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Case Days Market Before lockdown (Average) After lockdown (Average) Difference in Means ((After-before)% Test for difference in Means = 0 (p-value for the two-sided t-test)
| Case | Days | Market | Before lockdown (Average) | After lockdown (Average) | Difference in Means ((After-before)% | Test for difference in Means = 0 (p-value for the two-sided t-test) | Is it statistical different? (i.e., < 0.05? |
| I. | 5 Days | Offline | 1.03 | 1.24 | 21% | 0.00 | Yes |
| Online | 0.94 | 0.93 | -1% | 0.91 | No | ||
| Wholesale | 1.28 | 1.27 | -1% | 0.85 | No | ||
| II. | 20 Days | Offline | 0.97 | 1.17 | 20% | 0.00 | Yes |
| Online | 1 | 0.95 | -5% | 0.05 | Yes | ||
| Wholesale | 1.11 | 1.11 | 0% | 0.98 | No | ||
Can anyone tell if this is the right answer for the question below and if
it is can you send the writing part of it? Q.From the data provided, can one conclude that there was a differential price response from the online and offline retail spaces to the supply chain shock following the lockdown? Use the data and run appropriate statistical tests to back up your responses. Data=
| date | Offline Price Indexed | Online Price Indexed | Wholesale Price Indexed | ||
| 3/1/20 | 1 | 1 | 1 | ||
| 3/2/20 | 1 | 1 | 1 | ||
| 3/3/20 | 0.98557323217392 | 1.03248405456543 | 0.996519386768341 | ||
| 3/4/20 | 0.965831398963928 | 0.947001278400421 | 1.04257035255432 | ||
| 3/5/20 | 0.952163934707642 | 1.05725741386414 | 1.02168667316437 | ||
| 3/6/20 | 0.943052351474762 | 1.07553958892822 | 1.05595707893372 | ||
| 3/7/20 | 0.940015196800232 | 1.17341649532318 | 0.967068314552307 | ||
| 3/8/20 | 0.938496589660645 | 1.078249335289 | 0.878179430961609 | ||
| 3/9/20 | 0.943052351474762 | 1.05745387077332 | 0.878447115421295 | ||
| 3/10/20 | 0.92027336359024 | 0.974357664585114 | 0.991432428359985 | ||
| 3/11/20 | 0.926347732543945 | 1.00967621803284 | 1.09477913379669 | ||
| 3/12/20 | 0.933940768241882 | 0.921689093112946 | 1.10388219356537 | ||
| 3/13/20 | 0.964312791824341 | 0.899540841579437 | 1.107630610466 | ||
| 3/14/20 | 0.965831398963928 | 0.964449644088745 | 1.1311913728714 | ||
| 3/15/20 | 0.965831398963928 | 0.956661701202393 | 1.10040163993835 | ||
| 3/16/20 | 0.965831398963928 | 1.0375269651413 | 1.12717533111572 | ||
| 3/17/20 | 0.965831398963928 | 0.993516147136688 | 1.12931728363037 | ||
| 3/18/20 | 0.965831398963928 | 1.0996378660202 | 1.1550201177597 | ||
| 3/19/20 | 0.97646164894104 | 1.07731866836548 | 1.12556886672974 | ||
| 3/20/20 | 1.00227785110474 | 1.07691991329193 | 1.15716195106506 | ||
| 3/21/20 | 1.03720581531525 | 0.994995296001434 | 1.19839358329773 | ||
| 3/22/20 | 1.01442670822144 | 0.934231102466583 | 1.24096381664276 | ||
| 3/23/20 | 1.02657556533813 | 0.845314919948578 | 1.3480589389801 | ||
| 3/24/20 | 1.08428239822388 | 0.83060222864151 | 1.46934401988983 | ||
| 3/25/20 | 1.18906605243683 | 0.887463331222534 | 1.48897814750671 | ||
| 3/26/20 | 1.27334845066071 | 0.876146733760834 | 1.36403393745422 | ||
| 3/27/20 | 1.27334845066071 | 0.955347836017609 | 1.31262826919556 | ||
| 3/28/20 | 1.25512528419495 | 0.925439715385437 | 1.2415885925293 | ||
| 3/29/20 | 1.20728933811188 | 0.988279163837433 | 1.31619811058044 | ||
| 3/30/20 | 1.18906605243683 | 0.907915115356445 | 1.10736274719238 | ||
| 3/31/20 | 1.19665896892548 | 1.0770822763443 | 1.07630527019501 | ||
| 4/1/20 | 1.2042521238327 | 0.973154246807098 | 1.08273088932037 | ||
| 4/2/20 | 1.21184504032135 | 1.00712049007416 | 1.15287816524506 | ||
| 4/3/20 | 1.21184504032135 | 0.996972799301147 | 1.10522079467773 | ||
| 4/4/20 | 1.20577073097229 | 1.01581847667694 | 1.10789823532104 | ||
| 4/5/20 | 1.19969618320465 | 0.995974123477936 | 1.05917000770569 | ||
| 4/6/20 | 1.18754744529724 | 1.01802027225494 | 1.04364120960236 | ||
| 4/7/20 | 1.17387998104095 | 1.00329482555389 | 1.05060243606567 | ||
| 4/8/20 | 1.13743352890015 | 0.935524523258209 | 1.09076309204102 | ||
| 4/9/20 | 1.10402429103851 | 0.834306836128235 | 1.08594369888306 | ||
| 4/10/20 | 1.09794986248016 | 0.816246509552002 | 1.07764399051666 | ||
| 4/11/20 | 1.09035682678223 | 0.816770434379578 | 1.05676031112671 | ||
| 4/12/20 | 1.08580100536346 | 0.847206294536591 | 1.02838015556335 | ||
| 4/13/20 | 1.06909644603729 | 0.90094393491745 | 1.00990629196167 | ||
| 4/14/20 | 1.07668948173523 | 1.01387548446655 | 1.00205266475677 | ||
| 4/15/20 | 1.08428239822388 | 1.03281342983246 | 1.00205266475677 | ||
| 4/16/20 | 1.07213354110718 | 1.02660548686981 | 0.967425227165222 | ||
| 4/17/20 | 1.05998480319977 | 0.979078352451324 | 0.957072734832764 | ||
| 4/18/20 | 1.04783594608307 | 1.00859749317169 | 0.960553348064423 | ||
| 4/19/20 | 1.05087316036224 | 1.02153062820435 | 0.946987986564636 | ||
| 4/20/20 | 1.04935455322266 | 1.02382850646973 | 0.962516725063324 | ||
| 4/21/20 | 1.03872430324554 | 1.00022161006927 | 0.973493933677673 | ||
| 4/22/20 | 1.02505695819855 | 1.02716600894928 | 1.01097726821899 | ||
| 4/23/20 | 1.00835227966309 | 0.973382115364075 | 1.00615799427032 | ||
| 4/24/20 | 0.994684815406799 | 1.05264461040497 | 1.00401604175568 | ||
| 4/25/20 | 0.981017470359802 | 1.11399912834167 | 1.00026774406433 | ||
| 4/26/20 | 0.974943041801453 | 1.25571084022522 | 0.988487303256989 | ||
| 4/27/20 | 1.00531506538391 | 1.21398317813873 | 1.01186966896057 | ||
| 4/28/20 | 1.0379650592804 | 1.09612250328064 | 1.02150821685791 | ||
| 4/29/20 | 1.07289290428162 | 1.01525270938873 | 1.03543055057526 | ||
| 4/30/20 | 1.05466961860657 | 0.915517330169678 | 1.01311910152435 | ||
| 5/1/20 | 1.03416848182678 | 1.04160439968109 | 0.989825963973999 | ||
| 5/2/20 | 1.01138949394226 | 1.04125499725342 | 0.970548868179321 | ||
| 5/3/20 | 1.01138949394226 | 1.19214069843292 | 0.978581011295319 | ||
| 5/4/20 | 1.01290810108185 | 1.07760119438171 | 1.03159308433533 | ||
| 5/5/20 | 1.0068336725235 | 1.03937256336212 | 1.04979920387268 | ||
| 5/6/20 | 1.05542898178101 | 0.98583447933197 | 1.04016065597534 | ||
| 5/7/20 | 1.09491264820099 | 0.998934090137482 | 1.00133872032166 | ||
| 5/8/20 | 1.17691719532013 | 1.09796595573425 | 1.02650606632233 | ||
| 5/9/20 | 1.19665896892548 | 1.05450439453125 | 1.05060243606567 | ||
| 5/10/20 | 1.22399389743805 | 1.04731714725494 | 1.23052203655243 |
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Statistical Techniques For Forensic Accounting Understanding The Theory And Application Of Data Analysis
Authors: Saurav K. Dutta
1st Edition
0133133818, 9780133133813
