|
|
Absolute deviation, 绝对离差
4 p1 u0 _$ T% L4 V1 U/ v _2 cAbsolute number, 绝对数
9 J" j2 r5 b- }5 H3 iAbsolute residuals, 绝对残差
+ X: E+ C6 m# \Acceleration array, 加速度立体阵
& Y& t: e- B' s2 o. j, eAcceleration in an arbitrary direction, 任意方向上的加速度
; M1 o) f" Z6 r% y9 aAcceleration normal, 法向加速度
& [ F/ {1 z. Z% uAcceleration space dimension, 加速度空间的维数' G+ b3 m- W7 B; w) M) w
Acceleration tangential, 切向加速度
! m9 M5 W$ v! P( C3 p1 y, xAcceleration vector, 加速度向量% B& [% l0 O3 h. V; Q& s8 N$ m
Acceptable hypothesis, 可接受假设4 ]/ u$ d) p0 E. ^
Accumulation, 累积1 k* N$ Y2 u: U" X( y1 j# f$ ?
Accuracy, 准确度3 _, L4 Y j. s( ?4 [ U
Actual frequency, 实际频数
( A" q) ?3 }6 V: P' |- ~: k& |* a' HAdaptive estimator, 自适应估计量 L+ x4 A c% Y
Addition, 相加
% C9 c& ?1 g( {Addition theorem, 加法定理, |! g6 S' f% o4 i
Additivity, 可加性
, j; h$ m' U9 q4 j- k5 p) F2 `Adjusted rate, 调整率
$ ]. ^4 h0 |0 D9 k5 t0 s" B; o! PAdjusted value, 校正值
& e0 m/ d8 E# |! r' z$ MAdmissible error, 容许误差3 F d/ {9 H1 i( H, `
Aggregation, 聚集性7 x* m/ {: O4 L0 T
Alternative hypothesis, 备择假设
9 u2 ^) R) ]7 Z+ Z. PAmong groups, 组间
; E1 c" O& Z7 `5 c% ?# w' iAmounts, 总量3 K0 \; k; U! W# [7 j* [/ L
Analysis of correlation, 相关分析2 \6 f/ @8 b4 h) o0 [! ]
Analysis of covariance, 协方差分析
, W3 M) ~8 j! cAnalysis of regression, 回归分析
5 O* X$ M A, |7 _2 SAnalysis of time series, 时间序列分析
& `1 Q# R* I$ U* U2 a$ h0 ^Analysis of variance, 方差分析5 P) h! {4 S+ s& L' h) G7 Y1 E, r
Angular transformation, 角转换
0 U+ W" X) y7 e3 R% C9 y- l/ e vANOVA （analysis of variance）, 方差分析: D5 R, g5 f( Q- Q% w. r( {
ANOVA Models, 方差分析模型
* w( R" c+ M8 E2 Y. eArcing, 弧/弧旋
# b B9 `2 {( y- @Arcsine transformation, 反正弦变换
9 g- Z" T" A/ S& V7 r1 a) X' zArea under the curve, 曲线面积
% {% y& B" t; }: r: L4 E3 TAREG , 评估从一个时间点到下一个时间点回归相关时的误差 0 K* f& B3 \0 H
ARIMA, 季节和非季节性单变量模型的极大似然估计 8 `6 _7 s0 D3 e {3 L4 u Z; g
Arithmetic grid paper, 算术格纸
% i& a6 t6 d; \1 p! dArithmetic mean, 算术平均数
% i1 d. v4 t8 E/ l6 pArrhenius relation, 艾恩尼斯关系
4 `, R) I" r5 X3 T! H+ R: TAssessing fit, 拟合的评估
2 k( I8 J' l* C$ LAssociative laws, 结合律
& w/ W5 J, b, p7 X& a+ v1 O; wAsymmetric distribution, 非对称分布
: h0 C/ V, L! P7 L' m2 qAsymptotic bias, 渐近偏倚; _1 T# [. v) @/ `
Asymptotic efficiency, 渐近效率
! y5 q/ _" z1 X3 H' p& o& Z/ iAsymptotic variance, 渐近方差
* b" O% p% |- h9 o% Q, E% H" xAttributable risk, 归因危险度1 s" d. d% b1 ^. \
Attribute data, 属性资料
& ], O/ M7 r, \/ S& D! q+ j7 w/ v' }9 aAttribution, 属性6 D" E; z3 |9 T% o3 u8 y$ b
Autocorrelation, 自相关# d) \, V1 Q5 J( t& |! t$ G/ n% C; t
Autocorrelation of residuals, 残差的自相关$ d2 S7 ~1 f4 e& s3 |2 ]
Average, 平均数
! O5 Y) y! i9 K4 N, cAverage confidence interval length, 平均置信区间长度
& U8 A* `. I- l9 ]4 T- Q7 r% TAverage growth rate, 平均增长率
3 E4 `+ @+ ] J: p ABar chart, 条形图
3 G+ O8 G P6 o$ a8 _, NBar graph, 条形图
, L, C" Y. W+ D: I3 S9 sBase period, 基期
5 c, r" I( E6 n+ L; mBayes' theorem , Bayes定理2 L3 E8 s" G: r! v0 U4 O( S G
Bell-shaped curve, 钟形曲线
7 T2 {8 G/ A G W' _Bernoulli distribution, 伯努力分布) r7 X9 E. W; W/ A5 {5 t
Best-trim estimator, 最好切尾估计量2 g6 M) r2 O7 {
Bias, 偏性3 _1 S/ r2 r3 y' F& v7 ^& S2 i
Binary logistic regression, 二元逻辑斯蒂回归& [' M O* R+ \3 Q- T
Binomial distribution, 二项分布
& f' i! D1 j; a Y8 P' BBisquare, 双平方
. f& V% z* |! _8 n1 @3 t3 \ jBivariate Correlate, 二变量相关7 Q; {" b1 m2 ]4 s" I4 Z
Bivariate normal distribution, 双变量正态分布
* D; N3 J; o8 I* r/ A) {, rBivariate normal population, 双变量正态总体: {% Z: z& Z% R. p
Biweight interval, 双权区间4 v* L6 J5 z! t3 I$ p
Biweight M-estimator, 双权M估计量
6 @3 ?) E* z+ H* m, GBlock, 区组/配伍组
$ d: _3 q3 X( B" F; \+ {/ R" `BMDP(Biomedical computer programs), BMDP统计软件包
0 d4 O) _( T1 f7 g+ S2 Q0 g/ o- T% QBoxplots, 箱线图/箱尾图
; F& j7 P8 O) O: H! P8 G0 G( cBreakdown bound, 崩溃界/崩溃点" f+ }: [8 O$ X6 B9 z' ~
Canonical correlation, 典型相关
) |$ o' _) N% K, u" F6 O7 SCaption, 纵标目 o+ \% E# M3 x& p) V
Case-control study, 病例对照研究# w2 R1 \( q: d: q
Categorical variable, 分类变量
% D: _" _7 }$ N4 c+ f3 u8 M/ GCatenary, 悬链线3 M: X+ `. ]4 U. O$ ^& g! L) u
Cauchy distribution, 柯西分布- k' U0 n. V4 M, P8 I+ _6 W
Cause-and-effect relationship, 因果关系
5 A& I a V* Q3 c: J1 RCell, 单元+ x- S( k4 _' A: o6 L
Censoring, 终检
6 x/ I! Y+ S, O! p/ z1 L$ C7 @5 ~Center of symmetry, 对称中心
1 T/ g" _3 D) Q7 B( \. I( p+ I! l7 `Centering and scaling, 中心化和定标
. t; z- z0 N2 J- f$ p rCentral tendency, 集中趋势1 a! v4 q& M2 ~- k t2 k
Central value, 中心值
: g7 a8 T6 [; H* iCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
$ G! X1 x7 o. [Chance, 机遇7 i% M/ S. }# H+ R" d" L2 U# C
Chance error, 随机误差, \9 j# }/ N. l& E' c
Chance variable, 随机变量0 L3 O( \7 P# K; J
Characteristic equation, 特征方程$ V0 E) z2 H; v) b0 N6 v4 G
Characteristic root, 特征根+ P( t! K5 {9 _8 s& _# `, |2 H0 B4 C
Characteristic vector, 特征向量
' W7 }% B f8 |, }3 bChebshev criterion of fit, 拟合的切比雪夫准则# n$ z* {" g6 Z8 [
Chernoff faces, 切尔诺夫脸谱图, o3 @5 X% C. Q: ^
Chi-square test, 卡方检验/χ2检验9 A+ T% @6 c; s) n
Choleskey decomposition, 乔洛斯基分解4 w8 t. T4 w4 m4 ~; s/ M
Circle chart, 圆图 ' c9 w8 p8 C: }0 W/ D, ]* v! n
Class interval, 组距% K" y- W! T) r# l
Class mid-value, 组中值! V+ c# p- R z! u$ M
Class upper limit, 组上限; ~3 W1 b8 \5 e& N5 D
Classified variable, 分类变量' H4 @3 a" W( T; S4 M9 }
Cluster analysis, 聚类分析
5 z1 V0 o2 }* o2 G8 yCluster sampling, 整群抽样
8 P+ Q' a9 N8 p' F! c' L/ QCode, 代码
/ I. M0 s' _. \- u7 MCoded data, 编码数据
+ M# c& \1 O8 \Coding, 编码, ] x L- l8 T
Coefficient of contingency, 列联系数
& B6 Z3 P) p+ Q, x% Y$ \1 s1 ^Coefficient of determination, 决定系数
9 T- U5 X! N J& n) w/ k7 x4 `/ CCoefficient of multiple correlation, 多重相关系数
0 a* n5 X' B: {, HCoefficient of partial correlation, 偏相关系数
$ |8 v$ v8 ~2 `# D4 a9 vCoefficient of production-moment correlation, 积差相关系数$ [, g5 P& B+ A3 P; y \
Coefficient of rank correlation, 等级相关系数
+ T( }$ e" D- U& c1 SCoefficient of regression, 回归系数
; P9 X t: j4 }" w3 Y5 ~Coefficient of skewness, 偏度系数; E- I) ^! a6 I; C( ^2 F3 {
Coefficient of variation, 变异系数, b9 m1 U( B. A3 C! p ^0 O- X
Cohort study, 队列研究
9 N5 Y0 [: P4 HColumn, 列0 p7 y8 L3 M" s7 H8 p& o2 @
Column effect, 列效应
7 I3 r' e0 \7 z- U5 ]: a7 BColumn factor, 列因素
2 R5 C/ m$ j7 eCombination pool, 合并 f* A B( Q9 K+ N& M2 k5 s5 [
Combinative table, 组合表, ]) g# X; a' F! V
Common factor, 共性因子
: D1 c7 j2 j; o% u4 qCommon regression coefficient, 公共回归系数4 c# K, o: t, ]% ?( y# G
Common value, 共同值# I, u. \8 [" `4 \- {7 |
Common variance, 公共方差7 F0 l z: a: \: p8 I3 S7 R) C) ]( t
Common variation, 公共变异
1 k# T% {5 L) L$ JCommunality variance, 共性方差, g8 @/ ^; T# p2 [$ q& A
Comparability, 可比性9 m1 `! H5 I/ y( K, I
Comparison of bathes, 批比较
" v9 F4 |; y! m- B2 E# [% Q2 cComparison value, 比较值9 v3 M1 S7 A: }" @8 |
Compartment model, 分部模型9 F9 `1 q( S6 U1 t0 h
Compassion, 伸缩% d1 p1 h' G3 r( }% h
Complement of an event, 补事件
: Q L3 t) g8 k* pComplete association, 完全正相关
, T% n1 O% u6 P* q w* c0 m7 ?Complete dissociation, 完全不相关& J! k. H6 M7 r! p( i
Complete statistics, 完备统计量5 C Q0 h4 f- M/ ~2 c
Completely randomized design, 完全随机化设计
8 C, q% |' [5 ~8 h, m3 T, a3 s' ?' L- [Composite event, 联合事件
6 s Y" w/ J/ P& w; [# u' }# W- }Composite events, 复合事件) J7 ?- X" z& e# r& h* { B
Concavity, 凹性5 V+ q: M) h5 K2 s8 L
Conditional expectation, 条件期望. [7 n; A1 ^ n) r9 V: t0 x2 S3 X. R
Conditional likelihood, 条件似然
9 J3 K9 N% p' R/ ]. o9 W0 X4 MConditional probability, 条件概率
# J. |/ R6 v5 q1 S! fConditionally linear, 依条件线性
6 ^6 x* v0 H& W2 V" |: Y# o3 `' EConfidence interval, 置信区间
2 J) X- U; ~5 ZConfidence limit, 置信限
% ^! T8 C) r9 t& g) VConfidence lower limit, 置信下限
4 A% s2 C2 P9 g2 R$ T" VConfidence upper limit, 置信上限
( D2 u- }# B1 E# s$ pConfirmatory Factor Analysis , 验证性因子分析; ^4 C* T; B1 e' f' f
Confirmatory research, 证实性实验研究% z& p2 y3 P% M. k" I! @
Confounding factor, 混杂因素# Z" f0 Q; I6 g5 F q" U, |
Conjoint, 联合分析2 G) O# i6 s* ?
Consistency, 相合性# t$ z/ U2 S8 s$ h( f
Consistency check, 一致性检验
! M2 [# v, `/ J; G6 c; }$ D" J1 ZConsistent asymptotically normal estimate, 相合渐近正态估计$ [; M3 ~: o: ]0 O" i
Consistent estimate, 相合估计
D( V0 l2 N0 }6 u) zConstrained nonlinear regression, 受约束非线性回归
! Y4 T; Y# @9 [4 U8 a* b* `- \Constraint, 约束
" {* F, u1 k, Z. {# J7 T! F$ l" vContaminated distribution, 污染分布) f) X( a. i* g# }/ Q) Q
Contaminated Gausssian, 污染高斯分布6 I c; `' h) G. G# W! k/ q
Contaminated normal distribution, 污染正态分布6 l: X7 s5 o# d s
Contamination, 污染- P; D* v# A* [1 b/ a0 D* T
Contamination model, 污染模型9 E: q& {# ]; f0 r, P4 Y
Contingency table, 列联表: F5 S' K/ ^6 V9 W O5 k4 B
Contour, 边界线
. g( _& [9 }; I9 w- iContribution rate, 贡献率
4 }5 C5 \# V8 hControl, 对照
1 B' f( b/ |4 O8 uControlled experiments, 对照实验: I8 S, z- q9 @# _ N
Conventional depth, 常规深度
0 a& M3 C. } l5 `9 z/ |Convolution, 卷积9 E0 Y4 I9 L" e$ _/ H& ?
Corrected factor, 校正因子& C6 O+ b' V" N. e! l3 e
Corrected mean, 校正均值
! J5 O+ R7 M7 c! `! n; [Correction coefficient, 校正系数( @" q5 w, o( n7 H
Correctness, 正确性
, D. s, s3 q8 H! X* v4 H7 M" w2 Q% cCorrelation coefficient, 相关系数" V0 s& p3 p/ v1 [4 @7 a- ^
Correlation index, 相关指数; ?* t# Q9 L/ [) _
Correspondence, 对应9 r' x0 e" V. I S( b
Counting, 计数* B# E. {! r! C4 v" S$ o
Counts, 计数/频数
8 P: T$ E; j) K! Y( QCovariance, 协方差8 _8 H9 ]1 _ w4 [+ ~9 V: F
Covariant, 共变 9 V9 d4 T4 I6 c( T, f) U2 d
Cox Regression, Cox回归
$ ^" {+ b( x) }* a) p1 v+ w8 i. eCriteria for fitting, 拟合准则
. z+ K. H6 z( _3 V( ^8 hCriteria of least squares, 最小二乘准则
/ M) i; \* G) O: n0 D, U: j$ ^$ CCritical ratio, 临界比
7 u7 b6 L+ G: p8 xCritical region, 拒绝域
. h. G3 Q2 o$ C0 _ ] Q6 I1 | WCritical value, 临界值
% r* v) O) Z( |2 gCross-over design, 交叉设计0 O7 J; x' k; w T$ I# k
Cross-section analysis, 横断面分析' k6 U F( O& n4 z% _! B! ^( P
Cross-section survey, 横断面调查
$ K5 v3 d, T# [% B5 o% {Crosstabs , 交叉表 * V1 w2 Q( d& B9 j/ b, g3 T4 e7 }
Cross-tabulation table, 复合表% K i7 Y# G. x
Cube root, 立方根
0 v0 a% X9 Q0 j1 Z1 r, H7 g$ P0 ^Cumulative distribution function, 分布函数
9 p) i6 K/ Z5 e+ y) ?2 i$ F: F9 u/ FCumulative probability, 累计概率
( E7 p1 |3 Y6 @& |- S: `# l1 wCurvature, 曲率/弯曲
; t% X) K$ n4 [Curvature, 曲率
# [ w! G6 x' y3 N n, gCurve fit , 曲线拟和
" }8 x% W* j. b$ h8 ^ K$ t ~Curve fitting, 曲线拟合
" \+ Y) X% D! i( f& @6 \Curvilinear regression, 曲线回归
" V0 |. z/ m5 O7 [) z; XCurvilinear relation, 曲线关系
/ f2 ^; L$ S. P" a( x) t) r. pCut-and-try method, 尝试法
7 E r& v2 |# _& vCycle, 周期
' ?, d; R; k8 `& q* Y NCyclist, 周期性9 o' F' C' ]) H# o0 m6 c8 r
D test, D检验: O' C' T( p$ d% w
Data acquisition, 资料收集3 n) C9 c' e2 r: }( V1 }3 d. {1 V/ i$ P- [
Data bank, 数据库; P& H4 _( Y7 q+ O1 X; h
Data capacity, 数据容量5 {$ N8 {! y7 { }5 D. G0 S
Data deficiencies, 数据缺乏9 G& [6 B5 }7 B# |" @
Data handling, 数据处理" I" l! Z) E* u* n! ^+ f
Data manipulation, 数据处理/ ~% o) T! A* S: ]
Data processing, 数据处理
# M1 o* `6 ^9 T0 L6 nData reduction, 数据缩减0 V5 t# m* o4 j! v$ I
Data set, 数据集
6 Y, }3 e2 M& K: q$ ?Data sources, 数据来源
/ a( e2 E, R3 ? V- m% aData transformation, 数据变换- K: i' T | [0 a
Data validity, 数据有效性( m. E& c6 V( [& f
Data-in, 数据输入2 P+ Q4 O4 P4 |9 S+ z5 l& f
Data-out, 数据输出# J* G4 ^8 n+ h% }+ w) N8 N6 m
Dead time, 停滞期. E& d/ I' F2 y* G& r1 f
Degree of freedom, 自由度4 H: }" O( m2 N7 e6 k: b
Degree of precision, 精密度
* K7 H# O0 T$ nDegree of reliability, 可靠性程度
% E$ w5 l& _. V% mDegression, 递减2 }! q! h' T: ~# f( ]$ A
Density function, 密度函数
! \+ k3 }2 Y5 gDensity of data points, 数据点的密度
# e* ] J# |0 |9 qDependent variable, 应变量/依变量/因变量
8 A, j8 m, S7 X2 C9 A0 M+ O& MDependent variable, 因变量; R6 ~7 f3 u$ H8 a3 ^
Depth, 深度
/ J9 e c6 e2 NDerivative matrix, 导数矩阵
0 r4 E. e3 B; s M/ }9 z9 ADerivative-free methods, 无导数方法
( J5 l) t3 Y$ T1 W/ W% j1 JDesign, 设计 H( O7 L+ ^( m- C# Q/ ^
Determinacy, 确定性
1 L5 r/ Y/ ^. e! h6 ^6 }& SDeterminant, 行列式2 [' O3 {8 r( t
Determinant, 决定因素
0 D! l" w( A' ]Deviation, 离差
6 E( Z& d9 v, {9 u" cDeviation from average, 离均差
0 i0 G& l/ R% f L7 SDiagnostic plot, 诊断图( ~+ n1 w) M! a
Dichotomous variable, 二分变量
' L& L& Y( v* P$ e: \8 t5 \Differential equation, 微分方程
; G; w7 X) N; Y7 F2 i/ rDirect standardization, 直接标准化法
% ?% P( v1 d, s* EDiscrete variable, 离散型变量4 z+ D( q6 \2 u2 V2 |
DISCRIMINANT, 判断 ! @. h. |9 u! d1 C/ _
Discriminant analysis, 判别分析9 k& L' D: k2 B" } ^
Discriminant coefficient, 判别系数2 x4 v, o8 c5 s4 @9 o: M1 I
Discriminant function, 判别值& Q9 K9 a- h, S- }; ] u
Dispersion, 散布/分散度
" g$ k& c" z$ WDisproportional, 不成比例的
1 g+ `& l6 \* R, ~3 \Disproportionate sub-class numbers, 不成比例次级组含量
4 X- D$ T6 Q. v5 `6 y% NDistribution free, 分布无关性/免分布3 Q5 \& x! p* p' p2 M
Distribution shape, 分布形状
! |- M/ {( @! b/ l# t* G5 R; _5 w. QDistribution-free method, 任意分布法3 O$ S! b* V$ D, p) x
Distributive laws, 分配律
2 B6 h0 c: r# CDisturbance, 随机扰动项
3 u2 B. @6 G1 |2 {, R: Z/ a1 PDose response curve, 剂量反应曲线
: t/ s7 R8 S D+ P/ gDouble blind method, 双盲法
$ d9 H2 K& c* d8 i# T; R* dDouble blind trial, 双盲试验1 l# L( {8 }$ Z' C; R
Double exponential distribution, 双指数分布
% L \% K8 V& g) {Double logarithmic, 双对数5 h4 ] B( C3 r, l# c
Downward rank, 降秩
/ ~+ N% _7 t+ g8 D" }" G$ O& H; O" zDual-space plot, 对偶空间图) u( v( P% z% _7 T! C. C) F+ r% p
DUD, 无导数方法' x+ k; v5 v/ k2 i2 y, [3 l' G
Duncan's new multiple range method, 新复极差法/Duncan新法
2 @9 S" I% Z" j, AEffect, 实验效应
2 e7 Q( m, L2 I2 |4 u+ x' FEigenvalue, 特征值
4 }; a) o# Z. P9 AEigenvector, 特征向量# _$ w, E! S3 Q4 T
Ellipse, 椭圆5 n2 \& @; b, w l1 _! z; E" V
Empirical distribution, 经验分布
/ |+ m$ v9 @6 _) M5 b' e) b8 xEmpirical probability, 经验概率单位
5 A- ]( {" s' ?% n9 z7 u$ O7 k; T# @- EEnumeration data, 计数资料
1 m& x2 ?9 d2 c! c, YEqual sun-class number, 相等次级组含量, t$ V2 p( F( u% b
Equally likely, 等可能6 `3 G; e; L2 p8 i @
Equivariance, 同变性- a9 [! D3 g# R" D. g+ C
Error, 误差/错误
& f( Z8 T* ^8 C1 l6 B, G* j% A7 S' [Error of estimate, 估计误差; O% V( q+ g1 N# R+ J: Q
Error type I, 第一类错误
, }+ Y7 l* ~6 F; k" a. wError type II, 第二类错误% |8 J% h2 n# x# m; |( e7 v) w
Estimand, 被估量, q% I. C9 ?. _6 O7 E. h
Estimated error mean squares, 估计误差均方* ^. f/ g, ~- s0 M
Estimated error sum of squares, 估计误差平方和
! F: r, x0 T3 u2 v; p- G( P: B' f) nEuclidean distance, 欧式距离
1 q# T- [; i0 j4 S8 e# lEvent, 事件
6 v& x; f, T ZEvent, 事件/ x: _: f9 \" i1 C. o! A
Exceptional data point, 异常数据点
- e. a' D1 Q& a; MExpectation plane, 期望平面
8 D" ^3 n/ m/ K) c- U5 ^5 [Expectation surface, 期望曲面4 H8 c% ~& R& R. {" `( E# \
Expected values, 期望值
' G' d- o: w: {, o8 ^3 e( @, iExperiment, 实验7 m9 z7 r0 e3 x. q3 N7 H V
Experimental sampling, 试验抽样
P( O: G& b. e0 X- O, x% cExperimental unit, 试验单位5 ?, N1 B( E6 t0 c! P
Explanatory variable, 说明变量
3 R' G& n6 K# ]% ~4 A/ I4 UExploratory data analysis, 探索性数据分析+ t; Y1 ^ w# w$ o; T% x* _ N4 B) M
Explore Summarize, 探索-摘要& O& I5 k/ o: f- i6 a7 x. \* x
Exponential curve, 指数曲线
" u( I" o- {; |3 G2 K5 qExponential growth, 指数式增长
7 | f, c, }' d" t% }4 YEXSMOOTH, 指数平滑方法 ; d% y K7 i# x3 f
Extended fit, 扩充拟合
% g# N. f/ z. s1 N. m- eExtra parameter, 附加参数
2 {% t1 e' `! O8 O* x& h6 aExtrapolation, 外推法0 Z5 E; Y' j8 w' ]
Extreme observation, 末端观测值
" f h* J$ X4 H& ]7 L& ]' w' OExtremes, 极端值/极值 h8 M" @! x. F+ W: p4 @
F distribution, F分布# ]& F5 O5 s5 V7 g( P5 v
F test, F检验" P8 r# I1 b2 h. X
Factor, 因素/因子, t: v }# G# p) Y* V+ J
Factor analysis, 因子分析
; v+ E6 P6 _) v: E bFactor Analysis, 因子分析( V6 r0 B3 m; x ]0 x
Factor score, 因子得分 ( T C- \# N3 o: _* }' J0 `
Factorial, 阶乘
T$ t/ l, X; G$ S1 `! bFactorial design, 析因试验设计/ p+ Q) e3 M2 S* A
False negative, 假阴性
5 `$ o3 Q- B9 }" S4 ]4 @. cFalse negative error, 假阴性错误2 k0 X3 w% ^5 d0 o1 I j7 C
Family of distributions, 分布族, P" r* L G3 N0 q9 S# N% g8 P* E
Family of estimators, 估计量族
8 J5 _2 H" H- f7 A2 |7 WFanning, 扇面: X$ Y( @0 o9 u8 \4 L5 y$ j
Fatality rate, 病死率& \4 F, s. y/ q5 b7 V8 }; t4 Q L
Field investigation, 现场调查& w! `7 Z2 K) D3 P/ F" ]
Field survey, 现场调查0 k2 e( L4 g: @8 y2 J4 @
Finite population, 有限总体
: K& O7 {8 X6 ~+ m* NFinite-sample, 有限样本- c6 P! ]/ d& [
First derivative, 一阶导数$ b6 z! k5 s, ]
First principal component, 第一主成分$ t) g( P4 I4 b [9 F0 ^
First quartile, 第一四分位数3 y0 N: Y( i' \) a, E+ c
Fisher information, 费雪信息量
) V7 ?; O; P9 Y. k8 u4 tFitted value, 拟合值
- O' k7 i) ?& z& r5 F+ mFitting a curve, 曲线拟合, c; K& O4 ~, H5 f, z7 j3 F
Fixed base, 定基
" P9 z; m5 c W8 lFluctuation, 随机起伏! L9 }! M( L, J7 a) h. g" M, }3 w. B
Forecast, 预测' [! T* m4 B8 p( F
Four fold table, 四格表0 \- ?& \& C5 Z' `+ L6 K0 J
Fourth, 四分点
- s7 M8 I! o" [3 o0 u3 y/ y' Z) BFraction blow, 左侧比率
5 `% ^' H0 ?" K: J! y8 W0 mFractional error, 相对误差: j; P+ x& M! R( T- I! n
Frequency, 频率
* l8 B' M' w# b* ~1 G) z3 d1 lFrequency polygon, 频数多边图: b4 j' |- V5 u" V+ u- P5 A5 Y$ P
Frontier point, 界限点
# Q% T7 w: t8 ^- H/ q: bFunction relationship, 泛函关系
! x9 l: O& k; ^9 R& d d% T) C0 gGamma distribution, 伽玛分布0 P+ d2 D; Y. w- C. l0 p
Gauss increment, 高斯增量) a5 K9 c, L- |" G9 Y
Gaussian distribution, 高斯分布/正态分布0 Z! l. Y' T; e9 ~8 F* m S
Gauss-Newton increment, 高斯-牛顿增量
. b! [4 O/ j: |0 jGeneral census, 全面普查- Q' X D' ]' q0 ~% o5 A2 l
GENLOG (Generalized liner models), 广义线性模型
7 \$ z9 t! w2 Z7 vGeometric mean, 几何平均数: {5 c7 c3 d- c' \
Gini's mean difference, 基尼均差
- E' N+ T/ l2 Q3 k1 lGLM (General liner models), 一般线性模型
- w4 R$ e& y6 uGoodness of fit, 拟和优度/配合度
& c" ~+ n* i2 m8 S0 q) I7 CGradient of determinant, 行列式的梯度
. j" x# j( G4 O4 ^Graeco-Latin square, 希腊拉丁方6 ]6 ^- _/ ]1 r6 w6 q- u
Grand mean, 总均值# h, ?% [9 X) p1 k
Gross errors, 重大错误
e/ p5 \) {/ B. S+ TGross-error sensitivity, 大错敏感度7 F, X2 q6 \9 r
Group averages, 分组平均
6 o! \, J" m" O6 j1 Y& BGrouped data, 分组资料
( V+ U" H2 F/ k2 n# jGuessed mean, 假定平均数" p4 s2 @2 m3 J* V4 v$ y+ i
Half-life, 半衰期
& t+ P3 c3 O6 ^& j6 rHampel M-estimators, 汉佩尔M估计量
* q0 Z; @; p7 P$ ^$ v) R8 P2 u( xHappenstance, 偶然事件
6 E% I2 j+ w7 U' [3 wHarmonic mean, 调和均数; p* N* c6 ~; t/ ]& s
Hazard function, 风险均数
9 A/ v2 j/ p1 SHazard rate, 风险率
- ~3 P+ l3 S5 r% `' G& i9 f: bHeading, 标目 0 H7 y a3 h; Z7 \! y. w: E/ u0 j
Heavy-tailed distribution, 重尾分布: P" J6 E9 \) M4 R( e a
Hessian array, 海森立体阵
7 C7 T/ ?7 N; z" o+ k& W, l2 VHeterogeneity, 不同质. G9 ]5 J$ E" t2 C9 K
Heterogeneity of variance, 方差不齐 8 d4 t0 {2 k: l. i' Z" V! B, L
Hierarchical classification, 组内分组
- h; x7 W9 u7 F+ z2 aHierarchical clustering method, 系统聚类法
# n9 e; c+ d* @9 G+ N5 u, GHigh-leverage point, 高杠杆率点 E4 V. e0 X D& z/ e: v/ z: q
HILOGLINEAR, 多维列联表的层次对数线性模型
8 `6 R3 [: v& m2 {' ?+ hHinge, 折叶点" K i: q4 a4 n! ^/ `7 U) X
Histogram, 直方图5 a$ Z1 a5 o: h3 u; e9 ?
Historical cohort study, 历史性队列研究
% d7 y( i7 c% R2 K' U; { dHoles, 空洞
: D. w: U: L4 c# oHOMALS, 多重响应分析
; ]% R5 a7 x0 I# u( t, DHomogeneity of variance, 方差齐性
1 h# `4 c% C; @ ^; P% {- r0 QHomogeneity test, 齐性检验" i' u% N( n7 q/ G
Huber M-estimators, 休伯M估计量5 y1 g1 w# u: M% m. Y7 ~$ i6 |9 O
Hyperbola, 双曲线
0 `" d# N% G9 P0 n9 f4 [) LHypothesis testing, 假设检验
2 G+ m- s; o3 v* s! V; r( F1 jHypothetical universe, 假设总体/ R1 p: @' c- \1 q9 F6 `
Impossible event, 不可能事件 `4 Z7 Q+ Q1 [: K o9 B+ f
Independence, 独立性2 {; s' e8 H+ {. f. p7 B: k/ _
Independent variable, 自变量
x2 l) u3 p) H, _9 K. i7 SIndex, 指标/指数
% ~. {' i, z# u4 n9 a1 q0 g! lIndirect standardization, 间接标准化法7 M! U C6 J; ~: r @. U- G* q
Individual, 个体) R; ~* }; k* t6 ?: B
Inference band, 推断带! H% \/ d& {5 K7 Q8 ]
Infinite population, 无限总体2 k) m/ _- Y0 S1 I+ T4 q' d
Infinitely great, 无穷大
& a0 F3 J7 K, XInfinitely small, 无穷小* d( \9 u! P6 }) B
Influence curve, 影响曲线
# m' F" i& T, lInformation capacity, 信息容量5 a, L( g: t% Y" R
Initial condition, 初始条件$ |" y* O4 z/ ?" R5 h2 C) I0 a
Initial estimate, 初始估计值
& Y) _# v2 X5 h6 r( TInitial level, 最初水平
+ C. z: T; Z% A0 _5 VInteraction, 交互作用
& i- k4 U# e: p& i' @1 \3 n% L2 Q1 t; uInteraction terms, 交互作用项
2 q# a, H' u* }4 iIntercept, 截距
( W, H( T+ Q+ }Interpolation, 内插法
/ B: F" W8 @& a, h& H; j6 M/ J' TInterquartile range, 四分位距
. G4 C g+ h$ _# }, DInterval estimation, 区间估计
8 Y; |$ k1 E" `0 G& l' \' Y& r4 ~Intervals of equal probability, 等概率区间
9 e7 k3 C7 T% l8 A1 h: CIntrinsic curvature, 固有曲率
0 \' E, V$ W+ I. ]Invariance, 不变性; X/ a" N }4 a
Inverse matrix, 逆矩阵
/ r: W( G( ?! ] Q* m# \( oInverse probability, 逆概率 u, h4 r U: v' p3 Y, I
Inverse sine transformation, 反正弦变换
& w1 k' T+ i3 X) i: NIteration, 迭代
6 f$ h' Q* M( O* d0 `" M EJacobian determinant, 雅可比行列式% F/ \5 `4 H) t2 _8 o* R. F( u
Joint distribution function, 分布函数+ R' H+ u9 t% ^ k6 p& c, V
Joint probability, 联合概率6 `7 P" X. m+ _- n' c5 c
Joint probability distribution, 联合概率分布; ~9 \5 b, E, b- ]/ i8 \9 u0 l
K means method, 逐步聚类法2 ]9 {2 [9 z& q7 |# k* A$ U
Kaplan-Meier, 评估事件的时间长度 / t2 M) |( v) z
Kaplan-Merier chart, Kaplan-Merier图
! n. X7 x6 y4 Z1 P2 [Kendall's rank correlation, Kendall等级相关
$ F( V0 S! x+ ` e. j/ w/ mKinetic, 动力学
8 e- b0 l; n6 z. T0 u* w/ m4 MKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
. p0 ^1 A5 x( H' ^) M# ^, WKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验& N% U2 X0 \4 t2 I9 u: V# Z
Kurtosis, 峰度
7 r! o5 g1 Q' c3 y! t; U2 W5 YLack of fit, 失拟
/ j) }2 K3 X4 \! w4 Q$ H. ^7 fLadder of powers, 幂阶梯& f R7 p s; D! d" o2 Q
Lag, 滞后
, X. T# ~; P- b/ k0 A+ ALarge sample, 大样本
2 T) A2 r, Y# I, B1 E9 V2 }$ hLarge sample test, 大样本检验# d4 e8 W# Z) n3 T! B E/ L
Latin square, 拉丁方6 R6 s5 T, d7 X: O/ g; K- d( P
Latin square design, 拉丁方设计
/ |: C$ U+ U1 l) kLeakage, 泄漏# `! ?! F3 G! U& D0 Y+ j" \7 o
Least favorable configuration, 最不利构形
6 g/ g, E( M/ E0 _+ f" }Least favorable distribution, 最不利分布: W6 L0 B7 Z5 I& a& ^; R% T6 Z# E [1 I
Least significant difference, 最小显著差法. P+ u0 P& o! U+ d: r' C, K, u. L" t- o
Least square method, 最小二乘法
r+ D/ W# a# W2 |4 z) I8 F( M3 GLeast-absolute-residuals estimates, 最小绝对残差估计5 Z( }' S6 F3 Y8 H8 i8 O8 G, L% S
Least-absolute-residuals fit, 最小绝对残差拟合
( t2 Y* _3 [! x9 ULeast-absolute-residuals line, 最小绝对残差线- i* g* U1 l) q
Legend, 图例% r4 C4 Q' @1 a1 n$ Q
L-estimator, L估计量) M4 D* `+ A* P8 k9 l8 I6 a7 c
L-estimator of location, 位置L估计量9 `( s! w D" @ }9 r
L-estimator of scale, 尺度L估计量4 c5 k8 _% y* T" _9 a" |7 o+ m5 m
Level, 水平
, Y& |8 @, s* V) CLife expectance, 预期期望寿命
4 k% D8 q. H% K& r- y& A6 RLife table, 寿命表
3 J9 n- P- n/ S q, E1 Z9 BLife table method, 生命表法' P% L" L- g; i9 p6 k4 M
Light-tailed distribution, 轻尾分布" f* v. I. y4 u3 B" C
Likelihood function, 似然函数
7 U6 S" n1 H8 C& q4 ~8 VLikelihood ratio, 似然比
* K8 Z5 K" v7 f! G: J* Zline graph, 线图
8 j( X- ~3 E- V+ zLinear correlation, 直线相关0 _ ^! C- P: _5 v! n" ^$ P
Linear equation, 线性方程: V) K) r* v! C. x; R# u8 x/ T
Linear programming, 线性规划
1 u* m0 P( p0 i8 J0 `Linear regression, 直线回归0 F4 F1 [7 J5 P' }# w& @* K) d+ R# t
Linear Regression, 线性回归4 z2 g& v* p! \" [' s
Linear trend, 线性趋势
7 D' M6 M6 {; n" s+ u: ALoading, 载荷
0 }# u% \% {. K; L- V$ Q: Q$ h7 lLocation and scale equivariance, 位置尺度同变性
# o4 a$ s# B1 L1 tLocation equivariance, 位置同变性4 t& I1 a7 n; c
Location invariance, 位置不变性6 |/ j; T! N5 X4 U
Location scale family, 位置尺度族
6 K* o$ q( K, Z3 f9 `Log rank test, 时序检验 1 k1 |3 P# E/ R8 `6 I
Logarithmic curve, 对数曲线& i) _2 l8 J5 q6 K+ B" }
Logarithmic normal distribution, 对数正态分布5 B. y! l) N2 Q1 E: u/ I2 L" i& ?
Logarithmic scale, 对数尺度
- h ^$ e2 {7 t- V, } q# {$ JLogarithmic transformation, 对数变换
4 @0 E- g6 n$ U& DLogic check, 逻辑检查
9 S4 L1 o2 ~' l* oLogistic distribution, 逻辑斯特分布
% _8 h' j, D ]" N! y9 p. O) g* QLogit transformation, Logit转换) i# a0 `0 K2 J5 y+ E; s0 t
LOGLINEAR, 多维列联表通用模型 x2 d# A6 |) R0 f5 a4 e8 e; f
Lognormal distribution, 对数正态分布
% g; `( y! ~ T3 Z4 @! n3 wLost function, 损失函数
+ y& N; i! @/ D7 W; h: ?Low correlation, 低度相关
; v ^6 n$ N% ?, C7 q; ZLower limit, 下限4 v2 @ z! {$ o8 `! h0 h3 s
Lowest-attained variance, 最小可达方差* `& t4 c3 f$ m" c ^3 T5 F
LSD, 最小显著差法的简称
. a: M3 N U. h( k" ?+ A1 [Lurking variable, 潜在变量
5 [ X9 y$ y/ P7 qMain effect, 主效应
$ Y% E' r7 Z1 ]" S3 s# dMajor heading, 主辞标目
, d, J$ P2 l8 U' S% l' s- iMarginal density function, 边缘密度函数- j% I% b1 [9 K9 S! E
Marginal probability, 边缘概率# B( |/ K& a5 |2 e' x
Marginal probability distribution, 边缘概率分布# I4 h4 U& F# G+ s# l
Matched data, 配对资料: X3 G G9 c: M% I
Matched distribution, 匹配过分布
2 B' s# k# h7 ]( IMatching of distribution, 分布的匹配
: V2 o8 S8 T z* O% UMatching of transformation, 变换的匹配7 B; O2 I+ K+ x+ K2 H
Mathematical expectation, 数学期望
" Q6 A0 j# ^! n: V7 ^Mathematical model, 数学模型
9 x" \5 p. w6 A, {; F; z6 w, KMaximum L-estimator, 极大极小L 估计量0 h1 A! r, C: p5 h `
Maximum likelihood method, 最大似然法
6 g0 b4 v2 V, ~$ `$ O( P. cMean, 均数( N# Y$ t' l& @4 O5 S8 G+ D: D4 A
Mean squares between groups, 组间均方
; J, q) l' v D2 G. sMean squares within group, 组内均方8 V4 M* I8 ?8 f7 k! A2 u
Means (Compare means), 均值-均值比较
6 ~& T# I( R; V4 N( N2 DMedian, 中位数- S% x$ ?+ K# m* n) Z5 k- F& O4 s
Median effective dose, 半数效量6 S$ a) H! m% j: d) a5 D; s( J9 i
Median lethal dose, 半数致死量
: i( c8 v' Z, vMedian polish, 中位数平滑 E, X2 W( ?, N4 K5 Y) ^+ M
Median test, 中位数检验' G* W3 A6 E# ]4 ?5 d+ @
Minimal sufficient statistic, 最小充分统计量9 Y( P5 I: y4 ]' U$ |
Minimum distance estimation, 最小距离估计
) g4 e' o/ Z: J/ \) u& |; m2 e0 h+ nMinimum effective dose, 最小有效量0 F; m! w/ F( G% l
Minimum lethal dose, 最小致死量, K0 w( i+ R0 J8 h4 n3 S0 d _
Minimum variance estimator, 最小方差估计量
8 C" t- w% h* `2 V4 \: b7 FMINITAB, 统计软件包$ C: k' P, R( U: ~
Minor heading, 宾词标目
T, u; \ J& `0 [Missing data, 缺失值
- E7 Z% s7 r! x; L/ f# Y9 jModel specification, 模型的确定$ L; S3 @5 S+ D! C0 u; g7 c
Modeling Statistics , 模型统计5 m# n) U- O2 J! ~' D! t |# ? Z( B
Models for outliers, 离群值模型
3 c9 |+ K6 X8 T6 X( eModifying the model, 模型的修正
# Y' M C+ [2 N- Y7 K% X5 }! qModulus of continuity, 连续性模( L9 |+ y4 h4 P0 i) _
Morbidity, 发病率 2 C5 W @5 R+ I x. q
Most favorable configuration, 最有利构形2 a, T* H, H- p- a
Multidimensional Scaling (ASCAL), 多维尺度/多维标度( u3 K; Y+ r$ y( M% ?& ~
Multinomial Logistic Regression , 多项逻辑斯蒂回归
& |2 |* D# E' [+ z, rMultiple comparison, 多重比较
* I! p0 b; T6 w( vMultiple correlation , 复相关
$ d" ^' L4 }# l' w8 N( jMultiple covariance, 多元协方差8 v u- H; c% F5 W
Multiple linear regression, 多元线性回归
) ^7 A" K5 H2 N$ D( @- ZMultiple response , 多重选项
+ J" v4 \& }! E7 { z8 S U0 wMultiple solutions, 多解" {7 c2 d! ?2 S
Multiplication theorem, 乘法定理( G/ w% m0 L" v3 M, g8 _, \
Multiresponse, 多元响应
) d( D) y/ z/ q5 U% P @+ t$ ~/ dMulti-stage sampling, 多阶段抽样
- `1 x# e% x8 Y1 r. M" Z3 |Multivariate T distribution, 多元T分布
; J8 a7 K6 F5 K0 @, J' ^$ H$ xMutual exclusive, 互不相容5 b1 [4 ~, ~/ H
Mutual independence, 互相独立
' d/ W( c5 Z0 {' Y+ B- qNatural boundary, 自然边界
0 }/ F" ~; R% g* u+ LNatural dead, 自然死亡
1 Q4 N6 [, ?0 U+ z4 k0 _Natural zero, 自然零$ P d7 U! \ I% Z2 ~1 B8 J: s
Negative correlation, 负相关0 Y; P& u. f, R) q. K
Negative linear correlation, 负线性相关* g! n @/ o }
Negatively skewed, 负偏, q) k( Y/ ^* e+ C5 r
Newman-Keuls method, q检验
' M* H2 L, ]6 f' z8 C! hNK method, q检验
+ j6 Z; p o( R; ^' i ^No statistical significance, 无统计意义8 |: ]4 B3 ?5 I" z# q2 E( i
Nominal variable, 名义变量
. J, j) Y y% u( H8 {4 Q* N1 \Nonconstancy of variability, 变异的非定常性# g# d5 L' d+ \1 U& y) S2 `7 p
Nonlinear regression, 非线性相关2 f/ \. t2 T) j+ o! K4 c; r
Nonparametric statistics, 非参数统计
: L" L5 F' z3 F* X5 i& wNonparametric test, 非参数检验, D( t8 d- h5 M0 `; |/ I
Nonparametric tests, 非参数检验7 Z& x' S) d6 J/ k, W6 }
Normal deviate, 正态离差
1 |( x6 U3 Q1 M: ?9 e% ^! t! vNormal distribution, 正态分布
( Z$ Z* E5 x7 w! ^; R/ |Normal equation, 正规方程组
; z# q9 N; S7 X9 P8 u- l3 nNormal ranges, 正常范围% a9 j' z5 |$ B2 }; q
Normal value, 正常值( t- |. _- l" ~5 D% J
Nuisance parameter, 多余参数/讨厌参数
- a; y9 f5 A. F1 M6 y& \Null hypothesis, 无效假设
; o+ U) D ^# |- Z5 ], |Numerical variable, 数值变量
* N2 N! r- F. v7 d* u8 Q2 XObjective function, 目标函数
0 I% s6 |; I6 d4 P1 `Observation unit, 观察单位
5 Z% k O2 @+ x2 D. }9 kObserved value, 观察值
; e+ f; _! a9 H6 R# v8 _3 p: W- |One sided test, 单侧检验5 E+ [5 h% j; ^; G! `
One-way analysis of variance, 单因素方差分析6 K+ p& U5 P1 B, U5 K
Oneway ANOVA , 单因素方差分析
7 k4 K# F% ]8 k0 T# M7 {Open sequential trial, 开放型序贯设计! _* Z5 r3 l" u
Optrim, 优切尾9 W% J$ K0 J$ E# p8 q
Optrim efficiency, 优切尾效率/ @' @0 d q7 Y& K* B4 _1 F
Order statistics, 顺序统计量
' \+ \8 v/ R( R6 X( zOrdered categories, 有序分类
, q9 p( `) M5 r X% b: |Ordinal logistic regression , 序数逻辑斯蒂回归" j9 d: q9 u( l% N" ]! b" H2 i
Ordinal variable, 有序变量
7 d( L3 Y8 k0 H8 kOrthogonal basis, 正交基) U9 T$ p% V$ w/ ? K
Orthogonal design, 正交试验设计3 K3 i ?- \* x: f5 i& H8 g
Orthogonality conditions, 正交条件. _5 K, w! L, Y5 w$ e6 s) o
ORTHOPLAN, 正交设计 # Z) O8 i! ]' V3 P, N$ @
Outlier cutoffs, 离群值截断点- _* L' Q4 a$ f, c+ T" U
Outliers, 极端值# T2 l- R. s* Q* T4 g s5 ?* D
OVERALS , 多组变量的非线性正规相关
6 S% Z) c* U9 K! b0 M) YOvershoot, 迭代过度7 Q! e. q4 B7 G8 \4 k# o( [
Paired design, 配对设计
u: r! `% h% XPaired sample, 配对样本
' P/ _+ c, J, e. D; ~* j9 `Pairwise slopes, 成对斜率/ h, A" c' q: J, e* R! s
Parabola, 抛物线
' L. y b3 V# a" p A+ cParallel tests, 平行试验2 O5 [6 K5 J, t' _4 P/ A+ H& _& u3 x
Parameter, 参数
# m* b/ Q7 S. H! KParametric statistics, 参数统计$ K. c* x# P7 S7 N
Parametric test, 参数检验
9 \, h" @. B7 ]8 K% }' VPartial correlation, 偏相关
/ P% Z$ l3 m6 f) B9 ^Partial regression, 偏回归
7 ?6 _" n* Y g6 b b6 D3 K# f& YPartial sorting, 偏排序
) f3 H5 @5 R6 G' p& j& R KPartials residuals, 偏残差
5 v" l( _! Q' \" ` @+ g* K8 fPattern, 模式
, P# i. P* r+ g; y( v8 LPearson curves, 皮尔逊曲线
- S) Y$ |/ {3 W8 a, L4 GPeeling, 退层
9 C" z/ v5 M3 C+ h1 D1 DPercent bar graph, 百分条形图3 m. h; ?' Y* K* [# X( n) O
Percentage, 百分比" f _2 E: n, V3 X
Percentile, 百分位数
1 H9 ]/ \$ T1 A( y! r6 S3 {+ M7 ]Percentile curves, 百分位曲线6 t. O7 b) }/ `
Periodicity, 周期性- o- X# h; j# `7 `; E
Permutation, 排列
1 l; f X Z! |P-estimator, P估计量+ E A4 Y5 W1 B3 j+ }2 P
Pie graph, 饼图( _$ H! _ u5 l7 S
Pitman estimator, 皮特曼估计量4 `9 Y2 ]2 | C6 q
Pivot, 枢轴量
, ^" v" P3 C3 k5 ePlanar, 平坦% r; r2 X: W. u9 Z! n. Q
Planar assumption, 平面的假设* q5 q: l3 U1 L4 i# o0 p( i
PLANCARDS, 生成试验的计划卡6 k) J& p# `& a8 c8 c4 V
Point estimation, 点估计0 e1 p \& a" x
Poisson distribution, 泊松分布
: i/ j! y7 l" n# L- W: J* z9 l" J, xPolishing, 平滑
% B' s! _2 n! `5 W; B# N. D+ p6 uPolled standard deviation, 合并标准差
$ [+ g+ f' s/ @7 IPolled variance, 合并方差) ]$ x0 `7 _! F8 E, S3 d% m, k
Polygon, 多边图- \1 E& x4 A/ |
Polynomial, 多项式
0 t! x( ]- \0 \+ XPolynomial curve, 多项式曲线
i, v* Y# t5 [, f% k! oPopulation, 总体
- v0 L: d# z2 q2 D0 k, sPopulation attributable risk, 人群归因危险度
/ M( G" f- b* ^; |9 K V5 [Positive correlation, 正相关
4 c# [! r2 U( b/ Q+ x0 ]Positively skewed, 正偏! L# y- i$ m9 f
Posterior distribution, 后验分布
% a5 @8 [1 _8 M! F( a! s. H/ nPower of a test, 检验效能6 z! h% X- F5 P
Precision, 精密度( V$ C$ n: K( s9 y. Z. V( h
Predicted value, 预测值
/ Z$ P; V$ O. zPreliminary analysis, 预备性分析
- ]( o- j0 K; {# {' z/ [Principal component analysis, 主成分分析7 _( S) \2 E( g
Prior distribution, 先验分布
6 N) N4 p! w6 ~- l) ~" o3 {Prior probability, 先验概率+ F0 H D. c) o
Probabilistic model, 概率模型
a# Z t- H5 w7 l; jprobability, 概率4 `8 C3 ^ _6 u/ g: h0 N; ~; C( U$ u) e
Probability density, 概率密度 {! r3 ^( v8 `; @- w
Product moment, 乘积矩/协方差3 ~" G9 Q0 C: |& t t) {
Profile trace, 截面迹图
2 e1 W& c. m! n: j" l7 c) a" s/ mProportion, 比/构成比+ k& N4 L, T7 S3 r( W( `5 C( j
Proportion allocation in stratified random sampling, 按比例分层随机抽样9 X+ k: i1 _; u# ?% B7 \) _
Proportionate, 成比例
# Y l! c8 }7 {* U6 L' oProportionate sub-class numbers, 成比例次级组含量, x6 Z$ W e& z( v. K" p
Prospective study, 前瞻性调查
( j" m1 h+ c1 D* dProximities, 亲近性 ( C7 r! R" w0 G6 N6 e* J
Pseudo F test, 近似F检验! l% ~" j6 w* E! {( V7 ?
Pseudo model, 近似模型! P' B1 [# u- n, Z* i/ t& J9 [
Pseudosigma, 伪标准差4 C- E. ~0 s) e+ R# ^& b
Purposive sampling, 有目的抽样
. x9 O P5 a5 _+ kQR decomposition, QR分解" G( F+ {6 D) ~0 ~6 R, r! M7 Y
Quadratic approximation, 二次近似4 G' }' i( {$ V6 J& G, Z! d
Qualitative classification, 属性分类
7 l8 E h3 A. E3 P% E8 H8 \* DQualitative method, 定性方法( ^4 B# s P+ a' g
Quantile-quantile plot, 分位数-分位数图/Q-Q图0 U% x, P! g9 {: a/ r) a9 R
Quantitative analysis, 定量分析
4 e# W* a* d& Q' hQuartile, 四分位数
2 V, S9 Z) v- e5 L9 fQuick Cluster, 快速聚类+ [6 t0 w& d$ K, y
Radix sort, 基数排序
1 B+ h4 X2 o/ v/ tRandom allocation, 随机化分组9 L0 L {( E( r, f& f3 ]( }9 m
Random blocks design, 随机区组设计+ a8 h$ [& t, k5 P$ k, {
Random event, 随机事件
0 A- W% N x! L( U" I, s, w* ^Randomization, 随机化
3 E. S% Q/ v% I5 e0 z `, L- GRange, 极差/全距
( b3 l( ^" }; H* f U; J, Z/ e- NRank correlation, 等级相关
& S: r& `/ s( C6 d4 y; hRank sum test, 秩和检验# j2 F; y9 g% h% i$ ~% B
Rank test, 秩检验" y7 q! b2 s. b4 {
Ranked data, 等级资料0 x/ `1 s9 G- K: D8 v1 e3 @
Rate, 比率" H. O6 q) s+ J$ w, B6 x. [
Ratio, 比例
3 c6 m' @6 `1 s) z$ j) jRaw data, 原始资料
, N4 e: B z; D; Y* X. M5 S; k2 nRaw residual, 原始残差
' I/ ]4 x( ^: l) N/ KRayleigh's test, 雷氏检验- f8 T0 y7 N8 F/ x4 A4 y; t" [) P
Rayleigh's Z, 雷氏Z值 8 t1 C% s# W" Q
Reciprocal, 倒数+ r) X8 w* L' p8 P# h# Z; u+ E
Reciprocal transformation, 倒数变换" E. r: h+ x/ b: v3 m+ h0 H
Recording, 记录9 c, l* l+ a+ s P' I+ o# A
Redescending estimators, 回降估计量1 J" M: r- W9 T0 y" p' }
Reducing dimensions, 降维
/ Y ^. M. n! y6 WRe-expression, 重新表达
) e+ t1 [9 `0 R1 c V: Q1 e {8 jReference set, 标准组0 z' Q+ ~' x! N+ Y
Region of acceptance, 接受域+ T% B, a: z+ e! y+ }: N
Regression coefficient, 回归系数9 `$ j9 C! n& g8 n; M
Regression sum of square, 回归平方和
& `+ `* H+ o7 c% lRejection point, 拒绝点
- w6 c) Z' |( |/ Y3 Y! jRelative dispersion, 相对离散度
- Z8 X# Z/ z3 [4 e# K: aRelative number, 相对数
6 |7 T- V+ J8 {) WReliability, 可靠性9 d4 k' ^3 c, U1 E
Reparametrization, 重新设置参数8 s' v4 ?8 I9 x0 b3 g6 g0 B- l0 \
Replication, 重复! ~0 p' g3 h4 Z% b M, ^
Report Summaries, 报告摘要0 A& Y7 n/ b, b+ F2 ^8 M$ L" W6 Q
Residual sum of square, 剩余平方和
7 `1 ?6 W p) {0 G6 z% rResistance, 耐抗性
: J( J3 d5 A( F- HResistant line, 耐抗线% L$ [. ?% @1 |9 {3 N) E+ v# S
Resistant technique, 耐抗技术
* F, ?+ [' |4 T6 v" Y* L% A T3 iR-estimator of location, 位置R估计量
+ l9 q5 r4 [% n! u9 j8 YR-estimator of scale, 尺度R估计量
' F& t3 {- z( w% \4 PRetrospective study, 回顾性调查
, w( h. L, e, {0 P9 FRidge trace, 岭迹
6 V8 d0 [+ o9 G* j$ w, |! @' ZRidit analysis, Ridit分析- `2 W4 A6 j% X( C4 k. ]% f! b& p
Rotation, 旋转+ |3 v& r- M9 N3 ~" k/ }, q
Rounding, 舍入
6 c. R( `$ x1 |Row, 行3 L2 T$ P. Y8 _
Row effects, 行效应. _% N w5 S1 |; Y& f- u
Row factor, 行因素
- Y) c+ h9 O# G) u- \% z' [7 e8 \. ARXC table, RXC表, T) @' @7 k9 a* {+ _ T% I
Sample, 样本1 N0 W; i$ v7 G; Q* c6 K$ g+ V
Sample regression coefficient, 样本回归系数0 B/ C% }' w. P0 u! z$ B
Sample size, 样本量
7 N5 R; o; g) `7 \' wSample standard deviation, 样本标准差) k$ F7 e) X; B( h) x
Sampling error, 抽样误差' I) z9 G) g+ P) \ ~8 P( ~" f
SAS(Statistical analysis system ), SAS统计软件包
' C5 g A8 b3 m$ W1 o: WScale, 尺度/量表4 u/ C$ j1 G! v* v- S
Scatter diagram, 散点图- {* Y @ z& p$ r) Y3 S
Schematic plot, 示意图/简图# _, W* a1 H4 j& i- ^" [
Score test, 计分检验
7 s0 g+ ^, t8 v z9 E: R( VScreening, 筛检- H& F" x/ K4 C
SEASON, 季节分析 ' e! c' g2 l) K2 Z; f! Q
Second derivative, 二阶导数
+ D7 R' c& U3 k; a) WSecond principal component, 第二主成分
# D5 l9 F: x# e& _SEM (Structural equation modeling), 结构化方程模型
6 N7 `5 \: C, _# ]% c1 dSemi-logarithmic graph, 半对数图8 b1 D; @; S! J( J4 A4 V" P
Semi-logarithmic paper, 半对数格纸
: N, }& B" C: g: }Sensitivity curve, 敏感度曲线, d2 g' c# A1 B8 u9 @% x. h* v; J+ Y
Sequential analysis, 贯序分析0 ]' U* o) A& E: n; h
Sequential data set, 顺序数据集2 t$ r7 x i/ `% F; G
Sequential design, 贯序设计
2 C* a7 }2 a' @Sequential method, 贯序法$ D% i h _/ |6 p. s
Sequential test, 贯序检验法
4 H- N& h) t- N" s0 T7 u( U/ qSerial tests, 系列试验/ Q2 s8 m0 ?! I q
Short-cut method, 简捷法
# z' g" V' b0 w$ V1 k6 zSigmoid curve, S形曲线
: h5 Q. Z: @1 K* `8 d) ^4 fSign function, 正负号函数
9 ?: A% [' g: z$ X/ MSign test, 符号检验
0 {# d( M, a/ E! g/ B) oSigned rank, 符号秩
8 X8 E' ^! V, h0 nSignificance test, 显著性检验
5 g+ C# A4 j$ `- ]8 @" }7 r6 O$ KSignificant figure, 有效数字
5 \5 X6 v( i9 e/ B' i5 N+ \+ oSimple cluster sampling, 简单整群抽样& f( l0 B3 f5 v7 b7 T8 L. ^2 H
Simple correlation, 简单相关( l9 _. H# j* A' U( V4 u" G
Simple random sampling, 简单随机抽样
: g9 J D- ?* C. J% RSimple regression, 简单回归. M; a$ S& Q8 k- D5 m
simple table, 简单表1 v, v- d- Z+ j+ ~- F* K
Sine estimator, 正弦估计量
5 l# @( g$ T4 `Single-valued estimate, 单值估计
- i$ e0 U4 ]. S# oSingular matrix, 奇异矩阵
- e% D6 m* f' ^0 M5 C+ @* B# rSkewed distribution, 偏斜分布
1 U4 _: }( g6 p) KSkewness, 偏度! m, E* i' D* M- r9 z- |
Slash distribution, 斜线分布
! g. t7 ]4 V! C: z, l9 mSlope, 斜率
$ }6 R/ H1 l B! JSmirnov test, 斯米尔诺夫检验
' q( V X0 T" ~0 ]3 bSource of variation, 变异来源' y! T5 p# d9 B# L; E
Spearman rank correlation, 斯皮尔曼等级相关: Y$ Y% P+ B" D) ?5 k( @
Specific factor, 特殊因子
; d7 X7 R' ~2 u Q; \4 ?Specific factor variance, 特殊因子方差
$ r# i3 r' ~; }( lSpectra , 频谱
e2 ]5 y7 K! F6 l+ N3 T) F3 eSpherical distribution, 球型正态分布
' G% ]- ]3 ~5 u% c( S- ~' lSpread, 展布7 m& `5 R* n+ l$ S5 x, L! \5 s3 J7 j2 n
SPSS(Statistical package for the social science), SPSS统计软件包
8 W8 v# I5 E( B3 q% _Spurious correlation, 假性相关
$ l( A: N9 ~* d4 h& mSquare root transformation, 平方根变换
2 x7 w; P( ?" r8 K9 l( e1 UStabilizing variance, 稳定方差
" w/ y2 C$ P6 n2 q1 yStandard deviation, 标准差
; k* k6 q' B; X( i+ EStandard error, 标准误7 b1 z8 |$ }. K3 V$ V
Standard error of difference, 差别的标准误
$ q$ g( k, v0 gStandard error of estimate, 标准估计误差
' _: j( }) a% WStandard error of rate, 率的标准误
" y( G: D) q2 x; V$ ] KStandard normal distribution, 标准正态分布
" R$ h/ }. a U xStandardization, 标准化
0 t' b. F. Q: TStarting value, 起始值
0 ^5 i: a7 C% lStatistic, 统计量
( t, [- C/ M) c" s6 _8 {* U- A) LStatistical control, 统计控制
b' T& N9 K- l. u. V' p3 WStatistical graph, 统计图/ }, x- `9 y- M0 M
Statistical inference, 统计推断
$ D* \3 z8 R# CStatistical table, 统计表
7 f0 Z& h+ S! V& `2 zSteepest descent, 最速下降法 s: k1 I% }- C
Stem and leaf display, 茎叶图4 C2 S, X" _1 j6 P1 T' D' ^( o
Step factor, 步长因子
- e6 l. ^+ V& {Stepwise regression, 逐步回归
; N2 D" o# J: y# BStorage, 存( d6 r+ O# P" \+ P1 r+ v: w9 b. l& o
Strata, 层（复数）
+ }2 B1 V& q1 @* Z4 UStratified sampling, 分层抽样
; ^( O( ~. {1 x2 R. j6 |% e- b. L" OStratified sampling, 分层抽样
& P4 c2 U7 q: ^Strength, 强度+ W3 o, ?4 A8 d% K4 \& K
Stringency, 严密性- F4 L# _. U8 s6 b/ @
Structural relationship, 结构关系
7 G. C, `; O IStudentized residual, 学生化残差/t化残差/ ?8 O9 s8 [/ @) s9 ~& I
Sub-class numbers, 次级组含量
) ?+ V# ]+ O& B+ hSubdividing, 分割' _: L$ h# h* w" S
Sufficient statistic, 充分统计量! s0 Q: z/ E; {- a$ k
Sum of products, 积和4 n; R/ j) i6 t0 G
Sum of squares, 离差平方和/ Y$ D0 e$ c' B
Sum of squares about regression, 回归平方和* V/ z0 U9 V8 u! m- u5 V
Sum of squares between groups, 组间平方和+ j4 c, {- R1 o4 q7 n) V
Sum of squares of partial regression, 偏回归平方和
' `) j" ]1 Y4 U0 N- P. QSure event, 必然事件6 S# E/ ]# j' m) z
Survey, 调查
; o: w$ v4 z* N3 n, h) QSurvival, 生存分析) r7 q% X- P- \( F* z# q2 b4 N+ b
Survival rate, 生存率
+ o0 W8 w- S. O- @Suspended root gram, 悬吊根图
/ w% O7 u$ @) P- U3 aSymmetry, 对称
. Q2 g/ {# S4 I- [1 r s4 d' cSystematic error, 系统误差# ]! b# j: F" s) m
Systematic sampling, 系统抽样$ q, b% F" P# {& ?
Tags, 标签
w3 H s" K: l Z3 kTail area, 尾部面积
+ q- U6 t/ o! z$ }# _Tail length, 尾长4 K- d9 a$ ` ~- \& a
Tail weight, 尾重; `) ]/ c [, k4 \7 S* b* J
Tangent line, 切线0 l) u. Z# U* D
Target distribution, 目标分布9 k+ _% n0 R1 _$ a/ ~+ R; S5 r9 `
Taylor series, 泰勒级数
3 S) y7 O" q- A# Y3 b8 G5 LTendency of dispersion, 离散趋势( j$ M6 E1 U8 D# Z8 z7 r
Testing of hypotheses, 假设检验& p A; C3 f& R+ C: g
Theoretical frequency, 理论频数) ^3 }' L7 ?, V0 _) J: M4 ?3 Z# ?3 E
Time series, 时间序列
( f; \ _" _5 d! H6 K2 n; V1 kTolerance interval, 容忍区间
4 D/ h4 H* W: m) M9 E# ETolerance lower limit, 容忍下限8 Q' v, w4 q9 U' m" S
Tolerance upper limit, 容忍上限
0 C) p8 o0 g" O0 wTorsion, 扰率
: [% P0 ]( A5 D/ ?" U$ y3 fTotal sum of square, 总平方和! R+ s6 S# [; T+ g* j; u
Total variation, 总变异
- z- q& A5 g2 l3 A' ?" lTransformation, 转换
4 L2 _5 H, d1 l3 |1 W- jTreatment, 处理
; Z& E: R+ e$ `, Q. N; v- B( tTrend, 趋势
( |( [2 ]" m7 Q3 G- ]Trend of percentage, 百分比趋势" ^) ` J' u7 q9 m8 U8 j; T( Z/ r
Trial, 试验
) n+ a1 V0 j6 O# W; ` L" u- I2 ]. J# y. fTrial and error method, 试错法' X$ K& O, [* g( @( {# Y9 F
Tuning constant, 细调常数
! N% j+ B0 C6 qTwo sided test, 双向检验. `$ c D. S* Q( f" r9 ?
Two-stage least squares, 二阶最小平方
5 u4 O6 m* U! |0 T/ gTwo-stage sampling, 二阶段抽样) x; a( z, Y+ E' ^' }, I) H& `
Two-tailed test, 双侧检验
! I8 E" x$ n% j) {4 ^- o8 w; ?4 f0 NTwo-way analysis of variance, 双因素方差分析6 U8 K# K; A" Z' S9 C' S0 w8 x5 c+ E
Two-way table, 双向表' e, F& U* } e' E* u
Type I error, 一类错误/α错误
T. q1 h6 ]% OType II error, 二类错误/β错误8 c* w% J/ \; W- V2 Q
UMVU, 方差一致最小无偏估计简称
- x7 v/ |/ r, Z2 O* D" XUnbiased estimate, 无偏估计1 Q8 e- A- `, A
Unconstrained nonlinear regression , 无约束非线性回归5 r3 g' K8 {% y
Unequal subclass number, 不等次级组含量- y8 y" z: h5 x4 n1 V0 \3 ~" P, r
Ungrouped data, 不分组资料
! q& X/ v# u- ^* }5 xUniform coordinate, 均匀坐标
' G" U# L( r* F: ~8 F3 S! ZUniform distribution, 均匀分布
0 c7 f- O* f9 ^ X+ K0 iUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
( }; w: D' H5 ?. a) d9 Y7 mUnit, 单元9 I% M3 ~" i! _1 ^) e m! C
Unordered categories, 无序分类1 W- A. K1 M7 L* Y2 F4 g+ q+ j
Upper limit, 上限5 N% ~$ T8 C& I. D8 D2 |- t6 |$ V
Upward rank, 升秩
1 @9 K3 }$ N* }. [Vague concept, 模糊概念
% c: _- O3 t; pValidity, 有效性, h0 C) w. C; \. I% b
VARCOMP (Variance component estimation), 方差元素估计+ k6 {, j7 Z( _6 }- N3 N
Variability, 变异性
& x3 X5 }1 P2 O, \Variable, 变量6 _* I5 t* E* P$ R5 ^' F0 k
Variance, 方差+ K1 Q* S* b' Z! ]/ `
Variation, 变异
" i& r3 r4 L: G0 S+ B1 U' S8 zVarimax orthogonal rotation, 方差最大正交旋转
# e5 Y1 @6 o+ S( {6 GVolume of distribution, 容积
# O2 ?2 h* m: K8 mW test, W检验6 T$ i( | [, l' H
Weibull distribution, 威布尔分布7 l; o( w0 L5 i2 \
Weight, 权数 S5 T! l- @' C. E$ |( x$ P- E
Weighted Chi-square test, 加权卡方检验/Cochran检验1 u# y' p* f9 ~0 c6 K; d( [
Weighted linear regression method, 加权直线回归
$ H+ ^/ e, F9 k- HWeighted mean, 加权平均数
0 f4 @$ G4 A# Q" D; ~ u* ^( mWeighted mean square, 加权平均方差& [& A; A6 X( b6 T
Weighted sum of square, 加权平方和
9 ~$ w0 F, D$ f/ QWeighting coefficient, 权重系数
' _" v5 j6 u0 ]# O$ W% p# _# J7 L" ?Weighting method, 加权法 ' N! o# B. c! ]% o9 e3 U
W-estimation, W估计量3 s& J0 x( Z" G: n$ P. j
W-estimation of location, 位置W估计量" O% m! q; x; m }+ P+ ?% s7 Y- T+ Q+ ?, R
Width, 宽度
9 y7 j, ` b6 i8 u7 S( v! c+ w6 JWilcoxon paired test, 威斯康星配对法/配对符号秩和检验, Z, a) ?: _; p; u# O
Wild point, 野点/狂点( ]7 z5 X; V% T( L/ g. t% B# c
Wild value, 野值/狂值7 Y% G$ t+ M3 t) ]6 x+ T
Winsorized mean, 缩尾均值4 u" d% D' H8 @3 ?+ U& c; ^( f" R7 G
Withdraw, 失访 , v' @) O% ~- z: Z* y2 F
Youden's index, 尤登指数. \$ M: V& y" T! X Z$ a6 [# e
Z test, Z检验* F* T" M" P& g2 ], ]
Zero correlation, 零相关' d M9 Z1 y- Y# y
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
