Table A2 Sample Clauses
The 'Table A2' clause typically refers to a schedule or annex within a contract that lists specific details, such as pricing, deliverables, or technical specifications relevant to the agreement. This table is often used to organize and present key information in a clear, tabular format, making it easy for parties to reference important data like payment milestones, product quantities, or service levels. By consolidating essential terms in a structured table, this clause ensures clarity and reduces the risk of misunderstandings regarding the contract's operational details.
Table A2. Component code (if any) Component title at the receiving institution (as indicated in the course catalogue) tick as applicable Reason for change1 No of ECTS credits Total amount of ECTS credits after the changes: Exceptional changes to Table B (if applicable) (to be approved by e-mail or signature by the student, the responsible person in the Sending Institution and the responsible person in the Receiving Institution) Module code Module title as indicated in the Leuphana course catalogue (mystudy) tick as applicable No of ECTS credits Total amount of ECTS credits after the changes: The student, the sending institution and the receiving institution approve the proposed amendments to the mobility programme by signature. Student’s signature Date: For the sending institution: (▇▇▇ ▇▇▇▇▇▇▇▇▇, Study Abroad Coordinator) Date: For the receiving institution: Date:
Table A2. Monitoring information and data elements
Table A2. Summary Statistics for Data Used in Analysis of Institutional Gaps and Income Gaps Variable No. observations Mean Standard deviation Minimum Maximum Landlock 68 0.1323529 0.3413936 0 1 Openness (▇▇▇▇▇ and ▇▇▇▇▇▇, 1995) 63 0.2252768 0.3423797 0 1 Log constructed trade share 68 2.721456 0.7672238 0.94 4.586000 (▇▇▇▇▇▇▇-▇▇▇▇▇)Latitude 68 6.318064 19.691030 –41.81407 61.06258 Ethnolinguistic fractionalization 61 46.377050 29.430240 1 90 Africa 68 0.3382353 0.4766266 0 1 South Asia 68 0.0588235 0.2370435 0 1 East Asia and the Pacific 68 0.0735294 0.2629441 0 1 Americas 68 0.3970588 0.4929263 0 1 Oil production dummy 68 0.2647059 0.4444566 0 1 Commodity dummy 68 0.6764706 0.4713010 0 1 Institutional index 68 –0.1134657 0.7704978 –1.978333 1.585833 Log mortality 68 4.588946 1.2550750 2.145931 7.986165 Log GDP per capita 68 7.794468 1.1091530 5.252923 10.031100 TABLE A3. Mexico: Summary Statistics of Variables and Data Used for TFP Convergence Analysis, by Industry Industry codea (Log) output Obs (Log) labor Obs (Log) capital Obs Labor share Obs 311 15.77 25 12.98 25 13.87 25 0.06 25 313 15.08 25 12.72 25 13.68 25 0.10 25 314 13.65 25 10.36 25 11.50 25 0.04 25 321 14.35 25 12.50 25 13.41 25 0.16 25 322 13.11 17 11.33 17 11.44 17 0.17 17 323 12.52 7 10.01 7 10.87 7 0.08 7 324 12.86 17 11.19 17 11.70 17 0.19 17 331 11.91 25 9.85 25 11.77 25 0.13 25 332 12.49 17 10.49 17 10.55 17 0.14 17 341 14.61 25 12.08 25 14.35 25 0.08 25 342 13.29 17 11.38 17 11.67 17 0.15 17 351 14.98 25 12.48 25 14.16 25 0.09 25 352 15.09 25 12.89 25 13.49 25 0.11 25 353 13.23 7 10.49 7 11.94 7 0.07 7 354 12.72 25 9.84 25 12.44 25 0.06 25 355 13.66 25 11.69 25 12.90 25 0.14 25 356 14.00 17 11.83 17 12.70 17 0.12 17 361 12.08 17 10.13 17 9.04 17 0.14 17 362 13.81 25 11.86 25 13.12 25 0.15 25 369 14.41 25 12.05 25 14.36 25 0.10 25 371 15.38 25 12.59 25 14.84 25 0.07 25 372 14.31 25 11.34 25 12.73 25 0.06 25 381 14.24 25 12.08 25 12.58 25 0.12 25 382 14.02 25 11.78 25 11.97 25 0.11 25 383 14.64 25 12.57 25 13.02 25 0.13 25 384 15.95 25 13.15 25 14.22 25 0.07 25 385 12.15 17 9.76 17 10.19 17 0.10 17 390 12.21 17 10.34 17 10.86 17 0.16 17 Source: United Nations Industrial Development Organization (UNIDO).
Table A2. Exceptional changes to Table A
Table A2. Course changes during your mobility must be listed under this category - During mobility. Under no circumstances should the student fill out entirely new LA for this purpose.
Table A2. 1 Business case canvas of Living@Sea
Table A2. Once you start the exchange program at ESIGELEC, you may want to change one or more courses. In such a case, you must enter information on the courses you wish to add, remove or replace.
Table A2. Tabulation plan for the exposure dose score of the Quality Diets for Better Health project. The exposure score represents the level project resources and activities to which the study participants were exposed during the first 6 months of the cluster-randomized controlled trial of the project.
Table A2. Probability of a polygon being assigned correctly for each ice concentration category (user’s accuracy, or p(m|x)). pˆ refers to the point estimate of the likelihood found in our sample data; lower and upper refer to the lower and upper 95% confidence intervals, calculated using a ▇▇▇▇▇-▇▇▇▇ multinomial confidence interval method. For any ice concentration category where the pˆvalue for each row does not sum to 1.0, the remainder was found outside of ± three ice concentration categories from the category denoted in the first column. Ice Concentration -3 pˆ lower upper -2 pˆ lower upper -1 pˆ lower upper 0 pˆ lower upper +1 pˆ lower upper +2 pˆ lower upper +3 pˆ lower upper 3/10 - - - - - - 0.345 0.172 0.525 0.517 0.345 0.698 0.103 0.000 0.284 0.000 0.000 0.181 0.034 0.000 0.215 4/10 - - - 0.091 0.000 0.254 0.250 0.114 0.413 0.341 0.205 0.504 0.273 0.136 0.436 0.045 0.000 0.209 - - - 5/10 0.093 0.000 0.227 0.056 0.000 0.190 0.167 0.037 0.301 0.370 0.241 0.504 0.259 0.130 0.393 0.056 0.000 0.190 - - - 6/10 0.096 0.000 0.248 0.038 0.000 0.191 0.231 0.0115 0.383 0.423 0.308 0.575 0.173 0.058 0.325 0.038 0.000 0.191 - - - 7/10 0.042 0.000 0.166 0.097 0.000 0.221 0.194 0.083 0.318 0.389 0.278 0.513 0.264 0.153 0.388 - - - - - - 8/10 0.051 0.000 0.171 0.090 0.000 0.209 0.282 0.179 0.401 0.513 0.410 0.632 0.064 0.000 0.183 - - - - - - 9/10 0.046 0.000 0.169 0.138 0.031 0.261 0.585 0.477 0.708 0.185 0.077 0.308 - - - - - - - - - 5 former operations analyst mentioned in this study who created the 76 polygons in SAR imagery. JFL reviewed the sources cited. JFL and BT revised the text (particularly from a modeling perspective), and critiqued the design of the figures used. BT modified the figure captions. All authors contributed to the interpretation of the results.
Table A2. 1- Details of the schemes identified Study (year) Target condition Programme name Country Type of scheme Issues with appropriateness/desirability, design, implementation and evaluation of the schemes