|
|
Absolute deviation, 绝对离差
/ O% I$ n/ i# m/ {" Z7 BAbsolute number, 绝对数, e Q+ ]- B# x. y9 c2 O7 n
Absolute residuals, 绝对残差; l+ W* s. O3 J, ?: E# I, Y3 E
Acceleration array, 加速度立体阵
) U. x+ \* }) f: ~6 v; ]Acceleration in an arbitrary direction, 任意方向上的加速度
- l' }* t D/ T3 o8 C0 LAcceleration normal, 法向加速度
2 _( k& I4 D# XAcceleration space dimension, 加速度空间的维数) B! _: p; m2 O& ~" E
Acceleration tangential, 切向加速度
: i% O9 O4 T( U0 A" S& `Acceleration vector, 加速度向量
( a" [$ }2 v3 r9 a- t' FAcceptable hypothesis, 可接受假设
7 T" l- k: Q! M7 rAccumulation, 累积2 T$ W6 k" V3 `* Q& p2 x( C
Accuracy, 准确度
8 c( t- O$ e l1 Z0 i0 d zActual frequency, 实际频数8 u; z1 V7 f- b! S7 ~
Adaptive estimator, 自适应估计量" n2 g2 {# l( Q9 F- E
Addition, 相加5 J& i; G, ~2 m! ], c3 O0 b8 H, g
Addition theorem, 加法定理9 K5 @9 s% M9 T# Q, b4 S8 L+ l
Additivity, 可加性: G- `) U/ w G, v8 i
Adjusted rate, 调整率8 F: `4 f$ B% d; q% j, x
Adjusted value, 校正值9 S% i) q; h: m& W+ _3 O; Y
Admissible error, 容许误差9 I7 W# R4 m3 Q3 Q9 j2 `; a, q
Aggregation, 聚集性: \& h' R4 g* q( L
Alternative hypothesis, 备择假设
# l3 i% [4 r4 m( \Among groups, 组间5 ]: m! y, t0 d ^4 g( {
Amounts, 总量
* | T% u9 |4 l* i' H0 {2 u9 n2 B) KAnalysis of correlation, 相关分析; E6 s; q. j( i% K5 {3 \
Analysis of covariance, 协方差分析
. w% W' x$ ] fAnalysis of regression, 回归分析9 c9 [6 g; `" I' M
Analysis of time series, 时间序列分析( _* U# u, d( f' a6 n" o, Z: X
Analysis of variance, 方差分析
/ p; e+ J( J) k+ e2 {4 JAngular transformation, 角转换% M+ O) f* B5 i/ D9 u7 w. B
ANOVA （analysis of variance）, 方差分析
% d1 Q2 o9 o' t+ z) }ANOVA Models, 方差分析模型
) c5 i$ e+ U$ G( t9 ]2 xArcing, 弧/弧旋: S* u1 M' m( C+ P3 E3 m- J
Arcsine transformation, 反正弦变换
0 v$ U& R+ p3 _% R. Y- TArea under the curve, 曲线面积# `6 p5 E$ y4 H
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 ' {! U7 {; q: {% Q7 N5 Y- |7 w W3 ]
ARIMA, 季节和非季节性单变量模型的极大似然估计 . E; m: \% j( \( q* |: N( ]
Arithmetic grid paper, 算术格纸$ p/ F! Z9 n$ v4 D2 _& U
Arithmetic mean, 算术平均数* u& Z8 j* j4 | K- p. T4 B6 z# E
Arrhenius relation, 艾恩尼斯关系! F4 w! w1 r& Z' i; J
Assessing fit, 拟合的评估5 u; l: T0 }2 W! w& D
Associative laws, 结合律
7 j; R2 I% a0 e" R4 UAsymmetric distribution, 非对称分布- ^* @/ b- H& E/ G' t3 q9 i2 K
Asymptotic bias, 渐近偏倚
# ^0 \7 |2 ?: @) }) _Asymptotic efficiency, 渐近效率5 d9 o1 @6 U2 V ]# j, p
Asymptotic variance, 渐近方差3 \7 W& A, a9 W, ~5 q
Attributable risk, 归因危险度
# B2 m; ?2 l) m) X" ~# M2 m" _Attribute data, 属性资料; r" u9 o: p# S, ^6 G) l
Attribution, 属性: g) w$ h& i5 u0 m% S1 ~
Autocorrelation, 自相关
/ Z9 ]' @, I7 K! R+ f' h( MAutocorrelation of residuals, 残差的自相关9 j; G* \7 I: ~+ v0 T4 G6 [# V
Average, 平均数: J5 K* {6 v' Q# W/ o
Average confidence interval length, 平均置信区间长度9 O- P; ]$ b) j
Average growth rate, 平均增长率
# e& v1 U0 {# G" H4 E [Bar chart, 条形图3 D! ~# E1 K& s) m
Bar graph, 条形图
3 Z! O' P; V8 N8 U( h7 m% F; XBase period, 基期: P& z4 ~$ [9 e6 s. ~
Bayes' theorem , Bayes定理. Y) W; Z. K% q- @
Bell-shaped curve, 钟形曲线$ b, e$ e. M& h
Bernoulli distribution, 伯努力分布
/ X: R$ g: }9 }' o* yBest-trim estimator, 最好切尾估计量
; f5 E9 @! E' ~& u+ m- G0 w5 d% @( ]Bias, 偏性7 J4 L& V8 T# O8 p) T; P- i
Binary logistic regression, 二元逻辑斯蒂回归
; z$ ]/ A( P& H, j7 Z" KBinomial distribution, 二项分布
) ^' C/ ? K/ c# m H# F# I2 yBisquare, 双平方8 c( c) H3 _& }: w9 K
Bivariate Correlate, 二变量相关" n* g& v% v. \) _: O2 K+ y# {
Bivariate normal distribution, 双变量正态分布& k/ H7 R% m" ?/ S6 M
Bivariate normal population, 双变量正态总体
9 C9 i' e% ?% I7 s$ S; y) \Biweight interval, 双权区间
/ U1 R2 L7 h9 [; FBiweight M-estimator, 双权M估计量7 n, m; m8 U3 W9 \# {
Block, 区组/配伍组+ O0 m( X$ t$ I6 g, @+ _0 a, I
BMDP(Biomedical computer programs), BMDP统计软件包
! a6 k# Z+ A: F' V5 O' MBoxplots, 箱线图/箱尾图
) ?7 V* o9 u* F, X% t. [Breakdown bound, 崩溃界/崩溃点+ g( y* _3 R% @+ L1 u
Canonical correlation, 典型相关) P9 L! g+ V; L$ {1 q
Caption, 纵标目
, {6 A" L( r7 N+ ]! U5 K( w! a- HCase-control study, 病例对照研究
3 s, e5 E3 [( b, \2 W% ACategorical variable, 分类变量
" X2 T9 U% l* KCatenary, 悬链线
7 W! O. W, B5 r# t/ L. _- T* BCauchy distribution, 柯西分布* K7 E+ ]' B% }" ^( \( X; E
Cause-and-effect relationship, 因果关系( C3 ~7 p. E$ X8 y* @& ~. Z
Cell, 单元
+ }9 C) w$ @2 Y4 P" BCensoring, 终检
! ~7 n9 N4 L1 P6 m. s" wCenter of symmetry, 对称中心
0 D G% L0 R% Q9 k" u6 R- L9 |0 RCentering and scaling, 中心化和定标+ k) D! A; q- L$ x
Central tendency, 集中趋势( ]. n7 c$ U) C5 Q1 E: G
Central value, 中心值
n# j9 U; t0 ICHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
# O# T: E, ^; T* T; Z eChance, 机遇. U/ M: w$ w1 ] L8 {( x- E1 s4 M3 I' C
Chance error, 随机误差
; u( _) ^4 d* q+ N0 ^$ o; ?Chance variable, 随机变量0 j; _4 `" |( q# L* t
Characteristic equation, 特征方程: u; F2 u/ T* z! j0 J) w( |
Characteristic root, 特征根, F, e1 B4 o1 f; u! R1 s
Characteristic vector, 特征向量3 A. q. y0 y! T! q& m: C: E
Chebshev criterion of fit, 拟合的切比雪夫准则* n( g/ [& I7 W6 q. }4 Z5 C
Chernoff faces, 切尔诺夫脸谱图) d* w+ E D+ m
Chi-square test, 卡方检验/χ2检验
" c# G4 i, f( `" g ]- ECholeskey decomposition, 乔洛斯基分解
* a, D! J8 t, q( y8 p% v% dCircle chart, 圆图 0 c n* C' Q/ \& d& k; T( q
Class interval, 组距
6 d! @ y( A2 _8 x3 w7 O `" PClass mid-value, 组中值: P+ n. W, T6 }$ @7 K
Class upper limit, 组上限+ I* `# ~5 b7 x6 |# F
Classified variable, 分类变量: g5 J" P1 A; E! T
Cluster analysis, 聚类分析
: a# U7 d: b8 m% pCluster sampling, 整群抽样
& L- T) _2 T, V4 b9 N- M9 W9 PCode, 代码
# W* H/ a$ r- K, ~+ cCoded data, 编码数据
/ C& o+ `/ u u$ BCoding, 编码# l1 B/ j3 s" ~5 Z. _# W
Coefficient of contingency, 列联系数; k. i. o0 { {/ o7 l
Coefficient of determination, 决定系数
& \9 y4 v, x NCoefficient of multiple correlation, 多重相关系数( `" r3 X1 V7 x2 i- x" M( \6 G7 c. x( ^
Coefficient of partial correlation, 偏相关系数5 g$ s/ }+ q% [5 s
Coefficient of production-moment correlation, 积差相关系数
" ]4 [3 N+ d" P8 ?Coefficient of rank correlation, 等级相关系数+ x% |2 o1 }6 d) f5 t& D4 \2 S
Coefficient of regression, 回归系数
! R/ m6 |4 Q$ D- ~3 d5 u2 n, P' Q7 kCoefficient of skewness, 偏度系数
7 [: F; {/ L0 s; |/ P# f) G# OCoefficient of variation, 变异系数
! l- r' ?4 Z$ b3 nCohort study, 队列研究
# c& r. u0 D2 w. @' Z0 ?Column, 列
% h7 A# t' y0 R" oColumn effect, 列效应
. ?6 R, L6 [1 B+ O4 `4 i" ?, gColumn factor, 列因素
W( t* L' h; y" U2 m2 d8 yCombination pool, 合并% D9 w4 \! b: R. n' ?
Combinative table, 组合表+ {6 \+ M6 Y( Y- L2 Q# ~7 w$ f
Common factor, 共性因子
% j8 ]6 ^' j0 B$ x) HCommon regression coefficient, 公共回归系数. |# n- c! h4 ?* P
Common value, 共同值
$ d" m- b! x6 o8 |# |Common variance, 公共方差
$ j$ {7 M; B4 _: |9 jCommon variation, 公共变异
! N( M9 ~' u* P- }/ N) RCommunality variance, 共性方差) }) O9 X l* M6 s6 {" s7 E
Comparability, 可比性0 p3 z3 B9 I [) W* q. R/ ]
Comparison of bathes, 批比较* B7 {1 W6 Y9 p E; J N
Comparison value, 比较值3 [+ M: y7 s0 N' K
Compartment model, 分部模型8 Y: u3 f" X7 W1 X& D+ I
Compassion, 伸缩6 Z% Q1 ?: K @$ w; r6 Z8 m. Y
Complement of an event, 补事件
/ ?+ X* f2 L4 c% zComplete association, 完全正相关
; K+ q. Q$ r" a f( l# E1 xComplete dissociation, 完全不相关
$ L ?: I8 J( c- wComplete statistics, 完备统计量
( {- x' F* N! Z2 Q8 A% U9 ?! aCompletely randomized design, 完全随机化设计
: O! Y3 }' g) P2 JComposite event, 联合事件
5 F4 J4 @- N( T1 t1 n) T) @9 JComposite events, 复合事件/ a% F6 z! S: B7 |
Concavity, 凹性
- \9 ?. R, S" A, o' iConditional expectation, 条件期望 g4 K7 A# T2 D. H5 C2 \
Conditional likelihood, 条件似然
" l8 Y8 h" G* y' q, LConditional probability, 条件概率3 M3 ^8 \, N% r, V9 N! B P A! P
Conditionally linear, 依条件线性: g W- I$ l6 V0 r0 i$ m% K
Confidence interval, 置信区间' F8 i `0 l3 K% g; B3 j+ e
Confidence limit, 置信限
3 d$ @& D( ]2 U. ]+ G5 g" MConfidence lower limit, 置信下限! }: |' n3 b; i: D- ~
Confidence upper limit, 置信上限7 n" M+ _3 W4 t) s' {$ e$ H3 F
Confirmatory Factor Analysis , 验证性因子分析$ _; N, r8 \' d: o. I
Confirmatory research, 证实性实验研究' ^, h N- C U& Q/ s
Confounding factor, 混杂因素
: k1 ]# Q. b: qConjoint, 联合分析
/ w, P, q, [5 c0 }. n/ ^Consistency, 相合性
. `1 q& T: a" h( N- g2 y' {Consistency check, 一致性检验$ o% j! h1 ?' g
Consistent asymptotically normal estimate, 相合渐近正态估计
+ n& u U' o! f& M( x! {Consistent estimate, 相合估计
" d0 p4 g, b4 r* @( yConstrained nonlinear regression, 受约束非线性回归
! h0 |" v% l. c# |% R& \, WConstraint, 约束
|. ~" K: \9 ^$ c% }Contaminated distribution, 污染分布
+ Z2 W% a# S" y( P1 l6 OContaminated Gausssian, 污染高斯分布
7 v8 V, @7 r/ Q! d$ R' C6 E, W" dContaminated normal distribution, 污染正态分布8 i; b# R' k+ I$ K( a# g
Contamination, 污染$ u7 R1 ~* Y7 U: P3 e7 g5 O2 N
Contamination model, 污染模型
7 ?8 v! t# v. h- [ D1 T# ~6 sContingency table, 列联表
/ `7 ]% Q }5 [$ l6 O4 _Contour, 边界线
2 O% s$ I. X2 b! H+ ~Contribution rate, 贡献率 }; `3 E$ _: @# c5 e
Control, 对照
. C. `. N' W' [5 ^3 K7 H' aControlled experiments, 对照实验
* Q8 A% u- u' E( MConventional depth, 常规深度4 J) M7 Q& S$ Y8 ~
Convolution, 卷积
) l5 y( J; @* r+ [5 f7 p3 yCorrected factor, 校正因子/ W5 i9 d) \; t2 _2 r5 Y. r
Corrected mean, 校正均值' l( V. M+ {" g
Correction coefficient, 校正系数: F0 \' r# v( N
Correctness, 正确性
) Z0 `+ T, } P7 N! [( ~Correlation coefficient, 相关系数
& |+ U: Y; W/ e& kCorrelation index, 相关指数+ }1 n2 h$ N7 I. G& K& O# s
Correspondence, 对应
9 w3 u" b; l3 ]; Q9 tCounting, 计数
. h& ]0 Q A& L+ V0 f _Counts, 计数/频数
) I' h6 T$ m; j i! a9 n5 G! x' S( dCovariance, 协方差
2 ?, K6 w6 B2 JCovariant, 共变 $ P1 v) w; E0 S6 m$ i1 S) _! ~
Cox Regression, Cox回归
, G S/ y# B1 o: d0 @9 ^Criteria for fitting, 拟合准则
8 C5 w$ }7 P/ u2 LCriteria of least squares, 最小二乘准则4 }/ \( m: S P2 Y
Critical ratio, 临界比! G( x u" h" N# {. ?! _; ^
Critical region, 拒绝域
3 m$ b4 ]( \1 C/ G3 G2 o' MCritical value, 临界值
5 y0 R/ T) I0 }7 e' v# ZCross-over design, 交叉设计
; ^6 E/ d+ \7 z- j2 o* ~! UCross-section analysis, 横断面分析
9 a) s5 C4 k% a3 D2 TCross-section survey, 横断面调查
" t4 @0 ?* k5 }0 cCrosstabs , 交叉表 ! ?: X+ _9 z' Y6 R, W: k
Cross-tabulation table, 复合表* q) i/ o! o5 f; y2 P
Cube root, 立方根0 X: W8 h; ~6 }3 h
Cumulative distribution function, 分布函数; t6 U+ j `9 i) n
Cumulative probability, 累计概率9 l ?7 ~, U/ k
Curvature, 曲率/弯曲" C1 c3 U# [, w) ~
Curvature, 曲率8 X, l8 h3 ] K
Curve fit , 曲线拟和
: b- x p# F! I% tCurve fitting, 曲线拟合
1 Q* w" M, Y3 d: z! x* gCurvilinear regression, 曲线回归
0 N" E/ O$ s0 y7 }$ zCurvilinear relation, 曲线关系) w) G h% Y" K0 \7 d) P5 _' S. q7 ]
Cut-and-try method, 尝试法5 b/ Z* I5 z5 V8 n# H
Cycle, 周期
7 o. B4 k" J% \* s' e. p7 S) d& o$ hCyclist, 周期性
' p+ b. ^7 ^0 w& o" I- R {, oD test, D检验
" \6 {3 ~2 Y3 ^) [3 ?Data acquisition, 资料收集
% B- k" i3 w5 E5 S! SData bank, 数据库7 {- s, e! d8 L+ g6 D) D/ B
Data capacity, 数据容量
' d% W; S) ] F7 ~* d' a. sData deficiencies, 数据缺乏
# x3 R- S8 V# Y! W2 q9 NData handling, 数据处理
% H! F; x3 ?, x7 Y! U% t4 |Data manipulation, 数据处理- w7 \4 e0 e5 x. Z' ?9 {9 v
Data processing, 数据处理
& D4 h% x! S" {1 J w, a& xData reduction, 数据缩减1 `( ~8 u+ F [* a
Data set, 数据集& e3 p3 Q3 K: A& D0 |( {8 G- n/ b
Data sources, 数据来源# @* U9 n7 i0 L2 A
Data transformation, 数据变换0 t; V6 _; [1 J% B9 ^- l3 P& {4 N
Data validity, 数据有效性0 o2 F8 B3 H" V
Data-in, 数据输入: `/ v/ m. Z- q
Data-out, 数据输出# L8 b; H3 p) i
Dead time, 停滞期
' B/ M% e- G( \Degree of freedom, 自由度
, Z( I; o2 n* p E# \2 v5 B6 J% MDegree of precision, 精密度
8 D, y" u9 n% ?: C$ o; `Degree of reliability, 可靠性程度
0 L6 I5 N' l" u7 U- VDegression, 递减
: F9 N% U K% L% @3 `9 ~( Y( h' NDensity function, 密度函数
4 l1 ?9 F& x, s* O" S I/ ~Density of data points, 数据点的密度# g: x4 M; b/ s0 R c
Dependent variable, 应变量/依变量/因变量 s. D/ S0 v4 O6 o7 o' a
Dependent variable, 因变量# F9 c4 r! u; y5 y
Depth, 深度
/ @4 g4 \1 S0 X% hDerivative matrix, 导数矩阵# x! E Y- b& H, m; x
Derivative-free methods, 无导数方法
6 T3 i% ?7 e% l P* n& J( pDesign, 设计
, i# w$ d2 K2 u) a" cDeterminacy, 确定性
; G! j, K6 z# NDeterminant, 行列式
v+ N2 K/ }9 `; b7 I* Y! ADeterminant, 决定因素
, n- F6 }5 |( EDeviation, 离差
# d* F1 y. J0 {% U, FDeviation from average, 离均差3 T/ T$ ~ Q; Q3 O
Diagnostic plot, 诊断图
/ B+ Q8 C+ c3 y% P$ Z X& `Dichotomous variable, 二分变量& `/ m5 W2 Y ~+ P' j l8 x
Differential equation, 微分方程
! ]6 t S; i1 cDirect standardization, 直接标准化法- Y. C0 }# V t' f3 q
Discrete variable, 离散型变量( s7 a# U* b* N- r V
DISCRIMINANT, 判断 3 H; z5 I' u5 }) G/ V( _7 r
Discriminant analysis, 判别分析5 O# a2 j. C& O/ X. k* C
Discriminant coefficient, 判别系数
8 e+ e& R6 H6 v/ H& T: [Discriminant function, 判别值
% h& K4 L \7 G6 M- g; sDispersion, 散布/分散度
8 z1 T% g+ U @- yDisproportional, 不成比例的2 l# }; g7 l Z- ~/ j% e
Disproportionate sub-class numbers, 不成比例次级组含量
+ Z& O- N: X8 b* ~: iDistribution free, 分布无关性/免分布
; {; |, T0 s3 \4 H( r4 ~. l7 hDistribution shape, 分布形状$ Z: G7 {- ?, H% }8 e+ w/ g0 W
Distribution-free method, 任意分布法
6 v6 W& t5 t5 d4 }7 L) hDistributive laws, 分配律
4 }$ b2 O1 B7 V/ |8 M, X% `Disturbance, 随机扰动项
/ Z1 l7 M, c5 m: A; PDose response curve, 剂量反应曲线& D0 ~1 s% [6 k. {" q; h
Double blind method, 双盲法
) r$ {$ T" ]4 w) z) r& e0 h, \Double blind trial, 双盲试验
' v. \! W2 g% _' _* v; {: ?* ?Double exponential distribution, 双指数分布2 ?1 J [4 r. V. r
Double logarithmic, 双对数
8 R% J1 N5 j/ E( UDownward rank, 降秩7 @+ H* l; ]. x- b( U. ]
Dual-space plot, 对偶空间图
* ?9 X& N0 H+ V8 z; bDUD, 无导数方法2 r: J3 `) A) `9 s% J+ p- ^
Duncan's new multiple range method, 新复极差法/Duncan新法 f, X) A i5 @$ Y3 d9 T8 B
Effect, 实验效应
: b- v) b6 U0 R) R bEigenvalue, 特征值
# W& K5 C, _. b& t5 dEigenvector, 特征向量
1 ?% w- w" }$ ^+ i3 f0 sEllipse, 椭圆
# Q1 u+ B5 K dEmpirical distribution, 经验分布! H7 _' X2 g' b; ?
Empirical probability, 经验概率单位
/ {. d3 e9 s7 W* \Enumeration data, 计数资料
$ D f( Q. M& N; _/ Z0 zEqual sun-class number, 相等次级组含量% j3 W9 W+ V9 X% p( O; b
Equally likely, 等可能! }+ n6 m ^& n9 @* J
Equivariance, 同变性
6 I0 y, r$ u1 @1 r9 qError, 误差/错误5 X+ z# r: D3 @7 K+ S" i/ }: X
Error of estimate, 估计误差) r5 v; d4 t) U$ m! {4 @0 ~& U
Error type I, 第一类错误9 B4 M& N$ Z. _2 V$ s' x
Error type II, 第二类错误0 `- Q3 Y/ w1 k5 _9 k
Estimand, 被估量0 q; a3 c! m& n7 v
Estimated error mean squares, 估计误差均方
/ X0 |2 Z, m4 z& v) ?/ R% ^) lEstimated error sum of squares, 估计误差平方和
. G1 `3 V" R1 y! }' oEuclidean distance, 欧式距离$ ?' y I# q3 ~: H# R
Event, 事件
7 ^* I) t9 v8 C) REvent, 事件* g! p7 V% K6 }0 h
Exceptional data point, 异常数据点
* m0 P- x# Q9 z; sExpectation plane, 期望平面
) w7 l |2 K" L. q, Y5 \) bExpectation surface, 期望曲面" C1 m( j: ]& \ Q4 m3 y
Expected values, 期望值" B! A# R E0 z. P& q2 b9 r
Experiment, 实验' s) `( x1 w8 z" }$ p
Experimental sampling, 试验抽样# a1 ]7 q8 {' f6 J, b
Experimental unit, 试验单位
% K2 f& T4 y; |Explanatory variable, 说明变量
- X/ z5 z6 {5 e yExploratory data analysis, 探索性数据分析7 w$ h$ l% T2 n# a* S) a# L
Explore Summarize, 探索-摘要
( P* |$ r% ?3 j2 W& g. J- aExponential curve, 指数曲线9 A. ]2 L! m& ?4 Z3 D( `
Exponential growth, 指数式增长
$ o, \3 N9 _, h! H* ~6 REXSMOOTH, 指数平滑方法 - j, F5 k0 F$ O! z. D3 |: F0 ^5 I+ r/ h- Z
Extended fit, 扩充拟合! Y$ _! v5 K; C
Extra parameter, 附加参数
1 X% Q: i$ ^% ]( e2 g MExtrapolation, 外推法7 ^1 I1 Z, D2 {! d' F
Extreme observation, 末端观测值
& r$ W; R, \( t! qExtremes, 极端值/极值3 N& f# f. {( _6 w" H4 W# L* b% Z
F distribution, F分布4 {# J' ]) |3 P3 Q! [# T
F test, F检验
7 R4 |* K$ ]& r$ j: Q) X$ XFactor, 因素/因子
. A% b4 R$ H* K( m) z7 \9 v% @& [. uFactor analysis, 因子分析' v. B8 a- l$ J- H
Factor Analysis, 因子分析' M' [- u5 a/ Z. {* I) P7 _" J
Factor score, 因子得分
6 q- F: j1 S0 Q E1 sFactorial, 阶乘
9 |5 r/ [# r, g: k6 w3 _Factorial design, 析因试验设计
; ^) E9 T( z R4 s g' q5 ~0 ~2 lFalse negative, 假阴性
# {8 c, a5 [6 _$ P0 r3 wFalse negative error, 假阴性错误8 X# S% o1 y; ~1 [1 q
Family of distributions, 分布族
# S5 H- ~8 F7 iFamily of estimators, 估计量族' }! n, V% v; l: g
Fanning, 扇面 W4 ?0 y8 Z* u% d. i/ s* T& J
Fatality rate, 病死率' D g3 `, ^, K6 t1 g9 M6 D
Field investigation, 现场调查7 P+ R+ a H1 p: x- Z/ H" J( I
Field survey, 现场调查1 ^6 C6 N/ W( r) c
Finite population, 有限总体
& L& j: d6 _4 v* B |7 A0 K: CFinite-sample, 有限样本2 Q6 v7 z" ]9 \/ f s" ^& \
First derivative, 一阶导数
: j9 H% z, S, @7 BFirst principal component, 第一主成分
* M8 n- ], P4 ?& `4 B- Y5 P6 l6 vFirst quartile, 第一四分位数
$ g/ F7 V! W' }4 B+ W5 m4 nFisher information, 费雪信息量
2 ?/ a* P6 B: b1 l5 W% Z7 j2 `; IFitted value, 拟合值
2 s* p- _- m/ h) j A8 S+ J/ jFitting a curve, 曲线拟合' |8 _3 J6 a" _. _( P
Fixed base, 定基& t6 L5 i% F- m; K+ x% ?% p
Fluctuation, 随机起伏- s; J( V! d7 y3 L2 \6 j
Forecast, 预测) N& _. M9 q. x, K; b. Z# h+ n$ T
Four fold table, 四格表
6 {2 m& O- m/ M6 K/ u, H- f, ?) DFourth, 四分点$ p Z* m, u4 H2 [" u
Fraction blow, 左侧比率
# \& V2 T" ~8 J! B$ G% X. ^Fractional error, 相对误差
1 E/ o8 e3 Y7 f, [- O5 OFrequency, 频率4 \2 y1 B9 z5 P' Z" o( o
Frequency polygon, 频数多边图7 \8 Y/ L% I5 y; i' P8 s
Frontier point, 界限点
& A0 T- s1 u( U2 U# F7 ]Function relationship, 泛函关系
( _. N& \& A3 E0 ] R, q) _! S( Z# WGamma distribution, 伽玛分布
d1 g' C8 k1 S. EGauss increment, 高斯增量5 ~# I8 w: \& X
Gaussian distribution, 高斯分布/正态分布
( _ y$ X2 n K6 e1 o. r. mGauss-Newton increment, 高斯-牛顿增量 C/ g2 F; t5 M1 l* C
General census, 全面普查/ ^8 \2 n% q+ k# F, y
GENLOG (Generalized liner models), 广义线性模型 + \! I7 Z! i0 b! P B M( G
Geometric mean, 几何平均数
7 H6 i# Y, q- V- o f2 R3 \Gini's mean difference, 基尼均差
0 S$ M T0 h" E9 m( hGLM (General liner models), 一般线性模型 & Z% m) x& `) o' C) l
Goodness of fit, 拟和优度/配合度3 ?2 i: `& L, q; B( u
Gradient of determinant, 行列式的梯度
n. v o& K$ F* |. ]+ v9 yGraeco-Latin square, 希腊拉丁方) t$ C, I* i+ X+ X& F( p
Grand mean, 总均值) j' N/ y: u* V! i1 b, h
Gross errors, 重大错误9 B, G! J, p3 o# G+ f
Gross-error sensitivity, 大错敏感度: s; v% ^5 L0 j' e2 j) f9 e
Group averages, 分组平均
1 Y% a! E/ L3 g3 CGrouped data, 分组资料
' p, Y o) U( K, O* C; rGuessed mean, 假定平均数
: J3 q9 _* A+ h' T) E8 LHalf-life, 半衰期$ K. o+ \+ P% ]8 c/ ]4 s$ v. j
Hampel M-estimators, 汉佩尔M估计量
+ L! R i- P9 G0 d( g6 a* CHappenstance, 偶然事件
7 u3 T% O0 }) A( o# x+ eHarmonic mean, 调和均数0 o1 D8 N4 C- @; B6 J4 u& P
Hazard function, 风险均数* m9 ~ a: D! y# K
Hazard rate, 风险率
/ q$ y, P1 W' c9 U: V; B" n$ I2 PHeading, 标目 5 B$ }8 N& w1 R5 a! i7 x
Heavy-tailed distribution, 重尾分布8 Y% \ E4 V2 l! U# g% @
Hessian array, 海森立体阵4 u* Z1 r# B6 L' u
Heterogeneity, 不同质, \1 i/ _9 A7 L) h
Heterogeneity of variance, 方差不齐 + j3 Z# R$ H9 p B/ k7 c0 l
Hierarchical classification, 组内分组
; g& a- I* `. M, D0 ?% vHierarchical clustering method, 系统聚类法
& ^% ~1 J5 F/ M" a7 dHigh-leverage point, 高杠杆率点+ C* R: S5 n1 W% I8 R
HILOGLINEAR, 多维列联表的层次对数线性模型
' `0 \) u' [4 C& UHinge, 折叶点
2 R# A- z& ]. E( @: XHistogram, 直方图
! o+ A; r# g/ _8 Q8 FHistorical cohort study, 历史性队列研究 & `6 \9 S3 o7 |' {& l8 \. a
Holes, 空洞0 b& a: d; y. w% u
HOMALS, 多重响应分析, [1 w& @1 e2 ^2 k" ?
Homogeneity of variance, 方差齐性; t% S6 l5 v, j
Homogeneity test, 齐性检验
0 H* n' Y Q4 j' q$ NHuber M-estimators, 休伯M估计量: Z- E2 D c: c! T: h+ r( ]
Hyperbola, 双曲线 x U! g- D2 w+ C! V2 |0 e
Hypothesis testing, 假设检验+ E5 R( h! F1 x/ f' f+ Q v. c
Hypothetical universe, 假设总体
% K1 A. g; ?3 @$ lImpossible event, 不可能事件
# k b! {, z$ {0 Z( iIndependence, 独立性- W% {0 r- t/ y' g
Independent variable, 自变量
, \. z, }3 }' i6 Q! C- D; y+ bIndex, 指标/指数5 Q- G/ U' Q. h8 d
Indirect standardization, 间接标准化法
( ~% } _' Z) u% n7 s' F0 X, LIndividual, 个体1 @" X, _1 `4 _
Inference band, 推断带, \; K4 |- t# B. B5 Z9 h6 v
Infinite population, 无限总体2 h) o) g9 I. |! c
Infinitely great, 无穷大5 o; f" V+ e4 F5 k. q( g! x
Infinitely small, 无穷小7 Q+ \& n; @& f* M
Influence curve, 影响曲线5 z5 i7 N4 D* g H
Information capacity, 信息容量- y2 b5 C. G3 I6 ~' G9 k! R
Initial condition, 初始条件
& k6 k# f; Y) `1 Q pInitial estimate, 初始估计值
* m5 s$ ~- A2 F9 `' l& l9 n# FInitial level, 最初水平
2 }1 f; B1 ?9 K5 p$ F& E$ eInteraction, 交互作用
; u( S5 f* u( K1 Y! nInteraction terms, 交互作用项
- c& K% X+ i5 G" rIntercept, 截距1 y$ L$ U" e4 {6 A# F& Q1 n" G
Interpolation, 内插法
, ]# {6 H9 \+ TInterquartile range, 四分位距
$ z% J* ]" h1 r0 H: V/ K5 MInterval estimation, 区间估计$ D9 h7 @/ k, W
Intervals of equal probability, 等概率区间! I& Z5 @0 |2 [/ h7 K" A
Intrinsic curvature, 固有曲率
& }" x5 K+ T. J# n# [Invariance, 不变性
$ @, W! o" f; LInverse matrix, 逆矩阵; L% J% A4 y( C9 n: I+ e% u8 ^
Inverse probability, 逆概率
; o3 U9 N" e9 L& |; {Inverse sine transformation, 反正弦变换
% T5 Z" ?) F7 W( w9 r- F' {Iteration, 迭代 2 ]0 M9 f& m+ N- O) V7 o
Jacobian determinant, 雅可比行列式9 E4 Y! @3 y3 X# _
Joint distribution function, 分布函数
5 n7 i5 F9 Z. W5 s- ]; ]% ?7 [3 {Joint probability, 联合概率: b" q% ]) g+ a
Joint probability distribution, 联合概率分布
6 _$ Y# a; _$ v# h7 P+ k: zK means method, 逐步聚类法. m" l! q( m2 u8 d- ^% |
Kaplan-Meier, 评估事件的时间长度
# H" q5 c+ j7 SKaplan-Merier chart, Kaplan-Merier图
: m3 t2 P- w1 w) KKendall's rank correlation, Kendall等级相关
) |; [& a, Q* p' B0 xKinetic, 动力学
8 w/ v$ w: i2 G; b( N" v" LKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
: i* ~( k3 t* V% x* FKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验" s* }8 v) |1 m, q. S! S0 B3 \
Kurtosis, 峰度
8 k, Y8 n! m; B/ KLack of fit, 失拟
& I1 l4 Z! D" q& {Ladder of powers, 幂阶梯$ G3 X2 Z/ X' n% W
Lag, 滞后
( r+ |8 i* y6 b' p& NLarge sample, 大样本* f0 h* K, Z8 i3 F
Large sample test, 大样本检验
1 v* l) K" k. D, {- DLatin square, 拉丁方4 Q7 k; d7 x' M- {
Latin square design, 拉丁方设计
, _/ q1 R- _# I9 n/ w1 kLeakage, 泄漏
! l5 h% R& \5 Z3 O- yLeast favorable configuration, 最不利构形- q$ L3 S4 [: w# I; p4 j8 B, w
Least favorable distribution, 最不利分布 N" a2 A' S- k0 f
Least significant difference, 最小显著差法9 {) E8 p* e. Y
Least square method, 最小二乘法7 \* ^5 C3 D* u! A( U! N3 o& h; d
Least-absolute-residuals estimates, 最小绝对残差估计
4 |' t7 l0 m, N1 l( k5 MLeast-absolute-residuals fit, 最小绝对残差拟合8 |4 A8 o0 k) G1 B: v: w9 ?
Least-absolute-residuals line, 最小绝对残差线
, _5 c) C% I* ^5 Z4 H- RLegend, 图例
# x$ N' O( [, R0 z' sL-estimator, L估计量
6 G% _+ |4 a* F' ~8 l6 c; s! q! iL-estimator of location, 位置L估计量
D" l7 y1 M$ mL-estimator of scale, 尺度L估计量- J. {" g2 {% U j, Q3 T
Level, 水平
# B3 A \7 s+ NLife expectance, 预期期望寿命9 n' c2 R! e5 ~6 @! s
Life table, 寿命表
1 Q9 P& P. G5 o: CLife table method, 生命表法3 C: O0 x( T4 T+ Q# ~
Light-tailed distribution, 轻尾分布: e. S1 F ]9 a8 ?: x/ j. }
Likelihood function, 似然函数
. \8 [4 z- U4 ^9 l- fLikelihood ratio, 似然比: o' z$ O2 z, B0 @3 x
line graph, 线图/ X- b& u9 M: \( |/ d* o
Linear correlation, 直线相关
: N3 U8 A# D {7 U: R* \Linear equation, 线性方程& s; }( L/ W5 q$ K8 G9 m/ c
Linear programming, 线性规划; c( `$ F9 z) ^) ~3 H
Linear regression, 直线回归4 a: n: ^8 G; R) J; l2 [9 J
Linear Regression, 线性回归
" B9 @) V2 h3 @9 i7 t9 _Linear trend, 线性趋势
# E/ s6 a4 l; ]% nLoading, 载荷
0 B4 p0 @) S2 b* b* q0 O" VLocation and scale equivariance, 位置尺度同变性1 z" z0 n' J# y
Location equivariance, 位置同变性
- P3 c6 p% C: z% p) `Location invariance, 位置不变性% }$ `. q5 \4 w: ]6 p$ G5 y) J& u
Location scale family, 位置尺度族
' D" R' D9 e# e7 @$ vLog rank test, 时序检验 & i9 D. O) w5 I6 Y# y" N" _* |
Logarithmic curve, 对数曲线; M' L% J. B3 Q7 o! @- l8 K
Logarithmic normal distribution, 对数正态分布
9 m3 I0 |8 D$ V1 FLogarithmic scale, 对数尺度/ \0 P2 u7 F1 \1 Q& S2 q
Logarithmic transformation, 对数变换
" `3 t9 B* ~, Z, \ CLogic check, 逻辑检查
P9 ~; k1 S2 t* o- v! R0 dLogistic distribution, 逻辑斯特分布
7 e! g# Y6 [2 T0 L/ r$ TLogit transformation, Logit转换8 v3 U& T. Q* c0 ^: t5 k1 J7 ?
LOGLINEAR, 多维列联表通用模型
. ^, H9 |) G( w! mLognormal distribution, 对数正态分布
4 v0 j, e' c1 m' r9 A r1 D! CLost function, 损失函数
0 y& s6 G6 C: z3 g, C8 uLow correlation, 低度相关
) ^5 b( k! V1 d' p2 {$ D# SLower limit, 下限' @1 E7 J7 t! U* j$ L9 u
Lowest-attained variance, 最小可达方差
/ p: s' t& z/ q% XLSD, 最小显著差法的简称
0 {' i. C9 R& lLurking variable, 潜在变量
8 Z+ f0 y1 P1 n: f3 a/ X" m, {5 lMain effect, 主效应
& X% v2 b+ p+ [! bMajor heading, 主辞标目: }7 e: g; h, F) X
Marginal density function, 边缘密度函数
% [' h$ `& r, Z( E7 mMarginal probability, 边缘概率
5 b/ A7 u, D6 M1 ]2 dMarginal probability distribution, 边缘概率分布
( e, t( P% F2 E3 g+ Y6 QMatched data, 配对资料
% _ Z( c9 L" p) OMatched distribution, 匹配过分布
, s' [5 H! v& A* } H L, dMatching of distribution, 分布的匹配
2 o3 d. i: m: j) v. V1 p" X4 aMatching of transformation, 变换的匹配
, f d. t( e& ~, o: W8 E5 }% AMathematical expectation, 数学期望2 ~. }- g7 C. f" x& u I% ^$ F
Mathematical model, 数学模型+ v* O5 `7 _: g: W( Q0 Q' f
Maximum L-estimator, 极大极小L 估计量+ G* m4 l9 \, G9 L
Maximum likelihood method, 最大似然法% t/ y* R# G+ u. k7 X# a& z v
Mean, 均数! k5 d4 D9 m) {/ d
Mean squares between groups, 组间均方
5 e+ b1 h" p* ]% _& {( VMean squares within group, 组内均方, m- c% H L, X" U
Means (Compare means), 均值-均值比较
) h2 ]& p4 c8 c. V, h! [Median, 中位数
! E7 ]' j7 U2 B* ~) ], gMedian effective dose, 半数效量* w8 ], u% B4 p3 |! Y5 C& K
Median lethal dose, 半数致死量
6 e. ]; g3 S+ X7 Y6 OMedian polish, 中位数平滑+ H- B2 |. O$ D. T* O3 W' b( j0 ^' Z
Median test, 中位数检验
3 ~/ Q) i) Q) U" x; NMinimal sufficient statistic, 最小充分统计量
, p P1 R+ A# t. N& A" CMinimum distance estimation, 最小距离估计
& S* u) z! I+ eMinimum effective dose, 最小有效量% D5 c7 A# W; m! r4 j) Z% x
Minimum lethal dose, 最小致死量1 G2 K, R3 \ k& P
Minimum variance estimator, 最小方差估计量
/ }3 ?! _1 Z' c8 k) X5 F& ^; r4 \9 qMINITAB, 统计软件包3 c0 R) ~! `( e+ S% u' j
Minor heading, 宾词标目
& e% r! ?& I2 j) pMissing data, 缺失值
$ ?9 Z9 Z2 g5 o& j! Q# i9 \+ RModel specification, 模型的确定
z. w- O4 I6 c8 k6 }Modeling Statistics , 模型统计
. r) D" Q, Q: U& bModels for outliers, 离群值模型
+ o! H" A" [& i5 w+ N" {* n) GModifying the model, 模型的修正) D4 ^. m: _4 L; |: e
Modulus of continuity, 连续性模( ], \( M- G: i3 ?/ Y
Morbidity, 发病率 ; w2 G5 c% j/ [+ _# R# w
Most favorable configuration, 最有利构形
0 K/ J4 I5 L3 u. q! }4 v, A% OMultidimensional Scaling (ASCAL), 多维尺度/多维标度& I. ~' K+ m3 n! Z! ~
Multinomial Logistic Regression , 多项逻辑斯蒂回归
/ U8 O# I( a" [# UMultiple comparison, 多重比较
8 z% o: v% W! _8 v& g6 _Multiple correlation , 复相关; R6 s+ G4 L' J z5 k: S; q# Z
Multiple covariance, 多元协方差& O- l1 J3 \, e& i$ d" [: A o
Multiple linear regression, 多元线性回归. a& D4 T0 @9 w
Multiple response , 多重选项7 C4 t) j d% D; ^
Multiple solutions, 多解: t8 t8 d U8 ^2 k4 a
Multiplication theorem, 乘法定理; B! @* }8 Y; h: x+ n% B
Multiresponse, 多元响应
: s9 D5 j8 l5 zMulti-stage sampling, 多阶段抽样
- ^, [' \* ?1 t% `) \" \Multivariate T distribution, 多元T分布
$ J9 Y% `$ r( G- gMutual exclusive, 互不相容
2 J1 C, r3 a+ j0 g/ hMutual independence, 互相独立
7 _+ d3 l' w) e5 u& d- UNatural boundary, 自然边界" c1 \' H) W2 v7 h4 Y, h! n
Natural dead, 自然死亡
' z A3 y {. \2 `0 N- D' |" qNatural zero, 自然零
3 ]0 L% h6 w8 z2 i$ i( D) ONegative correlation, 负相关
" P+ u7 E, n4 @' _6 vNegative linear correlation, 负线性相关. ~! [# X5 m( M4 G4 k9 ?0 q. a
Negatively skewed, 负偏1 a* g5 \4 `( Y6 `9 n% D9 {$ f
Newman-Keuls method, q检验
# }& i$ X. L$ f8 R, K; J; vNK method, q检验
/ X' [/ _& G2 s4 k6 a5 i/ ?No statistical significance, 无统计意义
7 W/ i1 \( l1 Q7 q2 ?Nominal variable, 名义变量
. R$ {" z4 A9 Z6 t, pNonconstancy of variability, 变异的非定常性( [- W& V. N9 \/ K
Nonlinear regression, 非线性相关& g2 b! D: q! \- h& ~, t2 J1 O( u
Nonparametric statistics, 非参数统计
3 W7 f1 ]8 ^+ ]6 p8 r+ Z: s y+ ?Nonparametric test, 非参数检验6 H; I2 c3 I/ h' ~' e$ {* `- _# i
Nonparametric tests, 非参数检验4 F' O5 z3 @. N
Normal deviate, 正态离差" k- B5 k* I. E% ?
Normal distribution, 正态分布
2 s: a$ [" q6 F9 d0 `" tNormal equation, 正规方程组4 k9 X/ l1 T- |6 X
Normal ranges, 正常范围
& A$ [: _. Y# E5 r% R) |Normal value, 正常值
9 n5 t8 L8 J: gNuisance parameter, 多余参数/讨厌参数9 Z( b' Z, n ]' H
Null hypothesis, 无效假设
" I b& c6 L% C5 ?2 t2 N3 MNumerical variable, 数值变量# I: e: _, m6 o& Q( g9 b- x% F& Q7 h
Objective function, 目标函数$ H9 G. a- u8 L; h$ W, Q5 O) y+ n
Observation unit, 观察单位
' t% W- b6 x2 U! f- XObserved value, 观察值' R$ z3 j9 t9 f) \# Y J$ ^9 {
One sided test, 单侧检验/ B5 q( D3 L% V. s& i, p3 ]& p" b
One-way analysis of variance, 单因素方差分析* Q' l' ]9 c! \# Q
Oneway ANOVA , 单因素方差分析
' v; B* b8 a$ @Open sequential trial, 开放型序贯设计
, |/ v s: F( ^# TOptrim, 优切尾3 {/ N* b) W- w" d7 v, p
Optrim efficiency, 优切尾效率1 S: M; b, w, p& }
Order statistics, 顺序统计量( A2 D. Q0 w2 A9 T7 k6 r% P
Ordered categories, 有序分类
& c& x2 R/ G6 pOrdinal logistic regression , 序数逻辑斯蒂回归4 o0 R' U9 K2 J9 r9 `
Ordinal variable, 有序变量9 B$ p: r; z# n' m+ c) e
Orthogonal basis, 正交基' Y, `" A0 Q" c4 u
Orthogonal design, 正交试验设计
; I1 p+ ^, H6 y0 AOrthogonality conditions, 正交条件, M( F5 [% [) f% r- G
ORTHOPLAN, 正交设计
9 |0 y! T! [! [2 M& H4 e8 y8 BOutlier cutoffs, 离群值截断点
; N# J3 S& T% ]1 M- Z( I9 S; xOutliers, 极端值
2 W/ A/ m0 g2 M% tOVERALS , 多组变量的非线性正规相关 4 F) G, v, T# n' u
Overshoot, 迭代过度
! {! w1 {! h) o( i( |8 j% A0 nPaired design, 配对设计) }' t. q. {! C# P; K- x
Paired sample, 配对样本
( D, c' A' q& ^: N# XPairwise slopes, 成对斜率; l- x4 J% N$ G% Z- e( p g6 s2 r
Parabola, 抛物线
; K* x; X1 Z) O1 A3 BParallel tests, 平行试验
}8 F! {$ l# ^0 u9 bParameter, 参数' R3 L5 q, S2 q5 D3 _
Parametric statistics, 参数统计
2 l7 Z1 C" l+ v* H% d0 W' gParametric test, 参数检验; j3 t" ~6 J T! `
Partial correlation, 偏相关
5 a9 n9 x* `$ Z9 @4 N3 C2 nPartial regression, 偏回归
! o" m# u9 ~; S! BPartial sorting, 偏排序
8 I1 x5 u) s1 P3 E% T$ E/ EPartials residuals, 偏残差
. e; f# D1 q k: z% A( ZPattern, 模式5 N5 u5 H6 \$ [4 p
Pearson curves, 皮尔逊曲线- w5 k3 }" K. U# ~/ G7 d
Peeling, 退层
$ h; }* Q$ U4 V Y( U. A) s0 EPercent bar graph, 百分条形图
# M8 Z: `! K. Y9 A/ Z( xPercentage, 百分比4 H, ^+ l7 ~/ d- ?6 x5 x/ Y1 _
Percentile, 百分位数
; p) @$ L7 e" M) b4 g3 x2 c8 oPercentile curves, 百分位曲线, I8 I3 r* c1 b5 }1 d; ~! P
Periodicity, 周期性
8 x# Y' j* E3 t, IPermutation, 排列
; n+ ~+ i6 O: K' M& G6 oP-estimator, P估计量
2 j& a R! z, ?" U* F+ `6 g% KPie graph, 饼图9 @# p% h% @) ~* Z, N% E
Pitman estimator, 皮特曼估计量& d& _" {- w9 m" n9 R. T/ O8 F Z2 \
Pivot, 枢轴量
L4 X% r' H1 O( w2 O$ yPlanar, 平坦
, F D# M6 p. lPlanar assumption, 平面的假设
: t" ^. A( C; Y6 q5 Z$ S' k NPLANCARDS, 生成试验的计划卡1 \2 @' d* p* o& i
Point estimation, 点估计3 s+ h+ ^' W$ O9 ?+ C: s" e
Poisson distribution, 泊松分布4 i; a$ H! O7 p: M: L
Polishing, 平滑 h/ U- S* p+ s; g9 T$ c+ U3 \% d
Polled standard deviation, 合并标准差. y' e N6 g) Y, t! N( I' O
Polled variance, 合并方差 K- C# _1 `* U
Polygon, 多边图2 A# V$ C; ]1 }
Polynomial, 多项式/ v3 T# I1 \; i* {, V, n0 M8 _
Polynomial curve, 多项式曲线
. M$ g0 I9 W7 J" t0 m1 tPopulation, 总体
V5 n" U/ J& ePopulation attributable risk, 人群归因危险度
' J: k/ x. }. X% y4 |6 P- W/ p* ^Positive correlation, 正相关
( |) E2 I- i6 u! A0 ZPositively skewed, 正偏! V" k7 Q1 @/ y1 l% r1 u
Posterior distribution, 后验分布 c+ c, X# l+ V1 }7 {) K+ C5 o
Power of a test, 检验效能; _$ c3 W) B, h G9 [+ `6 y
Precision, 精密度: s: X @* {4 R+ D
Predicted value, 预测值$ M! A3 V3 I Y2 n$ }4 C
Preliminary analysis, 预备性分析
6 N- \6 X( e! W( Y3 @' z2 i, \Principal component analysis, 主成分分析0 ]4 j& e2 K7 d. G) w* @
Prior distribution, 先验分布
0 ^' B1 }+ ?5 p& ^3 e; v/ WPrior probability, 先验概率! u/ m4 n# g! B6 O+ g
Probabilistic model, 概率模型: d$ l' R% Y6 D' ~# A- s
probability, 概率
% K N/ b: E5 o$ G( C6 K+ d+ UProbability density, 概率密度
$ E) k' v4 l7 z2 `2 W+ AProduct moment, 乘积矩/协方差7 {5 ^/ t* C1 Z7 D% q1 ]) d
Profile trace, 截面迹图' k0 Z2 w! r: m1 q
Proportion, 比/构成比
8 |* y- e" H+ K* kProportion allocation in stratified random sampling, 按比例分层随机抽样
5 m" O' W7 M( N% I/ T( {Proportionate, 成比例
0 x: [: W0 H5 ^; {1 B$ ^# g: c& wProportionate sub-class numbers, 成比例次级组含量/ t; D* N# E! z/ `) o6 _, P
Prospective study, 前瞻性调查
4 ^7 v/ ?8 h. B0 QProximities, 亲近性
$ v/ U( t; s; V1 {Pseudo F test, 近似F检验
* j G: F- ^# b, k) x2 s5 d3 WPseudo model, 近似模型; {4 I/ r# n" z
Pseudosigma, 伪标准差- [5 F$ q6 U7 ?
Purposive sampling, 有目的抽样( y7 Q _$ c" I3 I5 H& O
QR decomposition, QR分解
: {% ]5 A0 z+ _* ]. IQuadratic approximation, 二次近似8 b: m* x- R; @( { f8 t
Qualitative classification, 属性分类
' F; L1 j" B2 x, G% Q- [$ YQualitative method, 定性方法$ i( M* r9 k) B6 S
Quantile-quantile plot, 分位数-分位数图/Q-Q图7 y( u" U! s- {# |* k
Quantitative analysis, 定量分析1 k1 f }& u& P( K
Quartile, 四分位数
: y4 D3 W( _4 X0 _0 X8 g+ ?) _Quick Cluster, 快速聚类
0 S4 J1 m, z6 u; T, J0 MRadix sort, 基数排序) ]0 {+ ]+ \# b l
Random allocation, 随机化分组
4 P5 a6 s4 [% f( y% |- y/ ^Random blocks design, 随机区组设计1 X* @8 r1 t- H+ j
Random event, 随机事件$ U$ z2 c& C/ C
Randomization, 随机化 x6 O8 c) w( f
Range, 极差/全距1 {: A' I1 K" [8 M
Rank correlation, 等级相关
7 t% D6 y) t$ k8 c, B( f4 j: jRank sum test, 秩和检验
8 W: [. k8 S1 W. c+ b4 ZRank test, 秩检验
( ^5 j! U1 ^: _- IRanked data, 等级资料
2 ?% k r, [. E/ ~8 IRate, 比率; J g! w4 @8 ] U! t
Ratio, 比例
6 [5 K5 S9 e$ R2 xRaw data, 原始资料
* b! c+ O. A* p5 G1 F. D3 }Raw residual, 原始残差" W" Z$ y) e% n. i1 c. ?
Rayleigh's test, 雷氏检验 m% N( m+ Q1 b2 P8 P: }) {
Rayleigh's Z, 雷氏Z值 5 B3 D& ]) P; f1 |
Reciprocal, 倒数
( u/ Q [3 d( [# b. |+ oReciprocal transformation, 倒数变换$ l0 j+ H7 E" ]. ?
Recording, 记录
& F* O7 d. O+ H7 nRedescending estimators, 回降估计量
$ |9 o" C7 G' kReducing dimensions, 降维8 g, A2 G9 C' b# ?/ [
Re-expression, 重新表达' S r! n& h; {7 c" V3 F2 g! [- @
Reference set, 标准组" j: ?. |! o$ \
Region of acceptance, 接受域
2 ?9 _! L F) f5 d7 VRegression coefficient, 回归系数# q5 p8 Y$ e$ h c: P6 o
Regression sum of square, 回归平方和" Y& M' P# {+ L5 A7 W$ Z* L
Rejection point, 拒绝点
, F$ [( E: V3 yRelative dispersion, 相对离散度* F; _& Q0 U" M$ Q
Relative number, 相对数+ d4 |* E2 ?3 H
Reliability, 可靠性- Y5 b3 [- I0 Y) p; v
Reparametrization, 重新设置参数6 ^3 s# h& n5 Q- u
Replication, 重复
" R0 ^. ?1 U/ q1 oReport Summaries, 报告摘要; N; t, O. V' K& r' L, D7 I
Residual sum of square, 剩余平方和4 H- ?: u' {5 K# L. Q
Resistance, 耐抗性6 w$ C, T6 f- F5 K2 o6 M2 G! o5 m
Resistant line, 耐抗线
6 i8 C1 h4 E. S. ^5 Q. W( p3 bResistant technique, 耐抗技术
: x x% D5 Q: X: PR-estimator of location, 位置R估计量
& ?- a3 D* W& QR-estimator of scale, 尺度R估计量
) a, N l8 p6 s3 N+ U- kRetrospective study, 回顾性调查8 ~' M) r* x: x" g+ O9 c3 h( ]
Ridge trace, 岭迹& a1 }& o2 N6 }: u3 V# y5 Q
Ridit analysis, Ridit分析
) Y7 V9 `6 ^6 C4 }2 ?Rotation, 旋转
+ b* }9 T2 D; z/ pRounding, 舍入
0 t3 ]* }1 ^/ F; ]Row, 行6 i2 u7 J* q$ l: N; h
Row effects, 行效应
, X+ `3 V E* ]8 C4 R/ bRow factor, 行因素' r0 _9 I6 P8 t% {" i# Y" O0 ]
RXC table, RXC表
" i( z8 J- N3 _, v2 |Sample, 样本
% ^: s) ?( z$ XSample regression coefficient, 样本回归系数' n: K! \4 X& b0 m* z
Sample size, 样本量% \6 {) `' ^7 [, g/ l
Sample standard deviation, 样本标准差' p5 r+ I% @# S( h+ e7 M0 X
Sampling error, 抽样误差0 W2 `- Z' a2 @! a q: z
SAS(Statistical analysis system ), SAS统计软件包
- O0 S- ?- u2 nScale, 尺度/量表# h) q9 S& I7 g6 f$ i2 ]
Scatter diagram, 散点图
, {& ~% n+ ]9 J! X: MSchematic plot, 示意图/简图
6 P' R% ~& z# q7 o+ P8 @5 jScore test, 计分检验
$ q8 E1 W" w$ B4 R+ \1 bScreening, 筛检" @5 K! Q4 D) ~
SEASON, 季节分析 ' z; e* [0 W7 L# g. s! E% X
Second derivative, 二阶导数4 g7 R) j8 F8 \+ C5 A
Second principal component, 第二主成分
2 m; \9 o( {, @& pSEM (Structural equation modeling), 结构化方程模型 & ~+ g. w9 h- g
Semi-logarithmic graph, 半对数图$ L% R, z% a* t
Semi-logarithmic paper, 半对数格纸0 j, a& P' A5 x8 f3 @' s( w
Sensitivity curve, 敏感度曲线4 d/ O) y6 _' P. N8 f. v; V
Sequential analysis, 贯序分析
4 K" b( d4 ?3 Z/ Z( i) B0 XSequential data set, 顺序数据集
( V8 A7 r0 ?+ n+ Q" ?Sequential design, 贯序设计
% C& n$ v' b# \5 ]* ASequential method, 贯序法0 N7 N9 A9 O9 i% @
Sequential test, 贯序检验法( U2 {) y2 N8 ?
Serial tests, 系列试验1 r' \6 F7 I. b+ ~( R' y" L+ i
Short-cut method, 简捷法
2 q5 \. E9 q, A& p5 [Sigmoid curve, S形曲线1 L$ V; @" V' x) G! s
Sign function, 正负号函数) z7 b9 v) i% \6 A5 ^
Sign test, 符号检验9 @4 N( Y. d1 Z" U% Z* c
Signed rank, 符号秩: K N3 a2 j m N8 i6 `
Significance test, 显著性检验
4 |9 t- _, { l/ |Significant figure, 有效数字
8 `$ ~* d& w. [1 M4 @3 D) \Simple cluster sampling, 简单整群抽样1 i2 r$ o5 \/ a) W x" n
Simple correlation, 简单相关1 J: k# v Y. s% \. W7 J+ B
Simple random sampling, 简单随机抽样
% P4 \0 v- H0 P$ y8 l* e6 DSimple regression, 简单回归5 @* d0 \% m: g, y' y# @
simple table, 简单表' T: P. ?9 l0 g1 g; _
Sine estimator, 正弦估计量) F2 j& H& W+ M( w
Single-valued estimate, 单值估计
* U4 n) h' t8 [- t( {Singular matrix, 奇异矩阵5 l% s$ G, ]# F: f6 a( Z
Skewed distribution, 偏斜分布6 d8 I$ Y+ V7 f6 R! D$ J
Skewness, 偏度8 q5 @. f9 B- X
Slash distribution, 斜线分布
0 ?- u$ u2 S0 C3 i7 y6 fSlope, 斜率
' s6 A* C* p6 w, ]4 h; gSmirnov test, 斯米尔诺夫检验5 z) r8 i, Y# [: P
Source of variation, 变异来源
% ~0 J+ q* y; B s- Q- mSpearman rank correlation, 斯皮尔曼等级相关
/ h9 p4 I% ^- C7 t( eSpecific factor, 特殊因子
! \9 z$ t* ~6 e( r/ K0 eSpecific factor variance, 特殊因子方差
' u% Z; d& x0 fSpectra , 频谱6 p6 H" c# R1 a q2 k
Spherical distribution, 球型正态分布8 n2 Z Q3 ?5 P% q/ x$ n, {/ G. c
Spread, 展布3 Z. I- W3 l7 Q) {; |
SPSS(Statistical package for the social science), SPSS统计软件包# T7 b+ F4 u* [; z: l$ W
Spurious correlation, 假性相关, H8 S" W, i$ t2 ^* Y
Square root transformation, 平方根变换
; ^) \. n. _ \8 ^7 m) kStabilizing variance, 稳定方差$ V, C. t/ o5 D+ k0 O6 p+ e5 d2 A3 M
Standard deviation, 标准差
$ C" N+ k* P3 X3 [Standard error, 标准误* Y, P+ B) E) p5 `1 w
Standard error of difference, 差别的标准误0 `( e& ]# X& Z# z P; S7 `6 X: \
Standard error of estimate, 标准估计误差2 a& o) t% M" l! h3 G
Standard error of rate, 率的标准误0 a0 x7 u0 k8 B5 n
Standard normal distribution, 标准正态分布
% K1 m; A& y4 ^* k, D7 h6 l. nStandardization, 标准化
" W2 @6 f( @1 y$ FStarting value, 起始值
2 A6 d" f0 O* E& gStatistic, 统计量
! \5 k* T7 q+ u, UStatistical control, 统计控制/ u! w0 }' H0 R. ?5 t# e" d
Statistical graph, 统计图6 {1 k g4 \& M
Statistical inference, 统计推断( G4 ]4 \# y" w# ~ Z
Statistical table, 统计表
8 V# ]$ I, S- NSteepest descent, 最速下降法5 i. F( w( B2 T9 f# @, I
Stem and leaf display, 茎叶图, S n3 `& o6 @5 C0 ]
Step factor, 步长因子
v* |1 R5 U. V) C" `( _! `# g2 `9 SStepwise regression, 逐步回归' s7 X/ W* C7 q) X& ^
Storage, 存3 b. W" X5 j) b' r" b3 p3 \
Strata, 层（复数）/ o! [2 \/ Q! r* q3 x( F {
Stratified sampling, 分层抽样
) C$ X. D% g) p7 U% p7 P4 jStratified sampling, 分层抽样 T; j# E& p& B
Strength, 强度
3 G B) ^: ~: a8 h JStringency, 严密性1 x5 L# R! a. m' M
Structural relationship, 结构关系
n" U/ i. Q4 w% A: z# z2 _Studentized residual, 学生化残差/t化残差+ N6 h# Q6 [, w& ]
Sub-class numbers, 次级组含量
7 S' n0 b6 L5 f* aSubdividing, 分割
. C& r2 ~$ `) I; L+ ?# ^, sSufficient statistic, 充分统计量; v) Y% P2 o. z* }1 i1 W5 |
Sum of products, 积和
% `* M) @* [- C0 c& S( aSum of squares, 离差平方和
: I( D8 R" i& A* T2 A+ {Sum of squares about regression, 回归平方和3 }0 V3 D$ z V% }* |
Sum of squares between groups, 组间平方和6 ]. H/ c' {' v* J
Sum of squares of partial regression, 偏回归平方和! r; b, e# s- n1 M0 m
Sure event, 必然事件
$ ]) s8 @/ Y; C3 Y9 A4 @Survey, 调查
. h- D! h2 t# t. \6 OSurvival, 生存分析 Q! {1 D+ A, |+ K+ r, V& f
Survival rate, 生存率" l1 ^2 i/ J9 @6 ]# y
Suspended root gram, 悬吊根图
" T w v4 T) p& M' {# r5 nSymmetry, 对称
- v& u, u3 M+ `% n4 r2 ` USystematic error, 系统误差) `" e; [) p7 {& e
Systematic sampling, 系统抽样& H) P6 @" \2 G8 K( Y$ R
Tags, 标签' a+ F# D+ k' u
Tail area, 尾部面积
8 L: g7 P; i0 [, v# R5 zTail length, 尾长2 R' i2 l# G8 ~: F4 ^) e
Tail weight, 尾重9 U y/ N- f) Y. _
Tangent line, 切线
; a+ e. Y) i! e% J/ z/ Q# j `Target distribution, 目标分布1 T+ d6 W1 h: k, R& Z3 b! x- h0 g/ H
Taylor series, 泰勒级数* ~/ l! _. L+ `3 E
Tendency of dispersion, 离散趋势
9 u/ E1 O3 o' z! UTesting of hypotheses, 假设检验
5 A- a& F) b) g5 w+ CTheoretical frequency, 理论频数
! S8 v" v, B" U1 }) bTime series, 时间序列0 C+ ~+ n N1 J' f
Tolerance interval, 容忍区间1 J* u% i3 l1 c' o! ]
Tolerance lower limit, 容忍下限# i/ P0 |& R& F: U7 W" P2 D; y
Tolerance upper limit, 容忍上限
) W. P: ~) L. \! ~9 W: fTorsion, 扰率
3 X$ M+ q! b: X7 `Total sum of square, 总平方和( B0 T# M# l( o; D3 R
Total variation, 总变异
# N0 i) D( Z# }1 u C6 t2 PTransformation, 转换6 A: O, ]& R( k/ P
Treatment, 处理
- ]: V, V/ ^. P! O& S# \" v+ Z4 vTrend, 趋势( ~' y9 A" l. @+ r
Trend of percentage, 百分比趋势6 q1 i- T6 c* V" T7 C) N
Trial, 试验
( `) Y9 E. t9 c }8 n1 s9 STrial and error method, 试错法
4 `9 W& o5 o8 k2 P0 nTuning constant, 细调常数
3 s8 w& [6 r1 h/ w2 J. x. oTwo sided test, 双向检验7 q+ x+ C, ] `# j0 Y l
Two-stage least squares, 二阶最小平方
8 M$ F" t }: U* C$ G* ~Two-stage sampling, 二阶段抽样
4 h1 D) X/ L6 f# DTwo-tailed test, 双侧检验8 C! R K6 b* Y9 e/ o8 s7 Y
Two-way analysis of variance, 双因素方差分析
" N, w! s5 t4 O: b' D9 d4 FTwo-way table, 双向表
4 z: G/ L7 Q; n, N! @Type I error, 一类错误/α错误
2 @( X" I6 E- h7 ^& `1 w3 SType II error, 二类错误/β错误
, I' `0 V# a1 v; m8 a( q3 FUMVU, 方差一致最小无偏估计简称3 U1 k' ]3 g& x6 Q4 F% A2 n# o, W9 `0 ^1 @6 K
Unbiased estimate, 无偏估计4 ^0 L, z/ z" B
Unconstrained nonlinear regression , 无约束非线性回归
9 \$ q- ?9 \7 a+ c% P$ oUnequal subclass number, 不等次级组含量; T0 v' y+ V' a+ V( I
Ungrouped data, 不分组资料) L! C7 U7 Z, A, O: B# X
Uniform coordinate, 均匀坐标3 @% k0 U( [$ o4 D% Y3 ]
Uniform distribution, 均匀分布
6 L0 f+ t& l" P% h8 k' FUniformly minimum variance unbiased estimate, 方差一致最小无偏估计& @; m6 [( j. L7 p: N( i# @/ Y& Q
Unit, 单元
3 |3 r/ I- L7 {/ |) A* M: dUnordered categories, 无序分类$ L5 C0 A7 `2 d; d6 n
Upper limit, 上限; @7 ?4 j6 d3 q: }5 J; _8 c
Upward rank, 升秩
$ {+ L% [' r5 F+ q* {" M% WVague concept, 模糊概念
+ ?6 @7 T/ ] p3 e( Z' T7 }" xValidity, 有效性' ^) O3 b0 i3 M+ S. ?
VARCOMP (Variance component estimation), 方差元素估计
& L% S* x( h# l+ X1 o- t0 w/ cVariability, 变异性
/ m: D1 h1 N& v3 r$ dVariable, 变量 w2 t" k0 a9 n( B( u1 h: b
Variance, 方差- i C+ `2 ~; B! ^
Variation, 变异
, S) I! r j# o. ~8 h7 t& t3 uVarimax orthogonal rotation, 方差最大正交旋转8 S- F M" v1 w; H b8 }2 c0 |
Volume of distribution, 容积+ y7 U- h. b1 t+ L+ s
W test, W检验
- u0 t( t0 \, \2 G. ^& HWeibull distribution, 威布尔分布2 d. p8 s, k3 }: d
Weight, 权数
# D2 `/ l; {3 C# `Weighted Chi-square test, 加权卡方检验/Cochran检验) O+ w2 Z* }8 q1 k
Weighted linear regression method, 加权直线回归* S3 F; |" f' K$ S" M3 V( z+ ~6 L
Weighted mean, 加权平均数
\: ~2 p, [+ ]9 j- F8 T% b3 MWeighted mean square, 加权平均方差
% A% g: ]: |! dWeighted sum of square, 加权平方和
7 f! r# Z( W# V+ P$ N1 }Weighting coefficient, 权重系数+ I# p0 p/ E8 n; ^" ^1 ]) H
Weighting method, 加权法 # `% B* ^; t0 m( _
W-estimation, W估计量
5 s/ {3 @+ G$ G. A. ?W-estimation of location, 位置W估计量8 H. y0 t: o( A6 v
Width, 宽度) J) m& J4 G( r9 m' J6 v
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
+ U4 ]) H F% o8 }) n" W8 z" mWild point, 野点/狂点2 M# n+ N6 W9 _4 e" l# F& Q) _0 @
Wild value, 野值/狂值
* T2 L/ O& @+ ?2 h+ ^* U. M, Q" FWinsorized mean, 缩尾均值
3 }. L5 c0 n* @8 M+ jWithdraw, 失访 / O& x( F+ Q' A* \ J) a
Youden's index, 尤登指数
# A! e" d7 j6 Z( p% l, L6 T5 U: Z# BZ test, Z检验7 E( T* O( W$ f' J; r
Zero correlation, 零相关
3 `! K9 B: Q# j8 l4 RZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
