|
|
Absolute deviation, 绝对离差# m9 n$ _6 J' Y/ K% ^) ?9 I1 ^. t
Absolute number, 绝对数5 t% m2 Q% [; I5 B/ J
Absolute residuals, 绝对残差- w- p. U8 z R
Acceleration array, 加速度立体阵
- k# Y/ t/ u, A6 r) wAcceleration in an arbitrary direction, 任意方向上的加速度
y/ K% l+ ^% [9 s* w n0 _! U4 \Acceleration normal, 法向加速度
j# @* @# S m# P* KAcceleration space dimension, 加速度空间的维数! I0 i9 H5 a% h- P+ V
Acceleration tangential, 切向加速度
8 N- `# Z, p; s) B) iAcceleration vector, 加速度向量
- I* z* {+ b+ `% F: P* V; g1 _, |Acceptable hypothesis, 可接受假设6 H; R6 l/ A( c( j3 h6 p; I
Accumulation, 累积
" t% \ e& [! MAccuracy, 准确度
. O" c3 ?5 d2 Z& t3 SActual frequency, 实际频数+ P6 T3 J- s: I0 E" i
Adaptive estimator, 自适应估计量3 S5 C% y& v2 H9 Z
Addition, 相加# H5 o$ B8 T. R/ i: E6 B
Addition theorem, 加法定理; o0 ^2 z2 B) B" @5 j/ ]. g6 r
Additivity, 可加性
$ k0 q; d1 U; {Adjusted rate, 调整率9 V7 x2 D) x3 v+ V& D
Adjusted value, 校正值
8 {5 U4 m7 s! f0 F- KAdmissible error, 容许误差
2 X2 u3 n; _! @$ u9 ]Aggregation, 聚集性
. b- _' p4 J `3 @/ B q4 C; tAlternative hypothesis, 备择假设2 W# Z; ]/ z9 D( |' w3 M2 ?
Among groups, 组间4 m+ j& l5 r/ A' Z$ O6 j: C, d
Amounts, 总量
) z% x/ t- S D7 m) eAnalysis of correlation, 相关分析' ~' j- e T) J: C
Analysis of covariance, 协方差分析
5 _" Y" E# C7 h H f/ F6 I8 U. ZAnalysis of regression, 回归分析
/ t2 R! z# \6 L# v8 MAnalysis of time series, 时间序列分析
, u, N& W0 n" |* n! E1 AAnalysis of variance, 方差分析. Z8 y8 r5 |3 X
Angular transformation, 角转换
( j3 j; O9 T. n% @" t' Y# b0 uANOVA （analysis of variance）, 方差分析$ K6 U2 Q0 R3 S
ANOVA Models, 方差分析模型, e8 K8 c! F& ^0 L+ b5 Q
Arcing, 弧/弧旋$ U* T; B/ t" H! d1 r
Arcsine transformation, 反正弦变换 G3 |6 ~4 F2 t- }
Area under the curve, 曲线面积% S, }+ H, ?$ [3 l4 f
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 & s+ E8 l% d& A; ]
ARIMA, 季节和非季节性单变量模型的极大似然估计 # C, k L4 z1 K/ K% h% x9 y
Arithmetic grid paper, 算术格纸
6 F3 C6 Z7 p8 KArithmetic mean, 算术平均数
* f0 N, |; n$ g; x) TArrhenius relation, 艾恩尼斯关系: ?2 ?6 q+ Y1 c* v
Assessing fit, 拟合的评估 Q. N) @1 V# p( T5 Q7 _( o
Associative laws, 结合律1 N3 U: J( f, i4 z3 Z( m9 O/ m5 L
Asymmetric distribution, 非对称分布# Y- p4 G' H3 Y( ?6 Y# |( @
Asymptotic bias, 渐近偏倚4 l) G& e& `' o; D) D% W: m. o
Asymptotic efficiency, 渐近效率/ d! M) V4 B/ |7 h3 ^: D
Asymptotic variance, 渐近方差: P$ A0 b: o, Q% y ]5 Q
Attributable risk, 归因危险度
7 K: P3 ^7 [, X+ X/ C: B) bAttribute data, 属性资料
* @: q. f3 G- e( mAttribution, 属性8 P3 [$ Q% r( b# i
Autocorrelation, 自相关+ `8 O D. G" f4 _) `, {$ |
Autocorrelation of residuals, 残差的自相关5 |& \6 n1 D$ C5 K5 j4 U
Average, 平均数+ s7 K' a/ |# B# n, O; G" c
Average confidence interval length, 平均置信区间长度5 M$ \6 q5 q0 {+ L; q% T. u+ B7 I9 X
Average growth rate, 平均增长率
7 k7 s; E& D! L" O- OBar chart, 条形图% n% S* `2 y9 I% @3 l3 ?8 |+ Q3 h2 T
Bar graph, 条形图7 U2 Y+ g7 J5 _/ j7 `
Base period, 基期4 `+ F% D* [ T
Bayes' theorem , Bayes定理4 d6 W# v) i _, k" O
Bell-shaped curve, 钟形曲线) \1 v& ~- ~& B0 ]
Bernoulli distribution, 伯努力分布6 O [) w* O* c' @2 N
Best-trim estimator, 最好切尾估计量
- z& g( I' {; z3 n/ x' ~8 }Bias, 偏性 c) N2 T# B6 c/ S6 z4 _ s3 U
Binary logistic regression, 二元逻辑斯蒂回归% {; [' Z7 C' v6 i0 m- m/ M
Binomial distribution, 二项分布; y) ~& v+ n. T7 ^
Bisquare, 双平方) T/ H/ f3 L- o2 ~( @
Bivariate Correlate, 二变量相关
1 R$ z( s, M* b( [ MBivariate normal distribution, 双变量正态分布* I) t5 [: e, X/ Y& Q X
Bivariate normal population, 双变量正态总体
' r0 l/ H" R) I7 {/ P* N+ IBiweight interval, 双权区间
& B! k) k6 q1 i7 y4 X% e( BBiweight M-estimator, 双权M估计量' Y" s- x) B S: m- R- R {) o
Block, 区组/配伍组
' F9 H( L J0 G5 \BMDP(Biomedical computer programs), BMDP统计软件包: q$ |5 W9 s0 G0 M" R
Boxplots, 箱线图/箱尾图
5 P$ k1 R% f( p1 T% _* |# LBreakdown bound, 崩溃界/崩溃点$ M5 q X" S( ] ]; p5 ^
Canonical correlation, 典型相关
3 P1 k# ?7 r# P. bCaption, 纵标目
3 ?( d3 ^ H0 K5 ~/ p* [ WCase-control study, 病例对照研究
5 D5 M5 Y3 A0 `* b- h% z4 yCategorical variable, 分类变量
- o0 D, E3 j/ O& [Catenary, 悬链线
- z; X2 K% y0 Y# YCauchy distribution, 柯西分布8 c7 Y5 l- e/ t+ D' [+ J- v
Cause-and-effect relationship, 因果关系, {) v, Z2 n. W5 V9 G
Cell, 单元
6 G5 x" ~$ Q% [3 UCensoring, 终检9 D( f- l+ D( Z* W
Center of symmetry, 对称中心9 P! f! T: ^; C0 ^& a5 q8 n
Centering and scaling, 中心化和定标3 {- C$ N5 P. {6 u, ^; G
Central tendency, 集中趋势
: t/ J1 [4 t; p( c7 X- p) W! ICentral value, 中心值
3 d3 T9 @/ N% g; ~' v1 K$ lCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测6 l: K& q& ~! N' o
Chance, 机遇
# }2 W+ s4 q9 h; h2 p, mChance error, 随机误差
) K* a0 _7 Z% x& pChance variable, 随机变量
3 W/ S. U3 o( C; G7 \Characteristic equation, 特征方程
' n% o$ q1 W) O# \4 H1 qCharacteristic root, 特征根
& @& m! Y3 |; wCharacteristic vector, 特征向量
! a$ b9 l/ K( E) X ~7 o, ~7 s kChebshev criterion of fit, 拟合的切比雪夫准则
4 U1 y8 s5 M' q5 HChernoff faces, 切尔诺夫脸谱图
! R2 u0 z7 x8 gChi-square test, 卡方检验/χ2检验
, ^4 [( a3 T7 x% \ jCholeskey decomposition, 乔洛斯基分解; e/ X7 [$ X, ^# `$ W' S
Circle chart, 圆图
- Q) Q* u' e+ JClass interval, 组距+ L5 k1 K1 f1 x: j# a# m. d
Class mid-value, 组中值6 }' ?% B+ M+ Z( Y( |3 o6 G
Class upper limit, 组上限- A- ]# ~' J8 R' H% p3 {0 [
Classified variable, 分类变量
; E* r# w2 d5 T% F# @6 j k) RCluster analysis, 聚类分析
- I1 \; m. W4 x1 u2 ECluster sampling, 整群抽样- u' y& z/ P0 e. c" E1 Q6 v
Code, 代码2 U& o7 q7 E" V: t
Coded data, 编码数据8 j8 e& R: o% x4 @, ~4 e7 Y
Coding, 编码* H; n2 m$ }! T3 p# B
Coefficient of contingency, 列联系数, a7 s4 c+ Y$ m8 {/ m, Z
Coefficient of determination, 决定系数
0 P5 X( O6 ?6 y8 iCoefficient of multiple correlation, 多重相关系数0 j; U' N- _/ u# b" M: c# q$ w
Coefficient of partial correlation, 偏相关系数( b8 a* e' a6 x
Coefficient of production-moment correlation, 积差相关系数* r, u6 Q1 l) M q9 S! `
Coefficient of rank correlation, 等级相关系数
4 F/ b; z: D" ?2 b4 @9 _& |$ @Coefficient of regression, 回归系数
# h, Y' t% G% G2 c( [Coefficient of skewness, 偏度系数6 l1 r Y+ C+ J0 a4 ~2 ~
Coefficient of variation, 变异系数3 I/ X/ X' j+ }6 U
Cohort study, 队列研究2 M5 o& q8 y* V9 R" G* P3 E4 d. k* K
Column, 列7 {/ Y1 N4 }1 P6 S$ s
Column effect, 列效应/ i5 k+ e3 C/ n/ ]4 H; c) V r s
Column factor, 列因素
$ b6 j4 ?! Y; x9 {+ K7 J6 A( DCombination pool, 合并
& ]" y8 T; i" T5 _$ {% ]# eCombinative table, 组合表
7 B$ W [! H; l( oCommon factor, 共性因子
2 e4 r: c0 O/ `; W8 ~Common regression coefficient, 公共回归系数8 }8 | p" e, Q$ ?- i2 |
Common value, 共同值
- W/ {! F3 r+ b2 Q0 R" D- yCommon variance, 公共方差
# |8 N9 i( q1 j' d- ~8 d- UCommon variation, 公共变异
" N0 t8 r! U' FCommunality variance, 共性方差
4 s! q8 u8 o8 J) ^! _Comparability, 可比性
2 s9 A. I9 y9 sComparison of bathes, 批比较
0 @8 ^9 G3 H6 a# LComparison value, 比较值% P. g g1 Z" M) s
Compartment model, 分部模型
& R" y9 n: z2 R! `' Y: e: }. WCompassion, 伸缩5 T. u( l- l4 V' F: w5 }2 J
Complement of an event, 补事件( h; N4 x$ j5 s l
Complete association, 完全正相关+ I9 ], ^/ D* d. q
Complete dissociation, 完全不相关/ k6 G+ W( C' |& _- K5 y. `: G
Complete statistics, 完备统计量6 c5 M: K! e, W' u. I
Completely randomized design, 完全随机化设计/ C# f; v5 y" V8 ^8 `" L. p# O9 w
Composite event, 联合事件/ \& _% z$ C2 L- a' t$ U) q
Composite events, 复合事件4 w1 a* v* w' r. v6 v# x
Concavity, 凹性
- I5 @7 o2 X! }6 ~7 w) @Conditional expectation, 条件期望+ ~* w# X) c' _( ]! h' B/ j
Conditional likelihood, 条件似然
: {3 ?6 ]6 z1 w$ j! G7 lConditional probability, 条件概率
( K& k0 v9 Z5 g6 wConditionally linear, 依条件线性
1 [- U9 |: A% q9 o+ S! qConfidence interval, 置信区间& b8 ]* s9 |' Z
Confidence limit, 置信限
7 q$ R) P: }% t" b9 `; v' }Confidence lower limit, 置信下限# E5 n+ x; K8 e2 b4 ?
Confidence upper limit, 置信上限
b8 ^8 |3 K* ?+ Q$ _: ZConfirmatory Factor Analysis , 验证性因子分析
A8 v( q& N7 PConfirmatory research, 证实性实验研究) P4 s' E3 v, F# T3 c- B; T
Confounding factor, 混杂因素
2 b: f4 A- b. @. nConjoint, 联合分析" D$ f: L }4 H( |) v6 l
Consistency, 相合性; B! ^4 M" r, L3 w3 a/ b3 l, A
Consistency check, 一致性检验3 D$ D: F) o% x5 M! z
Consistent asymptotically normal estimate, 相合渐近正态估计2 z1 F: g% @# g1 A" H/ s
Consistent estimate, 相合估计/ |% P2 f: A4 {" s5 f
Constrained nonlinear regression, 受约束非线性回归
M q" T B1 C0 r, I, N" t% YConstraint, 约束
- C; m, r8 Y4 A7 OContaminated distribution, 污染分布
" p" |8 }1 q( y/ `, F8 F' C8 GContaminated Gausssian, 污染高斯分布: L' B" F0 F. ? f% e3 I
Contaminated normal distribution, 污染正态分布( l3 T" x/ N3 \, G# E- u" x
Contamination, 污染
7 O+ M8 F. Q4 DContamination model, 污染模型4 g7 G; v$ s) G5 V
Contingency table, 列联表
! d1 c& A0 R# n0 AContour, 边界线1 _, y, m1 s8 U s2 Y' W7 E
Contribution rate, 贡献率
; v4 U# g" f+ f6 P S8 r8 {' n6 \" vControl, 对照
' n: F5 a6 o4 mControlled experiments, 对照实验6 a+ |4 e- Z8 ^% M- D- f+ D( J
Conventional depth, 常规深度 z/ j5 a' f5 _# q$ \' a
Convolution, 卷积
2 J& _9 W' u5 w) Q/ aCorrected factor, 校正因子6 j2 {+ e9 u2 F6 {. f
Corrected mean, 校正均值
" T. x( `. \6 r! F% }# BCorrection coefficient, 校正系数& t2 a! u+ p! [& V1 ]1 n+ }8 g
Correctness, 正确性) Q7 C8 Z" |: D6 }* ~% A5 r& A, U F
Correlation coefficient, 相关系数
b, P0 v1 X* T* y7 ICorrelation index, 相关指数. l. U: k4 K) Z4 T
Correspondence, 对应' i9 J+ Z3 n( `# f
Counting, 计数
/ Q0 n* o" E& O2 d5 i2 w, P; VCounts, 计数/频数
8 a7 E, M/ }6 Y A7 wCovariance, 协方差. c2 j7 E1 E& K$ ^
Covariant, 共变 0 o" \* y/ f8 m+ x3 ?3 P
Cox Regression, Cox回归
, Y, [) X! P6 A- F$ Y/ QCriteria for fitting, 拟合准则
; x1 g1 U5 a! [Criteria of least squares, 最小二乘准则/ L: ^2 Q3 i: J( o
Critical ratio, 临界比
, w& h# `- g' U) a5 A OCritical region, 拒绝域4 B( M, z* ?- ^8 K! a
Critical value, 临界值! O9 N5 J, d/ ]2 A4 N* {1 d' L
Cross-over design, 交叉设计7 G( K8 V/ e4 |: w/ w+ u8 V' O7 t
Cross-section analysis, 横断面分析
9 Q: D$ Y, @/ K# y" j. l* V# [4 LCross-section survey, 横断面调查
6 |* K6 A. ?) ~# x+ HCrosstabs , 交叉表 % R2 B; h- q' E$ s) T/ s6 E
Cross-tabulation table, 复合表5 w1 M2 J% @9 l# `8 V. O! ]
Cube root, 立方根
) O L0 A$ }9 l) BCumulative distribution function, 分布函数* p. P& @+ _ ]& x' `
Cumulative probability, 累计概率/ v) \7 [7 U5 {$ V* G' F4 H, u+ e
Curvature, 曲率/弯曲
& c+ p. x3 h- o' O0 L0 M8 ]Curvature, 曲率
9 ?) a4 d" o/ b$ c- P$ H1 k- V# hCurve fit , 曲线拟和 & b, r0 X2 w8 g) L
Curve fitting, 曲线拟合1 t8 f3 h9 T7 i# `* P Q# ?
Curvilinear regression, 曲线回归
- l0 s3 L6 E Q. G" S4 BCurvilinear relation, 曲线关系% h. F% q/ F/ k1 C) }8 C; P. Z: J
Cut-and-try method, 尝试法
* t& n+ u5 u4 n; ^& sCycle, 周期, j5 m: Y2 \4 h* r' Q s
Cyclist, 周期性; i6 w7 Q* |1 O7 U2 L+ Y
D test, D检验
2 I+ J# E6 H* [9 I9 G1 x+ V* p) EData acquisition, 资料收集( M. Q0 ]) \2 b: l5 k& S+ z
Data bank, 数据库: C6 H* n0 [# D
Data capacity, 数据容量6 L' {# @1 Z( G# w5 w
Data deficiencies, 数据缺乏5 [& C+ M6 F( {
Data handling, 数据处理. S/ O! q. }* A2 b- R" P
Data manipulation, 数据处理
5 A ~. }3 x l! c& L D4 G- dData processing, 数据处理7 D& W% p) l, I4 M1 y0 J0 `
Data reduction, 数据缩减8 e2 z/ A6 e# l" n$ J
Data set, 数据集
7 w+ g, g! Z3 z/ j iData sources, 数据来源
5 i. U* y. S& X: H2 ?; d; \7 a% kData transformation, 数据变换+ g) \3 h! h- R* r
Data validity, 数据有效性
% Z* e: s0 G7 @8 B# f2 [Data-in, 数据输入! K( F& N5 W* Y; H) W+ P
Data-out, 数据输出' `! k V" C4 [
Dead time, 停滞期
* C- T& [! y$ u0 \Degree of freedom, 自由度
/ c( D& i, A5 P$ ], Q) qDegree of precision, 精密度+ ~0 T' \: E m4 t
Degree of reliability, 可靠性程度
( }! x2 \% I: `( JDegression, 递减
_) D5 S1 Y jDensity function, 密度函数 ^7 m( V4 h" |, o" S
Density of data points, 数据点的密度0 b0 g# ]0 ?! Z4 d+ \
Dependent variable, 应变量/依变量/因变量( }3 t3 ]' a; k0 e/ r3 Y+ F; D7 L2 |
Dependent variable, 因变量
0 h, {" |' g8 P; r) m1 v5 a' YDepth, 深度) m- H! _' | E# B- ?- U$ F7 L
Derivative matrix, 导数矩阵
; N7 q; h; o& ~- K; FDerivative-free methods, 无导数方法
1 e6 |" C) f7 u, b- J# }Design, 设计
7 @- C& \9 D2 \" L& ?; l, l. uDeterminacy, 确定性
7 d0 T: }" q4 [, ]0 y( sDeterminant, 行列式
$ d# A. W; F% A+ SDeterminant, 决定因素
: i! X$ S- S5 E8 J* }0 tDeviation, 离差
: ?8 S, t; V5 hDeviation from average, 离均差# m: P, i3 D& }" w* s- Y! l) c
Diagnostic plot, 诊断图
" T s8 M; }/ Y1 A, {Dichotomous variable, 二分变量
' `& t! \ q1 dDifferential equation, 微分方程
. Z4 k7 W' q5 {0 S7 U7 S0 gDirect standardization, 直接标准化法% X' _- ]: \: D0 f9 J5 {
Discrete variable, 离散型变量& D# n+ _' _4 m0 ]
DISCRIMINANT, 判断 . x" z& C5 p' I' f: t
Discriminant analysis, 判别分析
/ H4 P# y1 r) A5 R- t" SDiscriminant coefficient, 判别系数 ]" |8 W" P5 P# Z
Discriminant function, 判别值, j! _# A5 R: k% i) C- j9 ?" ]
Dispersion, 散布/分散度
- l- F1 C2 V2 D( HDisproportional, 不成比例的
& [% u& l% X/ ^# M1 |/ g( {* S# GDisproportionate sub-class numbers, 不成比例次级组含量 T( t8 V3 {' E. {5 l
Distribution free, 分布无关性/免分布7 {' Y: F2 ~ O
Distribution shape, 分布形状/ e6 _8 U7 }2 S% O X0 f$ i
Distribution-free method, 任意分布法5 N. U3 M" d! H4 u
Distributive laws, 分配律, w' `3 K) B" |$ u5 Y& |1 B
Disturbance, 随机扰动项
% a+ e0 S# r( b7 C& P3 u! @3 v) `Dose response curve, 剂量反应曲线" Y- ?( ?. u, n1 }
Double blind method, 双盲法+ ~$ s4 u6 b$ o! m/ Y$ T; A
Double blind trial, 双盲试验
* w/ I `2 b0 M. A. K6 [$ aDouble exponential distribution, 双指数分布; Q/ ^0 y* q8 ?. Q. `* _3 }0 z0 ^
Double logarithmic, 双对数, k- B. [! b4 d
Downward rank, 降秩1 G2 r0 f5 X1 R$ J2 q' p
Dual-space plot, 对偶空间图3 r+ w* }2 P5 C+ @
DUD, 无导数方法
. R. P: i5 X* h5 S, kDuncan's new multiple range method, 新复极差法/Duncan新法& k2 F/ U$ z) V! f- l; h4 W7 C7 G
Effect, 实验效应
9 Z8 b" H1 F3 c5 x3 a( {Eigenvalue, 特征值
; h' N1 A" y' c4 k% D, n$ `* MEigenvector, 特征向量+ S' K' j$ W! q8 u3 D# ]2 M
Ellipse, 椭圆! g& E2 c2 u! G' a& \' U
Empirical distribution, 经验分布
* m: S2 ?7 |4 L4 i5 c- QEmpirical probability, 经验概率单位
+ K- O% I! b) {" D! j! ^Enumeration data, 计数资料
5 a2 s: ~0 v9 m$ {Equal sun-class number, 相等次级组含量9 Z s7 R6 n$ V' ?3 ]$ |0 k: o
Equally likely, 等可能1 a" F) T$ G. |8 @
Equivariance, 同变性! `! M. G [/ y+ [0 [
Error, 误差/错误
/ S/ {& G, I, X# fError of estimate, 估计误差( ?# W( c! A* E8 {: n# O: ]
Error type I, 第一类错误2 g6 |1 c! [# A2 i& t- _
Error type II, 第二类错误
7 {, i" D, a6 y) v; i( E" W" OEstimand, 被估量
$ z V* Q9 j6 e; m. XEstimated error mean squares, 估计误差均方
" x3 `5 A6 d6 n; }, L/ W8 K& ?( H/ BEstimated error sum of squares, 估计误差平方和
5 c W) _ V" M3 cEuclidean distance, 欧式距离9 c1 B9 H+ A2 r9 b, k3 N# \: |
Event, 事件
: b3 x$ N2 t2 \( g* j; yEvent, 事件# _7 l, P# [2 z& c9 E
Exceptional data point, 异常数据点0 f# _. e c" k A7 L
Expectation plane, 期望平面
$ A- F1 U& B Q) i* L7 d( jExpectation surface, 期望曲面' j& {) V8 j9 j, O& ? Z! F
Expected values, 期望值
7 m' } Z. j& \1 w% d8 s2 JExperiment, 实验
" p6 F+ `/ [6 B! ?5 i2 e2 o) GExperimental sampling, 试验抽样3 j6 G$ Q6 D% P% t' X
Experimental unit, 试验单位
; v" F& \4 r' S9 N+ ]" o% O2 p7 L: D/ aExplanatory variable, 说明变量
6 T. [+ U& N" Y6 w7 p% CExploratory data analysis, 探索性数据分析
: t+ S- C. u, A9 r& |. cExplore Summarize, 探索-摘要) a9 h( V# l( r, G- j
Exponential curve, 指数曲线
% q$ ~! o% H( N8 S' M O1 A/ }4 vExponential growth, 指数式增长
9 \& }2 N* J. L8 {3 ^EXSMOOTH, 指数平滑方法
7 j0 T. |& C. ZExtended fit, 扩充拟合( h. L8 U' z) @
Extra parameter, 附加参数
7 r( i9 j0 ], f: m" G* iExtrapolation, 外推法" H, l* R4 G- q0 y
Extreme observation, 末端观测值
3 D/ ]9 ? F1 @" o1 L gExtremes, 极端值/极值, F* k) Z& B. w
F distribution, F分布
- v- ^: M. J' M5 V- J3 \F test, F检验4 [ Q7 |, b8 e+ a
Factor, 因素/因子8 p( f5 u1 z0 I+ ~# c% ~2 @
Factor analysis, 因子分析
3 Y4 k. Q$ C8 \3 G( cFactor Analysis, 因子分析% X) _6 ]8 \4 D3 f4 f+ _% y& S: z! L
Factor score, 因子得分
5 [ S: K1 P- v- W! |5 p) sFactorial, 阶乘 T$ [* T/ E4 Z8 d2 n0 f6 L, g
Factorial design, 析因试验设计5 I# S- Z9 K& ]) ?, i2 ^5 I
False negative, 假阴性$ I+ ^" f1 G' [: G' y3 u
False negative error, 假阴性错误
: a5 z; E. F: @3 oFamily of distributions, 分布族$ t& a# P( e/ n( Q# P
Family of estimators, 估计量族& l% p2 e0 s( X1 Y; ~2 t; C) s
Fanning, 扇面
' s4 J8 [ K8 }3 f( bFatality rate, 病死率* ^9 H; Q2 f) f! C
Field investigation, 现场调查* Z# I! {. {& q' c1 O7 @; Z6 m& X
Field survey, 现场调查
1 g8 Q# g. w3 z8 oFinite population, 有限总体
! E/ c8 H2 s G! ?& gFinite-sample, 有限样本
5 ?2 E/ K+ f, j" IFirst derivative, 一阶导数- L% e; D) S1 T0 ]: y1 O
First principal component, 第一主成分* m) O1 j& j- l5 a1 t+ W, M e
First quartile, 第一四分位数7 h- b3 H4 ?, p$ g3 k& y
Fisher information, 费雪信息量
' K" Z2 n* E( U% eFitted value, 拟合值2 E W9 L( n: f! G: S b
Fitting a curve, 曲线拟合
7 g6 k" R/ ]% O m% m. {/ z9 p8 `Fixed base, 定基. r2 G6 [0 F" R) A
Fluctuation, 随机起伏
1 P: l5 l4 v7 n0 n2 `% iForecast, 预测# l8 E; k, B) H5 N& O- a/ q9 e
Four fold table, 四格表
Y* H% x' j) S1 gFourth, 四分点
' V4 y2 x, l, f: hFraction blow, 左侧比率- F! I: \7 N, Q7 N9 Z! t
Fractional error, 相对误差
4 \9 s* u1 X9 o, f9 c, D* mFrequency, 频率
6 ^/ r3 Z- q G YFrequency polygon, 频数多边图
7 B$ Y% M7 H* u1 k$ h4 nFrontier point, 界限点! n B& j+ Y* G% T& z
Function relationship, 泛函关系; r* i; [# G2 T# b
Gamma distribution, 伽玛分布
' ]$ W5 V( [; R* F1 z; k- jGauss increment, 高斯增量
5 `9 ^/ Q& {8 V8 HGaussian distribution, 高斯分布/正态分布
! |1 `5 K: h" O# T. xGauss-Newton increment, 高斯-牛顿增量- g+ m8 @' A# o- l1 N) G
General census, 全面普查
+ h0 `5 Q- N2 k3 {2 `) a4 XGENLOG (Generalized liner models), 广义线性模型
/ p: q% n3 t( ^0 s/ H8 BGeometric mean, 几何平均数" w4 r! [+ h1 ]2 ^
Gini's mean difference, 基尼均差
i& z8 i+ i4 UGLM (General liner models), 一般线性模型 & X+ I! G4 j) C
Goodness of fit, 拟和优度/配合度3 I' D4 o& {* T* T/ E
Gradient of determinant, 行列式的梯度, P9 e. X& H5 p# C
Graeco-Latin square, 希腊拉丁方
+ g4 H; L- o5 C& m7 hGrand mean, 总均值
" B7 U- _1 C, ~; C. G3 k1 u, K vGross errors, 重大错误( Z8 p. ~& u2 n% ?8 B
Gross-error sensitivity, 大错敏感度( ~) Y8 e8 `) K' ?% C7 x
Group averages, 分组平均
& I& u: H5 [) \Grouped data, 分组资料
" @- B) G) X; S: lGuessed mean, 假定平均数9 _" C! K+ ^; C6 w5 [1 ^- y3 x& ~
Half-life, 半衰期
3 H# F2 q( N2 ?6 m5 s, qHampel M-estimators, 汉佩尔M估计量9 X9 x0 |- H6 ^0 q: V, j8 a
Happenstance, 偶然事件
9 ^# o& i2 }& ?1 b6 oHarmonic mean, 调和均数
7 K, F" h: _8 j/ a; i: v4 k1 bHazard function, 风险均数. {$ T+ C$ J$ @ R! `( s* N
Hazard rate, 风险率- ^; S" c+ @7 O
Heading, 标目
6 a7 n: t8 q6 q* n4 k0 }Heavy-tailed distribution, 重尾分布
; \: {* Y4 t$ KHessian array, 海森立体阵; w4 U5 ]; l% e) _8 ^4 a
Heterogeneity, 不同质5 D1 d/ F) Z/ k; U+ i/ Z
Heterogeneity of variance, 方差不齐 7 C, m+ y- ?, @) A
Hierarchical classification, 组内分组
, H6 o) r: \% @6 D; wHierarchical clustering method, 系统聚类法
8 u7 Z3 C+ I9 @1 n7 Y& hHigh-leverage point, 高杠杆率点2 p% s7 S' G9 U& }: P& u8 M
HILOGLINEAR, 多维列联表的层次对数线性模型
: Y# {; Y0 T8 V6 O( I" O8 o+ G2 H5 _Hinge, 折叶点5 [1 R6 Y( \, p9 ~8 S1 m
Histogram, 直方图
$ W/ |& v( C: g: w: H4 S' oHistorical cohort study, 历史性队列研究 6 `/ r$ V- ~- g8 f, C9 {( S# |' g/ F; d
Holes, 空洞6 Z O% G, F0 w- j& _
HOMALS, 多重响应分析
! d( u6 l' O0 u) pHomogeneity of variance, 方差齐性
; n7 }4 c; K, s0 B( fHomogeneity test, 齐性检验' a( v3 g6 m1 \" _1 }
Huber M-estimators, 休伯M估计量
+ \, `! Y n3 f" g* D# Y x. sHyperbola, 双曲线) Y- {* P2 b' \
Hypothesis testing, 假设检验
( B4 d# a+ @7 a' tHypothetical universe, 假设总体
1 I) N I0 n$ z* U3 M" v7 H+ IImpossible event, 不可能事件4 ^/ H' A- s4 B9 K
Independence, 独立性
7 V& V7 h% q5 H6 p$ {9 x1 ]Independent variable, 自变量
+ K* P! S6 l9 l1 ^* h) U& v: [Index, 指标/指数/ Q- r4 {4 L2 a/ z% k* m3 ?
Indirect standardization, 间接标准化法
* U& o4 E2 U5 c V1 }Individual, 个体
! j0 Q( J! H. D/ J% S9 KInference band, 推断带
! w W" H3 [& N, G3 `8 ~; _Infinite population, 无限总体2 C9 J. U$ Y9 X# E7 ?
Infinitely great, 无穷大% [/ J$ F b3 y4 X/ l
Infinitely small, 无穷小
1 c7 N/ q( A; [/ sInfluence curve, 影响曲线8 M* w# `1 v0 B& \ p. R4 j
Information capacity, 信息容量- I7 G9 N B C3 B8 m
Initial condition, 初始条件
+ X: Y- ?4 A) t, R6 BInitial estimate, 初始估计值% r2 i4 o/ B1 u
Initial level, 最初水平
& }4 L A( e: \' @. y) QInteraction, 交互作用4 x+ u, V2 e7 F4 J
Interaction terms, 交互作用项+ S, p2 T, B; o" a" e) E
Intercept, 截距9 r. P/ q4 ~! M, y' \
Interpolation, 内插法' ^; b4 }. K) o V" t2 Y' Y
Interquartile range, 四分位距
; {, ^5 X: y4 r! N% t7 q' Y& ZInterval estimation, 区间估计
- h, m' s4 r3 a: xIntervals of equal probability, 等概率区间
. H; E# T2 F, n% F$ H2 uIntrinsic curvature, 固有曲率
6 I% M/ J; K$ ^* u5 W" {) NInvariance, 不变性
& t7 b8 J { S) c, WInverse matrix, 逆矩阵
" X. Q* } m# t3 YInverse probability, 逆概率; b6 `3 ?( t; |1 S
Inverse sine transformation, 反正弦变换& N! O0 t( V- |7 {! C$ U A, U
Iteration, 迭代 * A! E* u% r6 n3 F7 i" A6 L
Jacobian determinant, 雅可比行列式5 e# q2 S& P4 V2 X+ {0 _4 c2 N
Joint distribution function, 分布函数
" B4 i9 w. y- a0 GJoint probability, 联合概率
/ h) E0 n. V7 V4 N7 j" }; I8 `3 TJoint probability distribution, 联合概率分布
) ], V" o" E; P& R/ ~! dK means method, 逐步聚类法( Y$ v2 A' f/ G! c/ I
Kaplan-Meier, 评估事件的时间长度 $ e H, u4 `0 ^8 u/ `4 ~
Kaplan-Merier chart, Kaplan-Merier图3 r0 ~* q0 U* ~8 }* p w
Kendall's rank correlation, Kendall等级相关
! R& k/ L: ~$ Z# D8 i+ fKinetic, 动力学
4 H3 X$ F5 f' {$ g+ Y3 YKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验8 \8 ~$ @8 v$ d, t- e3 p* O
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
9 J6 P9 C5 r- @+ D3 WKurtosis, 峰度 j! \4 ]# b" {& _. E9 B2 D9 D" |# r
Lack of fit, 失拟9 h! Z( h" S0 i
Ladder of powers, 幂阶梯0 |5 x1 o$ j+ w: X4 u
Lag, 滞后) e: H) [: k* K# Q
Large sample, 大样本1 e! \3 j* w) L1 W4 S+ J3 U: z
Large sample test, 大样本检验
) d% H) @: `* A0 ~" fLatin square, 拉丁方
; E$ w5 g7 d# YLatin square design, 拉丁方设计& C* a; }2 M' Q& }: c- H) u9 N
Leakage, 泄漏0 Q3 l2 T7 g3 p) v: h
Least favorable configuration, 最不利构形/ v6 v9 P/ Q2 H1 H3 a8 {; j/ a i+ C
Least favorable distribution, 最不利分布
2 I' O/ `% [% n6 \Least significant difference, 最小显著差法6 g2 z+ |: c! M; F" Y1 s
Least square method, 最小二乘法& D+ R9 [" m, V! o
Least-absolute-residuals estimates, 最小绝对残差估计4 B9 n0 c6 h: |# H; [! |
Least-absolute-residuals fit, 最小绝对残差拟合: l7 F& D% a8 x- u) Q! n
Least-absolute-residuals line, 最小绝对残差线4 k e1 i6 ?6 r# Y* Y3 y! V
Legend, 图例
- ^! b1 p7 Z+ h4 I8 QL-estimator, L估计量7 h* v! O- K; B' G; ^! Y6 S8 q
L-estimator of location, 位置L估计量
6 H, Z( B. L1 L& R5 KL-estimator of scale, 尺度L估计量
1 n2 g# G( w) w" rLevel, 水平3 b% S, S: L- ^) D) W! t; q
Life expectance, 预期期望寿命- [! H" S" D+ i% i" A; M9 m0 P; l' j6 s
Life table, 寿命表
: a" N. w) Y! U% l) HLife table method, 生命表法0 j, l3 \% ~1 {; Z! b
Light-tailed distribution, 轻尾分布3 I; d9 u* j' D8 A1 R2 i0 I
Likelihood function, 似然函数
- P1 v" m V P1 ]' [Likelihood ratio, 似然比
2 u/ d& H: ^' `; n# W. Qline graph, 线图
, F* B5 F6 E) S: R& X" CLinear correlation, 直线相关0 K3 y4 Y I) X" d/ s. Y
Linear equation, 线性方程
% |" k2 d* ~" v+ n, |Linear programming, 线性规划
7 U$ ?% J+ y+ [/ ?/ d1 r5 f3 SLinear regression, 直线回归
' K0 i1 ? }$ GLinear Regression, 线性回归
4 _- k( {$ a X5 @$ vLinear trend, 线性趋势
* \! @9 V! l' S" lLoading, 载荷
, Z' R) j+ b% i" S" H$ U+ v+ rLocation and scale equivariance, 位置尺度同变性9 j3 D& o4 {4 W( V
Location equivariance, 位置同变性5 Q) z5 v. d" r z! n2 w
Location invariance, 位置不变性
5 k2 c& _ z2 g* |" wLocation scale family, 位置尺度族
" P& ^1 ^, l- l# ELog rank test, 时序检验
$ V" E, w4 t( b2 {# T1 |Logarithmic curve, 对数曲线- e/ ], i; m' R" B
Logarithmic normal distribution, 对数正态分布
" h; Q3 i$ t' t3 D5 E$ BLogarithmic scale, 对数尺度
" A* a/ {6 s& N, `! xLogarithmic transformation, 对数变换
( f/ q9 C4 o' w- m; A* F, {# @Logic check, 逻辑检查* F) m: ] A! ^) G
Logistic distribution, 逻辑斯特分布( h# |! i t2 b- S: I
Logit transformation, Logit转换
6 N2 g' I0 @2 x! ?LOGLINEAR, 多维列联表通用模型
+ E$ ?) e1 V% D' G" DLognormal distribution, 对数正态分布
( r- }. F3 S( C- I/ RLost function, 损失函数
& {& v4 F ~2 }9 h. a! z4 @& T' DLow correlation, 低度相关
& y& R3 |/ Z2 c* FLower limit, 下限6 l) G/ Q1 C0 r$ i( Q" K
Lowest-attained variance, 最小可达方差& [# C6 j% l2 g* [0 C) c0 [8 [
LSD, 最小显著差法的简称" r! H& m" W: Y d* M, A& R9 o+ h
Lurking variable, 潜在变量! r) n: Q/ W+ e% U" ^
Main effect, 主效应
! n U) Z/ g1 qMajor heading, 主辞标目
8 {4 g5 p7 U3 n2 FMarginal density function, 边缘密度函数/ @+ G/ E: ]+ A$ F# ?+ A/ w
Marginal probability, 边缘概率
$ k* Z' g8 b8 I H% z' n* [( zMarginal probability distribution, 边缘概率分布
& o+ x# }& C: W( a! x- }) XMatched data, 配对资料4 T. P6 R- a* M
Matched distribution, 匹配过分布
( l) o& Y* l" u- Y$ i) VMatching of distribution, 分布的匹配
1 h* q3 U. v/ F4 [2 r0 Z, }( a( fMatching of transformation, 变换的匹配
. _1 w# d% b- PMathematical expectation, 数学期望& q. i4 p8 c7 F
Mathematical model, 数学模型' n8 T; F- U# u, [. A4 X6 k
Maximum L-estimator, 极大极小L 估计量
& c% Q8 x# ^; v2 k. X* y7 h# [Maximum likelihood method, 最大似然法* X+ F6 [5 R- f4 l2 R4 }! F
Mean, 均数5 S. a+ s& y- |$ H
Mean squares between groups, 组间均方" c. o% _$ P. }$ S6 T
Mean squares within group, 组内均方
5 m: h X! x* n, a" x* O6 RMeans (Compare means), 均值-均值比较7 O6 Q) z9 l) m
Median, 中位数8 c' M( @5 u' a, e
Median effective dose, 半数效量7 N) x9 s: L/ x
Median lethal dose, 半数致死量
# b g, F7 K: z! ^Median polish, 中位数平滑
8 L. ]; Z9 e/ p% X5 W1 s$ PMedian test, 中位数检验6 l J" `8 U. o7 N+ u7 E
Minimal sufficient statistic, 最小充分统计量$ _/ v' W$ I" U0 R P- d- |
Minimum distance estimation, 最小距离估计
0 W' n' p. X8 {4 N1 p# I! B0 U$ OMinimum effective dose, 最小有效量0 J, C& e" ~8 ]' D N
Minimum lethal dose, 最小致死量
# E. t" X- T! X( z* a' hMinimum variance estimator, 最小方差估计量, x" _# |' e! Y( [5 o4 @
MINITAB, 统计软件包
0 g8 U6 \) B; v$ D* ]% T5 p6 w8 K o7 xMinor heading, 宾词标目8 {; j" I. s# A- N9 [# b
Missing data, 缺失值 M. }7 O! d, m2 e- W4 Y
Model specification, 模型的确定1 e" B. H) F' d% i
Modeling Statistics , 模型统计. B& [7 {9 }6 r: G0 `
Models for outliers, 离群值模型4 S" m, w7 p. Z! s. p$ ^
Modifying the model, 模型的修正* I. Z9 b0 F& F2 @$ C/ a+ R8 E
Modulus of continuity, 连续性模/ d9 y; ?6 N* y8 T; A/ @$ Y) Z6 h! A
Morbidity, 发病率 ! k4 v" f M' w& Q
Most favorable configuration, 最有利构形) N! ]2 k4 f0 c
Multidimensional Scaling (ASCAL), 多维尺度/多维标度( s" p9 v- o4 ], [7 L+ K+ \
Multinomial Logistic Regression , 多项逻辑斯蒂回归0 K4 Y \5 B# f8 G& z
Multiple comparison, 多重比较
; g0 N0 I- @, t" DMultiple correlation , 复相关& V! j( u4 x ^8 Y' A
Multiple covariance, 多元协方差
' K6 |8 p7 a' Z4 u" zMultiple linear regression, 多元线性回归
_: l1 t, O+ W# v2 ^Multiple response , 多重选项: }# I2 Q' v2 N
Multiple solutions, 多解
$ x7 j4 F5 T6 d0 }% F( wMultiplication theorem, 乘法定理 g* ^! D( o/ k, y1 w- e- B' e" p
Multiresponse, 多元响应
" F9 d `3 K2 _! w$ h/ e2 XMulti-stage sampling, 多阶段抽样
3 s& ~# g) M& F5 b( Q3 lMultivariate T distribution, 多元T分布: f- y/ {# Y6 F$ V" l+ n6 J5 Z* `) y
Mutual exclusive, 互不相容" l" |3 Y! _$ E* \$ X( t
Mutual independence, 互相独立
( L$ d9 ~1 Q L/ b- |* A* vNatural boundary, 自然边界; Q. f& a# W' N# [8 N& P" }- T
Natural dead, 自然死亡
* @7 Y, S% s% ?/ B' p. ~Natural zero, 自然零
. P& u1 t0 U! h1 fNegative correlation, 负相关8 l m' k0 Q& Z1 ?& P3 F" m2 X/ ~
Negative linear correlation, 负线性相关$ x/ m4 e3 I# s5 T$ y
Negatively skewed, 负偏
( y; M$ `& U' W* XNewman-Keuls method, q检验0 }* x! J) Z( l) }# @' U
NK method, q检验
0 o7 g' W" x' ^ Z4 o! QNo statistical significance, 无统计意义
9 @+ U0 R0 g. \, Q- {Nominal variable, 名义变量1 c* q8 g+ D b
Nonconstancy of variability, 变异的非定常性
% d3 g! ~; B9 I7 rNonlinear regression, 非线性相关: o' F5 X2 c- A$ c# p
Nonparametric statistics, 非参数统计
* E0 F3 x/ m0 @1 r0 C9 G, S2 J' w- ZNonparametric test, 非参数检验
& Y. Z |6 g/ r7 VNonparametric tests, 非参数检验0 x0 u1 Y) ^# F3 @7 p7 q
Normal deviate, 正态离差+ ^% ^: V! n r) T
Normal distribution, 正态分布
6 k$ P& s1 W) L5 NNormal equation, 正规方程组
* O/ M/ l, w5 Q' KNormal ranges, 正常范围( q$ B5 O5 X+ p* f
Normal value, 正常值, t2 E, y* O' l& N( k) [
Nuisance parameter, 多余参数/讨厌参数
4 p' [' f5 m0 t$ z# \4 k2 N! sNull hypothesis, 无效假设
( n4 H% c& W8 s" ?. ^Numerical variable, 数值变量
! h/ D& V8 p% N# ~4 [8 Q' HObjective function, 目标函数
/ ~$ o2 a( [+ c/ Q( N9 x* RObservation unit, 观察单位
$ }0 ]; o$ H- |" ?Observed value, 观察值" t+ S; }2 K; a$ j4 w
One sided test, 单侧检验5 J1 X1 k( L, Z( P6 t
One-way analysis of variance, 单因素方差分析
5 w' }2 O; o, e- C# qOneway ANOVA , 单因素方差分析9 E/ O/ G: }# R
Open sequential trial, 开放型序贯设计2 H7 N' [' z, g& s5 j& R& X
Optrim, 优切尾: z, {% p- _2 M
Optrim efficiency, 优切尾效率
* D( o1 ] D4 N" oOrder statistics, 顺序统计量* ~6 q% ~5 q9 E- E8 J6 p
Ordered categories, 有序分类
- s$ M9 O, |3 f- N m) B6 ~7 D4 ?5 pOrdinal logistic regression , 序数逻辑斯蒂回归0 |* i8 M! o) u+ F" _2 }+ E
Ordinal variable, 有序变量
5 F2 `* @# Y; b7 K7 `9 \2 y' s" iOrthogonal basis, 正交基
6 v- G& t1 X. N: P1 Y, iOrthogonal design, 正交试验设计6 X: T7 Q' o, u6 X
Orthogonality conditions, 正交条件1 }+ T4 C3 ^/ [% e
ORTHOPLAN, 正交设计
. u9 A# f) U$ y9 IOutlier cutoffs, 离群值截断点
6 _; K) C4 n1 C( hOutliers, 极端值
( K" R) t* y T4 ~$ b2 I7 LOVERALS , 多组变量的非线性正规相关 6 d1 j/ g& I+ A' p: d& A
Overshoot, 迭代过度1 g; B5 Z# T" J! s
Paired design, 配对设计
! ]6 g) n3 ^4 p! W( O( Z" y4 S) UPaired sample, 配对样本. C. D$ n, A2 ^
Pairwise slopes, 成对斜率
F/ S& v# h4 q# ]+ w1 G: LParabola, 抛物线7 E, P. u% x; t/ Q. T
Parallel tests, 平行试验
( b5 ^% s- F' l0 I1 ~9 x- TParameter, 参数
8 f0 C* l) Y _4 P. x5 j" p$ _+ mParametric statistics, 参数统计$ U& O( _; J2 K/ _2 W( f1 u
Parametric test, 参数检验( @8 F/ C, e* f" ]5 C
Partial correlation, 偏相关! p- H7 |0 N8 s9 O# y$ \
Partial regression, 偏回归
, S& X- T( X) O' s; K J5 UPartial sorting, 偏排序3 a. j* d. u5 z
Partials residuals, 偏残差
5 B! x1 z8 k3 H/ NPattern, 模式
: `& {' K/ W1 VPearson curves, 皮尔逊曲线1 x. d2 N$ o( X5 b5 q/ Z# s
Peeling, 退层! u+ Y5 Q8 d; B, M" l
Percent bar graph, 百分条形图( l" O8 @$ Q( r" `3 h, }
Percentage, 百分比
- j6 I) g+ I2 f8 XPercentile, 百分位数
A( p& z6 ?/ S& r2 u0 V5 ?9 O2 tPercentile curves, 百分位曲线
0 w: Z M" B$ z) s1 h( k7 [6 l& ~4 |Periodicity, 周期性
M, a; m n2 W" PPermutation, 排列
4 g% D$ g d E8 ]P-estimator, P估计量4 p* B1 y. u/ A$ p! {& ~+ W7 {: P
Pie graph, 饼图
) U9 O8 \* k4 y: U/ ?Pitman estimator, 皮特曼估计量
, w4 W; v! @! R5 e1 C4 I7 z% `Pivot, 枢轴量6 v9 o% R8 b, @. s
Planar, 平坦
9 A) N+ Y- ~! J1 l/ w1 ^- k" X2 NPlanar assumption, 平面的假设* { U# J" k# ~4 Y$ b7 g
PLANCARDS, 生成试验的计划卡
, d7 m( |/ ^# k3 R( B& rPoint estimation, 点估计
% V* b K& u6 b) f& TPoisson distribution, 泊松分布! _# T1 B# L2 H5 l7 V2 x
Polishing, 平滑# U4 }) ^/ q! s+ P1 ]/ v, ~
Polled standard deviation, 合并标准差5 }0 S( J* @0 U U
Polled variance, 合并方差
, K! [. I9 W5 X% g/ d! y% m2 ?Polygon, 多边图
' Y( i6 J6 g: Y; Q- O& r D( f4 FPolynomial, 多项式: H3 e4 K. O: V
Polynomial curve, 多项式曲线
/ U: K: B( Q5 U' h) j" y( j) o. FPopulation, 总体
) \( n" I1 m, r" F3 ^- A9 vPopulation attributable risk, 人群归因危险度
! h" ^% q2 V0 {1 KPositive correlation, 正相关
) {3 z6 k6 A' ]: u; X; r, M/ F, {Positively skewed, 正偏
; e' }9 h! K& z9 H+ C* W5 I* oPosterior distribution, 后验分布
, ^2 z( }/ u7 I( N8 @) g0 ]9 c+ rPower of a test, 检验效能
/ u4 t+ N; o0 e# sPrecision, 精密度- G# B. M7 s. s
Predicted value, 预测值 w( e6 _; j4 Y
Preliminary analysis, 预备性分析
0 V/ f+ D: m% q/ q' pPrincipal component analysis, 主成分分析- x/ I; `( G4 W2 m+ A' Q
Prior distribution, 先验分布& S6 }8 U: M3 d t1 U" f% n
Prior probability, 先验概率' @4 w. H1 B* p0 j; ?2 [
Probabilistic model, 概率模型
, d! O8 j- ^2 x- d5 u% X# A) Qprobability, 概率
: x5 k' a1 U3 `( T$ IProbability density, 概率密度
6 ?; o5 |" O5 e' m6 f3 z; U# \Product moment, 乘积矩/协方差
( Y3 P, Q- f5 A, ~& Z; AProfile trace, 截面迹图/ J. j, |1 X; e( }
Proportion, 比/构成比
: G( u/ |% O; x, N* FProportion allocation in stratified random sampling, 按比例分层随机抽样. f( j* w5 o1 V% Z+ J3 G- p# Z
Proportionate, 成比例5 B z7 v- c( e$ z- ?) X6 l- ?
Proportionate sub-class numbers, 成比例次级组含量
/ L5 d/ s! q6 U( A8 d, x+ c/ q2 iProspective study, 前瞻性调查1 ]5 V9 |* D8 ]
Proximities, 亲近性
/ H4 j! i/ ]" Q8 t2 B8 |9 m) I+ NPseudo F test, 近似F检验7 I1 h% m' q, R, m
Pseudo model, 近似模型 y" `* n/ p% \% i/ p& m
Pseudosigma, 伪标准差
5 Y$ [6 L o' V, M2 m, X8 \) yPurposive sampling, 有目的抽样2 B: ]; b! }. U$ k
QR decomposition, QR分解) E) `" u F: @( i3 h, z6 h5 E
Quadratic approximation, 二次近似4 ~; U! l3 i# `) J( e* C. T+ b
Qualitative classification, 属性分类
1 `! B, n3 s" AQualitative method, 定性方法: j. ]) a ]5 r0 a
Quantile-quantile plot, 分位数-分位数图/Q-Q图
) h; C3 F: o# j. t4 f& ?' i, u' ]Quantitative analysis, 定量分析0 k% n, g. O' i$ d! i
Quartile, 四分位数3 ?" ?; v, R. O1 Y8 c V: Q9 E
Quick Cluster, 快速聚类
- L, D, ^8 l7 i. l$ v7 \Radix sort, 基数排序
" t- B/ x2 l, v# Y8 MRandom allocation, 随机化分组0 b- j8 [0 Z8 b: n
Random blocks design, 随机区组设计
( e4 C9 c7 J: w$ J- h5 r3 [" VRandom event, 随机事件/ @6 T$ R" n t+ Q1 a
Randomization, 随机化
3 U, j: m" e y: @; V/ aRange, 极差/全距7 R& H; j* W6 p9 O) M: R w# U
Rank correlation, 等级相关
+ {4 _; n) m8 o) T8 jRank sum test, 秩和检验& `0 t6 P( p" {. _( p
Rank test, 秩检验( ^/ U# p w" Q" \* I2 Q+ E
Ranked data, 等级资料
1 G1 `( B( m, e5 bRate, 比率
1 {* n3 U: b8 V% X2 Y: JRatio, 比例
" Y3 N) a6 \: I( ^- J8 MRaw data, 原始资料& R5 K: k8 b, B# S/ V; I
Raw residual, 原始残差! y8 Y3 E3 t! {- E1 O# Y& ?
Rayleigh's test, 雷氏检验
4 G3 Y: i- D2 F# {. y( R" ?0 ?Rayleigh's Z, 雷氏Z值
2 q: L/ l0 K, x, l" rReciprocal, 倒数8 \4 e& F1 y! M2 A
Reciprocal transformation, 倒数变换* v' C/ f& X$ R( ]- l$ ]- b4 P
Recording, 记录
3 x2 u' }# u* w( q5 F i6 ?Redescending estimators, 回降估计量, N- Z. z: ^* z7 }" Q! { z) Z' N
Reducing dimensions, 降维5 g* O: I) K) X; X7 K* G# N$ M
Re-expression, 重新表达1 o* h/ O/ z8 {( T' P
Reference set, 标准组
. F! A8 U5 z# O# ~4 fRegion of acceptance, 接受域* W" B9 x8 J' N* s5 }9 P8 B
Regression coefficient, 回归系数
" j2 k; J* C! G1 M+ WRegression sum of square, 回归平方和" K6 G! o3 c4 R3 H
Rejection point, 拒绝点
6 Z6 t r' f" Y- x5 K5 cRelative dispersion, 相对离散度
M/ M( m y4 b0 Y; JRelative number, 相对数& l6 H6 N1 R9 Z0 Q: ~ r) I
Reliability, 可靠性9 @1 e) X( O/ g9 Q5 K; ^/ e
Reparametrization, 重新设置参数
) `8 Z. K8 X% D8 wReplication, 重复
( ~/ E1 o6 K$ f* o0 vReport Summaries, 报告摘要8 r2 k4 ^" F4 J J6 n" f
Residual sum of square, 剩余平方和
. f# R( |$ K: f$ n' J1 { n BResistance, 耐抗性0 p1 C) x/ g+ U3 y% u6 X, ]
Resistant line, 耐抗线
+ N4 o7 s' i, `! g0 fResistant technique, 耐抗技术
" _/ M; e$ R6 @R-estimator of location, 位置R估计量$ Q/ G4 N2 J* a
R-estimator of scale, 尺度R估计量5 _8 s8 W# u; m; c. w. ]$ Y8 W; R; v P
Retrospective study, 回顾性调查' t& Z0 p) |' q4 Q' a" ^! y6 ]* O
Ridge trace, 岭迹, @3 S: @2 L2 K, Y* q, k( b
Ridit analysis, Ridit分析5 [% {. h% ^9 O/ N
Rotation, 旋转
9 o2 N/ m6 F3 \$ I' Z' GRounding, 舍入5 W3 M9 O6 }% i3 n$ G+ ]! a
Row, 行( \' j3 O3 D9 z V0 D4 ?
Row effects, 行效应- z1 T) X2 c3 t3 U& H
Row factor, 行因素6 c+ P X+ q5 C2 c% U
RXC table, RXC表
+ n" C; \, Q8 D! G/ F- }5 @) P3 XSample, 样本
: `/ Z. k2 d" C2 h2 W0 v$ m3 mSample regression coefficient, 样本回归系数' X% l, k `5 l5 W
Sample size, 样本量$ }& N7 k% m/ E* w7 C
Sample standard deviation, 样本标准差 Z# v, c- X% ]/ O+ P
Sampling error, 抽样误差9 L5 r' S1 Z2 ~1 K3 e. G
SAS(Statistical analysis system ), SAS统计软件包
4 k3 T$ z: I4 B X; e. F* r7 h% BScale, 尺度/量表, v* C9 g* G* D
Scatter diagram, 散点图
9 }9 F: K" B- b1 wSchematic plot, 示意图/简图9 C, t: V% u; T) R, ?
Score test, 计分检验
/ D; ~1 y7 }5 \5 MScreening, 筛检
" v; n2 c# }: ~2 }! nSEASON, 季节分析 ~, X8 v8 m; D% I" H
Second derivative, 二阶导数, }2 j7 D2 @0 J4 z
Second principal component, 第二主成分( z: q/ F( |5 [) X
SEM (Structural equation modeling), 结构化方程模型 6 [( z% K: I9 o4 t3 j
Semi-logarithmic graph, 半对数图1 ^8 E1 j' m: D4 X d# w
Semi-logarithmic paper, 半对数格纸
* W/ {% V- U& L. iSensitivity curve, 敏感度曲线6 J. b0 n( x7 z: l& `( w
Sequential analysis, 贯序分析
4 m! I, n; e1 U% z0 e6 nSequential data set, 顺序数据集
! a- \: y+ j. ]4 b; Z9 LSequential design, 贯序设计, u1 ?, V) ?" N# L: [& ?
Sequential method, 贯序法
$ `5 @( W8 e4 S$ b4 @Sequential test, 贯序检验法- F8 p3 E7 q6 _% C) F* q
Serial tests, 系列试验
; ]9 D$ _8 T& @1 R+ rShort-cut method, 简捷法
) |8 c2 r4 W4 c8 M% i4 TSigmoid curve, S形曲线
0 s% f+ M: D& k6 [! X/ rSign function, 正负号函数
) P/ Z `1 N/ XSign test, 符号检验
$ T$ M3 E [- P& v% nSigned rank, 符号秩, Q1 J( n, b0 f8 s$ ?
Significance test, 显著性检验; U* d5 o4 p0 P: f4 P
Significant figure, 有效数字* W3 m$ x1 T+ I
Simple cluster sampling, 简单整群抽样
, t4 G8 @0 x- U# R8 u" ^Simple correlation, 简单相关# r4 D5 |2 _3 J; V9 Z: A0 |
Simple random sampling, 简单随机抽样5 p2 q3 Y; @: X. Y0 ], o* O: G
Simple regression, 简单回归
( u+ ]! s4 q1 m) }6 s, v- t# Nsimple table, 简单表- i6 \& ~2 ~0 f( P) q
Sine estimator, 正弦估计量
0 h. N z) S' F+ g( G% nSingle-valued estimate, 单值估计2 n3 X1 q8 c9 d! r; b
Singular matrix, 奇异矩阵
8 s+ B% y+ d5 x! N PSkewed distribution, 偏斜分布+ ^) _( x5 q: _! [ u
Skewness, 偏度
0 |/ |6 t% ]2 Q/ j) q" u' W5 uSlash distribution, 斜线分布
4 a- V8 y" E6 M* n% ~Slope, 斜率) O1 {& E0 }4 \" x+ n) H* K. r
Smirnov test, 斯米尔诺夫检验
( ]0 s# \! d1 Y- s& U# eSource of variation, 变异来源. c4 t& f) R9 T) G, e
Spearman rank correlation, 斯皮尔曼等级相关
! J9 a/ e1 V8 ?8 q& B. HSpecific factor, 特殊因子7 ]! V, r4 N3 g; Q
Specific factor variance, 特殊因子方差
3 [7 v) d# B" a/ [7 G! s( fSpectra , 频谱) F1 L* _6 M7 \; m
Spherical distribution, 球型正态分布3 e/ E" a# t. V
Spread, 展布! ]8 u7 J8 V$ l$ C& I( P$ A" {
SPSS(Statistical package for the social science), SPSS统计软件包% H) X* }( C+ i
Spurious correlation, 假性相关
P" G( G ]1 }- N/ ASquare root transformation, 平方根变换
+ h. e& _* B% o' ?. |* H s( G. S% QStabilizing variance, 稳定方差( D n0 i+ y5 n- \ p; [
Standard deviation, 标准差
: `. d j' d. P. E7 Y' oStandard error, 标准误7 a) g$ `- f- Q* g' H! M) i
Standard error of difference, 差别的标准误/ R" L; H/ C+ x9 {" ^; k
Standard error of estimate, 标准估计误差2 f8 I, g) h& @( T, f3 I' D
Standard error of rate, 率的标准误
1 R0 M/ T4 S5 h" ^: fStandard normal distribution, 标准正态分布
+ o/ ^3 y: P1 x+ L6 ]" tStandardization, 标准化
0 M/ n4 E9 W! ?& |- `Starting value, 起始值3 X3 |$ n) }/ J3 ]2 Q3 B
Statistic, 统计量
: b9 A; f9 @7 a7 w2 }5 G* D1 S6 hStatistical control, 统计控制
; D; _" ], f7 p( PStatistical graph, 统计图
" l7 b* f$ B4 y, W& D/ n$ @Statistical inference, 统计推断+ F; r. q D/ G
Statistical table, 统计表+ R. Q( X: A: Q
Steepest descent, 最速下降法
+ G- m9 `8 P$ U2 T9 MStem and leaf display, 茎叶图: j1 n. H3 ^( F$ t
Step factor, 步长因子
- T) Z, }/ ]/ a( @3 s. w9 X) cStepwise regression, 逐步回归
2 f5 V: |$ `+ {( Y. GStorage, 存
. J" k8 A5 g- w1 w$ VStrata, 层（复数）
. e$ k4 _1 s4 [6 R4 Z) I- ^Stratified sampling, 分层抽样
$ L+ q& }( _5 L* y/ tStratified sampling, 分层抽样
; O9 y7 d8 k @Strength, 强度9 D$ i- M+ w3 E+ _ U8 O
Stringency, 严密性
4 ]5 ^# [4 y* D3 b8 ^Structural relationship, 结构关系0 }* ^/ _* r8 o s/ Q
Studentized residual, 学生化残差/t化残差! n% c2 P1 g7 L( ?: H" a
Sub-class numbers, 次级组含量7 n% o! G$ Q+ s( S6 d& a
Subdividing, 分割
6 P7 I) k2 y( F p5 }0 d ZSufficient statistic, 充分统计量4 l8 w( r' U6 {4 {% H' P+ P( y
Sum of products, 积和% L! ^: C3 _ M. T2 H! k8 {) m; \
Sum of squares, 离差平方和
) I4 G/ c+ B; R% \1 f5 }Sum of squares about regression, 回归平方和
$ [; B; m# b. T T, m( ?Sum of squares between groups, 组间平方和8 x8 H- ]0 g3 s7 a% @
Sum of squares of partial regression, 偏回归平方和2 g% K, g$ m& N2 }
Sure event, 必然事件: Y8 ~! a+ h2 R) C/ l
Survey, 调查/ S u' W. ^* U* K
Survival, 生存分析
0 n$ p2 n2 c, V" ?" dSurvival rate, 生存率. u" A! e, B$ \0 q, N
Suspended root gram, 悬吊根图0 ] i5 A$ }" O5 h% ?
Symmetry, 对称1 ?6 t: h) B+ z: B! T2 l3 _
Systematic error, 系统误差
) C. b6 `8 }, [Systematic sampling, 系统抽样
. D8 k4 \# }! \4 CTags, 标签
" B" g6 O8 Q. ^+ J4 m- h8 J" Y" `2 lTail area, 尾部面积
$ J& u0 G; v' n; o' `. v8 KTail length, 尾长' k8 J+ m9 k) a- ?2 Q6 m
Tail weight, 尾重. `' R, z B' Y6 O% K
Tangent line, 切线' C# _, W, T* I' B
Target distribution, 目标分布' W# d1 p# A7 v7 d3 a$ w
Taylor series, 泰勒级数; ]+ L) w% U/ ]# o" b" B9 f
Tendency of dispersion, 离散趋势0 `2 v2 d) s0 g4 O! p! J
Testing of hypotheses, 假设检验3 _5 b3 M) r( r" N$ ^' Q6 Q" l
Theoretical frequency, 理论频数- ]) u& E7 j* j0 Y3 m1 V& D
Time series, 时间序列- j. L3 D0 ?& z W2 k
Tolerance interval, 容忍区间
4 p7 C1 Q" k+ |& i0 K4 BTolerance lower limit, 容忍下限
- s: w4 r5 Z5 s2 U% C" M" eTolerance upper limit, 容忍上限
+ C% Y6 z, M/ Z. e" y) L9 a; k/ eTorsion, 扰率, i# ^) m b3 C) V
Total sum of square, 总平方和
+ U6 N& j4 i! A/ ITotal variation, 总变异& f6 m& r4 _5 H, I3 D; e
Transformation, 转换
: z8 o# j* u7 x/ X: vTreatment, 处理2 V, |/ Z( | k7 Q' ~8 \# k6 I9 _
Trend, 趋势8 L% o; m* b, H9 {4 @+ k, r$ S
Trend of percentage, 百分比趋势
; t/ M8 e/ R$ x6 B4 DTrial, 试验- a$ `4 a P8 h, ~/ Y, _
Trial and error method, 试错法( B. K8 |# b- e9 ~
Tuning constant, 细调常数- R5 P6 r; N1 k. A6 [. [/ o: a8 @
Two sided test, 双向检验& g1 u9 V, s" p( N0 M4 f1 V
Two-stage least squares, 二阶最小平方9 d. X7 r8 ~5 L9 K" X6 x: k- Q
Two-stage sampling, 二阶段抽样
: _; A% E& s) {7 {Two-tailed test, 双侧检验
% J; J6 i! \2 z: Q' ]5 [Two-way analysis of variance, 双因素方差分析; U/ s$ T( j$ o! m# c
Two-way table, 双向表
! ^( f. n' B/ ^9 {5 xType I error, 一类错误/α错误6 d8 T% T1 b6 b7 \
Type II error, 二类错误/β错误* C9 r2 {. K8 y4 `. ?; D
UMVU, 方差一致最小无偏估计简称+ ]) d* b- Z6 o, D1 L& F
Unbiased estimate, 无偏估计" {9 M( I7 ^1 a; B3 i n
Unconstrained nonlinear regression , 无约束非线性回归
" Z K& Z1 |0 D. V6 J0 Z; K }+ lUnequal subclass number, 不等次级组含量. q1 I& R( X" D9 ^& G5 m8 e
Ungrouped data, 不分组资料' k& r) i# r! i& [$ f& e4 y5 {
Uniform coordinate, 均匀坐标
5 b; v# ]" {7 W+ rUniform distribution, 均匀分布
* Q; G" d1 D% P M8 B$ \6 tUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
( U" j2 b2 v& ]' U' qUnit, 单元
6 h4 `: L: v( a) U/ N# ZUnordered categories, 无序分类/ ^8 y J: u% q1 T$ H7 g; K
Upper limit, 上限& q" F# r$ V8 G0 Z
Upward rank, 升秩' o2 u4 D. O$ J! ^8 U
Vague concept, 模糊概念
: O3 W, a- ^9 V1 CValidity, 有效性
4 X' A; ^+ v# f4 M9 q+ ^8 yVARCOMP (Variance component estimation), 方差元素估计7 ~( g: c+ ^/ }4 B
Variability, 变异性- B5 e+ q, ^( E6 _4 p" U+ B
Variable, 变量
- }2 `( T& n5 ~4 J8 n* k) Z, DVariance, 方差
) z0 r* h9 f' M0 CVariation, 变异' ], A- b5 k! k+ |3 @+ d- `: }, g
Varimax orthogonal rotation, 方差最大正交旋转
: _1 Y9 s0 Q, q! M. e# _Volume of distribution, 容积
' X, i* ?* B% bW test, W检验
% j; ~# x4 r! d/ E2 ?. l9 w( YWeibull distribution, 威布尔分布
% k1 O3 @% I6 W9 @Weight, 权数3 g- @0 P5 f) a7 ?/ D) \
Weighted Chi-square test, 加权卡方检验/Cochran检验
- b5 Q7 T" L. w* S+ yWeighted linear regression method, 加权直线回归 `, m5 G a" N% l
Weighted mean, 加权平均数6 A+ W- @& m' H; B, w
Weighted mean square, 加权平均方差9 Z0 x" m4 W) b- ]
Weighted sum of square, 加权平方和1 i! V) f+ u" j, r& Z0 @
Weighting coefficient, 权重系数
7 F0 D! r: l7 c" ^7 pWeighting method, 加权法 # o. |& I) L7 u4 G$ F: k
W-estimation, W估计量
- ~+ k1 I( h2 Q; f- oW-estimation of location, 位置W估计量
% v9 J7 F( p& P6 o6 t* b" QWidth, 宽度
/ B% I! H' j5 t$ T, K) bWilcoxon paired test, 威斯康星配对法/配对符号秩和检验1 ~& s' ]8 G V' E/ n: E
Wild point, 野点/狂点6 [ Z$ l G% }0 m0 ]. W: q
Wild value, 野值/狂值" B+ p4 z* u1 h& y
Winsorized mean, 缩尾均值
, H3 J" K" g( l, DWithdraw, 失访
1 o0 l6 f' D4 G$ A% |Youden's index, 尤登指数) f2 ^' {5 V2 B2 [( @0 q
Z test, Z检验
# [* S3 J" n: D! Z k: I fZero correlation, 零相关& d$ k* s4 E8 L$ a% \8 B
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
