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Principal Components Analysis (PCA) and Canonical Correlation Analysis (CCA) are among the methods used in Multivariate Data Analysis. PCA is concerned with explaining the variance-covariance structure of a set of variables through a few linear combinations of these variables. Its general objectives are data reduction and interpretation. CCA seeks to identify and quantify the associations between two sets of variables i.e Pulp fibres and Paper variables.PCA shows that the first PC already exceeds 90% of the total variability. According to the proportion of variability explained by each canonical variable , the results suggest that the first two canonical correlations seem to be sufficient to explain the structure between Pulp and Paper characteristics with 98.86%. Despite the fact that the first the two canonical variables keep 98% of common variability, 78% was kept in the pulp fiber set and about 94% of the paper set as a whole. In the proportion of opposite canonical variable,there were approximately 64% for the paper set of variables and 78% for the pulp fiber set of variables kept for the two respectively.

Indoor air quality (IAQ) is referred to as “the air quality within and around buildings and structures, especially as it relates to the health and comfort of building occupants” (US EPA, 2015). Indoor pollutant levels further determine the quality of indoor air, and one of the indicators used to measure IAQ is carbon dioxide (CO2). Drawing on data collected from a classroom, auditorium, and gym setting in the Mount Royal University campus, the aim of this report is to determine if CO2 levels present are within established margins substantial to result in adverse health effects. Environmental factors that are considered in this report include: room size, supply air, and occupant load in the specified spaces on the campus. The results of this study suggest that there are a myriad of factors that may affect IAQ and that CO2 is merely an indicator of poor air quality. Overall, peak indoor CO2 levels can further be used to determine appropriate ventilation rates in an indoor space.

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Math 206 homework

Michał Kwiecień's CV. Created with the moderncv template.

Trabalhos Gráficos para a IP Acesita

With the emergence of systems archiving and distribution of PACS medical imaging, also emerged the need to store those images off-site environment, this project aims to study this need, trying to offer a service within an information infrastructure that can integrate the environment site with a remote environment, a transparent and heterogeneous, taking account of the needs of users of teleradiology. Keywords: PACS, teleradiology, Medical Imaging, Archiving.

Benford law states that the occurrence of digits from 0-9 in a large set of data is not uniformly distributed but instead in a decreasing logarithmic distribution with 1 occurring at most. Almost all set of data follows this trend however this law is widely used as a base for various fraud detection and forensic accounting. Benford’s law is an observation that leading digits in data derived from measurements doesn’t follow uniform distribution. Different financial statements such as cash flows, income statement and balance sheet of the 20 tech companies of the Fortune 500 are analyzed in this project. Cash flow is the net amount of cash and cash-equivalents moving into and out of a business. Income statement is a financial statement that measures a company's financial performance over a specific accounting period. Balance sheet is a financial statement that summarizes a company's assets, liabilities and shareholders’ equity at a specific point in time. All of these data of financial statements are extracted from Morning Star database and are analyzed by Python program written by me.I also wrote the Python program to calculate Benford's second digit and third digit probability using the formula. I would like to thank Prof. Erin Wagner and Dr. Courtney Taylor for helping in this research project.
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