|
|
Absolute deviation, 绝对离差. [2 K( }0 }( N3 D' ]; g5 T
Absolute number, 绝对数
- r8 K+ _1 U* n% OAbsolute residuals, 绝对残差
+ _/ @, V6 g6 S0 E' L4 `; zAcceleration array, 加速度立体阵
M% ~1 R7 [0 ^* s( h; i9 y( `1 R5 \% j* j) sAcceleration in an arbitrary direction, 任意方向上的加速度
' P% R. S4 X0 s1 b, E: \# `. S6 H) N1 f& jAcceleration normal, 法向加速度' J( Z; ^' p! y# a
Acceleration space dimension, 加速度空间的维数
; t2 U5 U m5 {( b) x' r: Z0 D2 aAcceleration tangential, 切向加速度
' t. ?7 B7 d- Q; X9 mAcceleration vector, 加速度向量; s" K( Q+ B! O( d* r7 v
Acceptable hypothesis, 可接受假设% w; v% [' V3 H0 v* _
Accumulation, 累积- }+ ?- s! ~) H9 I! p
Accuracy, 准确度
* j* }4 S1 x& r' F; K% n" zActual frequency, 实际频数% o. b1 e( {. T( e
Adaptive estimator, 自适应估计量
+ x5 Y: m# J6 b( tAddition, 相加
* D- T8 x& B |# A T+ fAddition theorem, 加法定理2 ?8 m2 r& x. Z! v1 m! h7 f7 [: s: A, q7 D
Additivity, 可加性
0 N) \3 Y l; y, ~/ [; MAdjusted rate, 调整率5 p( P$ `0 l& G: s1 K$ e; }# T" i
Adjusted value, 校正值: r$ w0 z; K$ \2 y! m9 _7 e- a& J {
Admissible error, 容许误差! N C9 U. k5 W7 G; u5 ^. Q& ?( l1 S
Aggregation, 聚集性
' v1 `) U9 T$ k* t/ SAlternative hypothesis, 备择假设3 l! L6 h2 }/ f4 ?- ]
Among groups, 组间& S4 C7 {- B, I% t' [. ~
Amounts, 总量9 A$ H F# K( O5 d- K+ j
Analysis of correlation, 相关分析/ D& p4 z( Q0 y8 K
Analysis of covariance, 协方差分析
8 _4 w' D4 l# i6 b+ @Analysis of regression, 回归分析
, g8 y" L" |6 E" T' r0 {Analysis of time series, 时间序列分析
* j& h5 c% v! j) LAnalysis of variance, 方差分析8 l# k0 A: T# J3 `" \7 A
Angular transformation, 角转换
7 y9 W& y1 B! `% a1 P+ aANOVA （analysis of variance）, 方差分析+ Y' a' G" v2 P8 |* L3 x
ANOVA Models, 方差分析模型
7 P, m8 ]9 \5 jArcing, 弧/弧旋
% u& N$ @3 V: }0 \) Z+ K% }Arcsine transformation, 反正弦变换
/ A p4 h N7 d4 U9 K8 uArea under the curve, 曲线面积! V9 m0 j9 Q6 a' [% m' E) S$ ~ C
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 2 l5 @. e% D3 U( @/ Q
ARIMA, 季节和非季节性单变量模型的极大似然估计 + ~' |/ B( b, [
Arithmetic grid paper, 算术格纸; t' _; P9 W. G! c7 X6 z
Arithmetic mean, 算术平均数
3 ?( m( R. V H" D& YArrhenius relation, 艾恩尼斯关系
% u# c; [- W" G! E. o5 @Assessing fit, 拟合的评估9 U0 P+ y7 ]4 W8 C+ ~$ @0 g
Associative laws, 结合律
7 l3 s6 g; \6 x" h9 d: s) oAsymmetric distribution, 非对称分布8 u3 s: Y; s7 v+ G- p% ^8 N6 ^
Asymptotic bias, 渐近偏倚
$ N* [ I# l% |5 m+ A/ Y `0 w5 ~Asymptotic efficiency, 渐近效率
9 r% o% Y; @9 m4 k2 e+ RAsymptotic variance, 渐近方差
! p6 I2 P! J0 |& x# ^Attributable risk, 归因危险度7 u' Q4 z8 Z+ v V' ~9 i# o7 q
Attribute data, 属性资料
& c1 ~" F1 {' C0 hAttribution, 属性& N) F# {7 D& [9 O
Autocorrelation, 自相关
% T( C n. z- }' `0 j/ {Autocorrelation of residuals, 残差的自相关. Q% K( i" a4 ]1 B/ M
Average, 平均数
( E& B2 T7 y1 E) M; v/ gAverage confidence interval length, 平均置信区间长度
1 u* O$ D0 E4 O8 h, _' ?& ]2 WAverage growth rate, 平均增长率
) ]3 |. ~* ?3 x1 F+ NBar chart, 条形图6 r) M4 f6 r- K% c, D
Bar graph, 条形图& o( Q( Q( M, }: z( Q
Base period, 基期
% Q+ U# j# N% ~2 C" ABayes' theorem , Bayes定理( D7 l8 O/ `+ }8 P5 c3 E( r1 K
Bell-shaped curve, 钟形曲线/ m1 J y/ A- f. x: M
Bernoulli distribution, 伯努力分布9 I1 s5 `1 F# u* v: s
Best-trim estimator, 最好切尾估计量5 c" ]- v& c( d+ ^# {
Bias, 偏性
6 J- q9 b# F. K# BBinary logistic regression, 二元逻辑斯蒂回归 c% w- a! Q3 q+ C8 v' r
Binomial distribution, 二项分布4 m* A" w- s, w$ u+ ?; c/ D
Bisquare, 双平方
* E2 v& ?+ S9 n" m- PBivariate Correlate, 二变量相关
! J( r9 b- s- wBivariate normal distribution, 双变量正态分布6 \1 b1 N, o0 g7 m5 e9 o
Bivariate normal population, 双变量正态总体$ ?: h( m K* Z' A
Biweight interval, 双权区间
4 E @! c1 U8 |% n2 j4 ZBiweight M-estimator, 双权M估计量
2 N1 l: v+ R/ g4 q( ZBlock, 区组/配伍组. }6 l6 V" K- u- V3 b6 i
BMDP(Biomedical computer programs), BMDP统计软件包
, L; f% h& Z6 U3 @7 RBoxplots, 箱线图/箱尾图2 ~/ u/ k( U) @, w& J
Breakdown bound, 崩溃界/崩溃点
$ @9 M! c( o! z( s+ Q; y. F; D( i& KCanonical correlation, 典型相关
5 t# b- v( `- [) K% d# M6 _Caption, 纵标目
6 D4 K4 W+ J( NCase-control study, 病例对照研究8 [ M8 _9 _/ g
Categorical variable, 分类变量5 N' p6 X3 _" d# [% R$ y$ k' c
Catenary, 悬链线- e3 c# }( i- `% u2 r1 L
Cauchy distribution, 柯西分布+ C# B& z) e& g4 ^, D
Cause-and-effect relationship, 因果关系; b& b# I7 |- h. P
Cell, 单元
2 B+ U3 k0 J% r# v) rCensoring, 终检
g7 B; x4 K1 G# \8 _3 H+ vCenter of symmetry, 对称中心
7 H0 `' U$ }5 w* B+ O3 \1 O3 F% KCentering and scaling, 中心化和定标
! w, ]" E# D# l1 zCentral tendency, 集中趋势
( q) u5 R6 c) X. C Y; _8 U" |& i JCentral value, 中心值
8 Y; }4 L8 |. C8 e) S+ nCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
# R+ i8 U- m. I! HChance, 机遇! o& J' G" N5 s8 B4 r7 D
Chance error, 随机误差
' ~! {2 u6 u+ ^ zChance variable, 随机变量0 K% E) G. u. a% a4 t
Characteristic equation, 特征方程
1 V0 U/ K, X- M, \/ rCharacteristic root, 特征根. a' v) q5 ?( T( g- X8 _
Characteristic vector, 特征向量& _1 {6 z5 M: F+ w
Chebshev criterion of fit, 拟合的切比雪夫准则
6 R8 x# U9 _* e" u5 DChernoff faces, 切尔诺夫脸谱图
5 p, Z, ^# k2 f R9 IChi-square test, 卡方检验/χ2检验9 n) s9 \- S* G9 o
Choleskey decomposition, 乔洛斯基分解
$ R& n. S# a! P; OCircle chart, 圆图
. N. P# s! q+ ?# H. u1 I. LClass interval, 组距) S( F7 z: L. N, ]
Class mid-value, 组中值
: P5 J0 W/ ?7 b; l' l5 _Class upper limit, 组上限
. x" k4 O' N/ q. ~Classified variable, 分类变量7 s0 B) P5 v5 C) Y& o$ h
Cluster analysis, 聚类分析
3 L4 o3 h1 Y0 t5 Y- y$ v, wCluster sampling, 整群抽样4 W; Z) M) a) y: v7 p3 P* S
Code, 代码 C: Q2 D" D6 q7 y
Coded data, 编码数据% ~7 [8 Y" }% d- d6 c8 u
Coding, 编码
* L/ A# g: b1 M* h$ j7 }Coefficient of contingency, 列联系数" q% b5 X2 S2 R- A+ `
Coefficient of determination, 决定系数$ e& }( y7 N. m, Y
Coefficient of multiple correlation, 多重相关系数& a9 q/ a: D' @$ H6 H/ R9 m- ^
Coefficient of partial correlation, 偏相关系数
; {9 O+ n# a$ o8 WCoefficient of production-moment correlation, 积差相关系数
% M$ f. E3 I( S nCoefficient of rank correlation, 等级相关系数
: @5 z4 ~+ s/ W! }Coefficient of regression, 回归系数- o( L0 z) R( I" |4 s
Coefficient of skewness, 偏度系数
2 R$ r1 \+ K) R: v' }1 XCoefficient of variation, 变异系数3 X0 w3 t7 `) ^. P; f3 Y. L
Cohort study, 队列研究
: I7 Z. a0 {% [# h6 B. ]/ JColumn, 列! T! S' J/ y$ s
Column effect, 列效应1 V# C* E( w; L/ g- x7 ?% q( k
Column factor, 列因素
- A% x" |( G% WCombination pool, 合并
8 y+ l3 I! b* i! e. ~" c6 dCombinative table, 组合表
" w9 T! W/ m, fCommon factor, 共性因子) s `& }9 q$ R1 N0 m7 r! B1 z
Common regression coefficient, 公共回归系数
" `6 s6 h2 t( t i6 qCommon value, 共同值1 t$ _; f2 [; A5 v/ `* G* d
Common variance, 公共方差
O0 L: J. |: `, C9 j5 }6 j) fCommon variation, 公共变异
0 t4 s/ P. `% _3 vCommunality variance, 共性方差: `1 e& ^, i/ K: R9 t
Comparability, 可比性
: I6 d, x. x6 }. HComparison of bathes, 批比较
# F( ` T, w9 p6 X$ t0 P8 z3 ZComparison value, 比较值3 C' T* |+ @0 i+ `% l+ [$ f s/ L
Compartment model, 分部模型$ A- k4 O* N; {
Compassion, 伸缩
- i* i/ Q! |! ^5 L4 V; g; B; `Complement of an event, 补事件( a" x; y+ M3 ?- t
Complete association, 完全正相关( a; c7 B) N! z0 R- x
Complete dissociation, 完全不相关
5 J A+ h' G' l6 E6 X4 M& vComplete statistics, 完备统计量
5 X0 v- Z5 V" r: @Completely randomized design, 完全随机化设计
8 z" p! {: U$ n$ i W) fComposite event, 联合事件9 y& `5 X- G" G2 K; q
Composite events, 复合事件
& {6 j& W4 t! J0 O+ DConcavity, 凹性4 v1 X) E( C. u5 C3 `; L
Conditional expectation, 条件期望
- [6 i/ X- I0 r9 T( g! Q9 ?Conditional likelihood, 条件似然 A: D% q( c/ H+ \ ~
Conditional probability, 条件概率
! k- O8 e! J j+ N* s8 U/ r4 PConditionally linear, 依条件线性 H) ?, @/ ~% S9 e
Confidence interval, 置信区间% A0 i9 k8 g9 W" z' y! `0 ?
Confidence limit, 置信限 T. c& t9 u0 t. A
Confidence lower limit, 置信下限
. ]* b: x% b( R" ]. MConfidence upper limit, 置信上限 z# D1 P% b' j- Q* _6 w# _
Confirmatory Factor Analysis , 验证性因子分析
8 J4 h* `( ~3 x0 \8 k+ hConfirmatory research, 证实性实验研究
; e9 `3 I1 y9 ~9 k F" ZConfounding factor, 混杂因素
; e: U- a2 o' R& n% }" rConjoint, 联合分析
( l8 @( D! x+ W" j) n) p3 m& DConsistency, 相合性8 z+ U$ k0 @3 h, P
Consistency check, 一致性检验# h% _4 B( G( ]2 ~8 }& b
Consistent asymptotically normal estimate, 相合渐近正态估计- l/ `' p; O; w: C! ]
Consistent estimate, 相合估计
' a4 L( L" c- R. h7 {/ |Constrained nonlinear regression, 受约束非线性回归
- T/ V3 B4 a& \( W0 S0 k0 Z% m! lConstraint, 约束1 p* q& t1 c4 v4 K0 J
Contaminated distribution, 污染分布
% ~/ E5 s m. \( X6 _Contaminated Gausssian, 污染高斯分布6 U9 [9 A: N; _0 b+ [
Contaminated normal distribution, 污染正态分布
7 n) v h8 B0 J% G2 R ^Contamination, 污染- [3 K/ J# W8 B3 U2 f$ I5 s' g: J
Contamination model, 污染模型0 G3 `' @( h6 h G4 d! ~
Contingency table, 列联表% e" d9 ~9 Z9 Q s: B4 Z
Contour, 边界线
v9 \$ {" B2 m" pContribution rate, 贡献率3 ]3 @6 v5 C8 F" k
Control, 对照) h+ X& g) d* _* h$ t( w+ k
Controlled experiments, 对照实验. m7 t! n+ y6 j4 P/ G
Conventional depth, 常规深度
* Y* V" x& t z0 Q: EConvolution, 卷积4 O% @5 h k! Q5 P- X _: g/ ]$ K, d
Corrected factor, 校正因子
: `+ t; o" d# E! ]; c2 L1 rCorrected mean, 校正均值6 R4 u" G: x$ X, u: a J" O' ]
Correction coefficient, 校正系数
, U9 N, I# H5 S2 z `6 O1 WCorrectness, 正确性, r5 [0 w! D% a& n# G, G9 U
Correlation coefficient, 相关系数
, }7 d5 O. f% e: JCorrelation index, 相关指数7 \ b3 o$ W4 j- b+ U. N! o
Correspondence, 对应
O2 O; v7 E( _6 C4 T7 l% U! eCounting, 计数9 K2 t& v% c, N+ Q
Counts, 计数/频数
$ {9 o3 G- }3 c" {Covariance, 协方差. F/ Y4 T! ^* Z
Covariant, 共变 A8 ]* M5 M2 a2 [' z8 z" Q1 c1 ^
Cox Regression, Cox回归
' P. @- `! `; H8 A3 U, VCriteria for fitting, 拟合准则: p( A3 _ J' c+ K9 A- Z
Criteria of least squares, 最小二乘准则7 p' Q/ p) i3 R- C$ s z
Critical ratio, 临界比
; D) O4 [; g. N; mCritical region, 拒绝域6 O' G$ |( t" X7 U3 V
Critical value, 临界值4 T$ E' z, a* X
Cross-over design, 交叉设计5 {; ^+ a; H' E' F9 x i
Cross-section analysis, 横断面分析. N3 I5 E# }- q0 u, N
Cross-section survey, 横断面调查
6 _2 G0 ^' Z1 bCrosstabs , 交叉表 - `& N+ C0 B! p3 ~& r1 G
Cross-tabulation table, 复合表
2 ^2 r2 G: P4 u# c; M( x6 KCube root, 立方根
7 g5 J# c4 m; c( v/ s6 wCumulative distribution function, 分布函数
9 d: K$ f8 C. G2 |Cumulative probability, 累计概率6 m' P( ]" i, J3 ^5 |: j; l
Curvature, 曲率/弯曲, u" g A1 B9 s* j% w
Curvature, 曲率- |; n/ }4 I0 O1 M/ i8 n3 P$ X$ ?
Curve fit , 曲线拟和 $ X4 F% F9 k" g2 D8 G7 m7 y6 X
Curve fitting, 曲线拟合
. o9 q8 x+ U) i8 }Curvilinear regression, 曲线回归
7 C+ R; n% y% J$ }0 F# NCurvilinear relation, 曲线关系- z' B' ]3 b: g) Z, G, }
Cut-and-try method, 尝试法
8 d$ ]& C* ~0 Q" QCycle, 周期) k' ]8 Y) I: C! P! p0 X2 X
Cyclist, 周期性
5 ~+ h! m( ]: j; {. e% e9 tD test, D检验+ B# D8 d! e1 X/ D! B& ^4 q
Data acquisition, 资料收集
0 @; w: H9 @. J: P d; ZData bank, 数据库! x$ V& X8 c8 J& ]- i
Data capacity, 数据容量
3 ~- T5 y# y+ I6 NData deficiencies, 数据缺乏. r' ~, Q. |0 x+ }
Data handling, 数据处理7 H0 K b+ r' g2 L
Data manipulation, 数据处理
, \1 x3 c1 E2 {9 IData processing, 数据处理
+ g$ `4 o+ Y/ G4 eData reduction, 数据缩减
/ c% N4 X j( a+ X& V, w. KData set, 数据集
/ T) k2 G5 T9 |0 S4 [# UData sources, 数据来源% ^! `; g3 C! b: x& K2 F
Data transformation, 数据变换: e3 }0 Q. E* k, K# b
Data validity, 数据有效性
- X4 [) D" e6 Y( Q8 qData-in, 数据输入
8 \* j) T6 v3 K/ k: e& SData-out, 数据输出# D8 F0 a1 i" m1 D
Dead time, 停滞期
* w, E; T2 y$ [( aDegree of freedom, 自由度2 y% h5 C7 `2 M; L9 a
Degree of precision, 精密度# H- S/ }8 |& l# ^ V) m
Degree of reliability, 可靠性程度8 U% F [8 U U" s
Degression, 递减
' P' W T; `0 _$ O$ L. fDensity function, 密度函数& Q. [$ O* @$ a: }
Density of data points, 数据点的密度
$ g' r9 Z8 c: B# w# PDependent variable, 应变量/依变量/因变量
4 |( k5 w+ k, k8 ]! `3 XDependent variable, 因变量& A- H" l' q" y* I8 J* s5 r) C: l
Depth, 深度% E; M4 E; {* X1 e( w1 v
Derivative matrix, 导数矩阵
: j! ~0 Q' ~/ N8 DDerivative-free methods, 无导数方法
6 V( g3 _( S; q1 n" g( x+ ]8 WDesign, 设计
7 T& b; t; }" |2 m/ @* pDeterminacy, 确定性* x1 r! M( o& R1 K' V, Y
Determinant, 行列式2 o6 m) `; ~9 w! c( `
Determinant, 决定因素5 G: M0 j0 V" g' o, q
Deviation, 离差
) q( V( _0 C& hDeviation from average, 离均差
6 r1 g7 H; v' nDiagnostic plot, 诊断图 r; u# l6 D9 g. c
Dichotomous variable, 二分变量, |8 ]% ~5 h0 f
Differential equation, 微分方程
6 O' }* ~* B9 p* L0 sDirect standardization, 直接标准化法2 ?) D( ]( ?3 g5 K$ _
Discrete variable, 离散型变量
3 _ T. u0 ~9 ]DISCRIMINANT, 判断
3 U& }$ m ]% Y" _. g7 g1 P6 bDiscriminant analysis, 判别分析" u x. V# o) E7 o% `; y; T. i5 U
Discriminant coefficient, 判别系数
* B( [9 A( _3 b; vDiscriminant function, 判别值
/ y$ R: m# n9 ?& N( e0 vDispersion, 散布/分散度
# o# d: b% B; h& w6 VDisproportional, 不成比例的- g4 Z4 ]$ Z$ y$ u, ~- A, p
Disproportionate sub-class numbers, 不成比例次级组含量
6 [9 T& ?: {# z5 b8 kDistribution free, 分布无关性/免分布6 ^2 b1 f/ i5 \ n8 j' Z3 P) N
Distribution shape, 分布形状- [, b6 W' k `+ }
Distribution-free method, 任意分布法
: h1 V( x$ T, q/ TDistributive laws, 分配律
: b8 o5 G" z# v8 I2 G3 g0 g+ mDisturbance, 随机扰动项
. {; x6 W' ^& N8 v: p: E: |Dose response curve, 剂量反应曲线
' F# ]7 E$ z& iDouble blind method, 双盲法
9 J5 H7 r$ a9 |3 ^# `( EDouble blind trial, 双盲试验; E) h G9 E: v& A8 h- a
Double exponential distribution, 双指数分布
4 H7 e( V2 l! K' l) U1 HDouble logarithmic, 双对数) f! }$ s: l0 L' n
Downward rank, 降秩
9 ]1 [ l! I5 J! _ v* uDual-space plot, 对偶空间图
% p1 T9 r$ w- g- G7 _DUD, 无导数方法
! I2 [$ V- n' D8 S, D) ^Duncan's new multiple range method, 新复极差法/Duncan新法6 C3 h( _! K( J, S' o$ u
Effect, 实验效应7 M7 V4 q1 C1 [. {
Eigenvalue, 特征值* T+ p+ c D7 k V* ?. f1 c
Eigenvector, 特征向量
2 Q. k0 k r* T) E" HEllipse, 椭圆% v' U: T" z( P- U: ]
Empirical distribution, 经验分布
* T" e5 }/ a+ `4 z. y- @Empirical probability, 经验概率单位$ p8 \. `. j8 t5 j
Enumeration data, 计数资料7 n s. k, \& d2 Z0 }3 w8 w
Equal sun-class number, 相等次级组含量' q8 k) Y7 h) p+ o' m
Equally likely, 等可能
- ?* M4 b. w# G6 ^6 k# yEquivariance, 同变性; L/ M* t2 M* t+ Q
Error, 误差/错误
! [) Z' \" g* y0 Q* M9 i0 I% e- \Error of estimate, 估计误差
" @& z( z& z6 e% i6 G4 X6 cError type I, 第一类错误" Q8 s( I& c0 Y4 A* r4 j5 e+ c
Error type II, 第二类错误
; ^" g) V$ Y0 H6 L- rEstimand, 被估量
0 I: Z: H% F% h0 {Estimated error mean squares, 估计误差均方
; g) _9 m7 J9 _: SEstimated error sum of squares, 估计误差平方和! E9 a1 E3 B4 O# w3 J' W
Euclidean distance, 欧式距离
# M& i6 U; I- kEvent, 事件
! ^ [! m- ~9 ^" iEvent, 事件
" h/ n( z: o6 F) ?Exceptional data point, 异常数据点
; F' L# C7 O3 _7 A2 H. o6 ?* EExpectation plane, 期望平面0 Z: h, F2 N$ s+ l0 o% k
Expectation surface, 期望曲面2 Q3 c! Y+ n- C9 M/ r/ `
Expected values, 期望值) }, H& |+ p" r# n% Y
Experiment, 实验" P+ s5 h; W a+ E( }
Experimental sampling, 试验抽样
c4 ?9 X3 @7 }: OExperimental unit, 试验单位
5 D+ p& t+ F, V& `, fExplanatory variable, 说明变量4 l) A% `" t, y$ G. l
Exploratory data analysis, 探索性数据分析 S0 g* \/ h r6 P9 ~# M! p# f
Explore Summarize, 探索-摘要* Q1 Q$ y4 f4 l' F7 O0 o
Exponential curve, 指数曲线: O+ q7 N+ Y0 B
Exponential growth, 指数式增长
- J2 _& k, ~' D4 z+ cEXSMOOTH, 指数平滑方法
5 y9 G3 z4 f) C7 O' ~) L& s4 GExtended fit, 扩充拟合
$ q6 S2 M4 |, e8 a. x" ^- NExtra parameter, 附加参数
# Y' y7 \4 G, J9 _9 R, TExtrapolation, 外推法
H$ G+ k6 H" x) dExtreme observation, 末端观测值) I: B- J$ m7 H# p2 R! l2 R
Extremes, 极端值/极值
3 k9 m X7 i M/ e+ p3 ` ]7 OF distribution, F分布
9 O+ n+ P8 T, T' vF test, F检验" R9 ?: x0 \- y" i2 s X1 O/ _
Factor, 因素/因子% O: v! r" ?" u+ b Z! e
Factor analysis, 因子分析
3 p! k2 d0 e, V+ KFactor Analysis, 因子分析- h- ?" o8 k2 f) m/ |5 P0 G
Factor score, 因子得分 5 I5 _( U2 c& v- i( S
Factorial, 阶乘1 x3 [/ N, p' ^ X' E
Factorial design, 析因试验设计' U/ L7 o0 s* w- _. o' W/ u
False negative, 假阴性. {3 r( p6 I( p4 V4 i7 M
False negative error, 假阴性错误% D1 g0 l; e, n! y4 I9 p
Family of distributions, 分布族0 o9 M$ g, T! p& J
Family of estimators, 估计量族' `* b% k1 Z$ _
Fanning, 扇面2 d8 R+ w# w% a _4 [8 Q/ }: ~
Fatality rate, 病死率
" |7 Q F: i3 B- u; p$ X7 F0 HField investigation, 现场调查
0 H! F9 g1 H6 Z' L0 Z3 YField survey, 现场调查
' k; L) r9 b/ Y' Z0 TFinite population, 有限总体/ [6 F# o- e$ n/ e3 W5 g
Finite-sample, 有限样本
9 X3 p6 p: Y, ]' ?First derivative, 一阶导数+ h/ h! Z# O5 f. @
First principal component, 第一主成分6 B" F- O) \3 v( a. Y/ z
First quartile, 第一四分位数
* m' r8 A8 j! ^Fisher information, 费雪信息量6 S: A7 l8 b6 f# M- ]
Fitted value, 拟合值) A7 t! a* t N; m. X
Fitting a curve, 曲线拟合0 T) v( N! B4 t0 @* t1 n, c
Fixed base, 定基
( s& U: G9 K2 E8 W; q' v( wFluctuation, 随机起伏+ p$ t i" c2 p
Forecast, 预测, M/ Z9 @' p) @. x p
Four fold table, 四格表
% a) X, ~$ }: a6 H- vFourth, 四分点# U* a0 i8 G \, M8 K$ h
Fraction blow, 左侧比率
+ T- V9 X& U" H* [" ?9 ?0 mFractional error, 相对误差9 w$ `! _4 I6 u/ S
Frequency, 频率% e7 P' G, m0 C0 p6 v: J5 N% ]
Frequency polygon, 频数多边图
5 n, G1 z( j7 ?Frontier point, 界限点
* N; O7 ~* N O* @3 n7 @1 S, eFunction relationship, 泛函关系
) A% b! u! w- zGamma distribution, 伽玛分布% ?9 j0 d7 b3 m1 u* `/ }8 v
Gauss increment, 高斯增量
" @% G! Z0 M; sGaussian distribution, 高斯分布/正态分布! i/ t4 \5 m* }- ]9 e
Gauss-Newton increment, 高斯-牛顿增量
% c/ e+ W+ n( v4 a* X1 eGeneral census, 全面普查+ S/ `0 V/ q: e8 D
GENLOG (Generalized liner models), 广义线性模型 I1 B. Z3 D& X8 ^0 K0 U
Geometric mean, 几何平均数7 t; X8 e6 w# o) Y
Gini's mean difference, 基尼均差
) P. N+ O) V# Z% IGLM (General liner models), 一般线性模型 ) I( d5 i* S. j+ N$ ^) x. N
Goodness of fit, 拟和优度/配合度( @- X5 B( t$ Y+ m9 R
Gradient of determinant, 行列式的梯度
6 E- H& B5 x2 }0 ~% UGraeco-Latin square, 希腊拉丁方0 A. U }% E7 r# r: y
Grand mean, 总均值& X1 P( K7 I' R* I2 f' h% Z/ R# H
Gross errors, 重大错误# I8 S/ { v M# O1 F
Gross-error sensitivity, 大错敏感度 h4 j8 t6 q) c0 }
Group averages, 分组平均& H4 s6 _, C: t9 w: t& u
Grouped data, 分组资料# P( O8 E+ M+ E5 w2 i1 r6 c4 v
Guessed mean, 假定平均数
3 Y3 \# U" u2 D- k- t WHalf-life, 半衰期
8 o/ `) G; U& S" ]0 G1 b2 mHampel M-estimators, 汉佩尔M估计量
Q5 C) R: S' ~Happenstance, 偶然事件' i, P7 J/ X {
Harmonic mean, 调和均数0 O7 r/ a0 J( Z# b
Hazard function, 风险均数
8 ]8 S. \: @% I* z8 {7 m$ RHazard rate, 风险率. c, g. A1 [0 u6 S9 L+ F) K& x
Heading, 标目 / k) _# z) {( }! f9 r1 O
Heavy-tailed distribution, 重尾分布
t) H" V) Z) L Z0 ~ {Hessian array, 海森立体阵( w B, m+ q, |" r4 I
Heterogeneity, 不同质( o# @7 V" j9 Y0 R" F8 C' D; y
Heterogeneity of variance, 方差不齐 # X1 Q# D$ W, E0 Q$ B0 F! T/ i6 {
Hierarchical classification, 组内分组/ d2 b9 O9 s0 K* t6 i/ d O2 ~1 S
Hierarchical clustering method, 系统聚类法# k' c" v& W y: l i$ ~
High-leverage point, 高杠杆率点5 C/ [: k0 Y& N; `9 t- q K
HILOGLINEAR, 多维列联表的层次对数线性模型2 {, [# ^' h- S$ P% k
Hinge, 折叶点
$ v2 z# E3 H6 p8 X' @2 ZHistogram, 直方图: [" W4 I- h0 x& {1 Z
Historical cohort study, 历史性队列研究
: p3 `; J' x% p4 D2 CHoles, 空洞0 C" R. p0 z6 w6 Z, J
HOMALS, 多重响应分析# K% T3 X, C2 |6 x2 Z
Homogeneity of variance, 方差齐性4 Z O/ l) P' V! s& Z: ^
Homogeneity test, 齐性检验9 C- A: g& m9 H) N
Huber M-estimators, 休伯M估计量. a% f; w: T( U1 P, l E
Hyperbola, 双曲线
9 l2 o) s6 R( q8 MHypothesis testing, 假设检验
8 c' x- P/ H) R) ^0 |Hypothetical universe, 假设总体- A' N. W! M9 @; N: G
Impossible event, 不可能事件
3 l, K* q N8 ?) }9 CIndependence, 独立性. \- e. q0 E! j9 O% ]
Independent variable, 自变量
& Z- Y8 d$ ]% o5 a* T4 n* lIndex, 指标/指数
% W+ n1 J2 D4 Y L+ e: ?Indirect standardization, 间接标准化法
- N; P/ L. d, D) a: l+ }Individual, 个体
9 x& J5 s9 W6 z8 s6 f& y) i: WInference band, 推断带6 _$ Q% G( d0 R2 ]2 ]$ b
Infinite population, 无限总体
7 ?8 E8 q" r2 U) U1 C$ g# u! yInfinitely great, 无穷大* m- F5 p! E/ U* f8 @1 c& z
Infinitely small, 无穷小
! g) x! H3 D5 C3 V1 e; W3 K/ fInfluence curve, 影响曲线# ^- s+ i9 k Q+ U* r
Information capacity, 信息容量) ]* ~3 c( v. i5 l8 ]
Initial condition, 初始条件' }! ^+ v& s7 s5 {/ N( Z: |
Initial estimate, 初始估计值
+ _8 @7 @$ V3 MInitial level, 最初水平
7 Y* v1 |% B6 U, y) I" iInteraction, 交互作用
4 ~" j \& X- w% v6 ^3 ?6 qInteraction terms, 交互作用项
) x7 h4 h. y9 h4 W" h0 @" pIntercept, 截距
+ z) h; V2 h+ U! f+ q& W& HInterpolation, 内插法% n0 k- E8 T$ C, ^$ \
Interquartile range, 四分位距% ~. F! g6 C& o: h* N
Interval estimation, 区间估计
" Q) F. q) p ~% K: VIntervals of equal probability, 等概率区间
* ]( l/ _* |3 T+ ^: q2 f U2 M' jIntrinsic curvature, 固有曲率( y3 \, k7 G; m. n+ a# N
Invariance, 不变性# }8 @1 W4 H9 u d
Inverse matrix, 逆矩阵) H( y0 h. n- N, L4 P9 N
Inverse probability, 逆概率
2 J: M# j; o' Q8 r' R7 CInverse sine transformation, 反正弦变换' T! G- n4 _' C4 O
Iteration, 迭代 3 ^' m2 l& i# g5 p. L! ?
Jacobian determinant, 雅可比行列式
8 x" ]1 u5 | z ~Joint distribution function, 分布函数. x3 b4 z$ E; h
Joint probability, 联合概率4 p& c' s W' {5 o+ g
Joint probability distribution, 联合概率分布4 }6 K+ D* ~# g# N2 J1 w
K means method, 逐步聚类法9 N; o# ] s( Q. ] g! G) r
Kaplan-Meier, 评估事件的时间长度
1 y. g% S8 _* W c& u! I+ N3 wKaplan-Merier chart, Kaplan-Merier图8 u/ u& G0 h* c/ x3 I# l5 K
Kendall's rank correlation, Kendall等级相关
8 K" z; T7 T3 ]' y9 a A' UKinetic, 动力学1 H% `* b$ Z1 F
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
! `1 ]4 E5 D, Y# vKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验4 G0 y8 b6 t0 l0 ^# n
Kurtosis, 峰度$ b* o0 q, ]) l( d
Lack of fit, 失拟 s# G3 z% o' K& l
Ladder of powers, 幂阶梯
2 d( W. ]0 k7 ~) rLag, 滞后
& }' c! t9 a. S0 dLarge sample, 大样本# s9 w- S) o8 @: k% g
Large sample test, 大样本检验
. ^1 I$ T- w+ D3 y3 X2 T7 gLatin square, 拉丁方
" K5 p9 J1 Y& B8 _1 S) F! b) XLatin square design, 拉丁方设计 w/ [6 C6 @, V* D& h- y
Leakage, 泄漏
6 o* g& s- G$ a) iLeast favorable configuration, 最不利构形, _% o0 Q2 R( W/ \7 x# x
Least favorable distribution, 最不利分布
2 U" z, | O" k; R$ O- o/ zLeast significant difference, 最小显著差法9 \+ e4 o1 ^9 o+ v6 [
Least square method, 最小二乘法
* i7 S( \. Z9 y* } I, l6 o# DLeast-absolute-residuals estimates, 最小绝对残差估计9 \6 |: n# v8 f" J) a
Least-absolute-residuals fit, 最小绝对残差拟合
! y7 D6 y+ L' ^' bLeast-absolute-residuals line, 最小绝对残差线
+ h I: E k+ Q* s0 }Legend, 图例
4 [# M O8 \3 `( W9 F+ D! BL-estimator, L估计量
1 R" u7 ]1 @0 P8 j$ \9 lL-estimator of location, 位置L估计量
% U8 Y; c! [" W4 P2 v3 v5 P! H, }% KL-estimator of scale, 尺度L估计量
! P9 U8 s9 R4 Z0 {# ?Level, 水平
% L" Q3 Q. L1 W" SLife expectance, 预期期望寿命) D: l' [3 J* Z1 J) l% B+ q
Life table, 寿命表3 ?/ L4 z0 I: y6 i. q/ n1 c9 y; f( K: X
Life table method, 生命表法
6 j' w4 f( X$ S4 A. \Light-tailed distribution, 轻尾分布+ y( f P1 `0 E+ v8 `$ y# [
Likelihood function, 似然函数
2 C. o3 O4 Y; S. qLikelihood ratio, 似然比; [4 a d5 T, S- Q7 d
line graph, 线图
$ w. h' _# N i. JLinear correlation, 直线相关* z# U) {& u3 E0 A) u/ A
Linear equation, 线性方程& Q& r8 e2 w5 C! k7 S, z# H
Linear programming, 线性规划
# e. f, f, f/ yLinear regression, 直线回归
. D$ E: ^4 p }% @Linear Regression, 线性回归& ~5 i0 N' M0 k
Linear trend, 线性趋势2 i5 ]; M% n1 J, x# W* t
Loading, 载荷
) r+ O3 e3 k- TLocation and scale equivariance, 位置尺度同变性
7 ~/ {, @: a( G. v$ J0 v' JLocation equivariance, 位置同变性
6 _. Z1 T$ q- t/ j2 e: pLocation invariance, 位置不变性+ X6 a. K! u* }4 c
Location scale family, 位置尺度族
- s* S8 I2 y3 ?5 aLog rank test, 时序检验
1 r s. `/ T' o# ?3 OLogarithmic curve, 对数曲线
) P/ E! k0 z* H% V+ G, U4 @3 gLogarithmic normal distribution, 对数正态分布
( l7 }) J9 d" s& y& nLogarithmic scale, 对数尺度3 V+ t& H) z) R" d9 k
Logarithmic transformation, 对数变换
* S, f$ g3 S. q2 g' A9 y' S& }1 FLogic check, 逻辑检查" V# H6 F2 e" }
Logistic distribution, 逻辑斯特分布0 @4 z. L% P: Y# R
Logit transformation, Logit转换6 K' Q( C8 H( G7 L) e
LOGLINEAR, 多维列联表通用模型 * M0 P5 F; u4 X% s7 h
Lognormal distribution, 对数正态分布- ?' o g1 B9 q8 ^
Lost function, 损失函数
* M1 L+ u7 H% `! a6 R) H! d" i [Low correlation, 低度相关/ H; _4 @+ M" @$ T
Lower limit, 下限0 [/ M4 g/ w V
Lowest-attained variance, 最小可达方差
7 |; L* R U+ _0 I+ P GLSD, 最小显著差法的简称
+ a, q. c) m3 YLurking variable, 潜在变量
4 h! {5 J- a' y" Y. gMain effect, 主效应- c0 x* Y4 T' C* l1 F! g1 m
Major heading, 主辞标目8 C5 h! X5 l h4 \ ^) g, L% ^
Marginal density function, 边缘密度函数
' E3 W7 I4 C U# u- M; I) j% @Marginal probability, 边缘概率
( ^6 u! a! P% z# ~- D! `. k* t. NMarginal probability distribution, 边缘概率分布# ^1 M: s ]& G
Matched data, 配对资料/ {5 U/ i0 d; y5 n
Matched distribution, 匹配过分布+ h5 z' U. W+ ~! N% B1 I: L0 s ^
Matching of distribution, 分布的匹配* g7 v0 l) n" p# I1 l: j
Matching of transformation, 变换的匹配7 I5 G9 {- j" t( @; g. f
Mathematical expectation, 数学期望
- W, h7 w1 V" U% y: T" iMathematical model, 数学模型
& h& \4 P' z0 _- UMaximum L-estimator, 极大极小L 估计量+ F2 @) o9 X* X( |7 J5 q/ Y! ?
Maximum likelihood method, 最大似然法! w2 \& a5 Q/ v' C/ i
Mean, 均数% J7 I9 i- E9 v2 X2 a( Q* C6 A) ?
Mean squares between groups, 组间均方
$ X" X% W3 q5 KMean squares within group, 组内均方
# ^' J# a y0 c. R7 m# G' LMeans (Compare means), 均值-均值比较2 O0 u( ?! G- e* Y
Median, 中位数 z! B" T, C! o6 q! I U% w
Median effective dose, 半数效量) {4 i& d3 T' C# s( X+ u
Median lethal dose, 半数致死量
1 E2 l6 @! c1 d) g* [* AMedian polish, 中位数平滑* P+ h/ v8 C; ?' O. i
Median test, 中位数检验. w- ` }( C9 U% y3 X: h4 J0 t
Minimal sufficient statistic, 最小充分统计量
- T" C! C- O: P/ ^3 JMinimum distance estimation, 最小距离估计2 a3 T# x% t" u( u2 R" `) W
Minimum effective dose, 最小有效量3 H( m2 F1 h! t. C. ?/ l! a
Minimum lethal dose, 最小致死量; \) p% b! x( T- n
Minimum variance estimator, 最小方差估计量9 e* Z: Q, k8 q/ w; Y S
MINITAB, 统计软件包
8 q+ b% [& ^+ ^- ]) jMinor heading, 宾词标目& B1 ]/ F) q9 T$ ^5 x* q$ [& A) k
Missing data, 缺失值. z* V8 M+ q+ [
Model specification, 模型的确定
6 F2 @4 j. H8 j* O9 ~" B* [Modeling Statistics , 模型统计) V6 z9 U; B7 b2 g, Y r: X# `
Models for outliers, 离群值模型8 f0 Y W0 L( ]4 y* h' }3 o
Modifying the model, 模型的修正/ w7 S6 @# T( `1 ~
Modulus of continuity, 连续性模: X3 h- @1 Q% z* ~& ~
Morbidity, 发病率 8 q- q& Q% M* R7 R
Most favorable configuration, 最有利构形
3 Q: E8 j% D/ p9 G$ W( kMultidimensional Scaling (ASCAL), 多维尺度/多维标度4 n: s8 ^ H5 K" v$ L" S y5 T
Multinomial Logistic Regression , 多项逻辑斯蒂回归. U- L, C a" o6 d* a
Multiple comparison, 多重比较
0 E R' [4 z5 ^( B% r4 \+ xMultiple correlation , 复相关
( Q- {# e/ M$ Q4 F* E. Q, \( X2 DMultiple covariance, 多元协方差
+ d+ j" c2 s2 Z; a; _Multiple linear regression, 多元线性回归7 R# s+ F" E6 p/ {; w, @3 `
Multiple response , 多重选项* q+ ^9 s/ T+ d4 g
Multiple solutions, 多解
Y; C' U- h$ D2 K" IMultiplication theorem, 乘法定理8 r9 p" h; _1 J
Multiresponse, 多元响应
2 t" t4 K6 h7 u% _Multi-stage sampling, 多阶段抽样
% R% L( ~/ Y8 C/ x- BMultivariate T distribution, 多元T分布
. n. T! N2 M5 Z6 J/ D; J3 nMutual exclusive, 互不相容* |9 O! N& t' u. H
Mutual independence, 互相独立3 [# H' A8 p5 j$ t! n1 `
Natural boundary, 自然边界4 U2 ^' j, l3 M3 I: S3 g
Natural dead, 自然死亡
i0 y' ?7 |% H) t( z0 iNatural zero, 自然零
1 c& i- z' I m: e- XNegative correlation, 负相关
6 w2 m- L$ U1 A/ q/ c8 BNegative linear correlation, 负线性相关
: Z# c. j; y @6 _7 |# C$ h4 Y6 QNegatively skewed, 负偏
; b$ |2 g: v1 R# p9 O+ CNewman-Keuls method, q检验
2 j+ n8 G1 @8 \NK method, q检验
" U# j" ?( J% T1 g: c0 oNo statistical significance, 无统计意义9 h- C: c8 R0 t+ ]# X# q' X" I5 ~' p$ ?' S
Nominal variable, 名义变量
9 \0 |1 n% p3 e5 r) ^9 e4 O+ QNonconstancy of variability, 变异的非定常性
) z1 T+ S9 R8 ]* MNonlinear regression, 非线性相关
6 v3 n, ~# D7 U1 V& LNonparametric statistics, 非参数统计6 ?" r( [+ i. _1 n
Nonparametric test, 非参数检验+ Y, y2 e% q, N) g" @4 M
Nonparametric tests, 非参数检验
. q$ F4 ?' w8 s# `Normal deviate, 正态离差
& [7 E" e% t0 g- |# E% m8 E" ]Normal distribution, 正态分布6 E8 x* g) `% \2 u
Normal equation, 正规方程组& ]5 u# q- L. V6 L+ U
Normal ranges, 正常范围2 G' l* C& a* q6 d, |# X* v
Normal value, 正常值! L4 F+ z: p3 [) Y; \6 D$ v
Nuisance parameter, 多余参数/讨厌参数
+ g" g9 \* M# P+ D) rNull hypothesis, 无效假设 : Q7 i2 {' m8 ~* H% Y5 i7 n: l/ n
Numerical variable, 数值变量
/ {4 m, c1 Z& u/ \Objective function, 目标函数
H! R6 f3 V X. E8 ^0 hObservation unit, 观察单位
" e& q+ ~& o3 V, n/ cObserved value, 观察值
! |% |) e7 K- _/ a1 Q XOne sided test, 单侧检验, ?/ A* [% D$ I, |: Z2 I
One-way analysis of variance, 单因素方差分析
1 e# X; i1 [; M" k8 w7 C [Oneway ANOVA , 单因素方差分析
& K/ _/ v* Z' H/ E+ C% X/ `Open sequential trial, 开放型序贯设计/ x5 I( V2 Z! [% q
Optrim, 优切尾5 e& ]/ ^, n3 v0 D
Optrim efficiency, 优切尾效率
: O; B& Z2 e' ^9 \8 A' H9 fOrder statistics, 顺序统计量; l: ^1 o, x: n: R
Ordered categories, 有序分类
7 p d+ Y: I& b" A4 l' DOrdinal logistic regression , 序数逻辑斯蒂回归
9 x$ [. g9 a' S6 L }; Y2 V }! l; fOrdinal variable, 有序变量9 z, I9 S" N& Q3 H
Orthogonal basis, 正交基
8 m4 Z3 m5 a" V: JOrthogonal design, 正交试验设计. s$ U! T& @$ \$ ~$ Z! j9 Y
Orthogonality conditions, 正交条件
9 N- `8 P# J4 |2 u" k- ^ORTHOPLAN, 正交设计 - C3 [7 s$ s! U5 {. g; T. K
Outlier cutoffs, 离群值截断点+ R! U! P4 M. s, ^( Z
Outliers, 极端值, F. G, v! v4 @. d& ^3 y& O
OVERALS , 多组变量的非线性正规相关 ; f4 O! L' j4 _: b0 C# K
Overshoot, 迭代过度7 r4 X% k7 C( h$ ?7 x
Paired design, 配对设计
% T- @2 p1 S2 s, f2 ]3 [Paired sample, 配对样本
: u* n- e$ r7 R; TPairwise slopes, 成对斜率' P* U: f& c& z
Parabola, 抛物线# A/ e: B- l' P7 y n$ M2 V
Parallel tests, 平行试验/ `5 G6 ?7 @) C3 v. ~$ y
Parameter, 参数
" ?3 g6 |; m0 d. i. SParametric statistics, 参数统计
- B$ F; z8 W+ eParametric test, 参数检验
, x( Y2 ?* b/ g) EPartial correlation, 偏相关2 `4 a0 g: [3 C
Partial regression, 偏回归
% E7 c% P! U5 Z: k; k8 rPartial sorting, 偏排序
' G. N" a! t" x5 dPartials residuals, 偏残差
- p0 A7 k; U5 uPattern, 模式
7 R- L7 `+ @, Q% Y; O) \- ~9 WPearson curves, 皮尔逊曲线3 P% w# g/ [: M# [6 k: ?
Peeling, 退层
5 a% Z, G3 o7 O& i4 X3 ~Percent bar graph, 百分条形图
y' q/ o# W' @) J5 G1 XPercentage, 百分比
0 e) w$ d# m2 H% o- IPercentile, 百分位数5 Q9 e0 M! I6 } q3 x+ U+ [' [
Percentile curves, 百分位曲线9 F' p% u7 C) |7 o; J
Periodicity, 周期性
9 z8 f) Y% T5 iPermutation, 排列 ]3 Q4 i, A( t/ P/ n
P-estimator, P估计量) ?' ^5 _, K3 a% v* E/ J
Pie graph, 饼图
' p; j6 v: s* rPitman estimator, 皮特曼估计量$ \3 K; c! L4 w* X
Pivot, 枢轴量 c4 n& X! t$ {' |* L" g4 h
Planar, 平坦$ P5 {6 [+ m0 T6 g
Planar assumption, 平面的假设0 d& k. W6 E; g5 R, B
PLANCARDS, 生成试验的计划卡& {# F/ l! s5 ^7 y* U: e
Point estimation, 点估计3 O, q8 e) o) ^8 Z
Poisson distribution, 泊松分布& F1 g4 x# S; g! U
Polishing, 平滑* T' M" S4 S/ H p
Polled standard deviation, 合并标准差
1 E+ }1 x5 |( U RPolled variance, 合并方差9 p, M, E3 ?4 x1 X
Polygon, 多边图
2 H# `7 N0 q) O* e$ \3 YPolynomial, 多项式) X3 X2 ~% k" g" d# O$ N
Polynomial curve, 多项式曲线+ S) U$ ?8 c, [7 F
Population, 总体
4 s( c( K9 {, }+ {- v% P; yPopulation attributable risk, 人群归因危险度
7 w4 W3 s. I5 lPositive correlation, 正相关7 H% H4 G( H* z
Positively skewed, 正偏; G* G% x) a3 k$ R( v3 a. h
Posterior distribution, 后验分布* \. l5 G9 N5 j- E. A
Power of a test, 检验效能
1 P' ^ I: a) _4 Y1 c n4 tPrecision, 精密度5 Z2 T+ ^) Q& G/ ?6 B
Predicted value, 预测值
Z- O" r2 ]9 r% j! `Preliminary analysis, 预备性分析$ D z4 U( ]$ Z4 t- {; R' j
Principal component analysis, 主成分分析
) m2 M8 i/ M |& hPrior distribution, 先验分布: f1 F6 ]6 F7 b
Prior probability, 先验概率
; C7 b) V( K, N( k& G6 Y4 [" gProbabilistic model, 概率模型
7 r$ Y8 f3 h2 f! m6 Rprobability, 概率
' @! Y8 b* Z6 ^0 q$ fProbability density, 概率密度
3 q5 j) O) ~9 [5 q( w+ |' L& gProduct moment, 乘积矩/协方差+ h" j/ w9 A! T! G
Profile trace, 截面迹图8 i( D$ d% [# m, | t' Y
Proportion, 比/构成比
* [4 X1 O% w0 a# cProportion allocation in stratified random sampling, 按比例分层随机抽样5 i) Z$ Q) O" ^/ E7 X- X
Proportionate, 成比例
; Q. y- p \+ Q% L i) |3 p8 c) wProportionate sub-class numbers, 成比例次级组含量) Q. Z" w, t- r& L
Prospective study, 前瞻性调查% ?/ N; x8 |, t2 ?" ~2 U% Q
Proximities, 亲近性
$ t4 ?1 b/ i/ O+ e! H, y6 KPseudo F test, 近似F检验9 y( [* [- [+ m$ m% W! R: i
Pseudo model, 近似模型
' {4 B* U9 I, |2 c/ r# zPseudosigma, 伪标准差( F$ M/ R9 e1 M& h9 m" W
Purposive sampling, 有目的抽样' q# d5 r& }3 d, R( d( [
QR decomposition, QR分解7 f4 _! d5 e* S/ [- h. a, `9 D' x
Quadratic approximation, 二次近似
) V2 |' r4 K2 E& d4 @( zQualitative classification, 属性分类0 [ x/ S9 I( S" Z6 B) p! ^
Qualitative method, 定性方法
$ s* A( W6 X/ @( s! hQuantile-quantile plot, 分位数-分位数图/Q-Q图
/ F1 ? F/ H0 `' ]0 a$ xQuantitative analysis, 定量分析
7 V% x" |3 A4 D. Q' R! g' xQuartile, 四分位数& F; p& \3 L8 `2 Z) G! a) K
Quick Cluster, 快速聚类7 D9 u! ~& h0 S, h% u
Radix sort, 基数排序
$ B3 A9 D: Z7 J( h+ bRandom allocation, 随机化分组
7 H$ t/ v; |5 A( Y0 c7 Y; xRandom blocks design, 随机区组设计! |0 a* U8 E% U8 k
Random event, 随机事件' g6 G/ T3 b# @' F
Randomization, 随机化5 Q r0 Z8 R4 C9 \
Range, 极差/全距$ p9 N8 B2 [2 c( I6 l- D n; ^
Rank correlation, 等级相关
/ B* X5 _: R) ^Rank sum test, 秩和检验
0 G' l1 v! h) |8 I' VRank test, 秩检验7 q% Y+ z W. Y6 `
Ranked data, 等级资料# h$ G6 s' ]9 D4 F1 | u& j3 p
Rate, 比率
7 v+ Q7 L' {& l9 d) M2 U. ?6 R2 I$ cRatio, 比例, T! F0 X O. _% @) h' x3 w
Raw data, 原始资料
4 |( A0 k# w' F; c5 t. bRaw residual, 原始残差
8 X. Q5 [5 i$ Z8 v# k$ `: m: `0 ~Rayleigh's test, 雷氏检验0 N9 U: d, H$ }4 ^$ {: a
Rayleigh's Z, 雷氏Z值
' C3 O8 o7 r" g4 M" ~0 ]. b$ _Reciprocal, 倒数
3 U$ ^( H8 H+ Z! `Reciprocal transformation, 倒数变换
( h! ~4 [5 _1 \Recording, 记录
1 p. n, Z6 r% C, @( `# XRedescending estimators, 回降估计量
/ c, K/ `' c U$ O# A: TReducing dimensions, 降维
7 R: l. w( v4 t2 D7 PRe-expression, 重新表达
' `) H% `- Y5 }0 t$ wReference set, 标准组! U" Q5 }' r" M. S/ f, N
Region of acceptance, 接受域1 x/ O+ y- |$ S% T- U5 e# w4 |
Regression coefficient, 回归系数( x, U& N& h) q, X4 _, @+ K9 I. o
Regression sum of square, 回归平方和9 a2 ^7 v3 K' Y* v
Rejection point, 拒绝点
# ?- P) ]7 p' _9 NRelative dispersion, 相对离散度
/ o7 _' v. Y V5 V- k }/ i `Relative number, 相对数
+ D, \8 G0 ~; nReliability, 可靠性) x! H. X# b6 U' F( L [" s1 U' N
Reparametrization, 重新设置参数
1 Q' d# N. `! Q0 @8 \. |! \, l1 tReplication, 重复
; U0 z2 @( J& T* [3 TReport Summaries, 报告摘要
* e. @7 k8 q* f: X. m* t1 @& GResidual sum of square, 剩余平方和
$ z' z, e0 W3 o- M8 d/ bResistance, 耐抗性
& s3 P4 g1 U( Z+ [$ TResistant line, 耐抗线
& _8 g+ I! m0 U* W+ q. RResistant technique, 耐抗技术
8 ~6 a6 s$ Y2 k4 jR-estimator of location, 位置R估计量* P# i5 p( g& f0 D
R-estimator of scale, 尺度R估计量
3 J7 i6 F5 z7 d7 VRetrospective study, 回顾性调查, i9 F+ d/ R* b t" P
Ridge trace, 岭迹
9 n! r6 T& ^8 I9 u2 }Ridit analysis, Ridit分析( |5 M2 O7 p; t
Rotation, 旋转9 L& |) j/ k1 r& c, ^
Rounding, 舍入+ i& m8 [( Q/ @8 A e+ \& ~
Row, 行0 ~! l: r7 R4 f5 s8 O. y
Row effects, 行效应
" u( U7 o# m3 F! |; G2 i2 K2 dRow factor, 行因素7 t9 Z$ R( M5 N4 r) y, z
RXC table, RXC表/ a& f6 v, f! M" k
Sample, 样本
0 I$ [5 B; Y) YSample regression coefficient, 样本回归系数
' J7 f4 `' P8 B( N6 m0 gSample size, 样本量
% q# o) q4 a, L3 o9 O' X1 WSample standard deviation, 样本标准差
, R( ?7 @' M2 Q" PSampling error, 抽样误差4 Y3 S. P7 t+ `4 W8 h1 W
SAS(Statistical analysis system ), SAS统计软件包: Z* \( p2 u- D, _+ g* {2 T
Scale, 尺度/量表0 g. H; w* \/ |* }% M1 T3 o- \$ U
Scatter diagram, 散点图
. y' f0 M3 t' J& v6 F6 Z, m) ?1 d, ISchematic plot, 示意图/简图# R- G( X# I: N \$ `. o9 ?. B; f
Score test, 计分检验4 G U+ H3 w8 `4 C
Screening, 筛检- R- Z' v/ y$ h+ a6 K) ^
SEASON, 季节分析
; J( S% m9 D) P& k% ySecond derivative, 二阶导数- ]$ q8 {- T+ } _% U8 J' X
Second principal component, 第二主成分% N+ e0 q0 V% ~4 H, O: f. G
SEM (Structural equation modeling), 结构化方程模型 ( r8 C* a+ v( J4 t& B
Semi-logarithmic graph, 半对数图* S3 \% d4 M, K& C2 z/ b
Semi-logarithmic paper, 半对数格纸7 ?8 i9 F1 @( G; @
Sensitivity curve, 敏感度曲线
" ]+ o9 f3 G5 j2 P3 O2 B( [1 f) OSequential analysis, 贯序分析7 X3 e2 B( T& \( a5 w$ a
Sequential data set, 顺序数据集
8 o: {. k* g+ ?; A. USequential design, 贯序设计
) L: i; D1 F4 W( I# l; B5 z4 Q8 o/ W$ c1 X ]Sequential method, 贯序法5 O8 H; k$ w9 P4 ^- P2 V
Sequential test, 贯序检验法
9 N; p* b3 r$ C SSerial tests, 系列试验9 T$ w3 ~$ \3 G, I3 K9 H
Short-cut method, 简捷法
% O5 F% O E0 |- KSigmoid curve, S形曲线
% O0 k" T& ?3 w. XSign function, 正负号函数* X; i ~) j5 A5 |* ]& a
Sign test, 符号检验* i5 F( w# t S% t; m" U2 j
Signed rank, 符号秩; o: b# D+ |! b; ?6 S9 p
Significance test, 显著性检验% R' Z9 z5 ^" H( t: b2 D
Significant figure, 有效数字9 c0 e! g( @+ u: W( I
Simple cluster sampling, 简单整群抽样 I( \$ P! |8 w+ O
Simple correlation, 简单相关; q X x( X4 M
Simple random sampling, 简单随机抽样$ I! G. l& F2 f5 A
Simple regression, 简单回归
+ T5 Q- W& z- `simple table, 简单表
' a5 f+ z- b+ n# W8 ~6 ISine estimator, 正弦估计量" ` g# R4 K" t1 {& p( h
Single-valued estimate, 单值估计
9 s+ A* G4 V2 I, `+ gSingular matrix, 奇异矩阵
. `' N2 w2 ^0 M' Q( V2 S. N4 iSkewed distribution, 偏斜分布! a8 m8 |3 M0 k$ Y
Skewness, 偏度
& ~( g# {/ e! }# _4 V+ z! CSlash distribution, 斜线分布
$ b: F9 L. W) w7 u1 W2 z( ?Slope, 斜率5 D0 ~8 J) ]* D2 u1 D
Smirnov test, 斯米尔诺夫检验
+ H8 ?& A4 j& k8 sSource of variation, 变异来源 L, r5 G" T' I- r/ U
Spearman rank correlation, 斯皮尔曼等级相关5 c" U# c) v* P0 J. j5 j& S
Specific factor, 特殊因子( m4 v) c9 S: z& F5 {2 y
Specific factor variance, 特殊因子方差& k: j; D& y9 d+ m3 T
Spectra , 频谱" {7 e* z0 K5 s" k
Spherical distribution, 球型正态分布8 r y9 W6 }, p: e. [, M) w5 \1 h! _: m {
Spread, 展布
8 h+ ?) J u( ?, LSPSS(Statistical package for the social science), SPSS统计软件包
/ h9 O* p0 h8 x6 `$ CSpurious correlation, 假性相关
& t7 U1 \# B2 g7 K- |6 d1 U0 t; |Square root transformation, 平方根变换
6 @5 {' F0 ?: E0 S. Y; oStabilizing variance, 稳定方差
; C& w9 W0 o$ j& f% g( n( D& \9 dStandard deviation, 标准差" R( e# ]1 V. v9 a4 u* C! s
Standard error, 标准误
. T$ R* C1 n2 z# v( S" SStandard error of difference, 差别的标准误
" c$ ]! R1 p. d r0 x. IStandard error of estimate, 标准估计误差 U2 O/ L, E! C3 E1 x
Standard error of rate, 率的标准误
$ @6 [) y( j& `6 u) E% RStandard normal distribution, 标准正态分布
1 u; W0 {& z* e- kStandardization, 标准化. e( G: P2 O8 ~: ?5 i
Starting value, 起始值
8 e/ {' i& p, T; R5 BStatistic, 统计量3 o W+ \2 j+ R, A2 p, Z
Statistical control, 统计控制
$ y; d+ i; ?( F7 r! B1 c, IStatistical graph, 统计图; [: R: w2 J1 z
Statistical inference, 统计推断+ H& f6 C5 G& ^4 i- H
Statistical table, 统计表
! k* L* y0 N4 K' c! b uSteepest descent, 最速下降法
5 I6 I1 J) {' [+ \" m: h/ `Stem and leaf display, 茎叶图
. M+ j/ Z2 t( I- uStep factor, 步长因子2 }& T4 P+ _6 c8 V) ~. N( h; v) J
Stepwise regression, 逐步回归$ H0 p5 a% N O" [- `& c) T# P
Storage, 存
% c+ `0 }$ E! n; Z8 U/ RStrata, 层（复数）( \) V3 m# j/ @; G. x
Stratified sampling, 分层抽样7 a& M! v6 V$ d# S/ J- ]1 R1 e
Stratified sampling, 分层抽样9 \9 p4 R( D/ J, I
Strength, 强度
0 _$ |( ^) U& }, h8 `( O1 n' GStringency, 严密性7 r- D1 a$ W! r# U4 s) J
Structural relationship, 结构关系
" {) g3 U9 T, K( uStudentized residual, 学生化残差/t化残差
% \ ~6 Y7 `8 I9 W$ U; ESub-class numbers, 次级组含量
( {9 ?1 v4 K, D+ d& O6 lSubdividing, 分割; X8 {, b- Z0 H: J% K( D
Sufficient statistic, 充分统计量
q* B% C9 S) R* l( e: r/ BSum of products, 积和6 M! P0 ~6 E4 l; D1 j J0 P
Sum of squares, 离差平方和. Q9 I/ m8 i/ i
Sum of squares about regression, 回归平方和
5 I! o: E& l/ I0 cSum of squares between groups, 组间平方和, [8 R8 L# |: I$ a+ J
Sum of squares of partial regression, 偏回归平方和+ S: v" o; B' A% t d% \; o
Sure event, 必然事件
! g9 d9 u5 z, D; L: W8 `Survey, 调查, P6 D2 }5 r8 a0 f; b( T V4 W
Survival, 生存分析! F9 p. O& |. [" V; `
Survival rate, 生存率
% u- G/ J, ?/ b" n) c' sSuspended root gram, 悬吊根图
, G* ?' L6 v3 @0 hSymmetry, 对称3 K; |* C7 e' g2 Q; g# p1 ~. j/ C
Systematic error, 系统误差
0 L- Q% x- u* B4 XSystematic sampling, 系统抽样
, f2 _$ M; @5 N1 S' T5 pTags, 标签& m# I4 h) k( Z' p
Tail area, 尾部面积1 |, b% G$ `" [
Tail length, 尾长
) h- C) X: n* s& u# w" ETail weight, 尾重
8 B9 D1 `" `" q+ S* V. J8 ~Tangent line, 切线' Z' F0 G) ~0 V8 X, [
Target distribution, 目标分布
. S8 h; M% v# M% E2 QTaylor series, 泰勒级数$ K2 m/ d) y) k/ i, ^
Tendency of dispersion, 离散趋势' n j i+ l2 Q
Testing of hypotheses, 假设检验
8 R2 y9 j& y) L' b! @6 C! U' sTheoretical frequency, 理论频数' Z* N4 n; D$ Y$ S# Q" c0 K9 j
Time series, 时间序列
! v. b- }6 ?( o$ b3 i: @$ kTolerance interval, 容忍区间
* Z& X1 k x, h; V2 Y( Y& j3 LTolerance lower limit, 容忍下限9 z$ y$ @; y8 n% g6 W& |$ L3 G) l
Tolerance upper limit, 容忍上限
! r" O- |& b3 J: _' d# j- Q/ \9 MTorsion, 扰率
% K2 r, w# b8 v% c8 x6 t2 dTotal sum of square, 总平方和: \0 t/ j& T: I
Total variation, 总变异9 N/ E0 O# f' F0 m& W
Transformation, 转换
2 T% U! X0 v# l, ^6 E' v$ fTreatment, 处理
) N2 M$ S9 b H1 S1 C# v* dTrend, 趋势
! k: y5 q Y/ F+ Y% e0 U1 OTrend of percentage, 百分比趋势- X( k+ o' g/ z y9 p
Trial, 试验5 S9 F- @9 i" D; m! Q
Trial and error method, 试错法3 k9 b3 }8 w8 C/ ?0 o
Tuning constant, 细调常数
: m, y) Z8 O, Z8 u$ T) LTwo sided test, 双向检验
2 z& O }- Q( K5 g- H( yTwo-stage least squares, 二阶最小平方) m# ` d6 q3 Z- K, a! }" ^
Two-stage sampling, 二阶段抽样
6 {7 i2 A! [ [Two-tailed test, 双侧检验5 v' p7 p4 y$ u9 f5 q8 U0 o
Two-way analysis of variance, 双因素方差分析$ Z" N0 N ~ p" E& v8 s
Two-way table, 双向表4 c$ H9 @- z: s0 H9 t% e
Type I error, 一类错误/α错误
4 I8 `& M* Z* J& p$ h* n1 h8 m% `Type II error, 二类错误/β错误
7 g0 b# Z4 Y% J% f! cUMVU, 方差一致最小无偏估计简称) W! s+ I1 y- q2 U% H
Unbiased estimate, 无偏估计' E' F7 p- W" ~3 l9 ~8 y; n: _
Unconstrained nonlinear regression , 无约束非线性回归3 U \$ k; f7 V' Y0 |5 ]
Unequal subclass number, 不等次级组含量
: |* j) z: B4 O, }* @Ungrouped data, 不分组资料0 C/ c2 ]& g2 R& K6 K
Uniform coordinate, 均匀坐标) S# M0 E; s u1 Y% W
Uniform distribution, 均匀分布4 \9 \/ e; ~7 V
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计4 x! u Y3 }/ ?0 I$ h6 {+ K) ^
Unit, 单元1 a) I# s7 ]# b D- J# S! f: b
Unordered categories, 无序分类" h: S3 Z' c+ W, ]4 T k& f$ Y1 @
Upper limit, 上限5 C9 Z6 M! t, }$ a: z8 ?
Upward rank, 升秩% x( I# R" n3 l, i z, w! z+ R
Vague concept, 模糊概念. q% h% s2 X7 W
Validity, 有效性
+ t7 B# z" a/ [5 _VARCOMP (Variance component estimation), 方差元素估计
, S/ y7 G% S* ~; o* T5 }Variability, 变异性
* ~+ F0 r7 ?8 f1 |% }# ~Variable, 变量6 r# D/ M ^2 e% R* ~
Variance, 方差0 J2 B1 y' Q/ x& z3 X
Variation, 变异8 T4 Q, \' y' u- X& C( _ J& `4 D
Varimax orthogonal rotation, 方差最大正交旋转
- d" o- G9 [# K7 G& D1 Q( `Volume of distribution, 容积) R1 u+ v1 f- _# A( F# z/ E7 l
W test, W检验" U. L/ R9 o# Q. F3 P p/ Z1 E
Weibull distribution, 威布尔分布8 y6 |/ x: _! ^7 K2 _2 n/ `
Weight, 权数
' g8 x: \; R# NWeighted Chi-square test, 加权卡方检验/Cochran检验
1 t" ?) p/ J/ l. p$ N3 aWeighted linear regression method, 加权直线回归
y$ p# N2 ^6 ], Q; U* zWeighted mean, 加权平均数$ ]3 T8 d) A& k2 a, M; Q
Weighted mean square, 加权平均方差
# q0 q/ w! t5 Y3 G4 d$ P; a7 {Weighted sum of square, 加权平方和5 l: c% G! b4 X Y' g% e$ A" Z
Weighting coefficient, 权重系数
: @' ]/ ]5 T! e4 t& Q6 VWeighting method, 加权法
# K; _) T- i- P% |3 a3 NW-estimation, W估计量+ k0 j* [$ Z9 G( ?$ q: X5 ]( S
W-estimation of location, 位置W估计量
$ A& \ U4 k( }7 k$ N$ e: EWidth, 宽度
6 ]3 S" `) I1 ]Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验. o- h" z5 O/ i$ D& ]
Wild point, 野点/狂点
4 U( X! W' C: ?; ]" j# bWild value, 野值/狂值
. R* {3 ?& o% p: H/ gWinsorized mean, 缩尾均值
! V' B+ j+ i. @# iWithdraw, 失访 0 `& A/ e. s2 L9 V3 c
Youden's index, 尤登指数
+ _$ j4 C1 V' R& s; P, h$ gZ test, Z检验
' G! D2 M8 t! J$ A) _& DZero correlation, 零相关7 w# j' |& [7 V1 [' h
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
