|
|
Absolute deviation, 绝对离差
9 |/ S# f" K1 e2 T l- N1 W3 O7 ZAbsolute number, 绝对数
, q% @( {" K H, YAbsolute residuals, 绝对残差2 O4 @, U8 ?/ d
Acceleration array, 加速度立体阵
8 d7 n/ S. K& l8 rAcceleration in an arbitrary direction, 任意方向上的加速度
* J7 J' S" M5 J& M# NAcceleration normal, 法向加速度8 T- r; b5 P$ r: G' e5 [2 ]- g
Acceleration space dimension, 加速度空间的维数
4 D: ]5 f! e4 UAcceleration tangential, 切向加速度& y! o& {4 Q5 {- F
Acceleration vector, 加速度向量" t8 {) _" b& ]! x+ x3 G4 }
Acceptable hypothesis, 可接受假设2 b3 L# O$ V$ l( k* S3 J; \
Accumulation, 累积) R, m) W x. J$ m& t1 j
Accuracy, 准确度
4 i8 m/ u. W4 v+ u! H# EActual frequency, 实际频数
- k9 e! l- G2 s4 r# hAdaptive estimator, 自适应估计量
" v5 \$ t9 x. L, D. o2 d3 mAddition, 相加
9 w4 n% L9 w {+ q) QAddition theorem, 加法定理1 h% b# a; H [$ e' c; X5 b% y
Additivity, 可加性
1 J2 [0 P* `" L! D* _' A% fAdjusted rate, 调整率9 ~! L2 A4 _$ D* @; t% U. j+ i
Adjusted value, 校正值
( S- |0 z7 F# A! ?9 e0 I# {Admissible error, 容许误差! l. g" L& d5 S3 }" k4 Q4 m9 e& l
Aggregation, 聚集性
- h4 h* a* ?) f+ M. O) Y& ?Alternative hypothesis, 备择假设
8 T7 }4 \* u8 c. K) K0 R d) aAmong groups, 组间; \; P- [& g* m3 C/ b
Amounts, 总量 O) N( i! W8 A- Y* _
Analysis of correlation, 相关分析
" a* p. R2 @! d! i$ rAnalysis of covariance, 协方差分析
5 t- x# b% T4 P' K4 VAnalysis of regression, 回归分析) M2 u' m3 h8 { F( m$ F) g
Analysis of time series, 时间序列分析2 ]% d6 _- t0 X* h1 P* T7 a* v- l
Analysis of variance, 方差分析$ l! ~' ?3 k- X! x# }
Angular transformation, 角转换, _( M5 m3 f! l; d6 R2 d
ANOVA （analysis of variance）, 方差分析
\: d# h: }7 Y) KANOVA Models, 方差分析模型, E9 }1 h4 o$ u$ x% {9 {2 T
Arcing, 弧/弧旋7 f9 L2 ^4 ~9 g6 b0 X8 E
Arcsine transformation, 反正弦变换
6 q+ u* F$ z- wArea under the curve, 曲线面积" w+ U. O0 u) G
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
0 Y, X6 g3 t7 [ARIMA, 季节和非季节性单变量模型的极大似然估计
3 e K: P0 h- T/ ?9 wArithmetic grid paper, 算术格纸
8 g( J( v u+ v9 lArithmetic mean, 算术平均数
; a: J; T# T: J5 O! v" U: I% N* CArrhenius relation, 艾恩尼斯关系6 r" x1 b$ d% R! _
Assessing fit, 拟合的评估
8 g6 @/ A' O" r }, YAssociative laws, 结合律
# x+ {2 e; b4 K, D, Y; mAsymmetric distribution, 非对称分布: ^. Q3 a2 X- u8 I: m% u
Asymptotic bias, 渐近偏倚
7 U: R) v5 ^1 N8 C) t2 aAsymptotic efficiency, 渐近效率2 h' q# N( I: F1 p
Asymptotic variance, 渐近方差
) L6 f) \7 J1 }% F, ~Attributable risk, 归因危险度
" @$ Z ?' _2 q3 U+ }: t1 e8 i8 FAttribute data, 属性资料0 e' W5 S5 y9 d# R: s; o' {' }# W
Attribution, 属性/ `- ^, x4 E3 ?5 ^) e) l' ~
Autocorrelation, 自相关6 s \7 ~2 t1 p; E' M
Autocorrelation of residuals, 残差的自相关
5 V0 n$ ~0 h4 @5 q; _' a/ gAverage, 平均数
+ }# O4 M8 ~; M' g. z) }Average confidence interval length, 平均置信区间长度
/ q0 }# K% N, {9 }3 \Average growth rate, 平均增长率+ A6 E7 X0 v" P. d0 h
Bar chart, 条形图
! S9 P* P+ k9 l# lBar graph, 条形图
6 t6 Y* X& L% V2 N+ Z; {Base period, 基期
7 A- S# ~% T! D' j3 _7 uBayes' theorem , Bayes定理
( U& t8 W6 `7 U, M D; GBell-shaped curve, 钟形曲线0 w$ I$ M4 m. l* R% D( |2 U
Bernoulli distribution, 伯努力分布
% y( W2 ^# L7 y* {4 ?& |% x" iBest-trim estimator, 最好切尾估计量
6 ?6 z0 p* v1 X6 h3 Z- \Bias, 偏性! U9 p9 U- ^# P& i& r) `7 x, l
Binary logistic regression, 二元逻辑斯蒂回归' Y& U. I( U2 }: l0 S0 a5 c
Binomial distribution, 二项分布
0 w3 ~; x+ l9 Y6 y3 GBisquare, 双平方 K. A% i+ {3 L2 U+ M$ R) F
Bivariate Correlate, 二变量相关
* Z6 \2 S$ q5 F9 {/ D, KBivariate normal distribution, 双变量正态分布! p7 K4 D+ n: m( _7 P
Bivariate normal population, 双变量正态总体
$ k% ^- x4 D4 h+ W; v' M9 F8 CBiweight interval, 双权区间
: e" g9 m; S5 o- m, TBiweight M-estimator, 双权M估计量
9 ~7 l" U E$ t5 I4 N; SBlock, 区组/配伍组
0 K1 j# Y" R, RBMDP(Biomedical computer programs), BMDP统计软件包6 a/ ~# m& z) b$ {) [
Boxplots, 箱线图/箱尾图, n5 S7 h- s, z1 W; v T I
Breakdown bound, 崩溃界/崩溃点
( |$ X% `: ~; xCanonical correlation, 典型相关 z8 q) p" Y, T- r+ A& \9 ]# A
Caption, 纵标目
0 _8 T/ ]! Q Z( _3 F6 k& j+ b% _% CCase-control study, 病例对照研究
$ o- x F: T( n5 I. Y4 X- cCategorical variable, 分类变量
" F6 W' P4 y! ~* Q+ |0 j& @" w8 jCatenary, 悬链线8 g2 ]. l- Y) f6 i! S
Cauchy distribution, 柯西分布! @ P/ _% E3 A% l" O. C5 n
Cause-and-effect relationship, 因果关系% ]/ L y0 P9 q8 W
Cell, 单元4 e! d- j# x7 v3 i4 q3 q) s
Censoring, 终检
, i m0 a, m& eCenter of symmetry, 对称中心+ i) d9 h' s4 _+ N2 K( y
Centering and scaling, 中心化和定标
: c, c2 o- Q: A }' \Central tendency, 集中趋势+ W8 z4 Y- ^4 V; b
Central value, 中心值( A* O2 d' T1 B3 v$ s
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
1 j* K, |. F! c/ [Chance, 机遇; ]2 P1 x) u. c: K6 X: i7 t3 q
Chance error, 随机误差1 S- d H# [# I! q
Chance variable, 随机变量- U1 s# P& o/ ~+ ]
Characteristic equation, 特征方程% j f+ R4 X# E5 m, } p
Characteristic root, 特征根. T7 o! y% R. P! q
Characteristic vector, 特征向量 ]4 F# |8 O% J6 N
Chebshev criterion of fit, 拟合的切比雪夫准则; s/ {- |, i$ y+ k p: O( B
Chernoff faces, 切尔诺夫脸谱图
) x4 h/ K" b8 l: r& {9 ^0 lChi-square test, 卡方检验/χ2检验
/ q" J& e% z! T3 o @" MCholeskey decomposition, 乔洛斯基分解
0 K q4 u5 Y% Z6 U- PCircle chart, 圆图
2 ^. u5 |2 O6 x- ]: l0 G$ a* fClass interval, 组距
& @3 M: M2 ~8 ]" `% x) e! t7 g6 iClass mid-value, 组中值; ?+ Q X) d* l( Q- s# `; n: A
Class upper limit, 组上限* D5 ^4 d9 t- R( s) t W# G
Classified variable, 分类变量
- t" N: F; l9 a( WCluster analysis, 聚类分析
/ K o7 W1 n% c: YCluster sampling, 整群抽样3 d( _$ t; X; I
Code, 代码" K1 c9 H) r# }, ^; t3 f
Coded data, 编码数据
* o% Z' b) `$ t: vCoding, 编码
7 m, T) u6 X( u$ F7 xCoefficient of contingency, 列联系数# P! Q" T0 M. F/ m% |
Coefficient of determination, 决定系数
P4 ~1 |# z- i( n RCoefficient of multiple correlation, 多重相关系数( U& Z' c' D2 m- n
Coefficient of partial correlation, 偏相关系数/ U0 ~( n8 L1 k+ b- K
Coefficient of production-moment correlation, 积差相关系数
5 h& X& p3 K9 m; p3 t) uCoefficient of rank correlation, 等级相关系数
* @" w, f& C$ p7 m/ [8 R, x4 q, P0 cCoefficient of regression, 回归系数6 A) ]$ L8 X' V
Coefficient of skewness, 偏度系数
$ t9 {; K7 w: _- ^( y/ C0 @/ ?Coefficient of variation, 变异系数: }+ P. ^" [; ]1 _3 ?
Cohort study, 队列研究
4 |5 g3 J3 O$ N9 ?& F/ X, C4 |5 eColumn, 列
0 Z' O, i3 P( TColumn effect, 列效应& k6 k5 x$ G! D, \* P7 ^0 y4 ?
Column factor, 列因素
~% |3 S$ s( m' h7 }Combination pool, 合并
8 k6 l$ C- U5 y1 @2 ]: xCombinative table, 组合表
^( j$ E0 H. @& HCommon factor, 共性因子8 N! _7 }9 h5 |. B% N3 H
Common regression coefficient, 公共回归系数
2 A0 H0 b% p* D+ U6 T u' Y% UCommon value, 共同值
W- g$ t& l8 i: VCommon variance, 公共方差" P( i% K4 _( M
Common variation, 公共变异
; Z5 l0 C3 n: T- N+ M$ S6 b. LCommunality variance, 共性方差
3 L7 q7 d7 p5 g% @Comparability, 可比性4 i( b) P0 K2 @3 a- m# _( k! Y. V$ ?
Comparison of bathes, 批比较
0 r) J" j5 q' e2 i3 H) t O4 vComparison value, 比较值" g B f5 D6 ^. @6 V, M
Compartment model, 分部模型& g5 C+ z; Q$ O# H: A* m
Compassion, 伸缩
% K4 _0 G5 N# p/ R8 vComplement of an event, 补事件, a7 x( x$ p3 Q# x; l) m
Complete association, 完全正相关
% }8 n& `8 B9 `9 m! ?* q( l- lComplete dissociation, 完全不相关
' O" @+ G8 o# u L3 rComplete statistics, 完备统计量
" M: r% g6 j/ W O7 l4 FCompletely randomized design, 完全随机化设计
0 S& U+ i! x8 j, v- n% ]* kComposite event, 联合事件1 l2 h, V8 U7 G% ?! x! Y0 @
Composite events, 复合事件
4 ]8 {" }& I; P' |$ nConcavity, 凹性 m- E, W1 B% ~5 l' E+ d
Conditional expectation, 条件期望
- s! e2 [- w, w Y" Z) ~ t9 X$ ?Conditional likelihood, 条件似然
! z# R% s" h; Q: y# Z+ N0 NConditional probability, 条件概率# {+ ]* N# m9 d' s
Conditionally linear, 依条件线性
/ u ]! O9 E% \, t& F9 FConfidence interval, 置信区间, @# r: Y6 U* X7 I% ^1 ~, O' m
Confidence limit, 置信限; `* J! a* _4 i! g/ Y# Q
Confidence lower limit, 置信下限3 Q; l7 ?3 ~* m& o1 v6 q
Confidence upper limit, 置信上限" u& s- n3 }& H% q9 S- u5 `5 _
Confirmatory Factor Analysis , 验证性因子分析
2 i3 d8 k% t- m* M7 w$ T% gConfirmatory research, 证实性实验研究0 V" q6 P K$ d: h3 ?
Confounding factor, 混杂因素
' g$ G# e5 F( `& ^( O7 yConjoint, 联合分析7 v. Q& v* _. }5 i; @
Consistency, 相合性! x v* h, a2 p% O
Consistency check, 一致性检验3 Q7 X, t( |! G. r3 O. K. r4 W) s
Consistent asymptotically normal estimate, 相合渐近正态估计
9 c: z* Z3 K4 m6 F; V5 N- k- y. tConsistent estimate, 相合估计
7 Z- ?+ S0 a x2 N7 W( T9 mConstrained nonlinear regression, 受约束非线性回归3 L* l: m$ I* G7 v
Constraint, 约束$ t: G7 Z2 J6 L U1 D: w
Contaminated distribution, 污染分布
& s& L" l+ K9 d& `1 sContaminated Gausssian, 污染高斯分布
# @4 e S& J6 e3 d1 f3 GContaminated normal distribution, 污染正态分布
" h( ]8 L! v0 g1 f5 g$ X* lContamination, 污染
" \0 I1 R* h" ~! [( \1 m9 [, zContamination model, 污染模型
. b& X9 e2 E- t0 R1 UContingency table, 列联表
' T* l1 W B+ ?" m: ?# C5 mContour, 边界线
# V6 ~ O' G2 @( V) @( q$ l1 pContribution rate, 贡献率9 H" U; v3 T' M/ q
Control, 对照6 _' w" ]" w5 \
Controlled experiments, 对照实验
+ _! |( f) c" b) S+ L' Y3 u5 @1 uConventional depth, 常规深度
/ p$ X( k6 L6 iConvolution, 卷积
7 ~; C6 H( d* M3 Z/ N4 J* o/ H1 cCorrected factor, 校正因子
. O- ]6 B8 ^$ }# [8 XCorrected mean, 校正均值
) F& u" }, U4 O$ Z: T8 oCorrection coefficient, 校正系数
a! n1 U6 ~5 l7 |Correctness, 正确性
- e% K$ S- a- ~! TCorrelation coefficient, 相关系数0 j. s% k9 M$ I- d6 Z! T
Correlation index, 相关指数
. E- u, m( ~6 T+ q6 eCorrespondence, 对应. z% ?: \; O/ b
Counting, 计数" `+ ~7 W8 ~) h8 F
Counts, 计数/频数0 G+ `9 v% z3 h4 N
Covariance, 协方差
( B( `9 `4 E5 C2 l) m8 pCovariant, 共变 % U& T* s2 H8 V3 Z$ u. n6 B
Cox Regression, Cox回归% c, R6 R+ X- c' y- d# O* U
Criteria for fitting, 拟合准则
! ], w& A0 x) m. ]' i- ZCriteria of least squares, 最小二乘准则$ A1 s' u r% M* h
Critical ratio, 临界比
8 K- E) ^; `, D9 X: G+ z6 JCritical region, 拒绝域
4 p" h! H6 ^: R6 k+ SCritical value, 临界值! x" l; j- d T4 ?; _6 e4 Q1 }
Cross-over design, 交叉设计
4 e( N: I8 q; J H0 G* |5 b/ e% i' cCross-section analysis, 横断面分析2 p, o5 K' Q7 ^3 ]
Cross-section survey, 横断面调查* k9 {, ]: J' Z! P# o; N( J/ o
Crosstabs , 交叉表
: }8 s/ ?) P' z' D# U- pCross-tabulation table, 复合表
/ ~, S! O* y+ G8 e# a" D' fCube root, 立方根# o+ a7 E- E3 a) X# N
Cumulative distribution function, 分布函数8 @6 o# G9 U c1 B' V
Cumulative probability, 累计概率
% Y$ A5 y6 f- Q+ {2 m N8 ^' l+ H" mCurvature, 曲率/弯曲
. b% ?1 S7 ^9 b7 l0 ?; U- |Curvature, 曲率7 q& w+ S/ ~/ t- t, I7 p" Y6 m8 i
Curve fit , 曲线拟和 2 ~. M0 x: l: w& G9 [* L0 r
Curve fitting, 曲线拟合
; B# J0 x W; Y4 b, ?% @Curvilinear regression, 曲线回归
* d: S- O5 l, S- M! WCurvilinear relation, 曲线关系
5 o& @3 s7 z" J: k) g7 KCut-and-try method, 尝试法# @! A7 }" S6 ?! M$ H
Cycle, 周期. x/ S Y! E j/ a6 I
Cyclist, 周期性4 l/ x! m& I" D, V0 W+ K
D test, D检验
! D9 x5 a. J) VData acquisition, 资料收集
+ V- j1 K7 f* j% BData bank, 数据库6 e/ O0 Z. D$ T; n1 K$ _8 f* H
Data capacity, 数据容量+ M+ X8 {0 l1 ~3 m
Data deficiencies, 数据缺乏" m* t/ M) n8 q' ^) k
Data handling, 数据处理
, S, m1 G, H& G; r9 u( u* _Data manipulation, 数据处理8 E- `$ f+ M r6 N% D
Data processing, 数据处理
& C3 V& a2 i- A6 TData reduction, 数据缩减
' M: v b. J- p0 o6 O ?3 JData set, 数据集8 K% W# r) l# t5 j
Data sources, 数据来源
& I9 I; t/ x ^) E& LData transformation, 数据变换) _) N8 s# J& R2 G) i* X/ a
Data validity, 数据有效性6 B; @5 I2 L1 L' C
Data-in, 数据输入
' L3 z& L; h/ G2 E& h0 z7 ]; y& V! h- nData-out, 数据输出
3 m2 x' m. U" u. W4 _ X0 ^Dead time, 停滞期7 D7 ?0 u' B8 C
Degree of freedom, 自由度
* q5 \; K/ ]$ a# d" aDegree of precision, 精密度
- Y+ x5 y: C$ e8 fDegree of reliability, 可靠性程度. s, N% P3 m2 {
Degression, 递减
|/ |+ }7 ^, Z3 ]! J& TDensity function, 密度函数3 \: c3 J- Y- h$ g5 t) A! E# U" V
Density of data points, 数据点的密度
' x8 n3 g v' x9 ?; r0 UDependent variable, 应变量/依变量/因变量
5 y; @3 B+ x0 b9 `7 EDependent variable, 因变量
$ R5 o, p' w8 ^' F+ DDepth, 深度4 d7 p8 P% n4 K+ }
Derivative matrix, 导数矩阵
S9 G. _! Z, ?; L3 WDerivative-free methods, 无导数方法: N2 ?! @6 h" m& Y1 [- F1 m. r( X
Design, 设计5 `) A2 t5 j$ Y
Determinacy, 确定性
* u& S/ C! ~' k. F. o" E% gDeterminant, 行列式, I6 B2 A+ G; |' ~& V8 P. D+ K
Determinant, 决定因素
* U' {- A- |- p2 JDeviation, 离差
2 `$ ?4 {5 c qDeviation from average, 离均差
7 H, o: u5 B5 q# |Diagnostic plot, 诊断图+ a+ y- U) H: p( j3 _; n
Dichotomous variable, 二分变量6 U2 `2 l, f4 N0 u
Differential equation, 微分方程
& t8 r* n4 g7 S' l! o; u! ODirect standardization, 直接标准化法4 b# D& {; f1 G- n% {( g
Discrete variable, 离散型变量. s q% d9 t$ E1 a& d
DISCRIMINANT, 判断 - P) Y9 O; C: F1 g0 t m( x
Discriminant analysis, 判别分析4 H. T! \5 z" o0 l
Discriminant coefficient, 判别系数
r% C- m9 T) j& ~Discriminant function, 判别值2 b' u% w4 s1 B7 w c3 Y0 G
Dispersion, 散布/分散度
z: A- d# @, y$ LDisproportional, 不成比例的
R6 q6 e, i; f! T: e5 UDisproportionate sub-class numbers, 不成比例次级组含量8 p" y& Y/ q8 {: }/ n
Distribution free, 分布无关性/免分布1 | h* [( l$ f. R
Distribution shape, 分布形状
% j+ D& Q9 V$ t: yDistribution-free method, 任意分布法
4 f1 a4 Z" P. S' s2 \# kDistributive laws, 分配律 \3 ?! J, V0 l3 X
Disturbance, 随机扰动项
) J" f/ e2 u: P GDose response curve, 剂量反应曲线6 {% t' a* e L' X# B$ j& V
Double blind method, 双盲法
( e% h" g- t! D% H8 X: ADouble blind trial, 双盲试验) y* E; `/ \9 B$ Z$ F
Double exponential distribution, 双指数分布
. c0 j; }/ y" Y4 v: ?( G8 G: R& qDouble logarithmic, 双对数- B0 q" w" J2 g% H" ^3 W p
Downward rank, 降秩
6 ^* {3 t! ~( R# ?8 X8 yDual-space plot, 对偶空间图 r; a/ I& J8 p6 q. Y8 {! O
DUD, 无导数方法
- [8 J5 `. M M: XDuncan's new multiple range method, 新复极差法/Duncan新法# s9 C" I, L" L# L, Z. _
Effect, 实验效应; C1 ]7 U! H( e( ]4 f1 d% L' G
Eigenvalue, 特征值
% \4 \! ~$ ^5 I Y# U# v: ~Eigenvector, 特征向量
7 N! x' G+ Y/ N. `; WEllipse, 椭圆
( u8 R, y# M- sEmpirical distribution, 经验分布% j8 z! H% P2 A& |6 `' U
Empirical probability, 经验概率单位( l x( g) W* V5 g# [( S. U
Enumeration data, 计数资料' }5 s# a( C0 T3 U& |
Equal sun-class number, 相等次级组含量- |& m8 b8 |, w4 |7 m
Equally likely, 等可能
- O4 I8 _) \( U) {2 E% kEquivariance, 同变性$ F; v7 b( Z# h6 Z: W2 u* z8 R
Error, 误差/错误
9 B/ g u. T! [, XError of estimate, 估计误差( a( [ v% @+ m! u5 U v! o
Error type I, 第一类错误! Z5 i; i' o; S8 A
Error type II, 第二类错误 y5 P1 F: A9 g2 I1 O
Estimand, 被估量
3 s( L; s2 C$ b1 M; D8 Z6 ~Estimated error mean squares, 估计误差均方; z- N( T( P1 Q) L6 x
Estimated error sum of squares, 估计误差平方和" E5 h5 Z+ D+ u- Q
Euclidean distance, 欧式距离$ R$ L8 L' I* n+ y; k+ v. V
Event, 事件7 K& h, I0 f& X, P2 T
Event, 事件
/ w, o% R- }3 x; v* s+ GExceptional data point, 异常数据点
+ r" j" X& m+ g- g% NExpectation plane, 期望平面
3 c1 B! J! F3 M- P4 {1 E& a5 t' mExpectation surface, 期望曲面# P6 `$ l# {# |, Y
Expected values, 期望值
; P+ B9 n/ X1 R! Q" Y# rExperiment, 实验; A5 z& m8 y+ B1 m9 @
Experimental sampling, 试验抽样8 N3 R/ N% s" ?6 @) t/ y* s
Experimental unit, 试验单位0 s {3 ^- y ?* H. n3 r, g5 h; z
Explanatory variable, 说明变量
( a3 D$ P% S4 j5 R/ G4 N MExploratory data analysis, 探索性数据分析
4 F B! Z3 q' C$ z) yExplore Summarize, 探索-摘要
, W3 X9 t. G/ D4 k- N( MExponential curve, 指数曲线3 K8 A& H6 ]1 C* p: j9 h& l
Exponential growth, 指数式增长
, |$ k! ?+ U$ NEXSMOOTH, 指数平滑方法
9 y( X& y) o" \ j, l* F& o4 O: \Extended fit, 扩充拟合8 k, V6 |( A6 W8 d2 C
Extra parameter, 附加参数
3 Q+ ~3 I) G/ H8 y0 _! ^Extrapolation, 外推法+ \ U# C8 [% `1 o/ Z( R! j
Extreme observation, 末端观测值
, l2 c' u; d" Z- jExtremes, 极端值/极值
. P* s( ?% I2 H& f0 p) X" d- aF distribution, F分布! H: H! N- Q4 P3 y! v* M
F test, F检验5 |2 U( K7 H3 A6 U% k5 h& n) N
Factor, 因素/因子# J3 e% o: A0 i0 V% G& o
Factor analysis, 因子分析4 }: a. Z5 f1 C: O: Z
Factor Analysis, 因子分析. O& a, d8 r$ ~3 F
Factor score, 因子得分
# w/ w: T1 | R' L% p8 ZFactorial, 阶乘2 ?( p. G5 n* t( g+ D2 y# l* i
Factorial design, 析因试验设计
4 k1 j( r- R( \! j% B# _" eFalse negative, 假阴性
1 v M( H! H3 oFalse negative error, 假阴性错误0 D' T, q0 P& Y
Family of distributions, 分布族
0 u/ w4 ]; e1 P* ^Family of estimators, 估计量族+ F; l% |# j: ]
Fanning, 扇面6 g5 P: V: q" V C7 ?9 [/ B6 o2 j H
Fatality rate, 病死率! \ Y- F( d$ K6 Q
Field investigation, 现场调查
# N5 L) y8 b! ^Field survey, 现场调查
0 B( \% h! c4 i5 [Finite population, 有限总体
. p8 A0 J* I0 D' c3 SFinite-sample, 有限样本" U2 z/ T8 c- ?
First derivative, 一阶导数
' n5 k0 O/ c" I% g4 r1 dFirst principal component, 第一主成分
1 f0 {* w9 ^0 J5 Z& {First quartile, 第一四分位数
K) X6 t: [3 R* s: c9 ]Fisher information, 费雪信息量
) \" t! k5 F& A3 a: X8 z: F: [- y) o7 lFitted value, 拟合值
- W5 N4 A8 _ @# G ]* qFitting a curve, 曲线拟合
/ ~ Q- m( X6 V$ M; m" iFixed base, 定基
$ b! e# E$ S# U3 K* o( ]2 [3 C7 WFluctuation, 随机起伏
& f1 ~" Z$ V+ lForecast, 预测
- h) w( \" ?0 V7 z5 N( B( ]' nFour fold table, 四格表! D8 ~7 h2 h/ |( s' O$ `
Fourth, 四分点
7 X9 e& D z' d8 IFraction blow, 左侧比率
# b( @" o$ s# ~8 MFractional error, 相对误差
3 j s( v Y- k. k0 @Frequency, 频率5 Y% s( o; ?# W, F$ m
Frequency polygon, 频数多边图
( V4 n, H0 h; W0 }Frontier point, 界限点' E$ f& W; e N7 Z& Q
Function relationship, 泛函关系
; ~" @. v! S( x1 F" Q- k* u AGamma distribution, 伽玛分布6 \7 h8 x- U0 O* h0 R" R9 ?: b
Gauss increment, 高斯增量- ~* @! F. a/ X0 d
Gaussian distribution, 高斯分布/正态分布
1 g& M! Y# `% L7 JGauss-Newton increment, 高斯-牛顿增量- C0 V h' U5 K) |$ Q, G: V
General census, 全面普查
: Z+ {- l1 N" C) KGENLOG (Generalized liner models), 广义线性模型 ; [- n% y( g# O" q3 R8 I4 t
Geometric mean, 几何平均数( D; V: h6 A% f; h2 n8 \2 r* X
Gini's mean difference, 基尼均差( a+ i2 R; }# h! ?' n
GLM (General liner models), 一般线性模型 $ L, ^( p, g5 [ O' T
Goodness of fit, 拟和优度/配合度+ E2 b. g# G( q+ ?$ V& ~, Q
Gradient of determinant, 行列式的梯度0 }) v. U6 \6 `+ q6 C5 L! f
Graeco-Latin square, 希腊拉丁方
$ q* r5 b8 v6 F5 L5 EGrand mean, 总均值
; |; r3 }% J6 D9 ?7 o- K7 WGross errors, 重大错误
1 S8 | }6 c$ D& F& h, W; J% X+ L- G: sGross-error sensitivity, 大错敏感度
7 j6 D0 w( y, M8 Q, v* `Group averages, 分组平均
5 U( [ m* @ I* s# gGrouped data, 分组资料
3 m U4 L& k" RGuessed mean, 假定平均数, q, Y4 a, V8 c3 @
Half-life, 半衰期% s! G3 ^! ]1 Y7 Q7 q9 G' y q
Hampel M-estimators, 汉佩尔M估计量
7 J4 Q& f8 n, Z. O/ S) k2 R+ YHappenstance, 偶然事件) {0 k$ h( j6 J; n
Harmonic mean, 调和均数
" `0 x+ i3 p' W5 ^% q+ l, s3 }2 WHazard function, 风险均数
6 q) A" v" U1 N! ]/ jHazard rate, 风险率
- |7 ~" F. f+ R' ]0 L" j) PHeading, 标目 5 v, L8 b, ~; ~$ x |
Heavy-tailed distribution, 重尾分布
/ s5 \$ z1 O% ]- M3 z' C5 ^$ B/ eHessian array, 海森立体阵4 _! d3 J+ q8 W+ o$ z0 d
Heterogeneity, 不同质
' L' f( L- [$ \5 Z4 s. lHeterogeneity of variance, 方差不齐
. H5 {! r3 x2 q+ }. N: G; M6 VHierarchical classification, 组内分组; Q' r6 k! G- z+ e
Hierarchical clustering method, 系统聚类法
. V8 l0 q# i5 bHigh-leverage point, 高杠杆率点
. Z5 c J7 \3 e+ ?* HHILOGLINEAR, 多维列联表的层次对数线性模型
( R8 U* v* ]: U6 d3 g5 c n! xHinge, 折叶点
9 D: B$ n: g0 vHistogram, 直方图
8 ~. r* R- E0 b! n% Y6 @. X9 ^Historical cohort study, 历史性队列研究 : i, i' K* ?: R
Holes, 空洞
% m+ L$ ~/ t* SHOMALS, 多重响应分析
4 k! W# g `5 Y/ [" p2 }& A8 QHomogeneity of variance, 方差齐性
0 U* t( P, o) G. `Homogeneity test, 齐性检验$ A$ b- J9 A) Z4 m' W4 O7 I
Huber M-estimators, 休伯M估计量, A2 \8 K7 i$ }/ q3 `8 k% K
Hyperbola, 双曲线
3 K; e- V; d2 c1 D) K( j9 |$ S2 GHypothesis testing, 假设检验
/ v9 r5 x# F2 A7 B SHypothetical universe, 假设总体
6 W9 Q' q/ y1 pImpossible event, 不可能事件- R2 R C! ~- b; v$ V2 Z( b8 B
Independence, 独立性
1 g( E G* ?1 CIndependent variable, 自变量
8 d' g3 B6 R; `9 j9 {' fIndex, 指标/指数* O* ?, q! W! ^3 K: |$ @
Indirect standardization, 间接标准化法7 j: j2 j) @- S4 a$ R
Individual, 个体
: J, Q! d6 h2 N1 M- r" I) ^" }+ JInference band, 推断带, {/ I1 V S5 i( f) n
Infinite population, 无限总体% m5 O* m0 Z' ~* E
Infinitely great, 无穷大
) Z3 @6 V# @8 ^' uInfinitely small, 无穷小
# O" z, r- `8 y0 D' y& N5 L; N U* vInfluence curve, 影响曲线
0 |* E: J/ h4 E' [' G' L- _Information capacity, 信息容量! z, X+ I. X4 O4 ]
Initial condition, 初始条件
2 j% J- v9 _) g1 q, r, P% S. c( [Initial estimate, 初始估计值
8 A; j# j. ?' h: ^Initial level, 最初水平( V9 K! Y6 Y" Z# X0 \
Interaction, 交互作用
3 ?/ j4 B4 s: s; l2 aInteraction terms, 交互作用项
7 t# ]; Z3 _' J% dIntercept, 截距1 j5 U8 w% m' _. Y9 T8 G5 C
Interpolation, 内插法
& u& W0 n2 _- Y* I' C" c& {Interquartile range, 四分位距
1 U. c7 l; Z! q/ q/ x/ c1 e, l7 r8 d! nInterval estimation, 区间估计
& O! x9 i1 ]3 w7 LIntervals of equal probability, 等概率区间# Y3 k: G" \& V1 D
Intrinsic curvature, 固有曲率
& c& `3 Z$ a) F9 y/ A- EInvariance, 不变性
/ q, W5 ~' y/ {$ ~6 hInverse matrix, 逆矩阵% N) }0 h" S/ c. Y% k. P- p
Inverse probability, 逆概率 Q. Z2 O+ }0 v% ]3 I
Inverse sine transformation, 反正弦变换5 F; F( W/ \6 [& ~9 o
Iteration, 迭代
- U# ~4 G; ~3 L; }( s5 X+ uJacobian determinant, 雅可比行列式% y9 j$ B- ^/ H* A6 C/ F
Joint distribution function, 分布函数
1 i+ _) e" U0 U/ B2 N0 {. cJoint probability, 联合概率! [* }# [$ ?* Z, d1 R$ g1 _& {" x
Joint probability distribution, 联合概率分布! ~6 i$ g" s/ p# K& _* t3 V# l% n
K means method, 逐步聚类法+ r5 |2 k% \- C& ^ p7 ~& Z4 X2 V
Kaplan-Meier, 评估事件的时间长度
: p8 k$ V0 s) S" tKaplan-Merier chart, Kaplan-Merier图
! o0 Z" S! E, P! T! IKendall's rank correlation, Kendall等级相关! W4 v, \/ m! V0 h
Kinetic, 动力学
( M/ L% [0 D0 e9 w% X" GKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
! t0 R1 x9 V. f% G) f- HKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
; d/ |' Z7 q1 G" i1 lKurtosis, 峰度 K% G' Q( t3 R. u; Q; X X# ?/ L
Lack of fit, 失拟
d e: u1 J! G9 k: s, rLadder of powers, 幂阶梯
1 J# S6 J- w3 Z6 H( D, @Lag, 滞后
( |- g# c" n' A5 G6 @% NLarge sample, 大样本. z& ?) @, g% K( N# a' U
Large sample test, 大样本检验; f Q3 _% N& h8 ^' V, C
Latin square, 拉丁方
& `, J+ U7 e# r t+ xLatin square design, 拉丁方设计. K5 i" y. X( E" f
Leakage, 泄漏' C: B1 Y2 _. U' R: b& q9 H
Least favorable configuration, 最不利构形
: U' f/ [) l5 GLeast favorable distribution, 最不利分布
7 [/ i+ s) ?9 C+ e [Least significant difference, 最小显著差法
( v# Q4 q# ]3 qLeast square method, 最小二乘法: Q8 g) p) I# x/ O
Least-absolute-residuals estimates, 最小绝对残差估计; Z2 P* W1 K; I5 h: i/ |) j
Least-absolute-residuals fit, 最小绝对残差拟合
8 J$ n- m6 w# R! f8 g" fLeast-absolute-residuals line, 最小绝对残差线, Q& L3 `" O, [- L
Legend, 图例/ ?2 q0 l3 O4 ]# ~ \' P. M
L-estimator, L估计量
5 p7 o* L* b- D3 J( D ML-estimator of location, 位置L估计量5 i3 B E: j: n& c5 W
L-estimator of scale, 尺度L估计量
) L+ z9 X; }2 SLevel, 水平7 L. z* Y+ M0 I/ e' u3 [
Life expectance, 预期期望寿命! ]+ {; l- \7 I% B6 j. _/ @# i
Life table, 寿命表: D9 C& a! e. d1 I- c* L
Life table method, 生命表法
9 x0 L/ B; x& N B. sLight-tailed distribution, 轻尾分布2 J! V( b0 |$ U, p
Likelihood function, 似然函数( S: G6 c4 k4 r/ f; V6 _' Z
Likelihood ratio, 似然比
8 {* {+ I. q/ p" U Jline graph, 线图8 P0 F! E# }$ @' g" a7 \- S* {- x% e
Linear correlation, 直线相关. \& t, ^# y; x1 t
Linear equation, 线性方程& I' w; `9 @9 E* h( x; {0 C: P
Linear programming, 线性规划
0 K& E3 ^ w, k, K% N2 G6 c4 uLinear regression, 直线回归
0 M0 @ S4 e( ILinear Regression, 线性回归$ u8 ?1 g/ d U" D, F2 p Y
Linear trend, 线性趋势2 j4 c6 B) m, f u5 P. r
Loading, 载荷
+ t6 ` n8 N, Z2 a4 V4 A. C4 jLocation and scale equivariance, 位置尺度同变性. ?" p8 k2 q' H+ }
Location equivariance, 位置同变性" E$ I' E# B3 K
Location invariance, 位置不变性
) K$ q9 f) N0 i4 `Location scale family, 位置尺度族
! T1 _; w* @8 ALog rank test, 时序检验 1 G# r' o3 g5 r6 h5 T
Logarithmic curve, 对数曲线
) s( T. u( V8 ?9 Q2 U) {1 gLogarithmic normal distribution, 对数正态分布
2 `2 b/ H! ~- H3 x! LLogarithmic scale, 对数尺度
7 V# p' w' @! c( T0 h5 V% [! pLogarithmic transformation, 对数变换& o! X$ L. R4 R4 s& h
Logic check, 逻辑检查) B$ g) X4 R: f! x2 Q
Logistic distribution, 逻辑斯特分布
3 S4 B* L/ o* {- x* T* GLogit transformation, Logit转换: @& X$ q; n3 Y" |# Z+ c
LOGLINEAR, 多维列联表通用模型 $ A7 [: @0 ^: ~! H
Lognormal distribution, 对数正态分布* I# `5 O- r9 @( z4 _2 N
Lost function, 损失函数
; h$ I! `8 H j4 XLow correlation, 低度相关
' y7 S& U4 L: h2 h# U) ^: X& sLower limit, 下限3 X9 ?7 j- l' ]% p' C! T Q0 H
Lowest-attained variance, 最小可达方差
4 n' s2 t& o( n/ a( O4 q+ E' yLSD, 最小显著差法的简称
" t5 I# Y! ^* c. ]# Z* WLurking variable, 潜在变量
' z5 y. ?: f* F, jMain effect, 主效应3 t4 Z' Y, Y; m! g- k/ n
Major heading, 主辞标目
& O9 s3 u! i# d H) W, s9 eMarginal density function, 边缘密度函数. ]( g+ u3 \+ Q2 u' j" p% j# e
Marginal probability, 边缘概率! M8 F" f9 _) j1 Z, |8 ]
Marginal probability distribution, 边缘概率分布; S, C2 M/ n! r+ v
Matched data, 配对资料4 O) h* v! `) D- c y2 S" P' O
Matched distribution, 匹配过分布
/ H1 f( q/ F9 l7 [7 V% `6 Y% cMatching of distribution, 分布的匹配- h4 ^# J7 V. |3 v
Matching of transformation, 变换的匹配
3 r1 R! d7 ]1 Z) U- U$ U0 [Mathematical expectation, 数学期望
# h( u8 i6 P& h* h! M0 l. a; oMathematical model, 数学模型0 |# e6 q. P# p3 ]* W' ~# R) S- J
Maximum L-estimator, 极大极小L 估计量; p# Q1 s& _7 ?2 H, f- ?3 z; W/ A) a
Maximum likelihood method, 最大似然法% Q5 p- H/ {! S
Mean, 均数
9 T) ~$ s- r* K) k, RMean squares between groups, 组间均方$ X$ }, f6 ?5 `) H2 m, W
Mean squares within group, 组内均方0 r( a- ]# }% v' q0 d
Means (Compare means), 均值-均值比较
2 @7 i$ ]. b" |) yMedian, 中位数
% s9 }* N" u8 G2 \7 M, }& S+ WMedian effective dose, 半数效量/ T1 @# N- I- G' e% o# m* R
Median lethal dose, 半数致死量
( z7 C7 Q9 T4 X6 _1 U# A9 G8 e" RMedian polish, 中位数平滑
) z' m. {/ j: V) }2 |Median test, 中位数检验
3 [7 [- S; Y- C5 n3 l7 xMinimal sufficient statistic, 最小充分统计量2 n7 x& x: z" L; p" Z2 R7 t, B
Minimum distance estimation, 最小距离估计& {2 R& l* R4 J: Q2 k) j R9 p) M
Minimum effective dose, 最小有效量* @8 q+ F, m, l3 V0 i2 ]1 p
Minimum lethal dose, 最小致死量' @8 ]; Z6 L$ U8 y
Minimum variance estimator, 最小方差估计量5 v# F, H. S# ^# U9 n* k
MINITAB, 统计软件包
# c( M( d4 Y# U( F/ iMinor heading, 宾词标目
( v; k" P/ G* Z+ RMissing data, 缺失值
, z O4 f& T- I: _: N8 gModel specification, 模型的确定
; [" N2 m2 ^: u& cModeling Statistics , 模型统计5 D. k5 d5 y6 C8 _
Models for outliers, 离群值模型, W6 p' x7 o" ^+ q/ }
Modifying the model, 模型的修正
4 j; o9 i ~) ^2 k- K" ?Modulus of continuity, 连续性模
$ s% w) g7 b" L* S% Y2 aMorbidity, 发病率 " x- |. P* k3 Q/ s
Most favorable configuration, 最有利构形
3 n, Z6 b Z5 Q9 H% I9 YMultidimensional Scaling (ASCAL), 多维尺度/多维标度6 L b" p/ b" A; @# F- n+ t
Multinomial Logistic Regression , 多项逻辑斯蒂回归2 R! J7 x6 [: D& P: \
Multiple comparison, 多重比较* z) {/ E# `: H1 i# y
Multiple correlation , 复相关# a% F# i( p' {6 @8 t2 r: C N
Multiple covariance, 多元协方差& T7 m/ ]0 B/ o
Multiple linear regression, 多元线性回归# Y# }! ^ ]- j5 T |* H# v
Multiple response , 多重选项
% F, s& a9 t: e7 V# \Multiple solutions, 多解0 x! A# p9 J; T
Multiplication theorem, 乘法定理9 N) ?( W: O1 `8 u7 a* D6 c0 S O! m6 R
Multiresponse, 多元响应
" I5 W2 ~3 p$ n+ Y+ rMulti-stage sampling, 多阶段抽样
, r; s3 F* M- N, i( IMultivariate T distribution, 多元T分布: D$ z& y7 N: ^! F7 F. G1 E r
Mutual exclusive, 互不相容
4 G) W6 r" d1 G" c1 C( G# DMutual independence, 互相独立
& N; B/ N$ j# W/ X0 ]( g% kNatural boundary, 自然边界, ` L3 C' e ?) Q+ V
Natural dead, 自然死亡
8 ^3 Q3 b4 x6 F* q* GNatural zero, 自然零
% h! i. G9 ^) g8 u. W. ^Negative correlation, 负相关3 }: F: L0 n2 P# m) W( ~
Negative linear correlation, 负线性相关
+ A5 O: Z$ N4 ^ S% ?! H- g# ENegatively skewed, 负偏
6 l1 X- M2 l3 w1 n c9 r4 h' aNewman-Keuls method, q检验
* H( C4 N8 i1 i; Z; eNK method, q检验
% o# y/ U3 k9 a) l* JNo statistical significance, 无统计意义$ G+ s8 e# D' Z4 E/ J
Nominal variable, 名义变量
8 \( C) S& d3 k# a. lNonconstancy of variability, 变异的非定常性
$ e K3 e( \$ T/ w+ _% w/ N& \Nonlinear regression, 非线性相关
9 {# ]7 A( H0 R( u4 V, {- C oNonparametric statistics, 非参数统计
2 P% q r( o0 o; S8 a: vNonparametric test, 非参数检验, h+ {6 T2 S; G6 u" [
Nonparametric tests, 非参数检验
; Z- J! t J3 y2 ]: T( \, s3 F) a$ XNormal deviate, 正态离差 D3 a3 v# w9 G# ]0 U) h
Normal distribution, 正态分布0 b0 R* E: a2 c: m5 j
Normal equation, 正规方程组
, @5 i3 D0 m! J' ]/ mNormal ranges, 正常范围
: }' R \& X% Q4 r. f2 J1 u, ?% i0 }( TNormal value, 正常值
& g( S8 I" G: k. c. M4 H3 U+ NNuisance parameter, 多余参数/讨厌参数" H. |/ F5 w8 J+ x4 `5 t0 {6 |
Null hypothesis, 无效假设 d9 K3 H$ N# P* Z
Numerical variable, 数值变量$ I, L! G) }- u c5 i: M Z
Objective function, 目标函数; _2 U d0 R. W3 H' ?
Observation unit, 观察单位 c& R2 y6 x+ l+ d) O
Observed value, 观察值5 i2 P3 g: q; [
One sided test, 单侧检验
7 h& k1 N5 n0 f d# jOne-way analysis of variance, 单因素方差分析: m; m3 {) N2 P1 f7 q. g* ]
Oneway ANOVA , 单因素方差分析
: r2 Q9 B% f qOpen sequential trial, 开放型序贯设计
+ T/ z3 n9 g# r+ x @0 DOptrim, 优切尾 p- ?" n! g/ x3 X7 M
Optrim efficiency, 优切尾效率, F% s! x H+ u1 d. U
Order statistics, 顺序统计量
5 K; j% F- b* M$ N. UOrdered categories, 有序分类
; N! P' J3 ~7 L& wOrdinal logistic regression , 序数逻辑斯蒂回归
" L5 Y" T5 R- H4 H3 ^6 U- lOrdinal variable, 有序变量% X9 Z" n* C" a- o3 p- A
Orthogonal basis, 正交基
$ [' `2 E: M4 ^Orthogonal design, 正交试验设计) K# ~$ ~) @9 F9 t
Orthogonality conditions, 正交条件
3 m) H: w' Y) f9 i" b& DORTHOPLAN, 正交设计
+ K# T! a8 S6 N9 S, S) |5 aOutlier cutoffs, 离群值截断点0 e4 ^) j+ {' b
Outliers, 极端值
* x- M" h( p% w/ r9 `OVERALS , 多组变量的非线性正规相关
* Z9 \. v5 T0 u& K7 wOvershoot, 迭代过度" |- u& Q. E0 e7 Q
Paired design, 配对设计# P- z2 Y; b3 B, ]
Paired sample, 配对样本
9 |* V9 Q8 F% z5 vPairwise slopes, 成对斜率4 T5 h4 Z4 n# y" o( T! J$ m% Q- M
Parabola, 抛物线, |% j6 p* L7 e( _' a
Parallel tests, 平行试验
. }& r/ _+ `5 |3 r8 p! i& FParameter, 参数
0 M' W; p. f0 g! I8 W! pParametric statistics, 参数统计
9 E) O! k" L0 X" C! E& r% |Parametric test, 参数检验
. k0 N. |( L( u1 P; _1 }Partial correlation, 偏相关
3 W( v7 ~% O! ?) m8 v- R6 P! G* y" RPartial regression, 偏回归) i6 M0 s7 g9 B+ L. j3 q. |
Partial sorting, 偏排序
8 I7 w1 L( Z) `' B' \' Q2 p, lPartials residuals, 偏残差9 f2 \; |$ a" ^
Pattern, 模式2 v" o: x' J" Y7 U
Pearson curves, 皮尔逊曲线
- R) |0 u a- U) t1 PPeeling, 退层/ r' R$ ?' ^2 H- ^
Percent bar graph, 百分条形图
' @) H+ Q- R7 ?& z8 T4 \: A; K" d j% lPercentage, 百分比, K0 f7 g1 z/ ?' H6 g& H* d2 w/ |
Percentile, 百分位数0 `: t( m/ z7 v, f. h, @
Percentile curves, 百分位曲线
& H9 | q2 w' m3 ZPeriodicity, 周期性
, r: f' s7 v$ }& iPermutation, 排列
! r( v, M" s0 o! s% i7 hP-estimator, P估计量3 Z0 h/ G7 X: h
Pie graph, 饼图; X' x3 ?! o# ?! V- [& Y
Pitman estimator, 皮特曼估计量4 {; @5 t# N& p+ U$ W1 u: Q1 b1 R
Pivot, 枢轴量
! _) F" o; N! ]1 v/ D2 v! m, V2 nPlanar, 平坦
$ \7 r" Q/ l3 d( Q( Z. bPlanar assumption, 平面的假设
+ M. E% g! `! [" p+ i5 H7 }3 TPLANCARDS, 生成试验的计划卡5 Z X* k7 ^5 _0 ?5 {, q+ i: y
Point estimation, 点估计
3 J$ A9 N& m* F) cPoisson distribution, 泊松分布" ]1 f! M b6 ]
Polishing, 平滑
, q# P T. |) R+ y e. U( S L" {Polled standard deviation, 合并标准差+ i% B/ c; N2 B+ P
Polled variance, 合并方差
& T8 c5 [2 N+ z: ^7 I+ dPolygon, 多边图
, h! \' ~9 N4 H+ x8 {Polynomial, 多项式
0 C7 G; f1 d5 k" X6 _Polynomial curve, 多项式曲线
: E8 }! o! n3 p s6 r0 qPopulation, 总体
% j& f5 [. H+ K- W' h9 y6 |Population attributable risk, 人群归因危险度/ y$ a" e4 A+ G, o$ l0 V9 @
Positive correlation, 正相关' l4 @5 b. ]9 p* }. T6 R
Positively skewed, 正偏
6 ~7 n; T* n d, J" ?4 Z* y9 }Posterior distribution, 后验分布+ V0 n4 |- P* d, I2 Q4 ~' I
Power of a test, 检验效能
% j9 A5 y: R5 s! Q' {Precision, 精密度. b: ~: p$ y1 B$ n/ ?4 [
Predicted value, 预测值; p# l1 ]( R; C
Preliminary analysis, 预备性分析
7 ]0 s W d4 M3 L( @3 C0 ~7 @: NPrincipal component analysis, 主成分分析
) H! t3 ~( t+ d# ~1 TPrior distribution, 先验分布/ }% ` K+ S& f/ C% b0 d& W
Prior probability, 先验概率' \# `, [3 R# M8 X% ]3 P7 p- F3 X
Probabilistic model, 概率模型' K2 F; @/ W+ S/ n7 S$ D
probability, 概率( I0 C; s# q7 ?0 Y a5 L& `8 j- T9 I
Probability density, 概率密度
6 t% T! v3 ~+ K* Z$ U8 RProduct moment, 乘积矩/协方差. t& c1 U$ F0 ]! H3 ?# X
Profile trace, 截面迹图
1 P E5 R, R' R2 F+ d$ u6 UProportion, 比/构成比 |5 n9 `4 u# J- m
Proportion allocation in stratified random sampling, 按比例分层随机抽样# _( R) w Z6 `) V; [; V
Proportionate, 成比例
8 ] u% b+ A- Z$ L4 R+ i" aProportionate sub-class numbers, 成比例次级组含量4 N) P! v f0 N4 K
Prospective study, 前瞻性调查9 q, p5 i6 k0 i/ e5 {' b
Proximities, 亲近性
& k w2 C: d7 y) A. q7 uPseudo F test, 近似F检验5 y- H7 l* U3 I9 [1 g5 ~
Pseudo model, 近似模型
' o, x9 l( g0 ?7 {7 fPseudosigma, 伪标准差: e4 `, L: M: Z2 g0 G
Purposive sampling, 有目的抽样, {8 u* h4 _% }. t& |
QR decomposition, QR分解$ m# X8 C, z1 M, E* q# ?; ]
Quadratic approximation, 二次近似9 D/ r- m+ G/ t
Qualitative classification, 属性分类
# p; ^. M7 a3 Z" d- V5 ~Qualitative method, 定性方法
t& T( [+ D0 t. _Quantile-quantile plot, 分位数-分位数图/Q-Q图: J2 }- _7 a; d* x% A: U+ n& y2 Y
Quantitative analysis, 定量分析
3 E5 l, X V) b2 C! qQuartile, 四分位数
0 I3 l7 d2 t, k. iQuick Cluster, 快速聚类; ]$ i- i9 w$ ~
Radix sort, 基数排序/ r y9 ]+ D f/ K
Random allocation, 随机化分组1 k$ Z7 V. I" k
Random blocks design, 随机区组设计
6 q2 v* h: k- [% i, A+ ?Random event, 随机事件
2 f% |8 b1 T2 ]' z' n. u+ ~Randomization, 随机化
$ j5 m# D& T: D& }Range, 极差/全距/ K7 B. t3 S" H2 T8 `% A6 K5 j: L# m
Rank correlation, 等级相关
4 Y; O( I/ H4 `Rank sum test, 秩和检验
0 h# H' a* s6 T! Y2 YRank test, 秩检验: Y9 k4 y1 ^) b6 \( N. w- @
Ranked data, 等级资料
' @ u# j" s* M: `& e1 x% PRate, 比率4 v$ z0 s% t, J) ^& W3 w! C
Ratio, 比例
) v4 U3 @0 e" f+ D8 ?Raw data, 原始资料( L. P) W @7 H& D8 \! Z8 U# _
Raw residual, 原始残差8 [5 ~' S" Q; u0 N6 ^) O/ x
Rayleigh's test, 雷氏检验
! s8 }7 z( J& d6 v; e% e: eRayleigh's Z, 雷氏Z值
; J6 \% O W; H3 ^8 cReciprocal, 倒数
& v! A" p3 T. q' ?& |Reciprocal transformation, 倒数变换! L0 |, Y' o. K$ C; Q
Recording, 记录8 G. q) i B4 P9 |
Redescending estimators, 回降估计量1 n9 |* \ `6 x% h) J* [2 @ z
Reducing dimensions, 降维
! O: e1 f; ~( Q9 @9 k7 S2 D1 ~Re-expression, 重新表达6 `* T. U2 ]: |
Reference set, 标准组
; w$ {$ H& W% j, O, H- m# }Region of acceptance, 接受域
$ \7 ~1 m2 ]+ E/ g) zRegression coefficient, 回归系数
( ~7 L6 i- h6 r; ?3 _, qRegression sum of square, 回归平方和
" C! L% l1 n$ @6 TRejection point, 拒绝点
# t9 P5 \4 @, @Relative dispersion, 相对离散度
+ ]; q" k5 ^. f% O4 j2 C& Y+ ?Relative number, 相对数
% N. ~& `1 u0 j1 w, \9 eReliability, 可靠性& Q9 n( } K/ ^) C, v
Reparametrization, 重新设置参数
* \4 ~- L6 R. dReplication, 重复
: `/ s! Z8 O# B4 ^& e# R% X5 GReport Summaries, 报告摘要
% l+ D1 G: [0 U1 SResidual sum of square, 剩余平方和4 p' x1 y6 l8 p4 f7 F f' d
Resistance, 耐抗性- z3 G# M9 D/ j- E7 N
Resistant line, 耐抗线1 e& t# Q8 P2 ] Z9 X( O
Resistant technique, 耐抗技术1 | T; y5 ^* }! l
R-estimator of location, 位置R估计量7 G5 i0 \1 j7 x3 e
R-estimator of scale, 尺度R估计量) a* H6 z2 j& g- n$ K
Retrospective study, 回顾性调查
! \' u! O( ?$ ~Ridge trace, 岭迹
4 ]& j0 b. G6 C4 N$ R6 x: nRidit analysis, Ridit分析 M5 T% k3 `1 [. a' A$ V5 u+ E# L
Rotation, 旋转
, K) {7 v) S: O( y- r1 t4 q5 K9 YRounding, 舍入
' M: K( c% F' ?, HRow, 行
' P2 G, L2 g& L. _: URow effects, 行效应
s# J4 D$ x' ^+ N0 F$ Z2 Q" p; n. H, LRow factor, 行因素
2 L* R) |. p1 T0 M( lRXC table, RXC表1 v% v0 ^$ Q! [7 Y
Sample, 样本
- i3 @* g+ ~9 B+ USample regression coefficient, 样本回归系数
* Q: w d) E2 @3 v7 Q8 a# bSample size, 样本量0 V3 n9 [! g: f
Sample standard deviation, 样本标准差
) t4 U# i! G5 l4 ] Y& @ j+ bSampling error, 抽样误差" C: [& i0 c$ a1 i$ W! `
SAS(Statistical analysis system ), SAS统计软件包
6 H* _2 I' _0 h: ~( _1 p" }2 aScale, 尺度/量表; z8 C2 Y6 ]; M" Y& K! [
Scatter diagram, 散点图/ y5 h0 U0 t# @9 W# ^6 Z
Schematic plot, 示意图/简图* _' {2 b- g' ^5 y! N% ]6 X) _ H" {1 E) \
Score test, 计分检验
$ G# B7 {( t7 \0 v! p# IScreening, 筛检" Q7 i- o3 ]. E
SEASON, 季节分析 6 S7 s/ R7 e6 w' c$ P& ^. N
Second derivative, 二阶导数" a0 C3 _* L3 Y! i7 ?" I/ x/ b7 y4 |, l
Second principal component, 第二主成分7 i. W3 E( L* O9 N8 L$ D) o
SEM (Structural equation modeling), 结构化方程模型
9 a) q3 v* z# Q* s& G' C6 D/ S/ jSemi-logarithmic graph, 半对数图
- a9 H5 s; K* a7 z; uSemi-logarithmic paper, 半对数格纸
/ \ Z N2 R/ ^8 _! @6 \Sensitivity curve, 敏感度曲线
* e/ I/ l$ ~. M4 f1 c2 j* Z0 c# \" lSequential analysis, 贯序分析
8 C5 u# \+ v( H& W1 \! dSequential data set, 顺序数据集9 y# ?/ K! `! z1 E, q3 l
Sequential design, 贯序设计7 W* ^/ n6 q' m
Sequential method, 贯序法; i `# T, h; }
Sequential test, 贯序检验法1 ?( J; f [3 y* `
Serial tests, 系列试验1 w% @* E8 N# {2 m7 s8 ^
Short-cut method, 简捷法 6 Z0 g6 ]% C! j/ L( }" @
Sigmoid curve, S形曲线, o( F D9 }- m; v; J ]: [& X
Sign function, 正负号函数+ A5 W& T# {' W( K
Sign test, 符号检验
4 ?5 N w& Z# M" Z/ l0 o! n" aSigned rank, 符号秩
- d+ h# s- m8 VSignificance test, 显著性检验
; }/ A2 F. X& p! f jSignificant figure, 有效数字, A( p8 k3 G+ n/ `% e) q: G& ~
Simple cluster sampling, 简单整群抽样
% |) A; h8 \7 P& iSimple correlation, 简单相关
' z I6 P* b& Y+ B2 ]Simple random sampling, 简单随机抽样$ r+ x! {, \: O) p
Simple regression, 简单回归
/ Y% c7 q3 Y& Z) L: ^& Esimple table, 简单表5 h9 L2 S. e8 y9 T5 A. p. z8 k
Sine estimator, 正弦估计量
% k0 {6 X; W+ E: J4 m5 G$ E CSingle-valued estimate, 单值估计
- K, _. L9 M, `1 `Singular matrix, 奇异矩阵
( f( @9 |9 n. K0 \Skewed distribution, 偏斜分布
$ M8 Q* M. F: ]Skewness, 偏度
) c6 A$ W: m3 a0 b6 e- b; uSlash distribution, 斜线分布
, v+ A' N9 ^0 d" lSlope, 斜率4 g3 G, }4 Y! c% ]2 o
Smirnov test, 斯米尔诺夫检验. W5 u; a8 m4 k' n
Source of variation, 变异来源! ?& a/ Z4 W' b$ w) N7 l
Spearman rank correlation, 斯皮尔曼等级相关
% C. E$ ^2 n: h2 o8 y$ a% NSpecific factor, 特殊因子
# D8 S" X( D( BSpecific factor variance, 特殊因子方差
. G; d: s7 U, H* I- G& pSpectra , 频谱/ ~/ r, `* k0 E. Y* H
Spherical distribution, 球型正态分布0 f2 A( z" t4 T9 C5 V& e- Q
Spread, 展布
% b4 X+ ?$ Y+ i( LSPSS(Statistical package for the social science), SPSS统计软件包
& V6 _5 R1 `, U! ESpurious correlation, 假性相关
% a, ?- Q9 T& J/ PSquare root transformation, 平方根变换2 Z; U' n# m# ~3 P0 Z
Stabilizing variance, 稳定方差
, w, s4 L7 v8 p* D4 y" fStandard deviation, 标准差
; f D, ?. Y# ^; dStandard error, 标准误
# N( B) M' [0 G$ ]1 nStandard error of difference, 差别的标准误
5 `8 |; f$ U* M6 h( JStandard error of estimate, 标准估计误差
! X+ G- ]+ ]; d/ U" b8 UStandard error of rate, 率的标准误
& O' `& Y7 ~4 m# nStandard normal distribution, 标准正态分布9 `7 V, |# f! A& d- z8 }1 }" [2 w
Standardization, 标准化
9 g) Y# ~0 v2 I7 m, N r* v& R wStarting value, 起始值6 r, f6 ^' L& Q4 G3 S
Statistic, 统计量
0 d. V, L3 h3 Q: YStatistical control, 统计控制; Y# N$ Z2 R' x, b
Statistical graph, 统计图. v) R; g6 h) q7 v
Statistical inference, 统计推断) j! I0 ?2 O/ K: S
Statistical table, 统计表
' L* j: v7 p5 j& VSteepest descent, 最速下降法! R5 E% k J, J- T. ^
Stem and leaf display, 茎叶图
5 g# }# J. w' u8 U. j& YStep factor, 步长因子" G2 H' }. ~5 ?& K8 P
Stepwise regression, 逐步回归
6 e- D2 D( X0 i" L# ZStorage, 存" t O+ \/ t3 }+ j0 x
Strata, 层（复数）! ~$ B5 z5 E7 F, u( P! y
Stratified sampling, 分层抽样
0 _# y, T; q% o z2 D9 n8 q- MStratified sampling, 分层抽样. \% k' n. a; J; I) R/ A
Strength, 强度
/ q9 B- A- h6 q; Q% s& [8 nStringency, 严密性
# T0 Z# _) J2 P# cStructural relationship, 结构关系0 ~4 b' E/ L/ a' J6 H
Studentized residual, 学生化残差/t化残差
1 W5 e3 w' G1 q* K5 f+ ^$ [Sub-class numbers, 次级组含量8 o( [1 P4 n+ F- W% o$ S% a
Subdividing, 分割4 s# a9 k4 f4 R
Sufficient statistic, 充分统计量) L0 u% h+ d5 a' ^
Sum of products, 积和3 f% e6 m7 R7 T4 Q! Y) k1 _
Sum of squares, 离差平方和
$ I& m( I/ r* |3 S; xSum of squares about regression, 回归平方和$ r' e( `9 q: F# D' h7 g' \
Sum of squares between groups, 组间平方和; V# k3 p4 e @- l! |% n+ s2 j
Sum of squares of partial regression, 偏回归平方和
$ k7 K. b6 w& D2 @; X* sSure event, 必然事件
% ^! B% a* }! u9 |% E' j+ g' fSurvey, 调查
) N: f* ]1 v. x& I0 l8 m# g/ H$ WSurvival, 生存分析" ?8 L7 `& r! q4 s3 k
Survival rate, 生存率$ X; B( ]5 T$ o
Suspended root gram, 悬吊根图! c5 c5 q9 ?& z0 c3 P5 l
Symmetry, 对称
# |8 H; i- }9 W8 I5 H! GSystematic error, 系统误差
! W5 S/ x5 M( U3 bSystematic sampling, 系统抽样2 \7 t. }* {& o. n, V; u
Tags, 标签" k! J& M5 r' u4 n6 l5 ^( ^
Tail area, 尾部面积
3 q) g M1 f; y7 `( ETail length, 尾长/ |7 ^7 B4 y+ Z: p" f- U& Y# I
Tail weight, 尾重
7 i5 B! U! Y" w; F' o" ATangent line, 切线) |) i) p% @- A" A; r. b- W
Target distribution, 目标分布
) V8 g9 {/ X( A$ MTaylor series, 泰勒级数4 d: y5 }) u( O$ w- H
Tendency of dispersion, 离散趋势
2 U" y% Z; T( s8 d5 E" iTesting of hypotheses, 假设检验
7 n& ^% H6 o7 }( {/ aTheoretical frequency, 理论频数, P8 c7 r# v) s7 _6 [
Time series, 时间序列
* ~+ H2 Z% p# e' k+ {Tolerance interval, 容忍区间: T3 }; t& n: Q9 `- h4 V: \
Tolerance lower limit, 容忍下限
) `% M c0 T# V+ y3 t: WTolerance upper limit, 容忍上限1 f- ~! i: n$ l4 p
Torsion, 扰率: ]. `+ S! s; Y( G" h
Total sum of square, 总平方和1 x9 b" P7 `/ l; R
Total variation, 总变异, E. e4 ~" h/ @ p7 {) l
Transformation, 转换* K& Y/ e" q7 a, ]3 M
Treatment, 处理* Z ?: |5 _6 V/ `# J6 b
Trend, 趋势
6 d' L+ ]; C% ^$ ~, G( ^! V/ ?, ~) S, hTrend of percentage, 百分比趋势8 r. c" M, ?8 I- L" s# }
Trial, 试验
- ]- d, O# \$ m) u7 K! l1 jTrial and error method, 试错法" Z7 B- q7 Q* T9 n; ?9 n2 I
Tuning constant, 细调常数; d) |3 T; z9 _$ U7 `& C% h. [
Two sided test, 双向检验( H0 K$ u% a2 P5 h6 D0 S
Two-stage least squares, 二阶最小平方, q2 r4 I0 R* a. t' H
Two-stage sampling, 二阶段抽样' A; d6 I0 G/ p% S
Two-tailed test, 双侧检验
3 @! Y- u2 f# t. m* tTwo-way analysis of variance, 双因素方差分析
9 w; O& ?, J$ l9 q& |Two-way table, 双向表
1 V; w3 K* I' W P' ~* z: l% |" lType I error, 一类错误/α错误
4 C0 w7 ]# S9 ^% S I1 q% t& T( zType II error, 二类错误/β错误
& y, K9 G% T5 W) Q/ S5 \5 tUMVU, 方差一致最小无偏估计简称9 h6 P- M X1 Z7 i
Unbiased estimate, 无偏估计
* B' i. ~- S# NUnconstrained nonlinear regression , 无约束非线性回归7 g/ Y% e4 o: v! ^1 b% x4 r9 D
Unequal subclass number, 不等次级组含量
0 H! n' b& U: e8 m. ^/ d8 SUngrouped data, 不分组资料6 C1 m% e5 N" j4 T& R
Uniform coordinate, 均匀坐标+ t y% K3 X( p
Uniform distribution, 均匀分布5 O- g% ^% y3 F% |
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
% p. M' i4 `6 ?# G6 d4 F8 a% Q' zUnit, 单元
4 h c A* w1 R9 _" M9 f! k1 ?; I& fUnordered categories, 无序分类2 i# h$ v; D6 c E+ I8 k0 h; |
Upper limit, 上限" ]7 l$ p x4 Z% G2 I
Upward rank, 升秩
. j m4 u8 q; i( t$ h: {Vague concept, 模糊概念) `( _) }1 |. z! p9 r: I/ c2 J$ R& A
Validity, 有效性
F; K3 {. F% Q( Z. v; aVARCOMP (Variance component estimation), 方差元素估计) K2 y! {$ T; E' w; R: Q
Variability, 变异性
9 g P& K- D2 ^Variable, 变量9 o; d1 q/ w% W( t2 D8 ^) x
Variance, 方差
" D- J6 ?$ J- L0 |* D4 t, A3 y1 q/ AVariation, 变异
! b; m$ z4 ]& ^6 BVarimax orthogonal rotation, 方差最大正交旋转
3 H. `$ [5 |$ Z) L+ i' yVolume of distribution, 容积
; r! f9 k& F9 S' |% k& D. t. Q! pW test, W检验7 t0 q1 b' _; m5 Z) V: `- A% N' K y
Weibull distribution, 威布尔分布
! w L, X- K+ d z9 V, {Weight, 权数+ P9 {' q) E9 J6 R( L
Weighted Chi-square test, 加权卡方检验/Cochran检验
$ W5 p' S% e0 B( I! M# SWeighted linear regression method, 加权直线回归
; g& o4 I( y: O- eWeighted mean, 加权平均数7 n7 } \2 Z& |) ?
Weighted mean square, 加权平均方差' ?0 E3 V0 B7 v& U' v
Weighted sum of square, 加权平方和
$ M/ m# n$ [* F& n+ sWeighting coefficient, 权重系数
$ N+ S4 k0 g7 Y4 c M6 bWeighting method, 加权法
4 ~5 K- @! K* l, }4 cW-estimation, W估计量
7 b, s( D" P5 bW-estimation of location, 位置W估计量
$ a- F2 M" E/ g5 ^/ JWidth, 宽度3 g! M `9 T- b0 ]0 l
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验( l: Q* P. |* w% V
Wild point, 野点/狂点- S8 c- z2 w7 f
Wild value, 野值/狂值! G# V7 b: W) ^) {
Winsorized mean, 缩尾均值) L8 a# l, E. w9 k
Withdraw, 失访
9 t/ F; P% g* BYouden's index, 尤登指数
0 _; P9 X. o+ c5 B" ^* M: a. KZ test, Z检验! z+ ?9 @9 J+ a) K' d: C2 ~
Zero correlation, 零相关# [2 `' t# t: {; k* Z6 n; v
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
