|
|
Absolute deviation, 绝对离差( m1 O4 g% h3 }) y% b1 `5 p
Absolute number, 绝对数
3 U. d) n5 t' [; k/ o' |$ H5 _, NAbsolute residuals, 绝对残差
( o4 t" W/ F- G: d$ G1 {Acceleration array, 加速度立体阵3 G% Y5 Y5 r p& w' m/ z- I
Acceleration in an arbitrary direction, 任意方向上的加速度4 D. }3 {" G B/ S3 S# W( P" i$ n W
Acceleration normal, 法向加速度
4 s( Y/ M8 U/ v$ p2 y, pAcceleration space dimension, 加速度空间的维数
6 B9 }- C1 B% F1 Y. TAcceleration tangential, 切向加速度8 c) I% [% f( Q+ `& h
Acceleration vector, 加速度向量
/ A2 y- J. x o) N/ [" ~Acceptable hypothesis, 可接受假设
. h$ z2 T& F# P- j% [4 g* A7 AAccumulation, 累积
7 ~( S7 |% u9 d" k& k. R1 f9 ?Accuracy, 准确度/ V; C$ j4 k4 i* V* J3 ^9 [4 O# d
Actual frequency, 实际频数
- c. |3 o7 |; T& c% d* ^, J. Q6 A: BAdaptive estimator, 自适应估计量/ l' K% o0 y. t0 N! o- a$ V
Addition, 相加
# S& j2 o/ b! A+ d9 v l! I5 F, k* pAddition theorem, 加法定理/ p2 Q( {( X0 f( B/ _" O0 Q# j
Additivity, 可加性
T8 E# E: h' G$ YAdjusted rate, 调整率5 U9 ^* M2 o( J8 l1 _' q/ y
Adjusted value, 校正值
" a7 o5 H" W- N% e4 u6 y) rAdmissible error, 容许误差
- k4 s( ^; [5 m+ ^* b+ `Aggregation, 聚集性% |" K7 [3 _% a
Alternative hypothesis, 备择假设
! D6 k( C% n2 a7 ]Among groups, 组间
- u$ n9 _: N) Z& t& G0 y9 A8 T, xAmounts, 总量
; C% r( q# M+ L* k. m GAnalysis of correlation, 相关分析
6 ?; ^1 V( i5 T1 WAnalysis of covariance, 协方差分析; A# L7 C1 ?( U1 D: l7 l9 E
Analysis of regression, 回归分析
- p- M" U0 |' r% ?1 Y6 J( NAnalysis of time series, 时间序列分析# I- |% ]$ s( c% t
Analysis of variance, 方差分析
/ Z7 I: s0 e! a& T6 C% XAngular transformation, 角转换& Y% d& E! G" D& e# O3 w: C; u$ v
ANOVA (analysis of variance), 方差分析. X, O. Y- `; ^, |
ANOVA Models, 方差分析模型+ e; i! B8 e* H2 n; {) G
Arcing, 弧/弧旋
5 h6 c! R! c' V) I# S' Z. MArcsine transformation, 反正弦变换' ? n/ ]& J& B8 C9 _
Area under the curve, 曲线面积4 N1 P0 n3 Z) i) U0 k
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# P/ i9 p' M& mARIMA, 季节和非季节性单变量模型的极大似然估计 ' B# L! I! [, T. k( @
Arithmetic grid paper, 算术格纸. z: J/ i; n1 C# W$ S! z! ~
Arithmetic mean, 算术平均数+ i% o$ F1 U7 Q' a9 V
Arrhenius relation, 艾恩尼斯关系
& w& C+ B/ @5 E1 i! v& a( ~8 K5 G9 zAssessing fit, 拟合的评估2 d. J1 e# Z+ ]4 J+ V, w
Associative laws, 结合律
( O! k2 S% W, J+ g+ h- NAsymmetric distribution, 非对称分布
% P: }2 W O$ h2 ?! ], zAsymptotic bias, 渐近偏倚1 `9 Q7 X3 ^! |* V2 C9 u
Asymptotic efficiency, 渐近效率
: I( J3 A& e9 s3 a( |9 l) z8 Y7 dAsymptotic variance, 渐近方差! q7 i" w* s! U- q6 `* A# b
Attributable risk, 归因危险度
; q/ {4 ^+ I3 G' e# Q# c2 LAttribute data, 属性资料
3 Q, q. d/ |- m8 \- G+ w0 cAttribution, 属性
9 g1 c G" h5 B7 _. }Autocorrelation, 自相关1 h" [* a( x# l4 s. Q$ q
Autocorrelation of residuals, 残差的自相关% J- I0 w1 M" l j; P7 |' {
Average, 平均数. D* A. N% L: X; ~ [
Average confidence interval length, 平均置信区间长度# K1 Y$ h( i& C3 u$ U+ V7 ^
Average growth rate, 平均增长率
; i* L! L$ a8 P- n% c8 W, s- L) ?4 kBar chart, 条形图8 H0 _9 o. `0 H# h* t
Bar graph, 条形图
6 m% p) z' I3 x" vBase period, 基期
7 t) w1 v# v7 Y+ b. o* v) bBayes' theorem , Bayes定理
, x2 X( g0 W9 K$ V" ^! m3 ]Bell-shaped curve, 钟形曲线$ S9 m5 q5 ]: b4 E# q6 Z0 S, A, u( E
Bernoulli distribution, 伯努力分布) V& J, W5 D K, q. z
Best-trim estimator, 最好切尾估计量
! i0 o& Y# O. Z) k- i! z3 eBias, 偏性
- W# ~% a3 q- B2 q4 t- @Binary logistic regression, 二元逻辑斯蒂回归/ N/ N9 g* z" o% [1 R" t# x! w
Binomial distribution, 二项分布- h3 k* S- S* j) Y( q
Bisquare, 双平方0 g# {1 |' L# Y" k
Bivariate Correlate, 二变量相关
+ s5 ~$ ]2 Z/ ~Bivariate normal distribution, 双变量正态分布+ @' v- h- G# j
Bivariate normal population, 双变量正态总体5 u m* d4 _5 e: {3 @
Biweight interval, 双权区间
4 ?9 }, ~. ^" LBiweight M-estimator, 双权M估计量
2 P2 B K6 Q8 _8 P3 z! }& y4 ^Block, 区组/配伍组
2 B! E4 y! a( y; P& pBMDP(Biomedical computer programs), BMDP统计软件包3 e& {% Q. N6 A4 `* `, o
Boxplots, 箱线图/箱尾图& G+ o; a3 ^! K* |4 E
Breakdown bound, 崩溃界/崩溃点
! @! b, u- j8 i& F- I, [Canonical correlation, 典型相关! ]2 ]: X, X6 z4 U# y3 S
Caption, 纵标目
/ ^, J# M) W. o( j" o+ XCase-control study, 病例对照研究
; i6 S. Q, A9 [Categorical variable, 分类变量
! C% t8 V" {; GCatenary, 悬链线
$ @; Y" ^ q/ s8 d' n5 K+ ~ ]Cauchy distribution, 柯西分布3 |2 {5 P4 Q) `7 V* a
Cause-and-effect relationship, 因果关系9 M3 ]. l; J4 g
Cell, 单元
7 t7 H/ A- K: c( d+ pCensoring, 终检( i4 I* L E/ w# O# l% U
Center of symmetry, 对称中心" ]! T# i! s* E( |- K
Centering and scaling, 中心化和定标
% z$ K: f" G6 |( P# |Central tendency, 集中趋势
( W& J( G y7 |; k* I8 PCentral value, 中心值
1 P/ F2 V M: E4 b- XCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测: B/ R/ c" i& J {" F# B4 Y
Chance, 机遇
3 C6 l: Z* O4 A. d4 |Chance error, 随机误差
) {' c. L# f* H- r; a+ w4 sChance variable, 随机变量
4 @1 e9 O. ^* W9 W$ |: Y0 l+ O! `% G' KCharacteristic equation, 特征方程
6 M# m8 k B1 x$ PCharacteristic root, 特征根6 e# _$ O0 A2 x" }0 I+ |( S% E& J, }) U
Characteristic vector, 特征向量8 P( c) W; @" H% x9 k- I a
Chebshev criterion of fit, 拟合的切比雪夫准则$ D3 L. s' ~, `1 ?
Chernoff faces, 切尔诺夫脸谱图
$ Q- o5 _( q- y4 `4 S* C/ HChi-square test, 卡方检验/χ2检验
4 @1 { f/ v2 o, n W1 i/ ZCholeskey decomposition, 乔洛斯基分解# x+ C6 q1 U% |* ]; L4 z
Circle chart, 圆图 # ^8 Z5 k2 F$ F* X0 N8 S: I, E. T
Class interval, 组距
$ u# J p9 i& I% w* \" F. V* K2 FClass mid-value, 组中值$ U' ~ c4 l( \7 G, b( Q5 ?
Class upper limit, 组上限
3 K0 ^6 C* m2 a; BClassified variable, 分类变量/ j$ T. `& B" t! h$ }4 _
Cluster analysis, 聚类分析
) N# k! N2 \$ U4 W) U: U$ wCluster sampling, 整群抽样
1 u6 M2 i% t4 ~- N/ ^# h0 lCode, 代码
8 H3 V, Y2 d8 Y/ U, X$ o i. D& mCoded data, 编码数据9 a9 d5 E0 v2 c* J- p; m: T
Coding, 编码8 O1 V; i8 \ c+ p6 k6 ]
Coefficient of contingency, 列联系数
) u' a9 S, G6 W! L2 ^Coefficient of determination, 决定系数% R( y1 U$ C X7 y& z+ e
Coefficient of multiple correlation, 多重相关系数
8 @# Y7 G% B( XCoefficient of partial correlation, 偏相关系数
" i1 p d6 a8 o5 ACoefficient of production-moment correlation, 积差相关系数
& @0 ^0 f7 x' S. VCoefficient of rank correlation, 等级相关系数" o9 s( Y9 R0 ]) C8 p
Coefficient of regression, 回归系数
% x. [; F. y" _9 g* U: E6 G `Coefficient of skewness, 偏度系数* W. A1 u o/ R ?* l a# a% a3 i
Coefficient of variation, 变异系数
. k( T: w$ b' O: D0 G2 PCohort study, 队列研究
. B1 T% M$ Q- k+ p9 l/ b/ lColumn, 列2 G' S, }& h5 E5 P2 V, f
Column effect, 列效应
$ e+ q- m8 l1 |/ [/ F5 G/ U. NColumn factor, 列因素; C4 j4 q4 E3 N6 w5 {
Combination pool, 合并5 {8 ?2 Z6 _2 Q% u
Combinative table, 组合表
- W e* A, |# BCommon factor, 共性因子4 g) M8 ~4 C A2 a( S- O
Common regression coefficient, 公共回归系数$ U3 [' ~+ H7 _" N. r$ W# F
Common value, 共同值6 \5 ?" S! Q% L" R. }
Common variance, 公共方差
# ~- E5 X# Z8 ]Common variation, 公共变异" n4 d0 J. w. I, z, [9 M; A2 n
Communality variance, 共性方差
9 r3 z% m8 M! l( H- SComparability, 可比性2 a4 G& X0 ~5 R8 g) C N" _' I
Comparison of bathes, 批比较
) Y+ Z4 s% F. v J- KComparison value, 比较值* p# O! T1 T3 W& x1 b: _
Compartment model, 分部模型
# x1 F" B3 i4 L) H" h- WCompassion, 伸缩
" U& c5 j4 _. c9 tComplement of an event, 补事件) N& W, f+ f( h5 p8 s! B
Complete association, 完全正相关
8 B9 W4 e8 k" s! |6 xComplete dissociation, 完全不相关
3 K" F% I& B+ F. {$ ~* E; ^/ o9 HComplete statistics, 完备统计量. ?+ ~: u# `! x4 `% `* p5 l4 C6 ]9 W
Completely randomized design, 完全随机化设计
9 ~- o1 u- |0 T9 ~Composite event, 联合事件
. f0 s, f0 j" g' W4 |Composite events, 复合事件2 ]( P, F8 Q. q
Concavity, 凹性6 }8 p7 Q$ f+ v6 |( n; z
Conditional expectation, 条件期望
' @7 ?: [6 X3 U3 s* DConditional likelihood, 条件似然
" r' r3 F; E# M( a# v+ M5 m( lConditional probability, 条件概率
1 s2 h" n3 M2 p! S. S% R! KConditionally linear, 依条件线性- Y6 i5 \( Q; Y5 _9 s
Confidence interval, 置信区间4 Q. v3 u: X/ P# r8 W
Confidence limit, 置信限
7 n& g7 `& U4 S/ `Confidence lower limit, 置信下限/ K h9 R O: R' x
Confidence upper limit, 置信上限/ D2 \$ T. y0 @7 ?; n: e
Confirmatory Factor Analysis , 验证性因子分析
3 r! K2 q6 `* _5 G; `' w- c& y, U9 hConfirmatory research, 证实性实验研究
; t, A9 `6 G& }4 W7 e, P4 S% |Confounding factor, 混杂因素
, i% I* k; r4 p6 ?. K+ i ^Conjoint, 联合分析7 R$ i5 C6 C4 K* \
Consistency, 相合性, Q. p+ K& R E+ O
Consistency check, 一致性检验% M" p8 d- B Y/ T- p" e1 L% B7 j I
Consistent asymptotically normal estimate, 相合渐近正态估计& W4 D: e/ U6 [/ q: B* B6 `& `$ s
Consistent estimate, 相合估计- u% E' G' F$ A2 X# T1 a; a
Constrained nonlinear regression, 受约束非线性回归
6 \. w5 Q& U0 jConstraint, 约束
) r; |7 D1 u/ w, |- N5 U7 V9 Z6 h! iContaminated distribution, 污染分布7 Z. U6 A+ H9 C" S
Contaminated Gausssian, 污染高斯分布! d$ O' D7 ^( w
Contaminated normal distribution, 污染正态分布
: p" V' B, p2 Q. e. c- jContamination, 污染
+ y3 }" a1 U. l3 y: x4 e: E" nContamination model, 污染模型5 ^1 i0 c" {% E$ Q7 v& a/ `
Contingency table, 列联表
# o2 E/ X3 \6 J) yContour, 边界线
6 |' k8 h6 y: }4 hContribution rate, 贡献率$ v! i f- \! D" E! n5 b
Control, 对照
' W# V5 X2 t/ LControlled experiments, 对照实验# T( R- I' c1 Z4 f, W; i* Q/ s s$ o
Conventional depth, 常规深度5 g- x# J5 _; d3 g7 o: l0 y F6 b
Convolution, 卷积
z8 b7 w& J" \6 g6 f$ gCorrected factor, 校正因子8 j7 y& Y# S7 U! b
Corrected mean, 校正均值! ~ G: F4 c! `8 i2 O6 m! j
Correction coefficient, 校正系数8 d/ U& i# s# D1 g% T; u0 H$ J
Correctness, 正确性/ F t9 d2 T Q' f
Correlation coefficient, 相关系数
1 S8 N" u! r$ }8 ?9 M' P+ H* {' VCorrelation index, 相关指数
0 ]/ _$ e( ]0 s9 V% q+ B; r; I GCorrespondence, 对应" k4 o# R1 w6 e
Counting, 计数" T' |6 ?% y7 G! j, c3 O
Counts, 计数/频数
- `: G/ X `5 |/ ]' M8 rCovariance, 协方差
1 _! Z( _0 G# DCovariant, 共变 ( I3 C7 }9 |1 r9 T
Cox Regression, Cox回归* C3 d! `# f1 V: k/ a$ B( q
Criteria for fitting, 拟合准则
5 P# V& X& ?; \8 Y+ [% ~9 u3 ECriteria of least squares, 最小二乘准则" H* B+ b, b: }) S
Critical ratio, 临界比
1 g3 `! T: [+ H2 S4 dCritical region, 拒绝域
. a# j. u# P# P! nCritical value, 临界值4 }$ |: {: ~+ r$ v8 p
Cross-over design, 交叉设计9 @# s8 s0 @0 X
Cross-section analysis, 横断面分析4 G6 h( i5 s9 D! j5 ]8 s
Cross-section survey, 横断面调查; { k" [+ \3 L- b* h# @4 _2 Q
Crosstabs , 交叉表 ' f0 y, r- R3 I) e+ {" v
Cross-tabulation table, 复合表
( w% a, {0 E- J6 x8 v) sCube root, 立方根% B, S" u n; E9 V5 u+ d
Cumulative distribution function, 分布函数 z0 }3 P- N! m: s
Cumulative probability, 累计概率+ o2 T5 O1 V/ o. Q1 d+ t
Curvature, 曲率/弯曲! `2 F% i+ [: M( W, P' k1 U
Curvature, 曲率, j! G. ^: R0 `4 d- H
Curve fit , 曲线拟和
5 j! n9 E6 {0 A3 m3 x/ {2 \Curve fitting, 曲线拟合
; x! }. _: e5 ]3 v8 RCurvilinear regression, 曲线回归- p5 W) g" X p, i( N) d0 S6 w7 e
Curvilinear relation, 曲线关系1 v! }8 H: s6 U
Cut-and-try method, 尝试法7 \* o, L' _, M
Cycle, 周期% ^7 l( W, q1 K P( ~
Cyclist, 周期性
$ \4 @$ a8 S' E9 r0 ]D test, D检验- J7 _, f% O0 X8 u
Data acquisition, 资料收集
* T5 f. P1 ]3 _+ b' rData bank, 数据库( C( C! }, e1 s9 S
Data capacity, 数据容量
& ]3 w2 s7 v% [- qData deficiencies, 数据缺乏
3 w+ q. o& w) R* Q( qData handling, 数据处理
$ L: k) C2 ^2 t) BData manipulation, 数据处理
4 E. B }" E8 f, W- sData processing, 数据处理8 b: \( b, @' Z" f* ?
Data reduction, 数据缩减/ p1 i# F. K3 K; ^9 p# [+ _) F
Data set, 数据集- ?2 h: T: G9 X4 D1 A
Data sources, 数据来源
: V! a3 S. m5 Q/ SData transformation, 数据变换
; o, V! b: _! @( ~' O( {Data validity, 数据有效性
$ b; W9 w8 n$ P% dData-in, 数据输入' q/ t4 |: O4 ]" V$ b, Y
Data-out, 数据输出# _7 Q( y6 c. V, ~- d; q* R
Dead time, 停滞期- e4 I: o: q; x6 t
Degree of freedom, 自由度0 i: N4 M+ F6 u D5 q- \
Degree of precision, 精密度$ e4 d9 c; w2 {
Degree of reliability, 可靠性程度, ^1 [ c8 K# u5 K
Degression, 递减, B: ]5 `! D# ?6 t) h0 V ~1 R3 J
Density function, 密度函数
) N. @- z; q- wDensity of data points, 数据点的密度
Q9 Z. P7 v: Q8 ]Dependent variable, 应变量/依变量/因变量9 {( Y- N, o3 ~5 q! e) j, q' b
Dependent variable, 因变量* N; B6 C: \/ ?' L9 Z% n
Depth, 深度' C' g8 l& T' }' [# z, l
Derivative matrix, 导数矩阵
2 G- {2 o- d7 T8 t' bDerivative-free methods, 无导数方法1 m) @$ @. i- z/ _
Design, 设计
: c- b: R+ R h" R3 H$ @ KDeterminacy, 确定性; ?! l2 d) t4 O- k3 ?3 W( G
Determinant, 行列式
6 Y+ H/ c& Y1 Y* y% V: h& ?+ \Determinant, 决定因素! j. i" m6 ]* O E; [) r/ j
Deviation, 离差
: p e* _) u' ~Deviation from average, 离均差
1 M& J4 q& j" RDiagnostic plot, 诊断图
) {' O. q1 C" d; ~/ L% v& `Dichotomous variable, 二分变量8 v6 N0 i$ f. G/ O
Differential equation, 微分方程
4 K, x/ u9 }( l1 {, JDirect standardization, 直接标准化法
; ?) {) Z' @0 k# X3 j! NDiscrete variable, 离散型变量. {+ `3 l" F) I+ S" f% }
DISCRIMINANT, 判断 & |+ @+ _& N) O+ v
Discriminant analysis, 判别分析$ G7 p+ k, Z6 V$ U
Discriminant coefficient, 判别系数4 f0 x% t R$ H8 N: M" {
Discriminant function, 判别值
9 C) R* q Y" ^7 _* X; N7 d6 @Dispersion, 散布/分散度
9 C! A' {2 J+ k0 G% _% EDisproportional, 不成比例的
$ e, p" L$ ~' c' \Disproportionate sub-class numbers, 不成比例次级组含量+ g% Q+ Z( V$ `# }7 }- |
Distribution free, 分布无关性/免分布
; c1 ^/ z4 F# F* L9 T5 } wDistribution shape, 分布形状4 R! }/ w: `( _. u7 F) `# z! n
Distribution-free method, 任意分布法9 p$ p, V* z b' }
Distributive laws, 分配律
! m! {$ p" S( s7 g3 gDisturbance, 随机扰动项
% L* ?: r1 v/ F# y4 B- YDose response curve, 剂量反应曲线% O G4 I2 Q* f" z9 g+ ~" J
Double blind method, 双盲法1 O' t8 W! Z8 b. {
Double blind trial, 双盲试验
2 c$ V9 c/ I4 _Double exponential distribution, 双指数分布; Z. t" m+ r; T, a/ N/ G
Double logarithmic, 双对数3 H$ V' N" c, M% O( L, O
Downward rank, 降秩
& v. ~. X+ `' p: _Dual-space plot, 对偶空间图; R- w, ?7 l9 B( }- ~$ X3 c% u
DUD, 无导数方法: P& z; L/ L; b$ ^9 F! g% ]
Duncan's new multiple range method, 新复极差法/Duncan新法8 x9 A) R$ G# f, q k B
Effect, 实验效应
! W, u7 Z7 C# EEigenvalue, 特征值
( e8 Q6 w, g- Y; MEigenvector, 特征向量! k1 Z6 c- I( ]. ~' d
Ellipse, 椭圆, O+ a' V" O& J4 G m8 g
Empirical distribution, 经验分布
" G, q0 X$ j7 N5 d! b* NEmpirical probability, 经验概率单位
) G3 N! E, Y# TEnumeration data, 计数资料+ R7 U; `3 O! D8 W4 W- c7 O1 ]
Equal sun-class number, 相等次级组含量
- D9 H$ C% _5 yEqually likely, 等可能0 g0 s' g9 `6 m0 {7 Y" [5 l' v" S
Equivariance, 同变性9 ^" I' n0 k# ^- R
Error, 误差/错误* F K* A: v; k8 m# A7 |
Error of estimate, 估计误差+ A' b/ d8 B1 e' v! `* L
Error type I, 第一类错误
1 W: t" f0 e$ [* F2 p+ O! FError type II, 第二类错误
. g/ |7 }( ~) ]( SEstimand, 被估量
; \& h3 A1 a4 D1 g* }( GEstimated error mean squares, 估计误差均方 r: K7 i6 W( a5 [1 [+ O$ ?; a0 L
Estimated error sum of squares, 估计误差平方和
" _. G$ y, G z/ _2 N( xEuclidean distance, 欧式距离
+ {# g0 w3 Z$ K) k. R4 v' d' z. fEvent, 事件% W5 i. g0 V7 {0 X" X$ r4 f
Event, 事件7 e( i+ d2 y$ @7 v* K
Exceptional data point, 异常数据点
@6 Q' A X% Z! cExpectation plane, 期望平面
/ l' [* [1 L; W' X, {7 p7 g4 a% TExpectation surface, 期望曲面) b2 k) P* C ?2 h8 u( O* J% l. j9 t
Expected values, 期望值
( k t: y" j$ }$ P$ F [2 E3 ^3 [! R* aExperiment, 实验1 J; P, a) x5 {& }
Experimental sampling, 试验抽样4 V. X' K/ p5 c+ ^% x- B0 G
Experimental unit, 试验单位
# ~4 B) ]7 }: ^9 t& _" l7 e- x" h5 {Explanatory variable, 说明变量9 B' \2 c, E% q S! N+ o
Exploratory data analysis, 探索性数据分析, ?3 l/ J/ B6 P. U" _* b$ n
Explore Summarize, 探索-摘要( A2 e# }7 D( N7 q# G; g
Exponential curve, 指数曲线
" ]" ^) J4 R u0 m3 EExponential growth, 指数式增长" L, a, M/ \, |# T! A2 d. A- L
EXSMOOTH, 指数平滑方法 ; G: |0 q1 U. ~( h
Extended fit, 扩充拟合
7 j* L) p* M& r, m1 \$ KExtra parameter, 附加参数
' W, q0 z4 J H" \Extrapolation, 外推法
" w2 ^( T! e$ j- c" DExtreme observation, 末端观测值, ~9 V9 M0 Y, d# Y/ t6 k! m. `3 R7 T
Extremes, 极端值/极值
3 U1 i1 i1 R7 |- }9 |* W' d6 \F distribution, F分布+ {, L3 e0 q: F5 b% ]" y$ C
F test, F检验6 N; H9 ^ g# A3 Z8 D/ ^0 c2 B
Factor, 因素/因子
$ p' g! l0 h4 D; f7 B. w1 ZFactor analysis, 因子分析
4 P9 L' a1 _# e2 MFactor Analysis, 因子分析
: y, \: R* J# q) J6 UFactor score, 因子得分
4 r1 N/ p! s. L9 P% o# s# l, RFactorial, 阶乘7 l' D* J3 Z; }3 q$ W( {9 }
Factorial design, 析因试验设计6 H5 v; K: k }9 H5 z$ E
False negative, 假阴性
: Q+ {, T9 Q7 n$ H. \, GFalse negative error, 假阴性错误
8 I+ h, d0 `: U' h yFamily of distributions, 分布族
6 Z( d% g& G& DFamily of estimators, 估计量族
6 J( r- W$ L# W( c! B; s; yFanning, 扇面
1 ]$ Q A0 e- s2 PFatality rate, 病死率- [9 J* X3 W1 _8 E6 V$ i1 A& X2 h2 _
Field investigation, 现场调查
5 \( N; Z6 `: L& z8 y/ DField survey, 现场调查1 i* o/ h7 Z8 {/ d
Finite population, 有限总体; U7 A: ^4 y k4 i4 \9 O0 a$ l
Finite-sample, 有限样本' x4 x3 }8 D( x; M
First derivative, 一阶导数1 B4 ^+ p. k6 t8 q8 ?* s; V5 |9 r" L
First principal component, 第一主成分
- T$ @6 c9 }+ x/ QFirst quartile, 第一四分位数0 c. X8 i. d5 p, E
Fisher information, 费雪信息量
( b, Y2 G {/ ]; W- T5 LFitted value, 拟合值
# q4 a j1 M1 E( q4 s8 T9 F" G2 _Fitting a curve, 曲线拟合
4 b: E' Z& e) \' ^Fixed base, 定基/ @. h# L3 F$ z8 s5 {8 q
Fluctuation, 随机起伏& ^; X+ _) I& \0 {% R: x$ x
Forecast, 预测
5 r, G6 Q3 n% C; l* @Four fold table, 四格表 N- M5 t9 ~1 X; ^4 s' X
Fourth, 四分点
) G5 E7 A' o6 G* b8 iFraction blow, 左侧比率
! `1 Z" o4 U! @. J& VFractional error, 相对误差
# F2 o# @$ F# Z" W. O# @Frequency, 频率
) g4 P* F4 c' r7 ]3 t [Frequency polygon, 频数多边图4 U' [2 F3 R0 C/ l1 n
Frontier point, 界限点$ }9 |! r, b* l s
Function relationship, 泛函关系) _' Q* N- G0 a4 {2 {
Gamma distribution, 伽玛分布
! ~( i8 g8 A- o, }$ X- h) z6 s, k4 q$ QGauss increment, 高斯增量% K# n6 Z* B2 h4 s* N7 s5 [3 g
Gaussian distribution, 高斯分布/正态分布
2 H \$ i$ \" oGauss-Newton increment, 高斯-牛顿增量
6 i) U" q' @" G6 ~2 V7 j$ aGeneral census, 全面普查
: N! q5 Z2 h) A! fGENLOG (Generalized liner models), 广义线性模型 1 ~$ q% }5 r( ?( O6 m# k9 q! E
Geometric mean, 几何平均数9 o. D* n$ C+ v$ ~: w2 c
Gini's mean difference, 基尼均差: D# K0 \4 B4 k6 p- l9 t* U+ F4 B
GLM (General liner models), 一般线性模型
$ r& z+ N* }; ]; }3 B% M9 JGoodness of fit, 拟和优度/配合度7 @0 x9 u0 F% v/ l' _, w6 Y
Gradient of determinant, 行列式的梯度& E$ J( A) t$ G( @# g8 B1 |
Graeco-Latin square, 希腊拉丁方
8 Z( u8 U+ f: C, f2 }) ^Grand mean, 总均值% x E4 f- u- O% ~" {+ [
Gross errors, 重大错误
5 h2 V. w" ?2 g: ^' YGross-error sensitivity, 大错敏感度0 ~, b' }; \* X- G& |2 C
Group averages, 分组平均& E, K4 r% p7 @( j \" \
Grouped data, 分组资料
+ @3 ?, q. M( `$ @4 \9 yGuessed mean, 假定平均数
# X1 n, F' O7 I5 o) g1 _Half-life, 半衰期3 K' Y3 p- \& z9 h: }# L: ?
Hampel M-estimators, 汉佩尔M估计量7 V. e* E0 r0 [. d) }7 Z
Happenstance, 偶然事件0 Y4 C4 C( k6 q. C: ~
Harmonic mean, 调和均数
3 s6 J/ a+ [4 Y# tHazard function, 风险均数
/ q% p$ F1 X) nHazard rate, 风险率
) v* F: B! k( N" m) \Heading, 标目
: f2 T+ P t6 c8 ]& eHeavy-tailed distribution, 重尾分布
: R r5 J8 o: n- S/ R2 rHessian array, 海森立体阵* b1 c( M( z8 U, _7 g' [
Heterogeneity, 不同质/ ?# R' ~/ ^1 ~7 L2 I
Heterogeneity of variance, 方差不齐
9 n# j; m! E, O2 x0 H2 FHierarchical classification, 组内分组
) O" b2 D( ]7 C" M( o1 |; BHierarchical clustering method, 系统聚类法
& f" {4 j5 s" Q% x% ^High-leverage point, 高杠杆率点, _2 ?; [8 _9 I7 [! i/ J
HILOGLINEAR, 多维列联表的层次对数线性模型
$ q9 S: b$ I$ z2 j+ H8 L: w% @Hinge, 折叶点
; |& V0 q% r( t LHistogram, 直方图/ t: V- R7 i2 i- H/ B" V
Historical cohort study, 历史性队列研究 - S9 w5 a! Z j/ N5 c, c0 R. w
Holes, 空洞+ m0 u. I* |0 [# L4 V, ~& n* G L
HOMALS, 多重响应分析
* i& N. Y: Y* K( L8 r' b/ t# |' pHomogeneity of variance, 方差齐性
' G/ o' n, b i4 G9 K* OHomogeneity test, 齐性检验
- R1 N( t4 N" ~( |6 D/ B# N6 N. y1 E+ JHuber M-estimators, 休伯M估计量7 Q. g$ v4 u, n2 J( |" a! O8 A
Hyperbola, 双曲线
5 l+ b* |" w xHypothesis testing, 假设检验
* U3 w! I$ B6 x; S- AHypothetical universe, 假设总体
6 A. ]: _+ v) H& [ f6 VImpossible event, 不可能事件2 {) L5 l V% C8 Z
Independence, 独立性
6 ]1 v, h) }2 w9 GIndependent variable, 自变量1 h& W/ B( }4 o# }+ M7 J0 l) q0 m
Index, 指标/指数2 H8 A- f6 e9 M) T# W C T
Indirect standardization, 间接标准化法" Z$ A% d4 I, }6 t! i
Individual, 个体
3 s& X- W& e+ x2 |3 a1 \Inference band, 推断带$ u. `0 w# `" J$ j2 w8 H2 o
Infinite population, 无限总体7 K; ~; j7 G" X- Q
Infinitely great, 无穷大
" S/ w0 e$ [9 B H! h6 O& jInfinitely small, 无穷小
8 q& p4 \& c5 ^" d% U7 x3 ~8 _Influence curve, 影响曲线
& o' [- I4 i t+ HInformation capacity, 信息容量; r+ ^ f7 T3 d* b
Initial condition, 初始条件
* C5 |; M7 `, j/ O, u3 B7 a) OInitial estimate, 初始估计值
% j5 R) S' U+ L( d+ S0 k/ AInitial level, 最初水平
; A' n) \ x: W( m, p% {Interaction, 交互作用7 K' @" A/ N X" |5 ]5 B! `3 D* r/ Y
Interaction terms, 交互作用项
: F- \2 @! E1 ~( HIntercept, 截距
" e1 q9 P* b: b; ~Interpolation, 内插法$ Y. W$ c0 w: ^+ x5 d
Interquartile range, 四分位距. d7 B1 k' g2 c8 }# f: s' Y
Interval estimation, 区间估计
6 W* \) E9 R+ V* `. YIntervals of equal probability, 等概率区间 K3 v. O" S& [
Intrinsic curvature, 固有曲率+ E# c1 {1 z8 E9 q+ R* ~
Invariance, 不变性, c! A Q" I0 W2 Q
Inverse matrix, 逆矩阵+ E/ V8 V2 N( T& l1 X6 Y
Inverse probability, 逆概率, o0 u' j v% m: Q4 C9 \ ?# J
Inverse sine transformation, 反正弦变换5 I/ n9 N7 E1 o) T) h( Y
Iteration, 迭代
* U4 Y9 B2 _; [) tJacobian determinant, 雅可比行列式
! s0 _' D$ G0 w0 n. U* aJoint distribution function, 分布函数! \3 [& w; R9 V+ ^+ n6 ^8 m
Joint probability, 联合概率 f+ @0 Q; A) n$ A6 a9 X7 N& m
Joint probability distribution, 联合概率分布
8 o: m$ j# q3 B- ^5 M1 L' \K means method, 逐步聚类法# p/ d/ v7 x9 O# q) N6 M" {2 I
Kaplan-Meier, 评估事件的时间长度
; e. g! F' {. ?; T7 o: y! p5 [Kaplan-Merier chart, Kaplan-Merier图
# x$ b% E8 c1 b5 b- U! H5 kKendall's rank correlation, Kendall等级相关: j: Y/ R k! e; X: T6 ^
Kinetic, 动力学, J3 O$ K6 G; a0 ?* a6 E
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验9 P' L$ s9 L, s1 j9 @0 R7 k8 v
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验" w$ `! p7 i, Y; f
Kurtosis, 峰度
. Y" I8 [! P; _ _Lack of fit, 失拟
+ m5 t/ ^3 V) _/ S# b/ R' R6 JLadder of powers, 幂阶梯, x9 g# P; [4 S& B, L: e2 t
Lag, 滞后: X. w1 H) i8 r4 b6 H2 h
Large sample, 大样本
+ N9 Z: A, u- Q0 nLarge sample test, 大样本检验
5 [. W" W8 D- U- `1 F* l) ]5 ]$ MLatin square, 拉丁方
' O2 [" J' S, Y! i- @& \Latin square design, 拉丁方设计
! U3 r" r1 U5 ^Leakage, 泄漏* ~0 g% h+ S3 h% @; p% u3 [
Least favorable configuration, 最不利构形
0 F6 V" e4 w5 _! E( a3 A$ d9 ^" ?% LLeast favorable distribution, 最不利分布3 L' U' D8 s" U4 _' }# w5 E
Least significant difference, 最小显著差法9 b3 l4 V* @: j
Least square method, 最小二乘法
# n2 A& s& t4 ]0 sLeast-absolute-residuals estimates, 最小绝对残差估计
7 o- i7 y! M% @1 ULeast-absolute-residuals fit, 最小绝对残差拟合+ v* j4 _" l9 ]8 ~: f
Least-absolute-residuals line, 最小绝对残差线
! w3 c5 {! r, ZLegend, 图例
- B6 N4 W% w) X( w, f/ W5 eL-estimator, L估计量& w8 q3 m6 h" O* C. `
L-estimator of location, 位置L估计量7 M4 h6 z }% T5 w, N9 m, c
L-estimator of scale, 尺度L估计量
4 p4 D B9 u3 @: ~- bLevel, 水平( S6 a7 J6 I3 J1 O) [
Life expectance, 预期期望寿命
) f: c( R6 e% O0 G9 N$ w, b' R: dLife table, 寿命表' d) x9 a* X3 Z* x
Life table method, 生命表法
! t2 T! `2 C. XLight-tailed distribution, 轻尾分布8 v% E( Q1 l0 l
Likelihood function, 似然函数) P3 Y6 R* W+ Z1 Z4 X0 W
Likelihood ratio, 似然比 O7 g! [6 V7 \# W+ H( @. i" I
line graph, 线图
! C. m8 w) m) R/ Q6 }8 p2 fLinear correlation, 直线相关
P. j% O# d$ [) NLinear equation, 线性方程: e1 e: `9 D+ x% Z0 e t$ V2 D4 u- e6 N
Linear programming, 线性规划( Y G" F8 V/ c( c, w! q# ?1 f7 x( r
Linear regression, 直线回归
$ |$ w$ D' L& A9 iLinear Regression, 线性回归$ V/ _8 y5 e& D: g
Linear trend, 线性趋势
5 \, v, ?) W/ z( w! ~Loading, 载荷
# _% i7 o; }& Y* @Location and scale equivariance, 位置尺度同变性
1 C$ H1 E. r9 P7 L8 w, x$ c/ }Location equivariance, 位置同变性
4 A1 {+ h& m1 \5 F! `2 M( |. ` CLocation invariance, 位置不变性
% C: g9 n. {. wLocation scale family, 位置尺度族
5 w& w- }' X. y; t2 C" |9 ^2 jLog rank test, 时序检验 ; r8 W# ^; y& }+ |
Logarithmic curve, 对数曲线
2 ^+ J9 t( ~( M+ n- gLogarithmic normal distribution, 对数正态分布
* k0 L- [, h) GLogarithmic scale, 对数尺度
) Q. J" g$ ]' y( @Logarithmic transformation, 对数变换
- w5 r& ^4 J1 N* {9 Q+ SLogic check, 逻辑检查
+ b) C0 S+ P) `Logistic distribution, 逻辑斯特分布, r, X7 R) g9 a( p6 b% i0 }
Logit transformation, Logit转换
4 a/ \2 o$ _; U" e2 r& e. Z7 ELOGLINEAR, 多维列联表通用模型
# m9 A. T* Y4 RLognormal distribution, 对数正态分布9 @+ _" k7 @$ ~7 V3 e' \5 n. F
Lost function, 损失函数
6 h/ {) g2 U0 w/ d4 j& qLow correlation, 低度相关) L; L9 N$ \/ ?# u
Lower limit, 下限
' H- Z Y5 F: a: qLowest-attained variance, 最小可达方差0 ?: ^2 y; ~! q: Y& b" e; g
LSD, 最小显著差法的简称
: c- q7 r8 A& S m- ^+ tLurking variable, 潜在变量) O m8 d( U. c) ?$ Q, h" V
Main effect, 主效应+ D6 z f i; Y8 e
Major heading, 主辞标目; Q$ k( t3 @1 O/ @
Marginal density function, 边缘密度函数. e% y W' f4 V8 `2 t
Marginal probability, 边缘概率
7 V2 W! n8 M$ h# @$ N1 Q0 eMarginal probability distribution, 边缘概率分布" v9 @# j& E( g1 U
Matched data, 配对资料: w7 D% @$ }5 R6 k8 `& i, ]
Matched distribution, 匹配过分布8 O4 v) U8 _6 Z- n
Matching of distribution, 分布的匹配
: ?# ~# e" f% VMatching of transformation, 变换的匹配; O( e2 `; I1 F% L5 R& _/ n
Mathematical expectation, 数学期望
6 A A2 i+ T7 ]0 y% ~Mathematical model, 数学模型" w6 \. \2 @( ^5 @7 Z0 D
Maximum L-estimator, 极大极小L 估计量
9 |9 ]$ P" `* L; cMaximum likelihood method, 最大似然法& }6 m7 M! f! k
Mean, 均数5 j* C! d3 m( O( e+ i' P
Mean squares between groups, 组间均方
% o' _; v' D* S- o: uMean squares within group, 组内均方
1 }' w9 p3 B. OMeans (Compare means), 均值-均值比较
2 F4 p( v+ J2 m" MMedian, 中位数
/ p$ H3 E: C3 {+ F5 x7 w% WMedian effective dose, 半数效量, y: e" r( d7 T+ F+ _
Median lethal dose, 半数致死量
6 }7 ?* q# ^+ xMedian polish, 中位数平滑
a* w$ D9 y" J/ _Median test, 中位数检验# U- {2 W8 Q( g" O G
Minimal sufficient statistic, 最小充分统计量
8 o9 h; t' I$ Z' O, f: ?! sMinimum distance estimation, 最小距离估计
) [* b6 Z3 K, s) {. U6 E, GMinimum effective dose, 最小有效量1 }8 q4 U3 l) l2 }. W. B6 |% @
Minimum lethal dose, 最小致死量
; J2 h, K5 }" @) N7 k7 T( V6 O; F0 dMinimum variance estimator, 最小方差估计量. S! p! Z2 `! C
MINITAB, 统计软件包0 j" C: m" m7 f7 Y1 a* m
Minor heading, 宾词标目, z% w6 a" x( f' s" e9 c9 G$ `
Missing data, 缺失值( l: D# x B4 L) u, a
Model specification, 模型的确定' m7 q9 q' B9 Q# [) f
Modeling Statistics , 模型统计6 [& W2 x! P, K
Models for outliers, 离群值模型) H6 U1 m! _: R; t. T
Modifying the model, 模型的修正
5 u; F, o% f" h! v9 z/ |Modulus of continuity, 连续性模3 }5 q1 P2 V: q1 S" K1 |2 m
Morbidity, 发病率
( X4 K3 v# u- U mMost favorable configuration, 最有利构形
2 y' v. A& }7 J' q( VMultidimensional Scaling (ASCAL), 多维尺度/多维标度- M$ U" ~* @$ W3 i5 {. u9 R/ S
Multinomial Logistic Regression , 多项逻辑斯蒂回归3 j, @. w0 e7 Y8 b# _* K+ z
Multiple comparison, 多重比较
$ R1 r6 @0 ? E7 w" MMultiple correlation , 复相关
8 t$ [( I3 Z& G- c; gMultiple covariance, 多元协方差
! U1 j V4 k' E: a8 HMultiple linear regression, 多元线性回归
' i4 r2 C/ B6 E+ U9 zMultiple response , 多重选项. Y# d3 `8 J! s" a$ u0 A
Multiple solutions, 多解" A1 f; i9 s/ G3 Z9 n5 i _' O
Multiplication theorem, 乘法定理& g! _# Y+ l7 x* [4 F
Multiresponse, 多元响应5 G/ b+ p. U4 C# }. f
Multi-stage sampling, 多阶段抽样7 j' r/ u$ K7 Y9 X: c8 p
Multivariate T distribution, 多元T分布' g. U. M. c$ W8 m
Mutual exclusive, 互不相容
! y9 y* l, b! E- v" T7 e8 Q; x$ DMutual independence, 互相独立( @) D* D) }5 m; u8 g
Natural boundary, 自然边界* f) t& G+ W. @7 q `# p! a
Natural dead, 自然死亡7 H9 |4 t9 C; |' p
Natural zero, 自然零
: m Z3 ~9 y( d3 QNegative correlation, 负相关2 H2 S0 H- M3 ?" Q& y
Negative linear correlation, 负线性相关" F. l \) G* _: p- I) ~- H' R
Negatively skewed, 负偏; a% k+ o, T0 Z' B% o* |" c
Newman-Keuls method, q检验% _* A; e0 f% ]0 H1 W' H
NK method, q检验
- b3 E* w+ }' @3 U8 U4 B' TNo statistical significance, 无统计意义1 y% @ u- r: _ Z5 ^: c
Nominal variable, 名义变量1 I% S% {) a. ^5 U: @9 Q
Nonconstancy of variability, 变异的非定常性
7 Q9 K. M3 V' gNonlinear regression, 非线性相关- N5 W# E( l* B- J4 N2 P# m! I1 i, G
Nonparametric statistics, 非参数统计
. ~" I& _) l3 u6 k4 {! ]) Z) D2 ENonparametric test, 非参数检验 k7 ]' V' z8 C
Nonparametric tests, 非参数检验$ r6 T- D( ^/ V5 i
Normal deviate, 正态离差
0 ~) Y0 T: T3 M aNormal distribution, 正态分布
& [1 c9 A( o: T3 M( ZNormal equation, 正规方程组
- d8 {0 W2 b, c: KNormal ranges, 正常范围, Z7 B) w" C! `0 d
Normal value, 正常值
* ?: r& i0 m/ j4 J' J2 @" [5 P. SNuisance parameter, 多余参数/讨厌参数9 f. t9 n% O( H$ @, s
Null hypothesis, 无效假设
8 R+ p) B- M) ^; G% O# I# mNumerical variable, 数值变量+ N3 n. [6 o3 y; }& h- @
Objective function, 目标函数
' A* v8 m( I, t1 L6 PObservation unit, 观察单位
& M3 Q2 N0 s- v) J6 z, YObserved value, 观察值
& A, e: |# a1 jOne sided test, 单侧检验7 n: T, H& k ^; \, _7 I* L
One-way analysis of variance, 单因素方差分析
1 G- o7 [- i% a x9 ^Oneway ANOVA , 单因素方差分析
K) e. S H8 @7 o& _; @+ EOpen sequential trial, 开放型序贯设计, \0 `9 E) g5 c0 ^6 K8 O
Optrim, 优切尾
3 Q9 S4 @+ Q D" i. s0 wOptrim efficiency, 优切尾效率
: l& t( N7 R' A! t8 C, COrder statistics, 顺序统计量
& {: X( u# R. WOrdered categories, 有序分类* S3 }2 f- I( S F k0 o
Ordinal logistic regression , 序数逻辑斯蒂回归! e6 N, [6 x3 I. B; g
Ordinal variable, 有序变量
- I( g7 ~' u0 u* p' e* ^Orthogonal basis, 正交基) }/ Q8 ~& C: `; S& p
Orthogonal design, 正交试验设计
) P K. ?; Q4 \3 Y4 F/ }3 YOrthogonality conditions, 正交条件! B) q% D9 ]# @$ F- k2 W
ORTHOPLAN, 正交设计 : I, X5 a5 I7 X f5 v
Outlier cutoffs, 离群值截断点# E4 e, R% v* j
Outliers, 极端值" c) O; o- {1 k& g7 _; t, C
OVERALS , 多组变量的非线性正规相关
# O" I7 Z" w# F( u# z, aOvershoot, 迭代过度$ ~) f5 H; s/ V/ l+ G
Paired design, 配对设计% S2 L' t* f* i) ?& U2 V! p
Paired sample, 配对样本
# U8 C: I7 ~, x# n5 A& {Pairwise slopes, 成对斜率
$ l4 E# R+ n; rParabola, 抛物线. n1 |( h9 R2 [* i0 d! P
Parallel tests, 平行试验
$ H: p$ R4 j$ g, W, T) B1 ?Parameter, 参数- x" y) A5 O2 |+ k6 V5 ]* s
Parametric statistics, 参数统计
, `! }/ [. d# a1 x# {7 l; s# AParametric test, 参数检验# p/ z- j; s: i+ l0 \* l
Partial correlation, 偏相关
0 n3 O. N+ E8 h! i. b! h" ^Partial regression, 偏回归
" D$ `! F) F3 F& ~; H( LPartial sorting, 偏排序
/ m) ^% f J" b9 O3 |% zPartials residuals, 偏残差. d, X. _& S9 Y$ c+ Y, j0 a2 M: a0 O
Pattern, 模式& c% \- ?- @$ D) J+ k
Pearson curves, 皮尔逊曲线" d6 j$ x2 |; a6 A7 ?
Peeling, 退层8 m5 z K5 H( D) a, J/ s
Percent bar graph, 百分条形图$ P' Q6 F8 B% @
Percentage, 百分比
# I' f! i- g& m$ n& f1 _Percentile, 百分位数6 u z' r o9 h
Percentile curves, 百分位曲线1 L8 ?7 K" V) \0 Z1 v0 q/ R
Periodicity, 周期性
0 X8 a3 W; |6 X; T' B/ o2 FPermutation, 排列; M+ ?5 E' O4 e' z! v
P-estimator, P估计量+ n+ Z: Z8 d! e m0 G% Q! L
Pie graph, 饼图: D# H; q/ {: F! u$ d
Pitman estimator, 皮特曼估计量
! {6 }+ v* _- ]6 Y8 i9 {6 KPivot, 枢轴量
$ t+ S& z% T4 U& [& [Planar, 平坦5 c4 Z# X( G4 N. v- g
Planar assumption, 平面的假设/ b* J4 @; o: {8 o3 R( A
PLANCARDS, 生成试验的计划卡
, `) Z0 G: w6 f0 vPoint estimation, 点估计
' W& A: j7 S% f$ A4 K! mPoisson distribution, 泊松分布
2 L" C$ h8 C! z- Z1 tPolishing, 平滑
# V: {6 E% O! q9 [Polled standard deviation, 合并标准差/ b' v! `' N% s- z# k
Polled variance, 合并方差1 g% ^( c2 P* x: A) d1 z0 [0 U
Polygon, 多边图7 T7 N' O4 ?5 n
Polynomial, 多项式
0 w$ V% D# r4 s1 q! ?% m0 JPolynomial curve, 多项式曲线
7 T' F3 B E' E7 n# `Population, 总体5 [8 L$ o M# Z
Population attributable risk, 人群归因危险度
- f2 ]! ]- F+ ?1 R9 M( q) I, SPositive correlation, 正相关
/ Y% o/ L. ~. w7 z0 O+ ^Positively skewed, 正偏
* o- B7 u9 ?& V, v' ^, cPosterior distribution, 后验分布- ?) v8 Q5 W" M, f) V% f
Power of a test, 检验效能: v( m- Z8 n6 P7 @( s4 m7 j
Precision, 精密度
( G( Z# E" g6 W; B! v( ZPredicted value, 预测值
* |+ s* G) l T$ f* \Preliminary analysis, 预备性分析
4 a9 ]7 Y+ i, g# rPrincipal component analysis, 主成分分析
/ @" {+ K% F; Q& o& U% g. ~Prior distribution, 先验分布6 r* V! }* ]/ Z% T
Prior probability, 先验概率: Z, I/ B1 R$ Q
Probabilistic model, 概率模型$ Y. X; y: I2 e
probability, 概率9 K1 m, g" V3 n0 o' w1 f4 ]
Probability density, 概率密度7 w) @* k C+ E& v" _
Product moment, 乘积矩/协方差
1 g/ g+ ?+ X" [Profile trace, 截面迹图9 \$ E& J9 R0 z5 L
Proportion, 比/构成比
. r* n& @9 b: ]& f& K- xProportion allocation in stratified random sampling, 按比例分层随机抽样
9 b0 d) K" g7 V, y" `Proportionate, 成比例# r+ N5 o' A$ z; Q- M/ d5 m) Q
Proportionate sub-class numbers, 成比例次级组含量) ]" q3 I' z5 W* @
Prospective study, 前瞻性调查
1 e B+ @ F# N! c$ VProximities, 亲近性 : o: Q3 E, s) _: X4 x- }
Pseudo F test, 近似F检验 v- \$ g X$ |9 @% R9 h# A
Pseudo model, 近似模型 \" |% p" O3 |( d. ?6 a0 `
Pseudosigma, 伪标准差
( ^' [4 B0 F5 N" zPurposive sampling, 有目的抽样* C) Q- b: ?* R, R7 E/ ~" j$ [3 t2 j
QR decomposition, QR分解
' t5 b Y3 T6 O+ OQuadratic approximation, 二次近似
" A$ o' O7 H. I5 kQualitative classification, 属性分类
' k% Q N- K5 D5 F8 AQualitative method, 定性方法
% Y& Z/ H8 t( {, qQuantile-quantile plot, 分位数-分位数图/Q-Q图
+ ~. r' U0 p; u3 g7 D) v2 tQuantitative analysis, 定量分析
, C' r9 U; F. A. C7 A1 m/ K. kQuartile, 四分位数7 w W, B3 O- O1 q; w" F
Quick Cluster, 快速聚类
8 G, b% ^% @, R# @' V, @! f. Y& Y# wRadix sort, 基数排序
1 v# q; T. B& [( m- U- |4 L6 c9 H) oRandom allocation, 随机化分组
, e! | z4 D( ^+ F- ?* j' \! qRandom blocks design, 随机区组设计
* G8 L+ G0 l' uRandom event, 随机事件
0 w# X8 @# g4 k5 n0 sRandomization, 随机化# v( f6 X6 j+ j
Range, 极差/全距0 Z. b3 c2 C! \
Rank correlation, 等级相关
0 ]) E8 k6 d- g9 B6 n& H8 r! ?Rank sum test, 秩和检验& q+ a h& ]) }# B8 V6 ~
Rank test, 秩检验
; F/ l' d" y% F. T }+ pRanked data, 等级资料
- Z2 i# v( P/ [: HRate, 比率
) P/ @! T& `5 ]) }! ?Ratio, 比例9 ?1 C8 c9 z0 ~2 ~9 \, y
Raw data, 原始资料
; D: ]8 T: {# H |! ORaw residual, 原始残差1 @2 w9 A- u4 y* O- K
Rayleigh's test, 雷氏检验
9 Z* |" A9 i( q7 YRayleigh's Z, 雷氏Z值
1 P2 a+ Z% y/ [ d' o! U& [+ E: A7 tReciprocal, 倒数
! [# g& k5 g" ^" U3 G/ SReciprocal transformation, 倒数变换
3 t+ `/ t0 o9 P8 ~% LRecording, 记录8 w9 @7 j1 Y8 `0 N! D A2 K
Redescending estimators, 回降估计量7 F% n6 y8 b1 Y
Reducing dimensions, 降维0 X/ o6 D& ~3 a
Re-expression, 重新表达
) m# D0 z6 P7 A* d0 t/ r' y# n n, U1 lReference set, 标准组
2 n# H- j7 Z7 U+ V- g0 sRegion of acceptance, 接受域
! ?1 m9 K7 [9 t2 h+ G1 d2 tRegression coefficient, 回归系数# I1 @, T- J- f" M6 A8 @5 j1 C
Regression sum of square, 回归平方和
' T; |" z4 _; q" S. V/ @! GRejection point, 拒绝点
6 Y8 L$ m J+ X: S6 o. iRelative dispersion, 相对离散度, ?6 j8 V6 _2 N
Relative number, 相对数1 w) ~% e. B1 {% H v3 M/ ^" c
Reliability, 可靠性
x* I) f! O7 ?# _0 f! U6 }0 p4 ~Reparametrization, 重新设置参数
2 E* h0 k4 b1 w9 W' K8 GReplication, 重复
+ z3 \" e1 t( P* d+ ]! Q+ }Report Summaries, 报告摘要
+ A8 P! @; ], Y9 I% N7 k8 iResidual sum of square, 剩余平方和, R; q$ q9 a3 \; b- v$ N4 ?
Resistance, 耐抗性- S7 R* T) k/ F, c+ [) g# ]! @; g
Resistant line, 耐抗线
# s8 x4 D, @/ Y, |0 LResistant technique, 耐抗技术
" U2 f6 F4 V j4 iR-estimator of location, 位置R估计量
) u; U2 s) h2 |! l$ y) R5 tR-estimator of scale, 尺度R估计量
! I- I/ f+ I+ a$ [, E+ o$ o; C8 zRetrospective study, 回顾性调查
$ J3 H V% z y# hRidge trace, 岭迹
0 ~, `3 i4 F, _" r+ U" DRidit analysis, Ridit分析: \& x; A, i1 T9 _
Rotation, 旋转, t. C, K7 x9 m2 J. j) Q8 l% a
Rounding, 舍入
B' \* I4 T' U! X- _0 R9 \, DRow, 行" C0 }2 x* e: c
Row effects, 行效应
0 F. c3 W) \* ?9 t, f: oRow factor, 行因素
3 P- a% _8 Z. @' p# DRXC table, RXC表& N. y' J, P6 k) ^
Sample, 样本
) ~7 r2 k: n# y" vSample regression coefficient, 样本回归系数
1 v' x" G" c$ d* S! `' \9 M. }Sample size, 样本量
& j; I, {0 C3 p A7 KSample standard deviation, 样本标准差
+ ?! P& g& n$ e) E }0 c8 FSampling error, 抽样误差- y3 K% k8 V } @6 w
SAS(Statistical analysis system ), SAS统计软件包9 p* H! K/ a2 I9 g! f9 A( H
Scale, 尺度/量表
3 F% B& G1 d& y: u! v' EScatter diagram, 散点图 ^8 G+ \5 f( N2 M, x7 S
Schematic plot, 示意图/简图) ^% [! v* p; `9 B. F
Score test, 计分检验
, T( r3 q, i. }+ u, qScreening, 筛检9 _* F3 Z+ k1 N/ M- ]* W( C& D
SEASON, 季节分析
/ R8 K! S# Y3 p; M$ o, p% OSecond derivative, 二阶导数% ^3 Q3 f7 s; A
Second principal component, 第二主成分- F- Q& H/ Y3 m' }4 i2 v1 T* D- G
SEM (Structural equation modeling), 结构化方程模型
! [% ~2 I: d9 {- Q: fSemi-logarithmic graph, 半对数图6 k! h0 I# V5 `
Semi-logarithmic paper, 半对数格纸4 E) }% b! q0 P* T. j
Sensitivity curve, 敏感度曲线
2 I: w, p" U3 ~5 l/ gSequential analysis, 贯序分析
) z' M9 C/ u) C+ n4 C0 J9 zSequential data set, 顺序数据集
9 w) m+ ?6 O ^5 v, h7 WSequential design, 贯序设计
! d+ |3 U2 n' C8 n, k! `Sequential method, 贯序法- Z8 O5 M; {: x2 Q3 M2 v/ u. K
Sequential test, 贯序检验法. u& B4 s4 T! b, {' @1 G- A
Serial tests, 系列试验
* P5 o4 _3 S$ v: k6 mShort-cut method, 简捷法
v- c! g. c# |- w1 bSigmoid curve, S形曲线
' ~ {7 y! b k& aSign function, 正负号函数
5 J8 L$ B+ T m6 BSign test, 符号检验
* `% L8 h& M' d2 l5 f) PSigned rank, 符号秩
+ V; R! V' r2 BSignificance test, 显著性检验
* h3 ]" [0 Z2 V" p0 OSignificant figure, 有效数字
6 M% S0 q' P t) n9 ZSimple cluster sampling, 简单整群抽样! f/ p6 C6 l2 U
Simple correlation, 简单相关2 r) r7 X1 ^$ ~- u# y4 m1 ]1 O! j
Simple random sampling, 简单随机抽样; d. s- T; D% N
Simple regression, 简单回归
! D/ O" M' K: f( u. g7 fsimple table, 简单表
3 Z; }; ]# C, N4 C7 ySine estimator, 正弦估计量
6 |; X+ P9 N, }, wSingle-valued estimate, 单值估计
5 c" v" {# m+ Z( ySingular matrix, 奇异矩阵
$ z3 u8 n0 a9 \Skewed distribution, 偏斜分布
0 r- J2 O" M0 X9 c) |( {) s4 P2 Y+ \. \Skewness, 偏度
& p0 \, F9 w7 u4 RSlash distribution, 斜线分布
3 n0 D: z8 ^, L6 u; ZSlope, 斜率
" |) U* R" N ?' t( v& B8 K) OSmirnov test, 斯米尔诺夫检验
3 w1 U$ h% N7 a7 L: Q" a# sSource of variation, 变异来源
, [. u) h2 }% @9 hSpearman rank correlation, 斯皮尔曼等级相关
2 e; g: f8 v9 Y, U& D a( f+ `Specific factor, 特殊因子' }% B5 q# h( s8 z- @
Specific factor variance, 特殊因子方差7 r& R# W9 ?6 j3 c
Spectra , 频谱
$ s- n1 e6 [$ K% pSpherical distribution, 球型正态分布, s2 `1 L/ j: [* F+ { s4 T
Spread, 展布$ i1 d/ a- ?: i r; @
SPSS(Statistical package for the social science), SPSS统计软件包
5 E$ n4 L7 y( G7 k% m! ?2 S$ PSpurious correlation, 假性相关
% J" x) N0 ^! x) F+ X: MSquare root transformation, 平方根变换: J+ c5 u1 e# g" O5 p) t. F/ N
Stabilizing variance, 稳定方差! N: H2 @2 F5 F3 ?! }
Standard deviation, 标准差- S5 |# j# ~. n" O, u
Standard error, 标准误2 m. \9 \0 e; K0 }) J ^- K
Standard error of difference, 差别的标准误" n" ]7 f7 o0 m& i4 q: ?/ H6 y5 I
Standard error of estimate, 标准估计误差% i. t, L7 u; B, v+ n. t; C
Standard error of rate, 率的标准误7 a" y4 A! o0 b! p
Standard normal distribution, 标准正态分布
% }4 I# @5 k9 y1 W) H2 v+ RStandardization, 标准化! c$ T" Q X( b! {" \& m! {
Starting value, 起始值- s$ b1 [$ j w {3 j4 M' A
Statistic, 统计量9 x' J+ t- K5 h( `* U, T
Statistical control, 统计控制
! H' s0 q- s. Q/ M2 z7 qStatistical graph, 统计图7 Z' \& r/ F0 K8 s! A: J
Statistical inference, 统计推断
0 s" ^+ X: w$ Y. t8 C9 RStatistical table, 统计表& c: A: K! Q9 K4 b' g
Steepest descent, 最速下降法3 _$ N: l5 X- N3 D; D/ G
Stem and leaf display, 茎叶图& X0 f8 o" s3 F; I( q& T5 e1 O
Step factor, 步长因子
; Y$ @+ s6 H2 y* Y% i( l9 z5 lStepwise regression, 逐步回归* a! x( g& M% M1 _ _& }, ?
Storage, 存
0 g" Z2 X+ Y) R8 k2 `" u3 bStrata, 层(复数)
- n% @0 O5 h' rStratified sampling, 分层抽样9 S9 Q& L# ^; ^/ ^
Stratified sampling, 分层抽样9 e$ } x! `0 }9 o6 Z+ `
Strength, 强度; P, _% A Q1 ` {$ G
Stringency, 严密性, I3 m5 z* y3 ?. L
Structural relationship, 结构关系" v$ s# x$ t' V+ `
Studentized residual, 学生化残差/t化残差+ N( \% J' W& w, {+ A9 E, h
Sub-class numbers, 次级组含量
; c8 u" r- Y4 _: v' W' C: n7 f& R6 MSubdividing, 分割; T4 S& j: J) Y0 _% a( j
Sufficient statistic, 充分统计量
. J4 W4 C* `0 s8 w4 v) K9 r. M/ lSum of products, 积和
" g# X, L( H( s% k! J5 USum of squares, 离差平方和
2 s9 {# j, g' D- _ W; I2 L! HSum of squares about regression, 回归平方和
: y- ^* w$ s4 }8 N/ `( c- f4 }Sum of squares between groups, 组间平方和
6 U! X% W' z7 ]2 K, S' FSum of squares of partial regression, 偏回归平方和/ A9 q4 |5 O2 |& E
Sure event, 必然事件
5 a% }4 h9 T, v2 t3 _' h1 M) xSurvey, 调查; a5 L2 \! f" l1 k
Survival, 生存分析1 K% S& Z" S' V; R/ B, o( s
Survival rate, 生存率
1 a: O1 e# L& L+ f4 Z' z- A. ZSuspended root gram, 悬吊根图) y. _8 t" a. ?8 k3 O2 @. M9 @
Symmetry, 对称9 p2 v. P% q# c2 {! Y* ^! O4 F
Systematic error, 系统误差
" w3 G3 H3 D" tSystematic sampling, 系统抽样! B/ z9 u1 |& Z! u
Tags, 标签
4 q% l+ ]! t! S0 f; u, r5 ]7 O9 H4 NTail area, 尾部面积
% B! k" M* K0 X) W1 Q- nTail length, 尾长
7 x- Q- U: k6 ^; V/ s$ |Tail weight, 尾重
, X& T* c$ b8 H# B6 sTangent line, 切线
" A, j, N' f1 H3 @2 y7 Y) RTarget distribution, 目标分布# W5 ?+ v; r9 ^7 o
Taylor series, 泰勒级数
+ H& c: n- Q: _. VTendency of dispersion, 离散趋势; s# Y6 f. ]# Z* {
Testing of hypotheses, 假设检验& ?$ i j; {8 Q6 Y6 X4 g
Theoretical frequency, 理论频数" q: _' d) j$ Y3 ~3 m( f) \
Time series, 时间序列) W' q; p7 ~# ]7 j- o7 j
Tolerance interval, 容忍区间
% m5 ?" ^6 _* s* iTolerance lower limit, 容忍下限
5 b( o* k( L4 q8 hTolerance upper limit, 容忍上限9 M! y2 j; T: g' X2 I. U
Torsion, 扰率" N r; I2 l' D4 c) C) f2 X5 T
Total sum of square, 总平方和
$ `1 X. y6 M c0 @9 X+ rTotal variation, 总变异
" B/ n) g+ M0 A7 i7 JTransformation, 转换
( a. W3 L( ^- T- d# ATreatment, 处理* g+ f& M% m' b2 t4 r8 M
Trend, 趋势7 H' V: ?6 g, i, J' B+ b& z
Trend of percentage, 百分比趋势+ M1 O: V9 z' r) f8 r
Trial, 试验
8 z0 a6 l" @% P# ~Trial and error method, 试错法
: s6 u k# p% _Tuning constant, 细调常数
6 d; \4 S6 t0 n/ m2 A6 {Two sided test, 双向检验) H* [ Z- I) V( q \% v8 x
Two-stage least squares, 二阶最小平方 \9 U, Z; F0 ^
Two-stage sampling, 二阶段抽样' o( o2 G# N$ ]2 q7 u' u7 Y% s7 t8 r
Two-tailed test, 双侧检验& \( } e& P- ]9 J5 \) t, {1 B
Two-way analysis of variance, 双因素方差分析
2 q; V+ \; i2 { c( ATwo-way table, 双向表
% D# L6 t+ N; \9 A0 M6 a' TType I error, 一类错误/α错误
/ B! v+ k: h1 k! {" F9 J, ?; t( cType II error, 二类错误/β错误5 p- i! e+ l' E* b) ?
UMVU, 方差一致最小无偏估计简称
9 z6 C5 W" j( [( dUnbiased estimate, 无偏估计
& ^" D( C) f2 R) Z* x DUnconstrained nonlinear regression , 无约束非线性回归
7 }! _: \4 E* XUnequal subclass number, 不等次级组含量
3 j$ H: d: X3 Q1 |& TUngrouped data, 不分组资料 z' h2 R3 \& X" z/ G' \
Uniform coordinate, 均匀坐标' o* a/ z+ @" o& `
Uniform distribution, 均匀分布8 f0 o* w! a) d5 P+ o
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
( F$ k0 E6 X7 sUnit, 单元
0 K u+ {) q# k; CUnordered categories, 无序分类
2 \* A4 G k; G6 n9 eUpper limit, 上限
" r* X. T. q$ U# E: G# f! pUpward rank, 升秩
4 T; D" }. }$ _2 K( s/ E8 CVague concept, 模糊概念8 p' q+ G, [% @: k# n8 _" I
Validity, 有效性4 @, T" F) G$ ?
VARCOMP (Variance component estimation), 方差元素估计% n6 \8 u% J2 \; z
Variability, 变异性0 v: z ?8 v% l& q9 h8 a
Variable, 变量
3 A6 a$ h2 p" e! E" n: Y9 cVariance, 方差
o( e" T% |5 b6 WVariation, 变异5 U" C* i; ^" B1 G
Varimax orthogonal rotation, 方差最大正交旋转! |( o, U7 ?# @
Volume of distribution, 容积
5 R* b' D$ v8 b( SW test, W检验1 z* J# Z7 M2 _- f) ^ u6 ?
Weibull distribution, 威布尔分布: c% e: I/ Z6 e: j: K
Weight, 权数
! _5 X! E) p% Y0 l& a8 I; m3 [Weighted Chi-square test, 加权卡方检验/Cochran检验
* d( ]: V7 R% u: c( {1 CWeighted linear regression method, 加权直线回归
, M: A5 r- U! |9 D6 C& B* T: IWeighted mean, 加权平均数3 C3 `5 G, _ R+ \7 M
Weighted mean square, 加权平均方差2 b* L* I9 l2 j" N/ n
Weighted sum of square, 加权平方和& h2 O) D! }+ j6 ~/ ~
Weighting coefficient, 权重系数
) j" Q* g: q# T9 U2 uWeighting method, 加权法 ) U6 z @7 M" _4 Y" e
W-estimation, W估计量- T( D5 e+ O( s" X5 P( p* Q+ o7 t
W-estimation of location, 位置W估计量
" M8 ]: y1 O( X; k9 {) {( zWidth, 宽度
6 s+ p( A, n+ y/ `. d* x+ i2 BWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
! t, a5 K+ b8 ?Wild point, 野点/狂点
& r7 E9 K4 C" g; |* v; U$ x8 fWild value, 野值/狂值
$ z+ K% N& N7 u- w3 yWinsorized mean, 缩尾均值
0 }: ^1 E+ Y& k1 q/ k% C7 pWithdraw, 失访
5 V" q+ L! ~* z% l* nYouden's index, 尤登指数
8 x# A6 x; A* }/ \Z test, Z检验
& l8 e& P# Z4 P* V: @ F' kZero correlation, 零相关
0 T3 C d6 H& f' QZ-transformation, Z变换 |
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