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[社会调查] SPSS软件中英文对照词典

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发表于 2009-1-6 22:05 | 显示全部楼层 |阅读模式
Absolute deviation, 绝对离差% c6 C# x0 V: \, _: S) X$ |
Absolute number, 绝对数
4 I0 x( r- \/ }. r& R+ w+ E* tAbsolute residuals, 绝对残差3 F: _" L" h& C% s2 x- c+ i, L
Acceleration array, 加速度立体阵
; t9 u7 e, D- kAcceleration in an arbitrary direction, 任意方向上的加速度; U% b' e4 D8 A' ]: m+ |6 K
Acceleration normal, 法向加速度
' r7 U% z5 b! B5 k3 B5 EAcceleration space dimension, 加速度空间的维数
0 ]! F8 j1 s4 uAcceleration tangential, 切向加速度
& T, h8 |* W- O/ HAcceleration vector, 加速度向量  p( N& |% @, ?, K
Acceptable hypothesis, 可接受假设; N/ f$ ~5 \5 `0 N: X# I
Accumulation, 累积7 H2 z  y# Y% i  \# q* H
Accuracy, 准确度3 P, }/ J4 v7 i( W
Actual frequency, 实际频数! V' c7 l; I% u# E: m
Adaptive estimator, 自适应估计量8 U9 Y* t3 d% K# R2 Y* ]
Addition, 相加
$ q1 K* m* e" Q2 Y+ LAddition theorem, 加法定理
: f) A. R8 Y, UAdditivity, 可加性
7 f' h" S! Y/ C% m( w' ZAdjusted rate, 调整率. z: c) w. {  ~. H3 U
Adjusted value, 校正值
# J- k, H! u1 i) D8 KAdmissible error, 容许误差
* N- {3 j% R9 ~) P$ d; \$ VAggregation, 聚集性
2 g# C* o) p2 d" WAlternative hypothesis, 备择假设
& I3 L2 W7 ^$ O9 [- eAmong groups, 组间9 C' a8 U+ x/ R0 r
Amounts, 总量
& Q% _1 `* H1 I, ]  a9 u" j! u) XAnalysis of correlation, 相关分析, _  N4 t, _; _
Analysis of covariance, 协方差分析
- I1 M' {5 }) ?5 z, g+ V9 s" R1 iAnalysis of regression, 回归分析- w& u# G, R! i7 w3 J
Analysis of time series, 时间序列分析: D! E% j  K. q$ P  ^
Analysis of variance, 方差分析
( d" q3 m3 ?% F, Y4 D8 s9 HAngular transformation, 角转换
3 y5 q# E6 l) Y. y5 Q7 m0 `, fANOVA (analysis of variance), 方差分析; G2 H% ~+ K/ U% X' \
ANOVA Models, 方差分析模型
! d5 k9 g9 |: AArcing, 弧/弧旋
1 S! o! u0 T+ a2 w! s% Z$ u% DArcsine transformation, 反正弦变换( d8 ]; K8 L. c% p" N
Area under the curve, 曲线面积
/ l- y" [, Y5 {% b+ C4 ]( c. XAREG , 评估从一个时间点到下一个时间点回归相关时的误差 ) Y8 \0 C" e6 x( X8 U
ARIMA, 季节和非季节性单变量模型的极大似然估计 : b+ w- c7 H$ s- m* r- @3 ~/ a
Arithmetic grid paper, 算术格纸
% D5 V" \& L9 c5 H: }3 W# L+ NArithmetic mean, 算术平均数
, O+ K" O6 O+ h% V- K/ AArrhenius relation, 艾恩尼斯关系: H- q8 b' \* }* j2 g
Assessing fit, 拟合的评估  v: E9 h! C4 Z0 Y8 f5 x- U
Associative laws, 结合律7 g7 v& i1 }1 t9 a2 U' _4 S0 B/ f
Asymmetric distribution, 非对称分布
  h$ P) I- g) p2 {Asymptotic bias, 渐近偏倚
$ \& A- H' X6 ^2 {$ g/ n3 h2 xAsymptotic efficiency, 渐近效率
0 a! E* s; A! V& h6 x( ]. }Asymptotic variance, 渐近方差+ ?4 K( O; P# ^6 F. {9 z2 H
Attributable risk, 归因危险度2 F- e+ R; Q% p' c8 K# Y% o' @+ ^6 D
Attribute data, 属性资料1 V8 I5 n, v$ l5 H
Attribution, 属性
( F8 R1 m8 J. C( [4 V# A, `' ]Autocorrelation, 自相关" e/ y6 N' p0 E9 F, U$ V
Autocorrelation of residuals, 残差的自相关
9 J7 [" F+ H) l  MAverage, 平均数$ v. D+ N3 f. `! `7 p+ c- A- N6 g
Average confidence interval length, 平均置信区间长度
6 [3 F2 V: C" v- N7 S  }+ \Average growth rate, 平均增长率5 c( a6 o! _5 p9 Q3 c$ Y
Bar chart, 条形图
: c$ B1 R; Z' W# `' B2 K* y0 S7 B* EBar graph, 条形图6 j/ p$ p$ a1 a
Base period, 基期
& t8 u- Y( z; G, p/ D" ^( R; |Bayes' theorem , Bayes定理
1 u' y$ L- z( q6 [5 p8 ?Bell-shaped curve, 钟形曲线$ c3 D7 J( ~# h0 P/ d
Bernoulli distribution, 伯努力分布" J) }2 Z  G; B: E, B1 Q
Best-trim estimator, 最好切尾估计量
5 d: Z# W/ v8 W' xBias, 偏性3 y7 s8 o" X0 @1 C/ R& q% }" x: j# x$ Q
Binary logistic regression, 二元逻辑斯蒂回归
5 k6 r, X, }+ EBinomial distribution, 二项分布! C& P, U8 W# w
Bisquare, 双平方+ @4 S  I2 [/ M# M* B
Bivariate Correlate, 二变量相关
: L" P8 D+ u# H  H9 O3 w7 IBivariate normal distribution, 双变量正态分布
& j# }$ A5 o5 E/ CBivariate normal population, 双变量正态总体
1 k# M9 Q2 V; a5 oBiweight interval, 双权区间
, f. z; m1 y( y" v# w* \Biweight M-estimator, 双权M估计量
; O# s/ Q# j- J. E. c4 lBlock, 区组/配伍组" q( G4 O7 ~$ z% z% H: Q+ Q4 p' M
BMDP(Biomedical computer programs), BMDP统计软件包
" k( X7 J5 o+ a$ A/ U! m: ?Boxplots, 箱线图/箱尾图
# s+ C% \9 ?% A: P0 j. |9 F2 e4 `Breakdown bound, 崩溃界/崩溃点$ y3 G" p, k) B7 ~
Canonical correlation, 典型相关) t/ T, G6 W5 ?, `
Caption, 纵标目
6 k7 C  I' V: j3 g$ ]: SCase-control study, 病例对照研究
5 x+ K) E3 y# S7 f/ _  ZCategorical variable, 分类变量
9 F% @6 i8 a% n9 H7 [Catenary, 悬链线
! j, }" K3 f$ NCauchy distribution, 柯西分布0 b9 h' l4 B; @4 r- r) i  ?
Cause-and-effect relationship, 因果关系' t/ e5 [! b/ s8 _: o- E' U' g
Cell, 单元# k3 T3 h+ E; f
Censoring, 终检' z  q! ~, R. p5 f9 m: v
Center of symmetry, 对称中心
9 I6 Y, @  }- _& SCentering and scaling, 中心化和定标
9 W( S9 M! ^( V6 a) ECentral tendency, 集中趋势
4 n. d) F# A7 M+ s, B7 ICentral value, 中心值
; U+ J8 p- W5 B3 yCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测. \) l" R& b, ]% t
Chance, 机遇
: J( ?  p' l; bChance error, 随机误差
- P7 k( `& y+ m+ J. FChance variable, 随机变量. A; T: Y6 Q5 ]  S
Characteristic equation, 特征方程
  _/ }, K) _# b6 g. e* g7 W- hCharacteristic root, 特征根) x2 [- L6 c  w4 Y9 R" U
Characteristic vector, 特征向量
$ u; ]5 p' x3 NChebshev criterion of fit, 拟合的切比雪夫准则8 h! |+ D! N5 D) u1 x4 M
Chernoff faces, 切尔诺夫脸谱图
4 K1 n7 r, b/ \  h  n' C' b5 GChi-square test, 卡方检验/χ2检验9 t! u: k# L" ~7 o) D; W, r
Choleskey decomposition, 乔洛斯基分解* a- O6 E- x, l6 P2 ~7 k
Circle chart, 圆图 ) z  q3 r: e3 s; K" V7 ]( R
Class interval, 组距
% Q# B9 Y; y* H6 ^6 x6 y& G0 kClass mid-value, 组中值
! I0 C" q" A1 J2 dClass upper limit, 组上限9 F0 i. a# [. D# g6 }
Classified variable, 分类变量
% n4 A% R3 x8 z  H5 r- yCluster analysis, 聚类分析6 T  T; g; Y; a2 u5 H  _
Cluster sampling, 整群抽样( f* z  _6 f- P% g6 \. |) R
Code, 代码
, x6 g0 N* L* t6 T1 g% p  E( ECoded data, 编码数据7 v; d$ c5 C! V
Coding, 编码; Z1 s6 H# t7 F, x, G/ c% r
Coefficient of contingency, 列联系数7 j" S8 l: M7 @2 W. y$ u
Coefficient of determination, 决定系数
$ n# E% r* c" a. O9 w8 E5 A; |1 ?; U6 mCoefficient of multiple correlation, 多重相关系数
* U) R% e. J* F! L6 n5 h: B6 y; VCoefficient of partial correlation, 偏相关系数2 r/ a6 K& k, K/ `) r
Coefficient of production-moment correlation, 积差相关系数
' `, Z  u7 B- N. bCoefficient of rank correlation, 等级相关系数
/ `. z1 t! f! w1 ?- bCoefficient of regression, 回归系数
6 w. [; W1 O* g8 C" {! {Coefficient of skewness, 偏度系数! _; q" V4 B1 m) ?6 t
Coefficient of variation, 变异系数- m6 P* L6 ~- r
Cohort study, 队列研究
! l4 |  w3 b, g  H9 n6 M5 EColumn, 列; i5 [; {& Z& R" M( i% z# T- b4 C1 y
Column effect, 列效应
2 b- H! L2 D( i! E5 ?$ gColumn factor, 列因素  G, D+ f4 `1 m: l2 E
Combination pool, 合并
/ {) h2 a8 l' J" _* O) c, K* BCombinative table, 组合表5 g3 t( G3 G% z2 X3 D- [
Common factor, 共性因子9 i: y+ ~2 u7 W, N/ A, z
Common regression coefficient, 公共回归系数  e/ |; z6 W" d" a" F& i
Common value, 共同值
: N5 P6 X1 C& P9 l6 r: BCommon variance, 公共方差
2 }* E2 A/ m5 Q/ I  w3 FCommon variation, 公共变异( i- ]  k8 }) K& `$ |+ i
Communality variance, 共性方差2 p% D# N0 D; H+ U" E
Comparability, 可比性# P) p7 w; Q, q$ W* k
Comparison of bathes, 批比较- p+ c$ C( A; z
Comparison value, 比较值, D2 P; z9 B% ?2 a
Compartment model, 分部模型
( k0 r6 M3 H) G$ z6 N# m+ QCompassion, 伸缩% t( T, j' k8 ?9 b4 B
Complement of an event, 补事件# g4 ]3 X9 s: H2 O5 s( X
Complete association, 完全正相关+ w+ u8 ]3 A4 t5 A. Q
Complete dissociation, 完全不相关2 t( R5 K! a/ i. ~
Complete statistics, 完备统计量
( R  J3 H! X' G; f4 ?Completely randomized design, 完全随机化设计
) r" D3 y, }: T6 g% `4 u, PComposite event, 联合事件8 ~4 d: w* q: _2 A& C9 i$ _
Composite events, 复合事件
8 z! h9 z0 h) O* G% R" C: u& k0 ZConcavity, 凹性$ a! m% V) u& U
Conditional expectation, 条件期望( T: m4 o1 }9 n- {) h1 v; E2 p
Conditional likelihood, 条件似然  [7 A1 J3 ~' \. H
Conditional probability, 条件概率/ o; m$ l+ E/ U: P' `9 a
Conditionally linear, 依条件线性
: N3 @! ~$ e+ ~3 A/ k0 f# k+ DConfidence interval, 置信区间+ k; s+ }8 W5 y0 l9 T
Confidence limit, 置信限  i+ c( W, H* Z, K. v# H# B! K
Confidence lower limit, 置信下限
( \  u1 }) }7 t- `% Q# [2 A  oConfidence upper limit, 置信上限
) w1 q0 S5 _# a* a5 X0 s4 xConfirmatory Factor Analysis , 验证性因子分析
- [( @0 i5 r" k2 y) @2 p% H: U. ZConfirmatory research, 证实性实验研究
4 L9 r; {: p) c$ n& |; ^" e( iConfounding factor, 混杂因素4 W0 G7 M4 p& t5 K; b+ G: @
Conjoint, 联合分析- T5 {1 L& B1 n2 f! m
Consistency, 相合性6 ?- L& ]# [2 |+ j7 D; J
Consistency check, 一致性检验
# f' ?, r' G6 m8 m" QConsistent asymptotically normal estimate, 相合渐近正态估计" `/ V+ ?& Z  E$ B9 j- A6 Q0 ]
Consistent estimate, 相合估计8 K0 n* c/ T3 I7 Z1 A
Constrained nonlinear regression, 受约束非线性回归
* M4 Q7 k& b4 \7 F$ FConstraint, 约束
0 N% ~( F9 d7 S7 m& kContaminated distribution, 污染分布
9 k7 W- A) u! ?4 f9 b- Q( FContaminated Gausssian, 污染高斯分布6 o8 K/ |. x9 ^, M
Contaminated normal distribution, 污染正态分布" R1 ]" h! q6 f' a0 G! @# G
Contamination, 污染3 V& c4 t$ C: E
Contamination model, 污染模型; E. L. g( a) p
Contingency table, 列联表
7 T" `2 q+ J# x8 t! bContour, 边界线1 U1 Y( l+ d! x
Contribution rate, 贡献率) x7 }- |7 w1 @+ y/ L" Z# O. y' S% M
Control, 对照6 p/ U/ u! {2 U5 N# H/ L9 b
Controlled experiments, 对照实验
2 A1 x% R% o' [2 U6 x7 p6 [  MConventional depth, 常规深度  S! R  I5 Z2 g8 z# E: O
Convolution, 卷积
% k, N7 m) c: G# g6 QCorrected factor, 校正因子& Z, `6 h/ \) M$ c! `
Corrected mean, 校正均值
( _( k1 f" T* r% gCorrection coefficient, 校正系数
( z3 j; Z% g3 N* K; y( v$ KCorrectness, 正确性- T, e0 ?8 C& s. @5 I4 t- J
Correlation coefficient, 相关系数9 g6 Z. p' ~" a2 w
Correlation index, 相关指数1 B3 W) D3 ?: i' \- C/ h' I
Correspondence, 对应" ?" k% q+ @; P8 N/ L
Counting, 计数
8 m' ?: C# f# Q) n. W- S! UCounts, 计数/频数" d  t# o" `& m5 |. S
Covariance, 协方差
/ {' N. f- A: V8 j5 y- cCovariant, 共变
; N/ K" _! V# aCox Regression, Cox回归, [9 y' C) X' ?" Q0 K
Criteria for fitting, 拟合准则
4 c4 i+ N* g( C1 C  ]# X- HCriteria of least squares, 最小二乘准则" a4 m5 a5 B( g; |% ^/ a
Critical ratio, 临界比9 z! J9 S" `/ P
Critical region, 拒绝域
3 v/ U8 ~& n# W* |6 ]/ CCritical value, 临界值
, t' x! t- g! L+ g; B* uCross-over design, 交叉设计
% ?; K3 M, L0 ]8 N. B0 `Cross-section analysis, 横断面分析
5 c$ C4 [! T4 `) c) A1 w0 MCross-section survey, 横断面调查% O* o9 i8 V, I7 D# z$ z7 [( E
Crosstabs , 交叉表 ' R) j  j* ]" o0 X. |6 l7 r! |
Cross-tabulation table, 复合表
" F9 |) }6 i3 r/ C& q8 P2 X) uCube root, 立方根( \8 ?2 g  _, q6 }! E# \# L: z
Cumulative distribution function, 分布函数
4 q" y. ~! o# S( ^) ^Cumulative probability, 累计概率
9 p# M) ]  ~; U8 S. V  U/ RCurvature, 曲率/弯曲5 O* Q8 \3 L! q: m5 R# a
Curvature, 曲率$ B) v  U& H3 s. p( j6 S
Curve fit , 曲线拟和
  h$ @, R  k9 A/ P% ^Curve fitting, 曲线拟合
& o; a) o' H6 x3 ~4 CCurvilinear regression, 曲线回归( g0 a; `  D) C$ t( m2 d. C8 X1 f
Curvilinear relation, 曲线关系
$ K/ ~- N$ r* y! Z4 X# F7 C# qCut-and-try method, 尝试法( e0 x7 x+ J8 Y
Cycle, 周期2 P4 K- ?% s0 Z+ \/ H
Cyclist, 周期性
  S  U, t( {  c8 {7 b- G5 QD test, D检验
4 n5 L* n* Y' g& `0 [Data acquisition, 资料收集3 z2 q* s( V& Q) p) W3 W9 F
Data bank, 数据库
* o  Z  R: h3 m' S( I* q$ pData capacity, 数据容量
& g3 m/ Q( R% R9 y2 LData deficiencies, 数据缺乏% |$ b6 e% Y2 @+ P& i) j: o
Data handling, 数据处理
4 u0 A- a* w7 H7 h  T3 W, QData manipulation, 数据处理
# e9 m4 P5 k# rData processing, 数据处理
+ }% W9 N5 |! x* Q0 Z( wData reduction, 数据缩减
. z; h8 e/ z" u( {: tData set, 数据集
# t4 O. j* o; r8 _Data sources, 数据来源
' X9 T% m: p" [  d2 b4 pData transformation, 数据变换
3 v% _5 a- ?" G7 U! {9 o( zData validity, 数据有效性
- s$ Q: g! ]% O% P8 B. NData-in, 数据输入
- Z6 R! F1 [9 q9 GData-out, 数据输出
5 P; L# R2 K  J( f7 Z! BDead time, 停滞期
$ C9 q' |4 H3 P& D9 fDegree of freedom, 自由度
/ x- \7 I+ i% i; p; W/ nDegree of precision, 精密度& m& {2 n( j, e, d
Degree of reliability, 可靠性程度
& l1 a' D8 x( i; {2 BDegression, 递减6 |$ [/ j6 N7 ~" L; @$ R' o
Density function, 密度函数
7 S) V+ V! v8 o0 v( Z  HDensity of data points, 数据点的密度- K& k- O/ h0 H4 _- z2 P
Dependent variable, 应变量/依变量/因变量
* R' x; R! B; D& x4 H$ i. j) c) b$ oDependent variable, 因变量, j& a+ ?( p$ `" Y8 F* y
Depth, 深度0 e6 @4 X- r+ q) M, [6 e7 r' E& U) L
Derivative matrix, 导数矩阵
$ e1 w+ X& Z7 G3 nDerivative-free methods, 无导数方法
0 L$ s# A0 n, a& X0 W* YDesign, 设计
$ `) ?1 N* G4 c" HDeterminacy, 确定性
7 M- _! |  d! [5 _Determinant, 行列式
& q' c8 T" t( f; _; a: `Determinant, 决定因素- S" t6 L" E0 W) B, J' C; ^
Deviation, 离差
7 [' I5 v2 I" I# Z' \! N0 B" e2 eDeviation from average, 离均差3 n' l; j1 J) q: d( H. l/ V7 ~+ C
Diagnostic plot, 诊断图; _  ~$ n4 L) v" K( ?# w* Z. D, W
Dichotomous variable, 二分变量4 T" V. R3 s) e
Differential equation, 微分方程
- |) e+ v: X7 WDirect standardization, 直接标准化法
/ s+ M, e2 S3 P. _, i% z( W4 P- d1 \% W' LDiscrete variable, 离散型变量
& n0 L+ p; m( d( }DISCRIMINANT, 判断 3 {% D. l% v8 s* Q( U/ _
Discriminant analysis, 判别分析
# E2 p4 }) O) A% w" I" }0 ^! c% w# xDiscriminant coefficient, 判别系数
5 }: E! x" F7 I0 Q+ v) N0 tDiscriminant function, 判别值
  J" e" r8 {; P; W4 _* c, |0 ODispersion, 散布/分散度
6 F% \" Z* c8 b2 ~! y" N2 g6 ADisproportional, 不成比例的( X1 i# L1 \6 W
Disproportionate sub-class numbers, 不成比例次级组含量& y- q6 r" O8 [! k& m
Distribution free, 分布无关性/免分布
+ `& ^  h5 z8 N. L* fDistribution shape, 分布形状5 p- ~8 b. l7 t% b& @% c1 R
Distribution-free method, 任意分布法
0 V! G% o2 |6 ~5 |; h! v6 wDistributive laws, 分配律3 N% n% I& z3 }& o% N
Disturbance, 随机扰动项
8 l7 X1 n) H0 `% MDose response curve, 剂量反应曲线4 j7 O% B2 Q0 e0 p4 a7 N0 h
Double blind method, 双盲法
) q' i3 d0 B% L- p3 FDouble blind trial, 双盲试验
3 S" I6 u  f$ N( y* F- @Double exponential distribution, 双指数分布
' v# F9 K+ `  _- Y7 m- F! jDouble logarithmic, 双对数5 [- ^1 L6 A8 T( l# \2 l/ s! _
Downward rank, 降秩( e. X0 g% p$ _$ d1 v; x
Dual-space plot, 对偶空间图
+ t) d" B4 L3 N* FDUD, 无导数方法
1 X3 s5 B8 f; i2 H, IDuncan's new multiple range method, 新复极差法/Duncan新法/ C: B  u! N0 u
Effect, 实验效应
6 L! ^. y9 E2 T0 xEigenvalue, 特征值0 ]  G( O5 D6 e% s, o+ U
Eigenvector, 特征向量
4 W7 k' H* D' `- f% oEllipse, 椭圆( ?, j" G* _, _" O" s9 w
Empirical distribution, 经验分布
$ G8 ^+ |9 ^$ F6 n# q* ^) _) REmpirical probability, 经验概率单位
1 t7 {8 z: _3 }7 T7 O$ ]* J; D4 fEnumeration data, 计数资料0 I$ j4 _1 C: u. s
Equal sun-class number, 相等次级组含量$ I0 \5 v8 A* Z! z! V; f  T
Equally likely, 等可能/ b" n3 V; J1 q4 O
Equivariance, 同变性7 T/ |* [5 o7 B
Error, 误差/错误' C, I7 L! K; ]. f, s4 Y6 ^
Error of estimate, 估计误差* S! ~& d4 Z2 C) Q& {& N
Error type I, 第一类错误, R0 q& J* ?" V1 K
Error type II, 第二类错误
& x2 Y1 i1 K& m  ZEstimand, 被估量
' _% z; o9 d- _4 d7 EEstimated error mean squares, 估计误差均方: `! _' c% K5 Q  A  ]  f$ G
Estimated error sum of squares, 估计误差平方和; T5 G" Z6 }' V$ e4 q0 w, M4 a
Euclidean distance, 欧式距离
1 c* q6 E. O# C+ |4 CEvent, 事件5 d! v) @8 Y% Z% N* n5 a# j
Event, 事件* x! ?: T# l* t, _8 d/ s
Exceptional data point, 异常数据点/ C. i9 a, p' X9 R6 ~7 n
Expectation plane, 期望平面
( d+ y8 a6 J- X: ?7 R2 ?9 Z/ TExpectation surface, 期望曲面* h8 x/ I& f7 ?2 ?$ a/ ~! v0 i) ?- O
Expected values, 期望值
/ I0 j/ h! B: v, \9 F% uExperiment, 实验
0 K; w9 Z: H1 X6 o' t6 q' }5 \Experimental sampling, 试验抽样, O8 h9 \! [' c1 C& `- c& j! W
Experimental unit, 试验单位3 _, o2 J6 F" a! s/ r
Explanatory variable, 说明变量) f$ e' y; v9 ?3 X& r
Exploratory data analysis, 探索性数据分析1 w/ g( h# @% i* n
Explore Summarize, 探索-摘要
" x% d2 K8 a2 t' Z3 k( wExponential curve, 指数曲线
0 F6 I# R% c; d- M, A/ Q) B& ]Exponential growth, 指数式增长9 }/ C% X! n( e4 p
EXSMOOTH, 指数平滑方法
% I+ E5 M5 B8 r, H4 g! ?, J/ oExtended fit, 扩充拟合
4 n! n1 y; m( X" {( c8 u6 m' h+ h$ hExtra parameter, 附加参数" P0 g9 [1 Q: Q' x3 j
Extrapolation, 外推法
9 V& M0 {. R4 r& S8 dExtreme observation, 末端观测值
5 S; G# V; J4 h; `3 b/ I+ {Extremes, 极端值/极值8 k( h+ m" R7 N% W1 |& M0 z
F distribution, F分布: r. n7 M1 ~4 |
F test, F检验  {+ C' G( h! X$ Z' T- m
Factor, 因素/因子
4 j& h) u, ~. P; r# y5 l" x; {Factor analysis, 因子分析, F. j  m0 V) S- y# d: [6 @
Factor Analysis, 因子分析0 E: t) @4 C. @% W9 z5 x: c$ e
Factor score, 因子得分
  f! G% B0 F; Q+ C; f( D* UFactorial, 阶乘
5 E" B" |# w5 ~- n3 lFactorial design, 析因试验设计
6 l# y6 ?9 E$ \False negative, 假阴性
3 A0 w2 D  D4 S8 @- R4 a* YFalse negative error, 假阴性错误
% {' r8 A9 T% A, h0 a* v$ mFamily of distributions, 分布族
5 ?# Y/ K3 C4 s: P* b, L) q+ @. ^Family of estimators, 估计量族' m% b7 ]. ~" X! V6 m
Fanning, 扇面! I+ d7 @+ o3 \! F% i$ b
Fatality rate, 病死率
' b# F0 M( `/ w' I) L4 o9 G1 k6 UField investigation, 现场调查
* r& k8 _9 b2 V% f; H3 B2 @, {2 uField survey, 现场调查/ `# }! {4 R* Z1 Q/ f- {4 d. Y
Finite population, 有限总体" z4 C" H! a# O
Finite-sample, 有限样本5 Y. V5 u" z  o- e$ L
First derivative, 一阶导数
" r! V4 x9 ?! B# \! ]! s. MFirst principal component, 第一主成分
" o; h. h! \, v' p# IFirst quartile, 第一四分位数. P) t$ @7 ]4 j" M, B3 b& @# y2 q+ G
Fisher information, 费雪信息量
1 y" }% V& u1 z, I9 TFitted value, 拟合值+ [, h$ l+ c3 p4 k4 |) \
Fitting a curve, 曲线拟合
) c2 z  w0 X* S8 I7 B; WFixed base, 定基# L# J: }2 x, u% d, W5 W
Fluctuation, 随机起伏* N; X! p5 U% L8 u
Forecast, 预测
8 P7 g3 f0 ^# v! _Four fold table, 四格表
! G( d; }+ k& B; iFourth, 四分点' H0 ]% N% H( ^0 u$ [8 l
Fraction blow, 左侧比率( q8 t; v4 }$ k) n
Fractional error, 相对误差
1 B  |. Q& m0 \# g9 n* QFrequency, 频率
1 b; D! n" B) y. ~7 I* PFrequency polygon, 频数多边图
3 g( _& {+ d/ p2 b  iFrontier point, 界限点" }: H; s( }1 d: \: u0 Z
Function relationship, 泛函关系4 V& R" z" @0 ]* s
Gamma distribution, 伽玛分布. Y! T+ z- i1 v
Gauss increment, 高斯增量
% u8 z, p: t3 c% `$ `Gaussian distribution, 高斯分布/正态分布
' @' \/ ~3 S6 j9 @; i2 U# VGauss-Newton increment, 高斯-牛顿增量
3 X7 E% b8 n: y" X0 jGeneral census, 全面普查$ l" V% a) f- O! e9 A
GENLOG (Generalized liner models), 广义线性模型
3 W6 }& U+ P+ X  h- R/ l' eGeometric mean, 几何平均数
- m+ B9 f, v; Z% ], w: bGini's mean difference, 基尼均差' C6 R4 j1 k8 H0 D* o/ u2 x& Q2 ^! b
GLM (General liner models), 一般线性模型
9 a9 g$ W3 R  |$ ]7 N6 K  RGoodness of fit, 拟和优度/配合度: ]! n! Y# p- G5 ]  e1 z
Gradient of determinant, 行列式的梯度! x+ x1 z) ]& b# B$ G! [
Graeco-Latin square, 希腊拉丁方
5 r' e) L, |! [Grand mean, 总均值; @6 I4 ~9 F5 @) O
Gross errors, 重大错误  a* b8 K: \! S; @2 M- z! e
Gross-error sensitivity, 大错敏感度
% X/ \, a) \. |7 LGroup averages, 分组平均( k* T; f7 ?" ?& [
Grouped data, 分组资料
+ @9 c6 o5 @. Q. XGuessed mean, 假定平均数3 ^3 _! ~/ _8 Q: W
Half-life, 半衰期' Y9 Q. Z( O* G" i
Hampel M-estimators, 汉佩尔M估计量
* H- l/ S+ b3 C, ~Happenstance, 偶然事件* @% H6 m- }7 p9 i, H
Harmonic mean, 调和均数( Z3 h+ v4 {0 p, W/ V1 O
Hazard function, 风险均数& W$ j2 s+ _: B2 i6 B; i1 X
Hazard rate, 风险率* t$ G5 y1 c* {7 A
Heading, 标目
. E* |. q: o; V5 e( lHeavy-tailed distribution, 重尾分布% L: b1 J* B* A+ O% p; `/ o' ?) c+ \6 s
Hessian array, 海森立体阵
; N! |/ Z- }+ `+ p( \Heterogeneity, 不同质
! u, p3 H9 K+ {- I, ~Heterogeneity of variance, 方差不齐 1 P6 m; p2 c% q& N$ ?/ \- p$ c
Hierarchical classification, 组内分组( r% _! |" b5 p& N# ~( j
Hierarchical clustering method, 系统聚类法
5 M' ^4 h& y# E; B  a$ fHigh-leverage point, 高杠杆率点
  [4 j# S4 }1 j$ S, y, @HILOGLINEAR, 多维列联表的层次对数线性模型
  r' C+ \1 N; L. R9 n8 U% u2 VHinge, 折叶点
$ |* {% ?6 s) I% i) T& z* AHistogram, 直方图
& q0 J: J2 D- G# eHistorical cohort study, 历史性队列研究 / W2 P% W8 h. q8 x! O
Holes, 空洞
  G5 ^$ I. E7 ~HOMALS, 多重响应分析+ U) B3 T* A( U: |
Homogeneity of variance, 方差齐性
+ x, J- P' m% P4 U. F; E+ ]1 WHomogeneity test, 齐性检验
' d6 k- S, j6 U/ G4 Z/ @1 k# K% kHuber M-estimators, 休伯M估计量
3 D& m9 k& G  dHyperbola, 双曲线, H% A1 {/ ?3 ~: D
Hypothesis testing, 假设检验
* R( d2 s7 A! o+ Q2 yHypothetical universe, 假设总体+ E$ x0 r6 w! D. _' [' _+ P6 n: [
Impossible event, 不可能事件
( Z8 C5 S* n& h1 R" EIndependence, 独立性2 K6 h+ X: N# x9 D6 W# k; k, r
Independent variable, 自变量
* x' C; n  y! t! @% LIndex, 指标/指数* }0 k, N5 F5 U- A! m  z0 y, X  ]# w
Indirect standardization, 间接标准化法
. U& u& l; t9 Z$ \! j5 PIndividual, 个体# M0 ?5 B) s0 Z! Z8 P0 _
Inference band, 推断带, }. z2 z8 t/ A
Infinite population, 无限总体! m9 v6 ?% r8 u
Infinitely great, 无穷大4 d# `2 m6 [) n7 @" z# k+ |/ a
Infinitely small, 无穷小5 f! I' g3 ^7 l) w  s( o
Influence curve, 影响曲线
3 f+ E* E5 @6 E9 Z. FInformation capacity, 信息容量
# ^! k6 E: ?- B. ~1 l, p- ?Initial condition, 初始条件
+ M- W! H4 J1 i& X1 ZInitial estimate, 初始估计值( A! s: w2 F3 R) i" k  s
Initial level, 最初水平
! [3 \7 b+ ?! ~' p6 ]8 ^Interaction, 交互作用
' z5 U, U+ E! ^4 k" CInteraction terms, 交互作用项, e3 ]% w; p# |' ~" ?
Intercept, 截距
- A) G/ }, _0 gInterpolation, 内插法: {' W, k; p- I& H
Interquartile range, 四分位距$ c  K; d3 S( B
Interval estimation, 区间估计
5 B# ]9 I2 g6 GIntervals of equal probability, 等概率区间; r4 a& z( m# v2 a, J* i: i
Intrinsic curvature, 固有曲率1 N7 N3 T0 g; }" H
Invariance, 不变性
8 G# p0 Q8 m8 sInverse matrix, 逆矩阵
: Z2 o; ~1 W4 n: [+ ~Inverse probability, 逆概率9 O, o1 L5 l( [3 G# p3 f8 T
Inverse sine transformation, 反正弦变换
# J2 K1 \) I6 SIteration, 迭代 - M% G4 p- [! Q. s8 I# s  [
Jacobian determinant, 雅可比行列式
. X/ N$ C0 P' X/ D0 c! }. e! AJoint distribution function, 分布函数
6 e" I: X& U2 LJoint probability, 联合概率
. A' h+ I6 G8 E0 l6 J( V1 E; x) e3 j" cJoint probability distribution, 联合概率分布. U) B/ c: z/ U5 n7 U
K means method, 逐步聚类法
, d" G9 c9 M0 j- DKaplan-Meier, 评估事件的时间长度
2 l# D: U8 E8 [  @8 k6 jKaplan-Merier chart, Kaplan-Merier图" N0 M' C3 y# u, l( z
Kendall's rank correlation, Kendall等级相关, L$ U0 b/ D) K7 L, `# w" X' }
Kinetic, 动力学0 X1 [+ T' `1 W8 \
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验$ z* ~6 M3 C3 k4 B
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
& m( Z5 f0 a) a; E& VKurtosis, 峰度2 v3 g% ~. {5 A9 q
Lack of fit, 失拟( G! E; [( M9 \
Ladder of powers, 幂阶梯
  R. t2 n  y0 c5 d# {. m6 fLag, 滞后
4 j. g4 `2 E) _" ?! u5 eLarge sample, 大样本3 o. E0 e! c0 R( X
Large sample test, 大样本检验
6 t6 m* F3 P3 D9 `Latin square, 拉丁方
  n2 w6 q4 U# ]: u* PLatin square design, 拉丁方设计0 L3 j* V* v2 r' w$ K5 t; \' i
Leakage, 泄漏
+ _; {. {9 q3 A6 ]" H; ~Least favorable configuration, 最不利构形/ M8 e$ `+ y8 j# ~
Least favorable distribution, 最不利分布5 W1 I) G, B' d, y
Least significant difference, 最小显著差法
7 o, \' s$ \2 T: E8 VLeast square method, 最小二乘法
% `- H+ E. L% e: }4 ILeast-absolute-residuals estimates, 最小绝对残差估计2 Z6 n: K/ n0 u* j
Least-absolute-residuals fit, 最小绝对残差拟合
" T5 V5 ^/ N( f/ U4 O( Y7 ULeast-absolute-residuals line, 最小绝对残差线2 Q$ ?6 f1 {3 a% y# U0 b
Legend, 图例
( x8 t1 j/ l6 p0 w, |L-estimator, L估计量4 I; G/ {  i) c' }
L-estimator of location, 位置L估计量( B8 P4 ~' i4 ?% g4 g+ e+ U5 {2 Q
L-estimator of scale, 尺度L估计量! V; O8 |) |% w$ [: i( P. g0 y# k
Level, 水平& }1 y$ B/ x- _2 L  E3 Q( S  v
Life expectance, 预期期望寿命+ Z# n9 N. Y- P; i2 L) t
Life table, 寿命表
" j8 }! }% y. V7 qLife table method, 生命表法
+ N, P6 N7 O! e8 a- C! D6 GLight-tailed distribution, 轻尾分布9 O- t! V, N6 |2 t
Likelihood function, 似然函数4 B: T( ?. l' @3 Q" Z. U$ ~/ Y- b
Likelihood ratio, 似然比
4 C' U# X/ \0 H: s! \* Y7 G) Oline graph, 线图
" B, n! i6 V3 y' n, rLinear correlation, 直线相关) e: h( h) J9 J
Linear equation, 线性方程
5 V  ~( u+ ?: \9 BLinear programming, 线性规划/ h: z7 T4 f; ?0 e
Linear regression, 直线回归* _& b; s+ L1 h$ m# h- I
Linear Regression, 线性回归
) N. g9 H: I% O# \" r5 ILinear trend, 线性趋势
2 t$ W5 C* K  g; W, {: ?Loading, 载荷 2 s, u8 l  [" ^3 |
Location and scale equivariance, 位置尺度同变性
7 S. r# a( P: ]6 e: dLocation equivariance, 位置同变性5 k7 f7 h. o0 S0 ^/ \2 Q5 ~
Location invariance, 位置不变性: _' o5 f/ @( A# l. o1 J5 ?
Location scale family, 位置尺度族% }4 |3 P: V; }2 a  {/ L7 R
Log rank test, 时序检验 ) F- V0 W* u  g: T; D0 P
Logarithmic curve, 对数曲线: @$ O+ D. P, ~: `2 R
Logarithmic normal distribution, 对数正态分布
0 E* r+ c! ]& p* S+ m$ DLogarithmic scale, 对数尺度
9 K2 p) B4 s3 J9 T0 A* SLogarithmic transformation, 对数变换
$ t) a9 G& m* X' `- e# l: @Logic check, 逻辑检查
4 j5 J6 N, G5 i( I; \4 ~Logistic distribution, 逻辑斯特分布" d9 @% j: W7 m# t$ h: x; ?
Logit transformation, Logit转换. u2 I& o1 Z5 [6 x
LOGLINEAR, 多维列联表通用模型 + p4 d! C9 {5 U, Y+ W
Lognormal distribution, 对数正态分布
; t' g. C7 [% i+ Y* C/ `Lost function, 损失函数0 p* J0 [# p1 d
Low correlation, 低度相关
+ H: E% s4 d: z/ M* G1 h/ B. bLower limit, 下限
: J  y; N, W/ X( C* [, lLowest-attained variance, 最小可达方差& e. t  l7 P& x$ y, U1 n/ o; I
LSD, 最小显著差法的简称# v4 g/ z3 u8 @* ?3 Y9 [
Lurking variable, 潜在变量7 [1 ]# N0 ]$ i) t6 j, X
Main effect, 主效应/ D- ^! ^! ~( o* c; @
Major heading, 主辞标目
# h7 z& t: I7 M+ k, o9 aMarginal density function, 边缘密度函数
4 X/ m% o$ b3 e' q  lMarginal probability, 边缘概率
* ~7 W4 `+ C; U- O: }; b3 uMarginal probability distribution, 边缘概率分布
5 w6 a5 Z* F: m7 X  T2 [Matched data, 配对资料3 K/ ~, j. X7 f- Q
Matched distribution, 匹配过分布" S1 H% Q% K; h* _6 h
Matching of distribution, 分布的匹配
- v9 _. K! ?2 u6 c# M6 k# bMatching of transformation, 变换的匹配4 K# ~6 U8 l4 C+ b3 E6 S
Mathematical expectation, 数学期望
/ f5 r% U  T- ?: |Mathematical model, 数学模型3 a8 }& N4 T8 b( B7 v
Maximum L-estimator, 极大极小L 估计量
9 A3 U! p1 K7 s0 r& \7 |Maximum likelihood method, 最大似然法# Y- o- z, g- }# \" M% `, v' `
Mean, 均数* v# X! Z+ b- u
Mean squares between groups, 组间均方2 L( N6 x, \9 v/ O4 F1 N2 s
Mean squares within group, 组内均方$ g, |( w' Z+ X5 k) X1 w1 X
Means (Compare means), 均值-均值比较- l7 C, S3 @, Y6 V
Median, 中位数
. w3 H8 v" d6 `+ }8 R% D4 a3 U1 tMedian effective dose, 半数效量
2 h( N7 ?& X/ LMedian lethal dose, 半数致死量$ g6 G; q$ ?* U  l" X3 S+ D0 M; ^' P' n
Median polish, 中位数平滑
8 \/ s4 a+ Q8 F2 M3 A% wMedian test, 中位数检验
* ]% O* R. q5 s" K( Y: `# k6 Y& dMinimal sufficient statistic, 最小充分统计量
- |" C  z/ s' y& d) U3 XMinimum distance estimation, 最小距离估计4 m: u/ [: V; I  x( O6 y, _
Minimum effective dose, 最小有效量
& |, b( e) r6 f" l( DMinimum lethal dose, 最小致死量, ?* v8 f; M- p1 M0 s- r# A: w
Minimum variance estimator, 最小方差估计量
9 v# [8 |6 i! D5 cMINITAB, 统计软件包. Y7 e4 V& F. z
Minor heading, 宾词标目0 o0 n- A( h$ w- }2 d
Missing data, 缺失值6 B2 q" k; @' {0 _# ~3 O) N5 B0 c
Model specification, 模型的确定
6 }: \0 S7 ~6 Z; i. E. m3 t1 CModeling Statistics , 模型统计
7 O$ t7 A" F  s9 v! UModels for outliers, 离群值模型( O! M; \( C/ ^. [
Modifying the model, 模型的修正& J+ |" k3 Z5 V) P/ B, D
Modulus of continuity, 连续性模
6 [. E; _* P7 W, dMorbidity, 发病率 7 @7 {* z3 Q) o; \5 ~. Q7 W- F
Most favorable configuration, 最有利构形4 e" ]7 ^$ a; d& }2 H
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
1 e$ }! c& s  e+ I% q0 xMultinomial Logistic Regression , 多项逻辑斯蒂回归" K: D7 C5 F4 m7 Z4 a8 E0 i
Multiple comparison, 多重比较+ h$ O1 _) ], _' A; E6 \8 {  _
Multiple correlation , 复相关& a3 @$ |  H- w' H" z  W4 y
Multiple covariance, 多元协方差1 k$ d- E4 x7 {1 o. i9 m3 d
Multiple linear regression, 多元线性回归/ k% P- z" f5 e7 m8 @5 z6 U
Multiple response , 多重选项
+ F1 V! z7 z" x9 E3 Q5 C: H3 y/ i# XMultiple solutions, 多解5 V' w. `* q5 K, T5 `+ X
Multiplication theorem, 乘法定理# ?$ ]  o6 U* J; Y* ?4 y( P
Multiresponse, 多元响应/ M0 P4 u6 ~$ `. d
Multi-stage sampling, 多阶段抽样
+ c9 ]+ T' F: j' R" X5 C: t+ c8 h% FMultivariate T distribution, 多元T分布) X0 E! p7 t9 Y  r
Mutual exclusive, 互不相容4 f* s5 \* E/ t0 `; Q
Mutual independence, 互相独立
  e! H! H- w3 d) k' hNatural boundary, 自然边界
" C* G- T( j' DNatural dead, 自然死亡
" T- O) ]! G( PNatural zero, 自然零0 M+ E+ w& S' ?/ l8 f9 s; J
Negative correlation, 负相关
" y2 i% h/ O. C/ G* a- mNegative linear correlation, 负线性相关
5 [! [, o# Q( }1 A' x7 m& ENegatively skewed, 负偏
, t; }; E" u( Q, TNewman-Keuls method, q检验- |) }* s" S4 B; J* \
NK method, q检验  E% Z* F1 H7 T3 T$ `5 z
No statistical significance, 无统计意义
! y7 U' i: Y5 V; j/ Q6 XNominal variable, 名义变量- _+ ^9 Z/ \" i% s
Nonconstancy of variability, 变异的非定常性9 x' K5 Y, n, X1 N3 C: ]
Nonlinear regression, 非线性相关# P$ t7 N9 ]/ V+ T, O3 X
Nonparametric statistics, 非参数统计* J& P% R  ]* Q$ D9 G( c3 n: \2 T
Nonparametric test, 非参数检验# t7 k" Z9 |' |1 q: w
Nonparametric tests, 非参数检验/ t4 R6 e% \5 ]  U' G7 o) u' X
Normal deviate, 正态离差! B% v4 c( M' |
Normal distribution, 正态分布
1 J) O( E8 [! j$ j4 M  T, DNormal equation, 正规方程组0 q- s$ j9 h4 `* X/ u
Normal ranges, 正常范围; J) s1 X9 r' L; ]' D5 o
Normal value, 正常值7 b; L. ]1 z7 H9 q, f- f" m
Nuisance parameter, 多余参数/讨厌参数
4 y5 h" C* O2 Q/ {) [$ {& e" aNull hypothesis, 无效假设
$ `' ]3 f; T0 J- tNumerical variable, 数值变量, O7 q' c6 U; M) H1 o/ g; f# s
Objective function, 目标函数: R4 r+ [; ?7 Q, }0 c( G
Observation unit, 观察单位
% j( n- `$ ~; |- @9 d" iObserved value, 观察值
3 Y1 Z% C. f5 T6 i$ T5 l' x* NOne sided test, 单侧检验
( C2 g$ }  ~2 w& K  HOne-way analysis of variance, 单因素方差分析
5 U7 b4 F2 B; e* q" ~6 p5 bOneway ANOVA , 单因素方差分析
" z% G1 m! ~* m: `7 ?' }; v" EOpen sequential trial, 开放型序贯设计2 [$ [3 y4 Z( m
Optrim, 优切尾' C, ?1 F( R* a- r$ t
Optrim efficiency, 优切尾效率
% r7 p. O' p3 t/ m" `Order statistics, 顺序统计量
0 a: g% A1 S# E1 m" |( AOrdered categories, 有序分类; b# s3 q" d- K4 Y, G
Ordinal logistic regression , 序数逻辑斯蒂回归8 u' B9 J$ {& d; `
Ordinal variable, 有序变量& n/ M. d6 _( l+ o4 H0 e! L7 f
Orthogonal basis, 正交基; Q" y, b% u8 D2 i, c
Orthogonal design, 正交试验设计2 o7 C3 ~/ n, g. q5 I9 `8 P
Orthogonality conditions, 正交条件
$ p# m& \5 F9 j! U) O( `ORTHOPLAN, 正交设计 + ]1 `( |+ p3 ?7 C
Outlier cutoffs, 离群值截断点
: Q0 D9 K0 ]4 k% V+ l# {) bOutliers, 极端值3 I* [7 V5 X9 d% C& m2 p5 C9 T, A5 a
OVERALS , 多组变量的非线性正规相关
2 ^+ l7 W! j7 H6 m' z, V7 h* A! fOvershoot, 迭代过度3 O3 ]0 q/ b* ]" K
Paired design, 配对设计) h  v( @" X* w# S6 s4 f
Paired sample, 配对样本7 `# P; j; [1 q: l9 {$ {& d3 N2 |
Pairwise slopes, 成对斜率
" J* q0 ?# v8 x8 y4 TParabola, 抛物线5 Q6 N9 i2 ]+ E) t/ a
Parallel tests, 平行试验8 F5 y/ Y# Z& [! j2 d
Parameter, 参数2 `* j4 ^  G2 e. _# e3 i. x
Parametric statistics, 参数统计
1 w* u, s9 W( p% Y. j6 WParametric test, 参数检验
, i6 `8 Q- |* ~0 M. P! O+ B# W& pPartial correlation, 偏相关
: O& P3 S% R* m" v& dPartial regression, 偏回归7 @- H& [' S7 A/ p
Partial sorting, 偏排序; b' L" @7 g% y7 ^+ o; N
Partials residuals, 偏残差
/ B! Y1 i9 T6 Y5 ]: A" l) r" DPattern, 模式* q. @& B; d9 K3 A
Pearson curves, 皮尔逊曲线$ |3 M! W, O. W& X, c* W
Peeling, 退层
; N; o7 M3 a/ x+ v9 W* s0 w- ZPercent bar graph, 百分条形图
! e6 W: @; t+ o' HPercentage, 百分比
5 ~$ x, t4 i% _7 S; G# CPercentile, 百分位数
% A0 |. T) D4 @1 j' B, e5 _Percentile curves, 百分位曲线. e* A6 }0 D! m% T
Periodicity, 周期性0 T7 \# L; X) g  _
Permutation, 排列
$ w$ o2 n* X% c3 f' tP-estimator, P估计量
9 Y0 f6 C* @, f$ ~Pie graph, 饼图
- {( l& S3 h7 c7 b+ hPitman estimator, 皮特曼估计量, a! j/ H6 b1 q$ ]2 z
Pivot, 枢轴量
( R( h" k, ?7 P# g8 a2 ~Planar, 平坦
/ a) H  b! q( |6 O; ~! nPlanar assumption, 平面的假设! s5 G, x, E8 n# T2 ]6 v  f' ^' S
PLANCARDS, 生成试验的计划卡
4 S! K5 o7 k9 `2 L+ f4 JPoint estimation, 点估计5 f! |! O  A/ Y, D- ?. }; s
Poisson distribution, 泊松分布: @+ [. o7 Y( `: Q9 |1 M
Polishing, 平滑
& u" _% V& h, T2 VPolled standard deviation, 合并标准差' R7 t. Q& a# B0 w$ z0 R- ^/ \! }
Polled variance, 合并方差
0 w# D1 H1 H/ P& GPolygon, 多边图
' m5 j6 z: w9 ePolynomial, 多项式" O8 C& C# y* X6 U( {
Polynomial curve, 多项式曲线
( f$ }: b0 `( s. f+ |4 {5 l: iPopulation, 总体
: S  ~9 Q9 b4 r0 v  X4 T7 _Population attributable risk, 人群归因危险度
- F0 f3 a- Q! I/ p' [( f8 b0 N9 ^  tPositive correlation, 正相关
) V1 R1 k. J2 G9 y3 F+ ~( U  ?! pPositively skewed, 正偏
- y1 j4 [; H- [, ]Posterior distribution, 后验分布- e5 ^7 H. t4 F- f+ q. Z& G
Power of a test, 检验效能
! `# e$ g0 k8 M2 E6 a2 ]  FPrecision, 精密度: u) \% ~) X# V2 q/ s( ?
Predicted value, 预测值- [% ~  q+ O! C& z7 d* q
Preliminary analysis, 预备性分析( z- W4 T2 K; S
Principal component analysis, 主成分分析6 U4 J: l$ D% @: N% H% f
Prior distribution, 先验分布
: k8 I: }: X2 f4 Y: R8 G3 MPrior probability, 先验概率
% |5 E3 D( O' n5 cProbabilistic model, 概率模型9 v3 S0 {# ~; b) i
probability, 概率
3 Y) U0 T" t6 h3 yProbability density, 概率密度; ^5 X! h. R( i( R9 x
Product moment, 乘积矩/协方差8 @& }+ B$ }  c% j: \# f9 e- H: Z
Profile trace, 截面迹图
" f' h- y8 P5 q3 M# o, RProportion, 比/构成比; [: _/ e! y# c. ?! A% h
Proportion allocation in stratified random sampling, 按比例分层随机抽样% Y- y0 T7 ~: \) C) E2 p
Proportionate, 成比例
" _6 d$ Y! G- z" p% l% ZProportionate sub-class numbers, 成比例次级组含量; P3 C7 h1 M2 P! |. s
Prospective study, 前瞻性调查6 S% Q0 j$ M! X( z
Proximities, 亲近性
# |; x: a4 |( @9 o) K% KPseudo F test, 近似F检验
! V0 E7 K' b: m) r, z' MPseudo model, 近似模型
& v! \% A) b; I# y: d' u! gPseudosigma, 伪标准差$ q+ \, w/ P9 b8 _8 F; |$ U
Purposive sampling, 有目的抽样
8 j( @' f  R5 C5 nQR decomposition, QR分解# t1 P# R  ]. H% y6 y
Quadratic approximation, 二次近似
1 R, \! E' e) X9 K* J7 FQualitative classification, 属性分类
( k. H8 ?1 Q8 T/ c* K" z' B/ ]  AQualitative method, 定性方法
% O2 E( N0 J, H+ m( x, t' Y7 TQuantile-quantile plot, 分位数-分位数图/Q-Q图) a, q, U1 Y# \/ d. R: h
Quantitative analysis, 定量分析" }5 }$ M' G5 y5 K+ U5 v+ c8 K. b
Quartile, 四分位数
* e+ {1 M9 d5 DQuick Cluster, 快速聚类
3 M( W5 V* K) f; O' ]Radix sort, 基数排序# \: e* P" U) O! C: ^
Random allocation, 随机化分组9 R4 d. C* E( @3 ?3 \( D5 I& H. ?
Random blocks design, 随机区组设计$ n1 u6 ~) \2 h, {
Random event, 随机事件
- v. Z% {+ e3 e& E! _Randomization, 随机化
6 o: ~7 J# u4 D. k( m+ V. y9 IRange, 极差/全距0 ?' f3 q; _& X- [5 c
Rank correlation, 等级相关
# O4 c. I; s: |# I7 ]% iRank sum test, 秩和检验5 \( Q, M2 R1 |( B$ x4 U
Rank test, 秩检验
- C. G7 F% u+ H; M% o* g& g9 ]) }Ranked data, 等级资料
- }" u- c' ?$ V! yRate, 比率, H" x& c0 K; w- y( x! M& i8 l
Ratio, 比例
6 k. O8 k7 U1 R) D7 v: @; BRaw data, 原始资料
6 f- j8 k4 {+ I/ l! s+ aRaw residual, 原始残差2 I, y& H- _% @9 _% \2 @
Rayleigh's test, 雷氏检验7 u3 q) h' H& ?" X0 m9 N8 n
Rayleigh's Z, 雷氏Z值
( e2 S5 Z! o8 _Reciprocal, 倒数
; P2 B5 x4 s2 IReciprocal transformation, 倒数变换3 d% K  [! I& |2 O4 W7 y7 [
Recording, 记录
0 ]8 G' r! K, s- \Redescending estimators, 回降估计量
( e9 w( W( F: f) |% s& _% h! Y; WReducing dimensions, 降维
' y' T3 B0 v, ^; y5 L- G# aRe-expression, 重新表达
0 w  ?1 s: \8 ?* YReference set, 标准组- d; I  k3 c9 w$ d  Q
Region of acceptance, 接受域% `9 O# j/ `& H  g8 |/ o
Regression coefficient, 回归系数# y8 g  {3 ^; E, N" z/ f+ i  [* H, s
Regression sum of square, 回归平方和
4 V4 x1 ~6 _, b4 M0 XRejection point, 拒绝点
/ Y2 Z' y: w( E1 Q7 Z9 jRelative dispersion, 相对离散度
8 N0 v8 ^0 n1 H4 ORelative number, 相对数
' X5 M/ p* b: |; jReliability, 可靠性! Z+ i4 j0 E+ B% |0 T, ~0 \
Reparametrization, 重新设置参数
, W3 d" x/ _6 u8 g9 EReplication, 重复
/ S2 T! z. J1 t* C# }3 v; GReport Summaries, 报告摘要1 j* f, Y, T- O6 F/ U
Residual sum of square, 剩余平方和
( S6 |1 z$ ?: ?2 w8 PResistance, 耐抗性
- n* f! d" ?" \1 J% @( WResistant line, 耐抗线
- _8 V' i* F+ p1 y& v* y) r0 ]Resistant technique, 耐抗技术9 C. b6 }/ c+ {& j8 E) M3 ]3 _
R-estimator of location, 位置R估计量" A% }- S' t# N! f
R-estimator of scale, 尺度R估计量
+ g* t8 T$ q- `- r8 CRetrospective study, 回顾性调查! z0 i' k' ~* S+ F3 M2 {6 r
Ridge trace, 岭迹+ w2 ]) o  ~5 B
Ridit analysis, Ridit分析1 S8 j) [2 H: a3 z
Rotation, 旋转
; h# X( I1 S9 u* S3 XRounding, 舍入
- z7 Y( I' I3 u+ J1 R  HRow, 行2 ^6 K! s2 s/ r; L2 M
Row effects, 行效应
7 T; C1 D, O# ]+ S9 \) ^% ]2 B# X. gRow factor, 行因素
( {8 g% O1 S+ |- a+ O, QRXC table, RXC表9 ^" E& y: |4 m- I
Sample, 样本6 v4 ]6 V& P0 h& c; e  ]) b, C* ^
Sample regression coefficient, 样本回归系数8 o5 r! A- [5 t( j0 }: L& q
Sample size, 样本量
/ |. \/ [9 E3 V: gSample standard deviation, 样本标准差
4 s8 H) D' E) d  SSampling error, 抽样误差% K% z% W; W: k; h# X
SAS(Statistical analysis system ), SAS统计软件包5 v' L1 Y* b; A
Scale, 尺度/量表9 G" p6 _. I9 k7 ~0 v/ h+ e) y
Scatter diagram, 散点图; `! n% ^& W* A; l5 Z: `7 k- ?
Schematic plot, 示意图/简图
6 [6 C( d; @' |8 }4 G4 I& ^Score test, 计分检验
' [' O+ P5 j+ X) D) y! vScreening, 筛检
/ W2 D7 l: B' E7 q( t3 Y2 R( ESEASON, 季节分析 " w& @. u" z4 I3 K! T6 X
Second derivative, 二阶导数
5 K0 I9 j  l2 c- f! hSecond principal component, 第二主成分
+ a* `/ k0 N/ u% Y# b  k# ]7 lSEM (Structural equation modeling), 结构化方程模型
# ~, w) j; A" p1 n/ oSemi-logarithmic graph, 半对数图- R9 H( d) Z, l! I9 }6 v
Semi-logarithmic paper, 半对数格纸2 {8 x' M) R7 L; p
Sensitivity curve, 敏感度曲线
( g7 D' J* n7 N' sSequential analysis, 贯序分析
2 j0 n7 c4 |4 L4 Y. b: Q* P6 QSequential data set, 顺序数据集5 e/ Y# N" G9 y" H
Sequential design, 贯序设计
0 M' T! h. Y/ ?/ U9 X+ ASequential method, 贯序法$ j. Y( X5 f* Q5 e. D% _: S
Sequential test, 贯序检验法
- J0 P8 f" @$ b+ ?7 iSerial tests, 系列试验
" Z; r6 w$ L) T% A# j3 w; k: [Short-cut method, 简捷法
4 W% H. W2 X2 }0 ySigmoid curve, S形曲线
4 {8 Y8 r; z3 `1 o" H& C7 MSign function, 正负号函数
( R" t  q; ]) e3 K3 @9 XSign test, 符号检验
3 _0 z( `( u1 F5 fSigned rank, 符号秩; g, C% j( k) H& n1 _
Significance test, 显著性检验
) V9 T; M  I$ T9 VSignificant figure, 有效数字( ?6 k* G) g+ f8 I( c# U7 L0 r# Y
Simple cluster sampling, 简单整群抽样. I  G. A3 y( i3 J  E# l0 Z
Simple correlation, 简单相关
! g% A: F* O5 }% q  ESimple random sampling, 简单随机抽样+ L0 o4 s8 V# r/ ]9 p  W
Simple regression, 简单回归$ Q( @0 v& B3 a% c
simple table, 简单表/ W8 i2 n7 [1 Y; D9 r& `- k  \
Sine estimator, 正弦估计量
2 Z, ~7 h% q! L7 A. n4 sSingle-valued estimate, 单值估计
4 n$ f, f2 B8 F$ M$ jSingular matrix, 奇异矩阵6 k/ v! A0 E% k/ _
Skewed distribution, 偏斜分布
% w% {% Y: w- T! E' j! C6 E* y% [Skewness, 偏度9 B2 _7 b4 y* t$ m
Slash distribution, 斜线分布
. u, ]/ S* w: f( Y9 L& [Slope, 斜率- q# p* k, x2 T6 K3 p. l+ T& ^, D
Smirnov test, 斯米尔诺夫检验( F% Z8 P% m: O. E
Source of variation, 变异来源
6 t4 N2 D6 o' u7 T1 k; B$ {! l# ISpearman rank correlation, 斯皮尔曼等级相关, L$ _7 p; M  v' H8 K
Specific factor, 特殊因子& M* n# e  q: I4 z) u  n) x1 G
Specific factor variance, 特殊因子方差" L  `9 ?2 E9 l8 }! |/ q, F
Spectra , 频谱
9 J* s* r+ \2 j# B. I. qSpherical distribution, 球型正态分布' K- T8 p6 ~8 t  C; O$ q
Spread, 展布
' ?; V- i. q" JSPSS(Statistical package for the social science), SPSS统计软件包9 u5 E6 N5 d. C. }8 S
Spurious correlation, 假性相关
* T" D6 C2 I8 X+ F0 \' JSquare root transformation, 平方根变换
4 ^# }( }2 U6 c- ^7 H! A7 RStabilizing variance, 稳定方差
( e1 ~+ ]; t: r: }5 l1 V2 q! eStandard deviation, 标准差7 o* V1 q- H4 ^; `, N, Y+ P
Standard error, 标准误
2 Y5 ]% u1 u( N/ D) y) i" EStandard error of difference, 差别的标准误
0 q0 ?" }  `. MStandard error of estimate, 标准估计误差1 t3 s/ H5 m; P7 M+ W, y
Standard error of rate, 率的标准误
/ p+ C1 U- i5 i1 U2 M$ qStandard normal distribution, 标准正态分布
% X+ K5 [4 a( a0 CStandardization, 标准化$ I* m; [! n1 B9 I: x
Starting value, 起始值
% Z8 D% B5 y" T& C8 N% ]Statistic, 统计量* D% w4 Y" b1 R
Statistical control, 统计控制, l, y8 o/ x+ l( G# j8 g
Statistical graph, 统计图
3 g! n4 Z- h& m* `) [' Z+ `Statistical inference, 统计推断
* C# n; A8 |" j- x* [% {Statistical table, 统计表: {9 o' g# F- z4 F8 k
Steepest descent, 最速下降法
, ]! ^$ x! w; |) f$ kStem and leaf display, 茎叶图  s$ X) P$ ^9 Y/ t& [, M
Step factor, 步长因子
5 e, R  F" Z  MStepwise regression, 逐步回归
3 Y5 F' J. k. ^( s2 ~' q2 [) f; j! FStorage, 存
% _# z/ q3 e2 C( h) XStrata, 层(复数)+ g" v: d- M$ m- ^0 o
Stratified sampling, 分层抽样; E' Q/ i2 u% x' m! S3 ]% ]! n
Stratified sampling, 分层抽样+ ^2 t' o* L( u3 F) J. K
Strength, 强度, K% t9 t  o) x, F8 [
Stringency, 严密性* m0 B4 w) u8 i- C% V: \
Structural relationship, 结构关系% m+ W$ }8 {3 Z% b3 P4 q/ I2 a
Studentized residual, 学生化残差/t化残差# r9 ^) J& w. X0 J
Sub-class numbers, 次级组含量1 c- v1 S) p  J
Subdividing, 分割* H2 F- `( j" l7 |4 _5 H
Sufficient statistic, 充分统计量7 E, a" i5 ~+ s. l) n* T" Z
Sum of products, 积和
3 |1 l- }/ x4 c6 a' wSum of squares, 离差平方和
' a1 h1 D2 S& USum of squares about regression, 回归平方和; K+ x" d. Y, O) k. W9 U3 v% {- o2 n8 X! I
Sum of squares between groups, 组间平方和. _& E3 G. J' s7 h5 d4 E. d6 G. y6 N
Sum of squares of partial regression, 偏回归平方和% `$ N- {6 q5 ^8 f
Sure event, 必然事件, m* p4 H2 `% `
Survey, 调查. ~" N9 b) n6 @& n7 Q5 f2 m) O  q
Survival, 生存分析
) i8 D. v! A" D% J& oSurvival rate, 生存率
; q( |/ j2 k. R9 g: G4 Q2 [Suspended root gram, 悬吊根图2 J! i9 O% l  G3 {  `+ e; N
Symmetry, 对称" ^: g7 H- D$ y% I% s
Systematic error, 系统误差
8 Q' M3 f7 U; [4 m/ C; uSystematic sampling, 系统抽样. A, {, H! {1 N+ \
Tags, 标签
' P' G$ F) A  b2 |& D# C' p+ XTail area, 尾部面积
) }/ }; ?- H( ^2 p9 R, uTail length, 尾长# i/ }0 o! |8 W# @
Tail weight, 尾重
' U% X' |3 J  H! MTangent line, 切线
& E' U5 L5 G) C- S9 b; Z( w- kTarget distribution, 目标分布
% n; [; W; ~) k* DTaylor series, 泰勒级数2 o$ U& M9 U) \" ^
Tendency of dispersion, 离散趋势
# G$ [- a. U- N6 hTesting of hypotheses, 假设检验: i4 g* k: @) S
Theoretical frequency, 理论频数
6 ?7 _( h. P4 k! k4 C3 d' N9 UTime series, 时间序列
* Y3 i. \" l9 X# a; _6 _4 ETolerance interval, 容忍区间
* O% |0 ?! p2 l* rTolerance lower limit, 容忍下限4 m  [' V/ U; \% [
Tolerance upper limit, 容忍上限
( Z9 O+ E- K! o& gTorsion, 扰率; B. u0 B$ y8 Q
Total sum of square, 总平方和
' O& m2 \& n1 U% XTotal variation, 总变异
" m8 N; l' W  V5 g& JTransformation, 转换
* \$ x0 x7 ?* X6 k3 t; D* w) \Treatment, 处理
; }  g8 K6 m4 v+ H8 v1 o: UTrend, 趋势! J" c  Y# ~2 b* i, E& r
Trend of percentage, 百分比趋势
: [5 Q, k. b  y+ V" MTrial, 试验5 C6 Z, C$ f/ L$ K' J
Trial and error method, 试错法
) o% ?# u1 m0 \0 xTuning constant, 细调常数
3 G* L8 c; |6 ~Two sided test, 双向检验. a0 l( i7 u! _0 B6 V+ C5 I4 P4 i
Two-stage least squares, 二阶最小平方
- H; x. y7 P* T- L( d& sTwo-stage sampling, 二阶段抽样
( @1 t' A" r6 U0 ^$ D+ D1 Y; _Two-tailed test, 双侧检验2 S9 H8 F! M+ @' v
Two-way analysis of variance, 双因素方差分析  ~, ?0 W- w: `. B4 u
Two-way table, 双向表
7 J1 i" _- g7 w4 K% _3 [5 G4 ]- k+ D' WType I error, 一类错误/α错误
/ y2 n2 O9 z. o& L' O3 EType II error, 二类错误/β错误
4 T$ l# B4 Q8 N0 @  X" oUMVU, 方差一致最小无偏估计简称
2 p; R" n9 m6 \: E3 u7 Y5 Z+ SUnbiased estimate, 无偏估计
0 S/ t" R4 q! i6 NUnconstrained nonlinear regression , 无约束非线性回归
) y  J# M9 y7 H! U, [8 g- _1 QUnequal subclass number, 不等次级组含量, R  P; L. ]( _4 H' X8 n
Ungrouped data, 不分组资料
& r7 U" F% E4 Y0 e- Z% iUniform coordinate, 均匀坐标% h' T6 P3 z( [/ \
Uniform distribution, 均匀分布
/ Y6 z2 q7 W7 K( k% G. zUniformly minimum variance unbiased estimate, 方差一致最小无偏估计( b7 Q6 `3 f: D& }
Unit, 单元
5 x# I1 G3 j5 F" o# X) @Unordered categories, 无序分类5 p) t3 H' Q+ j( Y
Upper limit, 上限
, w+ n, ^# [6 Y4 s2 x1 a  @8 DUpward rank, 升秩
* v- u5 f4 m8 L$ A% H6 vVague concept, 模糊概念: Q: y6 Y' c5 u3 y2 P
Validity, 有效性4 v* c% A: ~+ b' I4 b0 {
VARCOMP (Variance component estimation), 方差元素估计8 M/ P9 U1 k8 R/ s) m( W, h
Variability, 变异性7 E6 S( `+ _! a/ j" J/ r' j
Variable, 变量
/ p, @/ \6 d( X* U* uVariance, 方差
8 D7 j/ d0 w6 ~; N( `1 `1 CVariation, 变异
# K' m. v4 T  O( TVarimax orthogonal rotation, 方差最大正交旋转) l! u5 `& s+ V( G$ G
Volume of distribution, 容积
: e" Q' \# a1 B2 i1 kW test, W检验( z7 U' F6 O. ~* [2 f
Weibull distribution, 威布尔分布
! Q6 I- R8 l, b! J0 k, _Weight, 权数
- D2 c! j; Z% d$ U$ L3 NWeighted Chi-square test, 加权卡方检验/Cochran检验8 x' G7 p/ T( d
Weighted linear regression method, 加权直线回归
0 A1 J. j8 V2 i! P$ W& m1 C( t0 |7 }& vWeighted mean, 加权平均数
! E  I; m4 W1 |1 V% _; gWeighted mean square, 加权平均方差
, R5 u3 l2 {2 r  q, a" Z9 NWeighted sum of square, 加权平方和. O3 @" O& U7 ]
Weighting coefficient, 权重系数7 C$ z5 \2 T/ ^1 J6 W. h- W
Weighting method, 加权法 ! l/ B& q! Y  P8 s* f$ X: r
W-estimation, W估计量
! @9 b' y( o! b8 T$ @W-estimation of location, 位置W估计量( F1 G; G4 e1 R" ?# R+ R
Width, 宽度
. w; w* m" b" f7 J5 f; u# aWilcoxon paired test, 威斯康星配对法/配对符号秩和检验5 E/ m" E8 {- g! s8 g( Q
Wild point, 野点/狂点* c5 W8 K- n- {
Wild value, 野值/狂值
- E* w) s( S: [. J5 }Winsorized mean, 缩尾均值
/ i! j/ ~3 a7 p0 ?Withdraw, 失访
- `2 n9 x( w9 r# k& CYouden's index, 尤登指数+ z( A% a3 p, x
Z test, Z检验2 N* l, X2 x. q0 @8 _1 V" s
Zero correlation, 零相关
' C2 `( }+ C  Y( u0 E, FZ-transformation, Z变换

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