| Studiju veids |
maģistra akadēmiskās studijas |
| Studiju programmas nosaukums |
Uzņēmējdarbība un vadīšana |
| Nosaukums |
Mārketinga lēmumu statistiskā izvērtēšana |
| Nosaukums angļu valodā |
Statistical Evaluation in Marketing Decisions |
| Struktūrvienība |
22000 Inženierekonomikas un vadības fakultāte |
| Darba vadītājs |
Elīna Gaile-Sarkane |
| Recenzents |
Deniss Ščeulovs |
| Anotācija |
Statistical analyses are vital to effective marketing. Data is paramount as a prerequisite for statistical analysis. There are several types of data and some are more suitable than others for specific purposes. Multiple issues may exist in the data and require resolution. There is always an unobserved part. No matter how accurately and diligently data is collected, no database can fully explain behavior. There are many statistical models available for every application. Each model has comparative advantages and demerits. The aggregate Nested Logit Model (NLM)of demand best predicted sales (indirectly using utility) and values of cross price elasticity between brands using explanatory variables. This is because NLM allows for uneven cross elasticity between products by using nests. |
| Atslēgas vārdi |
Marketing, sales, statistics |
| Atslēgas vārdi angļu valodā |
Marketing, sales, statistics, nested logit |
| Valoda |
eng |
| Gads |
2014 |
| Darba augšupielādes datums un laiks |
03.09.2014 16:36:40 |
