|
|
Absolute deviation, 绝对离差
; H, v0 V5 m5 q+ v8 S3 gAbsolute number, 绝对数6 o5 P' _( U' V+ E% b
Absolute residuals, 绝对残差) ~1 K, D3 g% u' q. d# i. N
Acceleration array, 加速度立体阵
- v e/ s% |6 F# z2 v. c& H. }Acceleration in an arbitrary direction, 任意方向上的加速度6 \# V% R, G" E% G8 z1 w
Acceleration normal, 法向加速度) `! G; d( O+ j) f* K( ~5 m% a/ n
Acceleration space dimension, 加速度空间的维数( _- X9 V: a' \: `& K& u# r7 x% ` Z8 E
Acceleration tangential, 切向加速度' o* u! b0 s" B
Acceleration vector, 加速度向量
( |9 u" z9 j \; J j# MAcceptable hypothesis, 可接受假设/ |1 n7 x4 _. A/ Z
Accumulation, 累积: M' d# ` O9 k% A. u) J
Accuracy, 准确度
& T, E+ ?$ |8 T ?8 yActual frequency, 实际频数
# ^5 X h3 ^$ V0 [; WAdaptive estimator, 自适应估计量6 C4 j1 k5 ?% Z7 |* A I
Addition, 相加! G4 ?7 F% M! J' U3 _8 |
Addition theorem, 加法定理. ]: l; y B8 a. M$ Z z$ l
Additivity, 可加性0 I5 B1 n! g! E
Adjusted rate, 调整率, b3 Z: v, U& J k
Adjusted value, 校正值
, F; O! b( L4 X' I/ m2 KAdmissible error, 容许误差
; t% H5 z" q: z" v$ H9 gAggregation, 聚集性3 o5 T6 v4 S2 a1 e
Alternative hypothesis, 备择假设
; i( q# k9 R0 yAmong groups, 组间0 v0 l7 M4 k) O9 {3 U- @& p/ v
Amounts, 总量
0 m- D1 j# ?8 l, l7 r$ [Analysis of correlation, 相关分析
U. e' c4 m T3 b: b8 mAnalysis of covariance, 协方差分析
( D! ?" Z1 {$ c9 b9 e& _+ X% yAnalysis of regression, 回归分析+ X! m0 k) S+ j8 r" t. H' T
Analysis of time series, 时间序列分析( ], N6 ?- X0 Y/ S+ D" i
Analysis of variance, 方差分析
$ Y. F, ^. k$ W8 G9 EAngular transformation, 角转换6 h% p$ u; s% O' Q
ANOVA （analysis of variance）, 方差分析3 Z$ ]9 a1 J8 A$ g% g; u
ANOVA Models, 方差分析模型
H: y$ l2 l. IArcing, 弧/弧旋# R$ _# b) ]- ~
Arcsine transformation, 反正弦变换
- f8 u0 L& `7 t$ r+ C! ]Area under the curve, 曲线面积
5 j" {& m8 R2 v1 I6 [9 y( Z/ h0 z0 FAREG , 评估从一个时间点到下一个时间点回归相关时的误差 4 L" E) K" l; D1 L7 H. _
ARIMA, 季节和非季节性单变量模型的极大似然估计 : p: x4 X* b, h {6 ]: e y
Arithmetic grid paper, 算术格纸
, U1 o, ~+ \; Z- F; gArithmetic mean, 算术平均数
/ b# X* b( [$ s/ i G1 v% EArrhenius relation, 艾恩尼斯关系% D* T) R3 Q: C
Assessing fit, 拟合的评估
2 m% j( S" N5 W( {$ w' kAssociative laws, 结合律' b; d4 a3 T* [7 n# [# B8 y
Asymmetric distribution, 非对称分布
) Z1 ?7 c% q: hAsymptotic bias, 渐近偏倚
' H" {$ R& ~" G- ^Asymptotic efficiency, 渐近效率! V- F5 w) }! H
Asymptotic variance, 渐近方差
' ~) c x! {4 G: l2 n# R7 fAttributable risk, 归因危险度
( X4 N1 x8 X1 Q4 [Attribute data, 属性资料# L8 n0 _4 Y! G& z6 [! i
Attribution, 属性5 Y; G, T, ^4 M5 l3 J, o
Autocorrelation, 自相关
9 r! W7 q4 H, \. {& {/ Q; f- L! LAutocorrelation of residuals, 残差的自相关
: f u1 W( E; }! c( G6 a2 d; [+ FAverage, 平均数
# E2 B( a) [0 a) g. EAverage confidence interval length, 平均置信区间长度& g8 F4 y. A$ D8 T
Average growth rate, 平均增长率
7 t2 b2 c: ]! O5 R! u% yBar chart, 条形图# S5 d0 I+ d) N8 }( v: f m! x8 t
Bar graph, 条形图
6 z8 k7 \1 q0 _$ a" ^" eBase period, 基期/ s, Y) J. L m5 x7 O% T. i
Bayes' theorem , Bayes定理- i. p' l, }- \, M* z: M$ g" h
Bell-shaped curve, 钟形曲线
' y* _ u& t# x4 v& SBernoulli distribution, 伯努力分布
% O! t# q8 {3 b- r W$ nBest-trim estimator, 最好切尾估计量9 n# }( Q( A4 r+ k
Bias, 偏性 P9 u9 q5 o9 {) A% Y- f
Binary logistic regression, 二元逻辑斯蒂回归; ^) O9 k: M: h0 Q
Binomial distribution, 二项分布
/ S9 ^; M; D& b1 i5 E1 \1 `% oBisquare, 双平方
3 B7 y$ }/ }3 O7 }0 KBivariate Correlate, 二变量相关# R C: p8 ^( J& ], ^+ I( l
Bivariate normal distribution, 双变量正态分布
# `4 X& {8 Z, ~3 R& QBivariate normal population, 双变量正态总体
; r0 ?/ {9 z( @Biweight interval, 双权区间$ `, T4 d2 C; c" Z$ B* P
Biweight M-estimator, 双权M估计量
P* e, k a7 |4 {% B5 dBlock, 区组/配伍组
- v6 P3 n/ U6 Q2 Z3 YBMDP(Biomedical computer programs), BMDP统计软件包+ W5 g( r! B; N! c6 s
Boxplots, 箱线图/箱尾图- P+ W( C) D" p7 g& @* \$ m, g
Breakdown bound, 崩溃界/崩溃点
3 i& G' l! R5 V% S) L( ?9 Q# ~. `& M1 QCanonical correlation, 典型相关
9 A+ A: ? V5 ?: I# d2 o6 ~Caption, 纵标目
! |$ _3 Z1 L9 h3 }Case-control study, 病例对照研究$ O1 S: N* k z( H! o
Categorical variable, 分类变量
# T$ H4 B* u5 i7 b& Q% LCatenary, 悬链线
: z: C) ^& X8 I4 U- i; BCauchy distribution, 柯西分布 d3 K$ T" h* ?5 M( i* L4 X( S
Cause-and-effect relationship, 因果关系6 y1 F1 T0 i; T# _- B, V; f2 L7 J
Cell, 单元
8 `2 O; {6 C$ A( ]Censoring, 终检
) D- r7 E( s/ {4 m- J K9 M1 kCenter of symmetry, 对称中心
" O) i6 L0 y$ _+ h* t- L8 u2 sCentering and scaling, 中心化和定标$ C: @4 e) P; A8 J+ O# T* Z' v' I
Central tendency, 集中趋势
; L5 w& }4 C6 t* HCentral value, 中心值
3 u4 Q+ Q3 k. _6 Y @CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
X! S/ {$ ~ f; OChance, 机遇
- N% X0 K ]1 h- ?, S( aChance error, 随机误差
5 [/ v1 g: W3 iChance variable, 随机变量; k: W% l3 G4 S3 q. |' U
Characteristic equation, 特征方程
6 {0 d8 U7 Q/ E5 _+ MCharacteristic root, 特征根. H& u4 {3 V0 m
Characteristic vector, 特征向量# A" D1 }+ n: a9 e/ }
Chebshev criterion of fit, 拟合的切比雪夫准则" G0 D- q$ E6 c
Chernoff faces, 切尔诺夫脸谱图
8 z, o9 K: W' E+ f1 NChi-square test, 卡方检验/χ2检验1 c5 {) S; @# }# j. b
Choleskey decomposition, 乔洛斯基分解
5 R; z" u6 z- ?* j8 I! \6 vCircle chart, 圆图
5 b+ Q* d, N/ E% u4 w& B& J/ l$ sClass interval, 组距
5 l$ ^" ^$ R' _$ {# \Class mid-value, 组中值% q6 O! ?; h4 O7 s3 p. ]! P$ u
Class upper limit, 组上限. Y9 F" G* y: f9 x7 J8 G5 y7 F$ C
Classified variable, 分类变量2 S- S8 B" K* {
Cluster analysis, 聚类分析- M9 o3 K9 o& T
Cluster sampling, 整群抽样- E) x, r1 t6 W; c' v
Code, 代码
1 Q% h5 E8 m' v7 x! O* yCoded data, 编码数据1 [& J. }7 S! m$ |9 E
Coding, 编码0 y! ^3 j+ w, v; l. a" N
Coefficient of contingency, 列联系数
$ o8 c: m# V9 h5 v" o! i8 A8 JCoefficient of determination, 决定系数
& Z( n3 T8 L3 s( nCoefficient of multiple correlation, 多重相关系数
* f4 v, A# J X, y) F) f' X! QCoefficient of partial correlation, 偏相关系数- ?) }4 q7 w" C0 N" m3 `/ I8 L( L
Coefficient of production-moment correlation, 积差相关系数
1 c/ [: c! d& x; u3 M3 Y; ]0 tCoefficient of rank correlation, 等级相关系数6 p- O( n0 d/ d( B" L- v" a& z
Coefficient of regression, 回归系数
1 P8 p1 N, }& ^( R" ^" mCoefficient of skewness, 偏度系数' f+ t# q7 M$ Z8 O
Coefficient of variation, 变异系数- g+ G# R u$ ]" Z y7 T$ T
Cohort study, 队列研究4 I6 Y9 a8 h; `; v6 q4 B; d% N
Column, 列
# f& y" s2 T4 h9 j+ J* Q/ ~ y0 C4 WColumn effect, 列效应; x9 E% h% S) n
Column factor, 列因素
# }4 j, Y1 v( m6 Y# J2 J3 E' }' ?Combination pool, 合并# }2 M3 S7 i" o8 W& Q" ^; v( d
Combinative table, 组合表 L$ U% e, {) o D# \2 X' t: m
Common factor, 共性因子. |7 x# \1 H+ j1 p
Common regression coefficient, 公共回归系数
5 H. D+ l; d2 [; U3 _Common value, 共同值
, O6 Q `" G* M! ^1 v8 N7 vCommon variance, 公共方差
e5 {/ t8 T8 s$ T, Q8 ?Common variation, 公共变异
# @" G+ e, @2 Z. eCommunality variance, 共性方差: Z: C& b! q% a k1 e- J/ `- D* i. `
Comparability, 可比性% F" a% [5 x4 Q* p3 e
Comparison of bathes, 批比较1 {0 D& n% N2 M8 Z! J/ [
Comparison value, 比较值
' k' j& ?. z" T9 v3 q3 W* lCompartment model, 分部模型) ~, u, `! z1 }
Compassion, 伸缩
! p/ ~1 r/ W! i* o5 I+ e( YComplement of an event, 补事件
0 z( r1 A5 B7 a: ^$ F7 F$ y: kComplete association, 完全正相关
2 s( v% X1 h5 I7 M9 i$ M: GComplete dissociation, 完全不相关
- b; C7 H4 b, e5 n- a K( G7 MComplete statistics, 完备统计量
8 @ y6 {2 f# l0 v- ^, g& bCompletely randomized design, 完全随机化设计" B) |# L# c+ C+ b+ A( m. K
Composite event, 联合事件0 n2 B) j2 p* m' \9 B# T
Composite events, 复合事件
2 C, H u( f$ f6 d+ L2 r0 FConcavity, 凹性+ J9 n6 m z9 q Y. a( N
Conditional expectation, 条件期望. U9 R" f8 o) ~, @2 k [5 S1 M( x2 l" Q
Conditional likelihood, 条件似然: d Y6 ~& o2 W5 i7 [
Conditional probability, 条件概率
4 L1 ]& J3 Z8 i( H+ t; @- x" r1 v% AConditionally linear, 依条件线性
2 k2 t$ p: k9 s" I \% |) }Confidence interval, 置信区间
/ ^2 b+ ~* |& } s8 S. SConfidence limit, 置信限& V9 c- N$ m' B6 d, R8 C
Confidence lower limit, 置信下限
+ F+ ^7 m: m, i9 d& v/ x: w; c* H5 }Confidence upper limit, 置信上限
! p" D1 Q6 w3 E9 O/ C6 [Confirmatory Factor Analysis , 验证性因子分析
* B5 C4 D; W6 d; N$ ?6 E; j2 o UConfirmatory research, 证实性实验研究, M" m( T8 J: t% {+ J3 f
Confounding factor, 混杂因素2 q6 S4 ~$ V9 D2 a2 j) F" E. b6 t% f* l
Conjoint, 联合分析- g/ \9 |! r9 l/ w; B9 x6 D w
Consistency, 相合性
7 Q4 o3 {' V* T* K" i0 u, CConsistency check, 一致性检验4 F+ n6 \, j+ n# e: w8 X2 [
Consistent asymptotically normal estimate, 相合渐近正态估计4 b+ Y4 ~ }9 \9 ]4 S; R
Consistent estimate, 相合估计0 U6 H. g# ` `" U1 k$ @
Constrained nonlinear regression, 受约束非线性回归5 k F% z% Y9 }/ N$ ]; l
Constraint, 约束
+ U! J. L: @: C; t" iContaminated distribution, 污染分布* x8 t1 v; H- B, {
Contaminated Gausssian, 污染高斯分布: N! _' N* N' _: s: d
Contaminated normal distribution, 污染正态分布
- q& C/ y' C9 O" o" aContamination, 污染
( [: \0 @/ ^/ L/ x" UContamination model, 污染模型
, U0 `) x$ @. `" s& X1 o( ?Contingency table, 列联表) }/ B, s/ D' B9 I
Contour, 边界线" _' x, t9 x) Z; r5 a0 V
Contribution rate, 贡献率: E; } y1 G7 p
Control, 对照) D# C' p' m' t& Q1 Q3 p
Controlled experiments, 对照实验
% d$ r# K1 L5 t& w0 \- TConventional depth, 常规深度
, E: j2 J6 a1 k6 l/ ?% }; N, LConvolution, 卷积
4 T1 l! n' m9 C6 RCorrected factor, 校正因子
% E7 v. ]$ \: F A+ zCorrected mean, 校正均值
) \; w$ V' I* o. l8 S+ `7 sCorrection coefficient, 校正系数2 ~$ W2 R' l; K7 l# q
Correctness, 正确性. K" Z2 n# ], C5 o
Correlation coefficient, 相关系数
* m7 C, j1 B3 W, w% T1 sCorrelation index, 相关指数3 G% ^8 l7 R( K& X/ E
Correspondence, 对应( I& C* j5 m$ ], d V7 n* ~
Counting, 计数
; k7 R2 @6 [1 { X3 x0 O* E/ `Counts, 计数/频数
, U5 k. _, r5 l& V7 XCovariance, 协方差( T% A# _# c( O0 u( b
Covariant, 共变 + M3 F, r- \5 R* w- k+ z( w: E' X
Cox Regression, Cox回归5 f7 |" ]2 ~$ p) M( n: R) V
Criteria for fitting, 拟合准则, ^* F+ m: l3 ]2 K) L
Criteria of least squares, 最小二乘准则9 p" O* s& U! j. m6 r: L+ N
Critical ratio, 临界比4 t* ^5 S! E' v2 {9 G5 P
Critical region, 拒绝域
: N3 M: i; ?4 |: W& yCritical value, 临界值% _' A& G4 y, [; I$ j0 C- X# F
Cross-over design, 交叉设计: |% |4 L0 [ K% ^" Y$ z& X* L
Cross-section analysis, 横断面分析% `4 M# z/ [' v2 k* k$ R
Cross-section survey, 横断面调查
) H: t$ w0 d; I6 GCrosstabs , 交叉表
# [- \5 S/ G8 W! GCross-tabulation table, 复合表# p8 f" f8 _/ Q( j: A7 w, {
Cube root, 立方根: f& Y/ [) B8 P; d
Cumulative distribution function, 分布函数% J. P" ?1 J& I* j3 C4 C+ S6 Z
Cumulative probability, 累计概率1 D: M: [; u }; M
Curvature, 曲率/弯曲7 ~# B" A8 j6 C! y- X7 Y9 K& o4 @
Curvature, 曲率
5 m! U- x5 \/ DCurve fit , 曲线拟和
' h+ F- y$ H2 L, X7 E0 b/ r& O) VCurve fitting, 曲线拟合
! w- N! M- j. D; r: C8 q/ SCurvilinear regression, 曲线回归- ^. _" d% {8 e7 Y _4 p7 i2 f
Curvilinear relation, 曲线关系
- B. S, Q# K) rCut-and-try method, 尝试法
% S8 L6 ^+ ~$ f& S; l" P) V1 m/ k8 aCycle, 周期0 ~+ [' v4 T5 ^# z* H; V
Cyclist, 周期性 q7 |, ^9 t+ q/ R
D test, D检验: W/ n) j% A+ U5 U8 Z2 K. r
Data acquisition, 资料收集
8 v5 [' y! q9 c5 S. l. _7 GData bank, 数据库1 J+ r' }& O a
Data capacity, 数据容量+ V" q+ w( |$ h1 Y
Data deficiencies, 数据缺乏5 h0 e* B# u; f. w2 R
Data handling, 数据处理4 i' a, K) q6 u% c" b r2 o) B, V4 u
Data manipulation, 数据处理, _: l( C, V3 X& p+ S
Data processing, 数据处理
9 X7 o* `3 U: q/ l E4 q5 |Data reduction, 数据缩减
" X6 G1 g+ |1 `8 q* i$ {5 WData set, 数据集& S& i/ s {/ v( |" q
Data sources, 数据来源
! @% Q0 _6 q9 M% ^Data transformation, 数据变换0 U5 X* V$ I" r: b* {
Data validity, 数据有效性
) r) U" X1 y& z6 r1 Z8 aData-in, 数据输入3 }& t. `+ a* K+ ] s
Data-out, 数据输出
9 \8 d3 `* y9 M! uDead time, 停滞期6 ~& A# q1 T- u( S) r; {8 {2 m
Degree of freedom, 自由度
/ }: L4 k4 S& lDegree of precision, 精密度
! W2 Y6 U) G& v% G' m( E* Q/ s0 ^Degree of reliability, 可靠性程度# y6 T5 y1 _: m# g1 e3 L
Degression, 递减, z9 X9 e1 a3 z- n
Density function, 密度函数! }, t6 `8 D- z* w
Density of data points, 数据点的密度8 {3 m3 v2 ?: C- k8 S
Dependent variable, 应变量/依变量/因变量 h+ k7 A8 L( k @9 l3 t
Dependent variable, 因变量% n3 |7 D( }8 p1 w8 x, N
Depth, 深度: f+ C# F- P2 |$ P' k( F: G
Derivative matrix, 导数矩阵
; ~! I4 j9 \. t2 bDerivative-free methods, 无导数方法0 Q+ j `, Y" b( z; u1 }
Design, 设计* k" t0 w% {; o/ P) U! X
Determinacy, 确定性2 p) a7 w6 i- T" l+ M3 `
Determinant, 行列式
, y- y6 C1 A9 B( @6 zDeterminant, 决定因素
' c8 B9 e% o+ t) l3 A, F+ h9 B& L2 O0 }Deviation, 离差
5 G9 [! K( U# N5 I8 d( }0 ODeviation from average, 离均差
% q3 c: L7 l( q+ p. t6 oDiagnostic plot, 诊断图4 v0 u* c0 F1 R1 L, O
Dichotomous variable, 二分变量
4 c. J, I( u- x4 t# I" MDifferential equation, 微分方程1 |( w- g- |+ x% O; r
Direct standardization, 直接标准化法5 d9 g2 w- Y- N3 P. V3 n, o1 y
Discrete variable, 离散型变量# b% X/ [; I g5 H2 f
DISCRIMINANT, 判断
( l6 q' J5 [9 z" H; x) DDiscriminant analysis, 判别分析1 N' s! d2 n, o0 r" S w3 Z
Discriminant coefficient, 判别系数
; j3 d; \: w6 J1 v5 K) |Discriminant function, 判别值
) Y4 g4 F3 L# Y* A* Y, sDispersion, 散布/分散度- ?) R8 }! @- x8 n* K4 W' Z4 `
Disproportional, 不成比例的
* Y4 K( J/ R( D' M" p9 FDisproportionate sub-class numbers, 不成比例次级组含量
- @& t" l" P1 R L: g! JDistribution free, 分布无关性/免分布
1 b; Q: t; O4 E. M( `Distribution shape, 分布形状
) @( O3 d' O% X4 A( c4 G( yDistribution-free method, 任意分布法8 s- M$ z$ j* ?9 Y& E0 @
Distributive laws, 分配律
( O7 U2 d; U" }# N" d5 ZDisturbance, 随机扰动项
! h+ J# {6 j" ]4 h" U$ mDose response curve, 剂量反应曲线: {8 t O ~: \ S! h9 @6 a
Double blind method, 双盲法" K: C: e& y3 Q8 f3 J6 X. k1 W- r
Double blind trial, 双盲试验
; ^$ k5 i1 t; J) M9 {: Y7 lDouble exponential distribution, 双指数分布
8 W6 k/ L2 _: w UDouble logarithmic, 双对数: T0 p% k7 S1 N. R# f
Downward rank, 降秩& D$ w# ^8 o9 E' f8 V
Dual-space plot, 对偶空间图
8 m' i' e Q& [, V: e( RDUD, 无导数方法
' J$ O1 k; j; V9 M5 BDuncan's new multiple range method, 新复极差法/Duncan新法. c4 R8 s5 ~ Y* u4 X) x
Effect, 实验效应5 K S z2 A0 q- H, }
Eigenvalue, 特征值
, V; I3 d. S. Z0 JEigenvector, 特征向量
+ ?4 M& J+ e/ D$ p- QEllipse, 椭圆
8 p, N2 A( D n8 u3 S0 SEmpirical distribution, 经验分布& C5 d' X! {4 ^8 K0 E+ I/ w, S
Empirical probability, 经验概率单位
- W7 j9 ^! W$ A/ FEnumeration data, 计数资料
* V6 e9 L( x# g) HEqual sun-class number, 相等次级组含量5 G( G+ W: i4 |
Equally likely, 等可能. |8 B. ^2 `/ U! r3 \" ~. ]! A
Equivariance, 同变性. I7 m" C. g6 e+ R% g
Error, 误差/错误
& U" u" [$ d! W; KError of estimate, 估计误差
5 z0 ]9 y7 b+ M% G9 F4 oError type I, 第一类错误
2 o3 c) O _; G; AError type II, 第二类错误# s9 |; T7 n" d
Estimand, 被估量0 \, B/ @/ s; i
Estimated error mean squares, 估计误差均方
; s9 x- t: f7 O. K4 y6 U4 dEstimated error sum of squares, 估计误差平方和6 }8 V" R" P" [; _
Euclidean distance, 欧式距离
1 b% r9 r9 p! i7 W9 q: V% l! N. `Event, 事件
, W% ]& B, J3 WEvent, 事件
* u$ T5 i8 H! GExceptional data point, 异常数据点
7 j: C0 J% P- \Expectation plane, 期望平面; c1 l% r9 [ _! `3 O( G1 |
Expectation surface, 期望曲面
' [: V! _. x# ~$ A% v' QExpected values, 期望值+ x# s" `# Q7 R$ V S) l
Experiment, 实验/ l% O) x$ g( C& @/ \
Experimental sampling, 试验抽样
4 m1 f: F$ Z+ S3 xExperimental unit, 试验单位5 a. s# [' I9 \1 c& w: \
Explanatory variable, 说明变量
1 w/ y7 ?' E, H3 T7 t2 fExploratory data analysis, 探索性数据分析; n- R, l! y& B9 o! u0 k1 R2 ?. v& S) F
Explore Summarize, 探索-摘要
! g1 c' j% N5 u4 J% v$ n: G5 OExponential curve, 指数曲线
6 s0 L. E# R9 @0 p# N% yExponential growth, 指数式增长
7 |6 E. m9 E7 MEXSMOOTH, 指数平滑方法 ' L8 s: j+ I2 h8 D
Extended fit, 扩充拟合
O: v5 A! X! v' `' d' A7 vExtra parameter, 附加参数
, Q. y7 E. D5 A' IExtrapolation, 外推法. y+ h/ M' J, `2 @# f" B
Extreme observation, 末端观测值1 f, _1 \# s/ x- G* |
Extremes, 极端值/极值
! w; j) T% `" gF distribution, F分布% K4 ]" ]/ L% @( g' W
F test, F检验
8 h! i% P2 K/ K- q5 s: u# p$ rFactor, 因素/因子
}# W3 L% V R6 J& z# BFactor analysis, 因子分析
4 E7 t7 k b7 I9 E3 G% j% F' vFactor Analysis, 因子分析9 J: J7 [- t s! J
Factor score, 因子得分 & ~, T/ V9 G3 g% r" |1 X( D! J' G1 p
Factorial, 阶乘
; d7 v4 l. P( d6 M, p; l" k6 x; fFactorial design, 析因试验设计& }; G8 j) J1 ]- l! H
False negative, 假阴性
- e/ b' z3 }9 T* ]. qFalse negative error, 假阴性错误9 a4 J# o! M+ R/ s3 Y
Family of distributions, 分布族
3 U0 R) J' V2 K! z, dFamily of estimators, 估计量族
4 r- h0 G( [2 q6 x2 k, eFanning, 扇面' Q' R# d4 W7 u7 u
Fatality rate, 病死率
( b" o0 H) f9 n) r: X1 K0 bField investigation, 现场调查
# I5 B5 L& }3 u* tField survey, 现场调查
+ H+ P! v w7 @4 f0 VFinite population, 有限总体! g2 r9 N, I% Q6 W) b- J! D
Finite-sample, 有限样本
+ s: D( G1 s: w# p s' ~First derivative, 一阶导数- y& n7 ^% ?+ g; C$ L
First principal component, 第一主成分5 j0 }9 w# G9 r! f) ]* f
First quartile, 第一四分位数8 [: j/ _! W( f
Fisher information, 费雪信息量1 o: c+ p9 \/ P8 R3 a6 @2 A) E: y' c
Fitted value, 拟合值
! Z0 T4 g) o+ u" r5 W* g; TFitting a curve, 曲线拟合
" f9 X4 ~5 u) j) ]0 K- o; S- PFixed base, 定基
8 F. m' P3 l. v: |' ZFluctuation, 随机起伏
% w8 h7 W- l0 o6 S' {1 K" U% NForecast, 预测
3 I; I# Z: `0 s6 GFour fold table, 四格表
) r' p# i8 S) T4 E& y/ mFourth, 四分点7 q7 }/ y/ G$ }. R4 O% R9 J
Fraction blow, 左侧比率
0 @ i3 o1 ^) R' H/ [Fractional error, 相对误差
6 W3 o" ^$ e' n- WFrequency, 频率8 r5 t& V$ i7 r; d& c3 Y. X
Frequency polygon, 频数多边图4 f- i' B/ S8 [3 K
Frontier point, 界限点
# `+ ^! W1 A+ f W. G1 IFunction relationship, 泛函关系7 l0 T/ @8 F! v Z+ Q/ W0 z
Gamma distribution, 伽玛分布9 d1 Z0 |1 ~3 A
Gauss increment, 高斯增量. _7 J3 }* A8 T9 d$ n$ ]
Gaussian distribution, 高斯分布/正态分布+ h& k: [: f( v% X$ w
Gauss-Newton increment, 高斯-牛顿增量/ ^) b- n8 H: s+ B0 k) _
General census, 全面普查+ Z- L* c: H% ~) d5 p
GENLOG (Generalized liner models), 广义线性模型
. u7 r1 s0 v2 M0 U" aGeometric mean, 几何平均数
0 |) p/ v2 q8 E7 u+ ]5 L( O" o5 hGini's mean difference, 基尼均差: L- v' T: _ R4 h9 G
GLM (General liner models), 一般线性模型
, @# R7 L( o0 k- J, S. f4 MGoodness of fit, 拟和优度/配合度
$ G' V6 p% b* G6 o& bGradient of determinant, 行列式的梯度/ G! M7 @# b! `
Graeco-Latin square, 希腊拉丁方+ N4 @* m# Z* O
Grand mean, 总均值9 I8 N2 q$ ~: w# ?" s! ~: z
Gross errors, 重大错误
+ t3 d: a& y! a% q fGross-error sensitivity, 大错敏感度
' m) `) T# M+ E2 Q! y7 z2 n, k3 sGroup averages, 分组平均
2 _/ \7 s6 B- Q3 I3 z C- h( NGrouped data, 分组资料) N, P; X* o- Z6 T* v
Guessed mean, 假定平均数
6 X0 g# B! W( _0 |$ J0 V% G- JHalf-life, 半衰期4 h4 k4 p/ V- o: V1 P! ~1 A6 T/ X9 S
Hampel M-estimators, 汉佩尔M估计量
) I( p/ b* A2 [Happenstance, 偶然事件7 h. w0 _. c" N+ d @$ o6 Y# L: q
Harmonic mean, 调和均数# f7 y) e0 V Y: W- b8 L0 Q
Hazard function, 风险均数
4 i% c/ Q# ^2 F+ X& `) C# N2 M6 ]3 `Hazard rate, 风险率
8 W' T! X9 {" q$ BHeading, 标目 5 L2 i: X8 |- J' O
Heavy-tailed distribution, 重尾分布
! `* e; O( ^- v# ~2 C3 CHessian array, 海森立体阵8 G7 H: g6 |% ?; d% s
Heterogeneity, 不同质
) P* G. O6 L7 w# _: V& ^Heterogeneity of variance, 方差不齐
) ]5 }( a" x& F' C, d3 c& gHierarchical classification, 组内分组2 U) d( G. i5 f! P2 w) {
Hierarchical clustering method, 系统聚类法
$ t4 [% o2 ]( L1 ~4 m% nHigh-leverage point, 高杠杆率点0 u* @0 L0 B5 z$ ~- a. y
HILOGLINEAR, 多维列联表的层次对数线性模型
' @( @9 }9 u$ J! nHinge, 折叶点3 u6 u8 R! v0 _: T$ _, G# H, D
Histogram, 直方图
1 R) V, F2 k+ f3 L4 T/ H [6 |. ]1 \Historical cohort study, 历史性队列研究
& V3 g7 M- |' ?# a$ Q! g4 iHoles, 空洞) A( ?8 u# `+ P* P
HOMALS, 多重响应分析
+ x( O( b9 v* J+ _0 G7 L& t7 e W. QHomogeneity of variance, 方差齐性% @" R; `; `" U8 G4 m
Homogeneity test, 齐性检验
7 _/ }3 z* r% f0 J5 \+ i1 fHuber M-estimators, 休伯M估计量! a) U: Q" _2 z& n& Q
Hyperbola, 双曲线$ E! ?" x. g; a% }" \# U
Hypothesis testing, 假设检验
7 n/ g, n+ ~$ x8 H' uHypothetical universe, 假设总体4 p, C) U, O8 T) f( }2 l2 f7 }
Impossible event, 不可能事件% x( H- l1 k1 r0 P( H# W0 D
Independence, 独立性" h/ v3 s: l5 M! Q
Independent variable, 自变量9 a l6 R/ l1 o& d# i( U
Index, 指标/指数
* r* q; m8 o+ @! n' F* ]Indirect standardization, 间接标准化法7 V3 F# r' l5 c; W# @" e
Individual, 个体
8 M5 T2 V {5 A/ C5 T% w. tInference band, 推断带
4 L& o- X ]- n( a; p- KInfinite population, 无限总体
8 @# B3 J S# _9 Y" [- N# QInfinitely great, 无穷大 {1 ^0 G' P) P
Infinitely small, 无穷小
4 p0 K6 l* `4 K! j. EInfluence curve, 影响曲线4 P" s" k& y7 t' |9 v, a
Information capacity, 信息容量
$ |9 q1 e7 n- t( u7 p, T1 k8 nInitial condition, 初始条件2 x+ S' l% T4 `/ _
Initial estimate, 初始估计值
$ a8 N; Z" O# {, a4 `Initial level, 最初水平
; t" ~: J- T N6 H& P+ eInteraction, 交互作用
2 b2 }# F4 s$ b# K: k( [; p- gInteraction terms, 交互作用项
5 b! Y* l- L" f( ]$ e# w5 rIntercept, 截距1 d$ Q1 Y. \& ?9 U
Interpolation, 内插法
1 V- ?1 ?, V# o: j, _3 OInterquartile range, 四分位距
0 {& u1 C+ H) Y+ a. TInterval estimation, 区间估计
; N, ` m. t0 u, e- UIntervals of equal probability, 等概率区间
, A+ t+ `& d0 v; ] g% DIntrinsic curvature, 固有曲率
0 a, U4 k& U. e+ n3 mInvariance, 不变性, \; m: W: K+ a, A- @& H* x ~8 ?
Inverse matrix, 逆矩阵
5 Z9 }2 R3 f3 O# {3 NInverse probability, 逆概率
" N$ e! j5 [0 _% o! j+ B, uInverse sine transformation, 反正弦变换1 E5 K. G; S, R' u8 g3 C Q
Iteration, 迭代
' I8 Z7 `! p7 @) bJacobian determinant, 雅可比行列式
: w0 j5 p0 y% r" QJoint distribution function, 分布函数" ^) W. z0 w; ~1 o; f
Joint probability, 联合概率2 t' P6 @! G: N. k: Q) B
Joint probability distribution, 联合概率分布" l% z& K- ~: O0 ~* e) n% F
K means method, 逐步聚类法0 J/ ]" b9 Y& ~1 A- U
Kaplan-Meier, 评估事件的时间长度
) A0 J) a8 O8 I5 p; bKaplan-Merier chart, Kaplan-Merier图* J1 r/ D7 @& v" h
Kendall's rank correlation, Kendall等级相关0 I" R/ v9 ?, a' B- `, V
Kinetic, 动力学
& ?+ B9 h d2 l z" ^/ F: _3 RKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
' I8 o( w/ d2 b/ TKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
/ o4 K0 x7 Q3 x3 d" A9 R. [. n FKurtosis, 峰度: _) {; E7 E- V3 D9 d
Lack of fit, 失拟
; {, j& @ i. u3 iLadder of powers, 幂阶梯
. _6 H1 [2 N' J( }: o R- `3 PLag, 滞后/ @) T# k7 D6 D$ ?+ t9 P# t0 @
Large sample, 大样本
8 t. W$ d7 b' Z: L! s. jLarge sample test, 大样本检验
! c# i9 C2 O+ R7 y/ Z& [Latin square, 拉丁方
$ c& ^/ [! ?8 B9 JLatin square design, 拉丁方设计
, \# Z1 a( N! ~Leakage, 泄漏+ n' F+ |" Y7 }7 m5 e" O5 t
Least favorable configuration, 最不利构形
4 N3 O; c) C) H/ M, T8 j9 \Least favorable distribution, 最不利分布
! T# ^! n4 @# m, v) f& }1 MLeast significant difference, 最小显著差法
. z2 w; Y0 {4 y) g% t# n8 Z7 G. LLeast square method, 最小二乘法0 [% V- ]/ Z* i) n* I& c* R# n& t
Least-absolute-residuals estimates, 最小绝对残差估计
; V# H6 F% p" eLeast-absolute-residuals fit, 最小绝对残差拟合
h7 @2 V8 k7 K6 {9 W6 x% s& gLeast-absolute-residuals line, 最小绝对残差线
9 Y% S! n; {2 _' P2 W, X3 ^' YLegend, 图例0 O/ R" b0 T( `, {% C8 @
L-estimator, L估计量9 f ]4 M, i c5 S/ l, V$ l
L-estimator of location, 位置L估计量, ~5 K- S0 ?$ C+ E1 Z' r
L-estimator of scale, 尺度L估计量; p3 W* b o+ ^9 _
Level, 水平7 \, n* \5 k0 Z h
Life expectance, 预期期望寿命. b$ \; u) m6 h. Z/ i
Life table, 寿命表! ^7 V1 y% m. d' |: ~
Life table method, 生命表法2 K( i% x- o6 o& e) A
Light-tailed distribution, 轻尾分布
9 u. l* r0 P4 `+ B3 OLikelihood function, 似然函数
O, S) N u/ }, MLikelihood ratio, 似然比: A" ?; t7 f: ^+ A" j2 b
line graph, 线图
: [/ J; [% m# \- @ YLinear correlation, 直线相关
5 j8 n3 m& V7 M, X7 WLinear equation, 线性方程2 Z' {; W/ l' @
Linear programming, 线性规划
4 x. r5 J Y' I, L" O9 {' w' T" b. A9 N2 `Linear regression, 直线回归; W* P% b' V+ ^$ g, f8 A
Linear Regression, 线性回归2 A6 S% ], d- {; s$ U7 L7 x$ U( ]. Z* H
Linear trend, 线性趋势/ Q0 b$ L9 o: U; }1 v1 g
Loading, 载荷 9 I0 z& \2 C6 J. X
Location and scale equivariance, 位置尺度同变性
& o5 R( H; O5 gLocation equivariance, 位置同变性
; V/ F! p2 z e6 S4 w$ r! ULocation invariance, 位置不变性
( g* j, P: @, F J% b( `' bLocation scale family, 位置尺度族
6 c4 h. P3 z1 a: @& \( [Log rank test, 时序检验
' t' c P" u9 E. ?) b( ^Logarithmic curve, 对数曲线& U1 D6 P7 x" C
Logarithmic normal distribution, 对数正态分布
' @5 m! A' s$ GLogarithmic scale, 对数尺度
' s! j% C3 p- J/ j5 ?& [Logarithmic transformation, 对数变换
; x+ {% y6 ^+ J# u# VLogic check, 逻辑检查
) s% p t& l& ^ I% V- ^Logistic distribution, 逻辑斯特分布
9 w8 J8 |$ k. i/ T* ALogit transformation, Logit转换
. q/ W. s. U @8 a/ d; wLOGLINEAR, 多维列联表通用模型
$ c9 @( b R: j/ d% ?Lognormal distribution, 对数正态分布
% _$ _8 n/ K& v, z0 X) P4 t8 b8 YLost function, 损失函数, `5 q% }* D; E: v9 x
Low correlation, 低度相关- }- n+ r3 a" {5 W4 \4 n; q
Lower limit, 下限
4 u2 _# {# y3 q/ b0 tLowest-attained variance, 最小可达方差
4 O, A( D( a4 p% c* r9 CLSD, 最小显著差法的简称
% @! t( F# J3 t7 aLurking variable, 潜在变量
6 Q! O$ \+ j* i' v3 h9 {: DMain effect, 主效应3 b! {! r3 v7 n* S1 ^# a) s
Major heading, 主辞标目6 v" i v6 S: t0 M C* V4 o; @
Marginal density function, 边缘密度函数/ R& \+ v R) ?4 O9 L5 r
Marginal probability, 边缘概率- I( {! v6 X+ e$ D# O, L
Marginal probability distribution, 边缘概率分布9 d. D: ?' j+ k7 I1 h! s' [
Matched data, 配对资料6 L9 I* W4 i! ?, O: ^, f8 S; E
Matched distribution, 匹配过分布
0 T0 P4 X- a* d$ k$ C7 JMatching of distribution, 分布的匹配
5 _) K0 C, Q( M% uMatching of transformation, 变换的匹配0 U1 k. b* x/ h* p/ ]% u& s
Mathematical expectation, 数学期望& J" _3 |5 T4 w) _& u; L
Mathematical model, 数学模型. |! ]3 x6 ^2 N
Maximum L-estimator, 极大极小L 估计量
: p" M' X/ l' g' o5 ^9 @$ r% wMaximum likelihood method, 最大似然法+ Z! \9 [* K% `/ Z
Mean, 均数" x) r6 S: U& G3 x3 ?; t1 E$ h
Mean squares between groups, 组间均方. c2 a# M" ]1 j9 V% [3 p+ Y
Mean squares within group, 组内均方
: G# b- F- j0 \, W* p! G dMeans (Compare means), 均值-均值比较
# q1 ^) T5 q" \$ b5 g- \- g/ b2 PMedian, 中位数
/ |/ [2 n/ x4 g* n% D" U1 vMedian effective dose, 半数效量) c! O& F2 m' O7 F. @+ L0 S, ]
Median lethal dose, 半数致死量
0 M" c0 g: N& GMedian polish, 中位数平滑* m3 v# M0 Z7 }3 `
Median test, 中位数检验
& E& i! M6 Q% @" g- S8 sMinimal sufficient statistic, 最小充分统计量
& `/ m/ R& c* i+ a; k" FMinimum distance estimation, 最小距离估计8 y2 Z! t; Z- L( G1 x* g) D
Minimum effective dose, 最小有效量1 y* U( _7 Z5 C. x) b2 \
Minimum lethal dose, 最小致死量3 S& K8 x% n. J' ^. |- W' I
Minimum variance estimator, 最小方差估计量/ N/ i9 i7 D, s4 J r! k
MINITAB, 统计软件包3 Y, ]7 F! n9 t2 x, A3 Z2 N
Minor heading, 宾词标目3 X' t: @! g+ O X
Missing data, 缺失值
3 F* ?% K3 w5 }/ k5 c0 R3 JModel specification, 模型的确定( \) X. E8 r2 k1 c
Modeling Statistics , 模型统计
! |2 ]- H" ?" VModels for outliers, 离群值模型4 U" Y( L- ^& ?- I% A! @
Modifying the model, 模型的修正8 t( M# _& Z4 u- _
Modulus of continuity, 连续性模
R% b! \. Q1 ~6 ]8 V) r( q5 d4 XMorbidity, 发病率
I1 {$ O3 ^) a: r& A9 |( m& ^- SMost favorable configuration, 最有利构形
% g8 D( }# J. R3 a$ `( _ R! | QMultidimensional Scaling (ASCAL), 多维尺度/多维标度
; X1 ]! Y) n" r; I$ O* WMultinomial Logistic Regression , 多项逻辑斯蒂回归& f% y; a- c3 s; E% H
Multiple comparison, 多重比较
1 b2 L1 J7 B! \2 {) V8 m; g6 X9 AMultiple correlation , 复相关
1 _: _3 t+ L! YMultiple covariance, 多元协方差/ I: s; \7 K* Q
Multiple linear regression, 多元线性回归
) ]3 ^- u7 l. E& Q ]Multiple response , 多重选项
% m3 }: {# l KMultiple solutions, 多解
% M; `8 j2 ]* q0 zMultiplication theorem, 乘法定理
, n5 t& n6 s; \0 v& FMultiresponse, 多元响应
0 R' D9 h9 q/ ^$ kMulti-stage sampling, 多阶段抽样1 G+ M/ W3 y% M1 J/ U- ?
Multivariate T distribution, 多元T分布" ^' C. Z& Y/ e7 V. o- g
Mutual exclusive, 互不相容
- h4 @$ | p# w k/ V i* \Mutual independence, 互相独立
; T& l( \2 }) B+ X- g* ?2 sNatural boundary, 自然边界/ ]4 A L7 {# g" U. g* B* P# R
Natural dead, 自然死亡9 i8 R3 b1 D! y7 ]: D7 A- x- ^
Natural zero, 自然零
& e9 _; a, } Y2 O/ x# S6 FNegative correlation, 负相关
; R" h, L2 m$ i& H6 JNegative linear correlation, 负线性相关& g; @: u7 {' \
Negatively skewed, 负偏) n5 J% T5 K8 R- h. v& }8 j
Newman-Keuls method, q检验
2 S7 q, {$ K) c% v# QNK method, q检验" e) k+ @% g3 l6 ], z3 D
No statistical significance, 无统计意义
0 |+ k C" N' Q, d! rNominal variable, 名义变量
) X5 Z# w( Y) m2 U' XNonconstancy of variability, 变异的非定常性
( ]: U& @8 ~' CNonlinear regression, 非线性相关0 X0 J/ |( l+ n5 @8 R
Nonparametric statistics, 非参数统计
- P& B M1 B+ ^8 R& ]8 DNonparametric test, 非参数检验4 u& {) H, X9 X, K' t
Nonparametric tests, 非参数检验8 u9 P3 _! Z8 n8 t" V- h8 X2 y. e
Normal deviate, 正态离差% S; ]6 c. j: A
Normal distribution, 正态分布
7 i, E: E( `1 t0 {+ ?0 ^9 b+ ENormal equation, 正规方程组$ ]0 @+ q o; K# r8 B
Normal ranges, 正常范围
0 e8 i! x! |, J* NNormal value, 正常值" M' h0 p% h/ H7 N2 j8 f
Nuisance parameter, 多余参数/讨厌参数
3 b3 P& ^( z5 L: P/ f" E7 wNull hypothesis, 无效假设 . M& F& G) J4 @' p* U1 c
Numerical variable, 数值变量
4 Z7 d' {) |2 X0 PObjective function, 目标函数5 U. k1 M) V; a+ Z; x3 B J+ s
Observation unit, 观察单位
7 o Z# d3 G! T3 w y3 H- ?Observed value, 观察值
, F0 Z4 ]9 W0 a: e* K2 {$ j, mOne sided test, 单侧检验
6 u+ J# z- T8 }4 uOne-way analysis of variance, 单因素方差分析4 r! @+ P `/ p, l6 v9 Q
Oneway ANOVA , 单因素方差分析
7 n7 w$ n7 R) e- v/ B9 o* KOpen sequential trial, 开放型序贯设计1 M t+ P% w; \9 _7 m: D
Optrim, 优切尾
/ Z3 c1 {: _# hOptrim efficiency, 优切尾效率
* D$ ]$ |' k$ Q/ ~/ w8 GOrder statistics, 顺序统计量) X4 ?/ y# o! P5 o2 @
Ordered categories, 有序分类
v! \ b- ?* ^2 s+ z6 W2 QOrdinal logistic regression , 序数逻辑斯蒂回归
' R7 S) k, G1 H7 L5 L% N5 Z. dOrdinal variable, 有序变量0 O$ ?2 w( V5 `, c) |8 f v
Orthogonal basis, 正交基
; S0 Y; c% z# [6 j4 Q3 GOrthogonal design, 正交试验设计9 O, j' `8 C4 K7 \% F* L( @
Orthogonality conditions, 正交条件7 m( S5 j: s: @" f
ORTHOPLAN, 正交设计
" I1 l. D( T h4 o! UOutlier cutoffs, 离群值截断点
3 m: L* W/ t! s" mOutliers, 极端值. l& T, v# s" m
OVERALS , 多组变量的非线性正规相关
' x& k! a% }0 m5 p4 COvershoot, 迭代过度
& t$ V! z% @! e% G+ r! o4 ?+ k* zPaired design, 配对设计% s, I% w9 `, l2 i/ C
Paired sample, 配对样本
$ U& ]' o: s/ ]3 q4 TPairwise slopes, 成对斜率. d% m+ h. E5 h& c! \
Parabola, 抛物线- L; D9 Q# c4 F3 a5 E
Parallel tests, 平行试验
* F2 w; ^! A& X- ~7 uParameter, 参数) u$ j+ R+ C) a$ |
Parametric statistics, 参数统计
* v7 {( |: f6 B9 c y* l& \$ T; y9 QParametric test, 参数检验
4 O Y) k* N3 ~4 ^# n; \2 APartial correlation, 偏相关( C& l# v {' Q( o
Partial regression, 偏回归
* ^0 l" [9 g2 s7 U- x4 c1 HPartial sorting, 偏排序
( n# b/ C. W/ i w/ j5 PPartials residuals, 偏残差& r6 | V0 U2 J; ?) E: ^2 Z/ {
Pattern, 模式
3 }4 |2 p8 a' g7 {Pearson curves, 皮尔逊曲线
4 w9 b0 A, b. w1 r( J/ QPeeling, 退层8 T/ f, G# G' ~7 }" h
Percent bar graph, 百分条形图* |* c/ \( U( `9 Q
Percentage, 百分比5 j* O3 y) n0 G7 E
Percentile, 百分位数( A- ~: g% {/ }- a8 S
Percentile curves, 百分位曲线6 x- t3 q( U/ ?+ c5 z0 f: t$ n
Periodicity, 周期性0 \( b; I+ {! O O9 z x
Permutation, 排列
( q. U& z! {8 K! o1 X7 RP-estimator, P估计量" s1 j6 i# w Q7 h
Pie graph, 饼图6 h; p7 n9 }, ]) k/ l; j7 a
Pitman estimator, 皮特曼估计量
, S9 k6 G" o- C' O" Q& \- K" uPivot, 枢轴量
: Z: F. H$ l1 ^% H1 H9 zPlanar, 平坦
4 ^, a8 B: j6 S7 B# Y2 N4 gPlanar assumption, 平面的假设0 G- a6 [7 n3 C1 M+ b9 j
PLANCARDS, 生成试验的计划卡
1 ?+ w5 h o. bPoint estimation, 点估计
% m0 m4 a7 w' }) F4 [2 XPoisson distribution, 泊松分布) N4 [. `) d, }! `& y
Polishing, 平滑
/ g2 r6 r" S* X) k: ^! T& CPolled standard deviation, 合并标准差, l" y s+ p! _6 `+ \2 C& y
Polled variance, 合并方差
( p8 o! j; ^/ Q+ J; _Polygon, 多边图( S1 S# u, J- ~6 e
Polynomial, 多项式" Q- ] K' N8 V4 F* Q, W: {
Polynomial curve, 多项式曲线, C: f7 ~! ~2 N. S
Population, 总体* g$ y! } D1 Z: _/ s. A' Z
Population attributable risk, 人群归因危险度4 S6 `8 w Z; x* i; z' b/ e
Positive correlation, 正相关! l4 K: G# q- T0 H( D8 C
Positively skewed, 正偏' Q6 j4 B+ e9 `* G0 z( h3 y& n
Posterior distribution, 后验分布% j8 ~) g3 ~6 o: V
Power of a test, 检验效能; _( ~' u3 o7 Q/ q6 H2 ^
Precision, 精密度
# n; i) ~/ o1 N+ }0 S6 j5 l6 IPredicted value, 预测值
8 H, i3 f8 N" X4 ?1 Q/ b RPreliminary analysis, 预备性分析
( @2 u) A" i* g V% V* pPrincipal component analysis, 主成分分析
4 G9 |8 g: j7 \8 _, p; e4 c% NPrior distribution, 先验分布
; b- G5 v# P7 c0 X& c E+ a9 cPrior probability, 先验概率
7 I6 H6 l4 o+ Z# vProbabilistic model, 概率模型* K. U3 S1 P; ]* |0 W
probability, 概率
7 @* ~5 N! G8 b) N% x. uProbability density, 概率密度1 ?. p1 T% e, L5 u0 A, `9 ]
Product moment, 乘积矩/协方差
9 V! c( d2 b4 L4 C# Y6 R8 Z1 _" q' VProfile trace, 截面迹图: I( q. b1 U' w# ~" t \4 h
Proportion, 比/构成比) Y/ |( [3 H( L4 D
Proportion allocation in stratified random sampling, 按比例分层随机抽样
, {* A8 p i& }+ EProportionate, 成比例
6 j5 t& n5 P& e- jProportionate sub-class numbers, 成比例次级组含量- L0 c+ m, g- E" M* q/ s9 ?( Q
Prospective study, 前瞻性调查
% c3 E4 k$ i2 b/ ?* \, t% X5 UProximities, 亲近性 ^% X) ^# r+ J9 s9 j! v
Pseudo F test, 近似F检验
0 A) V g" b/ A" b8 dPseudo model, 近似模型8 p7 l7 R' C1 z) c. `- M9 |- {# Z
Pseudosigma, 伪标准差
$ [( D5 c% Q2 VPurposive sampling, 有目的抽样
! t% \# ~6 m9 Z, sQR decomposition, QR分解
6 b$ R( Z2 _4 z3 c8 H9 P1 |3 WQuadratic approximation, 二次近似2 F: [, A5 J; K6 I2 B! r9 Z
Qualitative classification, 属性分类
- N: t' J3 E. S3 a7 M; GQualitative method, 定性方法8 ]3 o( x h k/ H9 `5 [4 n
Quantile-quantile plot, 分位数-分位数图/Q-Q图
c5 L/ h1 |& D yQuantitative analysis, 定量分析
; l- H% Y. V+ a8 D d) MQuartile, 四分位数" y9 T: ]0 m4 i/ u$ @% k! t, z
Quick Cluster, 快速聚类
# y3 i0 F7 V3 k7 S4 Z) [Radix sort, 基数排序
; u$ H' T2 L! w: ~: X; @1 TRandom allocation, 随机化分组5 ^: L! M! m: ^4 w+ B; }
Random blocks design, 随机区组设计
+ y2 z; N8 E4 u5 t; y) \Random event, 随机事件
2 d* f8 n7 z4 i# g9 a% PRandomization, 随机化
% S+ p/ O0 }0 O7 g& y% ZRange, 极差/全距
# h. e0 {% L7 h6 jRank correlation, 等级相关, P/ ~* f2 V- c3 p" ?
Rank sum test, 秩和检验
% @9 j/ Y9 M+ `9 a wRank test, 秩检验
. X* ?' ^4 y2 T( eRanked data, 等级资料
- C8 r# a$ s4 K) \# n% VRate, 比率3 H: v, ?! n2 G- D/ T# A" S
Ratio, 比例
% I E t) r7 ?% R9 E6 ]- O! c" K% tRaw data, 原始资料
9 L5 U% E( M7 K. u9 q; ^Raw residual, 原始残差
0 e+ D3 Z/ q& I- K- v' n7 c! MRayleigh's test, 雷氏检验
( j4 X$ V0 P( c" qRayleigh's Z, 雷氏Z值
$ r- o: P7 T! }% d+ j& x- E! [Reciprocal, 倒数
7 @( U5 S# ^3 @0 G: FReciprocal transformation, 倒数变换
, o' r2 K; m: j2 |5 K# YRecording, 记录& U4 E9 d( `/ C' V, V% `
Redescending estimators, 回降估计量
1 Z8 G, ?" h. H) Z8 |Reducing dimensions, 降维% r2 b6 ^; [. w) V5 u- v
Re-expression, 重新表达+ m, z0 k4 ]; e, J# j
Reference set, 标准组
$ e$ {, w4 g8 |Region of acceptance, 接受域 |; l% y/ {5 Y# N' E' a) A# m
Regression coefficient, 回归系数/ o5 } o+ b6 A5 j# k! I! s6 c x
Regression sum of square, 回归平方和- ?6 E9 r4 O; G+ f( X
Rejection point, 拒绝点: T7 G e. P3 u5 C C0 c& l: o: ~! I* c
Relative dispersion, 相对离散度
# r' h4 W. j" f: V" oRelative number, 相对数
6 @0 d; }( g( oReliability, 可靠性2 {3 A1 m# z; P% T& @
Reparametrization, 重新设置参数. I$ A1 G+ N# D2 Z4 k6 j- U0 l7 m
Replication, 重复6 n' e+ m& o: Z( r$ J
Report Summaries, 报告摘要' v9 u: N. [' @4 }# D& d6 b
Residual sum of square, 剩余平方和
3 u" W; f8 H. Q+ ?& K- iResistance, 耐抗性
+ E1 Z: L; q4 @4 N dResistant line, 耐抗线
+ F# p7 i0 U# m, \Resistant technique, 耐抗技术
# J9 x0 e3 b' v4 N- V- \0 Q: W- IR-estimator of location, 位置R估计量' j. o) I8 y( I8 s
R-estimator of scale, 尺度R估计量/ U5 p) m) Y3 R5 p( o
Retrospective study, 回顾性调查4 Q1 J& t/ V7 o6 p6 o! j
Ridge trace, 岭迹
! \& s7 s) _3 s; ARidit analysis, Ridit分析
4 X) j! I. I B) aRotation, 旋转
" e2 I& m$ I; [9 dRounding, 舍入
" y1 ?' k+ c- K* r6 T* tRow, 行6 [3 r7 l; v R
Row effects, 行效应& z5 I7 g, h( T1 U; V5 q* L
Row factor, 行因素- |) g' X! [2 @7 W: d
RXC table, RXC表) S' F) p7 U4 ]9 e+ s; Q
Sample, 样本2 R; O3 f- p" z4 n
Sample regression coefficient, 样本回归系数
: @/ L* L( U7 P7 N8 o/ RSample size, 样本量
4 T9 j7 G' j4 H/ w# ^$ a1 HSample standard deviation, 样本标准差
8 z* _4 u/ ~$ W' i2 g& @$ \Sampling error, 抽样误差
' ?* Y: |; D* f2 J6 P9 OSAS(Statistical analysis system ), SAS统计软件包
2 o0 S; z) m0 x5 q- m0 v) ~Scale, 尺度/量表
# Z5 `" ]! D: @& D" a1 sScatter diagram, 散点图
# c Y7 y( ]# d$ o2 _$ J# lSchematic plot, 示意图/简图+ v3 P6 w: a' v; F# F
Score test, 计分检验
. B9 g% b1 X/ u: H* k3 vScreening, 筛检
/ Z% C8 x4 p$ ^( WSEASON, 季节分析 5 u+ s" L% {6 M: E8 X. C* g1 N
Second derivative, 二阶导数/ I+ Z* ^; _6 C- r. G4 W
Second principal component, 第二主成分" D8 l0 d+ X/ ?# n
SEM (Structural equation modeling), 结构化方程模型
4 g7 l" M# O5 m4 RSemi-logarithmic graph, 半对数图
0 A8 ~$ t/ E5 `Semi-logarithmic paper, 半对数格纸
0 B }, R2 _3 r0 s4 u1 f+ s4 lSensitivity curve, 敏感度曲线$ b$ R$ P+ z- n/ P6 ?
Sequential analysis, 贯序分析: T- l: _' p4 @7 w3 e1 _, |8 o$ O
Sequential data set, 顺序数据集9 x2 j e0 h/ E4 T
Sequential design, 贯序设计
% v' V. t2 J6 tSequential method, 贯序法0 S$ h8 X" ?2 s* ]/ n V m
Sequential test, 贯序检验法: ^/ b8 D+ N2 o" ~9 I3 Z
Serial tests, 系列试验 K/ w2 _3 K- e' s' d% z0 s ~
Short-cut method, 简捷法
5 y- F9 @' F( q! R! M4 |Sigmoid curve, S形曲线: k9 j" k3 u+ W! K/ j. j% V
Sign function, 正负号函数
9 m& c, x9 o0 U# C/ [0 r& ]Sign test, 符号检验
' \7 n. \; d2 R; n$ @* m3 O+ ^: ESigned rank, 符号秩
7 ~! e9 H0 b& N9 LSignificance test, 显著性检验
! q4 p7 Q" W' gSignificant figure, 有效数字; p! O8 Q# d! i; V$ _
Simple cluster sampling, 简单整群抽样
6 C% n! {! L6 I. [) ESimple correlation, 简单相关- r+ e1 c! F0 ~+ Y/ A
Simple random sampling, 简单随机抽样0 Y+ X! U! h+ m
Simple regression, 简单回归
' v3 c4 d0 U% ?4 D- g$ Tsimple table, 简单表
q' U1 G" v8 d3 wSine estimator, 正弦估计量 ^& @3 z/ W1 N& h. X
Single-valued estimate, 单值估计
7 F0 P5 z* h. U O) I, P* W7 oSingular matrix, 奇异矩阵9 z* a4 k# c0 M, z$ B: F
Skewed distribution, 偏斜分布
5 ^+ b8 [: y' S7 P) V( y5 D8 {Skewness, 偏度
3 E$ E0 W6 _3 zSlash distribution, 斜线分布8 m: [" F: J: A4 B, m
Slope, 斜率
1 s0 \7 m, |9 x8 k% Y8 {! rSmirnov test, 斯米尔诺夫检验( L5 w; O9 x) D9 c" T- g+ q
Source of variation, 变异来源
$ V* i8 q2 K) F. S2 WSpearman rank correlation, 斯皮尔曼等级相关
( G- N3 O! s* U$ USpecific factor, 特殊因子8 ~1 a9 x& p% {3 i# V
Specific factor variance, 特殊因子方差% c6 |7 N8 \8 A& C7 N$ A* L2 s( v* r
Spectra , 频谱
0 p1 ~6 C6 p- o" |1 q" y- ~Spherical distribution, 球型正态分布
/ k% l$ b! `& o3 q; E' y7 a* wSpread, 展布
9 F' o# U: l8 l3 }6 L, YSPSS(Statistical package for the social science), SPSS统计软件包' C! P9 |; a2 s. G( J! n# J3 G/ ]
Spurious correlation, 假性相关
1 ?* q9 k8 G1 |% @8 A& C8 @Square root transformation, 平方根变换
8 w( u/ W3 M5 n: A8 s5 k- o4 kStabilizing variance, 稳定方差
. I& I4 U1 T. dStandard deviation, 标准差! |- I3 S3 A& B$ S4 M$ u2 t& Q
Standard error, 标准误+ z, V! c5 j+ }! ?
Standard error of difference, 差别的标准误
9 ^+ {+ x- P: ]% a, EStandard error of estimate, 标准估计误差! Y! t/ ^4 a! m( _# D- s
Standard error of rate, 率的标准误
9 N* `' v8 U d* V: s" l7 `6 SStandard normal distribution, 标准正态分布3 w/ r$ D# r8 I+ |4 v
Standardization, 标准化( F) ]/ U9 o! w% E* n0 F
Starting value, 起始值4 C4 X$ B2 ^8 F: Z
Statistic, 统计量7 Q! ^9 r7 g; M- S
Statistical control, 统计控制
5 s: {3 f) z8 o7 ? bStatistical graph, 统计图
5 i7 J- u: D, ]' B1 CStatistical inference, 统计推断
% c. }+ m! L) ^+ V7 [Statistical table, 统计表
- q N" m0 U. t3 k1 e# m3 E( H) gSteepest descent, 最速下降法7 n A8 f0 C/ \; f- W/ F; s" V
Stem and leaf display, 茎叶图
& h6 _: B a P' m6 o: j. ^Step factor, 步长因子
' C. d7 T- T. O" E: N( H, A' GStepwise regression, 逐步回归
& `5 Y5 w1 A' ]8 z" n# U2 sStorage, 存
/ N; I' [7 P6 ^Strata, 层（复数）
. c+ g" R0 Q2 @: D9 c! }' zStratified sampling, 分层抽样; \! o5 [5 i5 j7 w2 W
Stratified sampling, 分层抽样
e* @ H0 I) c- q7 y8 h- i$ GStrength, 强度. Q! I! e, Q, L1 r+ {
Stringency, 严密性
* C& B0 B" @. E% q% `3 C* ^4 U+ ZStructural relationship, 结构关系2 S: t. |5 \& J! a' Y1 h( q
Studentized residual, 学生化残差/t化残差& Y, O) H+ M2 q& N) f
Sub-class numbers, 次级组含量
6 l2 f3 D4 @6 CSubdividing, 分割% y8 D+ m- l; w7 b6 I( h, M
Sufficient statistic, 充分统计量7 v$ b' a2 n+ D: v
Sum of products, 积和
- `8 L( A' k. j% o7 ?+ _+ J, l# dSum of squares, 离差平方和& V6 J; {; B6 J0 p8 L
Sum of squares about regression, 回归平方和0 ?; I" m% W% D7 T, H/ ?
Sum of squares between groups, 组间平方和' P' k& K! h( i8 @& B) f
Sum of squares of partial regression, 偏回归平方和6 w; H( D4 ^- A5 h& }2 T, H2 E
Sure event, 必然事件' ~' O* R2 n; J
Survey, 调查
6 F0 q, ?, z+ k1 A, F! V% j: ESurvival, 生存分析4 X8 m) ^4 F0 s5 Z% _
Survival rate, 生存率
5 h4 @8 O9 f( j) i, R5 WSuspended root gram, 悬吊根图' W! W8 x0 Q: g; @
Symmetry, 对称2 |( l$ @0 p( f8 H3 D" ~- h
Systematic error, 系统误差
, {) ? m) B, D% x WSystematic sampling, 系统抽样
9 M3 Q6 F3 I7 L. @9 }Tags, 标签
% c0 f" Q4 F. a" G! w# FTail area, 尾部面积2 N2 d2 U a3 l4 l7 Y: r
Tail length, 尾长8 e' Y. r8 C2 z# {
Tail weight, 尾重
' v4 z# Y# i `( _# y1 k6 WTangent line, 切线
8 G6 \% B! K+ X* ?8 a; V1 pTarget distribution, 目标分布- t' B, {" D# I' L% ~- X
Taylor series, 泰勒级数1 ^) k& C( V' x% a4 z7 b
Tendency of dispersion, 离散趋势
$ ], z$ O* W. U$ N6 lTesting of hypotheses, 假设检验
' y: }2 {& `' ^/ |& d1 FTheoretical frequency, 理论频数; i% U5 c2 Q4 S5 w$ t/ x8 E
Time series, 时间序列
# Q. T2 H0 }6 s+ w+ YTolerance interval, 容忍区间( B6 O0 J# R, ?' U* n* P# y, `
Tolerance lower limit, 容忍下限
/ H. L. s8 b- R( r* T* D; \ y0 VTolerance upper limit, 容忍上限$ D; D- V) _' u& r
Torsion, 扰率& d# H4 Q* ?: R! Q) r' I6 h0 ?
Total sum of square, 总平方和% p' f% u! r! A; o
Total variation, 总变异4 A+ w' q1 G$ p& `2 t2 B
Transformation, 转换
& e* p! M- |* A8 V& {. j+ N* YTreatment, 处理) X- g9 O* g$ W$ f1 ^0 y# @) k- H) L
Trend, 趋势( u0 z" s O2 C% e0 r( I) i; T
Trend of percentage, 百分比趋势
8 q) J' S8 }+ o3 Y" `Trial, 试验
" q# O( d Q/ H* ~$ rTrial and error method, 试错法
4 V% Y# w9 `. C6 c' p) ]Tuning constant, 细调常数9 G }2 z3 s& F0 X/ L8 w
Two sided test, 双向检验% l1 P- @ @/ ]( h0 A
Two-stage least squares, 二阶最小平方! i- S) L2 E" j) G# n3 _
Two-stage sampling, 二阶段抽样
5 |, l; z* v- ~5 k9 |Two-tailed test, 双侧检验. _/ C. B% _7 L" e$ D
Two-way analysis of variance, 双因素方差分析 y; Y8 {! m: }* {5 a
Two-way table, 双向表
' N$ r( a! J! Q; Z) \2 U. [Type I error, 一类错误/α错误' `! v+ L ?( u: \ e( g
Type II error, 二类错误/β错误
' U3 s4 f+ o( L( S" L% `' V5 h7 |UMVU, 方差一致最小无偏估计简称
1 v! L# A+ Y- r% d/ V/ x9 PUnbiased estimate, 无偏估计
8 }; X- g z7 yUnconstrained nonlinear regression , 无约束非线性回归4 S6 E; X( W0 W2 I0 o7 T
Unequal subclass number, 不等次级组含量
) \, K1 ^1 d5 W) E, y. \6 ]Ungrouped data, 不分组资料: B- _6 N' T7 N* X
Uniform coordinate, 均匀坐标: \3 I0 @! o: B( j1 f( z( t
Uniform distribution, 均匀分布 c4 ~& K! n( ? W4 x" @! \- b
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
7 u+ e" F$ J* Y+ n4 uUnit, 单元* z0 O5 `; a9 ^
Unordered categories, 无序分类$ b* W9 e5 _6 W- w9 C- x9 |- D& M! X
Upper limit, 上限
' ^- I$ {; D: x/ BUpward rank, 升秩
% U8 }' F# L5 r8 T, tVague concept, 模糊概念
% \# A( ~1 l/ v5 lValidity, 有效性
2 t# y7 Y, y3 {VARCOMP (Variance component estimation), 方差元素估计
1 w8 P: e" o; f$ e1 v- SVariability, 变异性
% a4 n& `, l6 ?2 @6 NVariable, 变量
' `3 S# [) J* U& ~% HVariance, 方差# j5 n8 v6 Y) `+ x* `5 t; K j+ m
Variation, 变异) i% K$ l1 f, V7 e, C+ Y
Varimax orthogonal rotation, 方差最大正交旋转
, @2 \/ }% a/ R; k. v2 dVolume of distribution, 容积/ t e: ~* \1 d3 g2 M
W test, W检验/ C( d1 M0 O/ S2 w2 p9 K
Weibull distribution, 威布尔分布* ?# \- O& r% {2 e. y, q
Weight, 权数
) {& \# B/ H+ W0 fWeighted Chi-square test, 加权卡方检验/Cochran检验
+ D+ i% f% G. o$ OWeighted linear regression method, 加权直线回归
7 [8 B# ]4 h: V% T' ZWeighted mean, 加权平均数
4 v8 I1 z: v4 w# x( L( s- c6 yWeighted mean square, 加权平均方差2 S( k5 h0 K) z
Weighted sum of square, 加权平方和
, F2 {' }, s4 C2 s4 n' TWeighting coefficient, 权重系数6 o8 M7 j3 n7 ~' m+ u3 L+ z e
Weighting method, 加权法 / d: W/ S. j' L* e0 ?9 `, q- B
W-estimation, W估计量
# v# \+ D, ^5 Q/ W t3 k' HW-estimation of location, 位置W估计量4 Y4 g6 A- `. t; e2 q7 r" S
Width, 宽度) g+ n, l0 j2 y) y/ F
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验1 `4 ?% e6 @( Z4 D( X/ C1 o
Wild point, 野点/狂点
/ `- A6 z: L4 C# vWild value, 野值/狂值) @% Y4 R1 \, X+ _& i/ P
Winsorized mean, 缩尾均值# ~: h8 | a8 y( m; b, \$ O% D
Withdraw, 失访 1 p. {" ]8 }6 ?* N
Youden's index, 尤登指数
- v1 }+ Z9 P2 ZZ test, Z检验- Z0 |) W$ |. j9 P9 d* v/ Y
Zero correlation, 零相关2 b; q% L0 S: s0 P; Y( y1 `/ `+ [6 E
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
