|
|
Absolute deviation, 绝对离差
% v* ?2 L0 c j, O; Z) `8 N3 w: A" MAbsolute number, 绝对数
* t- d- y* R1 J9 ~! {: T: {4 `Absolute residuals, 绝对残差
% s! q$ x+ ~ v# i: KAcceleration array, 加速度立体阵, E. b0 l( h2 q0 x7 l& z3 Q
Acceleration in an arbitrary direction, 任意方向上的加速度& T% w3 n; H. N& ]2 C, \8 K+ N" u
Acceleration normal, 法向加速度/ k6 M' d0 j4 a1 V& |" v! B0 j
Acceleration space dimension, 加速度空间的维数
3 Z7 i3 W5 Q% x) t7 s- bAcceleration tangential, 切向加速度8 v5 s5 I& b' e# E( {$ I1 K
Acceleration vector, 加速度向量4 E# h. `. o/ f; d* g8 O
Acceptable hypothesis, 可接受假设
) C" B' J1 F, E6 V' ]$ b+ Q# c7 O* ?& VAccumulation, 累积
5 n6 r+ } R8 k/ a& @Accuracy, 准确度
( S3 e3 M( {, q- m* KActual frequency, 实际频数9 _% w! d* f q; l' U
Adaptive estimator, 自适应估计量4 t. z: L8 O+ {& Y4 D, v* F; b+ ^$ c
Addition, 相加8 K2 [' m+ o m
Addition theorem, 加法定理3 n- g3 ^% a5 r J0 B4 p
Additivity, 可加性: x' m) W* Y" H; ]) [) F( _& c/ u
Adjusted rate, 调整率
% ]5 C( ]# j1 t7 M8 q" qAdjusted value, 校正值: E8 y" Z8 C- _, d
Admissible error, 容许误差
5 D; a/ o. [: u: T2 p2 [5 eAggregation, 聚集性8 M3 L; T% C2 [$ p3 O3 Y
Alternative hypothesis, 备择假设
0 m, `! P+ M" |8 b7 E- |" e+ AAmong groups, 组间/ b# p" [: O, r' f6 v" J' j
Amounts, 总量) u: g1 x, J% o8 a1 K
Analysis of correlation, 相关分析$ u/ Q, j0 v+ U g# T9 u! s3 z
Analysis of covariance, 协方差分析% Z& f1 N% E9 \7 I& N
Analysis of regression, 回归分析
% ~/ r( ]& o+ s" y* EAnalysis of time series, 时间序列分析
) R" v8 r% e: j' C" i7 A) S1 RAnalysis of variance, 方差分析
" D( L9 o1 e. q4 N9 x) i: [0 ~5 dAngular transformation, 角转换4 C$ D! h! ] q! l+ K7 D
ANOVA （analysis of variance）, 方差分析
. ^' i, J* i9 f# P: A! ~% {( a% yANOVA Models, 方差分析模型3 T( {, y( C3 C, v! y& F
Arcing, 弧/弧旋
6 g$ ~( z4 \: J' M2 ?/ t6 IArcsine transformation, 反正弦变换
& O3 p) o! d. a" f) ?Area under the curve, 曲线面积& ~) P: G% G0 A b* j& ]
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
# d$ q$ k2 g- z- N+ dARIMA, 季节和非季节性单变量模型的极大似然估计
4 {# n2 G9 a" e3 m Z2 e% CArithmetic grid paper, 算术格纸4 y8 g! w8 w# x) {8 o
Arithmetic mean, 算术平均数$ i% v' {1 V8 R
Arrhenius relation, 艾恩尼斯关系
- C; Q6 Q5 d: K K, z. s" DAssessing fit, 拟合的评估2 J6 k0 l, U4 Q7 X
Associative laws, 结合律
, J. c! d9 @2 s* yAsymmetric distribution, 非对称分布0 r; |. ], F; `' x% x
Asymptotic bias, 渐近偏倚% t- R: t2 |- N: x& \% P& \
Asymptotic efficiency, 渐近效率
/ r5 C k0 ]$ n: U$ z! DAsymptotic variance, 渐近方差6 F/ z& Z v- b4 I2 |) `
Attributable risk, 归因危险度
$ N. v0 L; \5 J! xAttribute data, 属性资料* E7 ?0 `2 _6 l. Z \$ M4 G
Attribution, 属性! \* K n; }6 V4 g& a- N% t( O: Z3 N
Autocorrelation, 自相关, l' P5 p% ?5 G. k# H
Autocorrelation of residuals, 残差的自相关/ b9 g& C( U* s% t5 C; a
Average, 平均数( {* C3 h0 y G" V2 Z
Average confidence interval length, 平均置信区间长度
) x; {: G; B4 d, T; t. ~: R& WAverage growth rate, 平均增长率
' L' _2 z2 m4 F% s' \Bar chart, 条形图
" o- y& X# X6 L1 _1 aBar graph, 条形图+ A/ K: {4 ~3 j) x, G
Base period, 基期
. U: P- U' \$ K- p3 Q" `Bayes' theorem , Bayes定理
6 U1 D4 X' r T! OBell-shaped curve, 钟形曲线
% E; H7 Q6 T2 d; ]! b' TBernoulli distribution, 伯努力分布
$ U) Y8 S& r4 I; ^0 m, D$ E( e g5 Q$ }Best-trim estimator, 最好切尾估计量
( e. n8 g! L" R- @+ i/ h/ ]" b! i( GBias, 偏性
* K+ }! D' q u7 s% LBinary logistic regression, 二元逻辑斯蒂回归9 k& s$ L9 F8 s |: s8 I" t! ?5 \
Binomial distribution, 二项分布
% L" Y- G2 r( J: e+ ^. K; GBisquare, 双平方
. t- X! V1 r2 w* U, z" ^ ~Bivariate Correlate, 二变量相关- A& W( T) V" g; S; o
Bivariate normal distribution, 双变量正态分布: V4 Z- h+ S5 p7 q6 O1 t( a$ G
Bivariate normal population, 双变量正态总体
2 W% s' ~) n! ?' o3 Y' M9 V% ^! lBiweight interval, 双权区间- x$ p; e' w( R- Q9 l3 q- H2 F
Biweight M-estimator, 双权M估计量1 H1 S. g! n3 }% F: a
Block, 区组/配伍组9 B+ \3 B; k3 K2 u9 O) M/ S
BMDP(Biomedical computer programs), BMDP统计软件包
9 f Z) k8 i" n1 {$ a! v# P( MBoxplots, 箱线图/箱尾图9 ^6 h, e9 |1 \; u& D/ X
Breakdown bound, 崩溃界/崩溃点6 Z0 i+ m7 m8 e
Canonical correlation, 典型相关
2 O) |) q( r/ _9 |( v& [& p) k* F; PCaption, 纵标目
" V& P1 ~" h) P' }Case-control study, 病例对照研究
7 v9 b" y7 ?6 E5 F# u2 gCategorical variable, 分类变量
5 }" l9 a8 g7 h" {8 H6 kCatenary, 悬链线
" }5 B! T5 s. D5 MCauchy distribution, 柯西分布
2 Z$ z2 e/ X7 Y- ]3 G! v+ Y- aCause-and-effect relationship, 因果关系
: E% t- h6 x1 {7 U% l1 BCell, 单元
% B1 h# @# e# R8 A- uCensoring, 终检
. ~; }. u( G8 f* j P3 z1 yCenter of symmetry, 对称中心2 |' G" ~" D3 b" _2 J D, z
Centering and scaling, 中心化和定标
( Y6 g% L" F6 _ ]! V% Z& CCentral tendency, 集中趋势! u" M; _/ W- ~/ Q; q6 U8 D( L
Central value, 中心值8 G$ K7 ~- y& n& k
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
0 F$ L9 ]& D" `$ e7 RChance, 机遇# R F& i5 K0 M9 V
Chance error, 随机误差
+ o3 F3 S* W& e+ Y8 J, \Chance variable, 随机变量
( p. U. N# U' f% [; O; i$ P. T8 O" PCharacteristic equation, 特征方程+ U: k4 z5 @* G6 `8 A
Characteristic root, 特征根
7 f" G0 `" U' q+ G3 t2 C5 J) kCharacteristic vector, 特征向量5 B! f) K9 u$ W0 M2 r
Chebshev criterion of fit, 拟合的切比雪夫准则2 D* Q' F1 x4 H
Chernoff faces, 切尔诺夫脸谱图
; m, r* ^# f9 j! g a+ K0 CChi-square test, 卡方检验/χ2检验! b4 c& Z' j8 w+ z% J
Choleskey decomposition, 乔洛斯基分解
- x3 d3 ~. D% h8 v! E+ ~8 O4 yCircle chart, 圆图
( P5 F% D2 p0 {% m- K3 K$ r# XClass interval, 组距
" R, G# d" P9 R( b4 r/ N" WClass mid-value, 组中值
- Y+ K& [1 u$ \, `; `# uClass upper limit, 组上限
% y: X- h4 n1 YClassified variable, 分类变量
7 x: r6 `5 N2 U( }2 k0 k& FCluster analysis, 聚类分析
0 C+ R: e4 E8 p' u6 s% vCluster sampling, 整群抽样% S1 y1 B* Z( Q+ J+ s0 Y8 Z
Code, 代码$ e/ X. ?% a# r) v3 X; s
Coded data, 编码数据" {$ E! y/ U. T/ R0 R4 M4 b
Coding, 编码
) R# b& x) ~9 x" D, ^* HCoefficient of contingency, 列联系数) n: F' M4 `. C C- f
Coefficient of determination, 决定系数3 \ D# g0 p( }" e7 e3 E
Coefficient of multiple correlation, 多重相关系数$ L- x/ T5 ^( @8 ]: S4 c
Coefficient of partial correlation, 偏相关系数* s$ Y( Y: a& Y! [# D
Coefficient of production-moment correlation, 积差相关系数
/ K5 J* D6 v" Y% v- L. FCoefficient of rank correlation, 等级相关系数
1 p+ k1 I S2 R6 P' YCoefficient of regression, 回归系数% q2 p+ ?" A% N4 u1 m. a
Coefficient of skewness, 偏度系数
: Q* B7 n3 n+ UCoefficient of variation, 变异系数9 q4 H! T \! q/ h! o1 C
Cohort study, 队列研究0 s4 o9 E, d/ L+ r
Column, 列* n: f1 f7 `$ q9 v3 v
Column effect, 列效应! R2 ^" ]8 P% j( j/ L3 c
Column factor, 列因素, J+ O& R% v; y6 ]' s( ~& d5 m- [
Combination pool, 合并* o! }' a9 C' I) E
Combinative table, 组合表
v$ O. i) s% h7 D0 F2 a/ sCommon factor, 共性因子8 b6 R9 z; R7 h7 B
Common regression coefficient, 公共回归系数- ]& C: V5 j4 p2 _8 b8 b
Common value, 共同值
( ^4 `7 O3 G1 _! L' \0 |Common variance, 公共方差
% |6 [5 V: @% {& } N! |, }0 q3 ^ OCommon variation, 公共变异
# Y! H+ m. S3 t4 ?/ nCommunality variance, 共性方差/ E0 r" {8 d6 t
Comparability, 可比性
! V% H7 N% Z) I5 v2 _8 N* VComparison of bathes, 批比较
7 }% E/ ~) |1 W' x. ^3 FComparison value, 比较值$ ]( s9 S# s1 ^# [
Compartment model, 分部模型
- t4 Z9 m' c# K( zCompassion, 伸缩# X3 s( ?; L' _* a" u+ X8 h+ y
Complement of an event, 补事件
/ u' [# l ~* ?( b3 lComplete association, 完全正相关
2 @1 P% W. @9 r7 ZComplete dissociation, 完全不相关. A h9 s9 ~; K$ w; r( b( C
Complete statistics, 完备统计量1 p1 T/ i( p: a& N% A. }
Completely randomized design, 完全随机化设计% W( e% X( D; ]) c. q
Composite event, 联合事件" l6 {4 I' A" U- v
Composite events, 复合事件, D! q: {# ?* a( M
Concavity, 凹性% _& h7 X: n2 P3 v' t4 U: R/ t
Conditional expectation, 条件期望
6 a% K2 N, [3 D, aConditional likelihood, 条件似然
* u) J7 x' |3 d3 _( ?% _6 N1 SConditional probability, 条件概率
3 ^+ w* D; u" S. i& g0 I1 xConditionally linear, 依条件线性
- Y- v/ c, Z6 Q" ]4 a" p- [: m, mConfidence interval, 置信区间
3 z; p- l% L8 u R& d$ gConfidence limit, 置信限5 \( E( S% K( r1 H/ L1 W
Confidence lower limit, 置信下限5 z" g1 B0 J! F+ A3 _# h9 _6 I2 l
Confidence upper limit, 置信上限
, p3 s* k$ f7 w; Y3 vConfirmatory Factor Analysis , 验证性因子分析- l) C; s7 m6 E" H( K$ D, K; ~) e
Confirmatory research, 证实性实验研究
% w1 G( j% U, h; u( T) @& l* J0 \4 KConfounding factor, 混杂因素
5 M; O1 o2 T7 H& @9 R% \' RConjoint, 联合分析
7 }6 @7 F1 R* `+ LConsistency, 相合性
2 P: h9 }: Z; H/ @Consistency check, 一致性检验* A3 m3 m& }7 H2 y) E7 E) l- x
Consistent asymptotically normal estimate, 相合渐近正态估计/ t7 G5 z; t9 ]" U. B
Consistent estimate, 相合估计
' x9 h6 f j9 i/ H' v g& DConstrained nonlinear regression, 受约束非线性回归
' n" a2 B! S+ Z+ }" aConstraint, 约束8 a8 C7 U) \, F7 ~9 w, \5 Q
Contaminated distribution, 污染分布
! j) {( O, d$ L- D$ t/ pContaminated Gausssian, 污染高斯分布
! v$ g( a8 z* F4 o* t: Y! fContaminated normal distribution, 污染正态分布
4 u: a+ F9 x/ ]4 Q/ e/ w. Y4 I8 VContamination, 污染
( B& D: U) J4 L) ?* w, w. T8 L+ l9 J: vContamination model, 污染模型/ Q, j) o/ Y8 h5 }
Contingency table, 列联表
8 b: k ?/ L/ {. P4 [) EContour, 边界线
: H! g. p8 \/ O0 _& D" K6 ?Contribution rate, 贡献率
% f; {% D5 y' ], \6 A3 p. tControl, 对照 C+ ^- ^) N" G5 }
Controlled experiments, 对照实验6 l. @2 O, S- T
Conventional depth, 常规深度: K; D: R9 z9 T6 c, c8 [
Convolution, 卷积
% S K4 a& E0 `# X0 v8 DCorrected factor, 校正因子6 r4 H* U" x% ]0 @7 A
Corrected mean, 校正均值" |5 y! J6 X5 b# t7 f! w5 f, {0 K% y
Correction coefficient, 校正系数
7 G ?9 R+ |/ V9 a; n* ?Correctness, 正确性% \: d/ B* t' h' a/ ~8 Q
Correlation coefficient, 相关系数
7 e* l+ D# @0 e) ~% y! I/ FCorrelation index, 相关指数
# m$ d' m+ D+ l7 iCorrespondence, 对应
7 H- b( [1 `. OCounting, 计数4 p% x( z- f2 m' }
Counts, 计数/频数' J! E# E' i- P& c0 S
Covariance, 协方差
' G( y' Q, d2 R% ^Covariant, 共变
, W1 L+ ^8 h" W/ F4 s6 NCox Regression, Cox回归
: E3 Q; T- K5 z' Y3 d* H# Z: v/ ICriteria for fitting, 拟合准则3 M* T4 j/ f- |
Criteria of least squares, 最小二乘准则# m' K, ?7 C- o; h+ i5 Q( e
Critical ratio, 临界比
& r( [ y$ [. m% X0 K% sCritical region, 拒绝域
+ g6 D) U) Z$ o4 dCritical value, 临界值5 C# W( p2 t5 k6 |; V/ X
Cross-over design, 交叉设计
. l: X3 ^) }0 C# [Cross-section analysis, 横断面分析
( I0 ~6 V( a: v7 @: D4 PCross-section survey, 横断面调查1 ~4 V3 R6 G7 n0 F U; T1 V
Crosstabs , 交叉表
& N- l' L4 y! u- VCross-tabulation table, 复合表
1 k ~. |2 l' _Cube root, 立方根4 j- W# ~9 k' x5 I4 s
Cumulative distribution function, 分布函数
7 t! X7 E( x) s0 f$ |, zCumulative probability, 累计概率
/ @3 E: i1 I2 r, XCurvature, 曲率/弯曲9 L, f, ?5 W0 o! N
Curvature, 曲率
$ Z/ D- W9 S. c$ Z# Z7 e4 FCurve fit , 曲线拟和 ; |$ B% ~7 ~6 H# G) g- F
Curve fitting, 曲线拟合* f/ m6 k( _0 b! t& V3 `4 I4 Z
Curvilinear regression, 曲线回归. Z7 r) i8 o, ]: `4 k# _6 K9 V9 `0 O
Curvilinear relation, 曲线关系& E! q% b0 t/ L. j5 }/ F
Cut-and-try method, 尝试法: l; o5 ^( W, v9 z
Cycle, 周期9 Z& h0 [. J" e* B4 c
Cyclist, 周期性! X- `. H0 m8 x8 O5 c7 l
D test, D检验
/ x6 z3 P5 r# w; Y( h9 sData acquisition, 资料收集# y' {+ M, Q9 O: z1 V$ v
Data bank, 数据库
, h' v( s0 ]# H8 uData capacity, 数据容量
' r; s( {6 S# V0 w* c2 R9 D5 \Data deficiencies, 数据缺乏
. g; b, g# @8 h$ m4 ~6 OData handling, 数据处理1 R# }# X9 P$ K# }9 a, K
Data manipulation, 数据处理
1 r0 l& ]; w: ?1 S& V7 G/ KData processing, 数据处理. @& O) f$ l9 E! a
Data reduction, 数据缩减7 c6 _! e( ~5 F9 P" w( C3 f P
Data set, 数据集3 e6 L4 B8 _( _1 L, e- x
Data sources, 数据来源' ?. D; M$ N$ a- E0 {
Data transformation, 数据变换+ S) w A B h3 c/ D
Data validity, 数据有效性# d H, Z$ d! i8 b" s5 \$ s" R
Data-in, 数据输入. q% @9 @5 C3 ]; M M- Y
Data-out, 数据输出0 D3 V# n( m" v
Dead time, 停滞期
, h2 Q% Y! i* ]1 i0 [Degree of freedom, 自由度0 y* U( m# X( F* e1 C* [
Degree of precision, 精密度5 S! M3 ]. T) t/ W: t2 y) \
Degree of reliability, 可靠性程度
6 D& W s3 c9 L# f9 |5 GDegression, 递减
+ |; C* n) @, B( B) FDensity function, 密度函数
5 N1 D1 ]2 a) D; ^( x) v1 kDensity of data points, 数据点的密度8 H- _3 o& d# g" Z0 ?4 Q6 _
Dependent variable, 应变量/依变量/因变量
: I; H9 h7 T& b9 {2 yDependent variable, 因变量
* G+ n. Y5 w$ f9 x: ?* ^Depth, 深度+ v, R' a4 H" U9 R3 Z
Derivative matrix, 导数矩阵
; ^: s) c# V \+ Y4 UDerivative-free methods, 无导数方法 r& Z5 U v- k6 Z$ ?, x: R& K
Design, 设计
6 s* l" b) a5 r5 d& P+ xDeterminacy, 确定性
& F' X% p, ^* s5 G0 Q# zDeterminant, 行列式
7 ~( k1 a4 L9 r5 _( MDeterminant, 决定因素
K' I W8 p& }+ r! l. tDeviation, 离差& j% x9 I+ {+ s3 d
Deviation from average, 离均差& a) q# s5 y0 Y5 |" T6 @& U4 k' U
Diagnostic plot, 诊断图
) t! h1 \ `7 E$ N( q/ Z4 ?7 pDichotomous variable, 二分变量
& Y% P/ c& j% T7 f8 p; `8 YDifferential equation, 微分方程
' e) X- J! j: v) RDirect standardization, 直接标准化法6 @! A1 r7 `( _* K
Discrete variable, 离散型变量
, L5 w& h7 K0 V' n3 X$ b' v5 ~DISCRIMINANT, 判断
$ T- w2 X% k% dDiscriminant analysis, 判别分析8 y) Z* i, R2 l* O7 A$ s( A
Discriminant coefficient, 判别系数" a: [2 I. P# p% E
Discriminant function, 判别值
. ]/ @" _" B+ O5 y, I" \8 x2 wDispersion, 散布/分散度+ g5 v5 z" N! r q1 c
Disproportional, 不成比例的
( _& z( e4 z w( e5 JDisproportionate sub-class numbers, 不成比例次级组含量
" S1 t5 q- V' MDistribution free, 分布无关性/免分布+ f5 G" m( c3 J5 J( y& l
Distribution shape, 分布形状
( o. U2 r% l. iDistribution-free method, 任意分布法, Q& m1 m- t5 T; ^- t
Distributive laws, 分配律
* C# o! H0 S$ QDisturbance, 随机扰动项* y% a$ n# }* H7 F% c5 L3 j* ?8 {
Dose response curve, 剂量反应曲线
$ }1 ~2 { S6 b+ qDouble blind method, 双盲法
- M7 o7 b4 t$ T0 m0 KDouble blind trial, 双盲试验
8 D1 X" ^3 I+ r0 V5 ^8 V/ fDouble exponential distribution, 双指数分布
1 T% c; {4 r, J' V3 X' ^Double logarithmic, 双对数
9 T W* s6 H) J( O2 l+ sDownward rank, 降秩, e% y" k5 Y7 L
Dual-space plot, 对偶空间图
- A6 }: @5 r. c E9 t1 W4 `DUD, 无导数方法# e3 G W/ {9 T; \4 K
Duncan's new multiple range method, 新复极差法/Duncan新法! ?7 y& d! G' p$ a8 e
Effect, 实验效应
8 x" R$ ~) \( O/ m' DEigenvalue, 特征值
5 C$ o+ R% J) ?$ n9 d9 JEigenvector, 特征向量 \: u" ~0 I6 n4 w" F) e
Ellipse, 椭圆
0 P( \# y% v6 h7 D( Q0 b( EEmpirical distribution, 经验分布! D" `7 l8 e& f* Z# I
Empirical probability, 经验概率单位+ {# r3 g8 P1 ~; t( ~
Enumeration data, 计数资料
8 @1 M& U' c- g, n3 d1 hEqual sun-class number, 相等次级组含量2 f+ H* b4 w9 b8 C, ~; E
Equally likely, 等可能& d/ D9 p C, I' J& ^
Equivariance, 同变性
$ u: `/ }7 T% D w& ]- d! TError, 误差/错误
4 n* J/ m7 f9 S6 F1 n+ ^9 {Error of estimate, 估计误差 [8 f% `) V8 a; p# B3 w
Error type I, 第一类错误
1 d- W& Z9 G, N! zError type II, 第二类错误2 P b$ H5 z7 j1 T0 \ g# C1 l: {
Estimand, 被估量: e; C% Y4 H; G. m0 J+ p3 m1 p5 Z
Estimated error mean squares, 估计误差均方" q; w3 v- f4 o' j2 w- |, A( ^
Estimated error sum of squares, 估计误差平方和
2 b+ k' T- M# n9 h6 O* XEuclidean distance, 欧式距离/ G$ r1 R: n9 m# ^% g: z
Event, 事件
% E2 l* e9 N+ x: s: c, PEvent, 事件, Y: r, `9 j) D) \
Exceptional data point, 异常数据点" J) e. U& m0 k* _4 c) V
Expectation plane, 期望平面
O: Z9 S- ?/ U l9 rExpectation surface, 期望曲面
& d, n- g" N4 } }Expected values, 期望值2 r: u. n. ^9 b" A! c
Experiment, 实验' m- k) F8 G/ y) i7 [
Experimental sampling, 试验抽样
2 L8 S1 j& g1 m9 KExperimental unit, 试验单位
3 [$ L4 Z, W `; I, m. AExplanatory variable, 说明变量
( X0 ?/ M, Q" i3 z( aExploratory data analysis, 探索性数据分析
2 F$ r# O, Q5 H8 u+ G: UExplore Summarize, 探索-摘要
% w( z V3 l3 q: V0 M3 [Exponential curve, 指数曲线0 b( L8 c) O8 Z+ o
Exponential growth, 指数式增长/ g; _% f# Q$ [, N
EXSMOOTH, 指数平滑方法
. h' o0 |" e$ l0 `Extended fit, 扩充拟合
* f+ J9 ^; B" a0 R: ?Extra parameter, 附加参数
4 \( I7 j) ?1 b, K0 H a1 G" N" kExtrapolation, 外推法6 p1 d g2 I2 Q( D( Y
Extreme observation, 末端观测值, o( Z* O+ z. A5 W1 l/ P2 `
Extremes, 极端值/极值
& @ M7 j$ }. `: T( t. D( j3 NF distribution, F分布
: Z6 F1 [6 |: e' o0 bF test, F检验
1 t+ i( s, D7 cFactor, 因素/因子
; c6 l8 I; q6 C; L7 u9 }- N+ p+ PFactor analysis, 因子分析
U9 W' [* k: O% QFactor Analysis, 因子分析+ W6 G1 l. j# n, a& S& d8 F
Factor score, 因子得分 6 o: h1 C" _( N" J) A; o* r2 |
Factorial, 阶乘
% ?7 M3 W8 w( e0 bFactorial design, 析因试验设计* H) {7 g) t0 {, h4 M
False negative, 假阴性
; c; X8 V# c# NFalse negative error, 假阴性错误: u1 f* q* s' v- K1 h {4 \$ K& e
Family of distributions, 分布族/ {! E% {7 Y& n# W" X) l) X2 E( C
Family of estimators, 估计量族
. d Q; R5 T: R5 x( nFanning, 扇面
8 ]- @+ A( v9 FFatality rate, 病死率9 c/ R( U) [+ f( s- ]* p
Field investigation, 现场调查
% a, k) S: W; X9 G, VField survey, 现场调查
0 i" ^9 A: o0 YFinite population, 有限总体
|/ U- y$ ?7 ~& o0 ~# {% y. {" h$ GFinite-sample, 有限样本
8 O6 x( d6 d' B" \- cFirst derivative, 一阶导数2 S4 \7 H( q- p/ U7 b0 V* `. T
First principal component, 第一主成分
4 V( _1 X" e. BFirst quartile, 第一四分位数' T7 Z( j4 `! M3 n1 s/ n7 }9 B
Fisher information, 费雪信息量$ I0 x& @1 L; s1 R9 \( }5 A
Fitted value, 拟合值
3 s7 Q! p- o/ a) s" AFitting a curve, 曲线拟合7 a, ?! Y4 k. Q, z: B: ]
Fixed base, 定基
8 z: v0 c& m) @$ X vFluctuation, 随机起伏& ~* ]7 ^( N( Q) ^8 F7 i: G
Forecast, 预测
g7 A* m5 e* y/ I' fFour fold table, 四格表
; `+ u) u8 Z6 z+ W, zFourth, 四分点
; O, E+ o6 Z6 [, \3 f. f3 H2 YFraction blow, 左侧比率
; k0 T6 k3 H8 `5 a9 M3 |Fractional error, 相对误差, I9 M5 h0 z$ f* k0 P
Frequency, 频率
J4 `7 `) K0 I5 l6 }9 y4 vFrequency polygon, 频数多边图
1 [( |' |; l. E7 M1 E+ FFrontier point, 界限点
8 `; {( @0 C7 g' s1 jFunction relationship, 泛函关系
& A$ @7 L. `4 |( ~5 _* s2 RGamma distribution, 伽玛分布
& i/ ^2 ?$ A& X, K. n- x! ~Gauss increment, 高斯增量: I) P, I) k% P* `' u; U/ H* D
Gaussian distribution, 高斯分布/正态分布0 [" l# T. W! ~
Gauss-Newton increment, 高斯-牛顿增量
# z: p! f& z, X1 } T5 MGeneral census, 全面普查
0 C2 y0 {* R+ P* F- k- q) k3 ]GENLOG (Generalized liner models), 广义线性模型
+ @" K' [* ~( @2 ZGeometric mean, 几何平均数
4 F# W- d6 }9 O+ a0 |4 Y( L) ?Gini's mean difference, 基尼均差/ j! R4 u* [2 }3 h0 k
GLM (General liner models), 一般线性模型 9 r% R6 w6 i9 {
Goodness of fit, 拟和优度/配合度
( Z5 Z* S1 F xGradient of determinant, 行列式的梯度9 o2 H: l8 r z8 y* `8 D8 l
Graeco-Latin square, 希腊拉丁方
& h7 c8 V; p$ N6 ~7 DGrand mean, 总均值
! Y. }& L% u E+ J ]Gross errors, 重大错误3 l6 |7 {' _+ X1 v
Gross-error sensitivity, 大错敏感度. @6 l6 x: v4 ^% w) n
Group averages, 分组平均+ N; V' D/ I' h& \$ W
Grouped data, 分组资料
: n$ _) R! e* RGuessed mean, 假定平均数9 n: \% r3 @4 |) }
Half-life, 半衰期
2 N- X9 @" l5 M7 H) O+ c& l; nHampel M-estimators, 汉佩尔M估计量
. Y& ?" J2 G3 A* g7 S* u3 O- U) BHappenstance, 偶然事件
/ @2 {* N, |2 W a* \. C1 ~Harmonic mean, 调和均数
2 U; L8 f, c0 \$ ?/ [% cHazard function, 风险均数
3 @: i# m; v! c. [. YHazard rate, 风险率
" T7 [: v( p$ w- x: P2 ]4 HHeading, 标目 5 w( Y4 j" b- K; p% r2 B8 S" f
Heavy-tailed distribution, 重尾分布* Q. U. I& d% A/ B
Hessian array, 海森立体阵
. l: f) h) {( V# T% ~Heterogeneity, 不同质
% d! r: x9 } J4 S5 ?Heterogeneity of variance, 方差不齐
/ s! M) e' T: a8 C* G) N3 hHierarchical classification, 组内分组
7 p; w9 `2 E4 d. d/ qHierarchical clustering method, 系统聚类法, O4 O2 ?' ?8 {7 N
High-leverage point, 高杠杆率点
$ n/ z9 R* D6 H+ G) oHILOGLINEAR, 多维列联表的层次对数线性模型0 D4 O) S, s9 N5 C3 f0 \/ C6 H
Hinge, 折叶点
, N5 I; E* g6 d2 g" t: WHistogram, 直方图7 k( [0 s6 |) h ?# G; g& P0 N5 K! P
Historical cohort study, 历史性队列研究
9 Q, U# V) S& d# UHoles, 空洞
' g, z- |$ l6 @3 fHOMALS, 多重响应分析: ~1 K* N' }3 U p9 s6 p% ?" C% \
Homogeneity of variance, 方差齐性
& f( l0 `4 `) E# _Homogeneity test, 齐性检验
7 N; n% |1 n l) hHuber M-estimators, 休伯M估计量
4 ?1 P0 r) l& u. Y5 nHyperbola, 双曲线
( M g& I9 W5 R2 ]Hypothesis testing, 假设检验( Y. [, }: f. z
Hypothetical universe, 假设总体8 c: j6 b1 G) R* r
Impossible event, 不可能事件6 h, W- e% k' M# ~% z1 G
Independence, 独立性
9 f- P, F ]0 X1 R. }1 WIndependent variable, 自变量
3 | z$ H: R4 P6 P1 X" U& g+ oIndex, 指标/指数
4 ^) i7 n: S$ U2 d+ ]* I" w7 mIndirect standardization, 间接标准化法5 C6 [+ ~4 e/ s, Q( B o" I
Individual, 个体
# ]4 r/ y* E5 S. XInference band, 推断带1 P2 R# r. [# F
Infinite population, 无限总体
6 x# N3 w# c' _, i# F' RInfinitely great, 无穷大
( a( J$ g" D9 q3 I7 J, AInfinitely small, 无穷小
3 e. A- X8 B% ]- M. I8 T/ LInfluence curve, 影响曲线
( x+ B2 E6 x+ T. c2 q, XInformation capacity, 信息容量
- ~5 F, g8 s: i: ?2 M+ RInitial condition, 初始条件
" O' j. g# o- t- R1 N. Z0 VInitial estimate, 初始估计值
- Z; n+ Y) N( y. ^4 iInitial level, 最初水平* q v' V* h, a6 j6 j. r& w
Interaction, 交互作用
4 G& {2 I* D7 f1 L2 xInteraction terms, 交互作用项4 w* p7 M' R8 M- u- q5 ~7 Z
Intercept, 截距& { Z5 X( m: f' a- h D% _
Interpolation, 内插法% W7 ]1 `9 [$ z* e3 P- C" M2 \
Interquartile range, 四分位距+ V8 l3 H0 @4 s4 ?
Interval estimation, 区间估计
3 T7 t P3 [" uIntervals of equal probability, 等概率区间0 O; N7 ]+ Y3 x; S, E+ x* \
Intrinsic curvature, 固有曲率
2 g8 q' I5 |9 F6 J: q0 D" ^Invariance, 不变性
# _. }" u1 u' ^! L: x' w& KInverse matrix, 逆矩阵
% { g: k X, l. p6 W+ C6 @Inverse probability, 逆概率
/ ^! V) @3 S+ d0 \7 ?9 mInverse sine transformation, 反正弦变换8 m7 _- F9 d2 p4 W* U9 J6 j
Iteration, 迭代 1 F. Q9 i/ k1 t" U/ f1 ]
Jacobian determinant, 雅可比行列式
6 H2 g1 T9 U* q0 U, R5 eJoint distribution function, 分布函数8 M$ h1 M( _0 j" j
Joint probability, 联合概率6 q/ A5 M- L, @. k% e* p
Joint probability distribution, 联合概率分布
! B9 v7 {: U) U* DK means method, 逐步聚类法. I* l0 p0 @( A4 U0 z
Kaplan-Meier, 评估事件的时间长度
; }7 `; T! a3 S6 O' R( _# R& bKaplan-Merier chart, Kaplan-Merier图. d. Z1 R a/ G' \" E
Kendall's rank correlation, Kendall等级相关+ f- d- t; O& x6 E7 n
Kinetic, 动力学9 P% S0 q2 V q& J0 [9 A
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
2 y5 {0 d. `) Z5 k9 W. K) h' fKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
% v; [1 c7 N4 ~7 Y; B& d- c9 WKurtosis, 峰度
) F) w; u% @( cLack of fit, 失拟
# o# q% n6 x" U! m' K) @1 r8 p% ELadder of powers, 幂阶梯2 o6 g' e* f- \: a
Lag, 滞后$ d5 e8 B; U; r' U( u6 c/ R
Large sample, 大样本
X7 {9 t( |( z) cLarge sample test, 大样本检验2 A. ?4 k' x) ~( Y) k, t, @8 a( w' o
Latin square, 拉丁方
. j1 O1 ^/ h" }1 e: |$ a6 mLatin square design, 拉丁方设计3 S8 j5 Q. M1 d
Leakage, 泄漏
& }$ c" D8 u- z/ ^2 W0 lLeast favorable configuration, 最不利构形
- F/ f2 J& v2 l# Y; }; cLeast favorable distribution, 最不利分布
6 v }3 ~' X4 B$ @) T9 q3 KLeast significant difference, 最小显著差法& P1 L T+ |/ _, F
Least square method, 最小二乘法; H8 e. x0 z q; v
Least-absolute-residuals estimates, 最小绝对残差估计
5 d( R0 Y- G) x7 `& oLeast-absolute-residuals fit, 最小绝对残差拟合: S/ \# v4 Z" p) u+ {' G
Least-absolute-residuals line, 最小绝对残差线" t/ k/ t2 ^' v% k
Legend, 图例: ]: ~+ N6 M: ~0 i: }, J- H- i
L-estimator, L估计量# Y2 @0 `5 V& v* y7 n4 e
L-estimator of location, 位置L估计量( [& s% u4 c6 @, w! C( `" m: E! L
L-estimator of scale, 尺度L估计量* o+ \4 b# }* @) h2 v3 I( x
Level, 水平
7 p5 H2 z0 f5 n* y; K7 dLife expectance, 预期期望寿命
6 c* N. {5 u) H1 ]' M$ dLife table, 寿命表* I v0 \+ }5 b# c
Life table method, 生命表法1 r7 D. K) O) ?+ x
Light-tailed distribution, 轻尾分布8 i3 c G' \; O {
Likelihood function, 似然函数5 e- C+ ]" J9 \. U
Likelihood ratio, 似然比7 c; k: v4 m, W5 v5 W- Q
line graph, 线图7 p2 H* Q% \# e1 j; z
Linear correlation, 直线相关
1 y8 d. M1 J% S; {2 P$ MLinear equation, 线性方程" I. V$ ~ d2 ?
Linear programming, 线性规划! }: o* }( M) O, C4 M
Linear regression, 直线回归
5 ?3 V6 K m9 ~( A& _+ E9 }* }Linear Regression, 线性回归
. \" W1 V3 }2 t1 _Linear trend, 线性趋势5 p5 k! d1 L3 d+ ~; i
Loading, 载荷 3 w+ Q& f: J3 ~, l2 U
Location and scale equivariance, 位置尺度同变性
. ?9 D* I! u( @- zLocation equivariance, 位置同变性2 O6 S% h {) U7 A! U6 v
Location invariance, 位置不变性! Q( }, v6 ?7 C I2 j# v
Location scale family, 位置尺度族+ g+ K% \8 j. g; s1 J% l* B8 t
Log rank test, 时序检验 9 e( S, g* B ]) S
Logarithmic curve, 对数曲线
0 h8 f2 ?8 j: h! |Logarithmic normal distribution, 对数正态分布, _8 K% j6 v2 b* d8 S
Logarithmic scale, 对数尺度) u4 S5 f/ F6 Y' w( P I* i
Logarithmic transformation, 对数变换
$ {$ I" ^1 M/ D3 S4 B+ `3 ALogic check, 逻辑检查
, c- Q! Q; S2 JLogistic distribution, 逻辑斯特分布
* N/ j/ M1 W4 e, kLogit transformation, Logit转换' _- @( l3 y" g0 G
LOGLINEAR, 多维列联表通用模型
. T O/ v' n: O% S! ALognormal distribution, 对数正态分布 u3 p% @3 i# u: q
Lost function, 损失函数9 K; P* r2 y* |/ q- I
Low correlation, 低度相关
& J8 D) l1 \* o' y/ hLower limit, 下限
" f: `1 v9 `9 w3 H3 I) c8 V8 eLowest-attained variance, 最小可达方差! T/ m& v: K" ~, k: z. ~
LSD, 最小显著差法的简称+ w. G/ D0 M8 y& i$ i7 V9 A, S1 |
Lurking variable, 潜在变量
& D" F, |4 D+ s4 NMain effect, 主效应
7 H% f8 z6 H2 tMajor heading, 主辞标目: P' H1 \5 x: H/ g2 y
Marginal density function, 边缘密度函数 L# p2 [. M1 p/ p* I' A
Marginal probability, 边缘概率
6 [( B. i5 T# @1 QMarginal probability distribution, 边缘概率分布* C" O: a4 ~+ I; G$ B
Matched data, 配对资料! Q. o7 L( \: t! }
Matched distribution, 匹配过分布
- t( M, P% P* h+ ~8 kMatching of distribution, 分布的匹配, c t& _6 @5 [7 u0 Y8 \0 x
Matching of transformation, 变换的匹配) _0 t1 [ U& h6 [8 D0 p6 ~& t3 O0 }
Mathematical expectation, 数学期望
0 i' L- {+ n Q; B# DMathematical model, 数学模型
/ N* e* g, S: R+ W' hMaximum L-estimator, 极大极小L 估计量# V0 j' u- F% O3 j; i7 `
Maximum likelihood method, 最大似然法
( V% b1 M+ W1 f% {2 V1 J4 ^Mean, 均数
1 r+ z& v9 _5 y1 c1 SMean squares between groups, 组间均方
/ O. a+ |# }' x( vMean squares within group, 组内均方1 g8 r' {1 |" _9 h T0 A
Means (Compare means), 均值-均值比较! c! x/ j/ c Z, t
Median, 中位数8 h5 h% e2 P0 ^4 i$ o+ s
Median effective dose, 半数效量. S9 B, X: u, q$ ]+ y
Median lethal dose, 半数致死量
t$ t2 s9 y9 D9 V0 mMedian polish, 中位数平滑; h {1 t4 a7 m3 ^) t) `7 ~
Median test, 中位数检验/ l- U' k7 S. L8 `! `2 \
Minimal sufficient statistic, 最小充分统计量7 d& T- e: Y" ~, U+ |
Minimum distance estimation, 最小距离估计1 [. K" s: Q3 I) R( L7 c0 k
Minimum effective dose, 最小有效量
M! x+ Y- n" m& D4 JMinimum lethal dose, 最小致死量% B% M/ C. s Z9 F; y2 V
Minimum variance estimator, 最小方差估计量5 \2 _9 c! x! B/ H; o
MINITAB, 统计软件包
3 z2 t0 o6 A& V. e2 W5 kMinor heading, 宾词标目
1 Y. {) v* @( o6 @/ U3 kMissing data, 缺失值' Y2 o2 y3 I }2 e: f: [
Model specification, 模型的确定
1 X( i& p/ Y8 L3 n$ qModeling Statistics , 模型统计# F; ]+ R+ y v% T4 P
Models for outliers, 离群值模型
! N5 a# i1 Y: j% Z! C9 a$ x9 n; nModifying the model, 模型的修正- u9 R; n% j a5 b- n
Modulus of continuity, 连续性模 X; d9 g8 E7 u4 `6 S: g
Morbidity, 发病率
$ D4 R6 T% q) Y+ _" y3 z& m0 D4 J& {. OMost favorable configuration, 最有利构形* l& `% Y% ~ d. K
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
3 g4 n7 D2 r! A M% t3 FMultinomial Logistic Regression , 多项逻辑斯蒂回归
, ?4 H, C2 c8 h6 _% AMultiple comparison, 多重比较4 X( K. s% M) {
Multiple correlation , 复相关
' }& X; A- o* b8 n: I$ @; bMultiple covariance, 多元协方差3 w8 s; @7 p$ ]" R9 e7 y2 A- z
Multiple linear regression, 多元线性回归
. I( ~# r: a/ z" X9 U9 P" e6 hMultiple response , 多重选项
# p, r2 K; J% a3 J2 h: f" DMultiple solutions, 多解& `! V! L. l; f% D) e) H h3 P
Multiplication theorem, 乘法定理
, q" c% b2 i" o$ WMultiresponse, 多元响应$ G" U7 l ]' Z: v6 J6 S V
Multi-stage sampling, 多阶段抽样
# k; I$ K9 \- }6 R' a) ^Multivariate T distribution, 多元T分布. W$ _: {+ H% F. W. H3 v7 J
Mutual exclusive, 互不相容
8 |, a0 z# h; [Mutual independence, 互相独立
) R/ m# z7 P* b- jNatural boundary, 自然边界/ I7 R! S M: U, h, P& k
Natural dead, 自然死亡. A! N& X" g+ k6 U0 x( y' T. \5 [
Natural zero, 自然零' ~9 f0 @7 X' w6 F
Negative correlation, 负相关
4 O4 G% U% k Q5 ?, B: jNegative linear correlation, 负线性相关
$ u8 A% u# d: j* E' j) M4 U9 FNegatively skewed, 负偏
) ?) {$ I9 F! ^: n0 ~/ INewman-Keuls method, q检验
( ]4 }+ M: A, [NK method, q检验, z& F8 O+ F' ]
No statistical significance, 无统计意义
$ F% L0 U; y6 M! y8 ^Nominal variable, 名义变量' R: m5 X3 _- q$ ^* h
Nonconstancy of variability, 变异的非定常性
0 O8 \* p* a9 O( F+ t" T: Q0 Q# U/ ?5 nNonlinear regression, 非线性相关" k0 ~# M) g4 R1 m* ^( k! c- i
Nonparametric statistics, 非参数统计
b! y0 O6 M- ]: lNonparametric test, 非参数检验, J" ~+ A* y H% W8 C, ^
Nonparametric tests, 非参数检验
( v7 `0 C! D4 v+ E2 `Normal deviate, 正态离差8 N$ \, p, S; o8 s: i* ?1 ]
Normal distribution, 正态分布
7 y7 y m4 V! w5 aNormal equation, 正规方程组
/ P' A9 K2 d3 f# z. t% @0 ~Normal ranges, 正常范围! E) c( g7 k) k, y8 k$ c; R
Normal value, 正常值/ U0 Q" R8 _2 n( R3 U% y
Nuisance parameter, 多余参数/讨厌参数
1 \/ U8 I* b' W% ZNull hypothesis, 无效假设 ; J0 Y; m& V h V0 h
Numerical variable, 数值变量5 z1 Y: s s0 M
Objective function, 目标函数
$ r. Z M* f( {; QObservation unit, 观察单位/ v, i- O2 @0 b( Z3 m
Observed value, 观察值
, w2 l. u) {# d/ t7 l9 ~1 COne sided test, 单侧检验9 q, g! g9 Q- J/ d" {- H+ J
One-way analysis of variance, 单因素方差分析
( l. H$ J9 I. \' @9 mOneway ANOVA , 单因素方差分析
5 E5 Z3 Q4 `4 U t& {/ b' AOpen sequential trial, 开放型序贯设计
, l+ ?& \/ J/ [, }$ ~9 y' s# OOptrim, 优切尾* I% e, B: K. c
Optrim efficiency, 优切尾效率
5 E5 i( _2 t v: i$ D3 g7 b) S4 TOrder statistics, 顺序统计量 X _2 {7 A+ x$ V
Ordered categories, 有序分类) o; O6 _+ T+ L& t: W- ^
Ordinal logistic regression , 序数逻辑斯蒂回归
( k& Z b7 D8 V* I2 eOrdinal variable, 有序变量
0 s8 |: M8 y! v; r+ W3 aOrthogonal basis, 正交基+ Z- B3 _9 N3 Y$ I2 ]5 Z8 a( u6 G, }4 ?
Orthogonal design, 正交试验设计2 e$ P& T, b' _2 k
Orthogonality conditions, 正交条件1 e' N0 {9 Y5 ~/ V7 V0 P
ORTHOPLAN, 正交设计 ( N. m2 ~* W! C( K. l3 K7 G; R
Outlier cutoffs, 离群值截断点' N. P) N1 Y6 H4 w8 |. r
Outliers, 极端值8 q# f' F! J2 E I( h
OVERALS , 多组变量的非线性正规相关
1 u! L! h4 g4 M( _+ S5 [Overshoot, 迭代过度
) L9 A+ ]0 w0 ]1 X% t: WPaired design, 配对设计
2 R- W% `$ a9 n" iPaired sample, 配对样本$ U' U3 \/ q) d) C5 I' ]
Pairwise slopes, 成对斜率1 U+ y2 B+ b/ _2 ?) y C
Parabola, 抛物线$ K& b8 Q/ Z# r1 h# C3 Y
Parallel tests, 平行试验
( M D7 [$ {( t, r6 [2 \. A3 v* z/ C0 yParameter, 参数3 _$ U0 d# L' \* F/ k8 `
Parametric statistics, 参数统计
+ b% S/ Y4 g9 t& b0 D# M6 L- m1 uParametric test, 参数检验8 I. u. r) {" E: y* X- g
Partial correlation, 偏相关
2 N* [0 }% ] \, J, OPartial regression, 偏回归9 N% f% h* s3 G4 B C( ?8 L% _7 @' N
Partial sorting, 偏排序4 q0 U: P3 [# m2 f; m2 \$ Z
Partials residuals, 偏残差
) t- r2 ?' S8 ?9 M4 XPattern, 模式
- u( B" N" t, q( PPearson curves, 皮尔逊曲线/ Z) h; u3 V) W$ z( V
Peeling, 退层
! M/ S& e2 u/ dPercent bar graph, 百分条形图9 s" B) H3 \3 p8 x( H# H: Z) o
Percentage, 百分比; j. f! f3 l9 S! L* A/ L# {* T
Percentile, 百分位数( n& V0 C) i2 [6 V9 M" y' a
Percentile curves, 百分位曲线
1 t' |7 Y) F' DPeriodicity, 周期性
. Z8 {! S: K8 }& Q: TPermutation, 排列
, A# N8 f. S" m x$ L+ V, p1 lP-estimator, P估计量
6 q1 r) N! D6 p+ B1 lPie graph, 饼图: t3 }/ y8 A- A2 I/ F- X& U
Pitman estimator, 皮特曼估计量" j. \. |3 V0 E( d. C, o* [' V- ^' m$ D
Pivot, 枢轴量8 L+ Q% E! Y, m: F# g: I) S
Planar, 平坦
0 Y" O, `9 r) h6 J9 j* Z; ?Planar assumption, 平面的假设
- ~1 C. Y- h9 S* a# j" ~0 GPLANCARDS, 生成试验的计划卡
( M) E& t- r1 e" _) d! Q! bPoint estimation, 点估计' r' B* a+ l/ m. k' n; m3 H% u7 ~
Poisson distribution, 泊松分布9 [3 t3 g/ {* x' U, w2 E
Polishing, 平滑1 p) u% _# v0 |& s) O
Polled standard deviation, 合并标准差% l: y. U- z% F: |( Z
Polled variance, 合并方差
% n4 ^: v q- H& k: j- NPolygon, 多边图
5 \( v4 P% E, uPolynomial, 多项式
9 D$ W- n' P P$ MPolynomial curve, 多项式曲线6 G9 ? O: Y' @
Population, 总体
5 A( q; w: x/ Q: f4 `Population attributable risk, 人群归因危险度
1 Y9 Y, l% i' k/ H# X W! lPositive correlation, 正相关$ ], I8 T- v0 v% G) f( D5 ~9 `
Positively skewed, 正偏
( D, d# g& @) ?& T4 S, @Posterior distribution, 后验分布
/ J/ ~7 P v$ p( uPower of a test, 检验效能% v, ]9 x" @$ C$ S! q) \
Precision, 精密度
/ @4 o# n- `5 N5 JPredicted value, 预测值" m2 C$ _0 ?" ?* G" f! _% c- e7 s
Preliminary analysis, 预备性分析
' s9 r" C9 D4 k) aPrincipal component analysis, 主成分分析. j8 l7 L9 c6 |9 l
Prior distribution, 先验分布7 h* g* s9 C7 j) i, O. \/ ]
Prior probability, 先验概率
3 O( o; N& S4 I" v8 @3 LProbabilistic model, 概率模型+ q* K; h! D. m: h* p8 f# A* G; m; q
probability, 概率
7 D) r( W1 Q" O4 z* d7 dProbability density, 概率密度9 L) R I7 R2 H0 H
Product moment, 乘积矩/协方差
/ B: `0 x; M6 d; lProfile trace, 截面迹图
5 t" `5 ?/ q' Q. W1 [$ TProportion, 比/构成比
) B& `, X+ H7 [2 e& ?Proportion allocation in stratified random sampling, 按比例分层随机抽样# z1 U0 T1 M" [" }; i) n" g7 P
Proportionate, 成比例+ z3 `8 k& J: A
Proportionate sub-class numbers, 成比例次级组含量! E+ l5 A( {4 P& V; h
Prospective study, 前瞻性调查2 T" k- R- R# J( H
Proximities, 亲近性 " A" ^; a: L7 e) x/ P
Pseudo F test, 近似F检验
7 h& `6 R7 U3 I# k/ f( U [- [Pseudo model, 近似模型
+ e2 h. X1 A+ Y1 CPseudosigma, 伪标准差% Q5 k+ H* [6 X0 S- _
Purposive sampling, 有目的抽样7 V% o* f5 u7 I; a9 r
QR decomposition, QR分解
l9 q0 `1 G8 [! TQuadratic approximation, 二次近似
+ I5 |4 }' y/ l4 |' i3 v1 d+ IQualitative classification, 属性分类4 H1 e; n1 p0 r
Qualitative method, 定性方法
/ d& L3 j1 H3 @; z/ RQuantile-quantile plot, 分位数-分位数图/Q-Q图
4 @4 ]) e3 s7 H! \Quantitative analysis, 定量分析( ?. D* R$ m: M+ y) x
Quartile, 四分位数
. d" ?( I/ L* w6 A { MQuick Cluster, 快速聚类/ U1 i" h" D3 r
Radix sort, 基数排序
P9 m% H7 T+ z: @0 ?5 ^Random allocation, 随机化分组0 e- y) `) Y1 t P: f
Random blocks design, 随机区组设计0 [% F9 V3 M( M' `
Random event, 随机事件( q! b; j0 h' Y( s( P4 a8 J* u
Randomization, 随机化1 q- B, W$ [: B z& m5 e: V
Range, 极差/全距
8 N( z) ^5 D3 T/ l! fRank correlation, 等级相关# u$ W5 a; v5 ~; p
Rank sum test, 秩和检验6 ^( Q9 x% A$ \; m5 s
Rank test, 秩检验/ e5 n2 g! {* I: _& h
Ranked data, 等级资料5 _+ P" E" L6 {+ k) u" F
Rate, 比率
6 O0 \% u; ?( `2 mRatio, 比例6 T% ^- P) J# U) }1 g4 t0 s5 j
Raw data, 原始资料" I' q' b2 d. x. d0 l
Raw residual, 原始残差
* O0 h6 Z* b. _% ^+ @& V* aRayleigh's test, 雷氏检验; ?' r2 ?4 l$ k! E
Rayleigh's Z, 雷氏Z值
9 k' Y; ?: z: D, SReciprocal, 倒数
# j; G, S. _$ W$ w& WReciprocal transformation, 倒数变换9 T) [# [1 ` q' I
Recording, 记录# F* o% j* a5 u) b/ h9 t, V
Redescending estimators, 回降估计量5 C. K7 e+ C# w( w. i& y
Reducing dimensions, 降维
8 u! }4 [. g) A0 gRe-expression, 重新表达1 m! x, K w2 A# K$ }6 Q% e- E
Reference set, 标准组: X. t; ?4 o/ f4 F3 ~- `
Region of acceptance, 接受域
- S* y9 a2 C# zRegression coefficient, 回归系数: K) Q4 E' d& q5 ~
Regression sum of square, 回归平方和; f4 B: j* ^3 T/ I4 t) I# f0 A
Rejection point, 拒绝点+ K2 d, U* J4 W
Relative dispersion, 相对离散度: n5 x2 d+ K9 Q! g
Relative number, 相对数1 V7 ?6 v- _: @7 K" A% E
Reliability, 可靠性
7 S2 T5 |9 M/ q* h0 A7 BReparametrization, 重新设置参数* ]4 T/ t. E8 u6 D- `6 h/ l
Replication, 重复& z( _- g# a5 Z
Report Summaries, 报告摘要2 u+ S! X7 v+ d" E( G# M% b
Residual sum of square, 剩余平方和6 o, T: B+ B# M
Resistance, 耐抗性
0 p6 s1 }3 G: h4 `' RResistant line, 耐抗线
9 ?. ?5 B- ]$ ~. |1 r; pResistant technique, 耐抗技术2 z( }) c, k; R! o$ T* {& N H
R-estimator of location, 位置R估计量! h5 V0 Y/ [1 `8 l
R-estimator of scale, 尺度R估计量! d! j; B) g Z3 Y4 b) z' o2 m
Retrospective study, 回顾性调查' n( ?1 |- \% f' m& Y
Ridge trace, 岭迹
" `* t' u: w% s% xRidit analysis, Ridit分析3 g+ m- W' Z- k! [/ E0 }6 R
Rotation, 旋转% k. s( t2 I+ Z" S
Rounding, 舍入
( _8 \! C% n% X0 W4 ]( E" w* {Row, 行
5 x2 o$ z. T5 @& N6 m1 XRow effects, 行效应7 E8 _. g- f: X( }
Row factor, 行因素5 [' h M1 `5 J1 g
RXC table, RXC表" Q; D& g* k/ h ~
Sample, 样本
& Z+ s5 X' s2 r; |5 A' }# g* k1 rSample regression coefficient, 样本回归系数: Z8 @6 T0 o+ n ^+ J2 K
Sample size, 样本量
# C% Y' w! _0 Z# Z" O" ISample standard deviation, 样本标准差
0 F8 R! \. j9 h$ vSampling error, 抽样误差- N( C: N4 I0 N$ _! P
SAS(Statistical analysis system ), SAS统计软件包1 V& o6 c# b: J1 `1 b0 m
Scale, 尺度/量表
: ^& a7 x( m5 e5 QScatter diagram, 散点图
$ f# C2 X0 i& }$ CSchematic plot, 示意图/简图- \$ Y3 G! L% s# ?5 J" h, b
Score test, 计分检验
2 B; A" f" T3 ]: ^Screening, 筛检, ^ x8 `/ H# X
SEASON, 季节分析 ! t+ ^4 W" H4 X; B9 b- n' d3 ~9 {
Second derivative, 二阶导数1 @) E) s. W: ` O& ?1 `) j
Second principal component, 第二主成分; ?! g3 S& O# }2 A( _% q
SEM (Structural equation modeling), 结构化方程模型 8 ~. \0 A k+ e& f( A
Semi-logarithmic graph, 半对数图8 J" l' e( _/ p) w3 L2 D
Semi-logarithmic paper, 半对数格纸
# |. ~+ v( G, r7 L; `Sensitivity curve, 敏感度曲线
2 M+ [0 s# b7 i2 dSequential analysis, 贯序分析" \3 @7 P4 {( N6 C
Sequential data set, 顺序数据集
3 s7 x/ W; R' L, Q. [. K# VSequential design, 贯序设计- b% k" s/ |4 r) e" U+ L' Q
Sequential method, 贯序法, s+ B+ n* d7 [0 M% D L
Sequential test, 贯序检验法
. C/ f+ L% }0 m5 P q4 ySerial tests, 系列试验6 u9 R4 I( a, I3 c- I$ l% k7 a
Short-cut method, 简捷法 # u3 M& U& K; E; T, X1 S* Z
Sigmoid curve, S形曲线
. |2 i; W6 ~8 b. E* ]: U; A1 F. O& C# ^Sign function, 正负号函数5 [5 `" Y& ~2 x' m: h
Sign test, 符号检验$ u) c- w# j) Z. i4 U$ l% B
Signed rank, 符号秩
- B' @' c' B! ?4 L/ SSignificance test, 显著性检验
9 M- v$ L, o1 {2 p$ }Significant figure, 有效数字
, n- ^% b1 c9 Z4 |* \6 eSimple cluster sampling, 简单整群抽样6 T; ~, `) Z! {# c7 O
Simple correlation, 简单相关3 ^" H! `. H @& D
Simple random sampling, 简单随机抽样" p5 `8 t$ m) ]6 k, c0 D
Simple regression, 简单回归/ D3 Q* B, u' c; h: l q. Z3 w
simple table, 简单表) L; G3 a7 M+ O- J
Sine estimator, 正弦估计量: w* ^, {1 x# V4 Y' b9 ?% Q3 ~
Single-valued estimate, 单值估计5 K5 a( S3 C& [9 T) i( B9 V4 r
Singular matrix, 奇异矩阵2 K9 h$ v! S3 H& r0 l
Skewed distribution, 偏斜分布8 F/ ]! F; H, @( H4 k3 r3 R
Skewness, 偏度& t* a7 O" Q6 s d
Slash distribution, 斜线分布* I' z( m8 x3 N2 S& U
Slope, 斜率
: Y4 ?+ q: H; G6 A3 Q2 nSmirnov test, 斯米尔诺夫检验
+ _( T; Q8 i) L2 {# O5 [$ dSource of variation, 变异来源6 w* {& U; c4 T- ~2 j4 S
Spearman rank correlation, 斯皮尔曼等级相关
% l5 O6 f4 q: C- Z. m( [Specific factor, 特殊因子# _ z; Y3 i9 `6 c
Specific factor variance, 特殊因子方差0 e- B, h( n3 F& a
Spectra , 频谱: d0 `( P/ P5 S3 z+ [
Spherical distribution, 球型正态分布9 n: w5 G8 U. a c7 d$ q4 I
Spread, 展布
- V" L5 z/ g. ZSPSS(Statistical package for the social science), SPSS统计软件包
1 e( X- i- r7 N0 ~+ y2 T/ ?* N5 MSpurious correlation, 假性相关
{3 H! N- R2 d7 zSquare root transformation, 平方根变换, U- S: _3 w% O# o$ d
Stabilizing variance, 稳定方差
4 q4 K @. a1 C+ A5 F' E' oStandard deviation, 标准差- C, F, J6 Z9 E9 o4 t
Standard error, 标准误
1 Q9 r5 T0 q6 C; ?Standard error of difference, 差别的标准误
: w5 c% U9 A1 c4 B5 T5 MStandard error of estimate, 标准估计误差
# j" r+ a, I5 S7 MStandard error of rate, 率的标准误- r' G( f. d% J- |5 V0 h, N
Standard normal distribution, 标准正态分布) [) y. ^' T/ C, p( q( ^
Standardization, 标准化
0 x H1 |' R! W) d* Z& o4 sStarting value, 起始值8 t$ |7 x& A! Q% O( _! O/ a
Statistic, 统计量
" \( T6 J; f3 c: {; Z# dStatistical control, 统计控制3 w( W+ L- p% U6 s
Statistical graph, 统计图
6 s4 x2 T8 X9 e. oStatistical inference, 统计推断
# _, Z* t6 ?+ o/ y6 \Statistical table, 统计表
3 V( e( \; E, E* r, q) } Y2 BSteepest descent, 最速下降法
; M) y4 I @! e0 KStem and leaf display, 茎叶图1 ^* H# {* P$ ~ u7 P+ h e
Step factor, 步长因子
/ N2 a# n/ w& H aStepwise regression, 逐步回归
, p* V+ T* X, \$ o3 c* PStorage, 存
" `+ ^3 ]% N3 B, M9 k" XStrata, 层（复数）
5 R8 N/ K/ ~6 JStratified sampling, 分层抽样6 { h+ ]7 ^' Z
Stratified sampling, 分层抽样
% m9 I* C* z/ B2 n( O8 i- @: tStrength, 强度
1 r5 n0 L& a$ [Stringency, 严密性9 m7 F9 a# o% U# D: l& d% }
Structural relationship, 结构关系% S1 X1 ^/ G' Q4 v
Studentized residual, 学生化残差/t化残差6 l/ v% f* k- |
Sub-class numbers, 次级组含量
/ l! |0 X( S5 n0 A9 bSubdividing, 分割
2 W& J K0 E& S; f- o' QSufficient statistic, 充分统计量0 ~ y4 }3 \" M& N
Sum of products, 积和
5 A* k3 X9 ?+ e1 d/ h$ U# ^* rSum of squares, 离差平方和+ |2 m& }; E3 O5 i
Sum of squares about regression, 回归平方和 {+ g" @- M# F5 ?* n& {& C
Sum of squares between groups, 组间平方和
7 f7 ^; T3 V8 H& g: rSum of squares of partial regression, 偏回归平方和4 z4 d" u& @5 E; M1 H q: v) @; g3 e
Sure event, 必然事件4 |" J3 i( v5 N/ _$ m$ f
Survey, 调查( [5 P+ \/ L! o& g% z! O
Survival, 生存分析7 X9 b, k0 p: N9 }0 O
Survival rate, 生存率
5 @) a& I; e5 U6 s6 C$ o+ kSuspended root gram, 悬吊根图4 a: O6 u9 i6 z, y& K0 B
Symmetry, 对称5 W) r8 ?2 W: @; v# R
Systematic error, 系统误差, b, u0 t7 M( G" x3 }
Systematic sampling, 系统抽样% m* L5 d: i* B/ y' X
Tags, 标签
8 n# M2 `! ?" N$ ^Tail area, 尾部面积
2 d+ p" l5 e a/ N+ v: uTail length, 尾长- ~5 y4 q9 [. Q( \0 Y3 a
Tail weight, 尾重4 h% l1 u5 z( K+ }* ?4 X
Tangent line, 切线9 B; P s2 C# ]$ p
Target distribution, 目标分布6 i* P" e' t$ U, h" o
Taylor series, 泰勒级数
. V7 Z6 m1 N9 m8 C* P9 qTendency of dispersion, 离散趋势
. b8 z+ ?& Y3 Y: [Testing of hypotheses, 假设检验
* o& b% @, \2 T! e0 h" _4 r; h0 KTheoretical frequency, 理论频数
, P6 p+ Q+ y- W2 wTime series, 时间序列. N, e5 b! r/ a) w3 C
Tolerance interval, 容忍区间( K3 U4 ?# G M# l- [5 B
Tolerance lower limit, 容忍下限
" Q5 Y% n/ R6 B W+ X. W' M5 r2 wTolerance upper limit, 容忍上限
1 }4 h* t" f, Q& F- |: ITorsion, 扰率% o' }+ C3 q! a4 A/ y1 Z
Total sum of square, 总平方和: _- L, ?1 b+ G
Total variation, 总变异
! i6 M N: r, E6 R$ {5 j7 cTransformation, 转换
+ l$ K1 j% z" N! P l5 w$ i3 O4 _6 t9 UTreatment, 处理, u, H5 M. c, f' J. r: s
Trend, 趋势
7 c% b$ l- u; ~ t! Y+ A; CTrend of percentage, 百分比趋势! `% I! w4 N- k5 n! o# G
Trial, 试验8 _6 v* Z Y1 X; s
Trial and error method, 试错法
$ H1 t0 C" P* ]. B* K- y5 oTuning constant, 细调常数4 I1 G2 U/ p# u: ^3 M
Two sided test, 双向检验
8 j0 w; B) I3 z) v7 o: A8 PTwo-stage least squares, 二阶最小平方$ _9 o3 Y; N- B# W
Two-stage sampling, 二阶段抽样
8 L+ D* N9 j- H9 V' K* E, h% gTwo-tailed test, 双侧检验
+ c$ {3 e o8 _2 q* CTwo-way analysis of variance, 双因素方差分析, n5 ]9 d- u; s1 D
Two-way table, 双向表
9 u+ k0 r. k K1 f* L: qType I error, 一类错误/α错误! d) V" f: D; X9 Y' a* O
Type II error, 二类错误/β错误
+ Z4 d, p/ w! x! [UMVU, 方差一致最小无偏估计简称$ p. ?: p4 J; a, L2 [7 C# Y0 R
Unbiased estimate, 无偏估计& i$ Z- U8 i1 l6 m& [
Unconstrained nonlinear regression , 无约束非线性回归; J. d9 U9 A3 j0 q
Unequal subclass number, 不等次级组含量5 x+ j, b. c$ }1 q8 M6 b2 W$ {6 K( b
Ungrouped data, 不分组资料
" A: c1 t; j' i( g+ gUniform coordinate, 均匀坐标
0 f# ?0 ?) n' p9 F7 c3 ]! k* U) Y5 tUniform distribution, 均匀分布
4 d% d/ x% b3 G0 P" K5 P, gUniformly minimum variance unbiased estimate, 方差一致最小无偏估计( @8 }. t3 I# P/ i/ Z% Y- w+ J
Unit, 单元/ B- L& J C `4 P' _: g
Unordered categories, 无序分类5 b5 a/ ?5 e8 C2 P# j5 D: F3 L$ s
Upper limit, 上限# _$ p& m5 f/ W' ^
Upward rank, 升秩0 B0 A1 {# v% ?$ Y; I
Vague concept, 模糊概念, b* ^# {; i1 ]" A0 D, j
Validity, 有效性
' [. e7 x0 Y; Q6 Q: G% BVARCOMP (Variance component estimation), 方差元素估计6 N! ^" h: R$ b0 O) d
Variability, 变异性# q0 i: h3 h5 m7 y1 _# Q
Variable, 变量
, W( C$ A' x6 Y3 j {3 XVariance, 方差$ K: _- ~% v) @7 w3 c
Variation, 变异
+ _0 f u$ b( @* A: [ ~; x4 HVarimax orthogonal rotation, 方差最大正交旋转
# q8 F. V& E# @! D% z9 _Volume of distribution, 容积2 y" }0 W% |8 b; a& l
W test, W检验
; X, Q A Q& M0 j$ ~Weibull distribution, 威布尔分布
4 {/ e: J l: S7 d. g' `Weight, 权数 d% B8 U# a( C/ q1 B ~6 y0 H
Weighted Chi-square test, 加权卡方检验/Cochran检验! h. l( a4 v2 ?6 L+ U" t
Weighted linear regression method, 加权直线回归
1 G$ Z1 m# A0 m% U$ q6 QWeighted mean, 加权平均数
: K8 f" X& M' |1 V) w* p7 W2 EWeighted mean square, 加权平均方差- X9 r( w+ w) `7 j) o# F- T
Weighted sum of square, 加权平方和" Q( r: v2 z7 E
Weighting coefficient, 权重系数3 z2 D1 L0 u0 j$ p0 E6 m, m7 f
Weighting method, 加权法 2 g% L: ?% `9 V2 ?# Q; O; [( E: B
W-estimation, W估计量$ _4 L( O7 b9 z: |. |2 \
W-estimation of location, 位置W估计量
8 ?% r. z0 J0 ~( D7 dWidth, 宽度2 I/ j" N, L) V$ r: z* k( l# s
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验8 h5 u, ]( ^0 R4 e+ C
Wild point, 野点/狂点
' K( D/ x2 ]3 o5 N0 \7 @5 y: \Wild value, 野值/狂值% y0 N( U% U; L2 `; F
Winsorized mean, 缩尾均值
7 A2 o9 g, B7 Y6 \Withdraw, 失访 ( ^. p) ?7 a( h% C
Youden's index, 尤登指数
6 q" y9 ~# F. V7 ?% m; GZ test, Z检验
4 }7 s# T5 s4 ?1 a( Z' S% bZero correlation, 零相关& N( i) j; V/ c! e5 M
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
