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Plus, he was raising so many cows and chickens on the farm, why not offer his customers fresh meat as well When Brian told Marilyn his idea, she endorsed it right away The Mistoffs chose their location, renovated the building and set their business plan in motion within a year Brian hired his family members as meat processors and cutters and BAM s Inc became a reality Brian and Marilyn Mistoff owned their rst business, and it was just what they envisioned As word of mouth spread through the community, most of the townspeople began patronizing BAM s The store s signature product became fresh-cut meat As business exploded, the Mistoffs invested and managed their money to the point that they could hire new staff members and then open a second store on the opposite end of town Throughout the 1960s, the business became more and more pro table.

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A kNN model uses the k most similar neighbors to the observation to calculate a prediction. Where a response variable is continuous, the prediction is the mean of the nearest neighbors. Where a response variable is categorical, the prediction could be presented as a mean or a voting scheme could be used, that is, select the most common classi cation term. In the learning phase, three items should be determined: Best similarity method: As described in 6, there are many methods for determining whether two observations are similar. For example, the Euclidean or the Jaccard distance. Prior to calculating the similarity, it is important to normalize the variables to a common range so that no variables are considered to be more important. k: This is the number of similar observations that produces the best predictions. If this value is too high, then the kNN model will overgeneralize. If the value is too small, it will lead to a large variation in the prediction.

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BAM s stores began opening in other towns around Greenville and a few years later, the Mistoffs purchased land and built their rst distribution center BAM s catered to the young and old alike, and began adding grocery items, mainly canned and boxed products People of every age eventually came to identify BAM s by the large statue of a cow in front of each store staring out over a ock of cars in the parking lot Children wanted their parents to take pictures next to a BAM s cow as soon as they arrived The Mistoffs vision of a friendly, neighborhood store became the place to shop in upstate South Carolina BAM s grew to more than 250 stores throughout the region, and eventually had a workforce of 15,000 employees The product line expanded and the company catered to clientele from lower to upper-middle class families.

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stocks, it is not surprising to see that it has the highest correlation with CAM s portfolio. The correlation coef cient can (and should) be used to nd out the degree of association between CAM s returns and those of its peer group as well as the other managers in the Emerging Leaders Fund. Covariance Covariance measures the degree to which two variables move together over time relative to their individual mean returns. It is calculated by multiplying the correlation between two variables by the standard deviation for each of the variables. The covariance is similar to the correlation coef cient in that it measures the relationship between a pair of variables. However, unlike the correlation coef cient it is not standardized (in a correlation coef cient the covariance is divided by the standard deviations of x and y). Calculating Covariance in Excel =covar(RS1,RS2) where RS1 = Return stream one. RS2 = Return stream two. Notes: See notes in the correlation section for comments on Excel Syntax. R 2 (R-squared) R2 is the square of the correlation coef cient. When calculating this statistic, you compare the return stream of the product/fund under review (known as the dependent variable) to an appropriate benchmark or other measures, such as median manager returns or the returns of another investment manager (known as the independent variables). The R2 statistic can be interpreted as the proportion of variance in the dependent variable attributable to the variation in the independent variable. Calculating R-squared in Excel =rsq(RS1,RS2) where RS1 = Return stream one (dependent variable). RS2 = Return stream two (independent variable).

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