigation, 现场调查" B$ u" O7 _6 T" A2 s
Field survey, 现场调查7 P( Q8 Y3 S1 l' w1 k, ~/ s3 q
Finite population, 有限总体
' l6 ^2 U2 ^' r% t7 g( v& M$ tFinite-sample, 有限样本0 {0 u7 u+ h6 v" d3 T+ M5 J/ v& z
First derivative, 一阶导数
' W! |( s& n' c; c2 z7 p0 ]First principal component, 第一主成分& ^9 N) ^4 k( ~3 K" y& I" ~) q
First quartile, 第一四分位数 [& P, [: Z H+ g% t3 X( q" a3 E
Fisher information, 费雪信息量
. {5 B9 ~4 w2 D( j* F4 h6 y+ q/ Y7 @Fitted value, 拟合值
' q- M& ^5 q8 B& E: E& zFitting a curve, 曲线拟合
. t# Z2 M/ b) L: S6 X1 I% yFixed base, 定基
4 h, i. j+ }! HFluctuation, 随机起伏% }* s% I- Z% ~& c( ?
Forecast, 预测: g& v8 i: K; ]3 S, w+ |
Four fold table, 四格表
% J( ~7 G. B3 W- G9 uFourth, 四分点& s2 K! _- g- w4 p3 D4 i7 a
Fraction blow, 左侧比率
5 e+ I, |. I& OFractional error, 相对误差0 O5 O5 V/ S; i% I9 D/ ?: E! {
Frequency, 频率
9 X+ V( i3 P4 b; ?# `Frequency polygon, 频数多边图" p' x6 W5 K) O' @- f2 F P
Frontier point, 界限点: S6 v8 ^" s" Y) c
Function relationship, 泛函关系; u- e; }4 t8 V% n( o
Gamma distribution, 伽玛分布( i6 ~ [7 d: N* H
Gauss increment, 高斯增量
3 ]5 b7 c y* Q$ [/ s: mGaussian distribution, 高斯分布/正态分布
# k; Y; b+ C( h P wGauss-Newton increment, 高斯-牛顿增量/ g# ^8 w3 W- c/ N, l, f
General census, 全面普查3 v3 C& I4 P0 ]5 h' q
GENLOG (Generalized liner models), 广义线性模型 % L$ M% _8 H* t5 M
Geometric mean, 几何平均数
2 Z8 [& c0 U9 Y) G' A2 M1 B0 gGini's mean difference, 基尼均差
( w" {7 R3 F9 AGLM (General liner models), 一般线性模型
! Z8 @0 p$ q) O+ I5 B+ @: q% y) ~Goodness of fit, 拟和优度/配合度; S% j1 y# ~: O$ K1 J) X
Gradient of determinant, 行列式的梯度8 }+ c: J, H% b* m/ v% F" _
Graeco-Latin square, 希腊拉丁方
- Z% h; _- \0 aGrand mean, 总均值
1 C6 N( E0 M+ Y2 A+ d, t* a1 Y9 WGross errors, 重大错误6 H# h* }4 H% X' u- K: o7 |5 H: }
Gross-error sensitivity, 大错敏感度
8 Y. K. u/ T* W6 HGroup averages, 分组平均; }: E( _. s2 w7 k
Grouped data, 分组资料: ~0 S6 e. {9 o# `8 Y% R
Guessed mean, 假定平均数
+ V8 c7 O; _5 ]3 n1 AHalf-life, 半衰期
( Y& K( J1 J0 g7 S: Q WHampel M-estimators, 汉佩尔M估计量5 d/ f4 F4 c* f1 e1 Y2 A
Happenstance, 偶然事件
( F4 R) M1 ?' H# a2 BHarmonic mean, 调和均数" U0 Q6 c+ g% L: v$ X* b1 ?% x
Hazard function, 风险均数
' _2 Q; Y9 g7 R$ ]Hazard rate, 风险率
7 L- H2 ~! ]) s* EHeading, 标目
3 Y* i o9 n8 C$ J& F5 {Heavy-tailed distribution, 重尾分布
- O( y1 ]$ m x( \% }: D! oHessian array, 海森立体阵
r- g$ M, ]# N; x, m( l0 V c3 |Heterogeneity, 不同质0 I9 \; r5 ?$ x
Heterogeneity of variance, 方差不齐 * C6 j% L- o5 j% D4 [( d# T y [
Hierarchical classification, 组内分组% q. D) ^7 M0 |) S5 ?% f. W V/ F
Hierarchical clustering method, 系统聚类法
/ J* L7 Y4 \" \High-leverage point, 高杠杆率点
% O, L! Y2 K% xHILOGLINEAR, 多维列联表的层次对数线性模型
" ?& X' A; d. E- ^8 N! xHinge, 折叶点* n+ E) R# q h, i; J) A; L
Histogram, 直方图+ Z0 E! f$ E- J. u
Historical cohort study, 历史性队列研究
r0 j- a5 d. `Holes, 空洞
! p p+ Z$ C4 @+ x0 qHOMALS, 多重响应分析5 b( q4 k+ E m* w6 D# C
Homogeneity of variance, 方差齐性
) ?4 M" `* N% i. WHomogeneity test, 齐性检验
" Y# E! ]% O0 h0 ?1 E/ t- y- `Huber M-estimators, 休伯M估计量, T9 R* B; T: O3 K2 `5 U
Hyperbola, 双曲线 N+ _5 w4 \3 D k, q+ h* s
Hypothesis testing, 假设检验# ?; a# J4 o, l% q3 h" }. m
Hypothetical universe, 假设总体
* T5 W4 _! d, u* c5 A1 ^Impossible event, 不可能事件
- _" t9 o: @" n: |% EIndependence, 独立性
3 E0 u) p& T6 }2 ]6 kIndependent variable, 自变量$ a9 s- U6 T* _. y
Index, 指标/指数" H+ K0 v- D5 S# \, c- [1 ]
Indirect standardization, 间接标准化法 Y. H8 g( `5 t+ ^; V3 |
Individual, 个体
& v* H$ |) \4 }3 F. R$ kInference band, 推断带; ]! s2 g- B, R) v: z
Infinite population, 无限总体1 O e% v- `4 `9 k, J- [
Infinitely great, 无穷大 v+ B- s M! L' }
Infinitely small, 无穷小# a( P! u2 N2 z2 Q7 ~
Influence curve, 影响曲线
9 l' O, m- S/ CInformation capacity, 信息容量 s. N. H- o3 @9 w
Initial condition, 初始条件
( E- e! n& L3 RInitial estimate, 初始估计值( P( M: Q# G3 |
Initial level, 最初水平4 E/ i$ K* H5 K6 N5 T+ q8 b( T
Interaction, 交互作用- L6 z2 \/ f( e$ r& v, R5 W. i
Interaction terms, 交互作用项
7 A% N; |; ?' `% x5 V3 } DIntercept, 截距
: J' y& V y& `* i1 k- Z: ]- P& `0 eInterpolation, 内插法$ C* G* d' |( K. g: ^! p* m
Interquartile range, 四分位距$ Q( P7 V* c p( L* P- H+ |6 |$ ]
Interval estimation, 区间估计# l. e. U$ U3 u; H) g7 i; N7 \
Intervals of equal probability, 等概率区间
* T5 ]/ P G/ R& i/ P) HIntrinsic curvature, 固有曲率$ v5 [' v* g, M6 F/ S8 ]$ d. Z5 ~
Invariance, 不变性4 K0 r( Z% m$ i: t. h, q0 X' ^
Inverse matrix, 逆矩阵
' S6 g3 I3 D* A. ~; M. c0 @Inverse probability, 逆概率7 q; g- i# W4 d+ l) P( ]6 ~! S" K
Inverse sine transformation, 反正弦变换$ a0 g4 X0 f# B; O1 o: }
Iteration, 迭代
+ o5 g2 G/ D) l2 Q0 v) tJacobian determinant, 雅可比行列式
9 _6 v# \$ e# O: P4 mJoint distribution function, 分布函数5 ~7 Z& s7 |, Y; w
Joint probability, 联合概率
7 L# {$ c2 U1 [6 vJoint probability distribution, 联合概率分布. O- P0 V% Q' B' p. t$ m
K means method, 逐步聚类法
) C0 R, P% \: a1 \% yKaplan-Meier, 评估事件的时间长度 ) m8 l' ]9 [+ _ c
Kaplan-Merier chart, Kaplan-Merier图
' A3 N9 {# R7 X' f7 I; FKendall's rank correlation, Kendall等级相关
9 F* a' k3 H2 `2 |0 M$ g6 ~2 AKinetic, 动力学
9 |, X ~( I% ?7 ]' q! k6 vKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
* g8 Q$ j* ~) ZKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验2 g$ }; }' A% j j1 t: ~
Kurtosis, 峰度* ]8 e- Q- R4 v4 n2 v( f
Lack of fit, 失拟
% s; q% A+ U! [& ?7 ALadder of powers, 幂阶梯
! L# N1 p- D+ J! N& ]Lag, 滞后
6 n2 p. S! [& y8 m" @9 h! oLarge sample, 大样本" K6 N) k2 x9 D& e0 {
Large sample test, 大样本检验
1 R) c& u j, j* ]. oLatin square, 拉丁方5 x' ?7 A w! D9 n/ I9 A
Latin square design, 拉丁方设计
, E) C5 e; \! _! bLeakage, 泄漏; K* t; D7 \2 X
Least favorable configuration, 最不利构形
$ x: `0 J* a! V0 C; ^; `$ @Least favorable distribution, 最不利分布
- `+ s$ h$ a* U2 u0 ~; m- v" `: O, N; I! cLeast significant difference, 最小显著差法
/ @1 ~) t' x. L" e+ xLeast square method, 最小二乘法! M5 s% H! J- u3 f4 \1 N J
Least-absolute-residuals estimates, 最小绝对残差估计
! y: E. ~4 }+ Q7 wLeast-absolute-residuals fit, 最小绝对残差拟合8 Z t' ?; x0 O' u" q
Least-absolute-residuals line, 最小绝对残差线
# `0 @8 [! [" m, R$ q |Legend, 图例
# k# `( \! ?. z, m6 C* U1 [5 ^L-estimator, L估计量& k! y- R0 C K/ @% c
L-estimator of location, 位置L估计量# b3 L1 j8 V; ^( w8 r; d. V
L-estimator of scale, 尺度L估计量
2 z! ?) ~) ^$ [Level, 水平" }$ S. T# w; S0 n
Life expectance, 预期期望寿命
" u, U' o8 \; p/ b7 \' sLife table, 寿命表
% n6 t3 a" L" c/ }Life table method, 生命表法
+ ^- S" u' f2 a5 N, H9 b' R) D( sLight-tailed distribution, 轻尾分布
7 g3 _) K7 f" o' t0 X: D tLikelihood function, 似然函数 u% r" _. d: k1 q6 o9 b
Likelihood ratio, 似然比! t) a& F( z A2 X5 h
line graph, 线图
2 ?7 d% x, v% Q) q w5 `* V+ hLinear correlation, 直线相关8 u6 g0 ~1 j% W" Z" B
Linear equation, 线性方程
) z- ~: [/ x* E# x/ c2 x- nLinear programming, 线性规划( O; l0 n1 v! C
Linear regression, 直线回归7 J2 Y8 @7 ^ C, L* w
Linear Regression, 线性回归4 }( @) k( C% L7 l$ z
Linear trend, 线性趋势
: \2 ], X) F; X: ^6 J$ I/ V4 XLoading, 载荷 ! a3 R1 @- {* d9 U3 {
Location and scale equivariance, 位置尺度同变性
/ G' x& \4 A7 ]3 }% j; aLocation equivariance, 位置同变性
3 h- ]9 ~ I! x7 E) t3 FLocation invariance, 位置不变性6 S n% ]7 m3 i; Q6 Y2 Y
Location scale family, 位置尺度族/ b; C: }- q( {) f8 r- y q
Log rank test, 时序检验
2 `+ f. m ?$ M# k4 x2 g, h2 L! SLogarithmic curve, 对数曲线
0 k, H: ` a. e& s" p. ALogarithmic normal distribution, 对数正态分布
8 k) |8 _$ _6 kLogarithmic scale, 对数尺度# t. y* k- |/ ?
Logarithmic transformation, 对数变换0 w" R0 @* _8 [
Logic check, 逻辑检查# A+ A, S9 k. o
Logistic distribution, 逻辑斯特分布: Y+ c# D' \( v/ I3 T. w. O
Logit transformation, Logit转换0 H# {7 P! L8 Z, h! V9 U/ Q# u, Y& |- w
LOGLINEAR, 多维列联表通用模型
( V! h: N# }+ ?) ~* ?! \9 L0 ]% `Lognormal distribution, 对数正态分布
+ R' B4 ^3 k$ I1 ?* FLost function, 损失函数
( Z- N; f- @# v$ ?* m( z* ^6 ^9 T% sLow correlation, 低度相关/ M, c' A- u% Q' `3 c
Lower limit, 下限9 H( c5 i( \$ `% O; @( R$ `) f
Lowest-attained variance, 最小可达方差
6 D- u3 q4 V3 p4 zLSD, 最小显著差法的简称
/ e8 @6 o- @+ d: TLurking variable, 潜在变量% A7 p3 J" i) o4 s4 w
Main effect, 主效应
6 @3 n% b8 X; d6 F# n- bMajor heading, 主辞标目* z+ U0 Y. l- y, h$ d4 O) ^
Marginal density function, 边缘密度函数8 u- B8 Q, T$ v" z4 t) c
Marginal probability, 边缘概率
6 y# B6 f2 }3 @' AMarginal probability distribution, 边缘概率分布
2 J1 i9 x. _& v4 sMatched data, 配对资料: w5 u6 A- q% Z# W) @
Matched distribution, 匹配过分布7 U: ]( m k8 q# l! o0 u
Matching of distribution, 分布的匹配; V# {' Q7 m, d" p5 Z$ [
Matching of transformation, 变换的匹配9 w& J f2 B2 D
Mathematical expectation, 数学期望
6 \. r3 T2 X0 f5 E- C0 aMathematical model, 数学模型
5 A( M; }# |. B) g: E* W6 HMaximum L-estimator, 极大极小L 估计量
( W C4 I) v$ S+ m7 r( i* lMaximum likelihood method, 最大似然法2 N6 C% `5 s' r0 K0 m
Mean, 均数8 x+ c5 z! l5 \: Y
Mean squares between groups, 组间均方7 `) c- ~0 s: B! q
Mean squares within group, 组内均方
1 [0 a. d8 j; w" S& zMeans (Compare means), 均值-均值比较
, X0 W- T& D9 {% J3 W$ f0 {Median, 中位数4 K, I8 Y1 Z" K5 g" V1 Y. L
Median effective dose, 半数效量7 V# Q/ H% [+ f \6 M$ B) M7 T
Median lethal dose, 半数致死量7 o& _! k6 C: H) W8 X0 \4 t, n
Median polish, 中位数平滑
% C `5 T8 g- A: d' sMedian test, 中位数检验
3 y& J$ e+ h, r) ~7 sMinimal sufficient statistic, 最小充分统计量
- Y$ h2 a( I0 w ZMinimum distance estimation, 最小距离估计3 S7 k. d: P4 J
Minimum effective dose, 最小有效量 B% M: Q6 ^) w% [$ G% d
Minimum lethal dose, 最小致死量0 h# n8 A! q# A. z
Minimum variance estimator, 最小方差估计量1 e) {, Q$ w! V+ S5 t* I
MINITAB, 统计软件包
& S; Z' @+ u6 R( e6 ]# M, r5 N7 bMinor heading, 宾词标目6 u6 f8 M8 D- ^+ ^( d! w# V5 I7 h- c
Missing data, 缺失值! ]. Z8 X$ f+ H+ ]+ A4 Z
Model specification, 模型的确定
* q5 g7 R' L2 _0 n( t3 {; P1 ~Modeling Statistics , 模型统计
. L: M& f0 a; q8 z. T) k) G' ~' cModels for outliers, 离群值模型
% {! R3 ?+ V' x9 S1 y# @8 A+ RModifying the model, 模型的修正
4 l# S8 |$ m# G% G2 F& ^* [Modulus of continuity, 连续性模2 k# v1 N, z# y" w
Morbidity, 发病率 6 Y( G: ~, G1 ^; v* T5 P" ^
Most favorable configuration, 最有利构形
) C( ~3 R' E6 ]Multidimensional Scaling (ASCAL), 多维尺度/多维标度1 P) S. k7 {4 f. ?0 g
Multinomial Logistic Regression , 多项逻辑斯蒂回归
' p2 `1 {% Q a: X% ^: {Multiple comparison, 多重比较
( o! I/ n3 e% ]: d6 r3 \" z" RMultiple correlation , 复相关% x: N& ?8 N2 F* h3 h( M I4 _- c
Multiple covariance, 多元协方差$ q( n6 {! ]% B w! j( n$ W
Multiple linear regression, 多元线性回归
& S; Q& Q# e: b, OMultiple response , 多重选项
1 T- a1 [5 F# X; h2 iMultiple solutions, 多解9 Q' {, h9 S y7 _. X% X
Multiplication theorem, 乘法定理
% N+ B n" Z {+ M/ k! M8 FMultiresponse, 多元响应* V. e8 z$ f9 A0 F& f
Multi-stage sampling, 多阶段抽样6 B- j/ F& C4 U
Multivariate T distribution, 多元T分布4 u- ~5 h" A2 b4 V1 S. C
Mutual exclusive, 互不相容
+ L9 M! P; \& \& c4 c HMutual independence, 互相独立! z9 z! K& x: M/ G7 i5 F
Natural boundary, 自然边界
6 @" o3 U+ C; s/ LNatural dead, 自然死亡
; h" a2 C9 s- A+ FNatural zero, 自然零% j% E" L6 ^' x4 V7 ?" q7 T
Negative correlation, 负相关! C# ~9 u- Q; V+ S% W: {7 G, d
Negative linear correlation, 负线性相关" ^8 O4 _, w9 ~. y/ q
Negatively skewed, 负偏
! \# O" x8 | |& b1 hNewman-Keuls method, q检验6 N5 F8 @) `- S% w
NK method, q检验
/ `6 Q7 R+ k- P& @! Q q0 rNo statistical significance, 无统计意义
$ w0 m6 E) d3 PNominal variable, 名义变量
9 s; y0 @6 {) R( ^Nonconstancy of variability, 变异的非定常性5 U+ {- c2 S4 f! v+ b6 k- t1 e
Nonlinear regression, 非线性相关
& O* v# s# o$ l+ ]Nonparametric statistics, 非参数统计. z0 r3 K9 f8 K8 p u
Nonparametric test, 非参数检验, u& _7 `. N1 T2 k) E& _& O$ }/ \+ ]
Nonparametric tests, 非参数检验
. L; r5 \) }- LNormal deviate, 正态离差3 G+ V0 g/ K! ^2 j
Normal distribution, 正态分布2 z' F! U7 ^. P' f! c, \3 A* g
Normal equation, 正规方程组
- i6 q% F% k1 a: {* x- |7 d6 g7 d) FNormal ranges, 正常范围2 Q# g5 U, z2 g: F, [ {2 y" R
Normal value, 正常值3 O% H ]2 O' y! b# M
Nuisance parameter, 多余参数/讨厌参数
t, z, B) }# n; K0 `Null hypothesis, 无效假设 $ C/ u' Y; L/ _4 ?9 r. B- S1 z' s# z
Numerical variable, 数值变量( ?# r) n9 e0 {# b
Objective function, 目标函数9 m/ ^& Y# o7 C0 h
Observation unit, 观察单位
: K$ h0 D; T* E* Q+ H; Y- k7 JObserved value, 观察值+ b0 R4 Q1 Q/ _
One sided test, 单侧检验4 r/ O' b8 w' x9 X( c$ y8 t$ g
One-way analysis of variance, 单因素方差分析2 d& `" a4 M8 O F3 _) d
Oneway ANOVA , 单因素方差分析
: w& A9 }1 u3 _) B. h J5 l6 l7 wOpen sequential trial, 开放型序贯设计1 J6 [0 L7 F# q; ^# K
Optrim, 优切尾
, w3 {9 ~! w- f. YOptrim efficiency, 优切尾效率3 _( d3 t6 n, e& V3 |; U! C: `1 I
Order statistics, 顺序统计量
& b6 l0 \4 P& X. F" z( g$ O7 DOrdered categories, 有序分类
" N$ X: D) I0 ROrdinal logistic regression , 序数逻辑斯蒂回归
( T5 V7 H5 j$ ]5 y D0 ]Ordinal variable, 有序变量
$ z: y* ^* E2 j* S1 _; j uOrthogonal basis, 正交基
0 F% _; X7 C* [9 ?Orthogonal design, 正交试验设计
2 ^7 e6 H7 u- e+ K R, }Orthogonality conditions, 正交条件
2 B6 E% A! D- a! l' ?8 z% G2 T% hORTHOPLAN, 正交设计 ' }' C& I: K, B
Outlier cutoffs, 离群值截断点
/ Y ?( m1 w. c* p. ~* O( JOutliers, 极端值
; b. T$ e' y! ?9 K1 a' Y" xOVERALS , 多组变量的非线性正规相关 ( L- C; K ~1 N9 y
Overshoot, 迭代过度2 v" O4 N% l6 ~' c+ M, t
Paired design, 配对设计
) J" m8 P+ _+ @ q Q8 ePaired sample, 配对样本
" J( E, B; @) {2 y8 {Pairwise slopes, 成对斜率
6 k3 s( X/ {$ ?; U. {/ D2 w, AParabola, 抛物线
0 i' d2 e" } J+ ?0 p/ ]; bParallel tests, 平行试验# U3 ~3 Y9 V; e, g0 }. u+ N
Parameter, 参数
t2 d: S6 M1 H: s+ P9 B, v/ j+ q3 qParametric statistics, 参数统计7 ~+ [9 E5 j& d) i# o
Parametric test, 参数检验5 ^1 r |. ^! I9 W5 {
Partial correlation, 偏相关
. F- s( N7 Z4 S! nPartial regression, 偏回归! n [) x1 L' w5 \: a
Partial sorting, 偏排序. k/ }6 v c% ]+ I$ Q: `0 |; j
Partials residuals, 偏残差5 W( i0 q: F6 \1 \) U: `
Pattern, 模式7 K- L6 K: t' b- U0 \
Pearson curves, 皮尔逊曲线
$ @* d# m w4 r/ i7 r- Y3 PPeeling, 退层
* u; u& G6 v) x7 M. }Percent bar graph, 百分条形图
+ J4 o2 z! }) `8 c VPercentage, 百分比
4 ?* }/ q$ A+ o1 uPercentile, 百分位数
/ x+ J' a/ l$ y8 q* @. i0 d/ }Percentile curves, 百分位曲线4 D2 ]8 o0 b- _) d2 A, W
Periodicity, 周期性2 U# R7 N2 m& g" ]% F4 _' u+ \
Permutation, 排列) z* ]7 i( h9 |3 g4 q- e! w
P-estimator, P估计量
: Y3 [2 m4 `: _ ]Pie graph, 饼图
" m* M- j$ n! W; vPitman estimator, 皮特曼估计量
9 `# Z& E) B! U3 }$ A9 hPivot, 枢轴量' N. x& m; c+ Q' }6 N! U9 x
Planar, 平坦
1 z3 c( L. Q5 ]1 A1 |& I) XPlanar assumption, 平面的假设3 v+ }) B% }( u! b
PLANCARDS, 生成试验的计划卡
0 q9 G! M8 I4 e: p' [Point estimation, 点估计
6 `/ Q K0 S3 A6 W% k% lPoisson distribution, 泊松分布$ D3 R: F2 ^# o1 _
Polishing, 平滑) m2 g6 S6 B; x# f/ v, n
Polled standard deviation, 合并标准差 c8 }& n6 a% B
Polled variance, 合并方差3 d, r7 k: F5 t' d8 c' d
Polygon, 多边图
3 j* g* \2 d, v3 b7 Q/ KPolynomial, 多项式
3 d6 `+ M$ l) ~( y. }! N: LPolynomial curve, 多项式曲线
! w& n2 X- d9 ^! vPopulation, 总体
$ H' {1 d5 l3 @2 K* i7 BPopulation attributable risk, 人群归因危险度
- P0 j: s& I0 @- WPositive correlation, 正相关+ w8 t/ I$ N; `9 `9 Y
Positively skewed, 正偏
' e2 K3 N& L( `* z) c2 hPosterior distribution, 后验分布
$ j$ y; K' n; n$ Q1 v2 PPower of a test, 检验效能5 T4 c, E5 X. w
Precision, 精密度
( Z- C) N$ F: S" ?" f7 YPredicted value, 预测值
9 `% K1 |3 l% x( J" X: e1 k2 m6 DPreliminary analysis, 预备性分析: G' E! }. Q0 O- f$ g
Principal component analysis, 主成分分析
6 E7 T, j' u% v/ l) j+ R3 ~5 bPrior distribution, 先验分布: K( R% o, o$ V2 X/ S6 r
Prior probability, 先验概率
$ a0 A0 e8 H5 [3 i# V8 |. zProbabilistic model, 概率模型: G/ } j5 O( i% @/ x. s
probability, 概率2 n# `; S) F/ {0 ?. X4 @1 j9 x7 R
Probability density, 概率密度! F9 S# h+ }% K4 w8 h$ ]
Product moment, 乘积矩/协方差8 w" p0 e8 I' Q! Z5 s
Profile trace, 截面迹图0 a; p6 B/ q" ^5 \
Proportion, 比/构成比1 a2 x+ D7 J+ A+ Z. g* D2 K2 [
Proportion allocation in stratified random sampling, 按比例分层随机抽样
6 x! R' e4 x+ N9 eProportionate, 成比例
& L" {- K' M- v+ ]Proportionate sub-class numbers, 成比例次级组含量- K( ]3 l& _: {
Prospective study, 前瞻性调查
8 a' y/ q' F } e6 u3 {Proximities, 亲近性 & ]5 x& ]( R1 \5 B; F
Pseudo F test, 近似F检验
0 G' l3 @$ U' K# x# ~; ?/ ]Pseudo model, 近似模型; `( S+ t% X5 z8 n ^# l% M
Pseudosigma, 伪标准差0 C% c9 e; I# l1 r
Purposive sampling, 有目的抽样
: v3 _: ~# p; @* E& `QR decomposition, QR分解, q1 u w0 Z0 R' A: A
Quadratic approximation, 二次近似9 @% M2 r! a" O3 S* U5 c
Qualitative classification, 属性分类
; j# _- k7 z" [Qualitative method, 定性方法
! S$ R3 U! ?9 w* XQuantile-quantile plot, 分位数-分位数图/Q-Q图
5 i+ n( x* l/ K& T$ W! S9 |/ GQuantitative analysis, 定量分析
8 M/ e0 C/ e9 K; ]. a% a0 Z a4 dQuartile, 四分位数. p3 d0 c7 Q9 c9 z5 \: v
Quick Cluster, 快速聚类
$ z7 x5 G! A S: W+ w/ c8 r9 HRadix sort, 基数排序
- w# p4 V1 ^. O- s1 PRandom allocation, 随机化分组; V& Y3 O" }+ d2 [6 C% @' D" v
Random blocks design, 随机区组设计4 q4 g8 c" N3 Z
Random event, 随机事件; \; q3 ]& U3 s1 ]+ J* z2 K
Randomization, 随机化( s1 V9 {: d$ D1 X* \' s
Range, 极差/全距& ?' N6 w8 S# r" m1 ]
Rank correlation, 等级相关
1 H6 h& ]: a( N( _% hRank sum test, 秩和检验8 b; `8 h# m5 i7 h+ Z4 ]' J
Rank test, 秩检验
: u% j6 e: @. o8 s+ {Ranked data, 等级资料3 o) j" R2 W/ D/ a1 i. y
Rate, 比率
{. }" G' \- Z% v. i& ZRatio, 比例
$ f1 P9 o* i( n! k# D/ R. LRaw data, 原始资料
! A _/ J% x2 C2 K" W# H* jRaw residual, 原始残差
! \$ m9 m$ o6 U( d( k SRayleigh's test, 雷氏检验
" Y0 Y. \* P+ r8 ^4 s# |* ?Rayleigh's Z, 雷氏Z值 6 n% c2 R1 T' h
Reciprocal, 倒数
/ ?/ j1 z" G2 Z& g) U7 E, {% `( xReciprocal transformation, 倒数变换
/ c' k! W, h6 CRecording, 记录
& ^% f4 q6 L: X1 @0 @$ oRedescending estimators, 回降估计量
! n$ O, x, Z0 j) H$ j0 ~ YReducing dimensions, 降维& Z' N. l2 g, c% t6 E% m
Re-expression, 重新表达" M- M8 P2 k/ r; y3 @+ z( X
Reference set, 标准组
* d! f. X. t" ^- [Region of acceptance, 接受域
' W4 s/ U+ R( }- c8 _Regression coefficient, 回归系数) d& ?& }8 q) }8 \5 k
Regression sum of square, 回归平方和
) Q# j+ {( m- VRejection point, 拒绝点
7 h: Y5 q) o; x' Y; VRelative dispersion, 相对离散度
; o* T9 m _ Y" eRelative number, 相对数+ ]0 r1 M* S3 z- J
Reliability, 可靠性7 X! K, p6 J) X. i2 ]
Reparametrization, 重新设置参数
4 |2 H7 }3 [; Z4 dReplication, 重复" v+ B& T/ {7 Y! n1 f/ J5 K% M! P
Report Summaries, 报告摘要' i, X; X6 o) i* w/ q
Residual sum of square, 剩余平方和 E: J9 J3 m5 ?" U0 e+ Z. R5 d
Resistance, 耐抗性
. n% E* J- M) z: kResistant line, 耐抗线. X, `8 \6 r& {
Resistant technique, 耐抗技术
2 E& d. D* v7 c3 o t/ GR-estimator of location, 位置R估计量
?5 F$ g' m6 PR-estimator of scale, 尺度R估计量
# ~1 d. I. Y* B" U/ o; l) ~& ]Retrospective study, 回顾性调查 _5 M8 R! D3 w/ }& l
Ridge trace, 岭迹- [: |! J" s3 V) g% g
Ridit analysis, Ridit分析3 h8 F# s2 p3 G! ~5 r
Rotation, 旋转
. }5 h0 i+ U& a6 WRounding, 舍入
& ]8 l7 e) [5 g. ]5 i; }Row, 行
6 T# |3 u1 M- J: U/ \4 yRow effects, 行效应
. _9 s, N6 n7 @/ \4 BRow factor, 行因素
l* {/ s5 f* s- f, m) k; X4 pRXC table, RXC表, t8 E# k" g) K# W, {, \" ^+ z
Sample, 样本
- F* U9 F w" LSample regression coefficient, 样本回归系数
. P8 T5 d4 R$ ]Sample size, 样本量- f0 @# q; }- A3 s4 U
Sample standard deviation, 样本标准差! d+ E8 t8 G/ J1 P) O
Sampling error, 抽样误差; r' Y5 n0 g F, }6 ^/ N
SAS(Statistical analysis system ), SAS统计软件包
2 X9 A" E! I, ~# K" D8 ZScale, 尺度/量表
6 ^. U9 j3 b8 g0 k9 D$ d9 z, L# KScatter diagram, 散点图0 o t. h. t7 Q+ T6 t7 l
Schematic plot, 示意图/简图; Z, v- E" T# N* f. H$ q4 |2 }
Score test, 计分检验
# F( m/ a7 x/ G1 u4 VScreening, 筛检
- y/ T0 `; ?/ M' i2 n, p. hSEASON, 季节分析
7 z" Y G% v: \$ N& K \Second derivative, 二阶导数- J% p l( t0 g# C
Second principal component, 第二主成分) w1 E5 D$ g4 V6 `/ u. z( e
SEM (Structural equation modeling), 结构化方程模型
2 _3 i% f- r! M& l. t' LSemi-logarithmic graph, 半对数图1 c7 [( `+ T" } y
Semi-logarithmic paper, 半对数格纸! p& L/ {2 r$ i" q+ H$ H
Sensitivity curve, 敏感度曲线9 @3 u M8 R$ b
Sequential analysis, 贯序分析
, O) b5 s4 G2 U. vSequential data set, 顺序数据集
2 @" b7 j) z' L" ~Sequential design, 贯序设计
. D. D& u$ U! J( ]4 }Sequential method, 贯序法* O$ N4 s1 Y3 O! {' x
Sequential test, 贯序检验法$ c2 d0 c% O& l$ {0 O* ]
Serial tests, 系列试验5 j- L" A& ?6 t$ J. V+ E' R
Short-cut method, 简捷法 , V% |- _6 Z3 F0 P; A1 w
Sigmoid curve, S形曲线
; u# f* [$ y7 Y% m7 A8 B1 DSign function, 正负号函数. o; o# q6 h7 x/ {$ ]; ^5 }
Sign test, 符号检验
; t: b! }8 N5 `# S, CSigned rank, 符号秩
9 S- x j8 O \. r0 r7 g! ySignificance test, 显著性检验
5 Z* b" x' q9 q( h( B' @1 h. vSignificant figure, 有效数字* [( U6 z3 V9 h! c ?; p p
Simple cluster sampling, 简单整群抽样% {6 |6 Y+ g3 o: @4 I2 A$ t
Simple correlation, 简单相关! B9 }: r2 O' x# T7 Z! M
Simple random sampling, 简单随机抽样
5 F0 R! T$ W: d; QSimple regression, 简单回归
, `2 b' n4 @6 P+ csimple table, 简单表5 u3 |& N# Y& J
Sine estimator, 正弦估计量6 C9 x; T# p# d! T/ z# v2 q
Single-valued estimate, 单值估计
) J/ Q; T: Y' g. ]% _Singular matrix, 奇异矩阵
& n. Y) k5 [+ {9 c3 s. mSkewed distribution, 偏斜分布
& e- a Q7 }' b8 R' tSkewness, 偏度; ]$ `0 S1 C! h v
Slash distribution, 斜线分布+ w2 O# {; q: H3 R/ k1 n
Slope, 斜率
, r) _% r8 T- j; E! I9 }& x. iSmirnov test, 斯米尔诺夫检验" A4 z5 {) J0 Z; c6 }8 J
Source of variation, 变异来源
$ w/ F" H# I4 s# BSpearman rank correlation, 斯皮尔曼等级相关
! J( z. r& p6 ^; H% Q# tSpecific factor, 特殊因子
K6 A$ q- m/ a6 d$ J9 FSpecific factor variance, 特殊因子方差1 [3 p" F; \3 x9 M4 D; H
Spectra , 频谱 S0 T3 H3 J7 z1 o" E% Q& g
Spherical distribution, 球型正态分布
: L/ m+ t- B, D% U& n1 L- y& jSpread, 展布
+ _1 r* w" m bSPSS(Statistical package for the social science), SPSS统计软件包/ v' Q% c' U# \' L2 H, i# }: m
Spurious correlation, 假性相关
" r# n1 r! @/ M' w! o- I3 H( T& Y- eSquare root transformation, 平方根变换1 b- Z. I5 E6 ^# y& b% L# n
Stabilizing variance, 稳定方差* w6 F& C6 b1 `, V
Standard deviation, 标准差) P3 s4 A( u2 `' |
Standard error, 标准误
/ F1 [( j. r) D% r: cStandard error of difference, 差别的标准误2 B" n: q9 |8 w* S' M
Standard error of estimate, 标准估计误差" p: K4 k7 e7 C1 [0 n. o* S1 l" C
Standard error of rate, 率的标准误8 U: N+ H' ]8 a6 ~. z
Standard normal distribution, 标准正态分布
2 f/ r( @% j! S' \# }Standardization, 标准化+ L* i/ K8 X2 O2 R0 G0 E" A; D
Starting value, 起始值5 Q7 U: C" P& Y3 t
Statistic, 统计量
$ n+ _* I! o' ^4 h2 N& t- JStatistical control, 统计控制
: ]/ `) p y- P% VStatistical graph, 统计图4 \6 c# w6 K n" `) y% [6 _. Q, [
Statistical inference, 统计推断' o8 `) e8 }3 R9 i- V% E, m$ L3 F6 m
Statistical table, 统计表9 t% j3 \+ ~( ?" x
Steepest descent, 最速下降法
" _6 Q; |) y) d- |0 G+ p0 V# b, zStem and leaf display, 茎叶图
! I j! a; e. A4 t* Y9 P0 TStep factor, 步长因子
! U: f1 b1 s G# \: p' |) TStepwise regression, 逐步回归
% Y, l: G2 @, G) CStorage, 存
; w3 N. k( p/ L3 N/ NStrata, 层（复数）/ {9 |! _1 r9 i y
Stratified sampling, 分层抽样/ c( ]0 O& K" S1 e) b" n( J
Stratified sampling, 分层抽样
$ ~3 F6 S7 l, b; R# N% x2 U$ tStrength, 强度7 L. c7 g1 Y# `/ h( w
Stringency, 严密性
' B Z3 M- s" OStructural relationship, 结构关系
7 C d9 J2 e+ M& l+ `Studentized residual, 学生化残差/t化残差
l$ f) j2 d3 I/ rSub-class numbers, 次级组含量
2 J5 {! S( T2 U1 k2 rSubdividing, 分割
- \" H7 k, Z8 E/ w: W `Sufficient statistic, 充分统计量
" i( f% ~+ o4 z* A$ z0 BSum of products, 积和: a6 i- s& c, _6 Z
Sum of squares, 离差平方和: k6 A' S _: a
Sum of squares about regression, 回归平方和! u8 G" w% v+ S' P- B$ _8 @0 b2 ?2 r
Sum of squares between groups, 组间平方和
; Y+ e4 e6 W) Z7 R0 B( USum of squares of partial regression, 偏回归平方和) H: a8 X" b& m$ V6 U
Sure event, 必然事件
, K* U& T1 P" d, t' ~Survey, 调查
4 S9 F2 Q! `9 `. jSurvival, 生存分析
6 {1 J, k3 z: k t0 u5 H* c" t3 wSurvival rate, 生存率1 V/ `: r+ t; q- W3 J1 m8 e
Suspended root gram, 悬吊根图0 Q/ m" l& ~2 c0 ?5 D
Symmetry, 对称 E/ N: F/ `( Q* X
Systematic error, 系统误差
; x c ?' }+ ^1 i9 ASystematic sampling, 系统抽样
8 G& _; Q8 U5 F/ P+ F. [& v% _" eTags, 标签
3 h( v$ t" e {) T' t8 r/ n: WTail area, 尾部面积7 u+ y; x& F5 m. k) g u
Tail length, 尾长# O$ ?4 s" E1 a
Tail weight, 尾重- L. s& Q1 i$ O0 [( v
Tangent line, 切线; }& O5 T( d. _$ b) d8 H* a% H# ^
Target distribution, 目标分布# E& b# ~( m* }
Taylor series, 泰勒级数
7 [, x7 f! x! r- Q" b5 @" E8 p3 O/ P) aTendency of dispersion, 离散趋势
8 J$ L6 W/ Q) O) v, R5 J6 NTesting of hypotheses, 假设检验
" O, a# D' O* dTheoretical frequency, 理论频数 H$ }, _0 G$ D0 `# B( S
Time series, 时间序列' e1 p% v! |, D2 F
Tolerance interval, 容忍区间
9 e' t7 q0 |) Q5 [Tolerance lower limit, 容忍下限
3 W: @1 h8 B8 x/ P/ LTolerance upper limit, 容忍上限8 C4 p# M: Y+ s$ ^5 Z s7 A
Torsion, 扰率
9 p$ g+ Q8 V% x& ~. tTotal sum of square, 总平方和, g4 ]. n& R" Y) {9 j
Total variation, 总变异
% Y3 ~ S0 ]& f& H% bTransformation, 转换( U0 F# V8 \6 j5 L9 D
Treatment, 处理$ ]5 _* @7 U* i( t1 g5 [
Trend, 趋势9 e3 T7 H. q! Y# M
Trend of percentage, 百分比趋势
8 Q8 z9 N2 Q8 I' MTrial, 试验
0 K E0 K( f; ~Trial and error method, 试错法
: \/ ?1 \8 g% R9 g: y& o/ f6 JTuning constant, 细调常数
* \' L$ i% O. ^$ t5 T" GTwo sided test, 双向检验
7 F/ R2 t. C0 _8 p0 k. xTwo-stage least squares, 二阶最小平方
8 w- Z1 @: i* v$ K) g# T5 K- o5 ATwo-stage sampling, 二阶段抽样
6 m6 }( ?3 ^! J' n, Y6 [6 hTwo-tailed test, 双侧检验: q% S# A. B) a' n0 c+ e
Two-way analysis of variance, 双因素方差分析
) _8 N. P# H$ w9 N% l. {2 ZTwo-way table, 双向表0 e, L- [& f0 U5 ^
Type I error, 一类错误/α错误+ g }) H, R* j7 j
Type II error, 二类错误/β错误9 @) I1 E0 f: X0 H9 N' D. o* |
UMVU, 方差一致最小无偏估计简称) k4 U1 L1 x6 K" I' \( k
Unbiased estimate, 无偏估计" F6 l+ d' p0 s' b3 _
Unconstrained nonlinear regression , 无约束非线性回归$ z- l F3 E0 C: x% Y m K
Unequal subclass number, 不等次级组含量9 h4 U0 P; P3 q# O4 Q2 i6 f
Ungrouped data, 不分组资料4 t9 x2 {2 a% [. m0 q
Uniform coordinate, 均匀坐标, a& o( q4 n8 h7 s9 \
Uniform distribution, 均匀分布
9 v; f- q' [% B" S/ D3 d+ FUniformly minimum variance unbiased estimate, 方差一致最小无偏估计, a" Z5 {& ?; D0 t
Unit, 单元
# ?: X. d& s- _! @Unordered categories, 无序分类
/ r: n) U0 x+ ?) PUpper limit, 上限) S& Y& @+ c3 w9 l
Upward rank, 升秩3 R- b2 m, n8 b/ c
Vague concept, 模糊概念4 w$ l( z1 b$ Z$ v' W& N
Validity, 有效性$ H, S% [; o& j* a/ E
VARCOMP (Variance component estimation), 方差元素估计- [( u5 M6 ?2 t; F0 l" ^
Variability, 变异性; e+ z! N: Q) `( M% B
Variable, 变量
5 I+ ~7 O5 J( v" n, b" O( H( zVariance, 方差
3 M, m3 O( x, e2 o+ E1 f1 NVariation, 变异$ x# |9 u# H, e; }3 e9 E8 |1 Y
Varimax orthogonal rotation, 方差最大正交旋转
( l, Z, w- U* ZVolume of distribution, 容积2 U) f/ L4 c8 g
W test, W检验
7 }0 V6 I; B$ O; N& IWeibull distribution, 威布尔分布+ W3 X4 }' Y Q9 Y4 N% k& n) e' f
Weight, 权数
7 t6 o1 T5 E0 L8 hWeighted Chi-square test, 加权卡方检验/Cochran检验
$ C. q) z( E9 L9 u8 EWeighted linear regression method, 加权直线回归6 k* l7 g7 ]8 `
Weighted mean, 加权平均数
) _" u3 B% L" l5 }% U3 ?Weighted mean square, 加权平均方差
8 O: \! V" [% H+ p+ h$ e! zWeighted sum of square, 加权平方和
0 g1 K o* \( PWeighting coefficient, 权重系数
7 k5 f8 }5 f5 h( ~Weighting method, 加权法 ' e+ T. q" E. F6 |3 b/ Q) U [
W-estimation, W估计量) b$ b) h7 @) G4 B) v& k
W-estimation of location, 位置W估计量1 [& ^7 e; E; {1 t- o
Width, 宽度* Q+ f; K7 ~- H# [% |
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验& d T+ q: J1 }+ x3 D0 n
Wild point, 野点/狂点: I- h) V9 n) l2 m2 X" l3 |
Wild value, 野值/狂值+ M ]# w* K. \) `( W, _; W, X
Winsorized mean, 缩尾均值
1 T" E6 ?* U v4 V/ x+ F, ]Withdraw, 失访
* V0 X1 f7 s0 S* c8 L, l. x4 l* N, |Youden's index, 尤登指数
2 V9 V% o5 I7 zZ test, Z检验
+ y/ c% c6 R5 Z, T, L% {' oZero correlation, 零相关
5 U m" v/ V bZ-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
