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* ±×·ì °¡ : ÃÑ 683°³  
  ÇÑ             ±Û ¿µ             ¹®
1   °¡°è¼Òµæ   household income
2   °¡´Éµµ, ¿ìµµ   likelihood
3   °¡´Éµµ[¿ìµµ]ºñ °ËÁ¤[°ËÁõ]   likelihood ratio test
4   °¡´Éµµ±â¹Ý ±¹¼Ò¼±Çüȸ±Í   likelihood-based local linear regression
5   °¡´Éµµºñ, ¿ìµµºñ   likelihood ratio
6   °¡´Éµµ¿ø¸®, ¿ìµµ¿ø¸®   likelihood principle
7   °¡´ÉµµÇÔ¼ö, ¿ìµµÇÔ¼ö   likelihood function
8   °¡·ÎÃà, ȾÃà   axis of abscissas
9   °¡¸éÈ­, °¨Ãã    masking
10   °¡¸éÈ­È¿°ú, °¨ÃãÈ¿°ú   masking effect
11   °¡º¯(º¯µ¿)ÃßÃâ°£°Ý   variable sampling interval
12   °¡º¯¼ö   dummy variable
13   °¡º¯ÃßÃâ[Ç¥Áý]ºñ   variable sampling rate
14   °¡º¯Ç¥º»Å©±â   variable sample size
15   °¡ºÎ¹ÝÀÀ, °è¼ö¹ÝÀÀ   quantal response
16   °¡ºÎ½ÃÇè   quantal assay
17   °¡ºê¸®¿¤ÀÇ °ËÁ¤[°ËÁõ]   Gabriel's test
18   °¡»ê°ø¸®   countability axiom
19   °¡»êÀÇ, ¼¿ ¼ö Àִ   countable
20   °¡»êÁýÇÕ, ¼¿ ¼ö ÀÖ´Â ÁýÇÕ   countable set
21   °¡»êÈ®·ü°ø°£   countable probability space
22   °¡»ó°üÇà·Ä   working correlation matrix
23   °¡¼³   hypothesis
24   °¡¼³°ËÁ¤   testing hypothesis
25   °¡¼³°ËÁ¤[°ËÁõ]   hypothesis testing
26   °¡¼³°ËÁ¤[°ËÁõ]   test of hypothesis
27   °¡¼Ó¼øÂ÷°úÁ¤   accelerated sequential procedure
28   °¡¼öÁØ   dummy level
29   °¡¿ª°ü°è   reversible relation
30   °¡¿ªº¯È¯   invertible transformation
31   °¡¿ª¼±Çüº¯È¯   invertible linear transformation
32   °¡¿ª¼º   invertibility
33   °¡¿ªÇà·Ä   invertible matrix
34   °¡¿ëµµ   availability
35   °¡¿ì½º °î¼±   Gaussian curve
36   °¡¿ì½º °úÁ¤   Gaussian process
37   °¡¿ì½º ¹Ðµµ   Gaussian density
38   °¡¿ì½º ºÎµî½Ä   Gauss inequality
39   °¡¿ì½º ºÐÆ÷   Gaussian distribution
40   °¡¿ì½º ÀâÀ½   Gaussian noise
41   °¡¿ì½º Ãøµµ   Gaussian measure
42   °¡¿ì½º È¥ÇÕ¸ðÇü   Gaussian mixture model
43   °¡¿ì½º È®·üº¯¼ö   Gaussian random variable
44   °¡¿ì½º-´ºÆ° ¹æ¹ý   Gauss-Newton method
45   °¡¿ì½º-¸¶¸£ÄÚÇÁ Á¤¸®   Gauss-Markov theorem
46   °¡¿ì½º-»çÀ̵¨ ¹æ¹ý   Gauss-Seidel method
47   °¡¿ì½º-Á¶¸£´Ü ¼Ò°Å(¹ý)   Gauss-Jordan elimination
48   °¡Á¤   assumption
49   °¡Áß°¡´Éµµºñ   weighted likelihood ratio
50   °¡Áß°ª, °¡ÁßÄ¡   weight
51   °¡Áß°ªÇÔ¼ö, °¡ÁßÄ¡ÇÔ¼ö   weight function
52   °¡ÁߺÐÆ÷   weighted distribution
53   °¡Áß»ê¼úÆò±Õ   weighted arithmetic mean
54   °¡ÁßÀ̵¿Æò±Õ   weighted moving average
55   °¡ÁßÁÖ¼ººÐºÐ¼®   weighted principal component analysis
56   °¡ÁßÁö¼ö   weighted index number
57   °¡ÁßÃÖ¼ÒÁ¦°ö¹ý   weighted least squares method
58   °¡ÁßÅõÇ¥   weighted voting
59   °¡ÁßÆò±Õ   weighted average
60   °¡ÁßÆò±Õ   weighted mean
61   °¡ÁßÇÕ   weighted sum
62   °¡Áßȸ±Í   weighted regression
63   °¡ÁöÄ¡±â   pruning
64   °¡ÁöÄ¡±â ±â¹ý   pruning technique
65   °¡Â¥¿äÀÎÈ¿°ú, ÇãÀ§¿äÀÎÈ¿°ú   spurious factor effects
66   °¡Ã³¸®   dummy treatment
67   °¡Ãø°ø°£   measurable space
68   °¡Ãøº¯¼ö   measurable variable
69   °¡Ãøº¯È¯   measurable transformation
70   °¡ÃøÀÎ, Àê ¼ö Àִ   measurable
71   °¡ÃøÁýÇÕ   measurable set
72   °¡ÃøÇÔ¼ö   measurable function
73   °¡Ä¡Áö¼ö   value index
74   °¡Æ®ÀÇ °ËÁ¤[°ËÁõ]   Gart's test
75   °¡Æò±Õ   working mean
76   °£¼·, Áß´Ü   interruption
77   °£Á¢°üÃø   indirect observation
78   °£Á¢½ÃÇè, °£Á¢»ý°Ë   indirect assay
79   °£Á¢Á¶»ç   indirect survey
80   °£Á¢Ç¥Áý   indirect sampling
81   °£Á¢È¿°ú   indirect effect
82   °£Æ® ÁøÇàÇ¥   Gantt progress chart
83   °¥·ç¾Æ ü   Galois field
84   °¥ÁöÀÚÇüÀÔ±¸   staggered-entry
85   °¨°¢°Ë»ç, °ü´É°Ë»ç   sensory test
86   °¨°¢Æò°¡, °ü´ÉÆò°¡   sensory evaluation
87   °¨¸¶ °è¼ö   gamma coefficient
88   °¨¸¶ ºÐÆ÷   gamma distribution
89   °¨¸¶ ÇÔ¼ö   gamma function
90   °¨¸¶ È®·üº¯¼ö   gamma random variable
91   °¨¼Ò°íÀå·ü   decreasing failure rate
92   °¨¼ÒÀ§Çè·ü   decreasing hazard rate
93   °¨¼ÒÆò±ÕÀÜ¿©¼ö¸í   decreasing mean residual life
94   °¨¿°ºÐÆ÷, ¿À¿°ºÐÆ÷   contagious distribution
95   °¨¿°Á¢Á¾À²   infective inoculation rate
96   °ª   value
97   °­ ¸¶¸£ÄÚÇÁ ¼ºÁú   strong Markov property
98   °­´ëÇ¥¼º   strong representation
99   °­µµ   intensity
100   °­µµÇÔ¼ö   intensity function
101   °­¿Ïºñ¼º   strong completeness
102   °­ÀÏÄ¡¼º   strong consistency
103   °­ÀÏÄ¡ÃßÁ¤·®   strongly consistent estimator
104   °­Á¤»ó°úÁ¤   strongly stationary process
105   °­Á¦Á¶»ç, ¹Ð¾îºÙÀ̱â½Ä Á¶»ç   push poll
106   °­Ã¼¿îµ¿   rigid motion
107   °­È¥ÇÕ¼ºÁú   strong mixing property
108   °³³ä(Àû)¸ðÁý´Ü   conceptual population
109   °³¹æÇü Áú¹®, ÀÚÀ¯ÀÀ´ä Áú¹®   open-ended question
110   °³º° ¿¡¸£°íµñ Á¤¸®   individual ergodic theorem
111   °³º°°¡°ÝÁö¼ö   individual price index
112   °³º°¼ö·®Áö¼ö   individual quantity index
113   °³º°Áö¼ö   individual index number
114   °³¿äµµÇ¥   overview diagram
115   °³ÀÎÀû È®·ü   personal probability
116   °³ÀԺм®   intervention analysis
117   °³ÀÔÈ¿°ú   intervention effect
118   °³Ã¼°£ ÀÎÀÚ   between-subjects factor
119   °³Ã¼³»   within-subject
120   °³Ã¼³» ¼³°èÇà·Ä   within-subject design matrix
121   °³Ã¼Æ¯Á¤Àû   subject specific
122   °³Ã¼È¿°ú   subject effect
123   °´Ã¼   object
124   °´Ã¼ÁöÇâÀû ÇÁ·Î±×·¡¹Ö   object oriented programming
125   °»½Å, Àç»ý, ´Ù½Ã »õ·Î¿ò   renewal
126   °»½Å°úÁ¤   renewal process
127   °»½Å·ü   renewal rate
128   °»½Å¹æÁ¤½Ä    renewal equation
129   °»½ÅºÐÆ÷   renewal distribution
130   °»½Å½Ä   updating equation
131   °»½ÅÁ¤¸®   renewal theorem
132   °Åµì°ö, ¸è   power (2)
133   °ÅµìÁ¦°öÀÌ ¿µÀΠ  nilpotent
134   °Å¸®   distance
135   °Å¸®ºÐÆ÷   distance distribution
136   °ÅºÎÀ²   refusal rate
137   °ÅÄ¥À½, ÀÜÂ÷   rough
138   °ÅÇ°¼ø¼­È­   bubble sort
139   °Ë»ç   inspection
140   °Ë»ç ´ÙÀ̾î±×·¥, °Ë»çµµÇ¥   inspection diagram
141   °Ë»ç ·ÎÆ®   inspection lot
142   °Ë»ç-Àç°Ë»ç ½Å·Ú¼º[½Å·Úµµ]   test-retest reliability
143   °ËÁ¤, °ËÁõ   test (1)
144   °ËÁ¤[°ËÁõ](ÀÇ) °áÇÕ   combination of tests
145   °ËÁ¤[°ËÁõ]·Â   power (1)
146   °ËÁ¤[°ËÁõ]·Â   power of test
147   °ËÁ¤[°ËÁõ]·Â °î¼±   power curve
148   °ËÁ¤[°ËÁõ]·Â ÇÔ¼ö   power function
149   °ËÁ¤[°ËÁõ]ÀÇ Å©±â   size of a test
150   °ËÁ¤[°ËÁõ]ÀÇ Å©±â   test size
151   °ËÁ¤[°ËÁõ]Åë°è·®   test statistic
152   °ËÁ¤·Â ºØ±«Á¡   power breakdown point
153   °ËÁõ·Â   test power
154   °Ñº¸±â ¹«°ü[º¸±â¿¡ ¹«°üÇÑ] ȸ±Í   seemingly unrelated regression(SUR)
155   °ÔÀÓ À̷Р  game theory
156   °ÔÀÓ, ³îÀÌ   game
157   °ÔÇÑ-ÀªÄÛ½¼ °ËÁ¤   Gehan-Wilcoxon test
158   °ÝÀÚ   lattice
159   °ÝÀÚ¹«´Ì¹æ°Ý[Á¤¹æ]   plaid square
160   °ÝÀÚºÐÆ÷   lattice distribution
161   °ÝÀÚ¼³°è   lattice design
162   °ÝÀÚÇ¥Áý   lattice sampling
163   °ÝÀÚÈ®·üº¯¼ö   lattice random variable
164   °á°ú, ÃâÇö   outcome
165   °á·Ð   conclusion
166   °áÁ¡   defect
167   °áÁ¤°è¼ö   coefficient of determination
168   °áÁ¤°ø°£   decision space
169   °áÁ¤±ÔÄ¢   decision rule
170   °áÁ¤ºÐ¼®   decision analysis
171   °áÁ¤À̷Р  decision theory
172   °áÁ¤Àû °íÀå, ÀÓ°è°íÀå   critical failure
173   °áÁ¤Àû °úÁ¤   deterministic process
174   °áÁ¤Àû ¸ðÀǽÇÇè, °áÁ¤Àû ¸ðÀǽÃÇà   deterministic simulation
175   °áÁ¤Àû ¸ðÇü   deterministic model
176   °áÁ¤ÀýÂ÷   decision procedure
177   °áÁ¤ÇÔ¼ö   decision function
178   °áÃø°ª, ºÐ½Ç°ª   missing value
179   °áÃø°üÃø   missing observation
180   °áÃøÀÚ·á, ºÐ½ÇÀÚ·á   missing data
181   °áÃøÄ­   missing cell
182   °áÇÕ´©À²   joint cumulant
183   °áÇÕµµ¼ö[ºóµµ]   joint frequency
184   °áÇչеµ   joint density
185   °áÇÕ¹ýÄ¢, ¹­À½¹ýÄ¢   associative law
186   °áÇÕºÐÆ÷   joint distribution
187   °áÇÕÀû·ü   joint moment
188   °áÇÕÁ¶°ÇºÎ±â´ëÀÜÂ÷ ±×¸²   Combining Conditional Expectations and RESiduals plot (CERES plot)
189   °áÇÕÃßÁ¤·®   combined estimator
190   °áÇÕÃæºÐ¼º   joint sufficiency
191   °áÇÕÈ®·ü¹ÐµµÇÔ¼ö   joint probability density function
192   °áÇÕÈ®·üºÐÆ÷   joint probability distribution
193   °áÇÕȸ±Í   joint regression
194   °ã¼±Çü¸ðÇü   bilinear model
195   °ã¼±Çüº¯È¯   bilinear transformation
196   °ã¼±ÇüÇÔ¼ö   bilinear function
197   °ã¼±ÇüÇü½Ä   bilinear form
198   °ãÃÄÁø ºÐÆ÷   wrapped distribution
199   °ãÃÄÁø Á¤±ÔºÐÆ÷   wrapped normal distribution
200   °ãÃÄÁø Æ÷¾Æ¼Û ºÐÆ÷   wrapped Poisson distribution
201   °æ°áÁ¡   minor defect
202   °æ°è   boundary
203   °æ°è°ª   boundary value
204   °æ°è°ª¹®Á¦   boundary value problem
205   °æ°èÁ¶°Ç   boundary condition  
206   °æ°èÈ¿°ú   boundary effects
207   °æ±âÁ¾ÇÕÁö¼ö   business composite index
208   °æ±âÁö¼ö   business index
209   °æ±âÈ®»êÁö¼ö, °æ±âµ¿ÇâÁö¼ö   business diffusion index
210   °æ·Î, ±æ   path
211   °æ·Î°è¼ö   path coefficient
212   °æ·ÎµµÇ¥   path diagram
213   °æ·ÎºÐ¼®   path analysis
214   °æ·Î¿ªÃßÀû   path backtracking
215   °æ·ÎÈ®·ü   routing probability
216   °æ»ç¹ý   gradient method
217   °æ½ÃÀû[´Ù½ÃÁ¡] ÀÚ·á   longitudinal data
218   °æ½ÃÀû[´Ù½ÃÁ¡] Á¶»ç   longitudinal survey
219   °æ½ÃÀû[´Ù½ÃÁ¡] È¿°ú   longitudinal effect
220   °æ¿µÁ¤º¸½Ã½ºÅÛ   management information system (MIS)
221   °æÀïÀ§Çè¸ðÇü   competing risk model
222   °æÁ¦Àû ¼³°è   economic design
223   °æÁ¦ÁöÇ¥   economic index
224   °æÁ¦È°µ¿Àα¸   economically active population
225   °æø   hinge
226   °æÇè°úÁ¤, °æÇèÈ®·ü°úÁ¤   empirical process
227   °æÇèÀû °¡´Éµµ   empirical likelihood
228   °æÇèÀû °ü°è   empirical relation  
229   °æÇèÀû ´©ÀûºÐÆ÷ÇÔ¼ö   empirical cumulative distribution function
230   °æÇèÀû º£ÀÌÁî ÀýÂ÷   empirical Bayes procedure
231   °æÇèÀû º£ÀÌÁî ÃßÁ¤·®   empirical Bayes estimator
232   °æÇèÀû ºÐÆ÷ÇÔ¼ö   empirical distribution function
233   °æÇèÀû À¯ÀǼöÁØ   empirical significance level
234   °æÇèÀû È®·ü   empirical probability
235   °æÇèÀûºÐÀ§¼ö   empirical quantiles
236   °æÇèÀûÁ߽ɱØÇÑÁ¤¸®   empirical central limit theorem
237   °è°îÁ¡   trough point
238   °è±Þ   class
239   °è±Þ°£   between class
240   °è±Þ°£ º¯µ¿   between class variation
241   °è±Þ°ª   class value
242   °è±Þ°æ°è   class boundary
243   °è±Þ±¸°£   class interval
244   °è±Þ±¸°£ÀÇ Å©±â   size of class interval
245   °è±Þ±âÈ£   class symbol
246   °è±Þ³»º¯µ¿   within class variation
247   °è±Þµµ¼ö[ºóµµ]   class frequency
248   °è±Þ»ó´Ü, °è±Þ»óÇÑ   class upper limit
249   °è±ÞÀÇ ÇÕµ¿(È­)   pooling of classes
250   °è±ÞÆø   class width
251   °è±ÞÇÏ´Ü, °è±ÞÇÏÇÑ   class lower limit
252   °è´Ü, ´Ü°è   step
253   °è´Ü[´Ü°è] ½ºÆ®·¹½º ½ÃÇè   step stress testing
254   °è´Ü½Ä¼³°è   staircase design
255   °è´Ü¿µ»ó   step image
256   °è´ÜÇÔ¼ö   step function
257   °è·®(Çü), °Å¸®   metric
258   °è·®°æÁ¦ÇР  econometrics
259   °è·®»çȸÇР  sociometrics
260   °è·®»ý¹°ÇР  biometrics
261   °è·®½É¸®ÇР  psychometrics
262   °è·®Çü   heterograde
263   °è·®Çü °ü¸®µµ   control chart for variables
264   °è·®Çü ´ÙÂ÷¿øôµµ¹ý   metric multidemensional scaling
265   °è·®Çü »ùÇøµ °Ë»ç   sampling inspection by variables
266   °è»ê, ¼À   calculation
267   °è»ê, ¼À   computation
268   °è¼ÓÀû °ËÁ¤[°ËÁõ]   consecutive test
269   °è¼ö    coefficient
270   °è¼ö(Í­â¦)   rank (2)
271   °è¼öÇü   homograde
272   °è¼öÇü °ü¸®µµ   control chart for attributes
273   °è¼öÇü »ùÇøµ °Ë»ç   sampling inspection by attributes
274   °è½Â, Â÷·Ê°ö   factorial  
275   °è½Â´©À²   factorial cumulant
276   °è½ÂÀû·ü   factorial moment
277   °è½ÂÇÕ   factorial sum
278   °è¿­º¯µ¿   serial variation
279   °è¿­»ó°ü   serial correlation
280   °è¿­½ÃÂ÷»ó°ü   serial lag correlation
281   °èÀý°øÀûºÐ   seasonal cointegration
282   °èÀý´ÜÀ§±Ù   seasonal unit root
283   °èÀýº¯µ¿   seasonal variation
284   °èÀýº¯µ¿Áö¼ö   index of seasonal variation
285   °èÀý¼º   seasonality
286   °èÀýÀμö, °èÀý¿äÀΠ  seasonal factor
287   °èÀýÁ¶Á¤   seasonal adjustment
288   °èÀýÈ¿°ú   seasonal effect
289   °èÃþµµ   strata chart
290   °èÃþÀû º£ÀÌÁî ¸ðÇü   hierachical Bayes model
291   °èÃþÀû º´ÇÕ±ºÁýÈ­    hierachical agglomerative clustering
292   °èÃþÀû ÀϹÝÈ­¼±Çü¸ðÇü   hierarchical generalized linear model
293   °èÃþÀû ü°è   hierarchical system
294   °èÅë¿ÀÂ÷   systematic error
295   °èÅëÀû, ü°èÀû    systematic
296   °èÅëÇ¥Áý, °èÅëÃßÃâ   systematic sampling
297   °èȹ   planning
298   °í¸¥ ¼ö·Å, ±Õµî¼ö·Å(¼º)   uniform convergence
299   °í¸¥ ¿¬¼Ó(¼º), ±Õµî¿¬¼Ó(¼º)   uniform continuity
300   °í¸¥ ¿¬¼Ó, ±Õµî¿¬¼Ó   uniformly continuous
301   °í¸¥ ÀûºÐ°¡´É¼º, ±ÕµîÀûºÐ°¡´É¼º   uniform integrability
302   °í¸³ ½Ã½ºÅÛ   isolated system
303   °íÀ¯°ª   eigenvalue
304   °íÀ¯º¤ÅÍ   eigenvector
305   °íÀ¯»çÀüºÐÆ÷    intrinsic prior distribution
306   °íÀ¯Ã¼°è   eigen system
307   °íÀå ¸ðµå, °íÀåÇüÅ   failure mode
308   °íÀå·ü   failure rate
309   °íÀå·üÇÔ¼ö   failure rate function
310   °íÀå¹ß»ý·ü   rate of occurrence of failures
311   °íÀåºÐ¼®   failure analysis
312   °íÀåÁ¡   point of failure
313   °íÀåÁßµµÀý´Ü   failure censoring
314   °íÁ¤¹éºÐÀ²Ç¥Áý   fixed percent sampling
315   °íÁ¤¿äÀÎ, ¸ð¼ö¿äÀΠ  fixed factor
316   °íÁ¤Á¡Á¤¸®   fixed point theorem
317   °íÁ¤Ç¥º»Å©±â   fixed sample size
318   °íÁ¤È¿°ú, ¸ð¼öÈ¿°ú   fixed effect
319   °íÁÖÆĸðÇü   high frequency model
320   °íÂ÷»ó°ü   higher order correlation
321   °íÂ÷Á¡±Ù¼º   higher order asymptotics
322   °î·ü   curvature
323   °î¼±   curve
324   °î¼±¾Æ·¡¸éÀû, °î¼±¹Ø¸éÀû   area under the curve
325   °î¼±ÀûÇÕ   curve fitting
326   °î¼±Áö¼öÁ·   curved exponential family
327   °î¼±È¸±Í   curvilinear regression
328   °ñ°í·ç ÆÛÁü   space-filling
329   °õÆ丣Ã÷ °î¼±   Gompertz curve
330   °ö »óÈ£ÀÛ¿ë   product interaction  
331   °ö, Àû   product
332   °ö´ÙÇ׺ÐÆ÷, Àû´ÙÇ׺ÐÆ÷   product multinomial distribution
333   °ö»ç°Ç   product event
334   °öÀÌÇ׺ÐÆ÷, ÀûÀÌÇ׺ÐÆ÷   product binomial distribution  
335   °öÀû·ü   product moment  
336   °öÀû·ü»ó°ü   product-moment correlation
337   °öÃøµµ   product measure
338   °ø(Íì)½ºÆåÆ®·³   cospectrum
339   °ø°£   space
340   °ø°£°èÅëÇ¥º»   spatial systematic sample
341   °ø°£°úÁ¤   spatial process
342   °ø°£¸ðÇü   spatial model
343   °ø°£¹èÄ¡½ÇÇè   spatial layout experiment
344   °ø°£º¯µ¿¸ðÇü   spatial variation model
345   °ø°£ºÐÆ÷   spatial distribution
346   °ø°£»ó°ü   spatial correlation
347   °ø°£½Ã°£¸ðÇü   spatio-temporal model
348   °ø°£À̵¿ºÒº¯   spatially shift invariant
349   °ø°£ÀÚ±â»ó°ü   spatial autocorrelation
350   °ø°£ÀÚ±âȸ±Í°úÁ¤   spatial autoregressive process
351   °ø°£ÀÚ·á   spatial data
352   °ø°£Á¡°úÁ¤   spatial point process
353   °ø°£Åë°è(ÇÐ)   spatial statistics
354   °ø°£ÆÐÅÏ, °ø°£ÇüÅ   spatial pattern
355   °ø°£Ç¥Áý[Ç¥º»ÃßÃâ]   spatial sampling
356   °øµ¿¿¬¼Ó, ¿¬´ë¿¬¼Ó   jointly continuous
357   °ø¸®   axiom
358   °ø¸®Àû ¹æ¹ý   axiomatic method
359   °øº¯µ¿   covariation
360   °øº¯µ¿µµ   covariogram
361   °øº¯·®   covariate
362   °øºÐ»ê   covariance
363   °øºÐ»ê±¸Á¶¸ðÇü   covariance structure model
364   °øºÐ»êÇÔ¼ö   covariance function
365   °øºÐ»êÇà·Ä   covariance matrix
366   °ø»ç°Ç   empty event
367   °ø¼±¼º, °ø¼±Çü¼º   collinearity
368   °ø½Ä, ½Ä   formula
369   °ø½ÄÅë°è   official statistics
370   °øÀûºÐ   cointegration
371   °øÀûºÐ°ËÁ¤¹ý   cointregration test
372   °øÁ¤ °ÔÀÓ   fair game
373   °øÁ¤(ÇÑ) °ÔÀÓ   equitable game
374   °øÁ¤°ü¸®   process control
375   °øÁ¤´É·Â   process capability  
376   °øÁ¤´É·Â°ª   process capability value
377   °øÁ¤´É·Âºñ   process capability ratio
378   °øÁ¤´É·ÂÁö¼ö   process capability index
379   °øÁ¤Æò±ÕºÒ·®·ü   process average fraction defection
380   °øÁØ   postulate  
381   °øÁýÇÕ   empty set
382   °øÂ÷¼³°è   tolerance design
383   °øÅ뼺   communality
384   °øÅëÀÎÀÚ   common factor
385   °øÅëÀÎÀںлꠠ common factor variance
386   °øÇ¥º»   empty sample
387   °øÇÐÀû °øÁ¤°ü¸®   engineering process control
388   °ú´ë»êÆ÷   over-dispersion
389   °ú´ë»êÆ÷ºÐÆ÷   overdispersed distribution
390   °ú´ë½Äº°   over-identified
391   °ú´ëÀûÇÕ   over-fitting
392   °ú´ëÀûÇÕ¸ðÇü   overfitted model
393   °ú´ëÃßÁ¤°ª   overestimate
394   °ú´ëƯÁ¤È­   over-specification
395   °ú¸ð¼öÈ­   overparameterization
396   °úºÎÇÏÈ®·ü   overload probability
397   °ú¼Ò»êÆ÷   under-dispersion
398   °ú¼Ò½Äº°   under-identified
399   °ú¼Ò¿¹Ãø   under-prediction
400   °ú¼ÒÀûÇÕ   under-fitting
401   °ú¼ÒÃßÁ¤   under-estimation
402   °ú¼ÒÃßÁ¤°ª   under-estimate
403   °ú¼ÒƯÁ¤È­, °ú¼ÒÇ¥±â   under-specification
404   °ú¼ÒÆ÷ÇÔ   under-coverage
405   °úÁ¤, °øÁ¤, ÇÁ·Î¼¼½º   process
406   °úÁ¤¼öÁ¤   process adjustment
407   °úÇнÀ   over-learning
408   °ü°è   relation
409   °ü°èÇü¸ðÇü   relational model
410   °ü¸®°Ë»ç   control inspection
411   °ü¸®µµ   control chart
412   °ü¸®»óÅ   in control
413   °ü¸®»óÇÑ   upper control limit
414   °ü¸®¼öÁØ   control level
415   °ü¸®Á¡   point of control
416   °ü¸®ÁßÀ§¼ö°ËÁ¤   control median test  
417   °ü¸®Áö   control sheet
418   °ü¸®ÇÏÇÑ   lower control limit
419   °ü¸®ÇÑ°è   control limit
420   °ü½É¿µ¿ª   region of interest
421   °üÃø, °üÃø°³Ã¼   observation
422   °üÃø°¡´Éº¯¼ö   observable variable
423   °üÃø°ËÁ¤·Â   observed power
424   °üÃø¿¬±¸   observational study
425   °üÃø¿ÀÂ÷   observational error
426   °üÃøÁ¤º¸Çà·Ä   observed information matrix
427   ±¤¿ªÇ¥Áý   extensive sampling
428   ±¤ÀÇÀÇ Á¤»ó°úÁ¤   wide sense stationary process
429   ±³¶õ¿äÀΠ  disturbance factor
430   ±³¹èü°è   mating system
431   ±³Á¤Áö¼ö   rectified index number
432   ±³ÁýÇÕ   intersection
433   ±³Â÷ ½ºÆåÆ®·³   cross spectrum
434   ±³Â÷°ö, º¤ÅÍ°ö, ¿ÜÀû   cross product
435   ±³Â÷°öÀÇ ºñ   cross-product ratio
436   ±³Â÷°øºÐ»ê   cross covariance
437   ±³Â÷¹üÀ§   cross range
438   ±³Â÷ºÐ·ù   cross classification
439   ±³Â÷»ó°ü   cross correlation
440   ±³Â÷¼³°è   cross-over design
441   ±³Â÷¿¬   run of crossings
442   ±³Â÷¿äÀΠ  crossed factor
443   ±³Â÷ÁøÆø ½ºÆåÆ®·³   cross amplitude spectrum
444   ±³Â÷Â÷ÀÌ   cross-over difference
445   ±³Â÷Ÿ´ç¼º(ÀÔÁõ)   cross-validation
446   ±³Â÷ÆǸŠ  cross-selling
447   ±³Â÷Ç¥, ±³Â÷Á¦Ç¥   cross tabulation
448   ±³Ã¼ºñ¿ë   replacement cost
449   ±³Ã¼È¸±Í   switching regression
450   ±³È£Æò±Õ¹ý   reciprocal average method
451   ±³È¯   interchange
452   ±³È¯°¡´Éº¯¼ö, ȣȯ[°¡´É]º¯¼ö   exchangeable variable
453   ±³È¯°¡´É»ç°Ç, ȣȯ[°¡´É]»ç°Ç   exchangeable event
454   ±³È¯¹ýÄ¢   commutative law
455   ±³È¯Á¤¸®   interchange theorem
456   ±¸, ±¸¸é   sphere
457   ±¸°£   interval
458   ±¸°£º°´ÙÇ×ȸ±Í   segmented polynomial regression
459   ±¸°£ºÐÆ÷   interval distribution
460   ±¸°£Ã´µµ   interval scale
461   ±¸°£ÃßÁ¤   interval estimation
462   ±¸¸é±ØÁÂÇ¥   spherical polar coordinate
463   ±¸¸é»ï°¢Çü   spherical triangle
464   ±¸¹Ý°æ   spherical radius
465   ±¸½½½ÇÇè   bead experiment
466   ±¸ÀÎ(Ï°ì×)   construct
467   ±¸ÀΟ´ç¼º   construct validity
468   ±¸Àû   quadrature
469   ±¸ÀûÁ¡   quadrature point
470   ±¸Á¶   structure
471   ±¸Á¶¹æÁ¤½Ä   structural equation
472   ±¸Á¶Àû °ü°è   structural relationship
473   ±¸Á¶Àû ¿µ   structural zero
474   ±¸Á¶È­Áú¹®   structured question
475   ±¸Çü´ëĪ   spherical symmetry
476   ±¸ÇüºÐ»êÇÔ¼ö   spherical variance function
477   ±¸ÇüºÐÆ÷, ±¸¸éºÐÆ÷   spherical distribution
478   ±¸Çü¼º   spherical
479   ±¸Çü¼º   sphericity
480   ±¸Çü¼º°ËÁ¤[°ËÁõ]   sphericity test
481   ±¸ÇüÁ¤±ÔºÐÆ÷   spherical normal distribution
482   ±¹°¡´ëÂ÷´ëÁ¶Ç¥   national balance sheet
483   ±¹¸éÀüȯ¸ðÇü   regime-switching model
484   ±¹¼Ò ¶ì³Êºñ   local bandwidth
485   ±¹¼Ò(Àû)°¡ÃøÀΠ  locally measurable
486   ±¹¼Ò(Àû)ÃÖ°­·Â °ËÁ¤[°ËÁõ]   locally most powerful test
487   ±¹¼Ò(Àû)ÃÖÀû¼³°è   locally optimal design
488   ±¹¼Ò°¡´Éµµ   local likelihood
489   ±¹¼Ò°¡Áß»êÁ¡µµÆòÈ°   locally weighted scatterplot smoothing
490   ±¹¼Ò±ØÇÑÁ¤¸®   local limit theorem
491   ±¹¼Ò´ÙÇ×ÃßÁ¤·®   local polynomial estimator
492   ±¹¼Ò´ÙÇ×ÆòÈ°   local polynomial smoothing
493   ±¹¼Ò¸ð¼öÀû ¹ÐµµÇÔ¼öÃßÁ¤·®   local parametric density estimator
494   ±¹¼Ò¹Î°¨µµ   local sensitivity
495   ±¹¼Ò¼±Çüȸ±Í   local linear regression
496   ±¹¼Ò¿µÇâ·Â   local influence
497   ±¹¼ÒÀû   local
498   ±¹¼ÒÀý´Ü¿ÀÂ÷   local truncation error
499   ±¹¼ÒÁ¡±ÙÀû Á¤±Ô¼º   local asymptotic normality
500   ±¹¼ÒÁ¡±ÙÈ¿À²¼º   local asymptotic efficiency
501   ±¹¼ÒÁ¦¾î   local control
502   ±¹¼ÒÃÖ·®ºÒº¯°ËÁ¤   locally best invariant(LBI) test
503   ±¹¼ÒÅë°è·®   local statistic
504   ±¹¼ÒÆò±Õ   local average
505   ±¹¼ÒÇØ   local solution
506   ±¹¼ÒÈ­   localization
507   ±¹¼Òȸ±ÍºÐ¼®   local regression analysis
508   ±¹Á¦Åë°èÇÐȸ   International Statistical Institute (ISI)
509   ±ºÁý, Áý¶ô   cluster
510   ±ºÁý°£ ºÐ»ê, Áý¶ô°£ ºÐ»ê   between cluster variance
511   ±ºÁý¹ÝÀÀÁ¤±ÔÀÚ·á   clustered response normal data
512   ±ºÁýºÐ¼®, Áý¶ôºÐ¼®   cluster analysis
513   ±ºÁý½Äº°   cluster identification  
514   ±ºÁýÅ©±â, Áý¶ôÅ©±â   cluster size
515   ±ºÁýÇ¥Áý, Áý¶ôÇ¥Áý   cluster sampling
516   ±Àº§ ºÐÆ÷   Gumbel distribution
517   ±Â¸Ç-Å©·ç½ºÄ® G Åë°è·®   Goodman-Kruskal G statistic
518   ±ÂÆ®¸¸ÀÇ Ã´µµ   Gutman's scale
519   ±Í³³   induction  
520   ±Í³³Àû Á¤ÀÇ   inductive definition
521   ±Í³³Àû Ã߷Р  inductive inference
522   ±Í³³Àû Çൿ[ÇàÀ§]   inductive behaviour
523   ±Í¹«°¡¼³, ¿µ°¡¼³   null hypothesis
524   ±Í¹«ºÐÆ÷, ¿µºÐÆ÷   null distribution
525   ±Í¼ÓÀ§Çè   attributable risk
526   ±Ô°ÝÇÑ°è   specification limit
527   ±Õµî ½ºÆåÆ®·³   uniform spectrum
528   ±ÕµîºÐÆ÷, ±ÕÀϺÐÆ÷   uniform distribution
529   ±ÕµîÁ¤¹Ð ¶ì   equal-precision band
530   ±ÕµîÁ¶°ÇºÎÈ®·ü¼ø¼­È­   uniform conditional stochastic ordering
531   ±ÕµîÇ¥Áý[Ç¥º»ÃßÃâ]ºñ   uniform sampling fraction
532   ±ÕµîÈ¥ÇÕ Æ÷¾Æ¼Û ¸ðÇü   uniform mixture of Poisson model
533   ±ÕµîÈ®·üº¯¼ö, ±ÕÀÏÈ®·üº¯¼ö   uniform random variable
534   ±ÕÀϳ­¼ö, ±ÕÀÏÀÓÀǼö   uniform random number
535   ±ÕÀϵµ½ÃÇè   uniformity trial
536   ±ÕÀϼ³°è, ±Õµî¼³°è   uniform design
537   ±ÕÀÏÃÖ°­·Â°ËÁ¤[°ËÁõ]   uniformly most powerful test
538   ±ÕÀÏÃÖ°íÈ¿À²   uniformly most efficient
539   ±ÕÀÏÃּҺлêºñÆíÇâÃßÁ¤·®   uniformly minimum variance unbiased estimator
540   ±ÕÀÏÃÖ¼ÒÀ§Çè   uniformly minimum risk
541   ±ÕÀÏÇÏ°Ô º¸´Ù ³ªÀº °áÁ¤ÇÔ¼ö   uniformly better decision function
542   ±ÕÇü   balance
543   ±ÕÇü°èÅëÃßÃâ   balanced systematic sampling
544   ±ÕÇü¹è¿­   balanced array
545   ±ÕÇüºÒ¿Ïºñºí·Ï¼³°è   balanced incomplete block design (BIBD)
546   ±ÕÇü¼³°è   balanced design
547   ±ÕÇü¿äÀμ³°è   balanced factorial design
548   ±ÕÇüÀ̺ÐÇ¥º»   balanced half sample
549   ±ÕÇüÀÚ·á   balanced data
550   ±ÕÇüÁßø, ±ÕÇüÈ¥¼±   balanced confounding
551   ±ÕÇüÇ¥º»   balanced sample
552   ±×·¡ÇÁ ºÐ¼®   graphical analysis
553   ±×·¡ÇÁ À¯ÀǼº°ËÁ¤   graphical significance test
554   ±×·¡ÇÁ Áø´Ü   graphical diagnostics
555   ±×·¡ÇÁ Ç¥Çö   graphical presentation
556   ±×·¡ÇÁ, ±×¸²   graph
557   ±×·¡ÇȽº   graphics
558   ±×·¥-»þ¸®¿¡ ±Þ¼ö   Gram-Charlier series
559   ±×·¥-½´¹ÌÆ® Á÷±³È­   Gram-Schmidt orthogonalization
560   ±×·¹ÄÚ-¶óƾ ¹æ°Ý[Á¤¹æ]   Graeco-Latin square
561   ±×·ì ºÐÇÒ   group divisible
562   ±×·ì ºÐÇÒ¼³°è   group divisible design
563   ±×·ì ¼±º°¹ý   group screening method
564   ±×·ì ¼øÂ÷¹æ¹ý    group sequential method
565   ±×·ì(È­) ÀÚ·á   grouped data
566   ±×·ì, ±º, Áý´Ü   group
567   ±×·ì°£   between group
568   ±×·ì°£ ºÐ»ê   between groups variance
569   ±×·ìÈ­   grouping
570   ±×·ìÈ­¼öÁ¤   correction for grouping
571   ±×¸®µå, °ÝÀÚ¸Á   grid
572   ±×¸²   plot (2)
573   ±×¹°ÄÚ   mesh
574   ±Ø, ±Ø¼±   polar
575   ±Ø´Ü(ÀÇ)   extremal
576   ±Ø´Ü°ª ºñ   extremal quotient
577   ±Ø´Ü°ªºÐÆ÷   extreme value distribution
578   ±Ø´Ü°ªÁö¼ö   extreme value index
579   ±Ø´Ü°úÁ¤   extremal process
580   ±Ø´ÜÃÖ¼Ò   extreme minimum
581   ±Ø´ÜÅë°è·®   extremal statistic
582   ±Ø´ë, ±¹¼ÒÃÖ´ë   local maximum
583   ±Ø¼Ò, ±¹¼ÒÃÖ¼Ò   local minimum
584   ±ØÁÂÇ¥°è   polar coordinate system
585   ±ØÇÑ, ÇÑ°è, ±ØÇÑ(°ª)   limit
586   ±ØÇѺÐÆ÷   limiting distribution
587   ±ØÇÑÀû·ü»ý¼ºÇÔ¼ö   limiting moment generating function
588   ±ØÇÑÁ¡, ÁýÀûÁ¡, ½×ÀÎÁ¡   limit point
589   ±ØÇÑÈ®·ü   limiting probability
590   ±Ùº»»ç°Ç   fundamental event
591   ±Ùº»Çü½Ä   fundamental form
592   ±Ù»çµµ   goodness-of-approximation
593   ±ÙÀ» °®Áö ¾Ê´Â ¿¬¸³¹æÁ¤½Ä   inconsistent equations
594   ±ÙÁ¢¼º Á¤¸®   proximity theorem
595   ±ÙÁ¢¼º, ±ÙÁ¢µµ   proximity
596   ±ÙÁ¢½Äº°   near identification
597   ±ÙÁ¢ÃÖÀû   near optimal
598   ±ÙÁ¢Ãøµµ   measure of closeness
599   ±ÙÄ£±³¹è   inbreeding
600   ±Û·¹Á®ÀÇ È¸±Í°ËÁ¤[°ËÁõ]   Glejser's regression test
601   ±Û¸®º¥ÄÚ-Ä­ÅÚ¸® º¸Á¶Á¤¸®   Glivenko-Cantelli lemma
602   ±Þ°£ºÐ»ê, °è±Þ°£ºÐ»ê   interclass variance
603   ±Þ°£»ó°ü, °è±Þ°£»ó°ü   interclass correlation
604   ±Þ³»ºÐ»ê   intraclass variance
605   ±Þ³»ºñ   intraclass ratio
606   ±Þ³»»ó°ü°è¼ö   intraclass correlation coefficient
607   ±Þ¼ö, °è¿­   series
608   ±Þ¼öÃßÁ¤   series estimation
609   ±Þ÷   leptokurtic
610   ±â°¢   rejection
611   ±â°¢¼ö, ºÒÇÕ°ÝÆÇÁ¤¼ö   rejection number
612   ±â°¢¿ª, ±â°¢¿µ¿ª   rejection region
613   ±â°¢¿À·ù   rejection error
614   ±â°¢Ç¥º»ÃßÃâ[±â°¢Ç¥Áý]   rejection sampling
615   ±â°¢Ç¥Áý   rejective sampling
616   ±â°¢ÇÏ´Ù   reject
617   ±â´ë   expectation
618   ±â´ë°ª   expected value
619   ±â´ëµµ¼ö[ºóµµ]   expected frequency
620   ±â´ë¼öÀÍ   expected return
621   ±â´ëÆò±ÕÁ¦°ö   expected mean square
622   ±â´ëÇ°Áú¼öÁØ   expected quality level
623   ±â·Ï°ª°ËÁ¤[°ËÁõ]   records test
624   ±â·Ï°ªÅë°è¸ðÇü   record value statistics model
625   ±âº»²Ã, ±âº»Çü   basic form
626   ±âº»´ÜÀ§   elementary unit
627   ±âº»´ÜÀ§, ÀÏÂ÷´ÜÀ§   primary unit
628   ±âº»´ëºñ   elementary contrast
629   ±âº»»ç°Ç, ±Ù¿ø»ç»ó   elementary event
630   ±âº»È®·üÁýÇÕ   elementary probability set
631   ±â»óÇÐÀû À§Çè   meteorological risk
632   ±â¼ö   radix
633   ±â¼ö, ÁýÇÕÀÇ Å©±â   cardinal number
634   ±â¼ú, ¼­¼ú   description  
635   ±â¼úÁ¶»ç   descriptive survey
636   ±â¼úÅë°è(ÇÐ)   descriptive statistics
637   ±â¾à ¸¶¸£ÄÚÇÁ ¿¬¼â   irreducible Markov chain
638   ±â¾à, ³ª´­ ¼ö ¾ø´Â   irreducible
639   ±â¾à¿ø   irreducible element
640   ±â¾î¸®ÀÇ ºñ   Geary's ratio
641   ±â¾÷½Ç»çÁö¼ö   business survey index
642   ±â¿©ºñ   contribution ratio
643   ±â¿î ºÐÆ÷   skewed distribution
644   ±â¿ï±â   slope
645   ±â¿ï±â ȸÀü¼º   slope rotatability
646   ±â¿ï±â, °æ»çµµ   gradient
647   ±â¿ï±âºñ½ÃÇè   slope ratio assay
648   ±â¿òÀÇ Ãøµµ, ¿Öµµ   measure of skewness
649   ±âÀú, ±âÁØ, ¹Øº¯, ¹Ø, ¹ÙÅÁ, ¹Ø¸é   base
650   ±âÀú, ¹Ø, ¹ÙÅÁ   basis
651   ±âÀú°î¼±, ¹Ø°î¼±   base curve
652   ±âÀú¹üÁÖ   baseline category
653   ±âÁØ   benchmark
654   ±âÁØ   criterion
655   ±âÁØ°ü·Ã Ÿ´ç¼º   criterion-related validity
656   ±âÁسâ(µµ)   base year
657   ±âÁغÐÆ÷, ÁذźÐÆ÷   reference distribution
658   ±âÁؼ±, ¹Ø¼±, ¹Ø±Ý   base line
659   ±âÁö¼ö, ¾Ë·ÁÁø ¾ç   known quantity
660   ±âÁöÇ×, ¾Ë·ÁÁø Ç×   known term
661   ±âÇϺÐÆ÷   geometric distribution
662   ±âÇÏÀû ºê¶ó¿î ¿îµ¿   geometric Brownian motion
663   ±âÇÏÀû È®·ü   geometric probability
664   ±âÇÏÆò±Õ   geometric average
665   ±âÇÏÆò±Õ   geometric mean
666   ±âȸ¼Õ½Ç   opportunity loss
667   ±ä²¿¸®   long tail
668   ±é½º Ç¥Áý   Gibbs sampling
669   ±é½º Ç¥Áý±â   Gibbs sampler
670   ±íÀÌ   depth
671   ²ªÀº¼± ±×·¡ÇÁ   graph of broken lines
672   ²®Áú¹þ±â±â   peeling
673   ²¿¸®   tail
674   ²¿¸®°¡ÁßÄ¡   tail weight
675   ²¿¸®ºÎºÐ   tail part
676   ²¿¸®»ç°Ç   tail event
677   ²¿¸®È®·ü   tail probability
678   ²ÀÁöÁ¡¼³°è   extreme vertices design
679   ³¡°ª¼öÁ¤   end-value correction
680   ³¡Á¡   endpoint
681   ³¢¿ö³Ö±â   imbedding / embedding
682   ³¢¿ö³ÖÀº °úÁ¤, ³¢¿öÁø °úÁ¤   embedded process / imbedded process
683   ³¢¿ö³ÖÀº °úÁ¤, ³¢¿öÁø °úÁ¤   imbedded process / embedded process




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