Search results for: data-analyst

Lake Data Analysis and Nutrient Budget Modeling

Author : Kenneth H. Reckhow
File Size : 77.16 MB
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Data Analyst

Author : Rune Rasmussen
File Size : 81.82 MB
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Data is constantly increasing; everything from app usage, to sales, to customer surveys generate data in an average business. Out on the streets data is everywhere too, from speed and security cameras, weather monitoring and measuring footfall to name just a few examples. Against this backdrop, data analysts are in higher demand than ever. This book is an essential guide to the role of data analyst. Aspiring data analysts will discover what data analysts do all day, what skills they will need for the role, and what regulations they will be required to adhere to. Practising data analysts can explore useful data analysis tools, methods and techniques, brush up on best practices and look at how they can advance their career.

ORD ADP Workshop Proceedings No 2

Author : Denise Swink
File Size : 53.71 MB
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SIDPERS User Manual

Author : United States. Department of the Army
File Size : 29.36 MB
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PowerPivot for the Data Analyst

Author : Bill Jelen
File Size : 87.30 MB
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ANALYZE HUGE AMOUNTS OF BUSINESS DATA FASTER, MORE EASILY, AND MORE ACCURATELY! Use Microsoft’s free PowerPivot add-in for Excel 2010 to analyze immense amounts of data from any source, perform state-of-the-art business analysis far more easily, and make better decisions in less time! Simple, step-by-step instructions walk you through installing PowerPivot, importing data, using PivotTables with PowerPivot, using super-powerful DAX functions and measures, reporting to print or SharePoint, and a whole lot more. Whatever your Excel data analysis experience, this book will help you use PowerPivot to get the right answers, right now—without IT’s help! Import and integrate data from spreadsheets, SQL Server, Access, Oracle, text files, Atom data feeds, and other sources Analyze multiple tables together, without complicated VLOOKUPs Format, sort, and filter data in the PowerPivot window Add calculated columns using new DAX functions Create powerful reports from PowerPivot data—and format them so executives instantly get your point Discover PivotTable tricks that work even better in PowerPivot Control multiple PivotTable elements on one worksheet, with one set of Excel 2010 Slicers Use DAX Measures to quickly perform tasks that were difficult or impossible with Calculated Fields Compare today’s sales to yesterday’s–or to sales from the parallel period last fiscal year. Use Named Sets to prepare asymmetric reports, show actuals for past months and plan for future months.

Occupational Outlook Quarterly

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File Size : 85.71 MB
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Data Analysis

Author : Michael Lewis-Beck
File Size : 30.6 MB
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This accessible introduction to data analysis focuses on the interpretation of statistical results, in particular those which come from nonexperimental social research. It will provide social science researchers with the tools necessary to select and evaluate statistical tests appropriate for their research question. Using a consistent data-set throughout the book to illustrate the various analytic techniques, Michael Lewis-Beck covers topics such as univariate statistics, measures of association, the statistical significance of the relationship between two variables, simple regression in which the dependent variable is influenced by a single independent variable, and multiple regression.

Intelligent Data Analysis

Author : Michael R. Berthold
File Size : 71.63 MB
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This second and revised edition contains a detailed introduction to the key classes of intelligent data analysis methods. The twelve coherently written chapters by leading experts provide complete coverage of the core issues. The first half of the book is devoted to the discussion of classical statistical issues. The following chapters concentrate on machine learning and artificial intelligence, rule induction methods, neural networks, fuzzy logic, and stochastic search methods. The book concludes with a chapter on visualization and an advanced overview of IDA processes.

Data Analysis and Regression

Author : Frederick Mosteller
File Size : 48.99 MB
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Approaching data analysis; Indication and indicators; Displays and summaries for batches; Straightening curves and plots; The practice of re-expression; Need we re-express? Hunting out the real uncertainty; A method of direct assessment; Two-and more-way tables; Robust and resistant measures; Standardizing for comparison; Regression for fitting; Woes of regression coefficients; A class of mechanisms for fitting; Guided regression; Examining regression residuals.

Python for Data Analysis

Author : Wes McKinney
File Size : 66.19 MB
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Presents case studies and instructions on how to solve data analysis problems using Python.

Exploratory Data Analysis

Author : Frederick Hartwig
File Size : 24.53 MB
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An introduction to the underlying principles, central concepts, and basic techniques for conducting and understanding exploratory data analysis - with numerous social science examples.

Admin Notebook

Author : Data Analyst
File Size : 22.19 MB
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Admin Notebbook. IT Support Notebook. DATA ANALYST and big data scientists for machine learning programming robot notebook and log checkered 120 pages 6x9 inches

Exploring Data Analysis

Author : W. J. Dixon
File Size : 41.81 MB
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A Python Data Analyst s Toolkit

Author : Gayathri Rajagopalan
File Size : 59.18 MB
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Explore the fundamentals of data analysis, and statistics with case studies using Python. This book will show you how to confidently write code in Python, and use various Python libraries and functions for analyzing any dataset. The code is presented in Jupyter notebooks that can further be adapted and extended. This book is divided into three parts – programming with Python, data analysis and visualization, and statistics. You'll start with an introduction to Python – the syntax, functions, conditional statements, data types, and different types of containers. You'll then review more advanced concepts like regular expressions, handling of files, and solving mathematical problems with Python. The second part of the book, will cover Python libraries used for data analysis. There will be an introductory chapter covering basic concepts and terminology, and one chapter each on NumPy(the scientific computation library), Pandas (the data wrangling library) and visualization libraries like Matplotlib and Seaborn. Case studies will be included as examples to help readers understand some real-world applications of data analysis. The final chapters of book focus on statistics, elucidating important principles in statistics that are relevant to data science. These topics include probability, Bayes theorem, permutations and combinations, and hypothesis testing (ANOVA, Chi-squared test, z-test, and t-test), and how the Scipy library enables simplification of tedious calculations involved in statistics. What You'll Learn Further your programming and analytical skills with Python Solve mathematical problems in calculus, and set theory and algebra with Python Work with various libraries in Python to structure, analyze, and visualize data Tackle real-life case studies using Python Review essential statistical concepts and use the Scipy library to solve problems in statistics Who This Book Is For Professionals working in the field of data science interested in enhancing skills in Python, data analysis and statistics.

Diary of an Awesome Data Analyst

Author : William Turner
File Size : 51.81 MB
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Cool writing journals with inspirational and hilarious quotes are the best choice for women, men, and adults to go spend their everyday with fun. Get this amazing sarcastic and hilarious journal and take it to work with you. Write all your important tasks, activities, and daily schedule in this journal and plan your entire day. 6x9 is the perfect size for handling. With matte finish and high quality white paper, this makes up to be the best journal you can get to plan your everyday routine. Maintaining a journal is a healthy activity.

Advanced Data Analysis with SYSTAT

Author : Kris Nolan Kirby
File Size : 51.73 MB
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Economists, biologists, health care professionals, and sociologists looking to do better statistics can confidently turn to this easy-to-follow guide to using Systat--one of the major computer-based statistical programs. The guide is brimming with helpful hints and practical shortcuts for performing contrast analysis in interaction, effect and size of estimation, and meta-analysis.

Multivariate Data Analysis

Author : Barbara B. Jackson
File Size : 78.72 MB
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A Comparison of Data Collection and Analysis Methods Used to Monitor Impacts Over Time in a Severely Disturbed Wetland

Author : Sarah Wynn
File Size : 25.45 MB
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The SPSS Guide to Data Analysis for SPSS PC

Author : Marija J. Norušis
File Size : 40.36 MB
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Become a Python Data Analyst

Author : Alvaro Fuentes
File Size : 61.53 MB
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Enhance your data analysis and predictive modeling skills using popular Python tools Key Features Cover all fundamental libraries for operation and manipulation of Python for data analysis Implement real-world datasets to perform predictive analytics with Python Access modern data analysis techniques and detailed code with scikit-learn and SciPy Book Description Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations. Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations. In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques. By the end of this book, you will have hands-on experience performing data analysis with Python. What you will learn Explore important Python libraries and learn to install Anaconda distribution Understand the basics of NumPy Produce informative and useful visualizations for analyzing data Perform common statistical calculations Build predictive models and understand the principles of predictive analytics Who this book is for Become a Python Data Analyst is for entry-level data analysts, data engineers, and BI professionals who want to make complete use of Python tools for performing efficient data analysis. Prior knowledge of Python programming is necessary to understand the concepts covered in this book