|
|
Absolute deviation, 绝对离差
0 {+ W4 N9 M3 u+ K# {# MAbsolute number, 绝对数
) g6 j! d! z/ |1 D4 A9 PAbsolute residuals, 绝对残差4 w4 p8 m8 @# L5 P2 ]! @4 c4 w
Acceleration array, 加速度立体阵: k: ?7 k( t! P* r$ u; j. I
Acceleration in an arbitrary direction, 任意方向上的加速度" L8 t8 k- ]) F! H, n# e. R
Acceleration normal, 法向加速度
. Q9 h' v1 f! Q) E$ A3 j& F2 B$ ~Acceleration space dimension, 加速度空间的维数5 Z6 |$ u; p0 v- k# w
Acceleration tangential, 切向加速度
; }1 P- H* o- u- Z3 E+ JAcceleration vector, 加速度向量8 A3 V# w0 V j+ j4 ^1 m
Acceptable hypothesis, 可接受假设
4 E* u% t9 a5 e, q8 _' b) Z4 i5 bAccumulation, 累积* g6 d) D' W6 I7 {" M' d2 H
Accuracy, 准确度* v4 p* I% ^1 F8 o& ^8 J/ E
Actual frequency, 实际频数2 L$ z0 P% I; Y
Adaptive estimator, 自适应估计量
5 `) N4 c. o3 P* _. M, } B3 z. Z7 K6 M' dAddition, 相加 A" s5 y4 n8 }+ A6 M
Addition theorem, 加法定理7 @0 C- ]3 T9 ^: ~
Additivity, 可加性
# n3 T7 `$ C0 e; `8 W8 oAdjusted rate, 调整率& Q) o( p9 x4 ? ]) _! \, }
Adjusted value, 校正值* T* e b, Q: f) j. C5 B+ O) {
Admissible error, 容许误差
4 U* s7 j# [; w1 g3 ?- s9 fAggregation, 聚集性2 E, X, v, V: w1 l' {2 B! p
Alternative hypothesis, 备择假设0 [3 k% [5 _* o9 E0 Z; ^; d0 m" s
Among groups, 组间
) ?: o9 }1 L+ \- @7 _# U( x9 W+ LAmounts, 总量
% @- N' K' p+ \5 D: s5 Q+ D4 I+ tAnalysis of correlation, 相关分析8 K& X# h8 u, Y- q/ u6 a: Z# n
Analysis of covariance, 协方差分析 C; H/ @5 F+ E& g
Analysis of regression, 回归分析! `6 u: a% L; a# d
Analysis of time series, 时间序列分析1 c( D. G1 j6 B
Analysis of variance, 方差分析
, M8 o. i* P$ B6 G' }$ \Angular transformation, 角转换
% c9 R* M. N9 I0 m6 f! R5 [ANOVA （analysis of variance）, 方差分析' s: S& a5 p$ O" Z/ J: q$ d
ANOVA Models, 方差分析模型- v9 h1 l8 }" ]5 y0 ]+ Z1 `
Arcing, 弧/弧旋& P U y) F/ m2 A% |
Arcsine transformation, 反正弦变换 U* B+ K7 I' `7 C& Y( d$ y; W
Area under the curve, 曲线面积
6 @0 g3 ^1 @7 r) u7 K7 {1 p( BAREG , 评估从一个时间点到下一个时间点回归相关时的误差
1 Q" i& w3 e: Z) \ARIMA, 季节和非季节性单变量模型的极大似然估计
" u7 Y* p, R |! G2 k+ oArithmetic grid paper, 算术格纸9 H5 y' Q; |- w9 e/ }0 T/ w5 G
Arithmetic mean, 算术平均数
# r: Y$ r9 O) x: J2 x* q+ qArrhenius relation, 艾恩尼斯关系, Y2 ]5 G/ C+ z1 f5 j' `$ u- }2 v
Assessing fit, 拟合的评估1 V. Q0 b' Y( a" X
Associative laws, 结合律
3 o0 k/ H% @ a' RAsymmetric distribution, 非对称分布
) D/ l+ x: s% |Asymptotic bias, 渐近偏倚8 h5 ]3 @: F7 h$ s7 R0 u9 n* M% n& z
Asymptotic efficiency, 渐近效率
v) |3 N9 u9 S: x mAsymptotic variance, 渐近方差
3 d7 V; h& S( {- E$ fAttributable risk, 归因危险度$ R& l3 J4 _* |9 v, T* J4 t
Attribute data, 属性资料
- q3 u) h C! _9 k( k9 Y; uAttribution, 属性2 h0 w, e: \: b; Z% u) E
Autocorrelation, 自相关/ ]8 a9 i9 n( B! I2 V& @
Autocorrelation of residuals, 残差的自相关
( E, `8 d+ F ^" XAverage, 平均数) ]1 r7 ^4 \2 r6 Z, W4 @
Average confidence interval length, 平均置信区间长度0 a5 R8 ^( n8 \# K2 }( L% i9 p
Average growth rate, 平均增长率# u8 J) D( ^' B
Bar chart, 条形图
$ J1 a; L3 g! ZBar graph, 条形图
$ h8 ~3 h1 `3 f; `7 i. |Base period, 基期; s$ F+ C) X+ T( W( k( ?
Bayes' theorem , Bayes定理
* A% s- l. ^- O( jBell-shaped curve, 钟形曲线: W. ^1 q( L7 C3 }( l5 J2 G
Bernoulli distribution, 伯努力分布
1 Y- x8 C7 I0 y+ o$ N6 R* b1 kBest-trim estimator, 最好切尾估计量
9 p; ~7 q- B" S$ B, O- j5 H2 PBias, 偏性3 D, i9 a; A( G& h9 U; C
Binary logistic regression, 二元逻辑斯蒂回归* Z/ z' S# w1 E+ r
Binomial distribution, 二项分布
4 ~' y0 `: B6 p. TBisquare, 双平方& b |1 q" D7 j! H I6 `, [) q' K3 |
Bivariate Correlate, 二变量相关
- E% X; m& m" m# B4 J$ PBivariate normal distribution, 双变量正态分布
1 B; l9 h2 x5 J ?* `, p# a1 rBivariate normal population, 双变量正态总体
h; p' p. {7 @; k$ T+ sBiweight interval, 双权区间$ A. E) C& o) L: z% j* \: D3 X
Biweight M-estimator, 双权M估计量
8 y8 v7 g$ }2 \ \& j" oBlock, 区组/配伍组& M0 H4 R* f1 |7 F7 ^# t
BMDP(Biomedical computer programs), BMDP统计软件包
0 s1 A O$ z9 Q! f* g! T: RBoxplots, 箱线图/箱尾图* s" R0 w; H) O" L7 i* P( m
Breakdown bound, 崩溃界/崩溃点1 m- X% i, o8 h& \6 T, _8 i
Canonical correlation, 典型相关" l2 W' E+ l" D% A! @
Caption, 纵标目( v5 ?3 x) j+ N/ p$ m& U
Case-control study, 病例对照研究8 F N! G7 g! Y6 X' d
Categorical variable, 分类变量( m1 _8 k6 K$ D* C, l" z) n
Catenary, 悬链线$ h. F$ E1 T4 Y5 Q2 u( d& N
Cauchy distribution, 柯西分布6 w& m; y1 F) Q$ g+ ]( Q
Cause-and-effect relationship, 因果关系
$ `- H4 l5 a) m( ~# S; |Cell, 单元& s( F& c" e% T) V- T" }% R' m; r
Censoring, 终检
# c) R5 a" f' [: {" y FCenter of symmetry, 对称中心
' m4 {9 G5 t1 e7 g0 L% W" i* A) bCentering and scaling, 中心化和定标
- P: c* u2 ~; b, `2 s/ c9 ~ s0 e# TCentral tendency, 集中趋势
+ G: D5 T0 t) w5 z- T2 u0 y* cCentral value, 中心值
) J2 u0 ^, N- n0 CCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测# w! J6 Y. J M, w& V# k5 m! N
Chance, 机遇$ {" r1 [4 ^3 E
Chance error, 随机误差
0 z5 J: M7 ~$ IChance variable, 随机变量3 o* q1 Q$ u* R) I$ {1 r1 ~: B
Characteristic equation, 特征方程, m2 i5 d3 k5 s5 ?; P
Characteristic root, 特征根
4 r8 H6 u% q6 W# C3 B1 GCharacteristic vector, 特征向量
. o) F" i6 e4 {$ K6 \Chebshev criterion of fit, 拟合的切比雪夫准则/ A- I9 G0 i# k* p5 u
Chernoff faces, 切尔诺夫脸谱图
! K; b( v6 ]) _2 L" E- t# o' \Chi-square test, 卡方检验/χ2检验- _- J' {. O: X5 y/ Q( G2 O% W) c
Choleskey decomposition, 乔洛斯基分解2 _8 Q ]7 M* N6 _
Circle chart, 圆图 ' K6 h: d: A! Q) g1 U2 E5 t* ~
Class interval, 组距/ I& ~5 y' z$ M; F$ F9 d# G& E
Class mid-value, 组中值
' e8 g. \; q1 ^" u. T2 GClass upper limit, 组上限& u* E+ F/ |7 y( F1 [
Classified variable, 分类变量
! u) C3 K! E5 t7 `+ TCluster analysis, 聚类分析/ k' h3 f, c! V& Y
Cluster sampling, 整群抽样
1 Z! L+ `- \$ O/ `- k3 P2 d GCode, 代码
$ N5 R% p4 U5 P rCoded data, 编码数据5 e! X1 d: L/ x2 u
Coding, 编码
( H( L3 T F9 j" w, I5 WCoefficient of contingency, 列联系数8 u7 Q! o' F$ o1 U
Coefficient of determination, 决定系数3 T2 K; u& M6 ?/ t$ U
Coefficient of multiple correlation, 多重相关系数' @# F6 f! `! F
Coefficient of partial correlation, 偏相关系数
; M# F: j( v4 X) }! N* lCoefficient of production-moment correlation, 积差相关系数0 C9 o) X9 z8 k* O* {4 ]/ ]/ l
Coefficient of rank correlation, 等级相关系数: S" X$ h8 S- Q1 r* v' a, l
Coefficient of regression, 回归系数
1 D. b1 H: N0 D8 W/ ~Coefficient of skewness, 偏度系数0 l3 E4 [0 e. A4 I. c$ \# D$ d
Coefficient of variation, 变异系数0 Y6 z/ I4 Q A7 A, c
Cohort study, 队列研究
" [) r0 j0 K& O3 P" ?9 Q( gColumn, 列
" M9 ` }( `: _ oColumn effect, 列效应* s9 q& T o* o+ j" k8 z
Column factor, 列因素' ^! R; r1 [* S- I; I* c2 @/ V( M
Combination pool, 合并
9 A8 k0 V" ~; d4 W: Q7 kCombinative table, 组合表
' w- f4 v) N( |, I" t, \Common factor, 共性因子; _& |: F9 f$ H `" r0 T/ P
Common regression coefficient, 公共回归系数- u, V* B% j4 R$ O
Common value, 共同值( v: `2 J% i+ _8 i# ]; r
Common variance, 公共方差
' b9 |( h9 g# {3 L1 SCommon variation, 公共变异7 u! O2 [- s8 m7 J4 x3 l
Communality variance, 共性方差
( G3 t& Z- u# k6 ~% F: CComparability, 可比性
( ?9 i( K+ I9 o" CComparison of bathes, 批比较
+ ^- k, O9 V, f. p4 ]' PComparison value, 比较值* _" |6 l5 L$ g/ S9 ~
Compartment model, 分部模型
1 K- A8 k! V6 @Compassion, 伸缩
) ]: H, i0 H3 h& m7 x4 NComplement of an event, 补事件
; S3 M; [% }9 t9 R2 a: QComplete association, 完全正相关
9 E$ v7 {1 {/ W7 x3 p& sComplete dissociation, 完全不相关& O8 k0 N$ B& u ]
Complete statistics, 完备统计量% w7 O Q% t% R
Completely randomized design, 完全随机化设计
! \7 P. f7 t, ^Composite event, 联合事件, w9 G8 G. W5 k0 r
Composite events, 复合事件6 |% X1 R! O8 ]/ w3 q M
Concavity, 凹性
4 s; |" ? g+ j) R# K3 TConditional expectation, 条件期望
3 U1 N4 q6 V% q7 aConditional likelihood, 条件似然
: p. H8 \) R5 W+ u0 ]3 S( }Conditional probability, 条件概率
$ K4 `7 G. r$ Z, R ^" Y7 IConditionally linear, 依条件线性( g' V: s. A: W! F
Confidence interval, 置信区间; m+ p. M) c! j5 |3 u3 H
Confidence limit, 置信限- D2 U" z7 v# Y! F! S! F% }
Confidence lower limit, 置信下限
2 S+ A: {0 b% aConfidence upper limit, 置信上限7 e0 Q0 V4 @. d
Confirmatory Factor Analysis , 验证性因子分析
: ~$ b2 J6 z. }; b' ]0 `Confirmatory research, 证实性实验研究+ l5 B6 Z/ h# k. ]' ^3 h! P% B' J
Confounding factor, 混杂因素
, Z4 ]6 d2 j% A m# hConjoint, 联合分析
8 m. [$ N+ Y% C* L8 KConsistency, 相合性$ N2 X. D% {6 B% h5 n0 A @! G
Consistency check, 一致性检验9 k2 w+ M7 S" ?$ Z# \) w @, E
Consistent asymptotically normal estimate, 相合渐近正态估计7 M7 h _- C5 C2 c- V- M; A& T7 b
Consistent estimate, 相合估计' ?0 _0 s( \5 r4 p. s B
Constrained nonlinear regression, 受约束非线性回归
5 s5 C" d; _2 {Constraint, 约束
( F4 i" T0 q, t$ v0 o, I iContaminated distribution, 污染分布/ T' D$ G1 v+ g/ k0 ^
Contaminated Gausssian, 污染高斯分布
2 _( B! y" Q6 w/ D5 D( lContaminated normal distribution, 污染正态分布; g- m- X, G# _2 R" G
Contamination, 污染
+ R; X6 {6 b& |4 RContamination model, 污染模型
$ G I8 l' @ G a% Y3 FContingency table, 列联表9 G9 g- V& u5 P5 G% Y5 K* V. F
Contour, 边界线: u' Q O# a& ^6 G" z+ K; ]) t
Contribution rate, 贡献率
$ m; E3 n+ b' {% D& |Control, 对照
# T& O% D, c+ f6 @" z# qControlled experiments, 对照实验
3 _" p& B7 }# _& m2 K. d0 w" d$ zConventional depth, 常规深度4 \$ A: W. W% Y; _) e# J/ c
Convolution, 卷积
C6 `4 Q/ t- q5 TCorrected factor, 校正因子, l! `; u: m3 s; r$ o
Corrected mean, 校正均值6 f2 q# p! g' l$ W- n
Correction coefficient, 校正系数
& S* R& S+ u, G! E: QCorrectness, 正确性/ Y1 ~! I: X- P+ l9 y) `6 k. N% E0 H% {
Correlation coefficient, 相关系数, V& w1 y0 t% t0 r
Correlation index, 相关指数
* ~. L& r6 v; t- TCorrespondence, 对应
; O+ L! B1 {- T3 ^$ VCounting, 计数' S& _4 B# Y4 H) Q
Counts, 计数/频数
% | O+ _+ p) G9 cCovariance, 协方差) N* \5 b/ S& ^- p9 a
Covariant, 共变 7 F( j* b4 x4 h& H* F4 E3 ^: z
Cox Regression, Cox回归
3 [: A" i( j8 K8 Z; T7 XCriteria for fitting, 拟合准则
|6 B: T- j7 M# z* |8 ]Criteria of least squares, 最小二乘准则
0 r( u- m6 j) t1 ]( oCritical ratio, 临界比# ?- `/ ]* w4 w7 E: E
Critical region, 拒绝域4 v( r$ n, s# [( Z% b
Critical value, 临界值; x0 w: S! p% T
Cross-over design, 交叉设计: z3 q, J6 m. D$ s; i( W5 H5 H2 i
Cross-section analysis, 横断面分析+ K; W7 Y3 w3 B$ N$ U
Cross-section survey, 横断面调查7 S S* F- d- Z- g: x
Crosstabs , 交叉表 4 v7 D3 v) r* Z" \
Cross-tabulation table, 复合表1 u: T& b+ ?* b9 C) v N9 R
Cube root, 立方根
- z/ i0 O/ E$ _8 X3 mCumulative distribution function, 分布函数+ w! L' r. R& O4 C$ ]+ j9 _
Cumulative probability, 累计概率
! b' ~' j* f2 N0 d, m# z& ICurvature, 曲率/弯曲. @2 G, p$ u# a% ?; d: M
Curvature, 曲率
! l9 u9 L& ]5 |Curve fit , 曲线拟和
1 P ?; n- f4 R/ y g; ]( }! _Curve fitting, 曲线拟合
6 U/ O$ X- i0 E2 g! W" PCurvilinear regression, 曲线回归& _5 S5 o# t; j/ s' r( j+ ?9 Z
Curvilinear relation, 曲线关系
6 h: ?! `1 a [, h; n# ^2 @4 v" U; P5 ]/ oCut-and-try method, 尝试法
# }; T8 w: \6 \9 `Cycle, 周期
5 `3 X. J( d- XCyclist, 周期性" L0 b5 l( y5 H; | b
D test, D检验- L4 V% Y7 C7 {2 F- o0 s2 h
Data acquisition, 资料收集
1 ^4 S" R$ Z! YData bank, 数据库5 |& ]" F) _$ P* l5 X6 s
Data capacity, 数据容量% }# n# Y0 v# M# ]. t
Data deficiencies, 数据缺乏, U R/ k6 N/ @8 I1 W# t
Data handling, 数据处理
0 u& K6 I$ y) |% DData manipulation, 数据处理
) L+ Q, O$ L' {/ a$ o* }* q3 bData processing, 数据处理
2 N7 g- }2 z2 A- K- g- d( AData reduction, 数据缩减
$ F c. a) G: @- x9 j# ]" @5 k( S% oData set, 数据集! g/ n/ W0 ~4 u! R/ v/ m3 w/ ?3 Q
Data sources, 数据来源
. j' f' |. R. e% ~' j2 D, D# x+ CData transformation, 数据变换
+ N5 l4 M: d6 S4 tData validity, 数据有效性8 n- P$ o/ }" v Y% ^
Data-in, 数据输入 I* [0 f5 L0 d! K1 g2 T6 V$ R5 c( R
Data-out, 数据输出
: ?/ j9 |' g7 g: X$ g( w K" x+ `6 TDead time, 停滞期
1 v: |6 f) v0 O- \* l& {Degree of freedom, 自由度
3 K. A0 C, B3 d* o2 KDegree of precision, 精密度
3 D6 L% I3 p) HDegree of reliability, 可靠性程度0 d4 q! f1 E7 L+ g) y
Degression, 递减
, I) ~: ~$ Z" }8 |! j* b! GDensity function, 密度函数
$ B' G6 \; p) r% B) x6 lDensity of data points, 数据点的密度
' Q8 ~/ S G; T+ U& v6 X. z" LDependent variable, 应变量/依变量/因变量( n2 j. T" w% _8 {' Y
Dependent variable, 因变量8 @- w$ U4 h& u1 i
Depth, 深度) k% v: b6 `7 v4 C' k
Derivative matrix, 导数矩阵3 {2 D( k& G, C
Derivative-free methods, 无导数方法
9 A. X* H8 H$ O* |' g/ @3 P: `: q* hDesign, 设计
3 Q6 b- H( w" g: e$ M4 dDeterminacy, 确定性0 A" @! {) f ]6 J0 O
Determinant, 行列式
6 m g% p9 J+ ?* B/ m% R( tDeterminant, 决定因素) j. f- M2 k0 p- X5 h( q) }1 V
Deviation, 离差
/ l |' |& k# Q' S2 D/ QDeviation from average, 离均差
1 M2 K+ b p( \% d# r7 R6 O5 R$ G( p1 [' \6 VDiagnostic plot, 诊断图' f9 R1 x! J. F+ Z
Dichotomous variable, 二分变量
# ], J; }5 C4 L; v1 t" DDifferential equation, 微分方程
4 {% U% }8 z( B9 J( r7 X* WDirect standardization, 直接标准化法+ _. _) c- S" c# m& v' F( F, w
Discrete variable, 离散型变量+ T* G ^1 q. L5 C- r
DISCRIMINANT, 判断 , b- t$ V) B9 c
Discriminant analysis, 判别分析1 g7 V7 f, P4 D; m6 I. h
Discriminant coefficient, 判别系数
7 m8 `' s' I+ }' b2 w+ UDiscriminant function, 判别值
% @' v* y# t* z- F9 i% n% m% K& YDispersion, 散布/分散度
( O' W2 ]+ U+ m7 a7 O& J- hDisproportional, 不成比例的2 D7 J9 R0 R6 x M2 F5 G9 T
Disproportionate sub-class numbers, 不成比例次级组含量
- |4 P4 O7 b! EDistribution free, 分布无关性/免分布5 K9 A, D" z' N7 `7 [4 r# p z
Distribution shape, 分布形状
: v; J y1 c$ V! x/ wDistribution-free method, 任意分布法
0 V7 z' a6 m& D YDistributive laws, 分配律6 [) w8 K3 h6 L/ Y7 d: J+ e
Disturbance, 随机扰动项
$ T9 i1 M% I) WDose response curve, 剂量反应曲线
! r' l% d, ]* QDouble blind method, 双盲法
0 _. \) y2 ^7 J4 p: ~( VDouble blind trial, 双盲试验
3 y) q. M7 ~8 {6 ~Double exponential distribution, 双指数分布% b) R# Y2 h7 F4 R% p4 k
Double logarithmic, 双对数/ k0 K7 S, k+ ~& c! ?3 K1 M5 y
Downward rank, 降秩: Y' e, \+ ~( L" Q# r4 w4 ^4 D
Dual-space plot, 对偶空间图
& } H5 B! U* e: t5 O6 sDUD, 无导数方法
$ T5 Y; f1 r/ A2 ^4 i1 VDuncan's new multiple range method, 新复极差法/Duncan新法3 ~/ N9 [2 G+ Y6 @9 M) h
Effect, 实验效应' d% o2 N! q- V% f7 B. j2 z
Eigenvalue, 特征值
4 U. F7 c* _5 k- eEigenvector, 特征向量
* X# g8 h" @( W% uEllipse, 椭圆- C- t1 S% e8 s8 r" B
Empirical distribution, 经验分布
: K: x/ Z' P3 F9 sEmpirical probability, 经验概率单位* Y$ N3 t- u4 P
Enumeration data, 计数资料/ M9 E6 E$ c% m( P+ t+ H, Z' u' e
Equal sun-class number, 相等次级组含量. ?& k+ F: L0 r6 E) N; F Z4 y* k
Equally likely, 等可能
4 f+ _1 M. t9 R+ R' W! JEquivariance, 同变性* A9 a3 B! ]6 y2 e, P, @3 t
Error, 误差/错误
: M5 \5 t; ^1 y1 _7 s; s) E3 ?Error of estimate, 估计误差
1 I, J7 l7 n, L1 {7 s* QError type I, 第一类错误. t5 e' t3 X# X2 S ~) o
Error type II, 第二类错误6 w7 H( z) _0 U$ C0 W1 f
Estimand, 被估量
8 \; V# ^& {1 g4 m6 b* hEstimated error mean squares, 估计误差均方
c5 y' H) r5 l! IEstimated error sum of squares, 估计误差平方和
9 t n( S9 B( F! `. |" @Euclidean distance, 欧式距离$ M" ]' {0 v/ z" t% Z
Event, 事件* w0 b. [7 s9 S
Event, 事件& q+ g4 Q, W+ j9 q: y; Q
Exceptional data point, 异常数据点9 W! n9 C$ s* A% x
Expectation plane, 期望平面
/ j N2 b3 @( m( P/ e6 ?6 d9 o& cExpectation surface, 期望曲面
1 |# u9 u/ |4 z/ X2 R. |3 {Expected values, 期望值4 P4 I7 c6 J6 ^# R
Experiment, 实验! F, Q% d3 w6 y Z9 w. M
Experimental sampling, 试验抽样# R2 J& N) b/ Q
Experimental unit, 试验单位* U' u. n0 c2 x: g3 x
Explanatory variable, 说明变量
! L: C5 B. J. \ o8 [' a8 OExploratory data analysis, 探索性数据分析( ?8 `6 K3 L6 {0 k0 D. O8 y! a
Explore Summarize, 探索-摘要
. }# v) q i) I! c5 ~7 iExponential curve, 指数曲线- {9 p- g. q' C8 r2 h( _* ] M2 w) G
Exponential growth, 指数式增长0 u. ~* {! d% v$ `$ b1 [1 R
EXSMOOTH, 指数平滑方法
# a. x% j ]$ P# r# W) H* GExtended fit, 扩充拟合
8 B' V; o* Z3 L6 Q( {! ~7 ~, \Extra parameter, 附加参数" K6 B2 Q) P9 I# a3 V: f( a
Extrapolation, 外推法
' e8 i- \6 @/ w4 \) x5 AExtreme observation, 末端观测值6 b4 q0 W# `8 J9 W1 g7 D8 H p2 m
Extremes, 极端值/极值
0 C9 C1 w" M* uF distribution, F分布
2 Z& f( Y9 I# h2 YF test, F检验9 ~; W! f2 o4 R
Factor, 因素/因子/ s% _: H8 m, }
Factor analysis, 因子分析
; x1 t+ b# }" a; F, m+ tFactor Analysis, 因子分析% T0 |- M* o* }( ^; S& w* S
Factor score, 因子得分
6 A& A' B% ~5 E$ s0 IFactorial, 阶乘
* D- x' p2 J* I2 G/ B& p/ ^Factorial design, 析因试验设计
& Z0 a2 ^1 X- A* w% j# U1 MFalse negative, 假阴性5 x/ w$ n8 z& o2 ]
False negative error, 假阴性错误5 s q& O6 z8 ~
Family of distributions, 分布族
# D( R4 t& Y8 {( a" i/ z$ HFamily of estimators, 估计量族& \7 g. y0 L9 Z$ i
Fanning, 扇面
4 b: A: F0 r2 I6 b9 s4 w3 P- Q9 x7 p4 uFatality rate, 病死率5 Y/ F8 {+ r, v( k( @4 U
Field investigation, 现场调查2 a @, u1 R6 g7 I5 r: w* b2 K
Field survey, 现场调查
4 i" A" o* i0 G, b) qFinite population, 有限总体
0 Q P4 q8 O- Y& P3 O9 wFinite-sample, 有限样本- S7 f- A6 H0 q2 Z' S% H
First derivative, 一阶导数# w& J8 e& D; ?. I; Z: q
First principal component, 第一主成分
/ @4 `8 W8 H B2 E) I5 wFirst quartile, 第一四分位数
! W( G, W/ q2 a3 jFisher information, 费雪信息量$ X& M. `# a% k9 h
Fitted value, 拟合值, V- ~" Z8 v! B& B+ }2 Q
Fitting a curve, 曲线拟合& P2 L0 Q, w: B& [# f$ u
Fixed base, 定基1 A& m u4 |- n! d1 o/ u; c
Fluctuation, 随机起伏% A( P) ~7 d6 p% o, H
Forecast, 预测! u' ?( S E, w; F. c" ]5 l
Four fold table, 四格表
9 u: Z! d, }1 U& sFourth, 四分点4 s; U4 Z4 P; Q
Fraction blow, 左侧比率
) T2 v4 t1 m5 r* H* `1 c& K$ O. fFractional error, 相对误差9 b: X5 p9 F: A8 {
Frequency, 频率
/ |: O: _; T+ o0 k/ b8 CFrequency polygon, 频数多边图
$ I" k/ o7 g; v8 N; G- Q. [Frontier point, 界限点
( a; A0 Q+ l& L& }) | K' L- pFunction relationship, 泛函关系5 p- n" ?8 R0 q9 Z" V1 A$ Q4 x
Gamma distribution, 伽玛分布. x: R9 `3 K6 ~0 c$ R
Gauss increment, 高斯增量. M* H3 M4 y- R# f3 c% ?2 l
Gaussian distribution, 高斯分布/正态分布
- e# i. G% ^( Q; {; P: z" WGauss-Newton increment, 高斯-牛顿增量
9 K; f0 _' ~0 g6 u. e! b; bGeneral census, 全面普查7 z9 a. A. x* }6 L+ F2 k" i% p0 G
GENLOG (Generalized liner models), 广义线性模型 ! D( [2 N3 x: a$ E% `8 \
Geometric mean, 几何平均数" A E0 J8 M: n, W
Gini's mean difference, 基尼均差
[6 o% }+ L# \GLM (General liner models), 一般线性模型 : j4 n" D- K0 z. Q$ n: t
Goodness of fit, 拟和优度/配合度8 c% M( x m% b h2 @# A- D
Gradient of determinant, 行列式的梯度
8 L# `, o. p+ TGraeco-Latin square, 希腊拉丁方
$ s8 X* V3 @/ B) S0 GGrand mean, 总均值
; r$ F, {* }" m Q' ]0 |; aGross errors, 重大错误
3 N! U$ i ~- h: o2 {+ vGross-error sensitivity, 大错敏感度
3 N: {6 N! L. T0 R% u( W' OGroup averages, 分组平均, n) J0 f6 K: ]: _% n+ r
Grouped data, 分组资料! d8 d0 N1 m# n
Guessed mean, 假定平均数- C- m q, Z; k& O9 U. m
Half-life, 半衰期
7 k! b+ `; a9 r! @. |- c# U% m! o* HHampel M-estimators, 汉佩尔M估计量
! G/ d0 G8 F# Q, cHappenstance, 偶然事件
& B+ K5 u4 i) o ~2 M Y4 A5 v; XHarmonic mean, 调和均数
; z3 s/ ]5 V' V t( X/ n/ MHazard function, 风险均数$ p3 y2 m. H/ [/ S5 k
Hazard rate, 风险率2 k7 R' R" a% K2 Z! j" [% y
Heading, 标目
# J+ Z) x, }- f/ @3 {" PHeavy-tailed distribution, 重尾分布
% w/ P7 T. T" J& QHessian array, 海森立体阵
9 w% H: u8 ?- m" ~! g( R ^Heterogeneity, 不同质% Y G0 h' L" ]
Heterogeneity of variance, 方差不齐 9 Q k: ]9 ^* J. w& M' C5 u
Hierarchical classification, 组内分组
9 ^$ z. M* ^" c5 j" CHierarchical clustering method, 系统聚类法7 J- i" u# c, s, y
High-leverage point, 高杠杆率点
, l5 R) E5 X) Z9 QHILOGLINEAR, 多维列联表的层次对数线性模型
" F! P% u) q& i, u* G9 M3 ?Hinge, 折叶点
8 h- t6 B M2 y2 xHistogram, 直方图
. x1 c$ y' X5 D! IHistorical cohort study, 历史性队列研究
1 B/ |6 u8 U3 C. l0 F5 a* S$ L2 FHoles, 空洞
' n. q! h9 I% ~* Y' C& C2 UHOMALS, 多重响应分析
; j% u$ _' R: m+ H$ kHomogeneity of variance, 方差齐性( I) s" z; I- ?2 V3 o
Homogeneity test, 齐性检验
4 I7 U2 @, h, X; N3 JHuber M-estimators, 休伯M估计量$ {8 S/ K3 b' d' O( [ z0 m* u0 i
Hyperbola, 双曲线4 ?" [8 U# c# @0 P9 y) [
Hypothesis testing, 假设检验
+ }) r1 S! K# e f8 o: ^+ I5 zHypothetical universe, 假设总体' X }: r. t* X+ x7 R( L0 _
Impossible event, 不可能事件
$ ]3 G/ {9 k, sIndependence, 独立性
# D2 v' R* U$ L: CIndependent variable, 自变量
; ]% W$ {' P: U8 y3 _Index, 指标/指数9 y+ g8 [8 G- q+ d' }/ h
Indirect standardization, 间接标准化法
6 |1 F* h% t. ]/ F+ C' E# m* dIndividual, 个体
8 C1 Z# b- _) p1 X" V" Z; I2 wInference band, 推断带: ^; F+ t) J7 J4 ]
Infinite population, 无限总体& l0 P1 R. o! e! V
Infinitely great, 无穷大# G# {- l" ]- P
Infinitely small, 无穷小
1 K( A6 z1 v1 Y8 A- rInfluence curve, 影响曲线$ |! D& b; B# k8 P0 N
Information capacity, 信息容量9 {4 y0 v" {/ t" i6 K c1 @2 I5 N
Initial condition, 初始条件- _* ]/ f3 c7 |" n7 ~9 t6 s# P
Initial estimate, 初始估计值9 E% S8 a4 c V, W8 [, _
Initial level, 最初水平4 a: `5 h# c8 C$ u
Interaction, 交互作用3 X7 V% X+ N7 m8 f6 }+ j
Interaction terms, 交互作用项3 {5 r. l) J/ k2 J
Intercept, 截距
- ^: `# a5 s" v' O' H; v& [Interpolation, 内插法0 ]) A, T$ t9 L k' Y
Interquartile range, 四分位距3 ^( \9 d6 e/ `9 F {
Interval estimation, 区间估计
. @3 i p4 Y7 x; y" n5 tIntervals of equal probability, 等概率区间
2 D3 _3 d3 K+ P* i, n# i( FIntrinsic curvature, 固有曲率
: o$ Z; k+ s# o& E2 f1 K% ?/ qInvariance, 不变性
- N9 N* ^4 J2 H* }* | }! m# y/ MInverse matrix, 逆矩阵
- O+ n; W* @' M1 ?) T$ N, r/ [' e' YInverse probability, 逆概率
# Q" U, K! I/ d9 W; `8 oInverse sine transformation, 反正弦变换! P5 h7 c( u! }0 m) [3 y
Iteration, 迭代
! d6 A& f7 F# e* e, G; mJacobian determinant, 雅可比行列式
# D! {- R7 w; [Joint distribution function, 分布函数0 ^& c0 {. j- M0 N; q
Joint probability, 联合概率
+ l; @8 I' U+ d0 K3 U( }+ gJoint probability distribution, 联合概率分布
' [! N& [4 x: y1 J* [K means method, 逐步聚类法. ~; Y3 C/ N& e0 M8 o; @: w
Kaplan-Meier, 评估事件的时间长度
" }- x1 F; N$ D( W4 P7 Z( MKaplan-Merier chart, Kaplan-Merier图
7 `) b% V9 L$ n3 g! q3 uKendall's rank correlation, Kendall等级相关! G4 d# H9 n2 d" V! G. u1 [
Kinetic, 动力学- c" U1 m7 |7 t! z
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
6 S: e' ^. @1 m! B$ O8 UKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
8 B8 [# Q5 P1 H4 k) G+ e# fKurtosis, 峰度. e: z. p: w& v7 T) W
Lack of fit, 失拟
% q3 c5 y$ t- Y0 L% h; a6 O" NLadder of powers, 幂阶梯/ i* Q* p& M3 K4 _, F" q1 m4 o; {" M
Lag, 滞后
2 i7 ?* n: E3 b- {7 xLarge sample, 大样本 w% H% Z7 ?( X0 d' Q8 D5 h1 A" e
Large sample test, 大样本检验) g" u6 Y' i C7 `4 ^) F
Latin square, 拉丁方
# P6 C# Z, w$ C1 p4 C/ FLatin square design, 拉丁方设计
! e, O. e3 h7 h8 Y5 D* o: LLeakage, 泄漏
& A# I4 B* c3 [: }9 ILeast favorable configuration, 最不利构形6 V1 b) R( v. ?. D3 l4 @6 k$ w
Least favorable distribution, 最不利分布
- ?% a4 L) T$ G* S$ _Least significant difference, 最小显著差法7 e4 |9 G+ A) Z' u! m
Least square method, 最小二乘法7 s' t& S: |; E# @/ P1 {6 L
Least-absolute-residuals estimates, 最小绝对残差估计 O! L- }8 n7 Y$ |- s9 k; x5 N
Least-absolute-residuals fit, 最小绝对残差拟合1 U/ C, k; ?# ]
Least-absolute-residuals line, 最小绝对残差线
2 m8 ]& {0 z; E$ ~* cLegend, 图例
/ ~! V7 a$ R+ m; Q1 N5 iL-estimator, L估计量5 E2 ^6 e! s' H9 [
L-estimator of location, 位置L估计量
, Z; ^$ [# M! s4 R8 o* n+ b4 B7 x fL-estimator of scale, 尺度L估计量
/ O: L% ^* H8 t3 XLevel, 水平9 D( Y1 s; Q+ V5 I+ j$ c6 r
Life expectance, 预期期望寿命
4 q7 W$ Q' v& y* ]1 kLife table, 寿命表" j' K6 k# ?; Y' @$ a. \6 O4 T4 E+ |: k
Life table method, 生命表法
$ s# S6 N* q- z% u7 Z: }Light-tailed distribution, 轻尾分布1 k% D; s' u" Q
Likelihood function, 似然函数2 J' s0 f9 c, R
Likelihood ratio, 似然比$ u, T: y7 R( M2 z7 j& O% y2 Y
line graph, 线图$ B' @! d/ @5 I* l9 X
Linear correlation, 直线相关
- ^* Q# R }& U& I2 W& PLinear equation, 线性方程
@* q% j1 M: Y h% T. bLinear programming, 线性规划% M+ s) x& k s c D0 ?
Linear regression, 直线回归+ A m, `: }7 ~* I/ a% N
Linear Regression, 线性回归/ ]% W6 G4 P% Y' t2 z8 L
Linear trend, 线性趋势
) j$ t- E( R+ q: T/ pLoading, 载荷 " {. D+ {0 ~$ ]& L% O- {5 j- b
Location and scale equivariance, 位置尺度同变性
0 {$ P v; w/ N) SLocation equivariance, 位置同变性
# p3 Z) A3 l$ m4 H# Z8 zLocation invariance, 位置不变性, k5 _/ n {: I' t4 D* d
Location scale family, 位置尺度族
7 a% ~9 [( h3 r' iLog rank test, 时序检验
% l Q) p6 _- V+ _2 b. eLogarithmic curve, 对数曲线7 @8 t B! ], u, M
Logarithmic normal distribution, 对数正态分布5 ~& h {6 c1 G2 J
Logarithmic scale, 对数尺度
% w' W" y/ h7 v/ s' ZLogarithmic transformation, 对数变换% ^: d7 f8 y8 W) l! K0 R6 m4 |
Logic check, 逻辑检查" ?# O# p& I% H: [! h
Logistic distribution, 逻辑斯特分布; \/ z1 i% E# V3 x
Logit transformation, Logit转换" }8 D" P& a6 G, y% B
LOGLINEAR, 多维列联表通用模型
' F& X7 _- @. b! t/ y- C( ALognormal distribution, 对数正态分布# B# X! [8 \2 o4 v7 O1 z7 f
Lost function, 损失函数
2 p n( e! _* G8 {. W% ~Low correlation, 低度相关
9 }; M T* u! Y! |* ]9 I$ P6 kLower limit, 下限
5 ]5 M7 |" `% q+ a+ r. M U, `0 ]' Y2 iLowest-attained variance, 最小可达方差
: h. m% o9 T: w0 ~5 k# yLSD, 最小显著差法的简称' M9 s; w/ |# r- g- {$ V1 @
Lurking variable, 潜在变量. ]) `0 G6 e6 [& b/ D2 J
Main effect, 主效应# a- M: j8 R+ x5 r
Major heading, 主辞标目* _. o; {5 ]/ x: b( t2 x
Marginal density function, 边缘密度函数
1 D; S( Q2 a- L, x. j% m( ]2 TMarginal probability, 边缘概率
V8 X9 V; f: Z0 k1 rMarginal probability distribution, 边缘概率分布/ S$ F6 W( s( g: l% c9 T6 v$ ]
Matched data, 配对资料& J( o! `* C; v- o
Matched distribution, 匹配过分布1 z7 E8 H0 R( _3 S! {
Matching of distribution, 分布的匹配
8 G+ w! `) d3 s3 ZMatching of transformation, 变换的匹配$ I- i" W" M6 {5 G6 B8 g+ R. }7 U
Mathematical expectation, 数学期望
8 z5 i; ^$ N, a: IMathematical model, 数学模型
6 @. q( T% q* r8 o! T+ AMaximum L-estimator, 极大极小L 估计量; n$ o+ ?0 ^- {3 D6 x2 M
Maximum likelihood method, 最大似然法$ Y! @+ X: q7 Z- ]. G& M
Mean, 均数
' {5 r" G) k8 i- O. J/ z$ YMean squares between groups, 组间均方
% b# j% M9 Q9 @3 @/ g; ~* J- ^Mean squares within group, 组内均方2 I- p4 Z, v. |% ?3 _- Z$ ~+ p8 E
Means (Compare means), 均值-均值比较
; m* Y( Y7 q& Y2 B$ b0 d/ FMedian, 中位数
r/ V: j+ n8 B3 p( k6 t/ O( ~* F' v8 rMedian effective dose, 半数效量
" T7 ~- f1 t t. AMedian lethal dose, 半数致死量
9 n, c# t( l+ G" hMedian polish, 中位数平滑9 [$ y y- n: n/ ^
Median test, 中位数检验, R: N, ` x# U( T. A$ o
Minimal sufficient statistic, 最小充分统计量, A% o( F7 `: K$ e* q' o0 f' N
Minimum distance estimation, 最小距离估计
6 U9 [, |1 x+ j. Q+ W: a7 W8 A6 EMinimum effective dose, 最小有效量" q8 }. s/ _# S0 {% D" a9 D
Minimum lethal dose, 最小致死量
& M/ M7 t. ~. iMinimum variance estimator, 最小方差估计量' H, W5 O3 ~; V2 |8 m
MINITAB, 统计软件包8 y4 x5 p2 X! @3 U2 b
Minor heading, 宾词标目" e7 v9 U! S& x6 p0 l" r4 z4 M4 l
Missing data, 缺失值. z( ~+ E; `) K" O4 `- {4 c, i
Model specification, 模型的确定' T; _/ e9 D* @' ~+ ?' b5 d
Modeling Statistics , 模型统计! N4 l; i$ |' `1 \7 q- s3 A
Models for outliers, 离群值模型
- n, {+ ~1 I; Y1 m9 M" bModifying the model, 模型的修正
6 i" u' y; F0 x7 nModulus of continuity, 连续性模! \2 n( c9 K! K! w6 A8 e
Morbidity, 发病率 7 {2 ?: |# \" x1 n3 y4 ~
Most favorable configuration, 最有利构形
5 \1 ~7 d+ ]# uMultidimensional Scaling (ASCAL), 多维尺度/多维标度0 @: w( b" n' b( i6 q, j: _
Multinomial Logistic Regression , 多项逻辑斯蒂回归
, }8 U7 A% ?+ i( } j+ SMultiple comparison, 多重比较5 d1 p e# R6 J; G" u: Y" `
Multiple correlation , 复相关" }6 C! C+ o( l6 M9 }8 Q
Multiple covariance, 多元协方差
! C" H5 W& {' i# HMultiple linear regression, 多元线性回归
. w& W4 A, v5 a3 g' mMultiple response , 多重选项
7 B1 P0 ~0 D7 M; g; ^$ AMultiple solutions, 多解6 ]8 {' @- ?4 X3 q2 N4 a/ ]( [
Multiplication theorem, 乘法定理) ^$ |+ B/ ~1 F9 y. D
Multiresponse, 多元响应$ \# ?0 f1 _- M" ~; p# [6 \. @
Multi-stage sampling, 多阶段抽样. Z. S& e8 d+ ]! U
Multivariate T distribution, 多元T分布. s$ W, a3 O9 Q: \9 C
Mutual exclusive, 互不相容
8 w' ~' C1 A" z7 @* ]( Y6 rMutual independence, 互相独立# Z- I5 l- X$ C" g
Natural boundary, 自然边界
' `6 J+ m$ Y/ N: S( a9 bNatural dead, 自然死亡
3 T5 i+ a' J6 B% K; \Natural zero, 自然零3 ~* w7 X( s' r# c
Negative correlation, 负相关. b5 j3 Y2 n4 V$ `$ M8 T: |' L" g
Negative linear correlation, 负线性相关
, g3 y. }' u7 w* T/ n7 aNegatively skewed, 负偏; `: d+ ?8 f. E
Newman-Keuls method, q检验 _% {$ n/ a. }! @
NK method, q检验
5 i% Z+ M- r7 s+ I, [No statistical significance, 无统计意义, Z9 p" Z) q( T' m
Nominal variable, 名义变量" a2 _8 O. _/ s |/ N& i
Nonconstancy of variability, 变异的非定常性% i$ H# @# ^1 D: {& I5 Y
Nonlinear regression, 非线性相关
# J7 a! D# V$ {2 j( YNonparametric statistics, 非参数统计) T0 G0 B# B' n; z; ^% \
Nonparametric test, 非参数检验* G# {5 z8 ~; ^% z/ f& j
Nonparametric tests, 非参数检验1 ~, j3 D. x* t8 V
Normal deviate, 正态离差 i% j% `" L! @
Normal distribution, 正态分布2 L, R8 L# J8 s4 f
Normal equation, 正规方程组+ j% `" W, f7 w" @
Normal ranges, 正常范围/ ]4 o% T" i. M2 S n* f: M6 M
Normal value, 正常值
# |5 E; m5 m' E: M tNuisance parameter, 多余参数/讨厌参数, b3 K9 o/ S3 } O) }+ \- ?7 `0 P
Null hypothesis, 无效假设 ; w" M; n& @/ y+ B' |; G0 s7 A" \
Numerical variable, 数值变量
; g, _4 k# q% r3 i* JObjective function, 目标函数4 g/ m9 F/ ~' ~
Observation unit, 观察单位
5 x, [% a s5 l5 `$ m E4 kObserved value, 观察值
- V6 c. L% C& j) y" N3 FOne sided test, 单侧检验1 Y6 T2 _0 w: E( B
One-way analysis of variance, 单因素方差分析
$ N" J' s) u6 ~3 D* g9 yOneway ANOVA , 单因素方差分析* E" D5 Z. a% Y/ g$ y
Open sequential trial, 开放型序贯设计8 B, \1 Y, m, L o8 l4 W, N( p% y# @
Optrim, 优切尾7 z' ~: A: H1 Y6 v; F5 |5 E
Optrim efficiency, 优切尾效率
+ A4 q7 k9 n: [7 _" pOrder statistics, 顺序统计量
/ ^3 G9 Z9 p0 }- O7 \, \Ordered categories, 有序分类
" N& M \8 `# F. ~$ h# n+ ]8 lOrdinal logistic regression , 序数逻辑斯蒂回归5 _% T. f5 a1 u5 w0 J; l
Ordinal variable, 有序变量; ^& P; l6 N3 f! w
Orthogonal basis, 正交基
A: O: |5 O3 H. ]4 w, n1 LOrthogonal design, 正交试验设计
: i5 q' `* w6 }Orthogonality conditions, 正交条件 H v' V' P' Q: H: `# H. v
ORTHOPLAN, 正交设计 & P/ g6 g9 S h, ~' C4 L" o6 [. y
Outlier cutoffs, 离群值截断点
7 ]! n; l9 d0 t9 w) h7 H" V' YOutliers, 极端值, m5 p, k2 I( L! @2 Z9 S
OVERALS , 多组变量的非线性正规相关
9 l0 w! f2 u3 v" K" Y! g& S+ w8 fOvershoot, 迭代过度
% H$ f0 O( f; R* Z. R" JPaired design, 配对设计( n4 k0 k" H; ~* N8 Z5 U' P( a
Paired sample, 配对样本5 `5 e6 C# I! c2 U4 \& ~
Pairwise slopes, 成对斜率8 {) m0 y) D& [
Parabola, 抛物线
6 B8 D9 S! K+ Y D) PParallel tests, 平行试验0 S; i$ l1 {7 y+ k. D
Parameter, 参数
5 Q7 ^6 g( E* F ?' jParametric statistics, 参数统计4 p+ _! M U" [5 _: O, b
Parametric test, 参数检验3 g# c, |: F; a' N( L
Partial correlation, 偏相关) l6 {5 h8 @* E, r1 c% {
Partial regression, 偏回归& f$ _) r/ y9 E1 p3 M9 ]
Partial sorting, 偏排序
* Z, w D4 }- S$ N3 l" z" ]3 r7 m( NPartials residuals, 偏残差$ s" w; R( Y2 K- X0 J" F
Pattern, 模式$ T( N; z. r f: W6 H
Pearson curves, 皮尔逊曲线7 [( c; ^6 ]2 T/ z0 t
Peeling, 退层
% I) B- r9 s! [3 ?4 W1 tPercent bar graph, 百分条形图, L- C2 T$ m; `% B& g5 R/ x) A2 ]
Percentage, 百分比2 S; p7 [ p U0 R9 h
Percentile, 百分位数5 D7 w, c. G7 O: ~
Percentile curves, 百分位曲线# `& d( W% _. N' g" X/ X- u
Periodicity, 周期性
+ O8 X/ |# b4 O6 h7 f0 yPermutation, 排列7 ^- i1 w# ~# M( Z9 l
P-estimator, P估计量
3 b- W5 Q4 T' f$ nPie graph, 饼图
( R% `, W4 x) iPitman estimator, 皮特曼估计量
" T6 Z2 b% ]: v5 {* A7 ~Pivot, 枢轴量8 P$ N U6 V% Y$ a8 s8 O* ^# T$ J
Planar, 平坦- ]% b# X9 v: X/ ?% A3 Y. Y! o
Planar assumption, 平面的假设
4 q1 }( ~% |( yPLANCARDS, 生成试验的计划卡
8 Q6 L" w, X3 WPoint estimation, 点估计
$ V5 ]# n0 d/ U! K2 B. zPoisson distribution, 泊松分布' `. Q, `4 M) a0 G M& X
Polishing, 平滑" v/ W% m1 z) s/ m" [( O T
Polled standard deviation, 合并标准差0 @/ a5 ]( G- X1 {. |* U/ U; U0 {
Polled variance, 合并方差
0 u+ h6 Y0 g7 ^$ M6 W ^Polygon, 多边图& f- ]6 S7 V4 t8 l( ]# R: ^' E
Polynomial, 多项式! d% U! l6 |$ K$ m. e
Polynomial curve, 多项式曲线
+ ^3 c6 Z0 C# w7 g3 T* lPopulation, 总体8 o* g* Z. `7 B6 Y
Population attributable risk, 人群归因危险度
3 C! Z- w- `4 r% hPositive correlation, 正相关9 v0 v- O/ D+ G% v
Positively skewed, 正偏
* c. u s* p* R6 A- ?) d2 h8 FPosterior distribution, 后验分布; n/ r- [3 L1 @7 j
Power of a test, 检验效能* `* T7 a) m* S: @! ~: p
Precision, 精密度
- @/ P3 f" k3 X) c9 P: OPredicted value, 预测值* s1 d# v/ q. ]% ^1 k, ?
Preliminary analysis, 预备性分析
" d+ ~1 C0 g& x6 d! X" lPrincipal component analysis, 主成分分析0 [3 C* q, r" }/ i6 w& \: T
Prior distribution, 先验分布- p; ?6 x. k0 n1 y/ n; ^& {
Prior probability, 先验概率
5 ?% y3 L" ?; ^5 p9 oProbabilistic model, 概率模型
9 y3 @1 `( M0 k' W5 X+ Qprobability, 概率% }9 b$ a" K! l, [: Y& @
Probability density, 概率密度
T3 O( \0 w1 x5 u" jProduct moment, 乘积矩/协方差
: @- \7 `, o& o7 r! U% cProfile trace, 截面迹图6 L* P0 c! {" L) E2 I! ?' d w+ {' o
Proportion, 比/构成比
. G7 j% c% _& w$ \6 sProportion allocation in stratified random sampling, 按比例分层随机抽样
- U5 V& O, U8 @2 ]6 M3 sProportionate, 成比例0 E. G/ [3 b; w }/ v' v
Proportionate sub-class numbers, 成比例次级组含量. e: Q( U* m3 O2 Z$ M5 P
Prospective study, 前瞻性调查
3 t4 E1 b& ~$ mProximities, 亲近性
3 d4 D+ ]* o9 UPseudo F test, 近似F检验
+ Z& J$ Y! A) y {1 k2 u- uPseudo model, 近似模型
) p9 j/ S! z7 h8 B5 g3 kPseudosigma, 伪标准差4 H9 Y3 y8 l& o1 u( Z* q4 \- a
Purposive sampling, 有目的抽样4 t8 k4 T$ P$ t( l$ \
QR decomposition, QR分解
" Q+ q) ?) O s9 [. B2 `Quadratic approximation, 二次近似
' X+ R _- S. |% E$ g$ r; c* a( nQualitative classification, 属性分类+ y, g1 x4 z( u4 P1 Y5 R! W+ p
Qualitative method, 定性方法
8 A+ ~) E1 P0 F" H w$ WQuantile-quantile plot, 分位数-分位数图/Q-Q图% F' G8 p" y! V9 c: O
Quantitative analysis, 定量分析2 [% C& P- h1 A o3 C: f/ o
Quartile, 四分位数
3 y# E$ l6 g9 N, ?2 uQuick Cluster, 快速聚类 R v$ ~) m6 m' _
Radix sort, 基数排序( Q/ u, U1 A2 S" I% G
Random allocation, 随机化分组
0 o8 e7 A) L7 IRandom blocks design, 随机区组设计1 h0 w; O- N- E9 b
Random event, 随机事件
# ?3 |3 t. M2 `& X8 H) y0 j0 s' pRandomization, 随机化$ }! |# d+ k# M$ H6 F. j
Range, 极差/全距
. C( D6 i% d7 d0 g& Q# LRank correlation, 等级相关3 K6 t1 W4 J. A6 s9 p: t q. t k+ t
Rank sum test, 秩和检验
/ E# e K! A1 n5 YRank test, 秩检验5 ~3 V- _4 z9 ?2 u: D
Ranked data, 等级资料) e2 Z5 h- R; E: z- A
Rate, 比率
. C' Y" J+ X! P3 d5 gRatio, 比例7 M# w# J/ U, ]2 ^: e3 B* `% l
Raw data, 原始资料
; Z+ a ?+ x" [+ C, @* tRaw residual, 原始残差# L! G2 m1 R0 ?- `) {: {
Rayleigh's test, 雷氏检验3 c Z! q9 L: }8 ~7 R! p
Rayleigh's Z, 雷氏Z值
* `5 U# c% @' A% XReciprocal, 倒数
* V+ ?/ S4 ^& x2 X, y' C- bReciprocal transformation, 倒数变换
, c( W* ]- l! [" K3 w& sRecording, 记录
m1 C l2 D- J6 P4 z) n# }Redescending estimators, 回降估计量! {" A. t; X9 N+ ~( n& f
Reducing dimensions, 降维
1 ^; Q6 ~# P" s& E, l, V) @1 J: n9 D2 JRe-expression, 重新表达7 s" I2 c1 O* s& y
Reference set, 标准组
[( k$ I) c( ^8 Z2 ?Region of acceptance, 接受域 h$ ?# S9 W9 H) F; s7 t
Regression coefficient, 回归系数$ U2 c8 i. _5 \8 m9 ]
Regression sum of square, 回归平方和
C* z* a1 `6 M4 {/ kRejection point, 拒绝点1 d- F3 _2 ~# E p3 v/ l
Relative dispersion, 相对离散度3 C4 r4 g# @1 ?( u
Relative number, 相对数
j ~# T6 C9 I2 S4 z+ QReliability, 可靠性
/ M ^) u) }3 j0 L) WReparametrization, 重新设置参数
/ a3 W$ h( p( ^. o; m& [$ kReplication, 重复7 ~3 \2 C7 A" j+ i2 {6 K" N
Report Summaries, 报告摘要
: v/ u0 [- X# F1 y- g7 TResidual sum of square, 剩余平方和+ R$ K" T3 `# P
Resistance, 耐抗性
: e" {/ b" d& J t2 X- s& zResistant line, 耐抗线* X$ {! d# F f9 A
Resistant technique, 耐抗技术
T( ? H( D! G* R; {R-estimator of location, 位置R估计量2 |/ ~3 v4 \4 w1 @7 k2 Y
R-estimator of scale, 尺度R估计量
5 _# x+ L$ l, K5 h+ ]Retrospective study, 回顾性调查
$ \' W! ?0 F( e7 A' cRidge trace, 岭迹5 b( V k/ x# _3 C3 d0 ], w
Ridit analysis, Ridit分析9 A" ~8 B9 t# a* z/ a+ T- j
Rotation, 旋转
( a# M5 G9 _$ \/ y3 a" b3 zRounding, 舍入
" |% @) Y- B W# URow, 行
- a- L0 P! {0 `8 T& q: xRow effects, 行效应4 c# E2 A# s; U4 f+ e
Row factor, 行因素
4 C- Y. R: M7 G) \. ~RXC table, RXC表
; B; N, ~; l5 M, A9 c0 }3 TSample, 样本* J; ~) \* i6 |
Sample regression coefficient, 样本回归系数
) Y! S2 Z! T, k, B9 C8 [Sample size, 样本量/ Y$ b% V* Q" g5 z$ r
Sample standard deviation, 样本标准差
+ H0 f M4 G/ F: BSampling error, 抽样误差
W$ P+ b' R: GSAS(Statistical analysis system ), SAS统计软件包
! H1 T4 {" ~1 F& m% |' B. gScale, 尺度/量表" q/ ] i& _# {0 \' h- a
Scatter diagram, 散点图6 i& [+ P0 ^, |. ~* b/ _1 \1 \
Schematic plot, 示意图/简图
( M1 G3 Q$ e& C. ?3 N* V! KScore test, 计分检验$ B. f( I+ p1 U% u$ k
Screening, 筛检
' J9 m+ M) d! v6 A' rSEASON, 季节分析
' |( E; c6 r: n q# p3 ?$ K8 N+ I5 r8 GSecond derivative, 二阶导数3 w1 T, t$ d1 e% ~
Second principal component, 第二主成分
+ E* l/ e W3 i" t' Y1 B/ J$ {SEM (Structural equation modeling), 结构化方程模型 - O g* r0 f% |
Semi-logarithmic graph, 半对数图 L% V# T0 R" \ ?
Semi-logarithmic paper, 半对数格纸
# [ X7 V. h3 I. q- u. r# ]Sensitivity curve, 敏感度曲线9 E" \* X9 m1 L2 G8 v
Sequential analysis, 贯序分析7 m7 v8 h T/ E5 `4 k4 @7 }
Sequential data set, 顺序数据集
% n, `3 A/ W1 C! RSequential design, 贯序设计
# a2 H8 M" y9 [/ ]4 ]- Z, r. OSequential method, 贯序法& C2 S* s$ X+ n$ b
Sequential test, 贯序检验法
+ _- S$ F# Q# p% p4 JSerial tests, 系列试验 h+ [: B. h' I$ \5 S
Short-cut method, 简捷法
, H% j) M" W6 O& |Sigmoid curve, S形曲线2 H. j3 K% h# K# D* c1 ?- B P
Sign function, 正负号函数7 t5 U8 P! V1 v0 [8 j5 Z
Sign test, 符号检验
8 k- j9 F3 P8 C: I* O, r; TSigned rank, 符号秩# f' g6 r6 u$ m h# D5 d
Significance test, 显著性检验8 g1 j' a' c3 }# Q; N
Significant figure, 有效数字. e' ~. B) R: L8 E
Simple cluster sampling, 简单整群抽样
' Y% P, x5 p) ]& C2 o5 oSimple correlation, 简单相关
; y6 ]$ m: T! [9 T) j3 j* t* b/ R1 tSimple random sampling, 简单随机抽样
" N' k9 P5 G2 W4 J7 v0 I5 c4 ^Simple regression, 简单回归: S- o, ]& @% i. b( a
simple table, 简单表, B7 I ?9 S* U2 ^
Sine estimator, 正弦估计量
+ b" ]4 T$ B3 V1 JSingle-valued estimate, 单值估计
- ]% }- g9 ]) ~ B3 O& F6 N5 fSingular matrix, 奇异矩阵1 H5 [, r$ t/ y* r" |9 d
Skewed distribution, 偏斜分布9 O. A: }- U, N! S) ?. z
Skewness, 偏度$ B. Q h& L2 g( b4 P
Slash distribution, 斜线分布
G" j5 h/ o7 o V2 kSlope, 斜率 g% |4 V6 o: D
Smirnov test, 斯米尔诺夫检验
( E2 N- h8 w+ N* G6 p% }Source of variation, 变异来源& ~0 H- u; j+ P
Spearman rank correlation, 斯皮尔曼等级相关' E e: l! L, J- T' z
Specific factor, 特殊因子) X3 a4 Q; i* F& _# I+ c) m
Specific factor variance, 特殊因子方差9 B" o! D8 U* k
Spectra , 频谱5 T/ X. F _* g. ]
Spherical distribution, 球型正态分布
( U5 F8 ]* C. {2 RSpread, 展布
9 `/ ^4 n3 z, \( a$ GSPSS(Statistical package for the social science), SPSS统计软件包+ T- R- Z$ j) V/ i+ u1 |
Spurious correlation, 假性相关( V6 f$ F' ~, J( _1 Q% }# y2 x3 O
Square root transformation, 平方根变换
\) i) p, b) L" h- g/ JStabilizing variance, 稳定方差
$ B z( v" x7 a! fStandard deviation, 标准差% A7 u! D7 g8 t5 d' b* z
Standard error, 标准误
8 E9 e3 f3 r; [+ Y4 p6 x% ]' sStandard error of difference, 差别的标准误- ^. W, }, O" P9 H2 G) k+ ]
Standard error of estimate, 标准估计误差2 `+ x# M& m% g P0 E7 f( q
Standard error of rate, 率的标准误' n' u3 @9 W$ o6 [
Standard normal distribution, 标准正态分布" r$ c6 H7 |: R6 K7 d- v+ G
Standardization, 标准化
" Y- R, i2 X( Y A' }+ s' B7 ~Starting value, 起始值
/ A0 H3 F& U3 v DStatistic, 统计量
8 O7 K$ i! x& u' n( JStatistical control, 统计控制: S7 y0 R# Q9 G5 o1 X2 X8 y, k
Statistical graph, 统计图$ _# K0 x4 @4 ]# W' X1 L
Statistical inference, 统计推断( U2 P! N6 I4 t. _
Statistical table, 统计表* x! V" {1 g; U( e
Steepest descent, 最速下降法3 W5 t1 r8 N9 Y" ]4 W3 Y+ p
Stem and leaf display, 茎叶图
6 W( C3 X6 C4 o. U8 H3 n( [Step factor, 步长因子
) s, _9 G- e gStepwise regression, 逐步回归
' b' ^4 n1 U! Z$ @( BStorage, 存1 D( s! d% m0 q5 b+ F. l
Strata, 层（复数）- I; J2 W4 m: h4 m" c
Stratified sampling, 分层抽样
$ @. W$ s2 L" a) L! v( J( B& R, uStratified sampling, 分层抽样
. F+ i2 A5 e2 w7 t/ @' OStrength, 强度0 D( P! ?' A( P1 G0 `" N
Stringency, 严密性
: L5 Z, e. \" aStructural relationship, 结构关系8 D" G6 j+ _; f
Studentized residual, 学生化残差/t化残差1 i6 H# E, x0 E! m1 |8 P/ K2 @, L
Sub-class numbers, 次级组含量
1 D+ \: }* M8 F! g& v" C; cSubdividing, 分割
" I- K% d: K/ Z, [8 ^/ c: a% \Sufficient statistic, 充分统计量
6 P* L( o+ i/ I9 ?Sum of products, 积和
+ W( u0 e0 \; bSum of squares, 离差平方和" ]6 V9 x3 f5 H% M) L) A% e! M- @
Sum of squares about regression, 回归平方和
, @8 `, ]5 R9 X l8 lSum of squares between groups, 组间平方和
f, d1 T$ i- O5 t2 BSum of squares of partial regression, 偏回归平方和; C; n4 f% t, w4 w9 J
Sure event, 必然事件$ r" O6 e0 g, b4 R0 d: l' ]$ b
Survey, 调查$ Y" a. B3 {) {6 y+ a% _) w
Survival, 生存分析
. R7 K; A0 j' \Survival rate, 生存率" S) J9 o* ]1 t8 Q& {
Suspended root gram, 悬吊根图- g. B6 D5 g K; }
Symmetry, 对称! ?& G4 j/ H8 p0 A% k& k' U
Systematic error, 系统误差
. V; y% {( z5 r, j# }5 i# YSystematic sampling, 系统抽样& B' ~4 g# _1 z, Z
Tags, 标签) V2 I9 x0 a J: O6 _5 p" e S
Tail area, 尾部面积
y3 U9 ~' U# k4 [% U, v5 XTail length, 尾长
* ]3 f0 k O+ f9 cTail weight, 尾重: g# E7 C" ?. A
Tangent line, 切线" R- T& X# ^0 r. ^- E
Target distribution, 目标分布
& A ~! z; @! f% fTaylor series, 泰勒级数! ?- _/ m3 ~& f6 ?2 v7 P8 G# k
Tendency of dispersion, 离散趋势
* t: Z0 z6 z3 VTesting of hypotheses, 假设检验
5 K% `% o7 z. o' E. |* MTheoretical frequency, 理论频数+ K, d) d5 a4 y3 Y+ Q; [
Time series, 时间序列
J4 U: Y# p* CTolerance interval, 容忍区间
# o* W- j# i$ Z5 TTolerance lower limit, 容忍下限
# [& h' U+ e! D- hTolerance upper limit, 容忍上限
Q1 J% n& ^6 i% S$ S' cTorsion, 扰率, e3 B+ g! Q9 c: _/ J( z+ z
Total sum of square, 总平方和
}9 q/ A( E; ATotal variation, 总变异: a' F* s5 d% m
Transformation, 转换
8 t3 ~7 _0 L' A! b) fTreatment, 处理. T+ I& m8 m7 W3 e, H
Trend, 趋势
' |+ p& O5 E6 `, k3 l: f5 I5 F7 i JTrend of percentage, 百分比趋势# L' w2 k2 E% ~6 q- \! g$ k& ]
Trial, 试验# i2 P/ S$ k' W" V5 j) c6 h
Trial and error method, 试错法
) a( O" g+ X* s$ h* w. FTuning constant, 细调常数
# m3 u+ O5 `% k" [Two sided test, 双向检验8 Z9 m& h, C* v" C
Two-stage least squares, 二阶最小平方5 b# p3 I; c8 C b* R. b# W$ a
Two-stage sampling, 二阶段抽样( ]% P0 ?$ A8 q+ D- X3 W
Two-tailed test, 双侧检验
4 @9 x. ]* T4 ?8 C: X, F, K* lTwo-way analysis of variance, 双因素方差分析
% r( N# }6 ?$ f2 c* N3 JTwo-way table, 双向表 z7 g$ X( D9 {6 W1 m- E$ A
Type I error, 一类错误/α错误
+ M- e, c% [4 W, v6 a4 bType II error, 二类错误/β错误7 X, e$ P; k8 }5 ~% h
UMVU, 方差一致最小无偏估计简称- O, \. x# ]6 `$ x" P5 s
Unbiased estimate, 无偏估计
3 {4 L$ D. U6 I: e8 c# L7 Y% pUnconstrained nonlinear regression , 无约束非线性回归9 x; E( [/ a5 E% z8 s/ h9 S
Unequal subclass number, 不等次级组含量
0 T% B( N3 \: `8 W1 ~( sUngrouped data, 不分组资料, c/ ], I' t5 h) V6 t* {
Uniform coordinate, 均匀坐标
8 U5 P2 k! e( o5 B( ?3 b5 K3 IUniform distribution, 均匀分布
2 S* W. s S6 e v) H% C+ jUniformly minimum variance unbiased estimate, 方差一致最小无偏估计+ M& p# I$ h% e" P$ y/ S
Unit, 单元$ ]$ \7 Z p$ Q e( H
Unordered categories, 无序分类
' t$ S, Z( E$ ^Upper limit, 上限
" P. @# E2 C3 J* `Upward rank, 升秩' d9 t4 ]! n" S D4 l2 I8 u% e, r
Vague concept, 模糊概念
3 o) i' J' W- C' H1 UValidity, 有效性, {1 v+ ]5 P) Y7 u1 _4 |
VARCOMP (Variance component estimation), 方差元素估计" A7 ?1 E- M" V) \5 ?$ d0 A/ P0 ?
Variability, 变异性& [2 Q1 t+ C4 ~, k
Variable, 变量
! X' K* ]1 g% h4 G# b0 ~Variance, 方差- p+ g' ?; u3 W- h
Variation, 变异
( Y O' m. D+ R2 ~) D8 J- zVarimax orthogonal rotation, 方差最大正交旋转9 x. \2 S. g0 n" F$ B9 M
Volume of distribution, 容积. Q* W4 ?, \- H8 n
W test, W检验
" m2 Q9 r0 N7 t; k" O3 _Weibull distribution, 威布尔分布
; Q, ?) K. O2 w, SWeight, 权数2 q% c/ ], m5 |, R' J
Weighted Chi-square test, 加权卡方检验/Cochran检验
; W; [# j1 i7 c: i5 jWeighted linear regression method, 加权直线回归3 L) q' e2 U6 @- o. j
Weighted mean, 加权平均数
$ S8 k+ D, S) d- DWeighted mean square, 加权平均方差
H8 G1 [7 k+ X, s3 M) bWeighted sum of square, 加权平方和
|) r' u- F' f$ Z6 x3 o% m, ~Weighting coefficient, 权重系数1 C/ u1 o- x h% R
Weighting method, 加权法 $ ?2 X0 G" V9 P: ^
W-estimation, W估计量
! B# y2 F* g$ V s/ B/ jW-estimation of location, 位置W估计量4 i9 e6 Y, i: ~) |. |) O
Width, 宽度
; ~5 I. y$ j5 _/ F0 R+ V W/ r2 xWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
' P2 g8 T/ b5 eWild point, 野点/狂点5 c: d# G( {1 Q8 \
Wild value, 野值/狂值
1 A* ]5 m7 S" k% J( _& \Winsorized mean, 缩尾均值6 ^9 d ^& |6 Q2 [# a' P( F9 A" N' u
Withdraw, 失访 0 x- s, d+ x; Q5 N9 D
Youden's index, 尤登指数
- l9 A' `2 U. [! r( d# {Z test, Z检验
* X) l. ]1 J! t' EZero correlation, 零相关0 R& s* }1 r K+ [" _1 {, u
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
