|
|
Absolute deviation, 绝对离差5 x/ g7 z( j8 z0 \, ^
Absolute number, 绝对数
; H' g4 V! v/ E+ T lAbsolute residuals, 绝对残差
! v. I' H. o- nAcceleration array, 加速度立体阵
3 L5 d: n) c) }, XAcceleration in an arbitrary direction, 任意方向上的加速度* i4 |, y- K7 \" b+ |6 ^+ k2 b" X9 |; x
Acceleration normal, 法向加速度
' x+ S& N8 Z* d+ B9 ]Acceleration space dimension, 加速度空间的维数: { `* O+ v% m: R& L1 B2 b
Acceleration tangential, 切向加速度4 I- u; ]+ Q1 Q) I! C2 j' z. T( h
Acceleration vector, 加速度向量* W5 H/ m. K" y" ~2 ~3 a
Acceptable hypothesis, 可接受假设7 d0 F/ e7 ]+ p' C" C
Accumulation, 累积
1 f+ i p& J5 q* P& lAccuracy, 准确度. l" a0 g2 y9 j- o: l: ^
Actual frequency, 实际频数
6 D) e, U M6 H& @. A* R( A: MAdaptive estimator, 自适应估计量
8 ], F, _* C$ }+ y9 C$ B: ^$ kAddition, 相加
/ x% m/ v( w5 s( F. LAddition theorem, 加法定理
3 |' V1 G2 F% Y2 Q7 RAdditivity, 可加性9 |; x8 Q a8 M
Adjusted rate, 调整率' \+ ~( w) L+ Z: l A' z3 h
Adjusted value, 校正值
, u, P. O1 p _# kAdmissible error, 容许误差# N5 a4 c4 p7 m" |9 ]: A* V1 O
Aggregation, 聚集性! j/ |- M+ o+ c8 h$ M! B
Alternative hypothesis, 备择假设- G8 w$ E: _2 ?
Among groups, 组间& t; j7 e4 X$ f9 Y/ s/ ]' @3 A" Q
Amounts, 总量' d1 n4 v! b" `- j
Analysis of correlation, 相关分析" e2 A( V5 ?* T- t( R
Analysis of covariance, 协方差分析
5 _7 b; j5 P+ s6 r7 u1 mAnalysis of regression, 回归分析 `0 g2 D% W( N7 T" \
Analysis of time series, 时间序列分析3 Z3 Q" k( E4 a+ E3 s. ?; t7 \! F
Analysis of variance, 方差分析1 P" K. d" A0 w8 `
Angular transformation, 角转换
]& N+ y- y, E# N7 ?. xANOVA （analysis of variance）, 方差分析9 r' w6 L; I! W. |- D6 j$ j2 s7 ~8 z
ANOVA Models, 方差分析模型
' S, i1 l+ I+ T% K# a# i- T1 YArcing, 弧/弧旋4 u/ z! K8 K; w) V3 i( i' [
Arcsine transformation, 反正弦变换
- Y" y6 W1 N$ nArea under the curve, 曲线面积% y) z5 H% n" y
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
: ?+ m S0 Q$ z2 n. n# [5 H* NARIMA, 季节和非季节性单变量模型的极大似然估计 4 b5 r+ |1 }0 S7 M6 o, N
Arithmetic grid paper, 算术格纸# I: U+ |: _/ C0 `9 r, z
Arithmetic mean, 算术平均数2 i) f* _2 I# y2 u+ |' r$ x
Arrhenius relation, 艾恩尼斯关系 V9 ^% O1 c6 X6 Z2 S8 a
Assessing fit, 拟合的评估7 G w, E, S( M& t9 _ K5 B
Associative laws, 结合律
1 o3 T7 s# c0 o# l3 f# c* VAsymmetric distribution, 非对称分布
' h: r8 ~# a) y, j, bAsymptotic bias, 渐近偏倚
& B3 h: U: G6 kAsymptotic efficiency, 渐近效率9 R/ Z/ Z6 e( }! D! c- o
Asymptotic variance, 渐近方差
/ O( u( o6 Y$ r2 x$ X( h+ iAttributable risk, 归因危险度
/ N3 j1 D* u" }2 }8 R2 IAttribute data, 属性资料
# M5 v, D/ @: |8 bAttribution, 属性
, ~: Y6 X' I/ ]( R" `7 q. k9 x, {Autocorrelation, 自相关
; E& ~* t1 L0 }6 b% RAutocorrelation of residuals, 残差的自相关
0 \, t; T& I8 |7 T0 O/ XAverage, 平均数2 s3 U( H' H6 L, K/ q
Average confidence interval length, 平均置信区间长度
5 \' Q1 s- j- ?, X4 s. Q( L6 cAverage growth rate, 平均增长率: m* }. @2 Y: w3 i
Bar chart, 条形图8 U" ]/ A, C: P
Bar graph, 条形图0 N8 O* @( f( z
Base period, 基期
! ^, v, z! M: b- p5 `$ O) tBayes' theorem , Bayes定理
5 I' W% g" K6 \6 \* ~* F/ YBell-shaped curve, 钟形曲线
0 T3 I* [4 B- F& _/ D4 HBernoulli distribution, 伯努力分布+ q* c( b5 L3 U% Q: q
Best-trim estimator, 最好切尾估计量
2 b9 ~/ z* p# b8 W8 N7 V1 YBias, 偏性2 M6 l, {1 a- g
Binary logistic regression, 二元逻辑斯蒂回归& O4 }& B4 R' _3 c* D; i+ \
Binomial distribution, 二项分布/ w; M1 q+ `) N( P" F
Bisquare, 双平方$ Y; @0 G4 y1 {( @
Bivariate Correlate, 二变量相关- O5 U0 _& S% z$ r2 r- h
Bivariate normal distribution, 双变量正态分布
5 Y. f4 Z m- ? V# `* vBivariate normal population, 双变量正态总体
" g+ n$ z2 Y" M+ TBiweight interval, 双权区间, u. |& Z4 c0 H
Biweight M-estimator, 双权M估计量
% D2 w. G3 w# l/ P* w6 k- vBlock, 区组/配伍组. ?3 b B) w v( I7 a0 b
BMDP(Biomedical computer programs), BMDP统计软件包5 | b' ^1 q! Z7 }9 m" h1 Y4 @: x& A5 ^
Boxplots, 箱线图/箱尾图9 O& Y$ v0 T9 x6 |* j, y( R* r
Breakdown bound, 崩溃界/崩溃点, g4 s. o5 |7 \& a. U) ]& ?
Canonical correlation, 典型相关+ a8 l1 W. S$ H' k! ]) B3 M' X; m$ B
Caption, 纵标目
8 Q( U1 Q; p: Q8 W2 c$ {Case-control study, 病例对照研究
* Q& x0 H6 k* P+ a. i5 u! HCategorical variable, 分类变量6 z2 V* i" l: g ~! C( m9 y X5 R+ y
Catenary, 悬链线
O/ |7 Q) q+ I) M! cCauchy distribution, 柯西分布
5 t+ T, K( ]+ w7 j ^8 _% v- GCause-and-effect relationship, 因果关系$ ^! Y1 t3 r( F" |
Cell, 单元( w6 `) |; W9 O% }
Censoring, 终检4 E4 Y& C3 J) v$ p0 f3 Z0 q
Center of symmetry, 对称中心) I* _/ N b3 N0 [4 F
Centering and scaling, 中心化和定标
4 ]3 R9 {* u( BCentral tendency, 集中趋势
6 k- s" v8 M. k9 j2 r4 c: VCentral value, 中心值
( [; r: C' S( O! C: U8 g( X% QCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
Y8 l8 b1 b5 o% [Chance, 机遇
$ ^2 |8 \% k( ?1 s8 ^9 e: nChance error, 随机误差
4 ?+ E6 ^+ W( DChance variable, 随机变量
! }9 d% A4 E) l i* k v; S# D. JCharacteristic equation, 特征方程
+ v( J# t. }3 d* rCharacteristic root, 特征根
" X; z# m* l/ C' V4 D5 OCharacteristic vector, 特征向量* B; @! R0 G( E0 V
Chebshev criterion of fit, 拟合的切比雪夫准则# f2 l2 s+ y8 j
Chernoff faces, 切尔诺夫脸谱图; F {# I: N, ]& E2 w `0 n! a
Chi-square test, 卡方检验/χ2检验" O; u: q3 B4 @; q. h
Choleskey decomposition, 乔洛斯基分解$ y: W3 O* N" E$ |1 p
Circle chart, 圆图 6 N9 w+ n5 y) }" u
Class interval, 组距
- z' K- T( f* g1 Y7 gClass mid-value, 组中值
8 G/ k4 W; S8 v7 a, _0 {3 iClass upper limit, 组上限
! N! b/ U1 l. A9 I! M) H5 S8 VClassified variable, 分类变量% Y6 A( D0 x& G2 {) s
Cluster analysis, 聚类分析
5 T, g( P3 ?$ ?Cluster sampling, 整群抽样
2 M$ \4 K* l0 a3 B; cCode, 代码
$ C5 M9 P. L* y2 K2 d: d; }Coded data, 编码数据
( z( q5 A+ |2 R- |3 q3 }Coding, 编码
& t! i' I3 i: ]; xCoefficient of contingency, 列联系数% s, b5 N) V( N( X0 j9 J& c6 A
Coefficient of determination, 决定系数9 C. o1 S- Y; W1 O
Coefficient of multiple correlation, 多重相关系数
' D3 N9 d8 f* I( S0 N) T6 vCoefficient of partial correlation, 偏相关系数* W! j. p# u, k
Coefficient of production-moment correlation, 积差相关系数
$ R+ |& z: W- @+ ~: J" ]Coefficient of rank correlation, 等级相关系数
7 }& i( ?/ k# z, UCoefficient of regression, 回归系数5 X/ R0 `/ z3 N: d$ w$ A1 `
Coefficient of skewness, 偏度系数
4 G8 k1 y n8 NCoefficient of variation, 变异系数& @2 \+ Q/ ~7 k& J* r
Cohort study, 队列研究+ _( x! U: p! V5 |% S5 \
Column, 列5 @$ m2 O$ D c* P; a1 a; K
Column effect, 列效应
/ O! E/ M! \. P- c! `Column factor, 列因素) C$ P4 r" J: u% c3 f" q6 f* W
Combination pool, 合并
1 w# ^' G9 h" eCombinative table, 组合表
" q) N6 {* L8 R4 _8 U- w$ ?4 ZCommon factor, 共性因子
7 W, Z% L) U1 F' w5 E. Z. CCommon regression coefficient, 公共回归系数 n9 I, N4 P$ W& V- \! [ b
Common value, 共同值- Y2 A) l" H- |) R: f; {. E" d
Common variance, 公共方差. j- p$ |3 h% _" e
Common variation, 公共变异6 b2 O- @- \; }. ~6 a, e
Communality variance, 共性方差
( U! g9 e. P' u) p& ^. M8 X( i2 _% GComparability, 可比性0 _5 ^! N' {& e) _
Comparison of bathes, 批比较" \, d& L# \ u& S, }* w# I
Comparison value, 比较值
1 t. ~2 Z% Q7 C$ L" GCompartment model, 分部模型
+ \, Q( Z* O& V8 [3 aCompassion, 伸缩" k& ~0 i* `4 \# D
Complement of an event, 补事件# w( l7 C0 R" s/ s/ K0 C
Complete association, 完全正相关
- G# D+ D% X1 A! q, G" H( @Complete dissociation, 完全不相关
7 k9 I' H6 g7 i' Z2 FComplete statistics, 完备统计量
" g6 X/ C& e, b; m# o% |! GCompletely randomized design, 完全随机化设计
& J( \1 j- G* ]* y2 RComposite event, 联合事件
, J& g/ `! I( A& SComposite events, 复合事件
- N! r; [! K" p. PConcavity, 凹性, P4 F, o' z. P% N2 `
Conditional expectation, 条件期望
) S* s A j( b% C* EConditional likelihood, 条件似然
' M- g0 s1 k* E1 c9 p+ h3 f2 AConditional probability, 条件概率. l" K& c% I9 \0 f( A
Conditionally linear, 依条件线性
1 a4 v$ O3 ]2 B7 p% Y* i' A( ZConfidence interval, 置信区间/ @, H; Y* D1 t- I6 |
Confidence limit, 置信限4 z* g/ `1 P1 |( C
Confidence lower limit, 置信下限) R5 O! V: \( F( u& C
Confidence upper limit, 置信上限5 W4 W% I& J3 p
Confirmatory Factor Analysis , 验证性因子分析$ \9 V" }$ n) c8 q& e9 m; I
Confirmatory research, 证实性实验研究1 Y o" t/ C3 H- Q9 `& { B9 e
Confounding factor, 混杂因素, p$ K9 H& f- `0 u
Conjoint, 联合分析' P% J" t2 N& w* L
Consistency, 相合性3 A* m. X+ T! y
Consistency check, 一致性检验) I2 n* b; P. T" T
Consistent asymptotically normal estimate, 相合渐近正态估计* t1 x( @9 J9 s2 C* Y5 x
Consistent estimate, 相合估计% |) f7 q& z2 L# w' l
Constrained nonlinear regression, 受约束非线性回归
2 d' s! J, y9 lConstraint, 约束
# B% [7 @% l0 m2 ^ E$ K' xContaminated distribution, 污染分布
) R; u0 w- T) c4 q9 t$ A" LContaminated Gausssian, 污染高斯分布; f J) v+ h6 T2 \
Contaminated normal distribution, 污染正态分布: w @: o& M6 V& D
Contamination, 污染 @1 |3 l1 i& }0 T- g3 z
Contamination model, 污染模型 @2 h1 [( A5 c8 W+ ?, m
Contingency table, 列联表
/ ~/ l* R# U# Z8 A1 gContour, 边界线, y# B2 {: ]- r0 a' m C; G0 E3 [
Contribution rate, 贡献率
" _! r- }0 u2 o, TControl, 对照
4 z ]" X; b; B& r mControlled experiments, 对照实验# M) [; F) q% S$ N$ A( a; E
Conventional depth, 常规深度
4 Z7 O# z' t0 Q @8 W! pConvolution, 卷积# d6 g; l6 K- C, c* C0 D7 w" f5 {
Corrected factor, 校正因子 p& W% [/ M7 H% R
Corrected mean, 校正均值
* W2 Q7 c0 `3 |Correction coefficient, 校正系数& d* ~/ S0 u+ Q5 }+ E, v8 |
Correctness, 正确性
& L1 `" [: X3 ~6 M3 B, RCorrelation coefficient, 相关系数
1 u9 v# @# B6 z% N3 N7 k B4 PCorrelation index, 相关指数
1 Q5 v9 W8 J9 |1 n7 c% e# n0 B) y2 r: QCorrespondence, 对应: ?: A9 g: B+ F7 l: Y
Counting, 计数, H$ t; x f( R* W: O& b7 ^6 K
Counts, 计数/频数/ @/ A- _3 P/ b0 S* M
Covariance, 协方差8 ?6 a" \) U/ b+ D' E' p0 L
Covariant, 共变
4 Y4 T8 X" v: k- G" X$ g/ LCox Regression, Cox回归+ Y1 n3 a# `$ k; u" m
Criteria for fitting, 拟合准则% a# J4 V; g! f, ~: K5 \$ o
Criteria of least squares, 最小二乘准则
& ` X! q+ r+ V C" p9 g7 SCritical ratio, 临界比. U! w) M( x6 p5 d: @: X1 |- b- x
Critical region, 拒绝域5 o) v6 T2 C! { o! `
Critical value, 临界值- S d! }; H; ~! E
Cross-over design, 交叉设计
8 U0 F- F9 E) Q0 hCross-section analysis, 横断面分析( h- q# t: P% U# x
Cross-section survey, 横断面调查
8 i1 b' g$ l0 U$ I+ l' p$ OCrosstabs , 交叉表
/ n! O/ v) ^* H4 g; Y& T. r1 T- lCross-tabulation table, 复合表
( b8 J- w/ U! VCube root, 立方根9 E) x, w5 D/ O/ E6 y
Cumulative distribution function, 分布函数% x2 x8 B+ T: L! W! U5 ^
Cumulative probability, 累计概率$ ~ [- G% W8 m5 ^
Curvature, 曲率/弯曲6 G: T: z* Y' Q5 w3 B% `
Curvature, 曲率% z" q# N; S( D. h
Curve fit , 曲线拟和
; J6 ~/ G% C: f% v( CCurve fitting, 曲线拟合2 F7 W4 K! @$ r' m0 a+ t
Curvilinear regression, 曲线回归0 A( v, O' j1 ]/ A: `, v
Curvilinear relation, 曲线关系7 n# i( t+ S5 O4 D3 A
Cut-and-try method, 尝试法1 \, ?8 @7 ^* k( I2 [ J F# v
Cycle, 周期
: m$ i- T$ w; a( c: K$ j CCyclist, 周期性
! w3 I8 _3 [0 S/ |0 B& @- c# YD test, D检验" i8 Q9 G* X% O# s
Data acquisition, 资料收集4 I+ }& ?( y5 ~6 w# o' [
Data bank, 数据库; a$ e9 J) v5 ?5 I8 H& {+ [
Data capacity, 数据容量1 j0 t0 G' u3 A- T7 n; ~& o: T
Data deficiencies, 数据缺乏
5 j: J% m( H" B5 O* S- kData handling, 数据处理
`' p9 S' ]3 lData manipulation, 数据处理2 f* h5 h. _. P1 B1 d* h
Data processing, 数据处理
3 s- ^9 b" ^) S0 |+ jData reduction, 数据缩减, @5 R7 h! D% w7 Z
Data set, 数据集
% e+ Q4 E. r- j6 W: H& B) LData sources, 数据来源) I2 ~1 Q$ Z# s& e- c# C& [
Data transformation, 数据变换. H3 {# \, ]1 `/ s; x
Data validity, 数据有效性: U9 [' h! m3 I1 j x, g9 N
Data-in, 数据输入2 @# q) J" L3 X% U# O' ~0 @
Data-out, 数据输出2 C1 p; n) S/ G) f" w) }( m
Dead time, 停滞期
5 N/ D) {% ?( v2 v* GDegree of freedom, 自由度
% l3 ?5 l+ \ ^Degree of precision, 精密度
4 k" O7 L* [% q' ^* U0 pDegree of reliability, 可靠性程度0 |: o( ?" l$ H, }! v7 [% f) q5 @
Degression, 递减
/ M) V3 i8 {; `9 ^1 L PDensity function, 密度函数
3 n5 Y1 j0 @2 TDensity of data points, 数据点的密度
; p h7 Y8 y( W$ { C& L' lDependent variable, 应变量/依变量/因变量0 Z+ v/ U7 w5 o4 m
Dependent variable, 因变量$ i4 a" x" ]6 p; n+ a
Depth, 深度' }4 t, g7 R: `9 k7 T* B8 x
Derivative matrix, 导数矩阵
" Y) G$ I" `7 m4 Q s: n& `Derivative-free methods, 无导数方法5 A2 A5 M8 k: n- ~' z, ^; |
Design, 设计% Q$ H* L5 l% i$ z
Determinacy, 确定性 R$ d% p4 O5 n' ~
Determinant, 行列式4 l7 ]1 Y% k8 W+ u1 F" X
Determinant, 决定因素
5 T+ k& g7 K4 A9 t9 Z' [Deviation, 离差
) U ~' r. A5 X, [( a8 hDeviation from average, 离均差. b9 E6 K+ T8 A7 Q2 u
Diagnostic plot, 诊断图
b5 C/ q6 f# x% J% x6 K H8 n, N$ SDichotomous variable, 二分变量
$ w' s% M% d7 K3 w+ w) P8 C. WDifferential equation, 微分方程
( P: ^ C: S( m9 i/ a# gDirect standardization, 直接标准化法
+ x3 z( I1 v' m( o9 kDiscrete variable, 离散型变量
& h: @# f8 @5 _7 }9 ]DISCRIMINANT, 判断
( {9 ]1 B# t& J0 y: z/ P$ h, hDiscriminant analysis, 判别分析5 C+ v) G( O' s9 ?2 M8 L& J( t
Discriminant coefficient, 判别系数4 x( A6 E, v$ U$ Z: K
Discriminant function, 判别值! x; k2 m' R2 W: Y- y! U; P0 B
Dispersion, 散布/分散度 L( K, r4 \$ D f1 J
Disproportional, 不成比例的
" P. ]7 S' e7 y. eDisproportionate sub-class numbers, 不成比例次级组含量4 r* Z6 {, a4 F) H& V
Distribution free, 分布无关性/免分布
1 f7 K# e# K5 W. o! N2 |' WDistribution shape, 分布形状" z" i: A4 _* ?9 f6 Q7 E
Distribution-free method, 任意分布法
6 y0 }) ~6 x4 |3 ]4 e1 b% `- ZDistributive laws, 分配律
: c- s* O, X# w* RDisturbance, 随机扰动项4 q1 ]: |5 U9 T" I1 `
Dose response curve, 剂量反应曲线0 s, I- O! T7 j6 f7 \
Double blind method, 双盲法$ J9 G8 {6 p8 C" b' |7 L9 f! W
Double blind trial, 双盲试验! P1 ?3 h6 h, c# n
Double exponential distribution, 双指数分布) f0 Q( H8 N0 H5 ?: C" \# ^8 y% q
Double logarithmic, 双对数
* P3 R/ _; j5 p( \Downward rank, 降秩
! c! Z# a0 `! bDual-space plot, 对偶空间图
! z: L; H4 x3 N# f9 J3 hDUD, 无导数方法
% u4 n6 C. `0 C, v6 Q. BDuncan's new multiple range method, 新复极差法/Duncan新法* v9 X) [8 h) j3 x( ~ ~
Effect, 实验效应
% j# ~8 K' S% E8 ?' vEigenvalue, 特征值
1 E% E9 a; I7 ~, o9 O. bEigenvector, 特征向量
: @( L# Q& ?0 M9 }' HEllipse, 椭圆
& V0 E' H- I7 q# {6 u0 IEmpirical distribution, 经验分布# \9 s1 F/ }+ H
Empirical probability, 经验概率单位) W# c+ `4 w) A% D
Enumeration data, 计数资料( \) K/ Z2 I2 y9 y8 W
Equal sun-class number, 相等次级组含量$ i6 h$ R2 Z3 h2 r: c: E: w
Equally likely, 等可能: Y2 g+ Q k1 W
Equivariance, 同变性6 o% x9 T* Z$ _
Error, 误差/错误: ]( ^/ ^2 _" U
Error of estimate, 估计误差
( H! H+ p1 K4 J8 Z& t( M- v+ ?6 iError type I, 第一类错误
3 X; `4 q8 g8 P4 p( ^$ }( eError type II, 第二类错误
+ r0 k/ S3 C, W6 U8 [Estimand, 被估量
( ^. r) y8 Z h7 ZEstimated error mean squares, 估计误差均方2 s; o- [) r; I; S& d# P. o
Estimated error sum of squares, 估计误差平方和/ O/ D" s* j& O; k2 n% P
Euclidean distance, 欧式距离
) O% B9 l5 d7 [$ j4 P+ b e( ?Event, 事件
; J: ^& `% _' L" ?5 |2 mEvent, 事件* {" z0 f) i0 T. H4 z/ T& G, z
Exceptional data point, 异常数据点9 U% G+ \" H3 e7 q# ]7 v! {
Expectation plane, 期望平面
; a) _+ Q, B' |# vExpectation surface, 期望曲面
3 `( h; Z8 E( x1 S& {- `Expected values, 期望值- p7 p z$ l( L$ A4 f) ?# w
Experiment, 实验2 o& _# v( O2 _# m
Experimental sampling, 试验抽样
2 I8 r `; L v3 M% tExperimental unit, 试验单位) M* ~% L- ?3 l. d7 K
Explanatory variable, 说明变量
& C0 u0 z {! NExploratory data analysis, 探索性数据分析
- P7 f3 E; j ?8 a3 D& |1 P* dExplore Summarize, 探索-摘要
. c4 u% U1 j' H7 @! n LExponential curve, 指数曲线8 }! `' c- V+ V& q5 V1 ]
Exponential growth, 指数式增长! \4 O6 ]3 i' d3 u- ~4 |' T
EXSMOOTH, 指数平滑方法
5 j" c/ t- ]% D# O# eExtended fit, 扩充拟合
$ @( e' _3 \2 n0 \" f Y9 l. {Extra parameter, 附加参数
. h k) D/ c0 WExtrapolation, 外推法
; T5 {, r( h8 DExtreme observation, 末端观测值9 t! n4 O2 _0 D( g
Extremes, 极端值/极值
/ R2 J" Z8 [7 RF distribution, F分布+ V8 Z" O7 K( r
F test, F检验) D# E% b" o; g; j, q, p+ R$ c
Factor, 因素/因子
% A9 J) T9 ]1 W! F3 eFactor analysis, 因子分析: s; L/ X, z' x4 S2 T2 p9 Y
Factor Analysis, 因子分析
. K' k" F9 K1 \9 [2 FFactor score, 因子得分
) w5 Y3 P" n$ t# f1 \Factorial, 阶乘
& C0 } P3 x. x- n3 x9 VFactorial design, 析因试验设计5 J1 j! }; g( n& x9 N1 K& Z+ M
False negative, 假阴性
( V& [3 }: p1 [2 ?False negative error, 假阴性错误
% q3 [ N/ v, }5 JFamily of distributions, 分布族
7 J8 e0 F: J2 Z% s8 o$ n% ]; q( ^Family of estimators, 估计量族
2 Y1 m# Z3 c1 L7 YFanning, 扇面/ k6 E# z1 K" |9 I6 }' I# E
Fatality rate, 病死率6 I# I5 o% M* L2 n, i( C
Field investigation, 现场调查7 v) o! J' Z( Y7 C* o6 E
Field survey, 现场调查
( H9 g* L. C2 G* wFinite population, 有限总体
0 M1 r* ~' {. P6 b) ]0 v- o4 UFinite-sample, 有限样本: I7 U! Y i2 |4 Q
First derivative, 一阶导数
. u( n* P; N7 n: QFirst principal component, 第一主成分) F/ t9 R; U/ {) D9 S* W
First quartile, 第一四分位数% A. F7 l" T4 _' n6 G6 F U
Fisher information, 费雪信息量: w5 v8 p4 ]5 M
Fitted value, 拟合值- k! N' H/ r! y& \4 z+ M
Fitting a curve, 曲线拟合8 g( b# N. ~% O# m5 r, \
Fixed base, 定基
1 v% v: l4 F$ yFluctuation, 随机起伏% X% E S: i) _" u; a% ?( {7 m" {! l
Forecast, 预测1 ^) w6 S! [( D# i4 U# k }/ Q
Four fold table, 四格表
4 z: P% [9 x) G% YFourth, 四分点
) O$ I9 b% D1 A7 H4 B, @- aFraction blow, 左侧比率
" y9 @) ]" j5 o$ l2 ]- K8 q7 BFractional error, 相对误差' A0 {* y1 k* h2 e# x/ s
Frequency, 频率
. F; r) p, E- j1 x4 _9 q! e, n8 ?! WFrequency polygon, 频数多边图
# Y4 b; \. y5 yFrontier point, 界限点
* D0 M. o# x; I4 {& L3 F9 p# LFunction relationship, 泛函关系
4 u1 X. T' z T( {1 Q* e! ^Gamma distribution, 伽玛分布/ h* {" d% x- ~' t/ K) V
Gauss increment, 高斯增量. h$ `/ V/ I! U" j
Gaussian distribution, 高斯分布/正态分布
9 e1 V. y+ c9 {) o( V6 }Gauss-Newton increment, 高斯-牛顿增量
( }: G, Z Y" U: iGeneral census, 全面普查4 @, }! y4 F1 u9 [3 Y5 r
GENLOG (Generalized liner models), 广义线性模型
+ K% w( a- c0 X3 ~4 n( jGeometric mean, 几何平均数. [# {# \; Q5 E! Q: s0 m' w
Gini's mean difference, 基尼均差# @2 `# w. ]" P& `0 C2 l5 m
GLM (General liner models), 一般线性模型
Q9 |- p* G8 g" e- q/ a7 Y1 ?: B3 L; oGoodness of fit, 拟和优度/配合度9 d* W/ X* B8 K3 x2 N- B
Gradient of determinant, 行列式的梯度( o0 Q4 d1 ~% u) ^ h V
Graeco-Latin square, 希腊拉丁方$ e+ f5 d/ Z% V7 P6 Z, s" U
Grand mean, 总均值
5 m& ^& ]; U4 d' ^3 A" {( NGross errors, 重大错误
p1 h( |) A( p3 t! z7 lGross-error sensitivity, 大错敏感度9 |3 R+ j, z* F9 Z
Group averages, 分组平均
# f! Z; d2 [% W: |, j; HGrouped data, 分组资料
. T0 E& m6 |; yGuessed mean, 假定平均数
0 g& @6 v! U! h2 x- h4 h& s0 p3 CHalf-life, 半衰期
2 c% `6 f6 T# ~- {Hampel M-estimators, 汉佩尔M估计量
* G3 s8 G: t. k# rHappenstance, 偶然事件' ?5 |$ N6 ^+ a* R4 R, {3 d7 f
Harmonic mean, 调和均数
- }9 _& Y% c0 ?/ D+ LHazard function, 风险均数, b8 q5 g- i y+ L8 X
Hazard rate, 风险率+ U7 a, R9 ~' I8 j4 R- a
Heading, 标目
5 s( f1 b0 s. b! r" d) ?) D) Z* [Heavy-tailed distribution, 重尾分布
* m) K8 C0 b* a- LHessian array, 海森立体阵
% W9 {2 l' L$ |# e) EHeterogeneity, 不同质/ {, J) J1 b5 t2 B l9 x3 N1 `% v3 q
Heterogeneity of variance, 方差不齐 ; O% {! ]% K/ n1 ^7 M
Hierarchical classification, 组内分组1 [6 P* D9 p9 h$ R9 q6 W
Hierarchical clustering method, 系统聚类法
& @; W' J8 H0 ZHigh-leverage point, 高杠杆率点# P3 ^) ]8 k( ]6 I3 K
HILOGLINEAR, 多维列联表的层次对数线性模型
% K6 e4 B# L* a) R$ VHinge, 折叶点 N5 V) _3 [" C/ e% g) _1 z
Histogram, 直方图
C$ R4 o+ z6 B2 w1 }3 `% VHistorical cohort study, 历史性队列研究
9 C# z- O2 n5 B3 M+ sHoles, 空洞
; x Q4 {3 ]. M) `, |! hHOMALS, 多重响应分析
; g, ^& x& H4 @3 M1 HHomogeneity of variance, 方差齐性
. T5 V% m' |( c, q& w( D! V- ]Homogeneity test, 齐性检验
. j }3 X2 B( M# F/ g: {, aHuber M-estimators, 休伯M估计量
0 L4 h" m7 v! f" H6 QHyperbola, 双曲线5 D" `3 g1 H# f9 J( X; A7 v9 f
Hypothesis testing, 假设检验
! U% a" g% L* ]Hypothetical universe, 假设总体4 D9 p$ x, d0 r' u q4 ?
Impossible event, 不可能事件
6 q" \0 I2 C$ QIndependence, 独立性
$ K. h) w$ a# x/ C/ s; ~# l1 v$ PIndependent variable, 自变量
" G5 o' m/ }/ n/ EIndex, 指标/指数
* q! u8 g8 w2 o5 w5 r% TIndirect standardization, 间接标准化法
, l3 o5 ?3 j. J. a, x2 n+ `Individual, 个体9 H. [8 m" k; x* ^
Inference band, 推断带. n7 K- O3 R' W7 ]0 r
Infinite population, 无限总体- A( y! A8 e8 W3 W8 b
Infinitely great, 无穷大
S* X/ U- ^1 W0 J) ]& }Infinitely small, 无穷小
( ^1 u3 H, W* iInfluence curve, 影响曲线$ E. r5 a' C- r) U( _( Y! l6 {
Information capacity, 信息容量
* O$ p7 s2 _; w2 w, ?Initial condition, 初始条件# K, b; H+ s4 ^( B1 J4 H4 d
Initial estimate, 初始估计值
9 j1 ]% `$ D; D$ S8 @Initial level, 最初水平
: U9 ]$ r! |+ Q, J, C3 y( v9 F2 |Interaction, 交互作用
9 g) Q& M. E: vInteraction terms, 交互作用项; ]. z' @) v L: L. o& }
Intercept, 截距
6 k0 ]5 O' n" R) B3 f9 AInterpolation, 内插法
: L% `) {( \; cInterquartile range, 四分位距$ V b% g2 A& l i; @# c& W: p
Interval estimation, 区间估计
8 X1 m9 n5 @, q9 p D) P1 @Intervals of equal probability, 等概率区间& S9 B e% K' l5 C1 w- D S
Intrinsic curvature, 固有曲率 d# t4 _$ W: U, i, N1 G- Q2 ~. m
Invariance, 不变性: w+ C& g) ~1 S5 ]9 }0 c+ z
Inverse matrix, 逆矩阵
" x5 m( S$ k t4 ~/ bInverse probability, 逆概率: J. ?& O% T) V' z& d) F5 T! W
Inverse sine transformation, 反正弦变换/ y! ^* _3 ^9 M& H
Iteration, 迭代
: r( b% l0 P& T* u/ hJacobian determinant, 雅可比行列式; w! ]; Z5 I* a; t. I
Joint distribution function, 分布函数8 A4 l3 t% \- J; w% @
Joint probability, 联合概率- q7 n/ [8 F. I% K! Z
Joint probability distribution, 联合概率分布. N" h( _# b& d# \
K means method, 逐步聚类法 ?. Y; _' U4 X/ D
Kaplan-Meier, 评估事件的时间长度
% h0 U* ~, W0 `+ PKaplan-Merier chart, Kaplan-Merier图. q4 N! |. I- }: J% k- P/ p
Kendall's rank correlation, Kendall等级相关
0 |6 |! W- m+ a2 tKinetic, 动力学
8 n1 X8 f- R- c. {7 xKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
2 B* ?) t, n3 J. M- J8 ^4 r6 H$ PKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验" L% n; F3 E$ D7 t* l
Kurtosis, 峰度
8 ?/ u( o0 N) {4 m1 Y2 E' @2 l+ hLack of fit, 失拟$ F. @4 k! \1 e3 ]& Z1 R. S0 V& {
Ladder of powers, 幂阶梯1 Z: y; e/ f) z& X" M" j; O' ^
Lag, 滞后' Y$ |; l0 Z' o* ^9 j
Large sample, 大样本, e0 Z l8 L. Y
Large sample test, 大样本检验
& u, \2 ?- S" C5 Q. P) Y4 [Latin square, 拉丁方
: F, H; ^' P2 _3 gLatin square design, 拉丁方设计
( B, }4 ]% Z5 j. Z$ v" JLeakage, 泄漏7 A6 c+ M7 n( `6 n! s. g
Least favorable configuration, 最不利构形
& I/ ~% W+ w) h8 d. \1 S4 hLeast favorable distribution, 最不利分布* }" @) ?. Z9 w
Least significant difference, 最小显著差法+ E7 j: W; b$ m% n3 g
Least square method, 最小二乘法/ S) L' E8 L* R* r/ r9 f' r
Least-absolute-residuals estimates, 最小绝对残差估计% B1 ?0 r3 F4 C* M$ C- `$ K
Least-absolute-residuals fit, 最小绝对残差拟合
! T! J! H& P9 x- D- jLeast-absolute-residuals line, 最小绝对残差线
2 P' e; u; M0 N: nLegend, 图例: j4 L& e" {! \1 K P# e! H
L-estimator, L估计量 J% h# u" P: p. t
L-estimator of location, 位置L估计量% j" _" V# o: U+ p$ m
L-estimator of scale, 尺度L估计量5 B z# r% M1 P
Level, 水平
( j% D! P$ a8 S: a! D5 S2 \Life expectance, 预期期望寿命. W. j, v8 d( f m
Life table, 寿命表2 l0 T) _ F' I9 Y. S
Life table method, 生命表法
/ V/ W& [: b$ ELight-tailed distribution, 轻尾分布
: B2 j* V S; X" J2 ^2 H9 `% W6 OLikelihood function, 似然函数
A4 s8 R. m8 O9 L4 t I% JLikelihood ratio, 似然比( D; b$ Z" A0 R" W( P3 r# ]" p
line graph, 线图
) |, K& h4 d0 P" CLinear correlation, 直线相关; B5 n c$ X4 I( s2 _7 g
Linear equation, 线性方程
0 ~0 N' Q" z9 mLinear programming, 线性规划
% J% g% @0 l. C- X/ B r; y; X/ L6 r! qLinear regression, 直线回归, a: D: R8 \) f% X+ a/ R( l
Linear Regression, 线性回归
- h. V3 G/ w( gLinear trend, 线性趋势
9 m( B1 }) L4 K2 j0 yLoading, 载荷 % O7 `/ T- c7 B% ?2 }6 i. _. T
Location and scale equivariance, 位置尺度同变性* A. e5 \ M4 o) n) K2 L
Location equivariance, 位置同变性
; E8 u! @* W2 g5 p3 d4 BLocation invariance, 位置不变性! |: b: |: i2 n3 ]- Y
Location scale family, 位置尺度族
5 i3 D+ O* y* ~4 `* }7 ?Log rank test, 时序检验 " t+ E C' H& G
Logarithmic curve, 对数曲线
# w# I4 @$ P, z1 PLogarithmic normal distribution, 对数正态分布
; W% @4 X$ ^0 ~$ k# @Logarithmic scale, 对数尺度
! S y( F: f; U5 l+ \7 f$ A2 LLogarithmic transformation, 对数变换
9 [2 F- Q. Z' G6 b$ x8 v) s5 h& X& NLogic check, 逻辑检查* u" q2 H; w& o! y5 s
Logistic distribution, 逻辑斯特分布; m& u# } `3 D* C, M5 ] {# V
Logit transformation, Logit转换. T$ c+ s* x( K7 [7 T' V, V9 \
LOGLINEAR, 多维列联表通用模型
2 N. s4 ^6 i( S1 _" d1 ~' ?Lognormal distribution, 对数正态分布) ~) v3 g( L5 Q# ]+ v b' l
Lost function, 损失函数
9 A' v' {! t; z0 x" lLow correlation, 低度相关( q% Y7 U. X, A) Q
Lower limit, 下限
; c* u# A7 K- u8 w# l7 \Lowest-attained variance, 最小可达方差" i1 m! u/ t8 {- |
LSD, 最小显著差法的简称
6 C& n2 w* t1 e$ q" QLurking variable, 潜在变量* u8 r$ T% I- ]4 b% i2 O( v! f
Main effect, 主效应3 @7 E( n9 c: y/ `: i
Major heading, 主辞标目# v7 ~3 W+ `; F
Marginal density function, 边缘密度函数
% [- B5 P: c/ _# oMarginal probability, 边缘概率% y* |1 H" w0 _+ T( Y
Marginal probability distribution, 边缘概率分布
0 z9 i8 W, g7 Z% ?3 _% Z) uMatched data, 配对资料
& k i& }0 @" _5 z: S- fMatched distribution, 匹配过分布& F5 p$ i' G# S3 o' {6 [* e/ M
Matching of distribution, 分布的匹配9 Y; p& x: A9 y/ G: s( ^
Matching of transformation, 变换的匹配
9 O8 E0 p- H+ t. E$ fMathematical expectation, 数学期望
% i, Z- y/ r a$ yMathematical model, 数学模型
4 i& R" v2 d* F% YMaximum L-estimator, 极大极小L 估计量# c W6 I& C9 t, I _) M
Maximum likelihood method, 最大似然法, `& Z: R) e6 H: V' k1 G0 t$ c
Mean, 均数6 |! M" ]/ A9 A, S- @
Mean squares between groups, 组间均方7 I) m; _7 V& J. q
Mean squares within group, 组内均方! Z0 ] S1 u4 o! l S; C
Means (Compare means), 均值-均值比较
, J! x! w% x9 w0 L0 e3 MMedian, 中位数
1 X9 V! h0 j" |Median effective dose, 半数效量
& s( j1 h' }6 j) t% U2 A l" IMedian lethal dose, 半数致死量
( n* {+ G) y# C5 dMedian polish, 中位数平滑
5 N, `' c' J O V/ C7 lMedian test, 中位数检验
( L5 x& L3 D1 L$ jMinimal sufficient statistic, 最小充分统计量" c+ s* e8 x6 j' s1 r; u3 A7 V2 S5 C# l
Minimum distance estimation, 最小距离估计
$ D. e P' H- N6 H1 y6 A# ~: RMinimum effective dose, 最小有效量
; M7 j+ }5 R0 T. PMinimum lethal dose, 最小致死量( b4 {* ]" m7 s( h" S- V% z
Minimum variance estimator, 最小方差估计量/ |, B0 K4 i$ ?1 }
MINITAB, 统计软件包
9 L! p5 {) b E# Z. j; LMinor heading, 宾词标目7 x+ [: ^2 N( ~6 r
Missing data, 缺失值2 q3 H0 j" x& `2 j: I
Model specification, 模型的确定* c7 c# V+ e! ~; z& ~/ F/ k
Modeling Statistics , 模型统计. \" i! [8 u: K
Models for outliers, 离群值模型
! p3 i1 N4 D& O) [Modifying the model, 模型的修正* c( S% ^: m9 \* o: B
Modulus of continuity, 连续性模; W9 k) z8 X1 C; `3 X
Morbidity, 发病率 : C; }/ Z4 c. Q: H' \
Most favorable configuration, 最有利构形# D( ~7 a# k: H6 \& E- Q% T
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
% M2 N/ A9 g/ G3 w, g5 }0 zMultinomial Logistic Regression , 多项逻辑斯蒂回归- ?3 N2 o! u X4 V' ], E
Multiple comparison, 多重比较
, N( v8 A" S/ p" B w) j+ z* S" J0 t* wMultiple correlation , 复相关
8 o9 I; w3 ?# `) V8 SMultiple covariance, 多元协方差: v' K, A; o! F! ~, U
Multiple linear regression, 多元线性回归& @* l3 j: h6 h0 i. I+ C' p
Multiple response , 多重选项
5 O( r; x. \+ G; ?) o8 B0 Q5 u% a3 r# \Multiple solutions, 多解. q0 E) ^# t$ J( p8 a( }& w6 W. `0 ?
Multiplication theorem, 乘法定理
9 I* G# K- A$ s" R! zMultiresponse, 多元响应- n. o7 U8 M/ t5 c5 Y+ ?% O; t
Multi-stage sampling, 多阶段抽样. K0 C* c0 i; }! o6 U9 i. t
Multivariate T distribution, 多元T分布( s+ A' \5 i9 l6 E% v% a2 a3 z
Mutual exclusive, 互不相容' I. N; W" r& f! z _
Mutual independence, 互相独立
1 t" e1 m' h! W, ~, y0 _ YNatural boundary, 自然边界
& J' T/ o2 U& k9 n) b9 hNatural dead, 自然死亡
1 E* X/ H* S* n' G- _. W" qNatural zero, 自然零
$ Z5 ]4 k0 k4 Z$ tNegative correlation, 负相关
6 \; D' K/ j$ [% ?Negative linear correlation, 负线性相关
1 `" a u9 m( i' d# f* DNegatively skewed, 负偏
! N. a- V _6 {9 N eNewman-Keuls method, q检验8 d5 h9 V% z$ V: n% A5 m; i
NK method, q检验2 m9 V% `& E2 w3 ] T/ Z# v
No statistical significance, 无统计意义
3 _2 i' ]6 f* q3 xNominal variable, 名义变量
$ ~+ h, }& K! s- K# k( [5 DNonconstancy of variability, 变异的非定常性' E9 [/ e2 F% M0 Z
Nonlinear regression, 非线性相关" p# ?) T7 t. b/ P0 O, C6 S
Nonparametric statistics, 非参数统计
, h o8 M- c r" nNonparametric test, 非参数检验5 _- \8 t, G1 W9 h
Nonparametric tests, 非参数检验6 S7 e. Y9 P- ^' t( p% t) x
Normal deviate, 正态离差- p6 F$ b+ d, v0 D
Normal distribution, 正态分布
) `( j% y0 c- i) ZNormal equation, 正规方程组
- W; z' m0 f/ U7 l/ G5 QNormal ranges, 正常范围
9 p6 n( }9 j6 r8 X) rNormal value, 正常值9 G, L' E$ D) v9 P' b
Nuisance parameter, 多余参数/讨厌参数
8 w$ H6 V. t. Z+ {2 VNull hypothesis, 无效假设
1 p+ u4 \& j G( m; iNumerical variable, 数值变量
7 X ~; x& j! J2 p( \- |1 TObjective function, 目标函数
/ f Q! T4 ^5 k: mObservation unit, 观察单位
% u2 ^! E+ z F# v; S" sObserved value, 观察值
* v+ s& N$ m3 R# \4 y1 FOne sided test, 单侧检验
- x, S. s8 O6 q) _% U7 SOne-way analysis of variance, 单因素方差分析
+ S- |0 K2 Y, I# E T1 {Oneway ANOVA , 单因素方差分析1 D( D' ] M: G/ D$ L; m# G( Q v! p
Open sequential trial, 开放型序贯设计% v1 k; C" r, \$ B
Optrim, 优切尾4 x2 Q0 A$ ` S9 H8 d) j
Optrim efficiency, 优切尾效率0 w/ `. Q3 A2 K7 b3 C E
Order statistics, 顺序统计量4 ]. X$ C3 k" g* i: U+ G G$ K
Ordered categories, 有序分类8 c5 D f% b5 C
Ordinal logistic regression , 序数逻辑斯蒂回归
5 D ]# p2 x7 @) hOrdinal variable, 有序变量& d# ~, u y4 @
Orthogonal basis, 正交基
7 `- |: u- v/ O/ e( [' G8 _% uOrthogonal design, 正交试验设计
# O" D' h* t/ R( [/ q9 L: _ pOrthogonality conditions, 正交条件
9 e8 B8 _5 d7 Q' F+ S. SORTHOPLAN, 正交设计
+ S5 L r7 P1 X0 M" Y# ]Outlier cutoffs, 离群值截断点- S1 p/ Q( U) B: f4 ^7 H* x
Outliers, 极端值! T' ~. a2 B- y1 S7 `) ], J2 v1 J
OVERALS , 多组变量的非线性正规相关 , j" L1 U+ O7 L) {7 e; p
Overshoot, 迭代过度
) r" ^! I; V/ J% k5 {' A4 M* RPaired design, 配对设计# a" e' ?+ z+ C8 A6 r
Paired sample, 配对样本) N0 |! @: W3 i5 D4 B5 f) t: Y
Pairwise slopes, 成对斜率
4 y3 j9 s& b' e. Z# i% G& ^8 ~Parabola, 抛物线/ k& @" e# O% m4 `
Parallel tests, 平行试验! B3 k" T- g! w: V3 B" G
Parameter, 参数
1 l: m* [) P7 r9 x1 E& S2 H6 ~' c6 `Parametric statistics, 参数统计
/ D5 T& X P" M; v8 k2 b1 ?Parametric test, 参数检验 m7 A3 `# O0 y' I d' q0 J
Partial correlation, 偏相关/ M3 h$ A, D4 h e6 }- t
Partial regression, 偏回归4 G6 J, w5 A, n* x+ @/ s& j$ z) z
Partial sorting, 偏排序3 h1 W! D! W- t( m$ X& a- n+ ~ d
Partials residuals, 偏残差+ c3 ^8 v) b0 s3 Q
Pattern, 模式
% X2 i+ X W8 i5 R v3 dPearson curves, 皮尔逊曲线
$ `/ _2 n* q2 W% m) J( X) N( e6 b" TPeeling, 退层
% z g# {1 W' C! p, zPercent bar graph, 百分条形图, {+ B5 E! x; N. f
Percentage, 百分比7 S- l6 F% x% D8 w! n
Percentile, 百分位数
: B: @5 p* {& g/ x4 m( B& fPercentile curves, 百分位曲线
9 h' r5 q" r5 y( J/ kPeriodicity, 周期性
& m* q* \+ S; G% _Permutation, 排列/ N. Z4 p( J. A8 T/ Y4 T
P-estimator, P估计量9 }$ U u! v) M) z
Pie graph, 饼图
* z0 p$ x: ?% W. Q. JPitman estimator, 皮特曼估计量6 q, B8 ~3 \5 o: d
Pivot, 枢轴量
' y! v2 G" \) c" D: x6 CPlanar, 平坦 t! }1 E5 _8 J Y$ D6 M; y4 T
Planar assumption, 平面的假设; z+ t. e7 _" H9 `# P0 {
PLANCARDS, 生成试验的计划卡
0 B9 L% x! c4 i# ?) C4 x; BPoint estimation, 点估计
( {. N/ r) o, _8 G' BPoisson distribution, 泊松分布) G0 a$ U$ e1 ~% F+ U% g
Polishing, 平滑 r- Z7 F' F; ]! ^4 C
Polled standard deviation, 合并标准差% h; x5 ]& b" w+ |% W; h
Polled variance, 合并方差
4 Z/ a/ C1 [+ R' RPolygon, 多边图
4 j" ]6 B8 v, o N6 I0 SPolynomial, 多项式
/ x; y# r$ V# c4 bPolynomial curve, 多项式曲线9 w# t+ I2 N2 H& \7 O6 k
Population, 总体
% B) R, ^* `1 `2 ]1 vPopulation attributable risk, 人群归因危险度
, ~9 s7 t2 y1 S! u! G7 pPositive correlation, 正相关
2 ]8 G+ {; S8 Z9 y8 K1 B7 oPositively skewed, 正偏
' V5 K4 W s: E$ ]/ I, s: bPosterior distribution, 后验分布
4 o- H( @1 Q1 t2 F% s) kPower of a test, 检验效能2 `) r, E2 O3 {1 n
Precision, 精密度
0 N# M" y& b! o/ bPredicted value, 预测值. m, {( ~& y6 i% l
Preliminary analysis, 预备性分析0 B8 \2 |- j7 b# m6 \. V
Principal component analysis, 主成分分析
1 B! p2 O1 D l3 ePrior distribution, 先验分布
! Z4 `. f/ F+ i4 q% H7 _Prior probability, 先验概率: X. v6 e2 H; E# P
Probabilistic model, 概率模型& u6 x- p# P7 a& A5 B
probability, 概率! f/ T7 X3 C& K. _: Z: E
Probability density, 概率密度6 b* L/ u$ H* ^; x. J
Product moment, 乘积矩/协方差9 ~( E( G: R+ T
Profile trace, 截面迹图
: h( k7 I H+ R$ \Proportion, 比/构成比
- s( p2 H: {; v( w/ V- {Proportion allocation in stratified random sampling, 按比例分层随机抽样/ P- M7 `- z6 _8 x- b
Proportionate, 成比例; G9 _1 a" X4 N- f+ ^
Proportionate sub-class numbers, 成比例次级组含量
; Q' P( Q2 E8 @3 I4 [Prospective study, 前瞻性调查 j+ I+ x* m1 s% L5 Q
Proximities, 亲近性 : L- F3 O& L1 ]/ U5 e+ {$ v" \
Pseudo F test, 近似F检验
" T! Q' {+ c8 K, j) L5 SPseudo model, 近似模型8 `2 x9 m; ^! O4 G; H
Pseudosigma, 伪标准差
I3 j/ j0 t" o2 bPurposive sampling, 有目的抽样
( P7 C6 x6 u# ?0 w4 @- N$ RQR decomposition, QR分解
( v- t, G$ T( hQuadratic approximation, 二次近似
: I. ]" p% i9 Y) ]Qualitative classification, 属性分类5 K0 p# G5 g6 u. T8 q
Qualitative method, 定性方法0 ^3 A/ I! {/ @4 K _/ R3 j( h6 f
Quantile-quantile plot, 分位数-分位数图/Q-Q图
9 s7 c' r2 f- E- u7 t; k- bQuantitative analysis, 定量分析
, \: q, f' g) g" p( E, nQuartile, 四分位数. k" Q z1 W- H3 D. l+ ]# y% }" v
Quick Cluster, 快速聚类
8 k) y. z" r$ B2 A) _* mRadix sort, 基数排序
. g) B% R- o) d# g, ~3 M5 I% Y! eRandom allocation, 随机化分组
9 Y1 _6 ~5 j2 j' yRandom blocks design, 随机区组设计
6 R% i7 G3 C/ n( \Random event, 随机事件
# ~: ]% F: l' \Randomization, 随机化. D2 a, y. l$ Z( R% ?- e% n
Range, 极差/全距
; v* L t1 e/ \Rank correlation, 等级相关) k- J O# `- k* F0 _ J
Rank sum test, 秩和检验
) T+ ^) y3 r. M. t, K3 sRank test, 秩检验6 h+ w5 f6 B3 I, G
Ranked data, 等级资料
8 F; _) n; X/ r$ ]Rate, 比率
/ ~" R( O& ?# @" ERatio, 比例4 O: F$ h6 r( s1 O' [0 r1 e6 y
Raw data, 原始资料
+ M- `! @) V+ L5 G% r* L0 G, X( H4 }Raw residual, 原始残差
8 T& r3 H: u; u) B/ {Rayleigh's test, 雷氏检验3 y4 Z8 C* u) [1 W5 H7 m6 r
Rayleigh's Z, 雷氏Z值 : Q X! v1 N3 N) b
Reciprocal, 倒数" E2 R4 t. O% m& ?6 l Z4 `' L
Reciprocal transformation, 倒数变换6 q' B* L. T# N4 G' ^- \
Recording, 记录
3 P" A+ H) s) i9 o- D5 ARedescending estimators, 回降估计量# c1 [% g# r0 O$ ?" [
Reducing dimensions, 降维
4 Y% D" }( `4 kRe-expression, 重新表达
8 Z4 o3 k* o9 A o& `Reference set, 标准组4 x- D/ x' m4 }: E4 c
Region of acceptance, 接受域1 @# o% y0 O1 }- i: g( ?
Regression coefficient, 回归系数
" a/ D3 P6 a1 VRegression sum of square, 回归平方和
2 R1 w4 ~; l, N* Z* Q) Y9 SRejection point, 拒绝点
% y% b$ ?( Q! g7 Q; E# {! oRelative dispersion, 相对离散度. S- w5 s# i3 S0 i' t- n; B0 B
Relative number, 相对数
" \5 _7 n1 c) K% z; C0 C6 uReliability, 可靠性; ]- O6 r' f( a9 W
Reparametrization, 重新设置参数
0 ?$ [! y8 `& A* F0 g/ AReplication, 重复' A; g) @, a7 W# G8 s+ }
Report Summaries, 报告摘要
/ Y1 |+ P3 g# zResidual sum of square, 剩余平方和" Q( Q/ r( u3 s& K
Resistance, 耐抗性
" L) D9 o' A9 ~4 s4 _8 d& l/ |Resistant line, 耐抗线; ?* V, x1 T. u0 B1 F8 r
Resistant technique, 耐抗技术, C/ Z5 U; L5 s2 a4 A7 E4 S( o
R-estimator of location, 位置R估计量0 U/ _! \3 z7 D. p& G. O3 k
R-estimator of scale, 尺度R估计量
, k# f& x9 r$ tRetrospective study, 回顾性调查! s! ]- o7 w% L/ d! p
Ridge trace, 岭迹1 F5 W8 C- _# t( q I& j! ~
Ridit analysis, Ridit分析+ {: |( X& B4 i' D4 u
Rotation, 旋转
2 ?( u7 }. ^6 n$ j7 e' @Rounding, 舍入
0 `! e( w" }2 eRow, 行
6 I. B( c8 a; c; nRow effects, 行效应
. d, \- u- n' Z7 |6 VRow factor, 行因素& T! b% T( h7 J
RXC table, RXC表4 x8 l4 }3 l; f% b) ~
Sample, 样本& x1 s+ L9 {" n2 }/ ~# S% S
Sample regression coefficient, 样本回归系数
' c# v/ D% ^* J, G" Q! hSample size, 样本量 T0 ?- T6 W8 ^9 @
Sample standard deviation, 样本标准差% z$ I7 q# }" ~, d
Sampling error, 抽样误差* T+ t% U- X3 I4 e
SAS(Statistical analysis system ), SAS统计软件包
& ~; L2 d; V$ D( c& `Scale, 尺度/量表
7 L4 m7 G- s4 t# e9 R ^# l `; k7 qScatter diagram, 散点图
( w: A O3 H f% G D3 o! ~Schematic plot, 示意图/简图' R# e4 \* w/ j3 _
Score test, 计分检验
9 v0 o% S* T a( yScreening, 筛检
4 A9 h L7 N7 fSEASON, 季节分析 f5 G: W8 R. o+ I# e# C
Second derivative, 二阶导数
: O7 ~% C8 ^& v( _; u: m3 k2 R' u& tSecond principal component, 第二主成分
/ p, c: E( _2 @SEM (Structural equation modeling), 结构化方程模型 9 r' _4 a* e. n1 z, g
Semi-logarithmic graph, 半对数图
' H: m$ l' q$ A8 Z+ y- b6 i% D3 lSemi-logarithmic paper, 半对数格纸
6 n! o2 m- z6 Z \7 HSensitivity curve, 敏感度曲线# v y% L$ L- P8 |. E: v0 v( u
Sequential analysis, 贯序分析
0 x) k. y7 w+ V q% G/ rSequential data set, 顺序数据集. v, F' s3 V. B7 C# F6 v
Sequential design, 贯序设计9 y1 |) @3 o1 J; e5 b1 v7 S( @
Sequential method, 贯序法0 A+ V# Y- y7 |$ k6 V" e
Sequential test, 贯序检验法
9 u( o1 ]; D: dSerial tests, 系列试验
9 C: _: g! _; a) IShort-cut method, 简捷法
. c# |( Q4 k: F* bSigmoid curve, S形曲线2 M3 d0 R6 f8 Z& M$ E
Sign function, 正负号函数
- d# m$ a# ~6 L" r- S( ?Sign test, 符号检验
- E# }/ V) b$ O8 OSigned rank, 符号秩
! h x0 S. v1 R0 X6 r+ sSignificance test, 显著性检验$ A# f, H( z9 T
Significant figure, 有效数字* J- M1 ^% U5 j* |( K
Simple cluster sampling, 简单整群抽样
) j" M+ v. K7 l8 L+ k6 RSimple correlation, 简单相关
- @4 @; k% u) y5 W% t2 `' G+ ~# P( ESimple random sampling, 简单随机抽样9 i5 y3 [7 C8 m( y) p
Simple regression, 简单回归
8 R$ b2 c: i+ R2 E4 z% q$ M6 ]simple table, 简单表3 k8 ~7 M# ~% p2 s
Sine estimator, 正弦估计量
: G* `- M5 C$ VSingle-valued estimate, 单值估计3 z& y& ~. H! |: g8 Y
Singular matrix, 奇异矩阵" S! `& a2 L' Y* t
Skewed distribution, 偏斜分布* i. G* g2 N! Z* B( g k: R
Skewness, 偏度
3 P, L2 B* E' y3 D7 O9 j: XSlash distribution, 斜线分布
( |& ^% ~+ e! bSlope, 斜率9 ^4 j h$ g$ y+ E3 u3 L
Smirnov test, 斯米尔诺夫检验4 w7 L: R4 a' b4 |* I- s
Source of variation, 变异来源
) m. K: h7 L- n0 P. j- `3 ^6 z( i9 kSpearman rank correlation, 斯皮尔曼等级相关, G- l* G" G6 F
Specific factor, 特殊因子
; ~# R* w+ j6 t7 C+ m; }8 NSpecific factor variance, 特殊因子方差
/ L, _( ^2 p: @) I9 _# ?) KSpectra , 频谱. J1 m, |$ }* u/ G# G/ j' ]+ ]
Spherical distribution, 球型正态分布
0 W' I* t* D- f' G- t- N9 iSpread, 展布
. k+ ]4 c4 V( e+ J6 @- ] FSPSS(Statistical package for the social science), SPSS统计软件包
3 |) Q# Q8 Y) s7 h1 {* f9 L% TSpurious correlation, 假性相关
: j! V& r! r0 T+ |2 D7 B7 eSquare root transformation, 平方根变换
$ o1 E1 V: q% W2 c: ZStabilizing variance, 稳定方差
) h. b0 h1 T. \Standard deviation, 标准差
" ^, ^3 ~; F& g8 r: h9 u8 YStandard error, 标准误
0 z' a1 P, O/ [/ a9 r- y! QStandard error of difference, 差别的标准误
0 P7 e" ^# C# b; ?/ Y0 KStandard error of estimate, 标准估计误差
; f+ A+ c6 @& I% k0 `Standard error of rate, 率的标准误/ L7 y! B: T- A
Standard normal distribution, 标准正态分布
. q: W; j! e3 @, gStandardization, 标准化9 a7 h3 c9 }& Z; |2 ?
Starting value, 起始值
6 G8 x+ L$ J$ o. A, r% _. gStatistic, 统计量1 F# v A) ~: w9 ~
Statistical control, 统计控制
% W& M( L. Y, \0 p1 _: nStatistical graph, 统计图& A) e, m* p, D4 c# J0 m' U @3 |
Statistical inference, 统计推断
/ ? z4 n7 _1 H' z2 eStatistical table, 统计表6 L! Q% Z: Y9 M: W3 C, V
Steepest descent, 最速下降法
: c' m( C# K8 Z4 |8 r' W# j W5 Q JStem and leaf display, 茎叶图
; R$ C' P/ u3 W8 v( l; M& i5 _Step factor, 步长因子
5 O1 o$ d5 v" Q! P8 V- k* XStepwise regression, 逐步回归" _3 U# u6 Z; H% ^9 o
Storage, 存6 o! P5 ?1 U+ d1 H8 B7 c
Strata, 层（复数）( k9 Y* n4 l) k& E
Stratified sampling, 分层抽样
; v; n3 j# M* ?( n! v! PStratified sampling, 分层抽样
+ v# L1 F' R( x! E- B7 i" C' R: P% ZStrength, 强度2 h$ z! B' `2 ` Y- j
Stringency, 严密性4 {' J* e1 y3 y5 R+ c) s
Structural relationship, 结构关系
3 @6 W, [" q: V) yStudentized residual, 学生化残差/t化残差
. n; V. B! B" l6 {! z$ \, F5 ?/ sSub-class numbers, 次级组含量
1 Z" P- Q( ]- \! v, G! XSubdividing, 分割' d) d) O$ y: ^9 G7 a
Sufficient statistic, 充分统计量8 |% _0 A: \! H7 o7 [1 |
Sum of products, 积和- h9 y1 G# V- V$ c5 Y2 ]
Sum of squares, 离差平方和/ _& e1 |1 I9 o0 O* s2 o
Sum of squares about regression, 回归平方和
, \2 s9 e& d7 Y5 Y1 bSum of squares between groups, 组间平方和, w; X( g' j3 ^) b0 a+ m; ?4 I* Z
Sum of squares of partial regression, 偏回归平方和: { }6 a6 O1 D0 M7 I
Sure event, 必然事件4 r# c/ |& V# r5 J8 F
Survey, 调查
1 L3 T d1 o W, E: dSurvival, 生存分析% b% \/ e! s6 L. V7 M) \2 A
Survival rate, 生存率
8 p, R2 ]3 L4 x$ M% ^Suspended root gram, 悬吊根图# Y/ j" m. F, b$ U" u( S
Symmetry, 对称
3 E9 r# B }7 m% uSystematic error, 系统误差
3 O8 P1 s; s) m$ s. mSystematic sampling, 系统抽样
- q5 o0 z1 {/ e0 yTags, 标签; O4 u1 D% D, _: x: ?+ E
Tail area, 尾部面积
5 j S( d$ ^2 A# |3 G/ O3 XTail length, 尾长
; @# i" v# {* K6 YTail weight, 尾重$ x' u& \- d+ Y. y% H& E( b0 u
Tangent line, 切线: @* v, D2 X1 |* w- ]& w
Target distribution, 目标分布7 Q9 m# r/ a9 F
Taylor series, 泰勒级数
8 Q9 g( \6 B4 A9 Q# c1 U, KTendency of dispersion, 离散趋势
# L, U( ~9 u. y; F" I+ c1 bTesting of hypotheses, 假设检验
; p% M8 o9 o( b: q3 uTheoretical frequency, 理论频数
; o6 M2 V( s( J. XTime series, 时间序列 a- l2 }( @% S$ x8 H8 n! W1 |
Tolerance interval, 容忍区间+ H$ s; y; `" P$ ~
Tolerance lower limit, 容忍下限
# z9 `6 {8 S' K6 m4 uTolerance upper limit, 容忍上限5 {6 j) M1 T I' ~
Torsion, 扰率+ I0 r$ Z7 V- g Y& m
Total sum of square, 总平方和
, y. ~0 O3 c2 f2 z4 C* y0 t* |& ATotal variation, 总变异
" s f' `0 e/ Z7 zTransformation, 转换1 Y: c1 F/ W5 `# O) N& K! U
Treatment, 处理$ w4 q+ ]4 U1 e" g2 h# h
Trend, 趋势
; L! k) V5 l4 iTrend of percentage, 百分比趋势
) q; p+ b7 ~# a5 W. B$ XTrial, 试验
% G/ c3 @1 e9 ~: NTrial and error method, 试错法
" l4 P/ O- P. Y. h) uTuning constant, 细调常数. \( ]+ h" v( n' J8 a0 l
Two sided test, 双向检验% B: l5 I6 O) A/ C- L# f6 A
Two-stage least squares, 二阶最小平方
\+ H# ^8 ^) O* ^$ V% ~Two-stage sampling, 二阶段抽样
3 x6 k$ Q( V( r5 NTwo-tailed test, 双侧检验' v" l( M2 s% p( n t1 k) b
Two-way analysis of variance, 双因素方差分析
1 Q6 V7 ~( k) O9 ?: Q; l% [- |Two-way table, 双向表
$ i: q" Y- a* A" [. J2 H% V& \Type I error, 一类错误/α错误
! F( \; J: W, _/ v/ r" L& xType II error, 二类错误/β错误
, ]: V2 ]6 H) L/ d- {% h( ]UMVU, 方差一致最小无偏估计简称
0 k& J/ @# K: q" @# e8 k1 B) FUnbiased estimate, 无偏估计
# t) V' L" q7 f0 A: o) J% O7 R8 {Unconstrained nonlinear regression , 无约束非线性回归" J( _( a0 i& P, u7 ]1 d
Unequal subclass number, 不等次级组含量0 ^0 T% x* n2 g( |2 s# T, y9 D
Ungrouped data, 不分组资料8 s" V' D% j$ E; N0 G$ ?
Uniform coordinate, 均匀坐标
0 S+ [+ i* R5 M: i8 c; _Uniform distribution, 均匀分布
0 l2 F G& V) V+ c0 _9 mUniformly minimum variance unbiased estimate, 方差一致最小无偏估计7 v ?- `( q# R7 ^( \6 ]) q6 Y
Unit, 单元/ b& o# ?! m- x8 S& ]
Unordered categories, 无序分类/ ]9 C1 Y4 m0 V' k5 X5 e8 m- D6 e
Upper limit, 上限
% k/ s2 u7 k8 n5 r% Z; oUpward rank, 升秩+ t. ~! ]) U v5 h" ` o/ z
Vague concept, 模糊概念
2 e& d" b0 F {7 @+ {! s# `Validity, 有效性2 G- ^2 a. U* U3 @
VARCOMP (Variance component estimation), 方差元素估计& M0 e( K* b/ P3 h. k! `
Variability, 变异性
* p' S. d9 t' m7 D! V/ @/ \2 NVariable, 变量
3 C" F) d# e, n2 Z+ dVariance, 方差/ A8 E' t8 }, _# m3 s9 K6 R% ?% l
Variation, 变异
7 ~: q! W$ i, C: {5 J4 n( D3 BVarimax orthogonal rotation, 方差最大正交旋转: A H0 F: Y9 Q2 n4 d, a# P
Volume of distribution, 容积
7 Q! l$ F' I0 C, z3 [W test, W检验$ o( z: r1 \$ I: X) V
Weibull distribution, 威布尔分布
) y! |( u4 {. [5 u) `+ O. SWeight, 权数
9 e# T0 l" d9 h+ c, C" ^; W/ j5 R! aWeighted Chi-square test, 加权卡方检验/Cochran检验 d, C" B c$ T
Weighted linear regression method, 加权直线回归% }5 U, a$ s- O/ e1 l( {% c* ^8 {
Weighted mean, 加权平均数
* x9 V" O; P7 @Weighted mean square, 加权平均方差
8 G! A8 L. E# U" {1 nWeighted sum of square, 加权平方和
2 M" l$ L. X& ]9 L2 q5 ^Weighting coefficient, 权重系数
1 L& Q/ a/ c" QWeighting method, 加权法
: K& y1 I0 ~, w% t* u- K& ~% xW-estimation, W估计量
0 A! v, ?! Z/ Q, U2 nW-estimation of location, 位置W估计量3 h' f; C, V( L2 W
Width, 宽度9 j6 E; B- u7 |) F
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验: R; \5 M6 d# G1 A% P6 `
Wild point, 野点/狂点
% D* K9 P: u# @! d# fWild value, 野值/狂值
0 |/ Z1 k+ t- HWinsorized mean, 缩尾均值
; D- K1 n$ |; `/ P! T: BWithdraw, 失访
- E. Y. b& U0 B, rYouden's index, 尤登指数& X, m6 y/ D+ v/ S+ t V
Z test, Z检验/ [2 E( z( [& j$ c1 M3 i9 j
Zero correlation, 零相关
1 ~. V4 ]+ M4 dZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
