|
|
Absolute deviation, 绝对离差
4 M4 Y8 }2 G% M! ?/ @( j& t, N# F# y4 JAbsolute number, 绝对数1 M3 c. V; x7 i: `* A
Absolute residuals, 绝对残差( ~0 s6 C2 k7 o9 W+ M
Acceleration array, 加速度立体阵7 M/ A& ~ {/ O) F2 V% J' S5 }
Acceleration in an arbitrary direction, 任意方向上的加速度; h( J: o) m6 r7 q1 Q
Acceleration normal, 法向加速度
" D' }/ e. T& \Acceleration space dimension, 加速度空间的维数0 N* `. i+ n3 X4 V! Y: ?$ F; t
Acceleration tangential, 切向加速度2 K% @7 O$ t" y2 A# A; e9 D& g h
Acceleration vector, 加速度向量
: L( A9 A1 v1 ?1 zAcceptable hypothesis, 可接受假设
: _, `& b. l( L' t8 X1 P: g2 l* g J3 ?Accumulation, 累积
" y# }) ]. X" CAccuracy, 准确度
' K1 Z s& A! W" a. cActual frequency, 实际频数
; @6 t' I' f0 X9 cAdaptive estimator, 自适应估计量5 V1 k% V# R# E4 f# H& S5 j9 Y7 V
Addition, 相加
$ s7 G. E2 E" x! xAddition theorem, 加法定理
8 S& E3 F' W1 R |Additivity, 可加性
9 L3 e0 A* R- x- P' HAdjusted rate, 调整率
1 ~4 f8 M* m6 j( K; FAdjusted value, 校正值/ ]% Y2 |; `: y. z. O* Q
Admissible error, 容许误差
& G/ \. b6 P" v* mAggregation, 聚集性* D7 G1 N C0 s6 Q
Alternative hypothesis, 备择假设" C9 }+ A% D. ^) P0 n1 I: i
Among groups, 组间
( P2 v, A! Z9 c. o! @5 kAmounts, 总量
+ m2 L5 B9 n& J$ d# @' hAnalysis of correlation, 相关分析
6 }/ h# b- X+ o/ r z, a; `Analysis of covariance, 协方差分析% U4 u% [- \1 S+ ?$ L+ D w
Analysis of regression, 回归分析
7 {& D% S8 {1 A5 \Analysis of time series, 时间序列分析: u9 W& o' W6 Q5 [/ \5 f
Analysis of variance, 方差分析0 \- C- Y% |1 v6 k' @( i. K
Angular transformation, 角转换
6 g: }2 C% g2 T5 |5 R6 @. J# iANOVA （analysis of variance）, 方差分析
7 F, E& Q% ^9 W5 PANOVA Models, 方差分析模型
& p! i% w! ^5 }9 v4 W* ]Arcing, 弧/弧旋
, _! h$ _; d' W2 c6 S' vArcsine transformation, 反正弦变换
+ K4 V) Z5 X2 xArea under the curve, 曲线面积5 L8 w- x3 H' I; \* J
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
8 j+ n3 w, Y+ h. L6 x" EARIMA, 季节和非季节性单变量模型的极大似然估计
- e/ X- U0 Z+ G9 ^3 c: w6 YArithmetic grid paper, 算术格纸
6 O h7 \3 _! D+ Y9 ?Arithmetic mean, 算术平均数4 d R6 N) i" h9 A
Arrhenius relation, 艾恩尼斯关系
2 y4 f5 a2 v) n# s- }! m6 E) o* O6 eAssessing fit, 拟合的评估0 ~5 }4 l& J# Y9 g% f
Associative laws, 结合律
" F" b, n1 x9 A, J! p+ `6 V5 J* KAsymmetric distribution, 非对称分布& I8 T% x) S; B E
Asymptotic bias, 渐近偏倚9 Y- Y, M. B5 y3 J8 ?5 I/ a( w
Asymptotic efficiency, 渐近效率
o, g/ L/ N. c$ mAsymptotic variance, 渐近方差2 A0 E2 a6 m* Z6 H
Attributable risk, 归因危险度
6 B- i# o& J5 j* Z7 M9 PAttribute data, 属性资料
+ X! j. C& u! b" ~Attribution, 属性0 V( A4 o2 D7 ?
Autocorrelation, 自相关
$ c' N4 F C( D" y+ q$ PAutocorrelation of residuals, 残差的自相关# h' h8 j" H2 l. j& o) L
Average, 平均数
* \* s# {( P8 Y( t4 a& Q3 oAverage confidence interval length, 平均置信区间长度; m& t1 E8 E4 s6 ]7 J: _; C
Average growth rate, 平均增长率
+ b6 q/ |9 A4 X/ b ABar chart, 条形图 }. H+ ~ r o+ f, w4 J
Bar graph, 条形图9 x+ ]) m) }$ F7 I: r0 Z2 `
Base period, 基期+ I# m2 ]) A/ ^3 S6 N% m0 U1 l
Bayes' theorem , Bayes定理
8 R8 L3 S7 b* `8 w3 x0 kBell-shaped curve, 钟形曲线- Z& a6 m. S* W
Bernoulli distribution, 伯努力分布$ ~/ F# f! K* s& _% Y7 I! s) U1 n& w
Best-trim estimator, 最好切尾估计量7 e J$ P5 g7 p$ _
Bias, 偏性; ~7 L- O2 |9 T& ? A- n/ L
Binary logistic regression, 二元逻辑斯蒂回归
, Q K$ P8 N! o V$ U: BBinomial distribution, 二项分布% h i E) q. ~& {% H* G+ c
Bisquare, 双平方8 R. G6 s f5 D
Bivariate Correlate, 二变量相关
; i! N2 T% \7 X' bBivariate normal distribution, 双变量正态分布; w! z6 s9 f H/ u4 h7 K/ W
Bivariate normal population, 双变量正态总体
7 u7 ?. j* r( G+ t' RBiweight interval, 双权区间0 ]& R, J1 j* E) n3 A! t5 \
Biweight M-estimator, 双权M估计量9 v, a1 G' z8 c, Y0 ^; N$ Y
Block, 区组/配伍组" x% h/ E! i! i5 X. }
BMDP(Biomedical computer programs), BMDP统计软件包
1 ^( d6 p" k( \ D- b. ^8 z3 R* }Boxplots, 箱线图/箱尾图4 @$ \1 C9 p7 b6 Q2 {# j) l, N
Breakdown bound, 崩溃界/崩溃点% [9 L7 U) O( A' W0 i
Canonical correlation, 典型相关6 n) _% K1 a# w0 N- ^, p
Caption, 纵标目5 i; h4 h5 ^2 M6 u9 J
Case-control study, 病例对照研究/ k& g9 ]6 b, I) L. o' b9 r
Categorical variable, 分类变量
3 k/ n1 j$ d( X! l& qCatenary, 悬链线
1 H, `7 r) A, y- _2 {Cauchy distribution, 柯西分布
, S. ~9 z' L$ D& KCause-and-effect relationship, 因果关系9 r# Y* Q$ q( o: S( i9 f
Cell, 单元8 v2 d, f. a* T" U/ Q4 q7 }2 \
Censoring, 终检
" j1 C. Q6 T% R6 K- e$ N7 OCenter of symmetry, 对称中心# {! [$ W3 s" e5 O* I
Centering and scaling, 中心化和定标# I7 `6 i: n" |. w0 C0 j
Central tendency, 集中趋势' b' X% h: q- Y0 s$ f
Central value, 中心值9 ]5 T8 g5 V; P7 n) Y. p
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测4 K% G5 x9 W, u4 a* z
Chance, 机遇! F3 x2 K( Q1 L
Chance error, 随机误差
" r4 h/ W$ L5 Q5 S+ ^! I$ q* y/ b" vChance variable, 随机变量
6 j. G, t; p1 I8 u. t* N/ u7 NCharacteristic equation, 特征方程" D1 a$ f2 ], Y9 H
Characteristic root, 特征根& L% o6 y! c# r- V! c
Characteristic vector, 特征向量
! g7 \% D( B6 d4 F$ ]& d3 E" I. lChebshev criterion of fit, 拟合的切比雪夫准则( ]4 E2 f& ?; @' b# W" D; c4 x
Chernoff faces, 切尔诺夫脸谱图
& |, R) c3 c# vChi-square test, 卡方检验/χ2检验! N. C0 Z. C( g, s9 t
Choleskey decomposition, 乔洛斯基分解2 y% P0 ~* y, o! I
Circle chart, 圆图
/ w, i1 f. t6 X" K3 e) @9 cClass interval, 组距
8 c) h0 O: g# a9 i7 yClass mid-value, 组中值
& n1 G& e ]% q" R! |Class upper limit, 组上限
& K' ?/ C+ o3 Q. J; `Classified variable, 分类变量
& _ Z1 x3 q- ^5 d0 j1 P ^1 A' t( VCluster analysis, 聚类分析
! N! W& i7 x1 i" }. B1 [! Z: wCluster sampling, 整群抽样( J9 l5 G" S; n8 m
Code, 代码
5 U. f( v' i3 }. ~- I- wCoded data, 编码数据0 _( C9 h- i2 k* B% N6 Y: z Z# t' E
Coding, 编码! y: m- n; P6 I! a
Coefficient of contingency, 列联系数
& A5 {( `8 R% m6 n; OCoefficient of determination, 决定系数
6 V+ F( B% u% }; KCoefficient of multiple correlation, 多重相关系数4 `1 k/ B7 ~2 R$ b
Coefficient of partial correlation, 偏相关系数 @; m" x4 H- ^% W! \( L$ M$ D( d" A
Coefficient of production-moment correlation, 积差相关系数' D* K0 G$ I2 D6 Z
Coefficient of rank correlation, 等级相关系数
6 U* y# u1 b4 H' _. r# @4 u( {Coefficient of regression, 回归系数- z! l$ a, W! d
Coefficient of skewness, 偏度系数
+ |, H/ S9 l [/ q+ \Coefficient of variation, 变异系数
) Q, K( S7 @. I, ?Cohort study, 队列研究# g3 r' g9 T/ M/ A' g& w
Column, 列% P4 F+ c* w/ t9 H$ o
Column effect, 列效应 A% l/ [$ Q5 V) U7 |/ |% T
Column factor, 列因素! l; K* L5 I5 ]6 [
Combination pool, 合并
- C! i+ [" Y+ i1 w, dCombinative table, 组合表7 W% e u+ U8 p+ W1 @5 ?, {+ \' A, B
Common factor, 共性因子2 }' J( Z. x' C, q- d4 k B7 _
Common regression coefficient, 公共回归系数* i9 Y: L. `4 c$ H7 z. ]
Common value, 共同值! G4 H; X: e8 I; d* [
Common variance, 公共方差
1 X0 l6 k H4 z, j+ w! @, N% jCommon variation, 公共变异3 |3 g# h1 Y' F
Communality variance, 共性方差
7 h1 n0 Z7 l! YComparability, 可比性
% k& z* ?- u, j* a1 X9 A& X( pComparison of bathes, 批比较
" b( I* v8 p. }( B; [+ `3 y' sComparison value, 比较值% V F7 j( z6 A" @) {5 L* i+ Q
Compartment model, 分部模型
) L2 E1 v0 b; C1 d# lCompassion, 伸缩, ~$ o% n6 l7 M3 ~8 ~7 P
Complement of an event, 补事件( i$ ?: }& H! R$ e2 G4 S5 q+ q7 v
Complete association, 完全正相关
" U6 B- u0 g" _: RComplete dissociation, 完全不相关& O/ d; I5 z5 w: G* a5 ?" P
Complete statistics, 完备统计量
- Y7 M/ V8 ^# ^1 c2 b( \Completely randomized design, 完全随机化设计
5 W% k) a! U# X' E: J: `# rComposite event, 联合事件2 x% I B9 D# L& \, X1 C1 M
Composite events, 复合事件
/ B7 J' R3 j5 X4 r. HConcavity, 凹性( m0 Q5 a! k5 ?. h/ N
Conditional expectation, 条件期望
6 s9 r) c$ L ^' B5 |5 M/ _Conditional likelihood, 条件似然8 @: e- Z. Z0 U' |
Conditional probability, 条件概率
) K% Z1 C- {* }0 x! l SConditionally linear, 依条件线性
# {8 l8 _* ~- I& e( w NConfidence interval, 置信区间
1 L# n, y. E) T5 `# O# Y1 m9 ?9 k* D% A oConfidence limit, 置信限
5 _3 n1 b- A$ v# R% kConfidence lower limit, 置信下限! Z. r8 m$ i% `2 f
Confidence upper limit, 置信上限3 o5 z* v, C) y- d3 \, I% z$ r
Confirmatory Factor Analysis , 验证性因子分析) ]; s, _/ y; T) F, E
Confirmatory research, 证实性实验研究
" s7 I0 ~: k! n/ B6 {Confounding factor, 混杂因素1 [# ^9 j7 \( _: {2 n% S
Conjoint, 联合分析
7 A# t5 z% P& TConsistency, 相合性
3 Q `* x+ `1 x5 QConsistency check, 一致性检验; L! A/ V7 b- f" y! H
Consistent asymptotically normal estimate, 相合渐近正态估计
) P& P, j) h- A5 lConsistent estimate, 相合估计0 B/ ` s5 e) e4 A/ w
Constrained nonlinear regression, 受约束非线性回归
1 [5 `! ?: R/ O# r8 j7 Y" v) }Constraint, 约束: Q, [/ E! h& y$ O- Q; I% b
Contaminated distribution, 污染分布, F0 [5 j' L6 N6 {+ D
Contaminated Gausssian, 污染高斯分布
8 q2 I4 i2 n1 p, }Contaminated normal distribution, 污染正态分布4 | Y* V8 H% p
Contamination, 污染
; ~+ T* B' U, }; e1 rContamination model, 污染模型) e6 s2 n3 x1 k
Contingency table, 列联表
& s6 O- _ Y" G' V G; X# a( }Contour, 边界线
5 L( D( U3 Z& @5 p" @Contribution rate, 贡献率
+ n* i' k* w; ~" h) L+ J/ OControl, 对照
; W! H+ Q1 K4 V- NControlled experiments, 对照实验
6 E8 v! `! x2 K5 QConventional depth, 常规深度) p5 ]/ Y% I6 j; Q$ {
Convolution, 卷积' {1 E; V c& p( [( H4 X- o% \
Corrected factor, 校正因子
- b' D! X2 ~. R6 |2 p, ECorrected mean, 校正均值
: B/ R. R) e8 t) y* c8 F6 V. r1 A( dCorrection coefficient, 校正系数7 D# D4 `! {& u% V
Correctness, 正确性$ l2 x% h) W- O# U
Correlation coefficient, 相关系数! D$ n0 a: ?& _! v
Correlation index, 相关指数( e+ [2 k' @8 |5 V! `+ [
Correspondence, 对应
. @* j; A: ~; w* j0 VCounting, 计数8 e+ Q: i4 L8 K- j N
Counts, 计数/频数0 K) l1 C+ x( ~5 `
Covariance, 协方差- h; N; P2 U) @8 b0 }' ]3 R
Covariant, 共变
- b- U$ T- R( B9 v4 q P* t) MCox Regression, Cox回归# S) c9 L/ [+ n
Criteria for fitting, 拟合准则
& B$ ^8 t! ?1 w7 o9 @ q. SCriteria of least squares, 最小二乘准则
1 L3 B* M( B1 E6 q" ZCritical ratio, 临界比$ Y/ |$ D& o( H- d
Critical region, 拒绝域
! K4 I7 c1 e7 dCritical value, 临界值, {$ |5 v$ [, B8 _; u
Cross-over design, 交叉设计
) y8 m; w. `" o% X( ^4 }% ]Cross-section analysis, 横断面分析7 R/ ]+ V, r3 M0 T* h
Cross-section survey, 横断面调查
- ?, y& N5 d& VCrosstabs , 交叉表
+ b/ z& n! ^( @Cross-tabulation table, 复合表6 _2 E/ a0 ]) N. [- p5 t' P
Cube root, 立方根7 T, P7 j5 G5 B1 ?2 x. a
Cumulative distribution function, 分布函数0 N z8 {" \6 _* m1 g
Cumulative probability, 累计概率
1 ?' f2 t8 S4 ` ~Curvature, 曲率/弯曲! X# G- s: h4 ?
Curvature, 曲率
. }4 Q) y0 N, j7 M; j P/ }- VCurve fit , 曲线拟和
4 A# V4 }7 h0 ?& J+ j- o4 b# iCurve fitting, 曲线拟合
, n# ^' K( p2 z3 S5 r/ nCurvilinear regression, 曲线回归- j6 W `8 @) v4 w7 A% _6 T* X( [
Curvilinear relation, 曲线关系
9 h1 a6 v& Y( F# X7 @Cut-and-try method, 尝试法
( Q, F: o& [' x* ^$ RCycle, 周期
4 g7 X/ l3 U( d( A, hCyclist, 周期性
2 K) f& l2 [& ]! sD test, D检验
* v9 f2 p& \! oData acquisition, 资料收集# Q8 I7 k) n, C+ z e
Data bank, 数据库
' [( O: T6 B$ Z; {. s" cData capacity, 数据容量7 P% h% w) w3 f/ D2 `4 ?: S) \
Data deficiencies, 数据缺乏 ?% X( q; Y3 f3 J
Data handling, 数据处理
6 F3 o3 I5 @$ V8 @) |& RData manipulation, 数据处理2 x& b& f; K) ~+ m
Data processing, 数据处理, ?% p6 f* V- W
Data reduction, 数据缩减
0 k* r! k% Q+ V4 L' qData set, 数据集
7 @6 o) R# J+ H* zData sources, 数据来源6 C, q5 |7 S9 b4 Y6 ]$ ]
Data transformation, 数据变换; d6 ]9 v2 X: v2 {6 L
Data validity, 数据有效性
3 n$ Z$ _2 k- X. x' f* h3 _Data-in, 数据输入# j; d: `8 }+ V, L1 y
Data-out, 数据输出 {9 I8 y$ I. _' \% g' f8 Y1 ^
Dead time, 停滞期% y1 U6 r+ J9 k# |' P
Degree of freedom, 自由度2 f9 h# `7 |( Z) i* {, |
Degree of precision, 精密度8 N2 G( C: I; O
Degree of reliability, 可靠性程度
' }3 @4 Q- m O* p) MDegression, 递减9 d& [# i: f* y7 ^' P
Density function, 密度函数8 }4 _& y3 B" e3 b& @
Density of data points, 数据点的密度& A0 B5 b7 o; m6 R6 G$ ?
Dependent variable, 应变量/依变量/因变量
1 F1 ~# Q3 i* ^Dependent variable, 因变量
! |' [. @2 Y2 y' f3 C3 h1 h2 WDepth, 深度5 r% W) X( K5 r5 v
Derivative matrix, 导数矩阵
4 |7 G% [% T2 \& Y9 ]4 L1 o ?Derivative-free methods, 无导数方法
9 z. M* a6 q' u9 SDesign, 设计& P# }4 ~3 ?6 K, V/ P+ W( y
Determinacy, 确定性
# w) B2 l, e% ?: TDeterminant, 行列式
7 P$ V% r% C# s8 _( j( m5 ^0 FDeterminant, 决定因素# O5 k- @4 B: X' C5 X. \
Deviation, 离差
) {' l9 U! {0 n# e+ T* R6 Q( P$ f+ HDeviation from average, 离均差$ H. j* k& w6 { n$ x, B, f
Diagnostic plot, 诊断图! {7 K0 _! C# \% G! A
Dichotomous variable, 二分变量7 `3 U- k- b% E# a$ M
Differential equation, 微分方程
- A' @- ~4 a$ n, Y9 K' M' bDirect standardization, 直接标准化法
# x1 d" Q' W& LDiscrete variable, 离散型变量6 E, o _' R3 \, e- n
DISCRIMINANT, 判断 , S( V) q3 D. g4 T% z
Discriminant analysis, 判别分析. {' e' H9 a% l z i6 y2 K
Discriminant coefficient, 判别系数0 j: W+ i* M- `7 ]
Discriminant function, 判别值
1 `% z4 }6 R& N. a# A2 r& E! wDispersion, 散布/分散度
5 E S1 _7 D* t' R2 N, G0 GDisproportional, 不成比例的
6 V( y! h( y) g4 z; G# {% @# X0 cDisproportionate sub-class numbers, 不成比例次级组含量 K6 O7 m; N) W9 E
Distribution free, 分布无关性/免分布
1 Z8 i3 j( C0 u8 c/ b9 s( b5 tDistribution shape, 分布形状
; V- h- c+ |# ?9 J' _Distribution-free method, 任意分布法
3 f' A A& H% H( {! o' Q9 IDistributive laws, 分配律
# o6 {3 Z# `/ I6 D* }8 Z6 s3 VDisturbance, 随机扰动项
( {8 v& z( K$ a8 gDose response curve, 剂量反应曲线5 e _- c3 e, j$ a q
Double blind method, 双盲法, ?6 Y7 H! P8 L# R- A0 O* J% |
Double blind trial, 双盲试验
( C1 T- w. Q6 K3 ?* \2 s4 W9 mDouble exponential distribution, 双指数分布
0 X1 x; x/ d' c+ P9 C$ J# VDouble logarithmic, 双对数
3 Q# M! h1 T, }* r6 _9 h! VDownward rank, 降秩" A5 q# e: O6 D) I
Dual-space plot, 对偶空间图
2 y% z, k; k8 f! i0 T9 T" mDUD, 无导数方法
3 d* q* @! ?/ b! b% G& QDuncan's new multiple range method, 新复极差法/Duncan新法! T6 g7 N! X- f" r. E% V; ~$ z! q
Effect, 实验效应
' u0 |7 h4 K2 x" j$ p% T3 _8 ]$ ZEigenvalue, 特征值' ]) P& ?; x' O' s- T
Eigenvector, 特征向量
, H3 u8 x" ]. ]9 ]7 HEllipse, 椭圆
6 X' f/ k! _5 q) EEmpirical distribution, 经验分布" w. I- `9 h% W9 Q! t
Empirical probability, 经验概率单位( Y% p2 K& X6 t1 v: C/ ~8 D' z
Enumeration data, 计数资料
- V- M! b# X/ i; b) n* dEqual sun-class number, 相等次级组含量 l5 g, A6 }0 i7 U& g2 ]3 Y! n
Equally likely, 等可能/ f; C' G1 O2 Z- x* W6 _
Equivariance, 同变性
5 T) V) }" z$ h3 C9 x( }# T. CError, 误差/错误5 A7 E) A) B; a+ ^2 g
Error of estimate, 估计误差
1 X5 [9 t: ]9 R# ~$ E2 P% T+ sError type I, 第一类错误
3 n! y: K6 X: Y6 R/ l4 K! k/ OError type II, 第二类错误" m- W, P' N8 y6 G& N+ N
Estimand, 被估量
" a ~9 h( f( k' k4 N( @$ d! xEstimated error mean squares, 估计误差均方! [; v' i2 i5 T0 y: O4 n' A( |
Estimated error sum of squares, 估计误差平方和% c" d! \; D7 D6 T) }! W
Euclidean distance, 欧式距离
4 {1 O- a7 O/ n# H/ Y3 l1 IEvent, 事件. c/ x( N# m Q* y" y" I; B4 m
Event, 事件 h6 d$ O' ]% {
Exceptional data point, 异常数据点/ T- p* r3 i6 [6 |; d- l* i& F) A
Expectation plane, 期望平面) W: _: s V9 }, s5 T
Expectation surface, 期望曲面4 z( B8 U$ T' [. `" l( |- E2 s
Expected values, 期望值! |1 J& i! V7 w: q6 d9 _8 {8 p
Experiment, 实验* U6 f6 G& H" v3 ?# s
Experimental sampling, 试验抽样5 p) g3 {1 U5 |+ L
Experimental unit, 试验单位1 b: @5 V: F7 z0 L* Z+ O
Explanatory variable, 说明变量0 g6 @( V2 V% ^+ {7 K- I7 a, D
Exploratory data analysis, 探索性数据分析
8 S% ?' _- H R ^Explore Summarize, 探索-摘要
. a# k6 |8 Q( Q2 m: T3 p& }" C- |Exponential curve, 指数曲线* |. g1 l H ?3 C9 b; e I& H7 V9 O
Exponential growth, 指数式增长; U _" B3 E0 s. c
EXSMOOTH, 指数平滑方法 ! i) Y) L) {) C; e. l) ~
Extended fit, 扩充拟合' E8 E( _8 `7 q! p
Extra parameter, 附加参数( |( E9 d' B' \( K- K
Extrapolation, 外推法
6 A! [7 W: B- Q# h9 Z! d$ I" nExtreme observation, 末端观测值
% J$ T% r8 T9 A+ M" q/ |! a" t {8 J8 {Extremes, 极端值/极值
8 W+ g/ J( S4 `F distribution, F分布
+ o) |0 A/ S& Z4 ZF test, F检验& ^/ B: l, X! ~
Factor, 因素/因子9 Z2 K% l. x! L5 h% N
Factor analysis, 因子分析
$ W d$ d1 n! G8 I1 l; A# j. CFactor Analysis, 因子分析
* ^. K' ~/ b, ?* ?% GFactor score, 因子得分 / }. b0 l: u7 H: C9 {
Factorial, 阶乘/ R( S: j/ T/ ^9 ^
Factorial design, 析因试验设计; J' r7 ]' _# R
False negative, 假阴性
9 U2 |& P# s! u- b+ LFalse negative error, 假阴性错误
: Z5 k- S' ?3 pFamily of distributions, 分布族
2 I" j$ t5 \7 i$ @" Q7 e, UFamily of estimators, 估计量族
+ H& p0 Y9 \* {( p. t1 L$ L2 a$ vFanning, 扇面
9 k3 h7 g/ t+ l9 {Fatality rate, 病死率
* }; C# ^9 T# n5 zField investigation, 现场调查: T" ^) }4 q$ o3 u9 U' G5 W- p C
Field survey, 现场调查3 n; z& L0 t$ F
Finite population, 有限总体
) X3 N3 s) E9 H7 P( OFinite-sample, 有限样本
g/ b I5 \! E# ~$ EFirst derivative, 一阶导数
1 e# N0 q# U' P3 |" r; zFirst principal component, 第一主成分2 t7 l1 C' g! m+ m" j# x
First quartile, 第一四分位数$ M: H. M; S7 m- } O0 N
Fisher information, 费雪信息量3 `5 c# g* C# }6 L7 Z$ ^
Fitted value, 拟合值
1 |0 J( E: Y& ~, R( BFitting a curve, 曲线拟合- `8 X' r9 e' Y1 I3 D
Fixed base, 定基0 b9 d8 ?" W" }/ m$ E: `
Fluctuation, 随机起伏
/ p9 u1 x7 B9 \, C3 E6 E/ fForecast, 预测
1 K$ B: ` M- h% Q' p. U! R8 EFour fold table, 四格表
, `, A# j- U( h3 |+ lFourth, 四分点
+ o5 O6 h+ o* d8 ZFraction blow, 左侧比率
5 C/ R) [5 I: p: RFractional error, 相对误差5 T& k9 m9 `$ M' d' ` X
Frequency, 频率
; j% z, r. a, b+ X% U7 a' H, bFrequency polygon, 频数多边图5 n+ t' d# d, E
Frontier point, 界限点& {( z. A a- h" X2 P- P
Function relationship, 泛函关系; q8 U4 N" D1 i4 ~1 P
Gamma distribution, 伽玛分布
% i% z6 F& J9 i( W6 N; e7 @Gauss increment, 高斯增量: M- B4 G. C& A1 H$ T+ V- c2 C
Gaussian distribution, 高斯分布/正态分布
) p6 X7 r$ `" I0 f% B2 JGauss-Newton increment, 高斯-牛顿增量
b1 _5 S6 S7 L3 M- aGeneral census, 全面普查
2 H B% A, t2 `4 p$ kGENLOG (Generalized liner models), 广义线性模型
6 \3 G+ ?) C$ C. c* \* i5 ~Geometric mean, 几何平均数: q4 Y4 ^& z! p! N
Gini's mean difference, 基尼均差* E$ M$ b* j' S
GLM (General liner models), 一般线性模型 3 F ]& l; z2 a, g0 ~4 G$ k/ I' Q
Goodness of fit, 拟和优度/配合度
6 {0 b, l- Z: a5 uGradient of determinant, 行列式的梯度
/ f- k( j+ m* c4 p+ dGraeco-Latin square, 希腊拉丁方
, I Z, \" ^6 d' oGrand mean, 总均值
% G: x, E* ~# X |; D9 BGross errors, 重大错误
; E, L7 ?* i- L' H7 {0 v( nGross-error sensitivity, 大错敏感度
! C3 \ R4 U& P! l/ S: jGroup averages, 分组平均
, f9 y) H5 Y) h6 P6 C; H4 jGrouped data, 分组资料
( o" {' u' q4 @0 F" U5 Z) RGuessed mean, 假定平均数0 U6 {1 k$ r% e0 B/ o3 P
Half-life, 半衰期
3 r4 Z2 n3 Z- j' M. u' h: rHampel M-estimators, 汉佩尔M估计量 x" D# Z5 y8 ?* Q
Happenstance, 偶然事件
7 e7 N# x4 F# f& x4 LHarmonic mean, 调和均数
' A+ O3 g1 V2 {5 _- Z7 qHazard function, 风险均数. v+ W J2 [( R+ @. V
Hazard rate, 风险率3 p; F# N3 x# W4 Y6 C- I
Heading, 标目
6 X8 {1 e6 ^' q8 G4 iHeavy-tailed distribution, 重尾分布% `9 m' R1 O: ^/ f& G% W
Hessian array, 海森立体阵
# L, P1 K- |1 K2 D- Q" o$ M lHeterogeneity, 不同质( q! V- M) b9 G. E _8 P4 ] A) ~9 Z
Heterogeneity of variance, 方差不齐 5 t1 o3 f/ {/ \; d' u. |
Hierarchical classification, 组内分组
) K: l' Z. }% Z! n6 P8 a# y4 u+ i9 ZHierarchical clustering method, 系统聚类法
( n3 N1 ?6 c* u% BHigh-leverage point, 高杠杆率点! T' \ {; ]0 f/ N/ h+ K! y
HILOGLINEAR, 多维列联表的层次对数线性模型 \. P, F8 P" G+ ?2 M5 r: }
Hinge, 折叶点& _9 Q, G5 m9 E: `; K
Histogram, 直方图1 A% T; t/ L S& A$ @# M
Historical cohort study, 历史性队列研究 * e/ i$ l# z3 z1 C9 \
Holes, 空洞
$ \- w( w' W0 ?; U$ d4 m% KHOMALS, 多重响应分析) G. v. ?" v9 Y$ A7 e p' B
Homogeneity of variance, 方差齐性$ H i8 s! f% }; j( D. A" a/ l
Homogeneity test, 齐性检验
0 K) X8 F0 h3 r; bHuber M-estimators, 休伯M估计量
$ U$ f6 B8 Y9 J- m: f8 _ V- GHyperbola, 双曲线
9 h( ~0 F9 K0 s6 ~. z8 d; y+ \# KHypothesis testing, 假设检验4 _2 o8 V' p" e W
Hypothetical universe, 假设总体
. N6 ?+ [5 Q8 U+ oImpossible event, 不可能事件) r% r' a+ O% x9 U. J# i7 {
Independence, 独立性
4 `' i, Q. G$ ]' f3 ?Independent variable, 自变量& d# `; W4 I- R \# g+ l8 n* i
Index, 指标/指数& [* L: ~' O; L5 W7 u0 j3 c( Y* o
Indirect standardization, 间接标准化法' B9 \) _7 a( M0 t- W/ d
Individual, 个体
/ H3 Y, i8 b2 wInference band, 推断带
* e' B' |8 x- y( Q' q! c, q/ ~( e2 pInfinite population, 无限总体& n" _) |" V3 C8 j. z. O
Infinitely great, 无穷大: N X6 R! y9 [, Q
Infinitely small, 无穷小4 X( l& W5 c: c: A- o, J F. y
Influence curve, 影响曲线3 L8 ]- u% D7 ^9 |6 j
Information capacity, 信息容量( J/ g& b" R6 l3 z! I. E; u
Initial condition, 初始条件 A# h# ]/ N! ^6 c" S) ^, C) h
Initial estimate, 初始估计值
% @* D) ]) W# \+ G5 r1 I( C2 ^Initial level, 最初水平
7 [/ F; R% F2 A& ?: J$ Z bInteraction, 交互作用
/ a: {& [0 s) n3 R) L/ HInteraction terms, 交互作用项4 W2 ^7 f1 O! Z N( T ?
Intercept, 截距
$ o- }2 C; A( V( iInterpolation, 内插法* \! c/ ^) F. [* g& p6 D
Interquartile range, 四分位距7 }$ r# y. }9 T, I& g
Interval estimation, 区间估计, b, ?, C4 j o! k
Intervals of equal probability, 等概率区间& @* Z& z# c N1 U
Intrinsic curvature, 固有曲率
: w4 n4 _3 A' tInvariance, 不变性$ \% @. j5 [0 g( G3 ~ L
Inverse matrix, 逆矩阵
0 C, h7 V( q, |Inverse probability, 逆概率
8 I$ H; m6 g( A. JInverse sine transformation, 反正弦变换" p2 R, k7 U* [" Y
Iteration, 迭代
; z! B: t( }6 ~& c: E! P- K% A, lJacobian determinant, 雅可比行列式) h- Q- c% m0 m
Joint distribution function, 分布函数5 y# O4 k9 i i$ P5 n1 s* K
Joint probability, 联合概率+ ^8 M* m$ z0 ~/ O# |' j
Joint probability distribution, 联合概率分布
4 @ g8 u$ l% b; o& \) UK means method, 逐步聚类法3 D4 i1 a( N1 O2 v
Kaplan-Meier, 评估事件的时间长度
; ^7 c6 g6 H2 S+ l. h) Q; f! k5 ?; ^Kaplan-Merier chart, Kaplan-Merier图
: N$ I H$ b ~5 jKendall's rank correlation, Kendall等级相关
( d' P2 X) U5 ZKinetic, 动力学
2 `) n* `! C7 SKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
. q' D' B3 f; O3 j* HKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验% f- x, }; _& ?; n. U9 k
Kurtosis, 峰度' i7 I, S# ` H+ B3 o2 I; [( R
Lack of fit, 失拟
; |( ]& s) ]' h% ]9 VLadder of powers, 幂阶梯
. i% q0 T6 `) m' [* { LLag, 滞后
7 d) L2 F7 w% C: ~6 b: r2 |' Q, ^+ WLarge sample, 大样本
9 y! w7 e- f' S6 w1 F1 m. ILarge sample test, 大样本检验
$ J0 H3 P& W' G" a ]Latin square, 拉丁方
) r! y _5 A" O7 `Latin square design, 拉丁方设计
' z5 L" _& F- LLeakage, 泄漏7 H3 z! p) @. B. `5 X5 y, r
Least favorable configuration, 最不利构形
( C `' [" b( G2 V6 @Least favorable distribution, 最不利分布5 I6 l6 q5 [, Y
Least significant difference, 最小显著差法( q: w1 `0 V5 f6 o: }9 E
Least square method, 最小二乘法
& c- E6 m. J) y" V6 C) NLeast-absolute-residuals estimates, 最小绝对残差估计, q7 C) B0 J# n" x0 w
Least-absolute-residuals fit, 最小绝对残差拟合
$ p1 C' ?1 B% I7 N9 |Least-absolute-residuals line, 最小绝对残差线
1 D0 g* M+ h' x9 E" {. dLegend, 图例
- [8 V; Z! a! | g6 LL-estimator, L估计量
* d7 \/ g/ u" S; h2 f! ~6 UL-estimator of location, 位置L估计量" S C3 b. |) c& e, a3 e- |; D
L-estimator of scale, 尺度L估计量9 q- }* }, v5 @+ i
Level, 水平& ~; @9 d! s" ?
Life expectance, 预期期望寿命
& J9 W: ?1 F) y0 m. d+ @9 l& G$ JLife table, 寿命表
) g5 G9 C. Q! n! X7 zLife table method, 生命表法
# y+ o6 y" V [: k" ]/ PLight-tailed distribution, 轻尾分布
( E8 d) S, e2 |( w, TLikelihood function, 似然函数7 K! c& L1 r0 }1 C! [% d
Likelihood ratio, 似然比
4 F/ c/ W% s9 @/ `line graph, 线图
7 P; v1 C0 q$ j6 @* r# N# jLinear correlation, 直线相关0 W9 ?1 V. s2 Z
Linear equation, 线性方程& G8 h; J- i2 u( q( e
Linear programming, 线性规划8 j$ U) J9 T* ~( p5 x
Linear regression, 直线回归; D$ k9 F, L, z3 _0 i3 v
Linear Regression, 线性回归
- ?9 |! U+ `; }! [7 RLinear trend, 线性趋势
6 R: `0 m2 @9 H8 Z# D5 HLoading, 载荷 & O L/ m% {* s4 P |
Location and scale equivariance, 位置尺度同变性
$ V/ d7 Z2 R6 g* Y$ t" d) b1 JLocation equivariance, 位置同变性* G, `. v, P/ b1 T* {: s
Location invariance, 位置不变性8 `; e4 h/ x& F; F1 d/ `5 L! j
Location scale family, 位置尺度族, |' @' n4 w" A$ b
Log rank test, 时序检验
4 u: ^. Y# E+ ?# T' G* U2 a% ]$ M4 OLogarithmic curve, 对数曲线/ q) l8 `: A; f2 l% l" W% d
Logarithmic normal distribution, 对数正态分布
8 r* T. P! v* uLogarithmic scale, 对数尺度
7 f8 @" B( G$ TLogarithmic transformation, 对数变换; W0 O- p' y9 p, E0 ~* T
Logic check, 逻辑检查
/ F( d0 Q" b0 Y1 e# n' RLogistic distribution, 逻辑斯特分布
9 L5 h+ f/ d+ C- Y7 X# OLogit transformation, Logit转换, R5 ?/ j- ^/ x( N' f- I% y
LOGLINEAR, 多维列联表通用模型 - w x8 e9 \0 u1 T6 l* b
Lognormal distribution, 对数正态分布
0 a2 d) O8 K1 D7 {5 r7 aLost function, 损失函数
5 l$ g, i1 n. DLow correlation, 低度相关
% f5 _. u) Y( L: ^3 B+ Q; `. }# i' CLower limit, 下限
$ k) _0 ^$ _# Q; W B, ^Lowest-attained variance, 最小可达方差# I. G9 L( g# ~; R/ T1 K
LSD, 最小显著差法的简称. B3 n' R) I9 g4 J- {2 D
Lurking variable, 潜在变量+ _4 Q$ Q6 P/ C9 L$ R- B+ Q
Main effect, 主效应
/ U& {/ P/ w" s# M* J3 u# ~8 o6 lMajor heading, 主辞标目
2 T* E: `0 K& v X4 M) ?+ T6 ?! PMarginal density function, 边缘密度函数5 d# t2 I! h7 [& ~2 B( ]; J: s
Marginal probability, 边缘概率1 V9 N6 \2 m' r4 ~7 v3 \& k
Marginal probability distribution, 边缘概率分布 Z+ T) @+ f" T3 @" |
Matched data, 配对资料 |1 O. h/ D# X9 W2 t2 B) a. I0 e6 n5 t
Matched distribution, 匹配过分布( {/ g+ u; b9 N
Matching of distribution, 分布的匹配
`4 G! X2 i! v/ b5 G$ s" G7 X5 NMatching of transformation, 变换的匹配
, | t7 l5 j& i) i9 B) yMathematical expectation, 数学期望
+ h; j$ Z, v" L; s4 J: K9 ]1 A$ OMathematical model, 数学模型
) _ u4 I7 z7 E, v: XMaximum L-estimator, 极大极小L 估计量
# E& k& y9 ` ]4 Z5 i( i7 nMaximum likelihood method, 最大似然法" x- G _3 @' d/ A) D* H
Mean, 均数1 x5 S* H- D1 S% C B( ]
Mean squares between groups, 组间均方* X4 ]9 ?& v5 Q j6 |" n y
Mean squares within group, 组内均方
$ P$ r7 a4 {% d' TMeans (Compare means), 均值-均值比较6 C' K( T% o4 f/ D: P
Median, 中位数& x6 z6 H( G' b& [7 t8 V8 {' w; K
Median effective dose, 半数效量' A9 Y* W e6 e, c2 H. z
Median lethal dose, 半数致死量3 D5 ]7 e4 r/ Q8 r1 L
Median polish, 中位数平滑
& b) x8 v# b, K' B3 Q+ L* k* Z1 JMedian test, 中位数检验
7 r" g- P2 g) J- uMinimal sufficient statistic, 最小充分统计量/ T: J3 K* U; s# o7 w) \+ A
Minimum distance estimation, 最小距离估计8 T. J9 y* R& I* ~
Minimum effective dose, 最小有效量
# G, q9 \7 z" X: b# _Minimum lethal dose, 最小致死量
7 X4 H6 \, f4 z( IMinimum variance estimator, 最小方差估计量
& f! G h5 g( k% U% U% f9 d# eMINITAB, 统计软件包9 H! [, {/ W3 [
Minor heading, 宾词标目
$ r, S' r. b1 uMissing data, 缺失值
7 ]7 W+ X% P+ B* S2 A) PModel specification, 模型的确定
8 ^8 M1 ]' g. S& o3 y% D$ h5 qModeling Statistics , 模型统计
# E: G1 O8 `8 m' n& ^Models for outliers, 离群值模型# o( [$ [; B. |* K( J
Modifying the model, 模型的修正
0 \* }! j# o6 m1 Q! AModulus of continuity, 连续性模
+ `+ e4 E; _% O3 hMorbidity, 发病率
; I. \; N+ A* ?Most favorable configuration, 最有利构形6 N7 n; @+ y9 B/ ~* a* |; |
Multidimensional Scaling (ASCAL), 多维尺度/多维标度& M$ j# @: s6 B1 \. q+ a, O
Multinomial Logistic Regression , 多项逻辑斯蒂回归' G; \: U4 Y+ C) f2 ~! t
Multiple comparison, 多重比较
9 Y4 h8 ?5 I% O. A: {Multiple correlation , 复相关
. N0 e+ D4 R& i8 A$ B8 mMultiple covariance, 多元协方差# B0 O6 f3 M0 E/ p: S
Multiple linear regression, 多元线性回归& Z6 I8 k& ?0 @+ _% b9 Z6 M
Multiple response , 多重选项
& J* d# {7 U+ `' t- C3 `4 e# dMultiple solutions, 多解
- i& ]; B. a- z/ A+ oMultiplication theorem, 乘法定理0 ^/ O/ @0 _% v+ m
Multiresponse, 多元响应
. a* m5 R; M4 F1 EMulti-stage sampling, 多阶段抽样% r3 E% n# ~9 l A) f' F0 |" {
Multivariate T distribution, 多元T分布
& \6 P1 [/ ]6 W6 ZMutual exclusive, 互不相容! y2 i8 g3 l5 h1 Z+ G
Mutual independence, 互相独立
* d/ o( p. M( t& l3 gNatural boundary, 自然边界* _2 [* D3 s$ z4 c* R' D# ` ?
Natural dead, 自然死亡- N3 I: D, ~8 L U0 x! e4 \4 F9 ^$ S
Natural zero, 自然零/ g) L% d" p l8 @; L- ^
Negative correlation, 负相关% L" l" D; \$ n0 F
Negative linear correlation, 负线性相关, q) S& C( A0 Z$ t& D
Negatively skewed, 负偏' z( @- j% k+ n$ u( U
Newman-Keuls method, q检验
5 V; @" C6 K! N' B: YNK method, q检验% B& v# s! A1 s& {+ O: f: q
No statistical significance, 无统计意义
3 L. F& a: l9 W+ H3 K3 }$ e/ MNominal variable, 名义变量. J4 H7 T% T N8 [! o
Nonconstancy of variability, 变异的非定常性
& w* p9 G# D, `9 q$ ~ ONonlinear regression, 非线性相关# K0 d8 m" d! A3 Q+ x% t. b7 E9 M
Nonparametric statistics, 非参数统计/ T1 ]! b' i; P1 J3 r, l3 n
Nonparametric test, 非参数检验+ y" _& b1 g( m& |$ g
Nonparametric tests, 非参数检验1 z5 j& x( W. J; }9 B& O$ Y
Normal deviate, 正态离差8 h; q# {+ E3 k/ M
Normal distribution, 正态分布! y B: l2 j( i* m
Normal equation, 正规方程组
; v+ M: D( J8 A) _& R7 {Normal ranges, 正常范围
2 n2 ^4 j) L% V& k; G+ cNormal value, 正常值, [8 @* I$ u3 d: `- w1 A
Nuisance parameter, 多余参数/讨厌参数! z4 M9 _% Z" g2 g# u* M1 p5 ^' u4 k, s
Null hypothesis, 无效假设
1 M+ Q; { A% C! \1 c; ?Numerical variable, 数值变量 W3 P$ @% }& ^6 o
Objective function, 目标函数- |/ k) D- W, [6 C; P! p
Observation unit, 观察单位
( W6 l3 }& V. o* L5 Y* GObserved value, 观察值: Q3 R! i4 T0 b5 c4 r7 ~: m
One sided test, 单侧检验
2 ^" F5 J& K% b. p1 z& BOne-way analysis of variance, 单因素方差分析( e& d2 U% |% P: w q0 T5 p
Oneway ANOVA , 单因素方差分析
6 }2 b: g: P. B% x% `. bOpen sequential trial, 开放型序贯设计" m0 B, \# U, }! s+ }1 w
Optrim, 优切尾
& Y+ H& k" s$ g: FOptrim efficiency, 优切尾效率6 |( ?- v, D, U
Order statistics, 顺序统计量- ?0 A4 T# F& U( \7 t- S2 K3 B' r
Ordered categories, 有序分类
0 X9 b7 ?8 g; o6 C2 f5 nOrdinal logistic regression , 序数逻辑斯蒂回归
B' e' q" @! g1 @* pOrdinal variable, 有序变量1 R# Y. K4 _9 p5 a
Orthogonal basis, 正交基8 ~% ~: }, E' ?
Orthogonal design, 正交试验设计, u& _+ \' J" ~, K @: I" M
Orthogonality conditions, 正交条件( X9 E0 w, S6 v% B" D. q/ d
ORTHOPLAN, 正交设计 ( H5 Z2 E+ l# q' F. L3 d
Outlier cutoffs, 离群值截断点8 F9 L- _" ?, d4 W
Outliers, 极端值+ x2 E9 l0 ~& b4 l$ ]
OVERALS , 多组变量的非线性正规相关
3 ]! G# f; x) IOvershoot, 迭代过度, r" a; a/ M2 |( f. D
Paired design, 配对设计4 c" Y2 z/ k5 J; U8 N/ l7 e
Paired sample, 配对样本
1 W, V1 m/ Z% _) C. @2 W! n( p4 gPairwise slopes, 成对斜率' i+ P$ I, o! i( a# x( l9 U
Parabola, 抛物线6 j) L" m& p9 s6 H
Parallel tests, 平行试验. K3 U& }4 ^6 A+ A, I) h/ r
Parameter, 参数
8 Y8 T6 m$ T* D, JParametric statistics, 参数统计
$ Y/ d' I1 @) k, z3 q0 m8 M2 s4 LParametric test, 参数检验5 @4 w7 e2 n' X/ v! L
Partial correlation, 偏相关
2 A) ^! D# a' j1 U4 yPartial regression, 偏回归
4 |' R. Y% ?& E& rPartial sorting, 偏排序3 r( F- g ^- w! Y- r2 \% N7 o- b
Partials residuals, 偏残差
% S& r9 M, L$ H+ C8 M% t9 b9 ~; oPattern, 模式2 p2 |9 j5 A' `2 o7 w
Pearson curves, 皮尔逊曲线
1 ?' q2 O6 z. ]) g/ }Peeling, 退层- t, ?2 o2 B; p" N, r( I* o
Percent bar graph, 百分条形图, H7 C) K9 y' J# J7 d
Percentage, 百分比
( y: |4 P+ A* n0 o( W7 g7 ]1 z6 HPercentile, 百分位数
* Y3 B. _0 h2 o( APercentile curves, 百分位曲线3 z3 r5 U3 L3 K/ W; ]- e0 P
Periodicity, 周期性
+ \% p6 ~. `' ^% @1 ]# lPermutation, 排列
$ g9 t/ p! p" c1 a% zP-estimator, P估计量
- Y( O, n ^, ^9 ?Pie graph, 饼图
/ A8 g% ?9 q3 J7 y/ k0 {% k; sPitman estimator, 皮特曼估计量
; ^' M% @/ a. f! _8 g$ n* D& T( q E( u" yPivot, 枢轴量
7 B0 H) b6 [* a6 n: G1 A/ dPlanar, 平坦1 R+ X; S1 ]0 O( \ z5 F1 `1 z5 L
Planar assumption, 平面的假设6 O) X0 y% P6 J) Q2 h% Z( w
PLANCARDS, 生成试验的计划卡
( H$ h$ Z3 h4 I8 L% QPoint estimation, 点估计) P4 y3 O$ L' Y
Poisson distribution, 泊松分布& ^: p+ o; E' \. r# A; H
Polishing, 平滑0 O7 m: N& i- \; B, L6 x# B
Polled standard deviation, 合并标准差8 {$ b& Y/ a: g) ]# [- ~
Polled variance, 合并方差
9 p ?5 ~1 I% l" F. M$ O0 TPolygon, 多边图
0 r+ z( Y/ j% P" q6 SPolynomial, 多项式
Y& D0 [; i6 H) ^Polynomial curve, 多项式曲线
4 Y, C6 _2 R( J( C: i3 H- _4 fPopulation, 总体
2 j. y% g# }( CPopulation attributable risk, 人群归因危险度0 U X9 B9 x/ O6 u; h9 p2 o# c
Positive correlation, 正相关" T! U4 P7 P# ^7 e% r" Q/ A
Positively skewed, 正偏 \' @1 t4 O" Z4 \. r
Posterior distribution, 后验分布
) W. q* p& V: t$ q* ?) D. D8 bPower of a test, 检验效能
* t2 y* e k& `9 x( _. iPrecision, 精密度+ X' q$ T" a0 \3 I
Predicted value, 预测值6 N2 A1 R( u- F( ^5 s) Q' `
Preliminary analysis, 预备性分析
9 s5 K& g* i. t9 IPrincipal component analysis, 主成分分析3 _2 h( w$ e( |3 N9 s. l! |6 Q9 v
Prior distribution, 先验分布+ T* z3 `/ w( O# u
Prior probability, 先验概率
5 N0 b6 \: K3 P$ n, jProbabilistic model, 概率模型
2 r% h0 U D6 i0 L, o" H4 c) m0 ?probability, 概率
5 A. j* C! k! W3 G$ Q# h8 ]Probability density, 概率密度$ U* |, ~/ ^4 G
Product moment, 乘积矩/协方差
$ ]3 t+ ?! a3 {+ E3 `! tProfile trace, 截面迹图2 Q# s6 u H' l3 s
Proportion, 比/构成比
. x" `1 `" z7 E" O, w, c MProportion allocation in stratified random sampling, 按比例分层随机抽样9 e* g0 w$ H9 V6 Q/ c% _* a
Proportionate, 成比例
- n a; F- C P- DProportionate sub-class numbers, 成比例次级组含量. f/ ~, X' H& K2 r- L7 p
Prospective study, 前瞻性调查% _7 T2 E; y. h
Proximities, 亲近性
9 c( Z( |% C! y1 g+ HPseudo F test, 近似F检验
) h! a& _" A( f0 kPseudo model, 近似模型% w3 b8 ^; f) {. t
Pseudosigma, 伪标准差
+ P! {0 F# P& f3 \ ]Purposive sampling, 有目的抽样
9 t% C9 X5 @* n& b0 N; vQR decomposition, QR分解
" j& C0 `% G, Z+ H3 Q: D% p; VQuadratic approximation, 二次近似4 K! x( q) E% y7 a( E/ g: }
Qualitative classification, 属性分类8 t) x: u9 x7 J2 f$ x& f
Qualitative method, 定性方法
) }# r: Y* W5 m6 V; HQuantile-quantile plot, 分位数-分位数图/Q-Q图9 d+ d7 K2 K3 e1 }. F$ b& g
Quantitative analysis, 定量分析* y8 u& |& W) V; g) {. H% r
Quartile, 四分位数* l3 t. X& A4 V4 {6 X
Quick Cluster, 快速聚类4 ]1 s, M$ {/ x0 B" b# m" U: U- v
Radix sort, 基数排序
3 X# r. Y- r/ I- z$ jRandom allocation, 随机化分组' G; a5 _7 i( |6 R; Q0 X' E, k0 X( V
Random blocks design, 随机区组设计
- N3 d# @% b3 M' J6 @Random event, 随机事件
7 `1 j: o% }* bRandomization, 随机化
* O0 g5 Y# }; ]' g3 D" ~( [" s$ DRange, 极差/全距( e1 I/ a `/ D' U6 o
Rank correlation, 等级相关
! ?% y }7 A+ \6 _Rank sum test, 秩和检验) b$ \( |6 S" b" X4 q) k8 ~
Rank test, 秩检验
0 ~! S3 ]& w6 c; T, X0 q! sRanked data, 等级资料
: t4 m2 E, w1 `; }Rate, 比率
, R' o& c% z) Z W5 O/ U8 y5 y, PRatio, 比例
4 m- Q9 [ j/ K# {2 JRaw data, 原始资料
" L# c& e2 k* J o) v. t0 q) RRaw residual, 原始残差8 s+ Z: M( o0 P) a2 x
Rayleigh's test, 雷氏检验
5 [$ x0 c" w' a* V# J* D& |Rayleigh's Z, 雷氏Z值 2 `& ]$ d& T5 y
Reciprocal, 倒数9 c0 a; m) F! x
Reciprocal transformation, 倒数变换6 z8 o* _- H& r1 t
Recording, 记录: q6 i3 B! ?" l6 A. B X; F# B$ r/ X
Redescending estimators, 回降估计量
, R3 c2 m7 L. i- w' |! DReducing dimensions, 降维, R6 }7 Y# W" n; g* }- a
Re-expression, 重新表达
( I: \: h! |0 r' [Reference set, 标准组
4 e ^: \2 q7 h( K/ T+ SRegion of acceptance, 接受域( O: |8 L8 j% m( X5 U
Regression coefficient, 回归系数
, o/ k1 _5 p0 X/ vRegression sum of square, 回归平方和
3 a& _* O5 H$ {Rejection point, 拒绝点
' X# v. Q" R8 U& i# T uRelative dispersion, 相对离散度
o. T/ d, u: @/ y6 TRelative number, 相对数
% x" E, ~0 R5 [Reliability, 可靠性, _' I% `/ h" R" P* [7 L
Reparametrization, 重新设置参数
2 Z9 H ~- q2 @Replication, 重复
) c6 n2 P0 y3 `1 x) x5 JReport Summaries, 报告摘要# X% G. u! V" u# h; F0 @
Residual sum of square, 剩余平方和( `5 L8 O: d: H8 {+ P
Resistance, 耐抗性
- ?% l _% `0 e+ {Resistant line, 耐抗线: r4 b% I; w% R, p3 b. G9 N2 C! O
Resistant technique, 耐抗技术
( z- L( [) ~( Q X! {- nR-estimator of location, 位置R估计量' u1 u& h. M1 F( G
R-estimator of scale, 尺度R估计量
& k6 `& G$ k; f' h) ^Retrospective study, 回顾性调查, h7 V7 t1 C3 U/ A+ F! W/ p
Ridge trace, 岭迹4 \1 V( x5 p/ S5 }+ [
Ridit analysis, Ridit分析9 |; }1 D; f* P( m; r6 ~3 p
Rotation, 旋转
X$ N1 o. A, M# gRounding, 舍入
* E0 Z! i2 j$ u& PRow, 行! w4 U- I7 _$ H3 d
Row effects, 行效应
" j: E- I O- K+ p5 R |Row factor, 行因素: b' I' t! b; n" O9 }- g
RXC table, RXC表) N. p) H, e. ^4 M7 I1 z$ N' a# U
Sample, 样本1 J) z7 Q9 r- A; {! f8 d
Sample regression coefficient, 样本回归系数0 l, n$ t$ _* `7 ~$ P) i% `
Sample size, 样本量
9 I9 m0 p, p' ^, w0 ESample standard deviation, 样本标准差
+ A) R0 D& X" [0 q$ ]- CSampling error, 抽样误差
! r1 C: C' M# GSAS(Statistical analysis system ), SAS统计软件包0 L3 k2 Q. \, D6 [3 k$ G( x+ V' \' b
Scale, 尺度/量表1 @4 P( B5 D) h7 n9 v% S
Scatter diagram, 散点图
% [, @6 u2 g# z( e! NSchematic plot, 示意图/简图
- {5 U, N1 b8 ], _( \ DScore test, 计分检验
) S- F( W7 v) i- s3 n/ nScreening, 筛检+ ?, g. P8 x. i4 i
SEASON, 季节分析
; m0 k' g) A) K0 L$ Q/ DSecond derivative, 二阶导数
7 O/ U9 z1 h0 r' [, d( ZSecond principal component, 第二主成分
' w3 B, c) z; z7 B) J3 |SEM (Structural equation modeling), 结构化方程模型 9 e1 G7 `$ Q0 k" J; N. G6 j: X
Semi-logarithmic graph, 半对数图
( k) S9 J" X& l2 m# n8 V4 hSemi-logarithmic paper, 半对数格纸6 T9 s9 @+ e3 _% B# |: H {1 k
Sensitivity curve, 敏感度曲线
, E3 A' h0 I5 z2 S$ tSequential analysis, 贯序分析
2 u1 _' Q' s. e( \7 Q# D6 J. _; xSequential data set, 顺序数据集
% Q1 d2 Z: d9 bSequential design, 贯序设计
% N( ], ? G& Y+ J4 q, RSequential method, 贯序法
8 n! P, X0 m/ B- n( qSequential test, 贯序检验法
7 t( a$ p/ Z5 V! t, k: ^7 TSerial tests, 系列试验) K, ~$ A( L% g' v, T& ~) B& n
Short-cut method, 简捷法 " }6 n/ T3 I& Z, o1 ?
Sigmoid curve, S形曲线1 _; X& f+ V* k8 @2 S
Sign function, 正负号函数9 z3 D' Q( N8 |) m5 I
Sign test, 符号检验; z6 r- C# l2 ]3 H4 g3 A" Y: O
Signed rank, 符号秩
H) i; r. z- fSignificance test, 显著性检验' ]) _$ Z2 c; d; k; }; {
Significant figure, 有效数字 \: `, p) l" ]
Simple cluster sampling, 简单整群抽样6 Y9 M' G5 K* J
Simple correlation, 简单相关
, Q9 t( W- W) YSimple random sampling, 简单随机抽样0 c+ f8 N8 I6 w% N# X3 ~
Simple regression, 简单回归
$ u) w) [9 y, V) {" Osimple table, 简单表( m3 Q- I$ y, u. a- }
Sine estimator, 正弦估计量
+ v, }1 ?8 n! Q) T( \4 kSingle-valued estimate, 单值估计
. q6 p; w' h( T1 T3 wSingular matrix, 奇异矩阵
/ h* [# M0 V0 LSkewed distribution, 偏斜分布
7 R0 x. @$ X% CSkewness, 偏度* m- B! h' ?9 k# N3 D( X
Slash distribution, 斜线分布5 j) p, W6 B: J2 S) X
Slope, 斜率. g" ?. _: G7 L' ]
Smirnov test, 斯米尔诺夫检验
- s& B; r8 {) v& [- |. Q7 YSource of variation, 变异来源6 c9 G. c' f, J9 E$ l
Spearman rank correlation, 斯皮尔曼等级相关
1 ]' [$ n6 o7 m; V# a) \1 SSpecific factor, 特殊因子' {4 ^. k' g2 |7 k5 m) v k/ Q
Specific factor variance, 特殊因子方差
& a8 H5 Z( B) D6 w' MSpectra , 频谱
6 ?5 h. j* X& a9 YSpherical distribution, 球型正态分布
- i! o, ~. `7 x9 J1 ^- @! oSpread, 展布
M9 E' h3 u* G. Y1 WSPSS(Statistical package for the social science), SPSS统计软件包
( j; u& f! Q) P/ |9 NSpurious correlation, 假性相关
) U9 g) E5 i- `& }! |# O' sSquare root transformation, 平方根变换
2 y2 z8 g) n: U' iStabilizing variance, 稳定方差 ^9 l7 u; A. Z+ T( A) y
Standard deviation, 标准差7 k! N4 f$ y! }# K4 \
Standard error, 标准误
4 m# p, ]! b( pStandard error of difference, 差别的标准误
; k! ?9 R$ i. x) TStandard error of estimate, 标准估计误差
6 O5 Q1 d- v! x/ nStandard error of rate, 率的标准误
3 B) g4 r/ K1 L* `0 S4 l z( FStandard normal distribution, 标准正态分布) q2 ~# \/ l8 A) X. x; u+ c8 `1 z
Standardization, 标准化
( n4 |9 D* \) vStarting value, 起始值1 b, I. L, R7 K$ w j( W. o
Statistic, 统计量# k) f( h( B' F+ n* [! L! G' z: Q' C
Statistical control, 统计控制
& ?3 i& \/ c1 L7 r a1 Z! wStatistical graph, 统计图0 `3 P' K, V. s
Statistical inference, 统计推断4 X1 t$ D5 l: m- A8 W
Statistical table, 统计表/ w) J" B& i, s' z7 b
Steepest descent, 最速下降法" E( ^6 P1 E* }1 Q& {3 F9 K& a3 x
Stem and leaf display, 茎叶图
1 k- v' h# D' e7 W4 c1 `5 `Step factor, 步长因子
7 Q/ u( a3 x" S2 v4 n6 EStepwise regression, 逐步回归
n3 y! _% v$ [0 e0 N, F7 ^; gStorage, 存
s: X! \% H8 M1 E& T4 P! y( \Strata, 层（复数）8 S5 x% m, i" G8 U3 t
Stratified sampling, 分层抽样5 W% h( L9 J3 q* j% K
Stratified sampling, 分层抽样$ o8 R* k/ g2 f- S w" T9 L/ K
Strength, 强度
0 z4 w' E M+ ~. I( m* O# rStringency, 严密性
2 b& f6 |" t: y# @2 m1 _! CStructural relationship, 结构关系- i# k) X: {5 d/ ^% b9 P- r) V+ Z2 {
Studentized residual, 学生化残差/t化残差
) v3 J- h- U) A, K c& zSub-class numbers, 次级组含量
0 `$ g" P i6 r. z$ ISubdividing, 分割0 T0 R3 }! U- N
Sufficient statistic, 充分统计量
; T- e1 a% P, ~ Y# V) i3 o, r. mSum of products, 积和" Q; d F9 @6 t$ M8 E1 K: x$ y
Sum of squares, 离差平方和7 `: n: e( m& Z; K0 r
Sum of squares about regression, 回归平方和
; r; [3 ?. {5 H5 X" Q$ ySum of squares between groups, 组间平方和
7 s4 _- e! M4 [ ^Sum of squares of partial regression, 偏回归平方和0 m; D- [& l- t! I% E
Sure event, 必然事件6 v( ?: Z4 k" v* h$ \3 v# b
Survey, 调查. u o4 e% L0 _( e
Survival, 生存分析5 F- l9 _+ D/ L2 [- Q7 W0 r I+ a
Survival rate, 生存率( D5 {; Q3 R# w$ ?6 f
Suspended root gram, 悬吊根图4 M" o A- S1 Z* p- h
Symmetry, 对称6 K2 j. ~0 f" ?6 c4 }5 {
Systematic error, 系统误差7 h# V# ~' @8 P$ V W# m
Systematic sampling, 系统抽样9 c% R' y" c9 j( [/ G
Tags, 标签) Q3 I# P9 g1 Z% {; ^: C7 |, w" E
Tail area, 尾部面积 o! F4 n% u0 P3 {# s) N5 L d
Tail length, 尾长
% @$ \% E) f. f1 M* WTail weight, 尾重/ x/ e; `: \; X7 u0 D+ k
Tangent line, 切线* n5 Y# a5 j" S+ J% G3 Y; T4 E( x9 _
Target distribution, 目标分布8 S5 W( ]# }1 e0 V6 y# N
Taylor series, 泰勒级数
" p' o% |8 N* r1 L- ]Tendency of dispersion, 离散趋势) o7 g% Z- m; r6 _1 ]9 p
Testing of hypotheses, 假设检验
4 S% E3 `# t' q+ ~Theoretical frequency, 理论频数3 v, i) e ^% a) p
Time series, 时间序列; H5 s5 l/ t- A% J9 A$ W5 B
Tolerance interval, 容忍区间
2 o' k* L8 Q* E( {Tolerance lower limit, 容忍下限, K! |. i7 W0 D2 s) H
Tolerance upper limit, 容忍上限
7 ~$ i+ _ i2 t* o! ^( oTorsion, 扰率
% z l$ K! A. C" n9 G1 MTotal sum of square, 总平方和0 }9 C1 g& y0 A# @9 v2 W" h8 |
Total variation, 总变异
; w1 D& a# J+ o0 \Transformation, 转换
: Y! y8 h' z! B) OTreatment, 处理9 |. c" X" j3 R3 }& t, W/ _: Y0 v) |
Trend, 趋势" b4 C4 Z" w0 _+ U/ E& x
Trend of percentage, 百分比趋势
9 t- ?7 S- _: \; kTrial, 试验
6 M- E3 p `( {+ q+ X: ^Trial and error method, 试错法% q8 r1 D6 g, J9 w7 k
Tuning constant, 细调常数
& n9 y) }/ F! d" W9 gTwo sided test, 双向检验
2 p. W% b2 g( b0 H7 j: |Two-stage least squares, 二阶最小平方# l5 A& \" \" `+ ~8 V/ x6 K# ^
Two-stage sampling, 二阶段抽样
7 \$ j# e0 \, K9 J7 wTwo-tailed test, 双侧检验 Q3 o4 @% U# o
Two-way analysis of variance, 双因素方差分析/ l8 l) T* S0 g' z: C T# X3 c
Two-way table, 双向表
4 ^8 \( P8 W3 JType I error, 一类错误/α错误4 N; K" x. p0 @" Y
Type II error, 二类错误/β错误
x1 ]) i* D& j/ B1 k( i7 eUMVU, 方差一致最小无偏估计简称
7 O" d! W- \" u0 k" S+ p& f1 _Unbiased estimate, 无偏估计7 _' s# F; {) j: W" _4 F2 S' a* b
Unconstrained nonlinear regression , 无约束非线性回归
2 a2 s: p7 g) O! b7 BUnequal subclass number, 不等次级组含量0 }$ k7 d# R, L* k# ]
Ungrouped data, 不分组资料3 D9 I1 A2 m- F4 B
Uniform coordinate, 均匀坐标0 L5 z, T0 n) s8 f7 d
Uniform distribution, 均匀分布
! {: a# [* U: x3 R# S1 P) p/ M) MUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
0 ~& u- C2 d2 s: ?* ?* S+ YUnit, 单元
: M0 G3 t. ?5 Z& F: y. Y: WUnordered categories, 无序分类, I( v7 u, e3 k9 J
Upper limit, 上限
1 ^! x: Q1 Q( w# E7 S2 vUpward rank, 升秩
( ?8 {: B9 s3 t- TVague concept, 模糊概念( Q( y) ]7 I$ ]2 K6 M; R6 ^
Validity, 有效性8 o5 c: G4 L: u6 n+ L+ y( a! \1 l
VARCOMP (Variance component estimation), 方差元素估计- a: [4 L! Z# j: D R: K
Variability, 变异性
0 z" L. J$ { EVariable, 变量
9 K$ e0 B1 a6 k$ [Variance, 方差
0 X3 f7 ^. X) M/ v( e' }Variation, 变异( Y, [' V7 W3 Z1 y+ b- T
Varimax orthogonal rotation, 方差最大正交旋转0 x3 `3 x: u0 {9 i1 i; A
Volume of distribution, 容积
' V, A! [' \1 e0 JW test, W检验/ u2 F8 C# K0 y2 a( u, W2 D0 a
Weibull distribution, 威布尔分布" h2 u5 E$ F( k& u1 ?& i$ r& v
Weight, 权数
; \! A1 k8 M' k4 oWeighted Chi-square test, 加权卡方检验/Cochran检验
: p) X8 M# d) X( x& ~& r# jWeighted linear regression method, 加权直线回归; O0 N; ]( u* N. F5 X; d6 v+ s
Weighted mean, 加权平均数- d& t3 r% ~5 a( \
Weighted mean square, 加权平均方差( ^# ]8 \/ Q, f, ~! U" ^
Weighted sum of square, 加权平方和9 q L6 b$ X, v0 ^9 W2 s# X6 ?
Weighting coefficient, 权重系数% H; [" @. r) q3 O* R2 A
Weighting method, 加权法
# V. w2 I# f5 ?: d* i3 hW-estimation, W估计量
% ]# P; c& o8 y* g1 q/ KW-estimation of location, 位置W估计量# p+ m P4 {; z! {& S; f
Width, 宽度" u/ m6 G0 D* j b# K
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
" T6 m) S( Z7 H* H7 V3 g/ @: @, DWild point, 野点/狂点4 _* o5 A* O7 I2 Y/ s
Wild value, 野值/狂值% P: I% T' }+ K' p! D
Winsorized mean, 缩尾均值
: O+ X2 }! `' R: T' N, x; ]Withdraw, 失访 # S5 s" i/ V" U" L$ x' g2 I& \
Youden's index, 尤登指数- |& r% w" ], ~# |* _0 `% q0 b
Z test, Z检验
$ l+ d6 b! y; a2 XZero correlation, 零相关
$ }0 z+ M8 g8 S: r, d5 ]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
