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http://www.inkorean.com/statistics_terms/index.html
* ±×·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 ÀÖ´Â 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 ÀÖ´Â 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 ¿µÀÎ 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 ÀÌ·Ð 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¤ÀÌ·Ð 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¦ÇÐ econometrics
259 °è·®»çȸÇÐ sociometrics
260 °è·®»ý¹°ÇÐ biometrics
261 °è·®½É¸®ÇÐ 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¿äÀÎ 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 ÀϹÝȼ±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¿äÀÎ 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 °øÅëÀÎÀںлê 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¿äÀÎ 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÷¿äÀÎ 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÷ÆǸŠcross-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)°¡ÃøÀÎ 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 Ãß·Ð 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 ±×·ìȼöÁ¤ 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 񃬔 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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