|
|
Absolute deviation, 绝对离差
/ ^$ E g% [# @* R# kAbsolute number, 绝对数
8 i) M6 K0 q1 @$ YAbsolute residuals, 绝对残差1 J+ n" Q) ]" x8 ?# M+ S2 q
Acceleration array, 加速度立体阵
0 c7 S1 H0 S& T7 e- K: v3 r- uAcceleration in an arbitrary direction, 任意方向上的加速度 Q; I1 f9 L: T7 B; ^* M% M+ I5 K9 x
Acceleration normal, 法向加速度
/ H) j1 t5 B( n2 t( g* d* DAcceleration space dimension, 加速度空间的维数
]; a9 H; L; f* ^" E- rAcceleration tangential, 切向加速度
) _ {. q5 L8 T: _Acceleration vector, 加速度向量- o( S& Y; d( b8 Z
Acceptable hypothesis, 可接受假设7 W7 q y/ `- N& a
Accumulation, 累积) I: n2 a# g4 w. l
Accuracy, 准确度" ~3 {. P# ~2 g8 {) N: d' y
Actual frequency, 实际频数
% J; u7 q" X# jAdaptive estimator, 自适应估计量
! z1 e v C! ~5 DAddition, 相加1 L+ y% \, P. d7 {
Addition theorem, 加法定理
3 J8 t* e( R" m4 i9 j; ^0 RAdditivity, 可加性' f) \4 [' M/ q# U/ i6 ^
Adjusted rate, 调整率6 M2 e# P4 v' p3 M* @
Adjusted value, 校正值2 F3 }, Q+ _; t
Admissible error, 容许误差; G+ v/ b( i0 O) M0 X. m$ r6 E
Aggregation, 聚集性
4 l, D# g j: n. e. `Alternative hypothesis, 备择假设* O; \: j% g2 _7 w
Among groups, 组间
. X3 k# I; B' `. l* xAmounts, 总量
( n" Z+ z2 ~$ J0 U. A3 vAnalysis of correlation, 相关分析% @3 f. k1 A* v* Z Y8 r/ }4 G
Analysis of covariance, 协方差分析
- C, g! k0 w. t% V% C+ w$ L' BAnalysis of regression, 回归分析& S s/ m$ J4 p; t+ v+ ~9 \
Analysis of time series, 时间序列分析
( t. k& D8 q5 J) @8 ^Analysis of variance, 方差分析
- Q! T6 O$ v, Z% L! J. _+ nAngular transformation, 角转换
* O# [6 P7 G% L, O" c s5 w/ F2 r' l: _ANOVA （analysis of variance）, 方差分析5 M) M1 R2 z8 ~4 J/ O$ D
ANOVA Models, 方差分析模型1 i) p( e* [: j- @; a
Arcing, 弧/弧旋% Y( z; b4 H2 \7 O! G, \
Arcsine transformation, 反正弦变换3 |8 y6 Y0 x5 u. u2 k" F
Area under the curve, 曲线面积* G3 T$ g, c% v- F. V
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
: r* d1 B" V% ^# z$ b9 Z6 ]" GARIMA, 季节和非季节性单变量模型的极大似然估计
0 P% ?8 _6 n0 s4 dArithmetic grid paper, 算术格纸
8 f X$ w) A7 iArithmetic mean, 算术平均数
, w5 s0 g; ]3 \. ?$ h) z dArrhenius relation, 艾恩尼斯关系8 Y! y2 g! n& e
Assessing fit, 拟合的评估
4 B8 F$ {, ? Y: d& ?Associative laws, 结合律9 T& _, ~" ~9 }8 x
Asymmetric distribution, 非对称分布
: n, P: B* ~' QAsymptotic bias, 渐近偏倚' O0 y1 i! k+ q. x: O7 ?6 ~
Asymptotic efficiency, 渐近效率
% d, |/ A( {$ Z) HAsymptotic variance, 渐近方差
8 e$ f8 R9 V- c% O9 ZAttributable risk, 归因危险度# y& a% ]/ d8 A/ O: a
Attribute data, 属性资料$ | G+ O5 Y; p) R3 }: j V
Attribution, 属性
+ q6 D2 h6 P+ N7 KAutocorrelation, 自相关& `1 Y. \: d/ g8 r0 w" {! ]
Autocorrelation of residuals, 残差的自相关
) Y6 w6 b, X, X3 S) DAverage, 平均数; B n7 K j/ P0 Z' N5 V, J
Average confidence interval length, 平均置信区间长度4 d) t( z* ^, r+ A! q# g1 D5 E
Average growth rate, 平均增长率
# k* ]! p) ^9 I5 X( D/ E& sBar chart, 条形图, Z+ Y R# K" { {0 y5 \
Bar graph, 条形图
. H6 A9 X' P8 E8 r) e7 v' S+ `) LBase period, 基期; R0 C O* \0 h! b) h/ E/ E; b
Bayes' theorem , Bayes定理
* b7 n$ }) \- }) V0 HBell-shaped curve, 钟形曲线
! t) D- `6 B. }' `3 V* j6 N4 VBernoulli distribution, 伯努力分布: P5 v% F; _6 {$ [
Best-trim estimator, 最好切尾估计量
6 }1 x0 M- M. G9 ?& l" D: jBias, 偏性& n' M6 l0 `8 j T) j
Binary logistic regression, 二元逻辑斯蒂回归& P1 O4 U* t- z/ m
Binomial distribution, 二项分布
6 {% c+ E7 q% b8 l1 ^Bisquare, 双平方1 t9 O$ E+ z0 m$ I3 X
Bivariate Correlate, 二变量相关 @& p- |* B2 W- z9 A5 d
Bivariate normal distribution, 双变量正态分布
, X \4 h: b( B. E) N$ ^Bivariate normal population, 双变量正态总体
8 b; N. O) U2 h) X0 rBiweight interval, 双权区间7 V0 l: R. F8 w* {& o6 O
Biweight M-estimator, 双权M估计量
" T8 z' \* v$ k) K# s: bBlock, 区组/配伍组
9 X* V1 \: U/ a2 j tBMDP(Biomedical computer programs), BMDP统计软件包* N3 F+ G0 r! i- u
Boxplots, 箱线图/箱尾图- i0 O k+ H: S" X6 ?
Breakdown bound, 崩溃界/崩溃点
& B( m5 o+ f/ l! I( g, rCanonical correlation, 典型相关
7 N; w5 f; o4 G, g2 S tCaption, 纵标目
- I3 l9 V6 A+ Z% K9 I+ _; _! ?Case-control study, 病例对照研究& B7 t4 |# e7 ]% ^: h( ]( A" I! t
Categorical variable, 分类变量
: a- x4 G& T: b; uCatenary, 悬链线
% I8 K; E6 X; uCauchy distribution, 柯西分布/ Y: X7 `, @9 |) y
Cause-and-effect relationship, 因果关系
! h& Y5 d% _5 l. n; W8 ?9 s! UCell, 单元$ \- j0 u( h: x0 N' ~
Censoring, 终检
3 v3 @. V! }9 }9 {* y# BCenter of symmetry, 对称中心% s7 I2 | U) |( W v
Centering and scaling, 中心化和定标' h, S/ S8 `; d* ~
Central tendency, 集中趋势0 R% y0 e7 A4 g9 {
Central value, 中心值. M0 w( L& D' P$ ~ I' q
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
$ w* V" H# y0 i t% ^+ SChance, 机遇
1 N8 a8 k# F6 G; D* t0 y. OChance error, 随机误差3 p7 E8 A% `7 ]
Chance variable, 随机变量* a% p9 Z+ w# ?
Characteristic equation, 特征方程8 t. W8 m- I9 q f4 J1 h
Characteristic root, 特征根
& U2 [1 J- |: U0 ICharacteristic vector, 特征向量
& S) R5 Q% V; ?# e8 Y" h, E8 UChebshev criterion of fit, 拟合的切比雪夫准则; D; S( M8 K$ X) R# V9 ?
Chernoff faces, 切尔诺夫脸谱图" i( {! V7 x0 D) ~+ M
Chi-square test, 卡方检验/χ2检验
, V6 v+ e0 J, t7 a% T, l7 SCholeskey decomposition, 乔洛斯基分解" u1 h* a/ ]6 `9 B' T8 m3 }
Circle chart, 圆图 & v d: N$ X. f6 h% I
Class interval, 组距- [* c* E2 ^8 E+ l/ G
Class mid-value, 组中值$ j) T# U7 @- Q
Class upper limit, 组上限
9 H! r$ m7 } iClassified variable, 分类变量
9 ?- Y* Z# F6 M& bCluster analysis, 聚类分析
9 L- c* Z# U d6 ZCluster sampling, 整群抽样' C; |9 v0 X3 \
Code, 代码0 E0 f. i. A. I* W$ h ]+ c
Coded data, 编码数据" g) u0 y+ V1 o! P! l2 b
Coding, 编码
) ]' d+ ?5 e0 d; W9 ^; M; @( h tCoefficient of contingency, 列联系数# t% u; K; g! a2 j: e
Coefficient of determination, 决定系数: K7 H. U) s9 I3 h9 ]$ I- S* S" G
Coefficient of multiple correlation, 多重相关系数
2 X+ @* E0 m1 u5 X2 q) s# y4 CCoefficient of partial correlation, 偏相关系数
( s" e, q, P5 }" P% n' G0 @# E tCoefficient of production-moment correlation, 积差相关系数4 u- P) }# ~4 T# b" o* Z' u
Coefficient of rank correlation, 等级相关系数
7 j* J" Y$ Q# b Y) T! o+ a& r" nCoefficient of regression, 回归系数
: B- @; R, ]- T" |$ ? o8 LCoefficient of skewness, 偏度系数; c6 Y2 |' ^% {$ O8 {4 e; U2 {
Coefficient of variation, 变异系数' w" r. S ~6 R2 ?6 c- M+ s* e
Cohort study, 队列研究
: d! G! I; x; b2 c/ b& RColumn, 列
2 r0 B% B7 r$ H- r' c+ [1 C) z3 N7 OColumn effect, 列效应( }3 z8 i& W; v7 W9 ]2 A+ l! ]
Column factor, 列因素
" d1 t& |$ {4 E8 V) \" Z4 ACombination pool, 合并
( j! A% u0 {7 X' kCombinative table, 组合表! a4 f4 T+ o2 w: P) W0 [
Common factor, 共性因子
v9 W! _% S/ O' Z1 g1 T2 {6 SCommon regression coefficient, 公共回归系数$ C4 |: r" U; g# y; `+ m. y5 n
Common value, 共同值
, j M( n8 `0 B2 Q% gCommon variance, 公共方差& y5 o2 x* V# ?& O+ ?3 j8 h, i
Common variation, 公共变异0 J0 K) \0 w# {: f$ ]
Communality variance, 共性方差
$ K/ W9 }8 x8 ~7 hComparability, 可比性
% H( x+ E8 Y6 {Comparison of bathes, 批比较
# |2 s% Z+ A- d. Q! g a. @* AComparison value, 比较值
7 _/ l$ a3 d, m$ s% M5 J( z/ xCompartment model, 分部模型
9 ]0 T. q: N8 \. U& K& LCompassion, 伸缩
4 j1 K: N2 c1 MComplement of an event, 补事件
W$ G! G1 ?- B8 N: C& T1 [Complete association, 完全正相关
6 i; Y. s0 S7 g/ \9 V% J8 G4 n" ZComplete dissociation, 完全不相关
{8 x, b: D7 r6 J. mComplete statistics, 完备统计量" X d% q5 e) f
Completely randomized design, 完全随机化设计2 Z$ T' m, I* i7 E: A0 b& k
Composite event, 联合事件
5 b3 t6 a" O' C0 w z1 S0 E7 I2 w6 e7 YComposite events, 复合事件& `! t! [3 R. u, k S" y/ I
Concavity, 凹性
, K. Y5 B" y) K/ ~2 L1 KConditional expectation, 条件期望5 z0 p F3 y) Q$ L; U
Conditional likelihood, 条件似然
& i% a7 C1 T; G- _+ HConditional probability, 条件概率- [ | w! X/ c! x) z
Conditionally linear, 依条件线性! I) F' g9 K, ~, Q( |/ w
Confidence interval, 置信区间9 ]; Q- F2 M) _; [
Confidence limit, 置信限
# M' b$ ^) [0 O7 y; n: _Confidence lower limit, 置信下限
# |$ w2 q& j/ K7 _- [% |( \( WConfidence upper limit, 置信上限
+ G- j1 i0 |- ^, N& q3 P6 PConfirmatory Factor Analysis , 验证性因子分析
a, i) `0 M" ~1 H/ _6 `. R5 ~Confirmatory research, 证实性实验研究
6 b; ^- z+ o5 \$ {) {Confounding factor, 混杂因素
$ P0 s7 c& v8 LConjoint, 联合分析
" z0 z; X9 @0 D [0 i) |0 QConsistency, 相合性
3 E/ X' T: G! }: D; ^, s' EConsistency check, 一致性检验8 t" f; {& {! z
Consistent asymptotically normal estimate, 相合渐近正态估计
5 g7 {2 c4 D0 [& {' Q2 LConsistent estimate, 相合估计2 ]3 R2 S A; ^. Z3 u( i& W+ G% L/ U
Constrained nonlinear regression, 受约束非线性回归
; U0 {* `! Z. }9 h1 CConstraint, 约束
( E' @& J( v0 b" l3 _Contaminated distribution, 污染分布
$ C& ~7 l: a! d6 J- \, DContaminated Gausssian, 污染高斯分布
/ p6 ~8 j; I7 V, |Contaminated normal distribution, 污染正态分布
) e7 V- c" p5 `* L0 g( H7 lContamination, 污染6 C2 X4 J: ]! c$ S
Contamination model, 污染模型# T' ?4 R! F' @9 ?
Contingency table, 列联表
: B7 A0 y8 i- x5 W$ I3 SContour, 边界线# Z0 S5 Y- J o- _, W0 L
Contribution rate, 贡献率
I1 i: L- o% gControl, 对照- s5 D# p6 g" b r! l! T* ^
Controlled experiments, 对照实验/ P0 A* z) c) l, v# s% e9 x
Conventional depth, 常规深度
* d* ?- B( [# D* U$ v7 c5 P! DConvolution, 卷积# F" m) \# e- l# {/ y T" |
Corrected factor, 校正因子
' V$ E3 ?* Q w M/ f @! yCorrected mean, 校正均值
: Z7 `. K4 _5 fCorrection coefficient, 校正系数- x% ^( A* h$ }/ g$ z# ~
Correctness, 正确性
% y" N* F5 l, }' ACorrelation coefficient, 相关系数
' W' d* U/ S# {8 w% \2 NCorrelation index, 相关指数: ?0 x( D! v+ j8 E9 G3 K
Correspondence, 对应
* v# a7 y+ j; eCounting, 计数
( w; H Q% p( q: `' f6 y& V' BCounts, 计数/频数' }% z, Q9 X- T& m& W
Covariance, 协方差6 y2 k( P1 S1 T/ q( J
Covariant, 共变
5 P/ Q% [% q' |+ P7 u/ `' @Cox Regression, Cox回归
2 ?* R% K3 z. @2 W ]Criteria for fitting, 拟合准则. l# F5 m3 w/ I2 ?/ f2 s+ h
Criteria of least squares, 最小二乘准则5 b/ U T& g/ d9 }6 s- L. K. [" v4 J
Critical ratio, 临界比
% }+ x% ^$ R1 t; r( v# B# oCritical region, 拒绝域0 H9 y* [1 D) k; ]+ O( e
Critical value, 临界值& D4 G9 _# x" ]
Cross-over design, 交叉设计
9 k8 X1 {$ V( ]3 z7 D3 OCross-section analysis, 横断面分析
+ l, l1 C; x; M' I6 A2 [Cross-section survey, 横断面调查: C) M0 x6 T# ^7 r0 G1 ?: g
Crosstabs , 交叉表 @6 O0 Z* w* O; r7 l
Cross-tabulation table, 复合表2 i3 _1 z' F. f! Z+ \9 u1 M
Cube root, 立方根/ D$ F7 p% w4 f+ O; l
Cumulative distribution function, 分布函数1 S: l1 _! X% z( w9 P% m8 {
Cumulative probability, 累计概率
) C" Y# i7 f# n, U' d0 `Curvature, 曲率/弯曲" Z0 z3 D8 v; {8 H
Curvature, 曲率
- d1 Y) P B* T. ^$ b6 k/ @Curve fit , 曲线拟和 q0 R$ B. R {& A
Curve fitting, 曲线拟合
* ~' U; `/ m; W$ }8 KCurvilinear regression, 曲线回归9 Z. |3 d, F8 @
Curvilinear relation, 曲线关系
) a" z$ F1 }- [! y; ?Cut-and-try method, 尝试法
! ^' | D& i6 M; x: C V4 |Cycle, 周期
, x* E# ^1 r! t6 k2 D8 N4 Z; x) wCyclist, 周期性
( g! o5 ]3 F# q% G% _ q" TD test, D检验
' K4 Q: ~& k6 t E' |0 gData acquisition, 资料收集7 n6 {- q) j. q4 o% l
Data bank, 数据库+ ^+ P" {+ Q9 l: [* ~, e; Z- Q
Data capacity, 数据容量# K( i/ Y* m# X2 r
Data deficiencies, 数据缺乏
1 ~ S8 r# M7 }% EData handling, 数据处理1 j0 R7 ] ~' l2 H3 S
Data manipulation, 数据处理+ I1 a4 ^, g5 K
Data processing, 数据处理
( R9 \% [* N$ h: u) k: VData reduction, 数据缩减
/ l. }2 G8 V4 d6 y$ R! N" aData set, 数据集5 W5 r. h7 f( y* t" ^$ A5 L
Data sources, 数据来源
( w8 h7 i6 l( O7 v L7 r aData transformation, 数据变换6 m t$ D, L( L& s3 Y1 s- x$ `) i- O
Data validity, 数据有效性3 U; k- \! y; A) N! D
Data-in, 数据输入, K7 n" _# a" _4 a3 O% o+ r
Data-out, 数据输出
' k. B+ Y& D5 Z; H1 hDead time, 停滞期
$ l5 x& w* u" E5 F- \Degree of freedom, 自由度
. B7 _) ]& ^. ?' EDegree of precision, 精密度3 B% {, F8 f4 t+ }8 @* q
Degree of reliability, 可靠性程度
/ z( W/ K7 S: H7 }& vDegression, 递减( A& [! |7 \2 M
Density function, 密度函数
0 X( v+ u, i2 h3 }6 E ~; sDensity of data points, 数据点的密度' k% @% X* [ q% r$ I9 K: _
Dependent variable, 应变量/依变量/因变量" o! i" e- e$ S9 Z2 @
Dependent variable, 因变量
- l8 { Q7 {/ bDepth, 深度+ ?6 {: t% G- g- I) s$ n
Derivative matrix, 导数矩阵1 I. g2 w( r! T
Derivative-free methods, 无导数方法
M& a" L4 R1 K) ?" J: Q2 KDesign, 设计
( r( K/ ^" X3 v* t* ~Determinacy, 确定性! c/ H6 S# C1 _* ^0 ~
Determinant, 行列式
5 U* ?5 E+ F! C% v: |Determinant, 决定因素3 G2 R. O! \6 e8 f6 H+ O& R
Deviation, 离差
6 K. ?% v2 s' b. N# e& k7 hDeviation from average, 离均差0 P( F- F0 E" {( u7 c+ I7 f# z, h/ N
Diagnostic plot, 诊断图& \2 ? V+ ?3 [& @1 S5 ?5 g: m+ Z$ {
Dichotomous variable, 二分变量
6 f4 Q3 N5 W( x" T" oDifferential equation, 微分方程
( n* Y W" V( A% g% _Direct standardization, 直接标准化法
Z: V" l. T: @: nDiscrete variable, 离散型变量
2 p4 R# B7 K- U ?/ V: i1 IDISCRIMINANT, 判断 / _9 _0 R% n) }# |2 Y5 p
Discriminant analysis, 判别分析
7 k9 x3 ]* a; L' Y" R$ m* v7 i' dDiscriminant coefficient, 判别系数
* o( r) a2 W+ N; a: W3 vDiscriminant function, 判别值
# s: f0 N. I$ b7 Y; D6 e$ Q, r MDispersion, 散布/分散度' H# N& G+ G; S9 r
Disproportional, 不成比例的
- V) K. u+ V; G7 ?; z1 s+ T& _Disproportionate sub-class numbers, 不成比例次级组含量
3 _$ j' `9 v; y8 ZDistribution free, 分布无关性/免分布& Z) p8 w/ }4 N
Distribution shape, 分布形状
+ K6 J9 D: k7 Q" w: H5 e% p7 EDistribution-free method, 任意分布法
}* J$ h3 I( O1 LDistributive laws, 分配律2 P6 C6 d( u* D
Disturbance, 随机扰动项* l# Q9 D, E/ ?. \
Dose response curve, 剂量反应曲线
; z( {8 j d+ T$ x3 ~4 qDouble blind method, 双盲法
2 @* t3 D$ i6 T8 I% k7 dDouble blind trial, 双盲试验 t/ Y4 t) d6 J
Double exponential distribution, 双指数分布1 s- q/ h, ?7 o, l
Double logarithmic, 双对数6 B* P( B, K3 J% Q/ q
Downward rank, 降秩# \$ ^9 x$ c* w1 K0 F
Dual-space plot, 对偶空间图3 I6 i" @" r% d o' {3 ~7 N* p
DUD, 无导数方法
. u6 R# @2 G/ j$ M7 a- Z8 ^! n7 v m7 nDuncan's new multiple range method, 新复极差法/Duncan新法0 R9 @3 u& c( Q) T% E
Effect, 实验效应
' n* d4 n3 d# J. K& }5 |Eigenvalue, 特征值
. n' w8 p4 @# U6 M U* c" k7 D" eEigenvector, 特征向量
) [9 A1 i" I, A/ d6 C; X' P: H* P# IEllipse, 椭圆# L( ^' @( B" k7 o" m
Empirical distribution, 经验分布: f) s2 a3 J2 W6 @ |6 h0 y
Empirical probability, 经验概率单位
) h+ o8 I& K) ]8 R3 wEnumeration data, 计数资料
7 w1 }' H! g, I, XEqual sun-class number, 相等次级组含量+ d+ v7 w- r- L; `* }3 w
Equally likely, 等可能* b* k3 h0 q" [$ B% O. a3 z8 a3 C
Equivariance, 同变性4 U3 M! P# i3 H, A8 M/ m6 g A9 L4 _
Error, 误差/错误 t5 ]* p9 g: I: H3 p3 e
Error of estimate, 估计误差
4 t" H e! }' Z, x5 p. qError type I, 第一类错误
/ Y3 A1 N- h2 c: b2 @9 uError type II, 第二类错误+ L5 V _! i0 _5 k+ s
Estimand, 被估量" d. k7 B, p8 u4 V! c) ^# b6 X
Estimated error mean squares, 估计误差均方+ y( C9 o4 L3 D/ m
Estimated error sum of squares, 估计误差平方和 ?( C2 f0 l: C9 e4 `8 `; `
Euclidean distance, 欧式距离$ _" h) l' F" \
Event, 事件
6 _, B+ q; ~( _% G& y1 wEvent, 事件# @# V2 k+ s- u, S h8 {3 h) K
Exceptional data point, 异常数据点
2 F: \& Z0 B2 k" Z2 _Expectation plane, 期望平面
1 c, Y' P3 K" W. cExpectation surface, 期望曲面
3 w C* V2 \$ H qExpected values, 期望值
4 D! Q& p( z" }' sExperiment, 实验
6 f; J0 I6 {; N9 S& ]# fExperimental sampling, 试验抽样* k5 U' p5 p- u7 K' p: q
Experimental unit, 试验单位
1 J% k: O: J5 X! bExplanatory variable, 说明变量
5 T- O& Q# \/ I3 \/ s8 ?Exploratory data analysis, 探索性数据分析
5 i4 H& X/ k# d0 ]" dExplore Summarize, 探索-摘要
. Q, p$ y1 P/ O" f5 vExponential curve, 指数曲线
+ Y5 G1 Q& T7 _ k6 G- ^2 q' ~4 P; ^Exponential growth, 指数式增长
# `$ m' T* [# m7 nEXSMOOTH, 指数平滑方法 E1 E1 U1 X3 }1 c$ u, y* Q7 O$ C2 F
Extended fit, 扩充拟合
3 W) P% D, q( f7 A" d7 NExtra parameter, 附加参数
: y) ?$ t: O. [8 k1 g1 ZExtrapolation, 外推法
' Q, b, {0 [# g- j" MExtreme observation, 末端观测值
8 w! _4 U+ P6 ?( IExtremes, 极端值/极值
r7 |/ M: `' VF distribution, F分布
" o2 f- y ?0 ]1 y/ L' H; ~" YF test, F检验
\+ U! I- u2 \' g3 p' `/ ~Factor, 因素/因子0 ]3 R4 {9 q t# L& M* h
Factor analysis, 因子分析
# X& h) K' P: f6 fFactor Analysis, 因子分析6 J( P+ k1 N0 u) |, z
Factor score, 因子得分 & Q* L+ r! A# T3 q- t s
Factorial, 阶乘& q$ H- S1 z/ `7 y
Factorial design, 析因试验设计& R3 v- C4 J3 q x5 r. ]6 s
False negative, 假阴性$ R$ Y0 g5 A" `. R$ X$ Q- I/ N
False negative error, 假阴性错误$ G5 i7 a6 N" s! v; \+ x
Family of distributions, 分布族
& N$ P+ A* y2 S% X3 u, f# kFamily of estimators, 估计量族% ~& [& }" Z2 D, d8 X- b" r
Fanning, 扇面- e4 i6 V! h, e$ X& J# Z c, D
Fatality rate, 病死率
# a, A6 E8 {7 u9 H' V; d, mField investigation, 现场调查7 }% U( O0 r' E3 Z
Field survey, 现场调查: H: v0 L: C* w/ ?3 J
Finite population, 有限总体) k( R! M& U7 d7 Y; ~
Finite-sample, 有限样本2 ]# f2 D/ \& k' W7 t: T
First derivative, 一阶导数3 G3 N3 j' ?/ Q( D8 Y$ f+ P
First principal component, 第一主成分
3 z- B5 F0 I! P- z- r) S0 q0 k/ eFirst quartile, 第一四分位数# O8 M5 c" ]% e( b; A
Fisher information, 费雪信息量4 I9 I% m; ~& x l r& [* U1 a
Fitted value, 拟合值
8 {9 k* D, g' y. P8 n3 `& a( F# lFitting a curve, 曲线拟合
' `7 K1 l, G: T$ R4 V! m1 ]% pFixed base, 定基
g' t) ]# g9 c9 V; D6 r3 ^Fluctuation, 随机起伏
4 D' e1 r+ b/ Z# o( L7 h5 Q& AForecast, 预测& w5 d& k: I/ b1 S: A
Four fold table, 四格表
0 p' X8 R8 D; W3 M9 sFourth, 四分点
7 ]' p' Q0 y5 FFraction blow, 左侧比率
# d J9 P8 D% q7 m/ k. M- y) wFractional error, 相对误差
" K, U6 b$ [& \5 E; v* u! wFrequency, 频率
" M9 x3 ?& d* Q+ c7 X$ G7 jFrequency polygon, 频数多边图" E) t8 b, R: u7 q
Frontier point, 界限点
3 p+ y7 u {& {7 b0 EFunction relationship, 泛函关系
9 w& Q- ?1 V) h* k8 b' k) |4 iGamma distribution, 伽玛分布
6 k4 B) u2 v* \Gauss increment, 高斯增量& s; S# s3 b; x. R/ A y
Gaussian distribution, 高斯分布/正态分布
3 E& r( j$ L+ u$ D7 W( |9 y: AGauss-Newton increment, 高斯-牛顿增量
/ Q. t3 z& l- C3 V) {# lGeneral census, 全面普查0 d- q0 L1 P8 d6 ~" t; j0 O2 ^
GENLOG (Generalized liner models), 广义线性模型 3 T1 F* M3 F3 _$ H
Geometric mean, 几何平均数7 d7 ` F _% u- O" J3 r; V# x( `7 {
Gini's mean difference, 基尼均差* ^( [+ P! ~) F
GLM (General liner models), 一般线性模型
( F2 M: f9 O0 B, mGoodness of fit, 拟和优度/配合度' O# U3 D8 F6 n, p; o9 e
Gradient of determinant, 行列式的梯度9 a. Q; S# O! F! H8 B/ d9 a
Graeco-Latin square, 希腊拉丁方
2 j: q1 t5 U# [) f3 S7 pGrand mean, 总均值3 J7 W* M3 a, l9 x! V
Gross errors, 重大错误% {- k b) w0 f
Gross-error sensitivity, 大错敏感度2 [6 [/ C. p& p0 a
Group averages, 分组平均% L2 P' p$ T: i. _% c9 @( K
Grouped data, 分组资料8 w# h" T! g( G% u0 [
Guessed mean, 假定平均数7 ^8 a; F/ Z! i9 g5 v9 C
Half-life, 半衰期& ~2 a( z: ]3 i) X# o
Hampel M-estimators, 汉佩尔M估计量7 g' C& u1 \7 B4 d
Happenstance, 偶然事件# x! b! k( F8 S/ ^( H
Harmonic mean, 调和均数# I/ f! R- b2 b
Hazard function, 风险均数% }, d9 u/ j$ N2 |! ?% Z0 {
Hazard rate, 风险率
' y% z1 | ~, H3 UHeading, 标目 * h5 _% O$ I, f
Heavy-tailed distribution, 重尾分布
6 E: h% x5 N0 R; Q9 e- f% a) lHessian array, 海森立体阵
W, A' n5 L/ c1 E [Heterogeneity, 不同质+ ~0 k" B8 x1 ?# g4 G
Heterogeneity of variance, 方差不齐 ' S( O6 c6 I3 K& A& }; K
Hierarchical classification, 组内分组
, r: ]! L3 o5 l1 UHierarchical clustering method, 系统聚类法1 x- _! Y9 A1 m, s' S, ^6 L" [0 z) _
High-leverage point, 高杠杆率点
, }% j& a0 p1 n' ~- E- uHILOGLINEAR, 多维列联表的层次对数线性模型" T' l5 r2 r; D3 W7 R% S
Hinge, 折叶点% R7 \$ I$ H( n+ V! A" U
Histogram, 直方图 \) n O) S- g& z5 G% G
Historical cohort study, 历史性队列研究 / b8 L. @1 C( d, @ f7 ~0 V* V
Holes, 空洞2 G9 h p" _7 g+ s% r4 `
HOMALS, 多重响应分析& p6 b, o3 k2 V7 {6 l! o3 u7 J
Homogeneity of variance, 方差齐性
9 _( ?2 z' w" B4 x; D( vHomogeneity test, 齐性检验9 G& M2 v& {8 u
Huber M-estimators, 休伯M估计量
( l I. v* }" G" A2 \Hyperbola, 双曲线$ {6 C) Z7 M. ]
Hypothesis testing, 假设检验
" x! O0 ? Q; p2 `" jHypothetical universe, 假设总体
7 w) m3 z( ?3 C7 _7 [* p$ P: L3 c0 VImpossible event, 不可能事件+ D4 {& o$ ?! V( t% X
Independence, 独立性" \4 W# R7 o3 }# W$ @
Independent variable, 自变量 Y \1 L: n# J6 h
Index, 指标/指数
0 C+ I- F! A4 E" {, _6 YIndirect standardization, 间接标准化法2 w* V) w& s) @
Individual, 个体
' R0 l' G$ T4 ?- k* w# sInference band, 推断带
, K- F* k. b: Q7 e1 B9 TInfinite population, 无限总体
, r2 Q3 ?8 c1 f. d) TInfinitely great, 无穷大
5 s) G K$ x! t4 P: a2 jInfinitely small, 无穷小/ i( ]& @7 f$ `& n1 y
Influence curve, 影响曲线7 a3 ~, a+ [0 \, U7 D2 J6 r
Information capacity, 信息容量, F; [4 ^2 H3 {2 ]% t8 ^
Initial condition, 初始条件
( `3 N+ N, E v; x8 U( \1 o3 fInitial estimate, 初始估计值2 @( Z: ^) b" ^$ j. [" c
Initial level, 最初水平2 j9 I( O' x& C3 k9 ?0 o$ y1 h
Interaction, 交互作用& ~( e. i* x: [' B/ a" g+ J
Interaction terms, 交互作用项
: u! l; g' }$ i# a- g8 zIntercept, 截距2 l8 h! [' R, C' U2 g% r B! u
Interpolation, 内插法0 r" @, J/ p/ f. P. E; A R
Interquartile range, 四分位距9 I: g, N% z& T3 O# L% p
Interval estimation, 区间估计, X2 a! f3 A; j( |" n! P
Intervals of equal probability, 等概率区间
( Y4 D0 o Z9 YIntrinsic curvature, 固有曲率; |5 b3 G$ H9 D8 \3 c1 P+ C
Invariance, 不变性, r0 U# Z6 F# \8 X. ]1 t
Inverse matrix, 逆矩阵; Y. I( }% l3 X0 _' \% N% W
Inverse probability, 逆概率
$ _' S! w' ?; b# z' z8 X0 ZInverse sine transformation, 反正弦变换) o) l1 O- k$ _+ Y
Iteration, 迭代
/ {8 ^# k! M1 ]$ gJacobian determinant, 雅可比行列式
+ a- J! l& X+ ?& vJoint distribution function, 分布函数
) t7 o0 Y" p; XJoint probability, 联合概率7 m7 ~4 y5 Q' J' H [; x; g% Z5 x
Joint probability distribution, 联合概率分布- T2 p+ U% U; ~6 u6 e! j
K means method, 逐步聚类法
* F: Z4 b5 B4 k2 j, t3 `6 g% HKaplan-Meier, 评估事件的时间长度
. g/ _; M2 f& P0 M1 h4 T9 HKaplan-Merier chart, Kaplan-Merier图3 H3 n- z# d0 j; ]! ^6 {2 u+ r
Kendall's rank correlation, Kendall等级相关
' ^8 _! a$ b9 L/ t- EKinetic, 动力学: e7 O9 ?. |/ E" ~/ W1 ?
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
4 s1 e# s2 @; ~# T$ S2 FKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验/ j' C5 ]3 @# n* z& {" S* w) N
Kurtosis, 峰度4 M* F* L n/ G0 |* l
Lack of fit, 失拟# m! W# y6 i7 |3 X" c
Ladder of powers, 幂阶梯
3 F* z" @, a- i) ^( bLag, 滞后: B$ c. a; Y, m# V
Large sample, 大样本* G, g& m1 P2 q0 R( s
Large sample test, 大样本检验$ x# s* t2 g8 t8 C4 C1 A
Latin square, 拉丁方
& S2 G$ e4 x/ g4 O' yLatin square design, 拉丁方设计2 ?6 t. I1 ^) u8 _
Leakage, 泄漏" V: e8 [5 x" Z; o
Least favorable configuration, 最不利构形
# I/ S+ t6 U' F4 V5 ]8 TLeast favorable distribution, 最不利分布
) S# h Z/ u5 q# T0 CLeast significant difference, 最小显著差法' _; d: c; e, C$ e
Least square method, 最小二乘法8 b* p) }2 d, \! B. V0 J
Least-absolute-residuals estimates, 最小绝对残差估计0 Z! O5 m7 f O3 z
Least-absolute-residuals fit, 最小绝对残差拟合" I' K0 I7 y8 v
Least-absolute-residuals line, 最小绝对残差线
! t3 o2 D7 V# O6 K! Y" J WLegend, 图例: _! X8 j) Z! p) T. U a
L-estimator, L估计量
+ ~4 {5 ` G- j8 x$ hL-estimator of location, 位置L估计量
/ A) h- S: q0 u, }6 x3 w. KL-estimator of scale, 尺度L估计量" E$ {9 c( M+ Q3 {: Q& _
Level, 水平. q3 S6 s7 \4 V% ~4 k6 Q- U7 {
Life expectance, 预期期望寿命* I9 \/ G; M2 l! s
Life table, 寿命表
! n9 D8 T- a# t( p Z5 d" {Life table method, 生命表法
7 K+ H6 I1 r. `/ d* c3 k( gLight-tailed distribution, 轻尾分布/ ]' L5 e9 N" j: G3 s# C: {
Likelihood function, 似然函数: J, I) K" b8 b! ^' N! G3 `1 R
Likelihood ratio, 似然比+ x' M! u% G) b" K
line graph, 线图0 ?' j# o, Y' y" Q4 c% J; I
Linear correlation, 直线相关
2 l2 K8 z( r) M/ i. GLinear equation, 线性方程6 |- R* Q: b3 n1 d
Linear programming, 线性规划
9 W0 c5 y H0 s7 w$ z+ @Linear regression, 直线回归
5 o$ ^1 d3 t$ G: o6 Y g5 gLinear Regression, 线性回归
r, |! D) p+ M& t: yLinear trend, 线性趋势
8 x: r; W; J% h/ G% x' VLoading, 载荷 ; v3 F9 r7 E! s! B) T/ ?
Location and scale equivariance, 位置尺度同变性
: q- m; n6 `6 A$ h6 M' f% VLocation equivariance, 位置同变性4 }) H" U S; R) y) H0 d5 u8 s2 B
Location invariance, 位置不变性1 I) @1 o6 q+ j$ o3 o
Location scale family, 位置尺度族5 d8 [! x. R, t3 A$ ]
Log rank test, 时序检验
/ r" [" R3 T/ g& t0 b( oLogarithmic curve, 对数曲线
4 x1 |$ B2 ]1 E( I6 F$ LLogarithmic normal distribution, 对数正态分布9 l1 Z) x3 U# i8 [4 j1 i8 x% W
Logarithmic scale, 对数尺度3 H/ `, Y8 N% `% u# D
Logarithmic transformation, 对数变换
2 s9 @' L+ m! ~$ _/ @/ e6 ELogic check, 逻辑检查
$ x, c0 N }& i! P! ~5 ZLogistic distribution, 逻辑斯特分布( I# g7 m+ \5 n% z9 R* F& e( ?
Logit transformation, Logit转换! n7 L5 l" |4 e
LOGLINEAR, 多维列联表通用模型
7 P: p* g" {7 @0 ~! u0 ^1 S( cLognormal distribution, 对数正态分布
4 O1 n% r- Z b2 J, h8 o- [Lost function, 损失函数; ]3 U" o s; q: m( Q9 B1 @' v" G
Low correlation, 低度相关
- j" x4 F3 J0 i" L, A. M( N5 F6 ALower limit, 下限; k( Z- `. A: L8 d
Lowest-attained variance, 最小可达方差
) U( E, O; M( XLSD, 最小显著差法的简称" p# _3 M9 W# h( f# G
Lurking variable, 潜在变量
% S" \0 q/ R+ [% WMain effect, 主效应4 i" S% ~2 e: Y2 k: H U- ]
Major heading, 主辞标目/ q4 O3 w4 s7 _, k
Marginal density function, 边缘密度函数
1 F3 R. N4 U4 g2 I m6 bMarginal probability, 边缘概率2 Y, N+ l& k/ g8 H) i
Marginal probability distribution, 边缘概率分布; E. y- @- L/ j' o- N% I* p. `
Matched data, 配对资料/ h i" }& ], a1 p! m; _& ]
Matched distribution, 匹配过分布
5 t d4 R* J" k# S7 Q2 wMatching of distribution, 分布的匹配
- t* D; Q/ ]/ j3 B, \Matching of transformation, 变换的匹配# c+ |) C/ C1 B, U/ D- s* ?
Mathematical expectation, 数学期望, O! f" ^% o# Y4 l/ A
Mathematical model, 数学模型
2 Q6 ]0 g) H3 LMaximum L-estimator, 极大极小L 估计量
/ l0 [2 L! v8 ?Maximum likelihood method, 最大似然法: K B5 E, }/ Q! @$ W/ t \9 p
Mean, 均数
% d3 m: j+ `2 @7 I" Y5 @Mean squares between groups, 组间均方& @6 Y+ V) I7 Q6 d$ e
Mean squares within group, 组内均方1 t1 D: W. f f' p/ D6 T/ P u
Means (Compare means), 均值-均值比较' W. D3 n7 j( l
Median, 中位数
1 @& s6 b Y1 O( ~5 W( K# LMedian effective dose, 半数效量
+ T) {1 Q6 G2 N3 A8 G T1 YMedian lethal dose, 半数致死量. E, k6 k8 `+ O6 C
Median polish, 中位数平滑! b+ v9 q. c2 @ V6 Q" J
Median test, 中位数检验, m7 m e# A- [$ K3 R3 V$ t, o
Minimal sufficient statistic, 最小充分统计量% M% \( Z7 } j
Minimum distance estimation, 最小距离估计# K+ s* G8 T, D, H9 E
Minimum effective dose, 最小有效量9 c5 K6 a# T* |4 d
Minimum lethal dose, 最小致死量
5 r: w/ W. G. |- Q! y6 ?1 L, }Minimum variance estimator, 最小方差估计量
) i& ]' F5 @4 A1 XMINITAB, 统计软件包* z" H4 ^! H8 A# j% o3 Y
Minor heading, 宾词标目
, C) I. W. ]* y* W WMissing data, 缺失值& n X* T0 L! X, @5 q$ A
Model specification, 模型的确定! c4 }; ]& t! w9 u. A7 r) Q
Modeling Statistics , 模型统计7 d8 s! V1 x. X$ W2 ~7 _9 f
Models for outliers, 离群值模型9 [& _# S) [2 g" c3 X
Modifying the model, 模型的修正
# E. c, {6 \, w% q- }4 y; eModulus of continuity, 连续性模: y" [' u0 k! ?; `% Q+ D
Morbidity, 发病率 ; c4 U8 t1 `" P, H; m2 l
Most favorable configuration, 最有利构形! n/ _" W& l" v3 G
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
% f2 X& a3 s4 c2 h+ b: RMultinomial Logistic Regression , 多项逻辑斯蒂回归/ a4 T( u$ D2 m; ]3 z( @ D7 c
Multiple comparison, 多重比较' D5 A9 f% q# O& V! v2 @. w& [7 k2 D
Multiple correlation , 复相关0 g3 z$ A4 A! _1 P% ~
Multiple covariance, 多元协方差
. W. R/ l" i. a8 gMultiple linear regression, 多元线性回归
! u8 |: Q1 P) j% p' b ]8 FMultiple response , 多重选项( w7 d, x' _ g6 I
Multiple solutions, 多解
0 u% I) g2 W) F0 v3 IMultiplication theorem, 乘法定理, u8 x9 q8 }, }
Multiresponse, 多元响应
7 z6 l# G0 A S2 x2 P: g( Y( q1 m- \Multi-stage sampling, 多阶段抽样9 q/ j/ d N! ? m- E0 u
Multivariate T distribution, 多元T分布- Q* ]) r6 P; Z/ Z- Q3 K
Mutual exclusive, 互不相容3 p' s) O# j- U' q6 h6 `
Mutual independence, 互相独立' k+ Q, {; D# N
Natural boundary, 自然边界
2 i) V8 X5 v. ]/ |9 w4 GNatural dead, 自然死亡
9 J; l7 Y( M* A, a$ y# m; T$ oNatural zero, 自然零( S4 V7 k6 x: D* z
Negative correlation, 负相关, M+ E% J- ~ E8 x# u8 s
Negative linear correlation, 负线性相关% P1 ]7 s c9 E) m# Q# \* F
Negatively skewed, 负偏3 Z$ R# h. m" O) L2 N, f" o
Newman-Keuls method, q检验
! _4 p: W, j& T' n' c2 K+ P$ \NK method, q检验3 Y! F& G3 v+ {4 r% e2 t# i: B
No statistical significance, 无统计意义
, s5 x N. ?& [- r8 G+ x& jNominal variable, 名义变量
& k7 w7 K& h. R2 j- A) N. p2 RNonconstancy of variability, 变异的非定常性: s; ^5 z# {2 s X2 S5 k0 K
Nonlinear regression, 非线性相关4 [" H! f* R2 Z, H* O
Nonparametric statistics, 非参数统计
' e3 z r: [- a* eNonparametric test, 非参数检验: }9 }0 p( _# Y
Nonparametric tests, 非参数检验
# T: s" [- V' A/ W9 }Normal deviate, 正态离差" L% G( j) }6 |. u) F8 }
Normal distribution, 正态分布( {# T6 p/ `3 d& u
Normal equation, 正规方程组
/ r% C n- j. @3 h+ ZNormal ranges, 正常范围
5 g- H4 k* O8 ]% d* w# RNormal value, 正常值3 g" s. _1 F) U
Nuisance parameter, 多余参数/讨厌参数
8 R* m5 g+ R# ]) i3 w' C/ ENull hypothesis, 无效假设 * R" ?& {) k% X9 a3 s2 w
Numerical variable, 数值变量8 ]- ^6 V5 _( G
Objective function, 目标函数
. ]6 H" R* V4 ?6 xObservation unit, 观察单位
; [- E! }) a3 A& @Observed value, 观察值
% i- ^* H7 D* i9 I2 fOne sided test, 单侧检验2 N' m, U& z/ o$ w- D# J5 s
One-way analysis of variance, 单因素方差分析
]0 i, ?7 \' g+ N8 k8 w) COneway ANOVA , 单因素方差分析
( d3 m1 |+ }) f% Z+ c9 ]Open sequential trial, 开放型序贯设计
4 @( Y4 F# r1 `9 ?- E8 I# K% P9 T5 oOptrim, 优切尾% Y1 e2 o1 } v& F+ t4 t, J# N
Optrim efficiency, 优切尾效率% p0 }0 `% [6 L6 k8 Z
Order statistics, 顺序统计量
5 N! H( t- J6 ]( E" s, `8 WOrdered categories, 有序分类) ]' v) z$ d) A: y' b& M
Ordinal logistic regression , 序数逻辑斯蒂回归# ~, b' a7 S. f8 J# T) n
Ordinal variable, 有序变量, ~/ M+ S3 G! c- A! V
Orthogonal basis, 正交基
6 [0 d- D2 X! [2 E; E; n9 hOrthogonal design, 正交试验设计" M3 o# f/ I2 ~, h7 k
Orthogonality conditions, 正交条件
8 \% C$ U) c3 }( u2 [ORTHOPLAN, 正交设计 2 Q+ {2 K9 n) y4 _3 w
Outlier cutoffs, 离群值截断点- H# ]7 A1 P* q
Outliers, 极端值" m4 M7 P+ s' X, V, e# h
OVERALS , 多组变量的非线性正规相关 ' n5 i- n; t; {
Overshoot, 迭代过度
8 X4 q4 u& M! r7 ~) M: N4 X6 [Paired design, 配对设计
. H9 v4 i' ]$ @4 {* Y. ]# QPaired sample, 配对样本0 Z4 y2 g Q7 V/ l1 F7 S7 b8 V
Pairwise slopes, 成对斜率9 u( x& K; F) I
Parabola, 抛物线
* H5 A; s8 r: B0 v9 PParallel tests, 平行试验( O- d1 e1 [" X9 W
Parameter, 参数3 y0 x' h# a& h" S
Parametric statistics, 参数统计4 a" ~+ Q- [- f# w( J
Parametric test, 参数检验
% v# y7 |, y+ W0 E! QPartial correlation, 偏相关3 ^. W; K2 |) h _/ U+ ~2 q+ E
Partial regression, 偏回归
# d( m1 W3 a6 K6 O3 bPartial sorting, 偏排序
: ?/ Q# v4 m/ Q7 b1 O" ZPartials residuals, 偏残差
7 g/ u! b) a! H8 d; t2 yPattern, 模式
1 b/ I5 \/ ^3 A. Y% N. q& oPearson curves, 皮尔逊曲线& H: U) s( S- [. W5 ]6 b
Peeling, 退层
! c5 G6 `) q2 I' a$ BPercent bar graph, 百分条形图
( E" ]% w: u" ?5 g7 v. mPercentage, 百分比8 w9 J1 ^# R3 R% Y2 w; R
Percentile, 百分位数
: C$ S: V: l, P* q$ i8 j& DPercentile curves, 百分位曲线
) o6 ~% v7 I! k" u. k, }Periodicity, 周期性
# s) r( l7 }; I2 e' Y3 @ fPermutation, 排列, x9 q8 n) v; J
P-estimator, P估计量3 `# P3 _' k& ?
Pie graph, 饼图
6 ^4 V1 a. C& P+ ^( Z6 L A, GPitman estimator, 皮特曼估计量5 q! I! E I! Y2 ]& B9 l2 D
Pivot, 枢轴量0 o; v( @$ ?" w4 I! ^
Planar, 平坦
2 W* X8 f) N# O% j) F v" |* Q) wPlanar assumption, 平面的假设! D1 x/ R! i2 D8 q, w- C" o9 |
PLANCARDS, 生成试验的计划卡' E# L; m" }# ^: T
Point estimation, 点估计2 q- x3 m7 W; ^& y' V: g) M$ ]
Poisson distribution, 泊松分布
3 t8 |" Y, Q2 P( OPolishing, 平滑 d( s4 n" L) Q6 E! e
Polled standard deviation, 合并标准差
: U) l& [" R" ^ qPolled variance, 合并方差
' ?- S P; E) q* N3 ePolygon, 多边图
% h+ U4 J5 V) u8 }; q$ _% iPolynomial, 多项式, }1 M! ~ a& Z* |5 q5 r# i* l
Polynomial curve, 多项式曲线
1 N1 B) O8 @0 c- ZPopulation, 总体1 V0 D$ q; G! }8 ` N3 g, q/ ~: U
Population attributable risk, 人群归因危险度; L6 ?6 {% w$ J G# Q
Positive correlation, 正相关
* L" c) x, P O" B5 MPositively skewed, 正偏
9 {6 Q: ~' G/ V F- pPosterior distribution, 后验分布
" f1 e9 F9 K: N7 JPower of a test, 检验效能! a& O5 C0 ] {5 s" p
Precision, 精密度
: l6 A$ q; Y# _* ?2 i* APredicted value, 预测值7 L( j; H4 X3 i* i) T$ }
Preliminary analysis, 预备性分析& F/ n: |+ \( r' G+ Y
Principal component analysis, 主成分分析
' v+ X) @/ w: x; ?- d8 VPrior distribution, 先验分布2 @- m+ I2 h4 w" }8 a
Prior probability, 先验概率8 x; F- L7 \: p2 U7 R3 J% U3 A2 v
Probabilistic model, 概率模型4 P9 y; q8 w/ j) a; k
probability, 概率6 p) [( O. w: Z4 B$ b p* @
Probability density, 概率密度
7 i4 W+ W+ P% `Product moment, 乘积矩/协方差0 k( o# F' ?4 y+ o: H* n$ h' w, `- x
Profile trace, 截面迹图9 M: N {) v4 l: t! ^
Proportion, 比/构成比
" d! ]& I' Z6 D) W; i4 l+ _ o( }Proportion allocation in stratified random sampling, 按比例分层随机抽样: ?% g+ E+ y' d1 A& {( d; O8 @! N
Proportionate, 成比例
7 R, C! }% Y" K9 S7 m! r: dProportionate sub-class numbers, 成比例次级组含量
2 [) X: ^9 C0 c0 b& Y, dProspective study, 前瞻性调查9 g' g" A; v0 b8 } a
Proximities, 亲近性 , L4 x2 f5 j+ _: _: q" b* i/ s
Pseudo F test, 近似F检验
+ i* `7 t6 _ J2 O. @Pseudo model, 近似模型
" Q( V4 @$ {% F3 tPseudosigma, 伪标准差
]* p) t9 e4 A9 I$ [1 IPurposive sampling, 有目的抽样
" e0 g D3 k6 L+ G1 h( [$ yQR decomposition, QR分解
% Z& b' Z1 a+ ~$ }3 O0 x5 f2 p. KQuadratic approximation, 二次近似
9 q" E h7 s( M/ BQualitative classification, 属性分类
3 W/ |; H, y( n9 [ d+ NQualitative method, 定性方法
; q" `! N4 N7 B8 k3 j" A6 u- SQuantile-quantile plot, 分位数-分位数图/Q-Q图
, V! M, C5 y1 T5 O, H3 o$ W) v3 PQuantitative analysis, 定量分析
, z8 F$ n$ a z" g/ }% y) ]Quartile, 四分位数
5 `' H- S/ p$ s) G) ~Quick Cluster, 快速聚类
" f( ~" q: J( Y% s% MRadix sort, 基数排序
! ]1 [9 J. S0 t9 G6 A. d |! k9 x& {Random allocation, 随机化分组( E7 ~. g+ Q9 i
Random blocks design, 随机区组设计
" E: h: ?: [8 s6 ?, FRandom event, 随机事件
* V- v1 T/ v1 X1 X* n; _Randomization, 随机化6 F9 Q/ @) s! ?0 M$ _3 V0 h
Range, 极差/全距: ?6 V4 r+ l: ]
Rank correlation, 等级相关, Y6 e& b- r j! v; Z3 f+ G
Rank sum test, 秩和检验( v& E2 `9 Y0 C7 d. K, ~& y
Rank test, 秩检验( x9 C' V; a T6 f8 e3 U4 F
Ranked data, 等级资料3 M2 C$ s; |4 V
Rate, 比率/ M; A4 i) t1 w
Ratio, 比例
! Y' U9 ?& V# ` s& N+ S8 S8 dRaw data, 原始资料. n# v% z6 _, ]. V6 E1 u
Raw residual, 原始残差
% ~$ H1 B# F' zRayleigh's test, 雷氏检验' j# P0 a6 L) z
Rayleigh's Z, 雷氏Z值 8 V* X& `2 d1 B" S% ~7 z6 T
Reciprocal, 倒数3 D) G, x# G q3 H% I+ _
Reciprocal transformation, 倒数变换
e" ]# S; N8 |8 }3 YRecording, 记录3 n) I8 ?0 x" h5 G4 A6 x( c
Redescending estimators, 回降估计量" f' Q6 K1 K' u2 d) K2 w# W, ]
Reducing dimensions, 降维
0 y; S* t7 Y: |Re-expression, 重新表达" @8 |' E, D& P: N! i5 B
Reference set, 标准组8 c& V* r8 p$ T5 L* v
Region of acceptance, 接受域) [& @3 Z5 N3 M+ {! C' M0 c
Regression coefficient, 回归系数
4 [9 |9 v# |" V% x/ GRegression sum of square, 回归平方和8 o! b" Q# \) \. j% `: f
Rejection point, 拒绝点5 b+ i9 Z" g' M6 a' v
Relative dispersion, 相对离散度 {# J) `# o% U8 N- `
Relative number, 相对数
, B- F' N0 ~' g' ~5 |Reliability, 可靠性# n$ y A: y6 S* c; @8 H8 S
Reparametrization, 重新设置参数) N* k4 |/ ^/ }8 [1 @: }5 w1 I
Replication, 重复
: C, h) s& b4 ~3 dReport Summaries, 报告摘要
# ~' b$ l* V3 W* v. H7 o& SResidual sum of square, 剩余平方和+ E w/ c* v" |3 L, D8 c" g$ w$ O( T
Resistance, 耐抗性/ M! N% u# u' u5 ?2 s
Resistant line, 耐抗线% K# r. h2 f$ Q
Resistant technique, 耐抗技术 J* K4 y7 k- N% q
R-estimator of location, 位置R估计量
9 c2 B; ]# X* a- b8 H" z3 }R-estimator of scale, 尺度R估计量
' q; |6 O7 H2 }9 _; g9 @7 CRetrospective study, 回顾性调查. _2 F( W. \2 r* m3 ~
Ridge trace, 岭迹
0 n- ?6 V4 p# w0 r- @# RRidit analysis, Ridit分析
0 D* M% t o8 U( J# J3 `6 m) nRotation, 旋转
+ d; E. m( l) a5 {: Y& k. P* QRounding, 舍入% q! l* I6 f) ~
Row, 行
6 L7 N" ?2 ?2 d2 k$ P8 ^* YRow effects, 行效应
1 Y8 D. H' q! X% ^& F" n2 y0 XRow factor, 行因素
$ G$ K4 M( e7 J1 {3 [- ^% ^' q/ [RXC table, RXC表6 Y6 E! ?2 L: V6 s$ D S
Sample, 样本* X9 q1 m, w7 o8 n& C/ j6 F' d% Q! w8 n9 t
Sample regression coefficient, 样本回归系数; p0 S4 h: ^* j4 \, C- x
Sample size, 样本量
3 X- J( d3 ]. t; i1 pSample standard deviation, 样本标准差" k8 G- d9 [6 y K
Sampling error, 抽样误差
. X* p% T! J% T0 O ~5 ESAS(Statistical analysis system ), SAS统计软件包
, K" N$ C: O' x! Q( K HScale, 尺度/量表1 E! |; I+ h* ]* k" @' n
Scatter diagram, 散点图% x8 B9 R/ d0 A; A" W- a
Schematic plot, 示意图/简图
4 }# `" `3 h: R% \: uScore test, 计分检验# r0 m. N9 P7 `; o
Screening, 筛检
; v: ~( j* F$ z9 N' w+ \SEASON, 季节分析
$ G0 m5 H- b& n8 j- t; M- b) `Second derivative, 二阶导数9 U2 Q' R" Y* _* X
Second principal component, 第二主成分( l6 G+ V' u7 r6 Y; Y: `
SEM (Structural equation modeling), 结构化方程模型 $ F [( q0 Z# f5 }2 L
Semi-logarithmic graph, 半对数图4 m4 i9 l6 Y+ b. P! \5 L0 x
Semi-logarithmic paper, 半对数格纸% t* i* s5 t: v, z
Sensitivity curve, 敏感度曲线
5 g0 K2 _8 }6 u3 L/ [) J; JSequential analysis, 贯序分析
, C7 A! h( q% B: l) P2 lSequential data set, 顺序数据集
6 |! Z% c- s9 x8 I X% BSequential design, 贯序设计
. B% t |) N! {/ T" ]2 |3 f7 QSequential method, 贯序法
! t" Y- L& V- H6 C( o$ r/ k" j/ F: CSequential test, 贯序检验法
% ^0 e# L, s4 T* r) c6 _Serial tests, 系列试验
: I: b. i0 k' Z1 \/ N; sShort-cut method, 简捷法 e! u# R/ h" ]2 f
Sigmoid curve, S形曲线- ?+ o9 o) b; O0 d9 W
Sign function, 正负号函数, Z* O1 h9 U) A! f0 O \6 Q
Sign test, 符号检验
6 P- t! P/ O4 t- p% L# s. M( HSigned rank, 符号秩
: l P! t. w7 T% N9 `Significance test, 显著性检验
6 z* S- ]- n m# N3 f# u4 `Significant figure, 有效数字) r( p. D [. B
Simple cluster sampling, 简单整群抽样
9 q& _' ?4 R5 p1 K' f2 gSimple correlation, 简单相关8 b# y/ z7 H N3 N* H3 b
Simple random sampling, 简单随机抽样
5 ] z4 G$ ?) @( g( o7 kSimple regression, 简单回归
$ S& Y* D5 j0 G6 Wsimple table, 简单表
5 i3 B6 p$ L% D9 X/ H( q' R. cSine estimator, 正弦估计量: U$ N/ i9 k2 ]6 m! ?! [) W! T
Single-valued estimate, 单值估计
, T$ A' c, ~* h; I3 Y/ F1 \Singular matrix, 奇异矩阵
! N# w/ k; P* ], g* {- KSkewed distribution, 偏斜分布
% r3 I6 D6 o$ `- v4 WSkewness, 偏度0 w- S# z# p0 `# \, y$ o$ `, ]
Slash distribution, 斜线分布
' ]7 I: J1 I, @8 w# lSlope, 斜率6 q9 K: U3 K& G9 L( U. L& v
Smirnov test, 斯米尔诺夫检验
& G% ^: C7 V Z( S+ V4 M6 sSource of variation, 变异来源3 `4 q1 i2 m- N
Spearman rank correlation, 斯皮尔曼等级相关
C/ ], l' Y# m3 r5 H& OSpecific factor, 特殊因子
' n# W! z1 U! G/ ?8 S1 I! dSpecific factor variance, 特殊因子方差
) W2 U) ]8 @( z) v7 g! c7 y* `) `Spectra , 频谱
( ~! l& z6 u/ i) W: wSpherical distribution, 球型正态分布
, e8 f) j1 X5 J! s1 k6 X/ w- a0 r" WSpread, 展布- X. m( u+ c4 E! w
SPSS(Statistical package for the social science), SPSS统计软件包8 p5 B& _- q; n& z$ R3 t- c8 @
Spurious correlation, 假性相关
( q: n' s! x. a! h" lSquare root transformation, 平方根变换
! X! i8 w+ z* W x- eStabilizing variance, 稳定方差! {- j1 {+ w. x3 F: I! ~# L
Standard deviation, 标准差
* w$ I+ V8 _, N9 ZStandard error, 标准误9 e' X* B j% f
Standard error of difference, 差别的标准误
, Q" k( u* \/ G# B. H' PStandard error of estimate, 标准估计误差* @& S: \- J j4 z. b' c! A. U' ?0 ^! p, Z
Standard error of rate, 率的标准误
& {' g/ D# M c! a# }# NStandard normal distribution, 标准正态分布
8 {+ [1 d3 f4 l2 F' ]+ U* D8 L9 o5 lStandardization, 标准化4 n! W i- ?0 L" o
Starting value, 起始值( Q/ J! V5 E, t: g7 m/ q
Statistic, 统计量, G8 _; [0 z6 D# b2 K. K
Statistical control, 统计控制
# X6 ?) z* u% q0 _8 E. fStatistical graph, 统计图
7 V( G5 {5 P; ?8 q( ^Statistical inference, 统计推断* e" D7 R/ T6 o0 H! X
Statistical table, 统计表7 {* u/ t4 l' v+ w5 G4 b
Steepest descent, 最速下降法
5 `5 k5 }/ R! V1 t& s dStem and leaf display, 茎叶图0 d. I5 \; M6 r
Step factor, 步长因子0 M2 j8 v }; m9 ~# R( n f: N
Stepwise regression, 逐步回归
% Q6 H! a9 m* ~" F7 aStorage, 存
9 M& ~$ Z* F. I% Z A/ c9 z% D9 @Strata, 层（复数）7 g. s* b7 ^( E1 q
Stratified sampling, 分层抽样
) \8 T1 |+ h: x+ K: i0 YStratified sampling, 分层抽样; m6 }1 {# s( S
Strength, 强度
: h" P( A/ W; _% H& O, v& pStringency, 严密性$ a, W& P: c6 w% y4 v$ I2 o, ?
Structural relationship, 结构关系
7 B' U% K& ~ ~/ A$ n5 y; f4 |* IStudentized residual, 学生化残差/t化残差" W5 l1 d6 T8 b! B0 c7 M
Sub-class numbers, 次级组含量
2 K" O& I+ V" Q c9 j2 mSubdividing, 分割
6 k7 w1 r6 g# ?+ y S# OSufficient statistic, 充分统计量
" {# j% G ~" D+ [: m% ^Sum of products, 积和
4 r0 G( I- v, f% ~! bSum of squares, 离差平方和
" f" Q) ]# O& @) g6 v) S* }" V9 GSum of squares about regression, 回归平方和6 R0 ]2 H* J; \8 d# b
Sum of squares between groups, 组间平方和& Q, @# m! Y5 Z: w L
Sum of squares of partial regression, 偏回归平方和
i4 Y7 y! o. }& [' ^Sure event, 必然事件2 P8 d3 J3 ^( @/ B, U
Survey, 调查2 t. |2 F4 i$ f( @0 M3 N3 o
Survival, 生存分析' k% D2 f' ~" g1 Y7 ]8 u. A
Survival rate, 生存率
& ~, \9 }, J! a2 ISuspended root gram, 悬吊根图" h: l4 t6 \7 U$ G4 v# f4 p
Symmetry, 对称
+ {( r* H( H: |2 B& k; M6 fSystematic error, 系统误差
5 z7 w+ C' R6 l3 mSystematic sampling, 系统抽样
4 c0 M' N7 X' j) F9 GTags, 标签/ A2 L1 [8 e! O# R0 X, m! x1 @/ m' e" ~
Tail area, 尾部面积. G% g+ t$ @" U* _) O- W
Tail length, 尾长
' k) A$ E2 p, x: t- @# T& WTail weight, 尾重
3 b3 j# Z0 x& P3 q- ]Tangent line, 切线
{) R3 `0 `* m# F' c7 e o6 HTarget distribution, 目标分布
$ h2 V: Z% T9 lTaylor series, 泰勒级数7 c z/ _0 W$ U
Tendency of dispersion, 离散趋势
# j: } d# M8 E2 g# [1 kTesting of hypotheses, 假设检验1 x& L6 b( Q. J; Q
Theoretical frequency, 理论频数
2 f5 b' z5 O5 {7 `Time series, 时间序列
, v! k, M5 K3 p* ITolerance interval, 容忍区间2 m( W$ G, E; z0 Q6 g4 ?
Tolerance lower limit, 容忍下限
. M" c& W% s' V! V- HTolerance upper limit, 容忍上限- d+ D( Q. `2 `/ J1 l
Torsion, 扰率
% n' J9 X( T( }1 S |8 rTotal sum of square, 总平方和% V G2 M& Y9 N
Total variation, 总变异' O+ ~+ [- g# I* p# P: `6 C! r
Transformation, 转换
) L9 r0 U' j4 p: T( V8 h/ Q9 TTreatment, 处理
! g0 h4 @$ ?2 s, k9 H# B/ Z( q7 pTrend, 趋势
2 J* I' T; q4 ^/ T6 ?Trend of percentage, 百分比趋势- |! r- }6 \( x8 F9 N f, G8 ?
Trial, 试验
2 X1 ]$ T8 ?) R$ E% GTrial and error method, 试错法
6 o' Z' ?: v7 ^3 o9 Y( l/ zTuning constant, 细调常数
# K# U' o& Q7 |9 GTwo sided test, 双向检验! d& Y; s% ?' b. c5 L% i+ t& [
Two-stage least squares, 二阶最小平方
6 X. Y% l& a6 a8 yTwo-stage sampling, 二阶段抽样; }+ e) l* q: U6 P
Two-tailed test, 双侧检验
" m( q; k/ t0 \( }$ K$ PTwo-way analysis of variance, 双因素方差分析2 f' v# I6 p2 Q( z3 v
Two-way table, 双向表
4 h3 P3 p; J4 p" Z# IType I error, 一类错误/α错误
9 f/ U3 I6 D3 k8 Z2 B2 F3 ZType II error, 二类错误/β错误
A- x- {* g8 k$ L# {0 T+ z# N+ I& eUMVU, 方差一致最小无偏估计简称4 k( s( _6 j/ j( C2 d2 g; {* j
Unbiased estimate, 无偏估计
8 H1 f; s9 R% w- BUnconstrained nonlinear regression , 无约束非线性回归! ~0 U" z) ~9 b5 W' D
Unequal subclass number, 不等次级组含量
6 }$ c A2 p3 t9 \7 U$ @, ?: {Ungrouped data, 不分组资料- S. P3 D4 d& ]+ L7 T5 ?. X
Uniform coordinate, 均匀坐标/ e5 j2 i5 A& D& T# }
Uniform distribution, 均匀分布
# \2 Y6 E* Q r" L0 O/ y: `Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
q" `( c: E) _( p. z( d' r8 vUnit, 单元1 ^( f! I; i) H- E2 D7 }
Unordered categories, 无序分类
6 U8 V3 C& s0 l) M+ pUpper limit, 上限# T0 F% v# K" i! S, _' J+ ~
Upward rank, 升秩
( N( k+ a. m% qVague concept, 模糊概念
8 z, e9 z5 h# i, w2 PValidity, 有效性
0 c/ x: e7 ^( s5 \VARCOMP (Variance component estimation), 方差元素估计
* [7 l# L Q7 R0 c6 d+ xVariability, 变异性( D2 u& K+ U5 x; b3 P% e
Variable, 变量4 ?3 ?8 Y; \2 V/ g! V3 n% n
Variance, 方差
) ?' [- u; B/ M. |$ J8 oVariation, 变异
) Z4 u0 e" h2 z+ HVarimax orthogonal rotation, 方差最大正交旋转
, B9 q) }3 {0 m* XVolume of distribution, 容积1 X' c5 Q# n- f" t
W test, W检验
& V! m6 s' ~3 R# P/ {Weibull distribution, 威布尔分布, } \3 T/ R9 i0 u, [& l) o
Weight, 权数
0 t, T: g6 e. ~Weighted Chi-square test, 加权卡方检验/Cochran检验) m4 ?: ^+ l3 A. z/ Y
Weighted linear regression method, 加权直线回归1 J. _5 f- x) R
Weighted mean, 加权平均数, C6 Z1 O: S8 N; R4 X
Weighted mean square, 加权平均方差
- v0 s% ?7 G) B0 T. [ \Weighted sum of square, 加权平方和
" ?6 `) F5 p$ nWeighting coefficient, 权重系数- K0 t, p* M; A
Weighting method, 加权法 : X, c% k7 @) X! \. W1 @7 k3 z
W-estimation, W估计量& K! E3 O: x- ?+ x
W-estimation of location, 位置W估计量2 L% k {2 L. K) p }
Width, 宽度
! k1 j' k! r! O0 ~9 }8 OWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
/ o* s8 Q/ K( R# d6 x: m6 \( g) j/ bWild point, 野点/狂点
9 P7 a, |! O6 s0 M2 i" Z8 WWild value, 野值/狂值- p% r, e- |4 U
Winsorized mean, 缩尾均值+ K, v: Z) [* \! t+ {
Withdraw, 失访 / G, b D! z3 \. r
Youden's index, 尤登指数
1 |" N" d1 p; Q- Z: GZ test, Z检验2 e& c: e1 }! P9 B9 s
Zero correlation, 零相关
" Y& C5 w. F0 j" p2 I& u K aZ-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看，没有账号？注册会员
x
|
|李越老师直播间|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
