|
|
Absolute deviation, 绝对离差
6 r3 m. W' H: l t wAbsolute number, 绝对数
: q, L- z. l* I; KAbsolute residuals, 绝对残差' t3 `4 @! j4 C5 C/ I
Acceleration array, 加速度立体阵" o' ^# v( ]0 y9 r! w, b# L/ \
Acceleration in an arbitrary direction, 任意方向上的加速度* O- `" f' G. Y
Acceleration normal, 法向加速度
7 Q+ Y6 b( B. nAcceleration space dimension, 加速度空间的维数+ k6 e' X g9 J2 H7 s( J- [- A% p
Acceleration tangential, 切向加速度' r4 R8 }; k8 B* e: m
Acceleration vector, 加速度向量
/ _: a8 s9 N2 b" j" q" ]+ CAcceptable hypothesis, 可接受假设
0 m, @( f) Y' ZAccumulation, 累积8 _) s; @( @; F( \; ] p$ M
Accuracy, 准确度 n7 X6 H# t9 ]; I" O: ]- q6 j
Actual frequency, 实际频数
9 l$ B) W& l% c, ZAdaptive estimator, 自适应估计量' T4 O M/ L" `
Addition, 相加& h$ S$ Y3 t: H7 W
Addition theorem, 加法定理
5 S- x y. u; K p! d0 i. FAdditivity, 可加性2 {0 C6 s7 W/ ]( s. m1 [
Adjusted rate, 调整率( m! y. J( e' b3 d+ y
Adjusted value, 校正值9 u9 V% D7 _# w
Admissible error, 容许误差5 }( K# p1 }6 O
Aggregation, 聚集性" A t" A8 i' P+ q% V
Alternative hypothesis, 备择假设: z& s, w4 l6 v+ Y$ Y: I5 o; |: l! g
Among groups, 组间/ R* ]1 g& {2 a8 I
Amounts, 总量
! V, n9 x- y( @9 o2 XAnalysis of correlation, 相关分析& R; }- c+ y, _! J2 r% g' ~
Analysis of covariance, 协方差分析' ?2 L- P a/ i: J1 K# B: q
Analysis of regression, 回归分析
" W7 Y' g' W; N" D; K+ pAnalysis of time series, 时间序列分析/ N. M, J) I8 L' I& k& @6 z4 u
Analysis of variance, 方差分析7 ]* A9 b8 X( q" m/ g/ I& |
Angular transformation, 角转换
/ U3 M1 Y# p3 I2 YANOVA （analysis of variance）, 方差分析
f' [4 @' @ n6 H$ mANOVA Models, 方差分析模型6 N* a9 K; m1 K$ p# R. g
Arcing, 弧/弧旋) _# W7 w! p+ o' G3 o
Arcsine transformation, 反正弦变换* y) h6 T" S% {3 [
Area under the curve, 曲线面积" O# E! a5 Y c' y
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
! \- m0 I/ u$ v6 w% R" }+ bARIMA, 季节和非季节性单变量模型的极大似然估计
! j2 n0 k$ Z h( W1 o6 dArithmetic grid paper, 算术格纸1 W! o3 w6 o5 z4 w( ~
Arithmetic mean, 算术平均数* u7 c" ^- Z# C4 n0 A4 Z- ?4 N* h! H
Arrhenius relation, 艾恩尼斯关系3 q! O& ^: ~2 T. w1 Z
Assessing fit, 拟合的评估) A7 z) m& i; r2 o+ g& U! d
Associative laws, 结合律
+ x4 K7 K8 B3 {) J' z) U# |Asymmetric distribution, 非对称分布
. Q* z6 @1 b7 C; A5 KAsymptotic bias, 渐近偏倚
, M3 D' L* I' TAsymptotic efficiency, 渐近效率$ G4 c* r' I. \
Asymptotic variance, 渐近方差* G( }5 M y: w* g
Attributable risk, 归因危险度
/ ~9 C% n) s R& [0 gAttribute data, 属性资料2 y5 ~( R8 [5 O1 U. Q: h
Attribution, 属性
, A3 C* S( D2 o# L$ y. J+ ^Autocorrelation, 自相关3 C: H }0 u# u0 Y% j
Autocorrelation of residuals, 残差的自相关; v0 X; x9 e$ \" G# Z
Average, 平均数& T% n1 w6 @% h& Y# ?. ^8 r9 e. Q
Average confidence interval length, 平均置信区间长度! ^; ?; y# ^; I& N1 S; r. A: n8 d4 @& v! A
Average growth rate, 平均增长率' ~$ A3 V! v8 L
Bar chart, 条形图
; F$ ?/ x- q! o& o/ ABar graph, 条形图
- j2 \6 r. ~4 j1 Z$ s8 a+ X# bBase period, 基期2 ]0 K7 `4 r/ m4 p9 t9 o
Bayes' theorem , Bayes定理
" {1 }+ {$ Y {7 ]3 ?+ P2 {Bell-shaped curve, 钟形曲线
4 |. J% d0 |. e# s1 d; N9 [Bernoulli distribution, 伯努力分布
/ T5 e" _ @$ H9 v OBest-trim estimator, 最好切尾估计量0 N" W! y2 {5 g6 G; r( K
Bias, 偏性# u% F. I3 c5 e1 j
Binary logistic regression, 二元逻辑斯蒂回归$ ~6 x% c% G n* x
Binomial distribution, 二项分布
) w8 }. H" i0 @7 Y' ?Bisquare, 双平方
# F8 [& T8 N, D5 U6 E* D- QBivariate Correlate, 二变量相关9 m, R* f# ]% c, H
Bivariate normal distribution, 双变量正态分布1 ]( e+ P. X5 W, F
Bivariate normal population, 双变量正态总体
0 ]0 L9 O' {' f% f/ q& T: mBiweight interval, 双权区间
9 D$ y& W8 E6 W$ ?: ]/ h1 CBiweight M-estimator, 双权M估计量" @* h! y1 r1 }8 x; `6 c2 Z
Block, 区组/配伍组; y" ]; y" U0 Z1 L; v% v
BMDP(Biomedical computer programs), BMDP统计软件包
$ ]9 l" P4 y" JBoxplots, 箱线图/箱尾图1 G2 w/ \: f4 h6 j% v2 e+ Y8 W! o
Breakdown bound, 崩溃界/崩溃点
! C' e: a5 v& K# A0 c; UCanonical correlation, 典型相关
; N; q+ l; g3 L( ^0 e9 tCaption, 纵标目
+ {; I4 P- G5 V, ZCase-control study, 病例对照研究
. E4 s+ b) M. t3 c# m7 K2 ^9 kCategorical variable, 分类变量) q" ]0 @& |& ` d( s7 n
Catenary, 悬链线& K% j# {5 [& s$ ~! C. ?+ D
Cauchy distribution, 柯西分布6 q) h5 T7 h! g0 |0 ?# K- I; q2 t
Cause-and-effect relationship, 因果关系- \4 G' b( E( f9 z7 J' W( Y) c N
Cell, 单元7 u1 F4 o$ U, u* j/ p
Censoring, 终检. L) W. _" P) m
Center of symmetry, 对称中心! p6 m3 P3 K2 d4 ? x# u
Centering and scaling, 中心化和定标
7 E+ ^ y8 H, t; OCentral tendency, 集中趋势
4 r/ h& ^7 `, K' bCentral value, 中心值
& B8 h% A9 T8 ?: `! Z6 hCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测8 Z( m8 j3 j2 K: S- d
Chance, 机遇
' V2 n8 E' K3 }4 P! B1 Y( S- TChance error, 随机误差" x7 Z( v- L+ w
Chance variable, 随机变量
# a1 ^7 M H) i1 ?& U5 g' ECharacteristic equation, 特征方程/ z5 q* @) O2 s& b* K. g; y8 \
Characteristic root, 特征根
* l7 D+ P2 F* Q$ C/ SCharacteristic vector, 特征向量/ \6 l' a2 ?& b! d& ~& S+ P% S
Chebshev criterion of fit, 拟合的切比雪夫准则
, A, c" p9 ^3 D( x% I; k nChernoff faces, 切尔诺夫脸谱图
& } ` [/ H- k" E+ F# ZChi-square test, 卡方检验/χ2检验4 X) u# J2 z F4 \! W# K2 M! Y
Choleskey decomposition, 乔洛斯基分解) P6 k. l; _: F1 M- q$ k
Circle chart, 圆图
7 S* d* A8 w* {' m& F; vClass interval, 组距& g: v' A3 ~% m, J4 k. F3 U- E1 _- |
Class mid-value, 组中值. m7 Y+ s" M) e! h, Q; U
Class upper limit, 组上限/ {+ b* {' a2 a$ s! w, Y
Classified variable, 分类变量
' \4 l" s1 W N/ _: D" l" `; C2 cCluster analysis, 聚类分析- m5 D, B1 P6 z0 |) K+ c0 g- A C
Cluster sampling, 整群抽样
( u* @. E! m" d4 oCode, 代码0 Z4 c! `; Y9 W: @6 W
Coded data, 编码数据9 A' H% \: G" }
Coding, 编码' G% q. x0 k) u* e2 n @, F; r
Coefficient of contingency, 列联系数
" J; ~, m( u2 X: l ?7 _Coefficient of determination, 决定系数
v$ ] L6 x# n# {. |+ j. n9 _Coefficient of multiple correlation, 多重相关系数
( o5 S" }; O& P( [! L5 x, bCoefficient of partial correlation, 偏相关系数* Y, m- l& J; _ Y1 f# |$ B
Coefficient of production-moment correlation, 积差相关系数 `2 q8 | l* F( p. e9 I" d# F
Coefficient of rank correlation, 等级相关系数
E3 o' E/ [6 W* ACoefficient of regression, 回归系数
* g/ y; E* D+ o( o$ yCoefficient of skewness, 偏度系数" }4 a5 H+ p3 G& m b
Coefficient of variation, 变异系数
, b+ b1 @# c+ l8 t V3 GCohort study, 队列研究
6 x4 D; V7 F# ]* ?: {Column, 列, c; `) N+ U0 ]3 @, O. J6 h0 k9 t
Column effect, 列效应# [" v0 ^4 F* I" x; g6 | g5 b
Column factor, 列因素; P9 j, R: Z: S4 p; @5 S
Combination pool, 合并( w; `- P$ C: ?4 w0 `' V
Combinative table, 组合表( K: o, c# `+ ?7 g
Common factor, 共性因子# ~- @- S* \7 Q" ~& f( o8 y+ A
Common regression coefficient, 公共回归系数2 r7 V5 \: c/ W7 R- l) J
Common value, 共同值
) ^* \% r0 e* K! fCommon variance, 公共方差& U+ n* D @# V6 L0 z& P: F; ^8 v
Common variation, 公共变异# W- M% G# t3 i
Communality variance, 共性方差
2 }$ d2 @. t l/ I( X4 UComparability, 可比性
T' |$ [3 N, M4 R- G0 }Comparison of bathes, 批比较
! b3 j, \0 _& o1 PComparison value, 比较值
. P0 e1 R) w# R' sCompartment model, 分部模型6 R7 N! y. U2 L/ E% V
Compassion, 伸缩* w7 c z }* J; x4 c( x) v
Complement of an event, 补事件
, h4 C. |. ^6 m% V& d* ]2 D. @ zComplete association, 完全正相关' }* ?) G$ a/ u; M9 |/ ~
Complete dissociation, 完全不相关
: f) @4 ?9 r3 h0 l, NComplete statistics, 完备统计量, F' h7 s- K6 V, z* c& U
Completely randomized design, 完全随机化设计% N5 j1 [. m8 K& L& Y, ]1 {* V3 r
Composite event, 联合事件( n& d) y# ~! K8 M
Composite events, 复合事件, T( ?( B4 l- i- R l
Concavity, 凹性; I( Q2 P1 c8 E0 {- e+ M
Conditional expectation, 条件期望, t; f3 ?6 b' B7 t& Q$ o, b
Conditional likelihood, 条件似然
# u6 k E; `* m3 L6 ^Conditional probability, 条件概率1 g4 [1 \3 j3 ?4 N
Conditionally linear, 依条件线性
' F u) |' ]! f# eConfidence interval, 置信区间0 B. V- R, V. q6 e( O; s
Confidence limit, 置信限- @8 f+ K4 h) x. z& s
Confidence lower limit, 置信下限
5 l0 O' y! e& H& v) FConfidence upper limit, 置信上限9 H9 o8 `5 W: g
Confirmatory Factor Analysis , 验证性因子分析
: F2 E! T& f& KConfirmatory research, 证实性实验研究
" H2 u: ?4 R% s* AConfounding factor, 混杂因素) L& R7 S& n) F1 b% F2 ^+ e+ B& N
Conjoint, 联合分析; s+ S7 ]: U- @2 j) A- ?7 [
Consistency, 相合性$ t) U. ~6 j! t& f
Consistency check, 一致性检验
+ ^: |+ ~0 \7 F# N" _Consistent asymptotically normal estimate, 相合渐近正态估计
) V3 C' |* ]. h) T' V/ \; EConsistent estimate, 相合估计
) v* C5 ?! r1 ? MConstrained nonlinear regression, 受约束非线性回归
" a6 v# p+ ^1 [9 A o/ A/ m; MConstraint, 约束
8 t4 G( V6 k5 u* _. [/ N, D! ?Contaminated distribution, 污染分布4 k! p; M$ M8 U
Contaminated Gausssian, 污染高斯分布
! k9 S* _7 [6 HContaminated normal distribution, 污染正态分布4 C( _0 P. k, Y6 Z3 B
Contamination, 污染
( r. q2 B+ m) w. NContamination model, 污染模型
) i) g5 H1 [% ^2 \- h* m" V% |9 ~2 A6 nContingency table, 列联表+ g- j& t1 Y1 @( Z( L
Contour, 边界线
y U! e+ k" E/ v! {! Q) LContribution rate, 贡献率* v& F: R8 N. h2 }* h
Control, 对照
$ L$ A6 H+ i* N4 e) {" n2 h$ O) FControlled experiments, 对照实验8 U8 ~ Z/ U9 c9 e2 H
Conventional depth, 常规深度
2 Z" l0 `, O! G/ AConvolution, 卷积5 C/ V9 d' T9 @5 t
Corrected factor, 校正因子" I4 ]- z3 ] Q- ~9 L- r, }
Corrected mean, 校正均值
4 e2 \! y; N k" ~% E3 C6 lCorrection coefficient, 校正系数9 C1 Z: P3 r* r) L, i( V
Correctness, 正确性6 e/ A K1 o* v: R% `8 X, H
Correlation coefficient, 相关系数
+ M% ~6 H7 C, |# y8 a6 z- @Correlation index, 相关指数: g# y$ Z; ]5 ^& O' a. U& x3 @ p7 w* J
Correspondence, 对应* C% j4 K- u5 ~9 f0 ?+ f
Counting, 计数1 ^$ l: p. v2 p+ T5 c+ t; D6 s
Counts, 计数/频数
6 h& y% k Z3 D' |) M6 z' c2 FCovariance, 协方差# ` k7 N' I8 Y3 b( F
Covariant, 共变
9 o! t9 Y5 ? u: N+ }* L0 U) b5 D6 m" wCox Regression, Cox回归
7 S+ q" z% ]4 y5 @$ L% }* O# WCriteria for fitting, 拟合准则
( p5 z$ s) ~+ S5 I) H" C5 _Criteria of least squares, 最小二乘准则
" D7 h" l/ b. o y- i7 XCritical ratio, 临界比
* E" i2 B/ r( d0 [Critical region, 拒绝域
x2 F3 w$ ]! Y8 g# G/ ^* HCritical value, 临界值3 N# N1 w- r: @7 ]' I
Cross-over design, 交叉设计 ~/ t A/ p- G% Q( m1 a- l
Cross-section analysis, 横断面分析3 N# Q& x3 v8 R E( k- Q6 u. d
Cross-section survey, 横断面调查
4 I' k' z* R+ M8 T# d) |: ]1 v8 {Crosstabs , 交叉表
, @4 t- ^/ y, P7 n% dCross-tabulation table, 复合表5 i& ~5 f/ K4 f" E
Cube root, 立方根8 o0 ?) p I4 D/ P& L$ J
Cumulative distribution function, 分布函数
8 s0 D5 L/ a, D$ `9 nCumulative probability, 累计概率( _) s3 D2 ?; F% y+ Z K4 g+ x
Curvature, 曲率/弯曲
/ ?' A# P) z" m0 G ]8 ]& tCurvature, 曲率
/ @( d( c0 z a4 s6 J: ~9 ZCurve fit , 曲线拟和
7 _( b+ S# i6 k) @Curve fitting, 曲线拟合- R9 f% O; E9 n6 `9 }6 f' l
Curvilinear regression, 曲线回归# G; ^; ~6 Z1 a/ u2 c1 M( Y- c
Curvilinear relation, 曲线关系( ^' s+ Z! N2 m+ J# X0 V! r0 w
Cut-and-try method, 尝试法
: C& j# h- D. d- f4 @Cycle, 周期
P& r1 y; R+ I5 u1 }* G! o- cCyclist, 周期性0 O3 n4 n5 R& |! C& l2 e
D test, D检验; k' r4 x, o6 l% J1 i) v
Data acquisition, 资料收集
& Z. g- _. D8 {8 s( sData bank, 数据库9 }7 Z) w6 n) H; r
Data capacity, 数据容量- }9 E7 l1 {4 D5 L' E0 y& Z
Data deficiencies, 数据缺乏6 R7 h8 K! V5 s! r+ A
Data handling, 数据处理- x& r l' Y/ G' g9 z- J* i2 }5 Z7 x
Data manipulation, 数据处理7 T; P& G+ H% y% M) s
Data processing, 数据处理7 n; o ?9 }; O+ |# u4 N& `- \
Data reduction, 数据缩减: R8 l6 C' u8 o
Data set, 数据集
1 y. k2 ]( b+ G; { l( v# ^Data sources, 数据来源
1 S& g. g4 Z5 n( H+ Q! lData transformation, 数据变换, T3 ]/ b3 {- b$ B( `/ T
Data validity, 数据有效性% i# C% x% R4 R) ~; o
Data-in, 数据输入
+ g( P: A' i+ W! J7 I0 q" gData-out, 数据输出
) p' R4 p" ?2 r5 I8 d- b$ sDead time, 停滞期
1 e. D0 c2 }# H j8 RDegree of freedom, 自由度
2 a7 v( K ~8 g+ E0 x( FDegree of precision, 精密度
/ b% c/ M) X2 t1 W) T0 jDegree of reliability, 可靠性程度
! y0 m9 F6 L k& t; ^( vDegression, 递减
. [9 y8 T* z+ n, ~& K& ^Density function, 密度函数
" P6 H: s8 C7 o/ m& n3 BDensity of data points, 数据点的密度
8 S4 z! A' N- U* eDependent variable, 应变量/依变量/因变量
% T" v% E/ v3 Y$ s' Q1 }2 nDependent variable, 因变量! A+ k) c; k0 n. ^- d' a* T& R1 p
Depth, 深度+ n6 n8 e* J% k: q* C
Derivative matrix, 导数矩阵5 l/ F0 u( \( R* X5 E; i+ Y
Derivative-free methods, 无导数方法
+ `: k1 d2 ?6 w9 w! Q. G9 r' ]8 B4 |8 _Design, 设计2 {% w+ ?# I9 W, t: h7 q
Determinacy, 确定性3 y* R4 }1 |$ D' d9 t
Determinant, 行列式2 Y( X) z3 X3 C
Determinant, 决定因素# ^+ z3 q' i: E. {% N, h# [' W
Deviation, 离差" {+ a$ s7 ^8 M+ c+ A: E8 z
Deviation from average, 离均差
* V4 _) t/ y! B7 p. }' jDiagnostic plot, 诊断图
N8 k% r/ J/ T7 ~# G) ]& y8 u) S$ wDichotomous variable, 二分变量# E; n1 u' g8 d9 W4 I9 J: c+ ]2 P9 _
Differential equation, 微分方程& |, v& L, {4 Y3 f3 `- H
Direct standardization, 直接标准化法) T1 I! ^) N( C L( k b
Discrete variable, 离散型变量: A# i" ]% \: a# R: T
DISCRIMINANT, 判断
9 D4 c3 x T5 C4 l4 |Discriminant analysis, 判别分析6 [6 K' G" ]% f% q
Discriminant coefficient, 判别系数) p; M( @* H1 ?8 `9 V
Discriminant function, 判别值9 V% O% [1 O- L6 B9 {
Dispersion, 散布/分散度" T* r% ^) f% w6 S* _
Disproportional, 不成比例的, u; W( H9 {: U: p5 v; a( ~2 J
Disproportionate sub-class numbers, 不成比例次级组含量 [- f5 A, G# c! S' a$ K0 F( i; B
Distribution free, 分布无关性/免分布
# v" ?0 q' | @3 MDistribution shape, 分布形状8 N4 U0 f: c" c+ Q( O F) C, A% a
Distribution-free method, 任意分布法9 U! Y# c2 D" z4 a3 C
Distributive laws, 分配律
8 u; w1 ]3 H+ R$ Z& Y) x. m: Y) _. uDisturbance, 随机扰动项7 S! j# X1 z$ Q
Dose response curve, 剂量反应曲线
8 _) [5 ]! z9 HDouble blind method, 双盲法# s( o! T% D. k. k! C+ T1 `
Double blind trial, 双盲试验6 O$ p8 x! G) E5 O1 _! d3 k. u. W% ~
Double exponential distribution, 双指数分布& u7 D7 u5 z# N/ m9 j
Double logarithmic, 双对数2 T: g* h* w* P6 |
Downward rank, 降秩) B/ C( |8 X) e2 N) d4 H8 h6 E( ]
Dual-space plot, 对偶空间图2 d1 T) |; k- @7 }) o
DUD, 无导数方法9 Q. s1 Q1 s" z$ H
Duncan's new multiple range method, 新复极差法/Duncan新法5 V1 V) B9 [& E! J2 t
Effect, 实验效应
" _* T W$ X. ?/ l& SEigenvalue, 特征值
2 A7 R, j6 l* [5 a! fEigenvector, 特征向量
9 z6 x8 ~5 r. P2 `5 L9 w: l' u& zEllipse, 椭圆
- d! F5 _& n3 T! r7 B l+ `Empirical distribution, 经验分布0 X4 g# U3 r5 C! V
Empirical probability, 经验概率单位# Z# |6 _( j1 V+ ]' A
Enumeration data, 计数资料
3 f T4 J# W8 d" [Equal sun-class number, 相等次级组含量) e1 ~4 \" G7 g" x3 P' B
Equally likely, 等可能
; S1 a) d3 }% M* @6 _Equivariance, 同变性
0 _# C" K! d. n) j0 i0 i- cError, 误差/错误 _6 @: J) ]9 X4 W" d/ L3 Z) a
Error of estimate, 估计误差
) Z; t& P5 v! S. r0 i: K& U' z. qError type I, 第一类错误
/ ?( l) a( h/ b8 AError type II, 第二类错误! g1 C9 w. P' s: A# T! x& v2 d
Estimand, 被估量
7 e) A) ^: r8 g3 E; KEstimated error mean squares, 估计误差均方& ?6 ] M! K- u; q, ^' D. W" }
Estimated error sum of squares, 估计误差平方和
+ z/ O1 l; S% n; f6 f! jEuclidean distance, 欧式距离' v9 _# o. {9 w6 p4 c! W* U/ J, i* @- b
Event, 事件
2 f* L E' G- W% V; Q' B7 yEvent, 事件" Z2 W% Z! O( G
Exceptional data point, 异常数据点- H4 D1 d; J2 v. f; A
Expectation plane, 期望平面6 U' R& P7 v4 h' |: q
Expectation surface, 期望曲面1 B. x. m' t' _1 H
Expected values, 期望值( F. c, g) Q# v' w0 |
Experiment, 实验
$ j' _+ U* N" N0 q8 y! T3 CExperimental sampling, 试验抽样
; W: @+ t: j; F" FExperimental unit, 试验单位; _2 x: V5 `: Y) i8 y% b
Explanatory variable, 说明变量
7 M! i9 n% B- C, e$ IExploratory data analysis, 探索性数据分析
; ]# z1 Q/ [: N' I nExplore Summarize, 探索-摘要1 o. J/ _9 e. \- L
Exponential curve, 指数曲线
) {0 M+ J) e- o! q* u: H; _Exponential growth, 指数式增长
# \; g( }: _# Y0 X6 e2 lEXSMOOTH, 指数平滑方法 5 O ^9 ^& J4 A0 P3 d/ ]; c: ?# |
Extended fit, 扩充拟合
1 O- s0 \8 q) E5 A2 V# k# {- |Extra parameter, 附加参数
5 k# F7 {9 j9 r( r+ _) LExtrapolation, 外推法
; t. ^* Y9 N1 X% g1 H: l8 MExtreme observation, 末端观测值
c; x2 U: P9 K7 D$ uExtremes, 极端值/极值
) {9 q6 ^% K" X( g7 b# K% JF distribution, F分布
/ @. j" Y! _/ X3 _F test, F检验
+ a5 I8 A2 r+ V* Y. {Factor, 因素/因子! P9 P# K3 L5 |3 j
Factor analysis, 因子分析' J9 e- B$ H% a/ r- M+ P* l
Factor Analysis, 因子分析9 e' X) c2 v+ B" p6 u. Y# Z+ u9 ^. a
Factor score, 因子得分 + N2 T6 ?8 U- J; [ U+ ^2 ?
Factorial, 阶乘
& U/ i _* V' z1 x& HFactorial design, 析因试验设计& v8 c8 p/ `+ |: G( g
False negative, 假阴性
" a) K/ o J- _- c3 @False negative error, 假阴性错误( Y+ K" }: Q5 Q$ b' e3 Y
Family of distributions, 分布族1 y! x3 b4 O8 R; X- X1 V
Family of estimators, 估计量族* C9 v8 s! A0 V+ X9 X# j
Fanning, 扇面
( W. ~0 B9 ?1 ?# a: I9 XFatality rate, 病死率! t7 A+ B. p) m8 F; F" u
Field investigation, 现场调查; J2 M% N7 g5 b) Y
Field survey, 现场调查! e% G& o2 V# A* ?+ E
Finite population, 有限总体
" n* p+ T$ J! X3 Q/ {/ R5 ]Finite-sample, 有限样本
' A6 A: j6 N- c! d gFirst derivative, 一阶导数! u2 `' v5 l) A, n; ]- `
First principal component, 第一主成分+ ^$ \6 W1 {4 k: t H$ B% q
First quartile, 第一四分位数& ?0 o# i" W5 ^$ ]( L1 w! Q
Fisher information, 费雪信息量( ]! H2 b. m, O; c3 K
Fitted value, 拟合值7 {7 l, c, b( W; b
Fitting a curve, 曲线拟合2 o/ W4 }; S( r4 F" S7 N6 l
Fixed base, 定基
( w P) H# @+ S, AFluctuation, 随机起伏
6 A+ j# R: K0 R [ g4 ^, s+ ^) jForecast, 预测
2 _& ?8 F; P7 y' yFour fold table, 四格表
4 U; L5 S, h- x) Y9 N; R- xFourth, 四分点3 a6 w# P& ^1 x+ E& g$ Q
Fraction blow, 左侧比率1 W+ z; v# P# T. v" u
Fractional error, 相对误差0 S1 G, f6 j- y3 c) j8 s2 n
Frequency, 频率3 e6 j! t7 O8 }. x. N" e: ?
Frequency polygon, 频数多边图 A" U# {8 H8 ~& R& V
Frontier point, 界限点2 ]7 K" R1 \2 F8 W) R* c. G* v X, S3 i
Function relationship, 泛函关系" h1 i F: ~5 e Q
Gamma distribution, 伽玛分布
6 P, d3 ]3 z' e2 z' JGauss increment, 高斯增量
1 u7 x. O9 r8 ]# h8 AGaussian distribution, 高斯分布/正态分布8 g% _3 P/ |! `9 k* @: X4 |- h
Gauss-Newton increment, 高斯-牛顿增量
1 `& A D3 B* }! ]- x9 s- bGeneral census, 全面普查
% C& e% s+ T& UGENLOG (Generalized liner models), 广义线性模型
7 N* D0 p/ ]+ Y! t7 uGeometric mean, 几何平均数
' E, l# X: u9 f5 k, h0 Z+ v3 G: g7 y: ^Gini's mean difference, 基尼均差7 D/ Q8 P, O, {" E. Y5 J4 }
GLM (General liner models), 一般线性模型
! Y$ H' S8 j* I2 ]Goodness of fit, 拟和优度/配合度; [" }- x+ V8 Q
Gradient of determinant, 行列式的梯度
. W* ~4 K) c2 U3 LGraeco-Latin square, 希腊拉丁方
* ^" e" p! D) U6 e- d; l8 A, oGrand mean, 总均值
) S' }6 J K( v% l m O5 Z( ZGross errors, 重大错误
+ [2 M& \" P& I& {; OGross-error sensitivity, 大错敏感度- K. x4 o k) c$ j! A
Group averages, 分组平均3 v$ ~/ G& f- r& m" H( f5 [
Grouped data, 分组资料8 C( y+ W, G) p0 q. G8 t \( T
Guessed mean, 假定平均数+ i- q' L3 M# @" ]
Half-life, 半衰期
4 B3 ]# l/ P+ M9 ?! CHampel M-estimators, 汉佩尔M估计量. ^$ z5 S! m1 r# C) x; @ W# ]
Happenstance, 偶然事件
: [; J5 P) T, |1 ^( Q L* ^Harmonic mean, 调和均数. L+ P; J4 |. A) J" o
Hazard function, 风险均数
* x! d u+ x% _6 L3 C9 MHazard rate, 风险率
9 k; o/ N2 m$ SHeading, 标目 5 H: F: u; S4 M2 G8 w6 n
Heavy-tailed distribution, 重尾分布
3 v; P4 ?& W2 E& ~5 JHessian array, 海森立体阵, y2 ~9 }8 W4 f( O$ t
Heterogeneity, 不同质6 N5 {+ j1 v. B" l# T) \
Heterogeneity of variance, 方差不齐
Y% G1 |; E; A8 ?. MHierarchical classification, 组内分组
2 ~- W- N p2 J7 \Hierarchical clustering method, 系统聚类法+ J. O( I1 g8 _8 p& J, J
High-leverage point, 高杠杆率点4 _ O7 ]) ?8 ^6 _- k8 A$ l
HILOGLINEAR, 多维列联表的层次对数线性模型' v+ [) p. ]6 C/ [
Hinge, 折叶点0 H, A% {4 v6 [( m% h0 g
Histogram, 直方图# V; n4 C0 ^! s8 a" G6 \
Historical cohort study, 历史性队列研究 " X! M% j, t& W: x" L$ S: z
Holes, 空洞' i! ]7 n9 m+ V6 o% A9 ~5 L' c
HOMALS, 多重响应分析" S5 G5 W+ T' `5 A
Homogeneity of variance, 方差齐性
, M, @- \% R6 F' O# CHomogeneity test, 齐性检验/ T1 ]" @7 y9 d6 [$ l, x
Huber M-estimators, 休伯M估计量
' }# M5 U8 w$ y( L9 @ r7 |Hyperbola, 双曲线
0 X2 W7 z1 H$ b% T# ~Hypothesis testing, 假设检验
1 o& V! k l5 x+ \Hypothetical universe, 假设总体
3 Z6 f; K; I: vImpossible event, 不可能事件% c/ _9 Z# [: [' G7 E0 Z( x
Independence, 独立性
$ r3 e- W- g+ @; _' k/ h6 z8 _Independent variable, 自变量7 W+ k2 N9 W) O
Index, 指标/指数
- V0 {- w8 a0 u: X) P' @Indirect standardization, 间接标准化法
% |. {2 K) A; b2 G- nIndividual, 个体
. j m5 y+ c" {+ m5 ~' rInference band, 推断带
* \5 G. E/ v% H" j8 tInfinite population, 无限总体4 }1 N# X% a1 q4 Y* t: J3 c
Infinitely great, 无穷大
, E7 P, A+ m( b- @" C, cInfinitely small, 无穷小% K' d# ?* b: e" C3 r
Influence curve, 影响曲线
" N/ B$ {$ K# O* p2 W9 aInformation capacity, 信息容量( Q- f' [; {4 f$ W
Initial condition, 初始条件! W! M- t% b, B5 l6 I! N* `
Initial estimate, 初始估计值. j% k4 m* F' K3 \* A/ @
Initial level, 最初水平
9 g: x% P, a) I& r6 R# B$ bInteraction, 交互作用9 | e$ s6 g' s! Y
Interaction terms, 交互作用项
; @& d l, ]7 aIntercept, 截距
8 {5 R$ H: H+ tInterpolation, 内插法
# ?- x: O0 ?. }) Q- o _# p4 ~5 VInterquartile range, 四分位距, G+ ^1 t- ^7 S3 E! ?: O. Q
Interval estimation, 区间估计/ I2 w b' W9 H6 z7 t: C: ]& l
Intervals of equal probability, 等概率区间
$ r$ }8 H5 z* j( E8 jIntrinsic curvature, 固有曲率! q7 e4 D& X- c, A2 \$ m
Invariance, 不变性
8 G6 h9 ^; ]6 i( z8 V6 r. cInverse matrix, 逆矩阵1 {- P6 h# [& }) x, g& Y
Inverse probability, 逆概率7 `5 O$ B* ?2 ~/ D
Inverse sine transformation, 反正弦变换6 G' w. X" B5 T8 w" e" i7 z) b* @' z; [
Iteration, 迭代 , z5 D) h/ w0 d' c
Jacobian determinant, 雅可比行列式
4 U0 P. H4 p/ ^, a# a2 ^Joint distribution function, 分布函数6 N4 l0 \" I% S! E/ h( ?. \
Joint probability, 联合概率1 t, z) ~0 y0 c H. N4 _
Joint probability distribution, 联合概率分布
5 X5 J! n7 M0 w! D( h" hK means method, 逐步聚类法
9 y' N4 q3 L1 j% VKaplan-Meier, 评估事件的时间长度 ) }& K# w% s% x. U( w- E4 l" D1 a4 t
Kaplan-Merier chart, Kaplan-Merier图
/ L. p0 ^3 T) y$ i8 OKendall's rank correlation, Kendall等级相关# C8 f4 S& @+ k7 L
Kinetic, 动力学9 U% d( ^1 A% n+ k" O) c8 O& J% H
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
" K2 Z" Q( \4 I5 [7 F7 X+ T' ^- dKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验 ^; w/ O* r' q9 z. x9 c; O+ f+ T
Kurtosis, 峰度
0 X7 z* W, h( `6 \8 x3 w3 K% QLack of fit, 失拟2 a* h& @# _- ^- y$ Y! f8 y' o
Ladder of powers, 幂阶梯* z6 n8 U, [# i+ g8 r% J
Lag, 滞后+ y& U6 K4 f3 Q6 {+ l
Large sample, 大样本
9 f8 c4 \" f* P2 ZLarge sample test, 大样本检验
- `* G7 m, |* l2 p h& A4 G7 D& w/ XLatin square, 拉丁方# _! W8 S6 c0 q0 U+ J. O
Latin square design, 拉丁方设计
# o$ N0 L- _. w% }+ s# lLeakage, 泄漏8 o( A' U \9 X
Least favorable configuration, 最不利构形" ?8 M& V0 d' @: O, `0 f. ^& \
Least favorable distribution, 最不利分布
9 E2 o# ^! ?" DLeast significant difference, 最小显著差法0 s: z L; n2 x
Least square method, 最小二乘法
# y! L3 I1 L$ _$ X) K1 ~( ?Least-absolute-residuals estimates, 最小绝对残差估计0 C* ^: R m! g
Least-absolute-residuals fit, 最小绝对残差拟合9 M" m$ y* q# P! M
Least-absolute-residuals line, 最小绝对残差线( w# t+ C' m2 _6 r K3 R7 o: n
Legend, 图例$ [/ M9 ~7 ?; T9 g! ~% d1 g
L-estimator, L估计量% e4 q9 \( z4 W" L$ b
L-estimator of location, 位置L估计量2 a& P8 X0 G3 M' A" y% P5 ?
L-estimator of scale, 尺度L估计量
+ r- Y. ~; F. `) ZLevel, 水平* z7 s1 z0 O. j+ R
Life expectance, 预期期望寿命
+ N0 `( w4 H/ B$ Z" vLife table, 寿命表
: b& y* V& b7 B, P3 m9 f$ PLife table method, 生命表法2 `) X5 f/ A8 M% y9 S V
Light-tailed distribution, 轻尾分布
" `$ l \# _0 h u1 \. c) a+ U% YLikelihood function, 似然函数9 g: B8 w) ^( d1 @" G
Likelihood ratio, 似然比
9 \) I P9 z3 v8 c5 P: Yline graph, 线图, p% o$ Z* a3 a- P ^
Linear correlation, 直线相关
: h3 o0 m, X7 r2 F) ~7 d6 ]3 hLinear equation, 线性方程6 [: X* n: C7 `1 G i ?* }, U5 v
Linear programming, 线性规划
I# N% S, x2 @8 D6 ELinear regression, 直线回归- X! a4 k5 }% C
Linear Regression, 线性回归9 A8 f: }' u% A; g0 d
Linear trend, 线性趋势
3 `* O+ Y- U0 H. x! R7 ILoading, 载荷
) u+ e7 [; W( V( `& J; t7 ~Location and scale equivariance, 位置尺度同变性$ o' }8 O) `) a( B
Location equivariance, 位置同变性) ]6 {5 S% k% ?& r
Location invariance, 位置不变性
! Y) _; {- ?1 f% ^& pLocation scale family, 位置尺度族- p* k) I" B+ ^& x ?4 ^# ]
Log rank test, 时序检验
- v0 a5 K3 w4 s P( D- ~8 v! ILogarithmic curve, 对数曲线
! S: I: `; h# @0 sLogarithmic normal distribution, 对数正态分布& u/ T" c# _6 H$ B" E
Logarithmic scale, 对数尺度$ Z. O8 g- n5 v2 ~" g& @2 i
Logarithmic transformation, 对数变换9 K% m2 q' f1 K P$ Z& K
Logic check, 逻辑检查' v: A1 p: {9 ^
Logistic distribution, 逻辑斯特分布% ^: O F' X0 H" T
Logit transformation, Logit转换' R* N, K9 x+ y
LOGLINEAR, 多维列联表通用模型 4 f1 g) J0 Y7 Y; V1 A
Lognormal distribution, 对数正态分布2 ?- W R6 h9 ?8 F5 Q
Lost function, 损失函数) h' V- d2 t* S! [9 Q8 A
Low correlation, 低度相关
; o' A# |* O2 g) LLower limit, 下限: d" z$ n1 Y: A
Lowest-attained variance, 最小可达方差
: g& u6 U/ Q5 \1 d. v7 X! qLSD, 最小显著差法的简称
. H; a3 C" p/ ?! R$ i7 T' y+ w3 VLurking variable, 潜在变量& C7 @" S+ L$ ?+ w8 N5 H6 W0 N
Main effect, 主效应
1 Y* n: x, Z# e: LMajor heading, 主辞标目9 u& {! }7 }) g2 a5 g
Marginal density function, 边缘密度函数
, e& Z% y; n' `$ zMarginal probability, 边缘概率
! v: H% I M' f6 H4 V, G: MMarginal probability distribution, 边缘概率分布
6 @) r6 D4 N, _1 ^3 I* HMatched data, 配对资料
$ [2 o7 {- K+ W! \# V1 vMatched distribution, 匹配过分布
5 t0 T5 @2 x, |4 j( s: K3 ?Matching of distribution, 分布的匹配
: Y; f( v' A: hMatching of transformation, 变换的匹配. { i0 y: \8 K% u) S: T
Mathematical expectation, 数学期望
# a. C* a% b" c6 U e. v MMathematical model, 数学模型+ f! K. {% Q% b. V' m* ?
Maximum L-estimator, 极大极小L 估计量
. c/ {! y) D, D/ r) }Maximum likelihood method, 最大似然法
8 N5 D8 |3 y e. E; {+ S) d8 mMean, 均数
2 l. J$ k) L+ ]/ p4 `# q- b( HMean squares between groups, 组间均方
5 s* a" }( e% @, A% TMean squares within group, 组内均方
: N( c* T3 D; w7 I5 o6 `8 [Means (Compare means), 均值-均值比较" `; R. ^5 T3 p; ]& {& P9 _0 c
Median, 中位数! {1 F) f( K9 l2 ?
Median effective dose, 半数效量! S4 ]6 p" W# r" s% O" ^5 j
Median lethal dose, 半数致死量
2 Z& G$ y& s, m4 S# C$ P8 B/ t* iMedian polish, 中位数平滑
+ X" w7 B" v8 q% |Median test, 中位数检验& P% ?4 y- x8 g( z, b. _0 C4 O
Minimal sufficient statistic, 最小充分统计量
# H- h, v( U! u+ F0 S# u" s( LMinimum distance estimation, 最小距离估计8 S- E J+ X" [3 m
Minimum effective dose, 最小有效量
7 P! L6 n, X' |Minimum lethal dose, 最小致死量% x) Z3 P: [, N( ~ v/ }
Minimum variance estimator, 最小方差估计量( J' a, ^& _$ [6 s3 B
MINITAB, 统计软件包6 c, ?7 S3 x4 f. B1 Y" J1 k
Minor heading, 宾词标目/ e" T& e& J1 T {
Missing data, 缺失值
7 K1 E1 }; K5 h2 \4 L2 r' OModel specification, 模型的确定
* v9 ?2 D" S# w4 ~Modeling Statistics , 模型统计! j) X2 u) S" Z( G
Models for outliers, 离群值模型/ I- a3 Z, @8 w; \/ @( }' {2 y
Modifying the model, 模型的修正( G$ x- Q8 Z$ S1 m5 `8 L7 w
Modulus of continuity, 连续性模; H) ^. |7 ~2 W
Morbidity, 发病率
# V+ \7 P+ g" M8 {4 p9 v7 o( YMost favorable configuration, 最有利构形
: _: |2 @3 ~! J- W. y! fMultidimensional Scaling (ASCAL), 多维尺度/多维标度$ V9 M( Y8 n( t
Multinomial Logistic Regression , 多项逻辑斯蒂回归
7 A0 l. p6 l* IMultiple comparison, 多重比较
+ }9 [7 B0 p+ k6 `1 yMultiple correlation , 复相关+ c: d$ d4 J! z9 G+ Z3 y9 |: d
Multiple covariance, 多元协方差
5 P! b" y, O! X9 Z: ~& [Multiple linear regression, 多元线性回归
# W& z" B6 x( \8 A- N* q- m+ F( SMultiple response , 多重选项. c8 S! e. h7 M% }% y
Multiple solutions, 多解
" S) `, t. e' `' n3 A" VMultiplication theorem, 乘法定理
# s" ?' q: W h3 JMultiresponse, 多元响应
. V, U5 L8 ]. N a$ VMulti-stage sampling, 多阶段抽样
! f- H+ u7 F) W0 @0 d" a% C6 h; I' C; SMultivariate T distribution, 多元T分布
+ U- \; W4 w: F, kMutual exclusive, 互不相容: L8 Q* v6 `* U; L; `8 G' l2 [
Mutual independence, 互相独立
/ i1 ~" r! ^6 P/ j: vNatural boundary, 自然边界( D! c. T; m' j; i
Natural dead, 自然死亡
, o& J' ~2 j/ t3 E( W0 YNatural zero, 自然零9 f1 P5 U6 T: G6 J( M; D/ v
Negative correlation, 负相关. Y. I* [' p& ?4 b. d |* {0 U+ S6 W
Negative linear correlation, 负线性相关' n9 {. D6 \- v
Negatively skewed, 负偏
; ]/ G D& A% f, E7 f% J2 XNewman-Keuls method, q检验
@ e$ H f7 ?$ L2 UNK method, q检验
) \$ `0 J5 O) T" O" G, ^) FNo statistical significance, 无统计意义3 _: y" l) W7 f5 z' ?$ R1 d
Nominal variable, 名义变量
, X( b8 t/ z/ w; H% ^" R FNonconstancy of variability, 变异的非定常性
8 t. A; \0 o' E$ W! L1 MNonlinear regression, 非线性相关
; `# L i( q! K' w/ pNonparametric statistics, 非参数统计1 o9 O$ y3 \, I1 i0 q* z7 R
Nonparametric test, 非参数检验
1 R9 w& }/ B. ZNonparametric tests, 非参数检验( X( ], S. G3 U" N* z
Normal deviate, 正态离差; ~( R o! x. H/ E2 e% P6 t! Z6 J
Normal distribution, 正态分布
8 [' _: ~% v$ q- L9 FNormal equation, 正规方程组
* H- v8 T& l" B1 vNormal ranges, 正常范围% v3 S# N% J K# o& Q) ^( a) u
Normal value, 正常值
' f; m$ L% e9 `1 V1 q- aNuisance parameter, 多余参数/讨厌参数6 {; h y; @ v5 ^2 r
Null hypothesis, 无效假设 $ \1 x" O/ s% c6 v) |
Numerical variable, 数值变量5 _4 [ x. Q% b8 k/ K* R& ?0 v
Objective function, 目标函数
- d& {" v1 R6 w0 o1 f& y$ EObservation unit, 观察单位
/ f* c( K9 F! C+ G7 |Observed value, 观察值
. C% I6 k: V* c' ~3 H; ~One sided test, 单侧检验
) M1 Z& q6 {) I3 J8 M+ uOne-way analysis of variance, 单因素方差分析
0 v1 k' U: h2 hOneway ANOVA , 单因素方差分析
8 _4 `$ s; q. C9 s5 E# gOpen sequential trial, 开放型序贯设计+ t/ l8 w% N7 M. \1 P) f
Optrim, 优切尾
% Y. ~ B+ c& o) \$ z( nOptrim efficiency, 优切尾效率
2 ^# p; j7 M E dOrder statistics, 顺序统计量
# X5 S9 \+ O# t5 eOrdered categories, 有序分类
# w( k- }! D: p) ^! R0 _' @Ordinal logistic regression , 序数逻辑斯蒂回归
W9 o7 N9 A W+ @2 s# c8 {2 H( xOrdinal variable, 有序变量$ i; r+ J4 n) c8 |4 B
Orthogonal basis, 正交基2 z& s& d7 c% z9 @9 U- x ]. D4 O, Z
Orthogonal design, 正交试验设计
. P4 a0 I2 t: O1 X3 m5 g: U* k9 BOrthogonality conditions, 正交条件1 F5 D0 ]% v9 I w- N- i9 @/ R
ORTHOPLAN, 正交设计 3 y, ?6 e( ~' U, v$ e% s" o
Outlier cutoffs, 离群值截断点7 m! P M. s5 P H G% i* L
Outliers, 极端值2 X" Q& P3 S1 p" Z G' b/ a
OVERALS , 多组变量的非线性正规相关
H+ b) U. ?5 d' m/ ~% a% YOvershoot, 迭代过度
" q/ J. e. t J( y3 |3 CPaired design, 配对设计
1 w) V& R7 S+ f j8 X$ i( \. bPaired sample, 配对样本$ s% @' `5 e+ U: U! C- |; P
Pairwise slopes, 成对斜率
" y. M+ f( p; n: MParabola, 抛物线: X ?0 m/ }5 ^; x8 S5 K6 a: ]
Parallel tests, 平行试验' t k+ `; {0 ~' O6 J
Parameter, 参数
|; J7 m$ \- E* d6 uParametric statistics, 参数统计
7 n# g3 I7 V4 ~" E$ `# D0 eParametric test, 参数检验
- S# D n3 G0 i# MPartial correlation, 偏相关
4 |+ X! p+ x8 X# d$ K2 ^Partial regression, 偏回归3 b8 @9 T5 T* w6 W, p
Partial sorting, 偏排序. b/ r D2 w) Y
Partials residuals, 偏残差
; C8 _3 D) a0 h9 G! ?1 t+ BPattern, 模式) G# o. w5 j, N/ d) a4 h3 w! J
Pearson curves, 皮尔逊曲线 S9 ~8 N4 A: Y& |
Peeling, 退层% i7 s$ v3 w$ k
Percent bar graph, 百分条形图: f0 c! ^. }+ b# R( {
Percentage, 百分比! ?7 `7 F$ }/ E! _: p8 B8 \
Percentile, 百分位数
* T2 l6 i& `; D: c! _1 a' J4 t, z6 TPercentile curves, 百分位曲线
7 i( p1 s3 k& x* Q2 S& EPeriodicity, 周期性
. p: C. z1 n8 L/ N$ t) mPermutation, 排列
, U0 F+ X9 |1 I5 RP-estimator, P估计量/ {9 a) t r7 d% W0 @+ g. v
Pie graph, 饼图; `* T9 Z6 e; z: Y
Pitman estimator, 皮特曼估计量
" m- H- f1 @+ V" c1 U8 r+ EPivot, 枢轴量
5 N) ~7 N Z& x+ y, hPlanar, 平坦
' Q4 q+ k$ Q6 s: y2 b+ IPlanar assumption, 平面的假设: t+ O; K7 g% k" q
PLANCARDS, 生成试验的计划卡
/ q+ a; y3 F/ [6 s- e; ]Point estimation, 点估计
5 [& _; i3 E8 Z& E' M* HPoisson distribution, 泊松分布
& t1 Z, g; | m' W5 ~Polishing, 平滑
; Z/ ^- j. h* ?7 }Polled standard deviation, 合并标准差
% l* i' H5 v! KPolled variance, 合并方差( t: s3 W8 X# u' u
Polygon, 多边图
1 C' p5 g, s, [, l2 `Polynomial, 多项式
/ ~2 R$ c4 V* X9 G L$ @# ZPolynomial curve, 多项式曲线; [5 v$ W7 K) Q. u; \. D; l
Population, 总体
& F6 g5 h3 E" }- `& h; QPopulation attributable risk, 人群归因危险度7 h! w" L5 _2 z) M" g" S
Positive correlation, 正相关
, @! ^7 Q+ V; w: z) `! tPositively skewed, 正偏/ s7 E$ D- B9 T: ~: a
Posterior distribution, 后验分布
2 N/ _" |: X7 {/ z L# P0 CPower of a test, 检验效能1 Z) M" u! Y% n/ X$ m
Precision, 精密度
6 L0 z3 V' B; e3 Z5 q4 F$ |Predicted value, 预测值
9 w' h. v1 o, B7 B% O$ W: OPreliminary analysis, 预备性分析, o& _- K! j" _! s9 Z
Principal component analysis, 主成分分析4 G% G) f! K; e1 l
Prior distribution, 先验分布 r; _/ C( c; K0 r" _. e
Prior probability, 先验概率
. B: N5 U0 _! c3 o' f! I rProbabilistic model, 概率模型
% A) J4 q! K1 o0 Pprobability, 概率
+ L7 R6 T5 A- R/ C! p. aProbability density, 概率密度
. M6 t0 j1 j x; {' d- gProduct moment, 乘积矩/协方差
" s( q( i* h+ R1 X7 V9 ?Profile trace, 截面迹图# H: `: t/ d8 c3 z. v; H
Proportion, 比/构成比
1 J7 } |" R1 Z' sProportion allocation in stratified random sampling, 按比例分层随机抽样4 Q8 {) y, g! W6 h+ a
Proportionate, 成比例9 G! B4 M+ u3 u
Proportionate sub-class numbers, 成比例次级组含量' V, d( j3 t6 s3 b% i) {& ?1 a9 K
Prospective study, 前瞻性调查5 e8 p" K' |( G& S$ q Q
Proximities, 亲近性 8 n9 h9 [" m; S' I1 b
Pseudo F test, 近似F检验
+ m/ `) {3 b* {: t) XPseudo model, 近似模型
, b4 G1 f0 N% ]! ?; w! y+ W+ uPseudosigma, 伪标准差) }1 z5 B u. [+ _$ H
Purposive sampling, 有目的抽样
# Q. l" L2 D6 }- i9 l( ^/ EQR decomposition, QR分解
. ]3 h2 k# n1 JQuadratic approximation, 二次近似
( K8 ]8 K( q' Y8 r4 l) }Qualitative classification, 属性分类' B8 g$ a4 N: \
Qualitative method, 定性方法
- R) T# F( s# y( v- sQuantile-quantile plot, 分位数-分位数图/Q-Q图/ N" v, A" i f# m: G
Quantitative analysis, 定量分析
- e. ~9 Q/ |- d; WQuartile, 四分位数
( n7 h7 K% T* n9 t' A3 k/ @( |Quick Cluster, 快速聚类0 E) Q7 h0 ?6 c# Y& x$ m
Radix sort, 基数排序
/ e! Q, y3 [6 s3 E! wRandom allocation, 随机化分组
; A* G3 s: {) e' B. {% kRandom blocks design, 随机区组设计
: T% B9 I, b6 v4 R' aRandom event, 随机事件
3 W( i' X) l6 IRandomization, 随机化
& k W9 [9 J# o+ m' ~. ERange, 极差/全距1 f& {7 j' q3 y, A
Rank correlation, 等级相关$ ]0 L3 x- J( H8 U, Y
Rank sum test, 秩和检验( V" r& z" W+ ~! q5 z% d: p
Rank test, 秩检验9 F1 E" B( c0 N3 G7 w4 p9 o
Ranked data, 等级资料
0 v4 I- x. t" s6 Y: d, wRate, 比率
) |7 Y& Y( M4 T2 YRatio, 比例
% L8 |5 M! L; M2 @! `0 u6 ]Raw data, 原始资料
% c) S! c, q4 `7 n1 l; ~7 ~Raw residual, 原始残差
$ i' W, M1 S q3 CRayleigh's test, 雷氏检验. j; N0 _0 _' t' f
Rayleigh's Z, 雷氏Z值
: `: q: W, Y' B1 b( R( jReciprocal, 倒数, V) |" `. c; J! n9 g% X" m
Reciprocal transformation, 倒数变换7 Q* v" N& d$ C5 S# Q) j, w3 P
Recording, 记录7 v0 X5 X4 I5 _) m4 k" K
Redescending estimators, 回降估计量
! y& n4 ]5 l4 n5 ^1 s8 u% a& g; eReducing dimensions, 降维
7 M' g& Z! q! PRe-expression, 重新表达1 Q8 J6 \. }: d
Reference set, 标准组: i: p8 G5 D! l
Region of acceptance, 接受域
% `7 ]2 ^9 z7 C) F* Q1 `Regression coefficient, 回归系数
, i7 M4 U+ ]# T& ?* \, n7 YRegression sum of square, 回归平方和
3 M) X c! V7 r$ w, g! i& URejection point, 拒绝点
1 h4 w$ b8 r; |! h" f4 |Relative dispersion, 相对离散度, p$ Z$ p& \, \, Z: Z( l' F: T
Relative number, 相对数
* g; f; E, ~; wReliability, 可靠性
( Y( B8 V, R Q6 J6 XReparametrization, 重新设置参数6 }" b% U- q' n
Replication, 重复9 R6 Q8 }0 i' v9 ^
Report Summaries, 报告摘要
) I* L! O4 g: |. I zResidual sum of square, 剩余平方和
' R3 z4 ^4 D0 l6 p3 I, J! A- {7 G4 LResistance, 耐抗性; h( c4 k$ n6 t; @$ ^' y' s/ p$ s
Resistant line, 耐抗线
1 a1 M7 Y; N+ v O1 BResistant technique, 耐抗技术
5 w$ I7 v8 |( ?! W& q/ WR-estimator of location, 位置R估计量
& |7 U8 D! E; a1 J; n! ]R-estimator of scale, 尺度R估计量
7 T: F1 l+ t7 [& Y7 R; K9 wRetrospective study, 回顾性调查5 o! h! F6 z. U& T" H
Ridge trace, 岭迹
5 c. R$ S, k* o2 }( _4 ZRidit analysis, Ridit分析
! A+ x7 {0 \# N( ~0 \% \- J8 FRotation, 旋转
. {. d* p6 Z0 ARounding, 舍入
6 r5 O6 u9 l8 \! e& b1 m% Y# D* cRow, 行
; E# u" j4 W" g6 h4 oRow effects, 行效应: V! C) q) j# K3 y k2 t. q
Row factor, 行因素
9 j! Z8 A) w. O& p& URXC table, RXC表4 u: R# B7 l7 c
Sample, 样本. Q/ y n9 I: z
Sample regression coefficient, 样本回归系数
g5 c' O0 h1 @2 F' L- ISample size, 样本量" k! u0 B# h, }: H; Z
Sample standard deviation, 样本标准差
5 z) Y. q8 M/ ISampling error, 抽样误差" u b, @% N; v4 E8 d
SAS(Statistical analysis system ), SAS统计软件包! b. M% r$ N; d' P
Scale, 尺度/量表
+ i% M I8 W7 \Scatter diagram, 散点图- _- e) r( G& E1 C: f/ T A& t. B
Schematic plot, 示意图/简图) D: ~' r. _ C% z3 U/ e
Score test, 计分检验
; v f8 E5 ~( i1 BScreening, 筛检9 _8 c% \9 A' q6 H- M& X) o5 A) `5 N
SEASON, 季节分析
" o) b7 x# `- f! A5 [Second derivative, 二阶导数
' {) h9 ?# l" TSecond principal component, 第二主成分
. k: K0 @2 Q" G: R. ISEM (Structural equation modeling), 结构化方程模型 6 v2 c$ v. D/ j/ _6 } Q
Semi-logarithmic graph, 半对数图. u7 j8 ^% e& C6 y; @
Semi-logarithmic paper, 半对数格纸9 {+ h- Z+ a7 K/ G; u" D1 L
Sensitivity curve, 敏感度曲线/ |- n2 s/ f9 d/ r8 h. ?3 J8 D6 k8 O2 y
Sequential analysis, 贯序分析5 B" G2 J2 z$ z+ d8 I, r: E9 g# l
Sequential data set, 顺序数据集
. p& z, n2 @% U. KSequential design, 贯序设计* Z% h3 A9 x. j* T
Sequential method, 贯序法
8 {5 D- B5 J) m% q6 z2 R" qSequential test, 贯序检验法
/ T( J/ p9 S. l9 k: u& TSerial tests, 系列试验" {+ P' p* ^% }3 H z9 i* h, D
Short-cut method, 简捷法
# l/ P$ H, U* J0 ]2 F$ pSigmoid curve, S形曲线
9 C& a1 O5 ^, k7 y! a7 F( dSign function, 正负号函数
8 H2 _' ~' }* }: G5 Z" ]& l0 `) rSign test, 符号检验: j" E: G: g0 N: |
Signed rank, 符号秩
; Z! M, D6 g5 G/ A, G+ \7 nSignificance test, 显著性检验5 U/ \$ ]7 D! E' ], C2 H
Significant figure, 有效数字
$ R& o% i$ Q' [; u' S% Y( HSimple cluster sampling, 简单整群抽样; E( _: g( W0 f- n
Simple correlation, 简单相关( y' A6 O5 e0 }2 d& y- J
Simple random sampling, 简单随机抽样( n5 E7 P/ `4 t6 e
Simple regression, 简单回归
# A& S) s% D- k6 C/ b! Csimple table, 简单表* t, m5 s5 ?' u6 C. q" n
Sine estimator, 正弦估计量6 P* G$ w$ U6 c3 ?4 {3 G
Single-valued estimate, 单值估计. D% S( Q! {$ V! s/ [6 V4 |, I9 o
Singular matrix, 奇异矩阵; w9 j% U" f- n y2 P; D5 \- i
Skewed distribution, 偏斜分布 w& V2 n8 a) k) k7 ?$ ^
Skewness, 偏度8 y5 U3 V6 g; |1 u
Slash distribution, 斜线分布
' n' S/ a+ E. |- QSlope, 斜率
( m/ L( a) `, c$ r$ k( a: L( cSmirnov test, 斯米尔诺夫检验! N- h5 @ G7 [
Source of variation, 变异来源
# ]2 r/ @. Y( w6 |* u5 y% K1 J- hSpearman rank correlation, 斯皮尔曼等级相关3 ]) g0 t6 a* Y
Specific factor, 特殊因子
1 {5 M/ a0 r0 d. ]( \$ k/ tSpecific factor variance, 特殊因子方差
, V2 d ?( g# qSpectra , 频谱
]9 f5 }! Z, Y/ Q y& i, Y' jSpherical distribution, 球型正态分布
5 ^/ p7 M4 I" G" f* VSpread, 展布4 K5 S2 z7 t0 d' x2 s
SPSS(Statistical package for the social science), SPSS统计软件包
5 {, }( p! Y: O4 e( l3 oSpurious correlation, 假性相关
' V. P+ G% R# fSquare root transformation, 平方根变换6 U" @. e, `- j0 W
Stabilizing variance, 稳定方差
3 O: B3 A p4 k) V- {Standard deviation, 标准差* F- K$ O D, j" k0 t
Standard error, 标准误
% ^/ F+ I: E3 a0 t* p- E! ^Standard error of difference, 差别的标准误! J' ^2 \" c$ ]$ @4 x
Standard error of estimate, 标准估计误差
/ I+ S/ M/ X+ r7 s% o) Z2 [Standard error of rate, 率的标准误
2 d- @" q- F! z' o. WStandard normal distribution, 标准正态分布
( s1 l1 K6 I. s9 M4 V) IStandardization, 标准化
) S; X( X& p7 ^; LStarting value, 起始值
8 O! a" L" V, Z7 O: w" D1 m# U+ RStatistic, 统计量/ C2 u- o. A( D
Statistical control, 统计控制8 p/ }6 t! R3 x" q# K
Statistical graph, 统计图
" n8 [! F9 y$ M: SStatistical inference, 统计推断* x3 p6 c4 O4 l% t- O5 i
Statistical table, 统计表
6 N, x) r% }: c+ wSteepest descent, 最速下降法
+ h5 v- j6 b" IStem and leaf display, 茎叶图8 y W' p, h/ [3 `' K* P3 A$ E. _
Step factor, 步长因子
+ g- m$ ^) A9 b$ h6 d- m4 Y; jStepwise regression, 逐步回归
8 l* G* x% q* O* {. B0 fStorage, 存: n2 a( W4 T- k: v2 S
Strata, 层（复数）
4 }/ K) f& j( V. WStratified sampling, 分层抽样
- @! R, ]7 F4 a& r- PStratified sampling, 分层抽样- m; r6 Y- _: t
Strength, 强度8 M( p9 a% J6 f, q q; Z6 l
Stringency, 严密性
9 y( s4 u/ T' \' N' g; ]Structural relationship, 结构关系
S9 J# r9 Y. {& }3 x) yStudentized residual, 学生化残差/t化残差
. D3 D7 f% S; zSub-class numbers, 次级组含量
- Y/ Y |1 h! x) XSubdividing, 分割1 L) n( v3 n) |# f6 a. ^
Sufficient statistic, 充分统计量. _$ ~0 y% y$ C
Sum of products, 积和
5 I+ V4 y+ g/ H1 z( r" B3 qSum of squares, 离差平方和
; V) O' S1 r) P6 F! kSum of squares about regression, 回归平方和
* t1 |" f2 d7 m- m4 ZSum of squares between groups, 组间平方和
8 S0 e2 ^1 K9 x5 |Sum of squares of partial regression, 偏回归平方和& n9 }. o6 @8 }( e! f! [8 P
Sure event, 必然事件4 V4 d z8 m6 ?2 m# e- U8 s
Survey, 调查
2 ?* a3 w& V( rSurvival, 生存分析- S6 }* X9 `# ^( l
Survival rate, 生存率
. @6 r6 E* S/ D5 eSuspended root gram, 悬吊根图2 [7 ~7 _& e) }: c
Symmetry, 对称" }+ V# f7 e) s, ^( w1 Q
Systematic error, 系统误差+ ~! {/ `2 e& h$ Z6 p
Systematic sampling, 系统抽样 u3 Q# e% e9 b$ ]
Tags, 标签
) f4 Y8 ~. L8 X. i( z, s, tTail area, 尾部面积
4 O% E- m9 Z0 ]( gTail length, 尾长
( L% F+ V- d7 O6 |9 KTail weight, 尾重
. r3 A! q. w# W3 v; p, L, ZTangent line, 切线
8 s- c. A2 L/ {/ }Target distribution, 目标分布: N8 c$ D1 _* R3 l' d2 T; p0 k) O
Taylor series, 泰勒级数
; T4 ?1 g' W* W; n) E0 D3 qTendency of dispersion, 离散趋势2 T& S+ U+ n( {
Testing of hypotheses, 假设检验8 M+ _3 K' P. l, \
Theoretical frequency, 理论频数
2 W3 u$ a$ V# G0 y/ [; n0 |Time series, 时间序列7 g: J0 I0 }. G2 @
Tolerance interval, 容忍区间
! N; c6 }9 V' UTolerance lower limit, 容忍下限3 T5 b: ~% ?7 n0 k
Tolerance upper limit, 容忍上限
( N1 A0 }' E" I( i& j: e2 Z3 UTorsion, 扰率) F c/ A" J( Q$ } D, n2 U
Total sum of square, 总平方和
( P- W; c5 Z3 l; ^) DTotal variation, 总变异- n$ _- E& f2 M2 O# g
Transformation, 转换
: _1 ]- e3 h" d( Z( d( `, O- ETreatment, 处理; o2 K$ z/ M: R$ \/ s! Q/ J, j
Trend, 趋势) a' p# w8 d+ @4 F
Trend of percentage, 百分比趋势( o; r' |1 v. V$ _8 U* J7 s- W( F
Trial, 试验7 Y" s+ ^: B$ j
Trial and error method, 试错法6 Z* }1 W9 O4 q6 f7 u' @
Tuning constant, 细调常数" I- f3 d! E* ~5 j( b* O
Two sided test, 双向检验% g; y+ J1 r4 y- H" _7 T7 D
Two-stage least squares, 二阶最小平方
: P: g G, L% j6 [/ X2 YTwo-stage sampling, 二阶段抽样
; V! T' \( J! DTwo-tailed test, 双侧检验
9 F/ \ |5 v7 W8 M, W, [Two-way analysis of variance, 双因素方差分析
' t) R: }7 G! G \ O. f4 E: ETwo-way table, 双向表
5 |; b9 f: l0 b& i) `' JType I error, 一类错误/α错误
* k" |: z9 F6 r3 S2 Y1 N2 KType II error, 二类错误/β错误
% [ R/ C" u7 w2 ?: G2 ^: j1 vUMVU, 方差一致最小无偏估计简称- A% c2 P s: f! Z
Unbiased estimate, 无偏估计
6 P# l5 Z& E! \' t9 lUnconstrained nonlinear regression , 无约束非线性回归( {) P5 g! @1 R2 u: y6 ?
Unequal subclass number, 不等次级组含量
, I0 @: o# I$ i! D2 {8 z4 JUngrouped data, 不分组资料# |, m/ E# |9 {) k
Uniform coordinate, 均匀坐标
% W" ]% G+ p/ ^; H# S: k1 N& g+ eUniform distribution, 均匀分布
6 @% l' N! [4 W2 j1 q1 Z$ f# c [Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
, k3 A. Q3 P+ NUnit, 单元
& G7 Q; c' ^- S, j/ p( ]Unordered categories, 无序分类2 X9 s3 q" G% U0 G/ \
Upper limit, 上限3 p! @; @! ?6 i) C" W
Upward rank, 升秩
: S7 B; R4 _1 Y2 c% {8 j9 c# {Vague concept, 模糊概念
$ B: ]0 m: m9 V3 K5 [! ]3 ?) WValidity, 有效性3 t. y9 g9 N6 P+ w% k3 {
VARCOMP (Variance component estimation), 方差元素估计
# n3 f [1 i* D+ V/ ~Variability, 变异性
6 i) x) G0 D- [- V( f9 S; ~Variable, 变量2 c, r. ~! v+ [
Variance, 方差& \2 o, [2 e$ ~8 f" W6 e# k# L
Variation, 变异
7 g% D. ~+ N) IVarimax orthogonal rotation, 方差最大正交旋转
& ]& ~8 L- B) z& E& c$ m0 DVolume of distribution, 容积
& Z; A( S0 R0 z4 ?& P( K% gW test, W检验
' s6 B& i8 B' D# B$ U3 NWeibull distribution, 威布尔分布+ _/ u6 n9 |8 B, Q# \# A
Weight, 权数( c$ ?" Q1 B1 V& y' ]6 z
Weighted Chi-square test, 加权卡方检验/Cochran检验+ T6 l# j) T' t/ g1 f
Weighted linear regression method, 加权直线回归: {5 R+ H8 k$ p7 l
Weighted mean, 加权平均数, D7 H$ Y. }; F# d S
Weighted mean square, 加权平均方差) {0 h" P, d9 A! J
Weighted sum of square, 加权平方和
# h9 ~5 i! G: }/ O2 cWeighting coefficient, 权重系数+ W% [! n% p8 N2 t$ a/ ^
Weighting method, 加权法
4 f9 @9 W, Z4 ]" L' uW-estimation, W估计量$ S" K1 w; \6 Z; [
W-estimation of location, 位置W估计量' [1 ]) }3 t+ }/ B+ ^! l
Width, 宽度! Z8 B) b- S+ K0 z4 ^8 C
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验9 i- r5 f: ~! v6 x
Wild point, 野点/狂点
, @7 N& x3 Q0 K, r6 A3 a4 YWild value, 野值/狂值/ }+ F9 U8 p; P2 L4 L
Winsorized mean, 缩尾均值8 F$ M9 A6 b. Z/ N( H
Withdraw, 失访
$ d( r; L+ h' A/ a* l4 Q& D1 SYouden's index, 尤登指数$ k1 O& T& m0 @1 X
Z test, Z检验$ a: @% j# n) X* _" R9 _
Zero correlation, 零相关
/ V& [! u8 v3 C7 u" n0 MZ-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
