Datamining group final version Essay

Forecasting the Future Female Veteran Population and Their Increased Use of the VA Medical System - VPT2

For this assignment we needed to compute the mean, median, and mode for five quantitative variables. The five that were computed in this assignment were number of total prior arrests, number of prior misdemeanors, number of total prior convictions, number of prior felony arrests, and number of drug convictions. The mean is defined as the average in a group of numbers, the median is the middle number in a group, and the mode is the most frequently occurring number in the group.

15c (124) = 1860 for classic. 12m (95) = 1140 which equals 1860 + 1128 = 3000, which means we will have enough to fill the order.

b) What number of credit hours students in this sample are taking would be at the 20th percentile?

An important part of our learning and growing experience must stem from our ability to analyze and reflect upon the groups that we have been members in. This reflection can define our understanding of the weaknesses both in ourselves and in the others within our group; and it can help to shape the way that we act in future groups. Adjusting ourselves to compensate for our weaknesses, based upon an honest and thorough examination of our actions within a group setting, is one of most important thing for any person to do. It is only through this evaluation that we can improve ourselves and our interactions with others. This paper will examine a group that was required to make an important decision about adding a new member

Continuing the discussion in my last paragraph, I now focus specifically on another one of the three criteria developed earlier using Hill’s ideas– the rarity of a work. Based on the fundamental laws of supply and demand, the rarity of certain works can drive their prices up, which in turn allows them to function as “trophies” boosting the prestige of their collectors (Hill 7). If one accepts this reasoning as true, collectors viewing fine art as an investment, of which there are several, have a significant stake in making their collections seem like mystic objects (if only to increase the market value of their own works), and one can understand why such collectors would covet rare Renaissance art instead of more easily duplicable advertisements. Stated slightly differently, we categorize certain works as fine art and see advertisements as relatively undistinguished not because one has elements of commercialism and the other does not, but rather because the commercialism present in each panders to different audiences. Advertising, which needs mass distribution in order to work effectively, requires its creators to refer to a product (and thus commercialism) quite blatantly. Art dealers, on the other hand, may refer more frequently to a work’s “historical significance” and rarity, using these attributes as subtle reasons explaining why certain works are valued so highly. Expanding on this idea, I speculate (albeit without proof) that if an art dealer focused solely on price and not on historical factors, people would likely realize that the artworks they were buying were not actually that special; after all, some consumers might reason that anyone with enough money could

In order to market the product into the market successfully, marketers need to have some marketing strategy to enter the desired market and make profit. Market segmentation is the process of dividing a market into subsets of consumers with common needs or characteristics (Schiffman et al., 2011). Understanding the market size and segmentation is valuable, but the keys to effective targeting is to know just how valuable specific consumer groups are, and being able to quantify the impact of consumer trends ( Berry, 1999).

The segmentation has been done on the basis of buying behavior of the customers. Knowledge of segment buying behavior can help redirect marketing resources for profit gain.

Customers are assets, and their values grow and decline. Segmenting customers based on their lifetime value is a powerful way to target them because marketing mix activities can then aim at enhancing customer value. (Ho, 2006)

As every customer has unique needs and expectations towards certain products, the ultimate goal of market segmentation is to organize customers into groups which allows targeting of customers with similar needs of and response to the products. The key is to minimize differentiation within each segment

BBBC is evaluating three different modeling methods to isolate the factors that most influenced customers to order The Art History of Florence: an RFM (Recency, Frequency and Monetary Value) model, an ordinary linear regression model, and a binary logit model. 1. Summarize the results of your analysis for all three models. Develop your models using the case data files and then assess them on the holdout data sample. Interpret the results of these models. In particular, highlight which factors most influenced the customers’ decision to buy or not to buy the book. Bookbinders is considering a similar

Expected value of IRR = IRR1 * probability 1 + IRR2 * probability 2 + IRR3 * probability 3

Data Warehousing and Data Mining has always been associated with manufacturing companies, where sales and profit is the main driving force. Subsequently Higher Education has grown throughout the years; this growth is predominately associated with the increase of online institutions. This growth has resulted in higher education to adapt to a more business like institution (Lazerson, 2000).

“A task force concluded, the past segmentation did not fully address the emerging shift in customer needs” “(Xiameter Case Study). Dow Corning had to thus try different segmentation variables, alone and in combination to find the best way to view the market structure. (Kotler et al, 2008).

This provides an overview of the steps that were used for the processing of the data. In general all of the processes were executed using batch macros in ImageJ and the resulting files were saved at each step.