|
|
Absolute deviation, 绝对离差
l ~( q% Q' F9 NAbsolute number, 绝对数
3 E3 @ U' [3 m: z5 y: OAbsolute residuals, 绝对残差
8 A) r1 J- ~) q8 e4 S. cAcceleration array, 加速度立体阵
/ }2 i, {8 q9 Q8 Z K ~1 Z- u7 D. DAcceleration in an arbitrary direction, 任意方向上的加速度
2 ?. H0 b+ F! W' o5 i9 A7 ZAcceleration normal, 法向加速度7 I9 j% N' W s" L% V2 O: r
Acceleration space dimension, 加速度空间的维数; y6 E, I( N9 c+ \
Acceleration tangential, 切向加速度8 j& R) U" e5 i8 O# c0 g, v* U
Acceleration vector, 加速度向量
9 @/ J+ L0 i4 c5 g5 F- zAcceptable hypothesis, 可接受假设. K9 l I' u, M( @/ {
Accumulation, 累积
. A6 V) i% Y4 _3 s/ HAccuracy, 准确度
6 I& z1 n: o: z' \5 o9 P7 N* UActual frequency, 实际频数8 ~7 W) R& Z* S8 w0 l
Adaptive estimator, 自适应估计量
5 @6 M* W+ n/ |. {; ^6 bAddition, 相加" E c0 m, M& u* d- {! l
Addition theorem, 加法定理
" I8 J6 t+ p4 L6 ^" ]8 b2 kAdditivity, 可加性
Y" v) u q: t NAdjusted rate, 调整率
* l6 z- m( P5 n) Z- f9 p k% TAdjusted value, 校正值0 M5 }6 ]" N3 }& b4 |
Admissible error, 容许误差
- s: D. o6 G) y7 S# N ^7 {1 zAggregation, 聚集性
4 G/ [6 a; W ^, l$ [+ D% f8 J- zAlternative hypothesis, 备择假设
7 x: f0 c3 Z% k+ ~7 sAmong groups, 组间& N+ b6 D9 F5 _2 t
Amounts, 总量, d, I# o+ E! `0 M
Analysis of correlation, 相关分析; R4 `1 B& A7 r) }0 T' B K
Analysis of covariance, 协方差分析
" ?9 \ O& F& \3 q, b7 VAnalysis of regression, 回归分析
1 F* A1 H/ J5 ~8 o8 Y2 p- ?' zAnalysis of time series, 时间序列分析 j/ D4 U ]2 b$ g* j( v
Analysis of variance, 方差分析
* `/ {; K: V& K* w5 x o; n! L; W- B' \Angular transformation, 角转换
2 Z% K( A I0 P+ IANOVA (analysis of variance), 方差分析5 @6 {1 z/ F( p, O
ANOVA Models, 方差分析模型3 m5 x" T. H# E9 l
Arcing, 弧/弧旋
( V) X: p0 b# AArcsine transformation, 反正弦变换$ u8 [ p7 s# v) B9 e! F; F
Area under the curve, 曲线面积/ f8 W9 b7 F" }' f% l
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
( l$ T% {/ z, y5 k. c* WARIMA, 季节和非季节性单变量模型的极大似然估计 2 S6 }- U- A( |' t5 w0 G1 e
Arithmetic grid paper, 算术格纸- c. n8 R) U4 s" O3 l
Arithmetic mean, 算术平均数
) t. K! K. b- N" vArrhenius relation, 艾恩尼斯关系
8 G! R" ?2 N0 r) u z1 ^6 ?Assessing fit, 拟合的评估
, m) g: y# v. @6 L) E/ i8 ?Associative laws, 结合律3 S$ Q# O) E. R1 M
Asymmetric distribution, 非对称分布
0 X+ ~( H r, ]) \0 qAsymptotic bias, 渐近偏倚
7 ^) q! W0 E/ H4 X% J3 m$ v- sAsymptotic efficiency, 渐近效率
) R, H; |8 x* i. M% _3 pAsymptotic variance, 渐近方差
9 T, y& }# { X: I! a3 u& a EAttributable risk, 归因危险度$ o; t; Z0 D* z/ G( p
Attribute data, 属性资料
; r" n3 R0 P3 x; _( Y' LAttribution, 属性
& S% `" X- `/ z1 L! L4 H- uAutocorrelation, 自相关) ]% j$ M- Z2 z; U( a, K! M
Autocorrelation of residuals, 残差的自相关
" `& q: c& ^* p5 aAverage, 平均数7 [( t2 k9 ^6 N$ y# q" i0 D
Average confidence interval length, 平均置信区间长度
9 ]1 J0 y: D( @; `+ }Average growth rate, 平均增长率& Y$ w4 X# n9 V% d% f1 l4 i, Q& r
Bar chart, 条形图/ m5 c7 g- ]0 Y Q. I
Bar graph, 条形图( L- o* `& M- \: H" S! I9 J0 c
Base period, 基期
( @3 Z" j% y$ o. T* CBayes' theorem , Bayes定理5 o5 U; @- u8 m
Bell-shaped curve, 钟形曲线7 l' H* p: h8 p& Y, n* i
Bernoulli distribution, 伯努力分布- a& s" c" Y+ I9 k
Best-trim estimator, 最好切尾估计量
! m) Q" y& P$ F5 ]+ P, Y1 m2 aBias, 偏性! V o' }' ]3 s# Q% f8 l. D
Binary logistic regression, 二元逻辑斯蒂回归
g( }$ M( Z1 p6 d/ ZBinomial distribution, 二项分布4 G+ Q- B$ C/ E; V% j! |& o
Bisquare, 双平方
/ m, J) z. a0 t0 x% lBivariate Correlate, 二变量相关( M9 |" ^2 a4 t5 C
Bivariate normal distribution, 双变量正态分布
6 K, k# V5 A& P* a( c* T9 J, }Bivariate normal population, 双变量正态总体% [# j# d( g: A9 D5 r6 {4 C
Biweight interval, 双权区间
- p I/ B% w5 Q* B0 k; W; j6 TBiweight M-estimator, 双权M估计量
. a# n+ M% F$ |Block, 区组/配伍组1 _- k; J/ @) ?3 [$ A0 Z( T
BMDP(Biomedical computer programs), BMDP统计软件包
, L% Y( R$ T v( y% E, U9 }Boxplots, 箱线图/箱尾图4 H0 D; K/ b7 O. o/ v/ @2 k
Breakdown bound, 崩溃界/崩溃点
/ v' g* g( ~" S% UCanonical correlation, 典型相关
- m1 O9 v0 A2 JCaption, 纵标目2 o" O8 E2 Q5 z, q
Case-control study, 病例对照研究
% ]) S! N" k9 X2 T( qCategorical variable, 分类变量
1 c1 J4 q1 q. E+ GCatenary, 悬链线
7 ^( Y) T5 Y }; s; [Cauchy distribution, 柯西分布
+ f$ @! R- y" k% z" O3 N6 R7 y; }5 NCause-and-effect relationship, 因果关系
0 j8 B4 C) M/ M' _Cell, 单元
% i+ H/ R: C& h Q% s) P( g4 Y9 DCensoring, 终检
9 t; r6 Z" a# rCenter of symmetry, 对称中心) ~5 Z5 k, @3 {2 [- i+ _9 }. K; d
Centering and scaling, 中心化和定标+ U7 B5 M4 u( R3 d8 w
Central tendency, 集中趋势; ~# u. I, \2 p" x' x2 L/ ~
Central value, 中心值
9 a1 E" N, J. G+ q/ p9 ECHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
1 u& ^4 t) d3 \2 {* W. Z$ x" GChance, 机遇$ w r" X7 g1 E% q- j% V9 C0 ]
Chance error, 随机误差
: m- V" q5 d* Q, jChance variable, 随机变量
. m( k% ~; k" P3 q8 RCharacteristic equation, 特征方程
! u2 N9 K& E' C, yCharacteristic root, 特征根* t6 B! l" L8 o3 C# |% v
Characteristic vector, 特征向量5 [" K; K% g, h9 H0 V
Chebshev criterion of fit, 拟合的切比雪夫准则( S: [; X" ~# O( y
Chernoff faces, 切尔诺夫脸谱图, ?' x' x6 Q; j; d, p8 {/ v. J
Chi-square test, 卡方检验/χ2检验
* \1 _" b3 P' g1 y- y( pCholeskey decomposition, 乔洛斯基分解/ P6 h* z" B: G ~* V) L$ N' ]- A( N
Circle chart, 圆图
! j5 Y- u* Q" C7 XClass interval, 组距
- `2 [$ u6 |1 F' S3 D- `+ SClass mid-value, 组中值' _8 t5 r$ @0 T4 P3 M8 [7 B
Class upper limit, 组上限
. B, S4 K: q. c' qClassified variable, 分类变量
- k8 h) W6 T! r! r) P M5 vCluster analysis, 聚类分析2 }; j; k' N' e: X5 V" V5 O$ z
Cluster sampling, 整群抽样6 I! e5 J4 ^6 G( M6 v5 ]+ m
Code, 代码! O% [ V' k/ N- g
Coded data, 编码数据: y9 I3 o* E6 a
Coding, 编码* p" m7 [& j" u. |& S9 |
Coefficient of contingency, 列联系数2 P# O4 L, v {: @" m4 W
Coefficient of determination, 决定系数9 o: K7 w: d; d' G" {
Coefficient of multiple correlation, 多重相关系数
% k. b3 W9 ^! W! N5 ^Coefficient of partial correlation, 偏相关系数7 r9 Y$ i; u. [0 }3 ~
Coefficient of production-moment correlation, 积差相关系数
6 m; e0 X8 c6 j1 R& @$ m: ~5 TCoefficient of rank correlation, 等级相关系数
2 m. X& q, m. K+ _Coefficient of regression, 回归系数
6 G0 x2 X$ Z: \/ {0 n' r$ mCoefficient of skewness, 偏度系数
5 Z( [- n2 j# P" H. |Coefficient of variation, 变异系数8 y; L5 \( k4 G% B* ^/ u3 X5 `, I
Cohort study, 队列研究
* C+ s0 y7 z2 ] V5 D" W7 }Column, 列: o0 m X8 k( c. g! o
Column effect, 列效应
) T8 E1 E4 m# N6 s0 d' mColumn factor, 列因素
) F% D* j c) q! G1 d a& }. ?* dCombination pool, 合并
) d- s/ d& E* c9 v% [1 X- r- KCombinative table, 组合表
$ U3 D9 g4 k2 A8 J2 ?- aCommon factor, 共性因子7 D4 F+ f- Q2 i4 ]3 \. [* v3 Q: ^
Common regression coefficient, 公共回归系数
m. n2 ]; E# U5 u2 mCommon value, 共同值: Z7 p- m. n$ O$ {/ c4 ]* S
Common variance, 公共方差& U, n! A: l4 c# z# j
Common variation, 公共变异1 N8 ~4 r3 t5 q, k5 R: F4 _
Communality variance, 共性方差( ]7 [4 H+ j8 d% b, @" T
Comparability, 可比性* B& J1 u% m9 s
Comparison of bathes, 批比较
1 c" S2 Q* X# W* G( I, RComparison value, 比较值( f) o {! U% v2 @2 f1 W: c
Compartment model, 分部模型
& ]# _- [- M1 a1 O) d2 u# aCompassion, 伸缩$ J* Y, k6 c/ P* E8 X
Complement of an event, 补事件
/ \0 H! {# `* b& Z' z6 {Complete association, 完全正相关
, R3 g0 Q6 F* m9 G) a. SComplete dissociation, 完全不相关! {6 V1 O$ k" d6 r3 D! U: Z
Complete statistics, 完备统计量
: a$ ~# V7 ]/ T/ KCompletely randomized design, 完全随机化设计
! }5 F8 }( a7 DComposite event, 联合事件
8 `* ^( p: x7 q0 u7 M$ u# _Composite events, 复合事件 `' R6 Z8 N& a1 e* r3 X
Concavity, 凹性
6 Z2 @3 T+ J7 m `# O- vConditional expectation, 条件期望3 e; g- E9 Q8 E6 ?; `; y
Conditional likelihood, 条件似然/ s% E3 O( e& N
Conditional probability, 条件概率7 H6 v o2 w& [7 T; ]2 I0 x0 Q
Conditionally linear, 依条件线性
) f( x8 e3 O f7 `6 s# g/ AConfidence interval, 置信区间* }# ?, }2 E+ \
Confidence limit, 置信限
$ G8 H2 V$ l. Y/ ?4 X3 ~: EConfidence lower limit, 置信下限
9 p# q& ~! b4 E- V: VConfidence upper limit, 置信上限
! Y$ }) z% w) K3 r' a- \: |' w+ XConfirmatory Factor Analysis , 验证性因子分析8 b( Z \9 a4 |
Confirmatory research, 证实性实验研究
) R! B. g; g* X, WConfounding factor, 混杂因素' B: y2 b3 ^) C+ j5 G5 f
Conjoint, 联合分析* p% J, H; k8 K+ q, r1 V
Consistency, 相合性
f7 d* \) F: L4 UConsistency check, 一致性检验8 e' F8 g, B! }
Consistent asymptotically normal estimate, 相合渐近正态估计" z$ k+ {0 B5 \, ~2 Q5 V% ?8 X0 \
Consistent estimate, 相合估计
; ], Q+ [( T+ gConstrained nonlinear regression, 受约束非线性回归
8 I; {5 y7 b- S1 l) D* R7 \Constraint, 约束
- ]% `( E1 D1 HContaminated distribution, 污染分布
6 a; _' z5 G9 H t5 K( w2 YContaminated Gausssian, 污染高斯分布5 Y3 i! s5 U, `
Contaminated normal distribution, 污染正态分布2 ]+ E9 l% C% v+ ]$ c
Contamination, 污染
2 _5 r$ p' B" z3 O8 UContamination model, 污染模型
' k6 D- R$ r5 r) V& i& yContingency table, 列联表
& t8 V, L! ^2 TContour, 边界线/ `' U! k) X( A! V( f6 h
Contribution rate, 贡献率
' L+ B' G( s* p- e( ?Control, 对照4 j6 {8 w3 L" o! B) f* f [" i; c
Controlled experiments, 对照实验0 P7 @6 y# h8 g6 X1 A# d
Conventional depth, 常规深度 w& c1 u& a8 N' [; |* W& }: Q
Convolution, 卷积
9 u/ C0 }, V/ aCorrected factor, 校正因子
; V9 h k3 l8 L5 Q- z {Corrected mean, 校正均值
3 q j' y1 V/ O8 f |7 p7 bCorrection coefficient, 校正系数9 |' f- ^7 a& B, L& a# b B
Correctness, 正确性
- t2 {5 V1 K/ r+ `; uCorrelation coefficient, 相关系数
v" r5 [* p q9 `! R# OCorrelation index, 相关指数
2 s5 N! V, E( `$ T. {6 iCorrespondence, 对应
" k+ M6 `8 d- ]/ M+ p! aCounting, 计数
+ q9 V/ ~8 E) T5 C# I0 TCounts, 计数/频数" P4 v% s9 c! ?0 _, m
Covariance, 协方差
( W* G+ G' y' j4 `, C6 h1 bCovariant, 共变
; h& E) x2 W4 @0 y% u( A% PCox Regression, Cox回归
* Y' i) m( f8 GCriteria for fitting, 拟合准则5 u# A2 Y7 v4 H( f
Criteria of least squares, 最小二乘准则0 \. O! A% ^: T4 d2 c! V4 B
Critical ratio, 临界比8 Q# S( w* |2 V& ?- H' K' `
Critical region, 拒绝域/ o+ |3 R. U4 Q# U' x
Critical value, 临界值
* l7 v/ o% o- K8 x" zCross-over design, 交叉设计1 V) n0 E8 X! \$ R L J
Cross-section analysis, 横断面分析
* x# ]9 g$ l$ T! ZCross-section survey, 横断面调查
( ~; U) ]/ T- R9 a2 Z/ ICrosstabs , 交叉表
4 s8 k& ~" f( Y, ]; k& q8 `Cross-tabulation table, 复合表0 ?2 Q8 t, v6 ?- }- @# o G
Cube root, 立方根
. A1 g' V% u% u; aCumulative distribution function, 分布函数1 s, R6 e4 V0 j% M4 x4 d, ~
Cumulative probability, 累计概率
: ]' Z# C5 E- \5 Z0 UCurvature, 曲率/弯曲3 A/ [0 s4 R5 S, Z3 M
Curvature, 曲率
+ g# V/ H1 Z+ h6 J8 Z) aCurve fit , 曲线拟和 - U8 r# R; H. S3 x# A: P" }
Curve fitting, 曲线拟合
+ A$ h3 A, F) Q" u/ ^6 tCurvilinear regression, 曲线回归- u* d+ m5 @( I! J! i. h
Curvilinear relation, 曲线关系
7 i1 R7 {! W! a* ACut-and-try method, 尝试法
) Q! w% T: K% h. Q. ICycle, 周期( @( q8 L. }9 B
Cyclist, 周期性
) j. T& J" u9 |: v$ q/ tD test, D检验
( e% Z2 }. f* yData acquisition, 资料收集
. u! A9 f5 z9 T3 F: b% ~1 V$ Z7 |Data bank, 数据库# i6 c% l* K) V: ?% }
Data capacity, 数据容量
0 l: u0 h# w1 M8 l( ZData deficiencies, 数据缺乏) o8 i/ X5 g7 ?# j; Y2 K
Data handling, 数据处理
7 l T9 x. x6 {9 @2 }" [Data manipulation, 数据处理
~/ r& o( G3 S0 ?+ e/ PData processing, 数据处理( P0 i" O* z, \) S# L
Data reduction, 数据缩减
* R; P- x" L3 S+ [$ BData set, 数据集
! t; {+ P. `# n' o7 H% \( c% R6 O; pData sources, 数据来源
5 U) m- ]" \" U: z A3 YData transformation, 数据变换9 f' N" p @6 y6 F
Data validity, 数据有效性
7 ]: p0 t% j/ y. c" i" wData-in, 数据输入
- Q4 ^7 e: J; S% QData-out, 数据输出+ D& k8 I W s$ w, z0 v. f$ m8 Q& `
Dead time, 停滞期
8 T+ D( |& R# T( _ a: rDegree of freedom, 自由度
8 e% ^( K5 U. W/ ~ e* f: ~Degree of precision, 精密度! p" V4 \* G5 u& J* _
Degree of reliability, 可靠性程度
( H, [: S( t; u5 qDegression, 递减: W1 P2 r0 \; k# Z# w
Density function, 密度函数: o# H: _8 o) F8 v
Density of data points, 数据点的密度: h2 R0 X' T' k4 f. ~# v7 ?$ [
Dependent variable, 应变量/依变量/因变量
! t l+ c4 J' L* Q. oDependent variable, 因变量2 t* e' q, t: J. n3 l5 S
Depth, 深度8 q6 ]# J: M2 E) U
Derivative matrix, 导数矩阵: d0 ], M* V! @$ p* I
Derivative-free methods, 无导数方法
0 T# J, f+ v5 QDesign, 设计
) G/ M8 e! D1 {- u8 K" a) h) XDeterminacy, 确定性
0 ^. d+ h8 S( V' f0 UDeterminant, 行列式/ w7 i8 @8 S1 n) Y
Determinant, 决定因素
8 W" \" c$ p' n5 t* _5 D5 b' FDeviation, 离差
5 D7 q( z s2 CDeviation from average, 离均差) L% k0 v$ p! n* r* q7 G! u. ~
Diagnostic plot, 诊断图
; w3 x, w V8 E, g) D8 ^Dichotomous variable, 二分变量8 s" Y, f" [6 @. p
Differential equation, 微分方程; ]9 m( U3 A, `
Direct standardization, 直接标准化法7 m4 |9 A- s+ f
Discrete variable, 离散型变量 k3 A4 K. j& w1 M5 E( v
DISCRIMINANT, 判断 : R3 V) I |0 @' O/ n
Discriminant analysis, 判别分析' t+ X' U; _* f6 \
Discriminant coefficient, 判别系数3 T; U0 U+ f- I% D! y
Discriminant function, 判别值
2 ~6 z- v5 q( D D" ?Dispersion, 散布/分散度
) ]) n" |3 Y* I7 n' k1 g0 \ JDisproportional, 不成比例的3 g6 y( a( S1 o0 P4 H
Disproportionate sub-class numbers, 不成比例次级组含量
/ C. S# Q& a! {- l3 LDistribution free, 分布无关性/免分布
0 j& W" U" l7 t) Q) yDistribution shape, 分布形状5 m6 a% e5 g( x c6 ?
Distribution-free method, 任意分布法$ c/ u5 ], [& r0 C, }9 s+ |
Distributive laws, 分配律5 N2 M. D+ E5 @7 W) a
Disturbance, 随机扰动项
# [) ?% f7 u' W- h6 f! ~7 r ?Dose response curve, 剂量反应曲线
$ q8 p1 y0 r2 T3 QDouble blind method, 双盲法
1 k, x& ? M0 o F" I6 }* |Double blind trial, 双盲试验
8 d2 Y: R8 I" ~Double exponential distribution, 双指数分布( z8 W2 Z% o/ S3 {) g2 Q- R; R/ p
Double logarithmic, 双对数
3 Y5 |1 g- E& Y( ~$ IDownward rank, 降秩- g* C t" v. `* f& s* O: Z
Dual-space plot, 对偶空间图: d; w( B9 ~: I$ |
DUD, 无导数方法
3 ]. ~) ~0 l# VDuncan's new multiple range method, 新复极差法/Duncan新法2 j# n' T9 T: M+ W3 e/ S/ E* ?% z
Effect, 实验效应# ?0 B z3 l, s" m
Eigenvalue, 特征值
% l# d+ {0 A& g O4 mEigenvector, 特征向量
& \$ `8 X0 x Z5 W9 c& nEllipse, 椭圆& b- @% \) B6 _, ~' I
Empirical distribution, 经验分布
% ~& l) S$ | i/ p" } h) I- e. M$ \Empirical probability, 经验概率单位1 T% v# a9 v- ~: n2 L
Enumeration data, 计数资料( p" F* ~, |0 w
Equal sun-class number, 相等次级组含量2 K& U. }) ~: v7 o
Equally likely, 等可能0 m& U. C7 A! i1 M
Equivariance, 同变性
# z' m1 [2 G6 fError, 误差/错误& ]7 ~$ C$ t7 r- _% X$ r7 F( Y
Error of estimate, 估计误差
" L3 e0 W9 e m+ rError type I, 第一类错误
5 e& E5 }7 k+ tError type II, 第二类错误
: T1 b- _% Y' W; K7 hEstimand, 被估量
3 P" H3 i/ X8 o; }Estimated error mean squares, 估计误差均方, G# {" z; K: S2 o) L
Estimated error sum of squares, 估计误差平方和
3 Z# J( k4 O2 t/ i9 d/ x- f5 d8 \' SEuclidean distance, 欧式距离
- V3 `+ @1 h$ [9 b$ l- qEvent, 事件
* p: P8 a7 k) L+ s! [" R) FEvent, 事件
4 j4 r) Y- t- Z# w8 kExceptional data point, 异常数据点 [; l% D% U* g! ^# ~/ E% c
Expectation plane, 期望平面
, q3 p1 g2 W0 s( a k7 EExpectation surface, 期望曲面8 J# r* r. T, g4 U0 H3 I
Expected values, 期望值
; e# Z7 Q* ~% Z8 n' P8 a0 PExperiment, 实验1 F: s: R. @! L, x4 }
Experimental sampling, 试验抽样- X5 z0 f+ M5 ^! [( V" r
Experimental unit, 试验单位" E" ^$ z9 f7 H2 \
Explanatory variable, 说明变量
2 m7 x) }3 N% H6 [1 C+ j5 EExploratory data analysis, 探索性数据分析) o) _/ f$ ]: [- L6 E- j) v9 |
Explore Summarize, 探索-摘要: e6 ^' H5 b- `& w
Exponential curve, 指数曲线. P \4 ^ J! I$ W1 w& H$ N
Exponential growth, 指数式增长- g8 [# X9 W ?
EXSMOOTH, 指数平滑方法
7 f/ _( e; e1 V) n% |+ V" G9 _Extended fit, 扩充拟合4 q- g! @" C2 w1 B9 C8 F0 u
Extra parameter, 附加参数
' q% w# M' o5 k" T. X7 t( Y MExtrapolation, 外推法
) I% k- M5 V- s2 L* z* Y" nExtreme observation, 末端观测值
# q7 f$ p! U' i' WExtremes, 极端值/极值
% g9 ]- [9 `( ^" zF distribution, F分布# a' e3 T; t- F; F7 p5 T' S- B
F test, F检验
* b; b5 @/ K4 F( I% gFactor, 因素/因子
3 r; |! H% Z0 M$ R2 f! sFactor analysis, 因子分析! J' j6 P; ?4 Q% [$ M
Factor Analysis, 因子分析
8 R( p$ @; ^9 R* }5 X: eFactor score, 因子得分 ) {5 d# v2 e9 m& ?- I
Factorial, 阶乘
3 {* F& z' C+ U9 DFactorial design, 析因试验设计% O6 Y- I/ K; j7 L
False negative, 假阴性
/ L$ I z: B, E6 o( OFalse negative error, 假阴性错误
' X- A5 q2 g6 e& e+ d- o5 I6 nFamily of distributions, 分布族9 K+ E9 o5 H. i
Family of estimators, 估计量族( {4 d/ f/ o: R
Fanning, 扇面/ ~1 O- N% M+ D- c- u; u- |
Fatality rate, 病死率
/ W; O1 d8 L; _/ J, DField investigation, 现场调查
9 ^9 ^0 u. Z& u/ aField survey, 现场调查
^$ Y' C/ S w: t1 W. {Finite population, 有限总体# p* E# e0 U! `* r1 e- A$ X; \
Finite-sample, 有限样本1 g2 t" T" G: E+ h N
First derivative, 一阶导数$ b ]) H, a' O `& g7 i7 I
First principal component, 第一主成分& t& m- i4 H% F+ _* B, ?4 X5 o
First quartile, 第一四分位数
! e3 I' q* W$ F8 kFisher information, 费雪信息量
1 t: K" X# f) g0 ~1 cFitted value, 拟合值' H' _7 @' y, |) g/ O+ V
Fitting a curve, 曲线拟合
. w, e. s0 t, n9 R6 p4 C9 N/ cFixed base, 定基, h8 j0 D# z5 c/ A7 t
Fluctuation, 随机起伏! } b4 L3 k( `/ T; [: }) ^" M
Forecast, 预测, Y' r8 F7 G$ ^4 p/ U4 T
Four fold table, 四格表 S: c, f4 n+ z9 N; w& P
Fourth, 四分点
- j' u" j5 {* L& T6 ?: SFraction blow, 左侧比率3 j: o$ _0 a& b5 e1 n; M! O
Fractional error, 相对误差7 @: G' z$ c! S7 O8 w6 M4 z
Frequency, 频率" E: Z& V9 p% U2 W/ C T! Q
Frequency polygon, 频数多边图
. H2 {5 Y8 t3 q3 Q# b+ g6 @4 DFrontier point, 界限点$ @9 e4 \$ ~3 Y: n# D2 X2 n7 U
Function relationship, 泛函关系; L8 Q q/ k+ `9 P( w
Gamma distribution, 伽玛分布
8 q9 |% r9 Q9 V4 s8 SGauss increment, 高斯增量
& ~" c! E& t' b! ^% N) u8 PGaussian distribution, 高斯分布/正态分布
! U P8 e9 U/ G9 U6 H( R9 KGauss-Newton increment, 高斯-牛顿增量
) X- j: E" w* v# w J8 aGeneral census, 全面普查
) M4 }* C7 _' fGENLOG (Generalized liner models), 广义线性模型
% u# r1 ^$ A) ^9 mGeometric mean, 几何平均数4 k3 e$ b5 [1 {8 w
Gini's mean difference, 基尼均差. D# o7 p' D. `" s( L( M
GLM (General liner models), 一般线性模型
" @5 d, y4 b% W; L5 D" pGoodness of fit, 拟和优度/配合度$ q* N1 E7 r4 V. J0 J5 G' x
Gradient of determinant, 行列式的梯度5 Y" v4 e8 u( k4 |
Graeco-Latin square, 希腊拉丁方8 D6 a! e: j: T0 g; T4 F
Grand mean, 总均值
- ]8 M# d& r8 HGross errors, 重大错误% L: P( t" L7 d+ N1 I$ Z& p
Gross-error sensitivity, 大错敏感度
% I1 Y( E3 c2 f6 U7 S6 y6 s/ H: WGroup averages, 分组平均
1 \2 L( A7 T, M+ `- gGrouped data, 分组资料, Z. E% `, S# z4 x. ?( N/ T
Guessed mean, 假定平均数. _( |& a# G. H9 u1 v
Half-life, 半衰期
* y+ g6 a ^, t+ v IHampel M-estimators, 汉佩尔M估计量
! E! h: d6 s7 V: yHappenstance, 偶然事件
9 n* \3 H- f$ OHarmonic mean, 调和均数
+ Q$ X/ m' J9 y T9 EHazard function, 风险均数* x- a1 S, D J! k! N5 }
Hazard rate, 风险率9 g/ E' f, U9 J4 j% z* O& q
Heading, 标目
* v# C% K/ q1 qHeavy-tailed distribution, 重尾分布
5 K9 G4 C+ @7 L+ `3 I# SHessian array, 海森立体阵, `$ C& ^6 @% J* S! L
Heterogeneity, 不同质
/ t4 Q( F+ c" }. f5 G4 Y. @; uHeterogeneity of variance, 方差不齐
% g6 n4 ?( Z4 t% z* w! VHierarchical classification, 组内分组$ z8 s* s: y3 n; ~
Hierarchical clustering method, 系统聚类法/ P; j" [$ v- r( |
High-leverage point, 高杠杆率点
" D8 u: q7 G7 }HILOGLINEAR, 多维列联表的层次对数线性模型6 I+ ], K8 a: f; O& L% ?
Hinge, 折叶点4 I. ]8 f% a+ f, J+ w$ `
Histogram, 直方图
. X0 S, m) K# J1 E2 C3 \2 Z) e, NHistorical cohort study, 历史性队列研究 " ^- \7 c4 m. O$ i
Holes, 空洞
0 D1 F; s6 p+ e1 b# CHOMALS, 多重响应分析
/ M& U( [7 _; g* l9 W) C8 J5 W7 _Homogeneity of variance, 方差齐性; ?' S* w4 c! w
Homogeneity test, 齐性检验
9 d a+ _) K( Q# _Huber M-estimators, 休伯M估计量: U8 ^% |& V/ n5 A+ j6 m8 i2 [) E1 M
Hyperbola, 双曲线
" Q6 h5 M" I: `2 i+ THypothesis testing, 假设检验
8 }$ D+ L4 r& H1 K' G4 e$ D% QHypothetical universe, 假设总体, a, o7 M8 L: K/ t; G& A
Impossible event, 不可能事件% l) o) D0 e3 q$ O
Independence, 独立性. f& l6 n4 a" I
Independent variable, 自变量
. k" H2 y0 D% I( C0 sIndex, 指标/指数3 S7 M4 e$ G0 I, J6 R. G0 _! c
Indirect standardization, 间接标准化法5 ]% a3 \2 b" L1 ~: ^* y
Individual, 个体4 `' c0 M+ G1 U4 E, |3 Z
Inference band, 推断带! M0 X$ O( a9 m, Q) D2 o
Infinite population, 无限总体
" |- y3 ]" |' x! m4 O) Y( xInfinitely great, 无穷大
[/ {8 d5 O8 E) _2 t3 ]$ @Infinitely small, 无穷小
- @" W- ~1 ?0 g4 ?6 NInfluence curve, 影响曲线7 r, v$ y0 w* z6 X' `0 W1 K
Information capacity, 信息容量* v" F( v" q2 U8 |* q
Initial condition, 初始条件
K, I$ ]+ U0 VInitial estimate, 初始估计值. J6 G L! A- m+ n
Initial level, 最初水平" x% j4 Q; Z/ j% _
Interaction, 交互作用! h N9 L, b2 L) q6 f0 C: x
Interaction terms, 交互作用项+ }3 M# k0 @8 \
Intercept, 截距, ~& G, b+ }1 D; e
Interpolation, 内插法
0 j2 t: v$ d( O9 gInterquartile range, 四分位距9 }5 i- H+ O+ N3 P+ p& O
Interval estimation, 区间估计
8 ]5 P8 k. |+ K" F) n* BIntervals of equal probability, 等概率区间5 l6 K1 {1 ^- t4 F$ t- h3 z9 l
Intrinsic curvature, 固有曲率. A1 h- u) }/ U/ V, t$ }% r! m
Invariance, 不变性
M) N R* I' i: C s8 fInverse matrix, 逆矩阵! o5 Y8 ]2 O; G2 T* `4 Z
Inverse probability, 逆概率/ C. M [1 \$ L7 Y1 X
Inverse sine transformation, 反正弦变换
, R: e; O5 C/ p# ^Iteration, 迭代 1 X2 F2 ]5 u e: h' z
Jacobian determinant, 雅可比行列式$ G! G' `7 T2 ?
Joint distribution function, 分布函数
$ x% h0 P# \8 D$ E5 b8 qJoint probability, 联合概率
, R9 C) K5 t. d, Q$ bJoint probability distribution, 联合概率分布
# X& e, _; \9 Y$ x; W0 `K means method, 逐步聚类法
& K" e, B! C: l+ L, u' v# ?0 gKaplan-Meier, 评估事件的时间长度 * G) p5 m: X1 ]! i! ^' \* `, u
Kaplan-Merier chart, Kaplan-Merier图: g: U) Z/ Z7 X" h/ ]
Kendall's rank correlation, Kendall等级相关
0 [% T8 J8 l5 j$ CKinetic, 动力学1 H3 j! s5 _6 N5 w' @. D. D
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
, M+ t. L3 @: D kKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验; f/ R3 J: g6 w5 F7 Q
Kurtosis, 峰度
, g; C7 K8 O& }Lack of fit, 失拟6 U! u- n& A: m: v6 R4 {, s
Ladder of powers, 幂阶梯: O, g' V+ Z9 i% K
Lag, 滞后4 }! V1 i, J7 Y4 Y; q: u' P J
Large sample, 大样本
$ |3 l/ x6 N; N( I ?Large sample test, 大样本检验
9 Z$ l; Q: ?+ m cLatin square, 拉丁方" `$ S, C' H& m/ ~' p" L4 x1 _
Latin square design, 拉丁方设计' l. a1 `9 g* [
Leakage, 泄漏( i1 g" W) H' G* l( L9 A+ q
Least favorable configuration, 最不利构形
/ q# S$ v9 h) O) mLeast favorable distribution, 最不利分布
8 G% v! s0 I, J5 x d. Y# ?Least significant difference, 最小显著差法# q. F" e# A1 H: Q u8 `+ d
Least square method, 最小二乘法
2 Z0 V) [6 Q( i8 |Least-absolute-residuals estimates, 最小绝对残差估计
) ~' s9 A' i, }/ BLeast-absolute-residuals fit, 最小绝对残差拟合
5 V9 h( R1 h5 FLeast-absolute-residuals line, 最小绝对残差线* [6 o; [8 C5 J# |" p" d% u3 U1 Y2 R
Legend, 图例
2 }: _/ m" U, k/ K* N9 PL-estimator, L估计量
( z% e* S4 [; I- N b; A* W# E6 v+ @L-estimator of location, 位置L估计量$ M* R1 g" I8 K/ b
L-estimator of scale, 尺度L估计量: x. r* ?$ x) R
Level, 水平" N4 }5 A4 M4 |4 a7 q
Life expectance, 预期期望寿命
3 G& U! N. z! Q# U& j/ y: HLife table, 寿命表$ t$ L4 u8 [8 z. Z
Life table method, 生命表法
& e3 }% k$ x. k% Z4 i( W1 M" KLight-tailed distribution, 轻尾分布
/ l5 H7 \/ R5 ~7 U: _4 e6 i8 VLikelihood function, 似然函数" u1 g4 P% p( G, A
Likelihood ratio, 似然比
" l6 N2 Y* H8 j" W3 Nline graph, 线图5 T8 `+ b7 I, v
Linear correlation, 直线相关/ E0 ]" t% [5 t }% I/ c
Linear equation, 线性方程
& [1 E! j. ]7 W: X% k) \6 ~( iLinear programming, 线性规划5 ^6 x# p$ n; I0 W% q1 }
Linear regression, 直线回归7 ~% H8 l$ Y* {
Linear Regression, 线性回归
2 O3 [ ^) @0 B5 u# A1 F, CLinear trend, 线性趋势
p q, U" R; [Loading, 载荷
$ g& h( }1 R ]9 _- x, j1 X/ E2 WLocation and scale equivariance, 位置尺度同变性
/ D% D7 M" o( y2 K/ ?Location equivariance, 位置同变性0 ~( C6 ` m0 T- t
Location invariance, 位置不变性
) c& [3 a( d9 J5 Z, g, n/ hLocation scale family, 位置尺度族
8 |9 s U$ s5 g" ?8 C( B. l" VLog rank test, 时序检验 " b0 C/ p1 ^- ^" ~1 U, [
Logarithmic curve, 对数曲线& F8 v5 ~! K! {3 S( o" y
Logarithmic normal distribution, 对数正态分布
1 b4 ~# `" }( nLogarithmic scale, 对数尺度
: ?" E4 y3 l) v' e0 `9 i; V- lLogarithmic transformation, 对数变换
, j7 s r+ B9 _% T! Z9 WLogic check, 逻辑检查$ n+ H9 j! x9 P: k' r I7 C4 D
Logistic distribution, 逻辑斯特分布
5 m, E' J4 D. i4 c( @- F1 ]7 KLogit transformation, Logit转换, l6 C( p5 z2 G
LOGLINEAR, 多维列联表通用模型
5 A5 z B1 K8 e- S0 sLognormal distribution, 对数正态分布
; }+ Z; m( U/ {! B- D+ zLost function, 损失函数. @ ^6 l( V9 A) V
Low correlation, 低度相关- v: B* P$ i0 j$ i4 b6 x1 [
Lower limit, 下限
8 m: H) C5 F4 c) ?Lowest-attained variance, 最小可达方差
1 C* n! t: S: S5 @ vLSD, 最小显著差法的简称/ M% q- Y. S" x
Lurking variable, 潜在变量. P$ Q+ P) E( G% h3 ?1 V/ |
Main effect, 主效应) {) E" M$ J" y* Z( S: ?: y
Major heading, 主辞标目
$ f' \# N" q6 E) C0 O6 YMarginal density function, 边缘密度函数7 i5 P" {& w6 Z0 ?1 b5 y
Marginal probability, 边缘概率
! W. U, M- E3 SMarginal probability distribution, 边缘概率分布- S7 u$ x7 U! o! o* m4 P8 \
Matched data, 配对资料
' g7 {/ r3 ?0 {+ b* zMatched distribution, 匹配过分布, i! _) |9 |' P* x7 y0 e4 f
Matching of distribution, 分布的匹配* V* O0 |$ s) _
Matching of transformation, 变换的匹配3 k5 i j( ~1 X4 n" b4 |0 @
Mathematical expectation, 数学期望
$ B& n5 d+ h, X, z& k7 V) o( ?Mathematical model, 数学模型
4 O# a% p2 t, fMaximum L-estimator, 极大极小L 估计量
$ z8 l5 ^) c* W a" k; Q4 PMaximum likelihood method, 最大似然法1 w3 c+ Y, ^! x9 G1 k
Mean, 均数+ z# n$ H& Z7 ]) d' N$ b/ h% r
Mean squares between groups, 组间均方
" _0 l$ V! r* U: sMean squares within group, 组内均方
. X- P5 I. g6 S" \9 p CMeans (Compare means), 均值-均值比较7 S8 y8 @! I- c
Median, 中位数
9 l0 r w2 g( D( K: v' aMedian effective dose, 半数效量
0 m- W% M4 g. N5 Y& ^/ `; VMedian lethal dose, 半数致死量
; x$ J" |: Z' }4 ^4 t7 X( PMedian polish, 中位数平滑
4 F* a$ _0 M7 f3 X- V5 DMedian test, 中位数检验
+ B/ ?# n# q3 W& TMinimal sufficient statistic, 最小充分统计量
; e0 h3 b* G+ |( BMinimum distance estimation, 最小距离估计* ~' d. \. H' \
Minimum effective dose, 最小有效量$ d* S+ Z% _2 Z/ V/ \6 H7 h
Minimum lethal dose, 最小致死量
S5 _1 h; p- D1 JMinimum variance estimator, 最小方差估计量
; H6 r& H' V7 r5 ]! U$ \MINITAB, 统计软件包) b. ?( q' U0 `1 g
Minor heading, 宾词标目
( Q+ p$ {7 B8 ^, PMissing data, 缺失值
7 E% O' d/ t+ u" [6 F% J) |Model specification, 模型的确定+ g7 L0 N; T1 {. R0 K& u! y I
Modeling Statistics , 模型统计
! \0 }6 P8 O& v4 L. XModels for outliers, 离群值模型
; k" x" m! A* jModifying the model, 模型的修正
4 z6 q9 o( `" |% ^( }; KModulus of continuity, 连续性模
5 S+ F( z5 B* l$ ~Morbidity, 发病率 : r$ a7 K1 h- ]7 e; z$ ^) a
Most favorable configuration, 最有利构形
: F J$ c q! M$ r! }& |' k+ [Multidimensional Scaling (ASCAL), 多维尺度/多维标度
, y) D M" M" ~, O5 Q; KMultinomial Logistic Regression , 多项逻辑斯蒂回归& [. O1 f9 Q5 Y6 y
Multiple comparison, 多重比较/ P; J; ] z* T# c+ ?
Multiple correlation , 复相关
0 X1 `7 Y+ }3 X7 q& {5 J! OMultiple covariance, 多元协方差. Z$ f& |: ?* _, f# z6 D
Multiple linear regression, 多元线性回归: W1 b. v u; D$ p
Multiple response , 多重选项
" Z8 t% p( x2 R" m6 s0 ~Multiple solutions, 多解
* R+ B0 Y" M* s8 E" U4 G3 h! y8 y k, lMultiplication theorem, 乘法定理0 |- t V' Z+ m1 ]
Multiresponse, 多元响应
" O0 d; ]! o7 F# s8 F+ SMulti-stage sampling, 多阶段抽样
7 Y# `7 k( ]) pMultivariate T distribution, 多元T分布
q% G8 Y8 p5 R6 s2 L4 qMutual exclusive, 互不相容
, C& N0 e* p6 W. y0 ~1 qMutual independence, 互相独立7 ?! q. f+ L7 @9 g
Natural boundary, 自然边界% J; K7 B* i% @. G' z0 U
Natural dead, 自然死亡
1 ^% ~! F1 _2 N, V* JNatural zero, 自然零
& O; A, k$ J# w2 T9 i! u/ I4 H$ mNegative correlation, 负相关' J0 ^& S6 N. N- W
Negative linear correlation, 负线性相关
/ R6 {. n$ l3 L# |0 q$ mNegatively skewed, 负偏
% b; g' r( M+ V( cNewman-Keuls method, q检验6 S: k% ?- i: |7 z9 E+ Y5 ^- S
NK method, q检验/ v, O+ j8 s7 r6 m, P' n s6 e
No statistical significance, 无统计意义
$ K" t0 s2 I% F+ h( i; w5 @" L( ONominal variable, 名义变量
- a, j* x5 L) {Nonconstancy of variability, 变异的非定常性9 `, V6 e6 ~( h, @
Nonlinear regression, 非线性相关
( k. I% Y. C3 C/ ?Nonparametric statistics, 非参数统计: M3 x; Q3 Q4 c9 A5 k* z
Nonparametric test, 非参数检验
. s% w( N* z4 p2 }Nonparametric tests, 非参数检验
^% G4 ]$ F! y- C$ [: z+ a- qNormal deviate, 正态离差6 _* z# ?. }* z3 a+ y
Normal distribution, 正态分布- g3 u1 x# a' Q8 t- X" ?
Normal equation, 正规方程组. S% i |! ^5 Q* z6 j
Normal ranges, 正常范围
9 Z+ O' R& z& p: b2 eNormal value, 正常值0 }! W6 _! ]% X
Nuisance parameter, 多余参数/讨厌参数
; b; Q' k% d/ VNull hypothesis, 无效假设 / f# y. H. t6 O2 { e4 X
Numerical variable, 数值变量7 ~& d# q1 Y6 B" c/ G$ v& f! n6 k/ ^
Objective function, 目标函数
) D, c* n1 c. [* t; KObservation unit, 观察单位( L( J( d9 K8 O. k" M u" u
Observed value, 观察值
, T: E5 m# d! ]: h7 l, COne sided test, 单侧检验# U4 ~7 B6 k2 D! ~7 ^8 A
One-way analysis of variance, 单因素方差分析: R+ _/ Y+ x% ^0 v! z: Z7 M
Oneway ANOVA , 单因素方差分析
+ n* g) m" t1 Q3 GOpen sequential trial, 开放型序贯设计
% ]/ W( Z, Z- K1 fOptrim, 优切尾
* M6 Z4 H% W, I# R# b' S) `Optrim efficiency, 优切尾效率1 c v' w: k$ o* g
Order statistics, 顺序统计量
" O" g# w5 D) \2 X* z/ COrdered categories, 有序分类
! v" l3 n k3 q$ h- I$ x: y% F& bOrdinal logistic regression , 序数逻辑斯蒂回归
# }3 C7 p( Q# b8 }0 k f; VOrdinal variable, 有序变量 n0 I6 B" F' w
Orthogonal basis, 正交基
6 l5 _) M+ g$ g# `Orthogonal design, 正交试验设计
+ c2 M) k# p' _6 H* `3 m3 QOrthogonality conditions, 正交条件
0 z) {' f, i% j9 z( T+ N& Q+ cORTHOPLAN, 正交设计
$ ?& I; D: X4 l) {& {Outlier cutoffs, 离群值截断点; h/ e8 r. h' R0 V0 S5 B) a8 {
Outliers, 极端值5 }. J! M+ S$ ]/ B+ _3 B5 O2 ]
OVERALS , 多组变量的非线性正规相关 : v" F {# v' F( p5 H" h
Overshoot, 迭代过度
1 F2 j- Z6 u& Z7 }( aPaired design, 配对设计
9 J+ v! y. \% V+ ?. oPaired sample, 配对样本
8 U1 C- ?9 X$ {1 z; Z; NPairwise slopes, 成对斜率
8 F( W# e# R* m/ ?$ j/ vParabola, 抛物线( ]! ~' r4 Z# s0 X7 f
Parallel tests, 平行试验
! \) M8 n3 a; O, t0 GParameter, 参数6 |" d" s( K' Z5 v: e% ~0 H
Parametric statistics, 参数统计8 j- p9 @; I. _( _! l' ^& b
Parametric test, 参数检验$ H4 X+ B5 Y; {
Partial correlation, 偏相关* C& [' M4 T3 p/ u5 s" ~
Partial regression, 偏回归
. `+ o/ m: V3 k( hPartial sorting, 偏排序
& U5 q( L& \: fPartials residuals, 偏残差4 y9 m9 I2 ~/ e7 l2 ?/ {3 [8 f
Pattern, 模式
0 P ^2 q( P3 K6 k- q" f+ j! oPearson curves, 皮尔逊曲线4 @8 Q4 Y- c6 i7 S0 O4 h
Peeling, 退层1 O% E) [: s4 G! z- U8 z
Percent bar graph, 百分条形图
4 `; y; q8 G. c T) CPercentage, 百分比+ s5 ~' w/ @0 ]0 B0 G3 e) E5 w( Q
Percentile, 百分位数 R! C* z* e. w* |* |
Percentile curves, 百分位曲线
4 Y0 l4 P9 f: o/ s$ W APeriodicity, 周期性7 _; A; F' F# v: ^9 L8 }
Permutation, 排列
8 ~+ L i3 r8 V! I% iP-estimator, P估计量. H& X4 j" @! G, U& L. Y
Pie graph, 饼图
I' Y4 a$ A- v) Q+ uPitman estimator, 皮特曼估计量
6 O( [4 I( E4 s0 j# UPivot, 枢轴量 Y1 l8 b# a# Q; t
Planar, 平坦& u0 M! P" _ g! _$ V" ?6 P
Planar assumption, 平面的假设
% K/ D2 F* @. l. D, rPLANCARDS, 生成试验的计划卡# f5 E' X0 ]5 q
Point estimation, 点估计
- p1 ?4 {+ Y* \4 q/ l, f4 R1 oPoisson distribution, 泊松分布6 E1 c5 h. L% q7 b3 s9 L
Polishing, 平滑2 d6 ]: u7 f7 p, i
Polled standard deviation, 合并标准差
+ `7 Y5 V% P g0 p% ?; ~/ mPolled variance, 合并方差7 Z! t% \/ t9 g4 f" Z1 l
Polygon, 多边图, x7 t! v6 I; A; d6 V* i- i
Polynomial, 多项式( s& O' C9 h% R
Polynomial curve, 多项式曲线! @5 Q; w* p t% S$ v1 o
Population, 总体
+ {4 z7 z4 V5 a, P" v, U4 UPopulation attributable risk, 人群归因危险度+ D) u, a5 z5 H3 g5 o, m2 N! C# x
Positive correlation, 正相关( D6 E3 s2 x+ ?, A) Q8 |
Positively skewed, 正偏
, p$ J d' [. m* WPosterior distribution, 后验分布6 p X4 |- c/ u
Power of a test, 检验效能
9 ]6 v% ~% R- q& n; N" XPrecision, 精密度
' \" A0 U% P, n, [% A* VPredicted value, 预测值
$ O1 v0 c/ ^, W) KPreliminary analysis, 预备性分析/ I* o- s3 C$ ~* k6 z% v
Principal component analysis, 主成分分析
, e( ?+ I1 D, a9 ^Prior distribution, 先验分布
* I; X+ D" U! j- X4 G" @2 [Prior probability, 先验概率
3 ]1 K) V4 G, S4 \) u7 s0 ~$ V3 sProbabilistic model, 概率模型( \+ S9 a9 Q( Y6 ?& Y( Y- o+ {
probability, 概率: f% @' w$ h% A7 M: a% M3 S+ r6 p/ J
Probability density, 概率密度
9 P% M9 c4 @ P0 b; rProduct moment, 乘积矩/协方差9 V9 u' |6 A% h/ ?) Y; h5 Q
Profile trace, 截面迹图
$ N; }; F* h& J. q( BProportion, 比/构成比
, C6 @4 Q5 K; [Proportion allocation in stratified random sampling, 按比例分层随机抽样2 {! H' g. d" g9 v5 v
Proportionate, 成比例
" }( j+ l# Q9 a& YProportionate sub-class numbers, 成比例次级组含量
d+ R% E+ f0 ? P+ d: g# O) ^; ?Prospective study, 前瞻性调查, \% W8 ]! \& \" I, \* l4 r: X4 f
Proximities, 亲近性
j$ J" w" E: E* L" rPseudo F test, 近似F检验
4 ]1 i' N! ], t+ m' v8 U$ Y* @Pseudo model, 近似模型
# t0 I1 f1 ~$ q' cPseudosigma, 伪标准差
1 g% Z( q4 H8 |Purposive sampling, 有目的抽样+ M \4 G7 p e2 a: [
QR decomposition, QR分解
8 A4 A( \- l% ]: ?' J# L7 L( DQuadratic approximation, 二次近似
1 H% c; E% |' _ s+ d/ m! [- F' ^Qualitative classification, 属性分类% K$ h$ }8 C( Y6 x
Qualitative method, 定性方法
( o- L2 o u! x& \4 GQuantile-quantile plot, 分位数-分位数图/Q-Q图; W; O9 j: R4 `9 ~( d
Quantitative analysis, 定量分析5 Z7 B. L% w; C
Quartile, 四分位数- P1 D: E# Z8 y; E- n
Quick Cluster, 快速聚类- C$ ^ ~" Y! L. |* I- Y
Radix sort, 基数排序. w6 x3 H E7 N+ o! S* [' Z
Random allocation, 随机化分组
( J5 V. _( `( f- g. c2 rRandom blocks design, 随机区组设计
6 Z z3 F9 e. M$ l2 v( H/ z8 I5 YRandom event, 随机事件. l0 U! G( N) e5 ~; ~' g
Randomization, 随机化9 A3 @, f' r4 L! f4 e% W# f
Range, 极差/全距2 K7 _1 D3 t; o8 O; B) c
Rank correlation, 等级相关
% n! A- i3 W% u; p0 O% `' v8 rRank sum test, 秩和检验! s; N$ K, A4 I- B% B0 c0 u
Rank test, 秩检验 d/ q' w/ s; n9 O' z
Ranked data, 等级资料- {7 \0 ]8 \1 T2 k3 \" |8 i: J
Rate, 比率- m+ W$ R5 S; l9 k, E3 V
Ratio, 比例
6 n- `9 ^7 C/ f, U( y' kRaw data, 原始资料6 l: {0 h8 |& _1 \8 R* s0 \
Raw residual, 原始残差
* n' h' D9 N" E/ }Rayleigh's test, 雷氏检验
5 Q& W7 g4 m* O1 Z1 x% PRayleigh's Z, 雷氏Z值 % E' i6 h1 j2 N8 j8 z, Z
Reciprocal, 倒数
" W4 v5 E/ e! _* KReciprocal transformation, 倒数变换+ |4 J) [5 z+ r# c
Recording, 记录
2 M% W% P& w9 q0 d' cRedescending estimators, 回降估计量
! g% d3 g2 J3 x aReducing dimensions, 降维
" ~+ Q8 ~! k+ r. r6 p: VRe-expression, 重新表达
: F, x C/ O* F' y& [+ M7 \+ XReference set, 标准组
9 W+ f& g9 _8 u+ f* C; I' h: BRegion of acceptance, 接受域, m5 Q8 @$ i, A k) {
Regression coefficient, 回归系数
9 o2 ~+ {; `2 m/ U, t- {2 }! zRegression sum of square, 回归平方和; n# e) |5 c+ c
Rejection point, 拒绝点3 W) W4 ?- n, j; J2 V" I
Relative dispersion, 相对离散度
. n, Y, y) C- }4 N/ m" xRelative number, 相对数
) I6 H" t8 W1 b0 B6 W GReliability, 可靠性, b+ {, J, x' J S
Reparametrization, 重新设置参数! n% j& L, m( {' m ~
Replication, 重复
- M# a A/ h* B8 }/ B, _Report Summaries, 报告摘要9 e6 O" V9 y+ b5 w p& A$ V
Residual sum of square, 剩余平方和8 H; H7 {) \$ }8 ]/ _) D$ z
Resistance, 耐抗性
- V7 b& ^; x$ z$ R& }" @1 wResistant line, 耐抗线 ]- G& G7 _2 ~3 D& b
Resistant technique, 耐抗技术
4 x( L# E, e* J8 I q1 sR-estimator of location, 位置R估计量5 Z4 i" f; Y6 W$ b
R-estimator of scale, 尺度R估计量
" {# m4 q3 A8 xRetrospective study, 回顾性调查
9 l" o2 w& l" t, kRidge trace, 岭迹9 @" g7 v2 u' }/ T) {; `4 U+ r
Ridit analysis, Ridit分析
4 D+ Q" e6 P6 ~Rotation, 旋转$ o# t1 A4 f d( [0 Y+ a' A0 ?& n
Rounding, 舍入1 b# a) z& e: Z" v5 B
Row, 行
" n2 Y \7 J- H2 d8 P0 pRow effects, 行效应! t8 L2 q- ~; w) B# G+ E9 Q0 h
Row factor, 行因素
- {4 t: Z9 A; Y* O- i( T$ n/ l: aRXC table, RXC表
& h/ o! V- @0 g1 uSample, 样本
: s5 A1 l; K3 A7 y- j* \' f% {& pSample regression coefficient, 样本回归系数
7 ^$ I' o7 F- d% w' @1 PSample size, 样本量+ W/ `- `/ m0 c5 |$ _+ e
Sample standard deviation, 样本标准差
$ x7 f8 H R3 N4 m4 DSampling error, 抽样误差' s8 t+ _$ O8 p
SAS(Statistical analysis system ), SAS统计软件包
+ E- t8 n2 \; d$ m& pScale, 尺度/量表( _: z. x6 z! Y5 e5 ~: F
Scatter diagram, 散点图! ]7 W# f- T' S+ L& H
Schematic plot, 示意图/简图0 G3 Q4 Q. t7 y
Score test, 计分检验6 r6 Z+ v3 b6 m; R# a
Screening, 筛检+ C& X& Y2 e5 {9 p; Y
SEASON, 季节分析
' G- N% Q7 x Q1 Y k3 K- t/ \Second derivative, 二阶导数
0 m1 }2 ^- J# _, iSecond principal component, 第二主成分2 f( m. r" {: j
SEM (Structural equation modeling), 结构化方程模型
( ]. q( O+ E: g# @Semi-logarithmic graph, 半对数图
! b- \% o P% X& N% G3 W8 [' lSemi-logarithmic paper, 半对数格纸
1 I6 Z$ o' K$ L% K/ m2 KSensitivity curve, 敏感度曲线 [1 x; B8 U, k
Sequential analysis, 贯序分析
- F( _" q9 \) R# f( U/ CSequential data set, 顺序数据集
7 `, E& w! K1 ?3 A1 oSequential design, 贯序设计
( L7 i1 A9 C/ g; e: @Sequential method, 贯序法( P) _6 f( E! q# d
Sequential test, 贯序检验法8 C/ }/ E* q1 q( `6 H$ Z! _& h
Serial tests, 系列试验
+ P: V" q; ]# u- I! a7 I" P6 `Short-cut method, 简捷法
, R8 ~7 E& b' {, l9 z+ x& |7 aSigmoid curve, S形曲线( R' l8 L' q1 W" p. M4 {) p
Sign function, 正负号函数
$ b) G4 s: i) y4 ?) v$ T& X3 j9 MSign test, 符号检验
4 \/ u7 F) M* ~- N4 Z; ?& I4 tSigned rank, 符号秩
% @- V' n4 @/ T& P/ kSignificance test, 显著性检验' P2 m; X! q- p4 z: Z: S0 j
Significant figure, 有效数字5 _! N; F! H, V/ F" F7 o6 _5 ]
Simple cluster sampling, 简单整群抽样
- h# y l( D1 M% o$ v/ k: P+ [Simple correlation, 简单相关
) `4 n7 m7 d, s! {# [- K' \( B! w. ESimple random sampling, 简单随机抽样8 v$ v6 V0 ]4 P- O6 b
Simple regression, 简单回归
5 _7 m5 R! ~$ h6 i5 lsimple table, 简单表
' v0 z7 z, Z/ J Z _9 ?Sine estimator, 正弦估计量
: {4 O0 G7 f+ V) c! pSingle-valued estimate, 单值估计
+ D6 M9 s* `( k+ T# @1 G0 z) nSingular matrix, 奇异矩阵; R4 ~1 s$ J6 v: ^$ h! x8 y$ Z
Skewed distribution, 偏斜分布5 `! e: ?5 l: k+ X
Skewness, 偏度
2 k' `! R3 B0 c+ Q! X1 b% tSlash distribution, 斜线分布
9 F% k8 Q5 _* |$ b6 USlope, 斜率
0 L ]% q4 j1 g, tSmirnov test, 斯米尔诺夫检验
& u/ g, Y: [0 {0 a# G+ uSource of variation, 变异来源/ [4 i0 c) A0 n! S1 i7 A: C
Spearman rank correlation, 斯皮尔曼等级相关$ h9 N% Z* r7 Z# P+ A# i/ F& T
Specific factor, 特殊因子' c8 |; \( R+ h
Specific factor variance, 特殊因子方差( m+ v3 Q9 q; }, U1 K! T+ W+ `7 ]) h
Spectra , 频谱: U# `4 G6 k" O* C" v4 n8 V; P+ W: \
Spherical distribution, 球型正态分布 t' }8 {# t$ ^
Spread, 展布
1 S9 e" h( ~) H. eSPSS(Statistical package for the social science), SPSS统计软件包
- R# t9 y7 D; H/ X1 S/ u4 tSpurious correlation, 假性相关" q3 M+ g7 z' @, R% W% \" g
Square root transformation, 平方根变换4 c/ D9 v" H/ {9 u
Stabilizing variance, 稳定方差
- g( ^2 q7 W( r$ w) x' a0 XStandard deviation, 标准差
+ X* w4 n6 e6 l+ GStandard error, 标准误
* g6 x) q( j$ @) q# sStandard error of difference, 差别的标准误8 B( z% [7 H" e' i
Standard error of estimate, 标准估计误差+ X1 P% p6 n1 g- z9 i6 Y
Standard error of rate, 率的标准误5 b. w3 _/ D3 U+ K1 I' [
Standard normal distribution, 标准正态分布
4 G6 C6 z O/ M bStandardization, 标准化
$ Q+ G, G4 o. JStarting value, 起始值
/ z1 t: d) B1 ` HStatistic, 统计量) c5 D% @) b" n3 E p* b
Statistical control, 统计控制
3 k/ q: k/ `) v- n3 [3 CStatistical graph, 统计图7 q' g1 S& c7 i5 s
Statistical inference, 统计推断
/ @# U f7 B0 BStatistical table, 统计表* m) B3 u" c5 w3 `% N) a
Steepest descent, 最速下降法: C# |9 w0 ~6 H. t& q8 M
Stem and leaf display, 茎叶图
i( u8 B, j" j* y2 eStep factor, 步长因子
1 S0 I+ r# ?' b: B2 GStepwise regression, 逐步回归* C2 _( Z: ^2 e. V m3 j2 x
Storage, 存
2 C- a5 j; o( i3 z) s+ i5 \Strata, 层(复数)
; H2 s8 \5 }! o P/ D% ZStratified sampling, 分层抽样
) g% p/ j! o( j2 O: P- _- K8 aStratified sampling, 分层抽样" {( l' h% x& L% [5 {# f& T
Strength, 强度
* e) z9 }: b0 n8 E% p1 j" tStringency, 严密性
1 p3 D, r- a1 @5 Z% UStructural relationship, 结构关系
% H6 t/ Z$ y- z3 a3 j/ |0 wStudentized residual, 学生化残差/t化残差1 G' ~/ V0 |8 Q: H: U5 ^ x
Sub-class numbers, 次级组含量) t$ U! S% T1 ?; v/ E4 k
Subdividing, 分割, e6 |) K; s$ @$ R ?; s6 p
Sufficient statistic, 充分统计量
# t8 Z, o R; I) {3 sSum of products, 积和
+ a; i% @! h% \6 J0 s% ~2 OSum of squares, 离差平方和
: k$ S: ]# M$ {* }' P8 V( T9 ASum of squares about regression, 回归平方和# ]& ^ Z) L0 E; n# _( }- d
Sum of squares between groups, 组间平方和, s7 H& M/ @7 Q
Sum of squares of partial regression, 偏回归平方和
! @& g( P' Y2 X+ W4 vSure event, 必然事件* u( }2 ]. J( y6 a
Survey, 调查3 G3 I: O% h: J7 f$ S
Survival, 生存分析
' c# f7 ^: Z5 d5 K9 t$ }Survival rate, 生存率( I ` K: Q" o
Suspended root gram, 悬吊根图2 C7 ]4 m& Y0 U, R! |, _
Symmetry, 对称
y0 l" w( t$ r$ FSystematic error, 系统误差( g U( P& h: C! {+ P Q" G
Systematic sampling, 系统抽样
" T$ ~: ?8 x' t3 X; wTags, 标签+ H- W# g3 L. U) b' R3 a6 L) W
Tail area, 尾部面积
Z* a k2 Q/ v: t# q1 ?Tail length, 尾长! B, A. W4 t' P3 t! y
Tail weight, 尾重
1 l1 P. ]* c% u# Q5 C/ {9 {Tangent line, 切线" _! {# W9 b+ h, g
Target distribution, 目标分布
! ^/ H G2 p* g( nTaylor series, 泰勒级数9 n* `; X4 | ~. x# p# E
Tendency of dispersion, 离散趋势! D8 h3 C' d1 ^6 C
Testing of hypotheses, 假设检验, ^$ |6 ~: X' n
Theoretical frequency, 理论频数
& ?0 T' U; O; t# x% HTime series, 时间序列5 P0 \$ t; [ g4 h8 r" G
Tolerance interval, 容忍区间
2 M: d$ W8 j: b. Z' xTolerance lower limit, 容忍下限$ i# k7 R `) r Z$ B. D0 \
Tolerance upper limit, 容忍上限0 V" s# B2 @/ J* L! h
Torsion, 扰率
6 m' [/ q. _' b7 rTotal sum of square, 总平方和2 A6 ~* X& b2 y
Total variation, 总变异
- Q% j/ _) _# H$ V! C, ]Transformation, 转换1 r' j" g2 Q. G: B# S; ` R
Treatment, 处理5 w8 A4 [2 X; g+ V; ?
Trend, 趋势
, v& E7 ~; B; r! v! o. W7 VTrend of percentage, 百分比趋势% C* i( @% v9 B! D9 m, _
Trial, 试验1 ]; h& [6 C s4 y1 J, d
Trial and error method, 试错法* r$ I( U& u K) v1 w
Tuning constant, 细调常数
) G9 m1 k0 ?$ k- J$ C. `0 ?# x/ Z8 QTwo sided test, 双向检验7 _7 W3 J2 Y. Q
Two-stage least squares, 二阶最小平方
* k, U6 A! k {" b0 q( |% y% HTwo-stage sampling, 二阶段抽样
0 u- P* w# e. [ P3 {Two-tailed test, 双侧检验
, {# l: n0 `$ i0 g7 e: l b# v: _9 FTwo-way analysis of variance, 双因素方差分析: g: z- ^; Y0 W+ M' |9 X+ U
Two-way table, 双向表
0 U+ p. F3 e, f5 }Type I error, 一类错误/α错误
) g! s2 Q) ~! f+ H) ^6 J- @( dType II error, 二类错误/β错误
( j0 @" X5 c1 ^+ \: hUMVU, 方差一致最小无偏估计简称
# C- R; f" i5 K2 H$ s. S- k4 CUnbiased estimate, 无偏估计
* C& |8 W0 g- ] s' B ~3 ~ zUnconstrained nonlinear regression , 无约束非线性回归 M$ g+ P8 G6 O
Unequal subclass number, 不等次级组含量8 ?9 w+ X1 Q0 i4 P$ l
Ungrouped data, 不分组资料4 a/ f% I) [4 _2 ~; B5 P
Uniform coordinate, 均匀坐标
- D7 G6 P0 k3 t- C) Z% K+ ~& mUniform distribution, 均匀分布* c1 v" z6 K; d' l9 O
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
( g% B/ {# X" S4 G6 M4 RUnit, 单元1 K Q5 Y# M4 x% X5 C5 k6 X7 ^: y
Unordered categories, 无序分类% r& _9 i) a% n
Upper limit, 上限6 W, i5 z% ~; g1 N/ J
Upward rank, 升秩7 T. h% k! u: \0 W0 ?% L) A
Vague concept, 模糊概念( B- t) y9 |% U" W
Validity, 有效性- @: [$ L) B, w; ^+ \( y
VARCOMP (Variance component estimation), 方差元素估计
8 |/ w' L! {" KVariability, 变异性
; {- d. |/ B# V" IVariable, 变量' M: A9 S- @' f. b d4 f
Variance, 方差
, g7 T7 k' Y- a/ F+ Z' FVariation, 变异) H, E+ \: W) H8 K* k: H$ R: y
Varimax orthogonal rotation, 方差最大正交旋转
% {; I) K5 f. {; v% ^5 q* mVolume of distribution, 容积
" E9 a6 m4 R. V+ ~& f V: |W test, W检验
! }) ~( S" ?3 w- |( cWeibull distribution, 威布尔分布. q! N. b: ?7 P7 i( |1 m
Weight, 权数
$ i/ S1 B: U! K# |6 p* K" {8 SWeighted Chi-square test, 加权卡方检验/Cochran检验
! \) {- W I2 ]: J# A- |& Y! b( DWeighted linear regression method, 加权直线回归' s% ?& Z# A- U1 r
Weighted mean, 加权平均数
! k9 n1 _, Z/ F, t. qWeighted mean square, 加权平均方差
; f, N' s# u! {+ D. r, K p- K! d1 ~ zWeighted sum of square, 加权平方和
6 t+ x, W' M5 NWeighting coefficient, 权重系数
4 `! \& V" R( aWeighting method, 加权法
5 z+ u' I6 ~, h1 L6 gW-estimation, W估计量. b& W, c$ Z. Q" s' k
W-estimation of location, 位置W估计量! ^! W5 ]5 Y4 R2 {* F# M5 @. K
Width, 宽度2 A' C* M* ]' x3 i! \$ n5 y) M
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
: z; [" N# i6 D" b' {! Y% C6 qWild point, 野点/狂点, y+ B. m8 B8 {0 U& `) q" E
Wild value, 野值/狂值2 t2 W D4 g: K8 H W6 N7 x
Winsorized mean, 缩尾均值
8 H6 Y B2 e& HWithdraw, 失访 5 `, ?4 F0 i0 K
Youden's index, 尤登指数. \) @" @! _* t6 m& c
Z test, Z检验, @1 Z0 B1 l1 A6 v D
Zero correlation, 零相关1 g. b8 B6 B# b1 P
Z-transformation, Z变换 |
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