Search results for "Introduction to Data Analysis Using IBM SPSS"
Items we need to order for you
R 519.00
Hands-On Exploratory Data Analysis with Python
Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandasKey FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook DescriptionExploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization.You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence.By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes.What you will learnImport, clean, and explore data to perform preliminary analysis using powerful Python packagesIdentify and transform erroneous data using different data wrangling techniquesExplore the use of multiple regression to describe non-linear relationshipsDiscover hypothesis testing and explore techniques of time-series analysisUnderstand and interpret results obtained from graphical analysisBuild, train, and optimize predictive models to estimate resultsPerform complex EDA techniques on open source datasetsWho this book is forThis EDA book is for anyone interested in data analysis, especially students, statisticians, data analysts, and data scientists. The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. Fundamental knowledge of Python programming and statistical concepts is all you need to get started with this book.
R 2,735.00
Angewandte Regressionsanalyse mit SPSS
Regressionsanalysen erlauben vielfaltige Aussagen Uber Bezie- hungen zwischen quantitativen Variablen. Angewandte Regressi- onsanalysen werden mit vorliegenden Datensatzen auf elektroni- schen Rechenanlagen durchgefUhrt. Dort installierte statisti- sche Programmpakete wie SPSS (Statistical Package for Social Sciences) verfUgen in der Regel Uber Regressionsprozeduren. Diese Prozeduren liefern dem Nutzer das Ergebnis einer Regres- sionsanalyse in Form von Standardausdrucken, die es zu inter- pretieren gilt. Teilweise bedingt durch die Vielfalt ausgedruck- ter Ergebnisse, sind viele Nutzer mit einer solchen Interpreta- tion Uberfordert. Die "Angewandte Regressionsanalyse mit SPSS" soll hier eine auch auf andere statistische Prograrnrnpakete Ubertragbare Hilfestellung geben. Dabei steht die statistische Analyse und nicht eine Beschreibung des genutzten Programmpa- kets, namlich SPSS/PC], im Vordergrund. Die "Angewandte Regressionsanalyse mit SPSS" gliedert sich in vier Kapitel. In der EinfUhrung (Kapitel 1) werden die Grundla- gen fUr eine solche Analyse vorgestellt. Das sind die SPSS-Pro- zedur REGRESSION, ein fUr die Analyse genutzter Datensatz sowie das Standardmodell der linearen Regression. Die anschlieBenden beiden Kapitel beziehen sich auf einfache lineare Regressions- analysen. Kapitel 2 liefert diesbezUglich eine klassische ag- gregierte Analyse, Kapitel 3 die zugehorige, auch auf einzelne Beobachtungsfalle bezogene Modelldiagnose. In Kapitel 4 werden Analyse und Diagnose auf mehrfache lineare Regressionen verall- gemeinert. Eine Behandlung des Problems der Kollinearitat kommt hinzu. Daneben finden sich in Kapitel 4 Verbindungen der Re- gressions- zur Kovarianz- und Varianzanalyse. Der Anhang umfaBt einige wichtige statistische und mathematische Hilfs ittel fUr angewandte Regressionsanalysen, zusatzlich einen Ablaufplan fUr solche Analysen und ein Symbolverzeichnis.
R 1,941.66
R 489.00
R 3,224.00
R 1,191.00
R 1,794.59
Applied SQL Data Analytics Workshop
Take a step-by-step approach to learning SQL data analysis in this interactive workshop that uses fun exercises and activities to make learning data analytics for beginners easy and approachable.Key FeaturesExplore ways to use SQL for data analytics and gain key insights from your dataStudy advanced analytics, such as geospatial and text analyticsDiscover ways to integrate your SQL pipelines with other analytics technologiesBook DescriptionEvery day, businesses operate around the clock and a huge amount of data is generated at a rapid pace. Hidden in this data are key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. Are you ready to enter the exciting world of data analytics and unlock these useful insights?Written by a team of expert data scientists who have used their data analytics skills to transform businesses of all shapes and sizes, The Applied SQL Data Analytics Workshop is a great way to get started with data analysis, showing you how to effectively sieve and process information from raw data, even without any prior experience.The book begins by showing you how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you'll learn how to write SQL queries to aggregate, calculate and combine SQL data from sources outside of your current dataset. You'll also discover how to work with different data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you'll finally be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation.By the end of The Applied SQL Data Analytics Workshop, you'll have the skills you need to start identifying patterns and unlocking insights in your own data. You will be capable of looking and assessing data with the critical eye of a skilled data analyst.What you will learnUnderstand what data analytics is and why it is importantExperiment with data analytics using basic and advanced queriesInterpret data through descriptive statistics and aggregate functionsExport data from external sources using powerful SQL queriesWork with and manipulate data using SQL joins and constraintsSpeed up your data analysis workflow by automating tasks and optimizing queriesWho this book is forIf you are a database engineer who is looking to transition into analytics or someone who knows SQL basics but doesn't know how to use it to create business insights, then this book is for you.
R 1,791.00
R 2,787.00
R 317.00
R 1,404.00
R 1,527.00
R 635.00
Data Flow Analysis
Data flow analysis is used to discover information for a wide variety of useful applications, ranging from compiler optimizations to software engineering and verification. Modern compilers apply it to produce performance-maximizing code, and software engineers use it to re-engineer or reverse engineer programs and verify the integrity of their programs. Supplementary Online Materials to Strengthen UnderstandingUnlike most comparable books, many of which are limited to bit vector frameworks and classical constant propagation, Data Flow Analysis: Theory and Practice offers comprehensive coverage of both classical and contemporary data flow analysis. It prepares foundations useful for both researchers and students in the field by standardizing and unifying various existing research, concepts, and notations. It also presents mathematical foundations of data flow analysis and includes study of data flow analysis implantation through use of the GNU Compiler Collection (GCC). Divided into three parts, this unique text combines discussions of inter- and intraprocedural analysis and then describes implementation of a generic data flow analyzer (gdfa) for bit vector frameworks in GCC. Through the inclusion of case studies and examples to reinforce material, this text equips readers with a combination of mutually supportive theory and practice, and they will be able to access the author’s accompanying Web page. Here they can experiment with the analyses described in the book, and can make use of updated features, including: Slides used in the authors’ coursesThe source of the generic data flow analyzer (gdfa) An errata that features errors as they are discoveredAdditional updated relevant material discovered in the course of research
R 9,335.70
Introduction to Bioinformatics and Clinical Scientific Computing
This textbook provides an introduction to computer science theory, informatics best practice, and the standards and legislation that apply to computing in a healthcare environment. It delivers an accessible discussion of databases (construction, interrogation and maintenance); networking (design and low-level application); programming (best practice rather than the specifics of any one language – design, maintenance, safety). It can be used to accompany the NHS Modernising Scientific Careers syllabus. It is also targeted towards those creating software rather than those using it, particularly computer scientists working in healthcare, specifically those in or close to the Physical Sciences, including radiotherapy, nuclear medicine, and equipment management and those working with genomics and health informatics. Features Combines all topics into one comprehensive introduction. Explores practical applications of theory to healthcare. Can be used to accompany the NHS Modernising Scientific Careers syllabus.
R 2,817.87
IBM Cloud Pak for Data
Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource managementKey FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook DescriptionCloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services.You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects.By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise.What you will learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho this book is forThis book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.
R 1,889.00
R 611.00
Digital Image Processing and Analysis
A NATO advanced Study Institute took place at Bonas from June 14th to June 25th 1976 on "Digital Image Processing and Analysis". This book is the lasting result of a successful meeting, where the best specialists of the field could exchange their ideas and results. The papers are arranged so as to present first the more general and tutorial articles and then the more specific ones on applications. The general topics cover two dimensional transforms, techniques of image restoration, recursive filters, segmentation and analysis of image parts, some points of view from psychology and physiology, and problems of software and processing. The application fields concerned are remote sensing, medical applications, TV image compression,and optical character recognition. The editors wish to thank the Scientific Affairs Division of NATO for the edition of this book. Acknowledgment: This ASI has been made possible by the financial support of the NATO Scientific Affairs Division and D. R. M. E. and the material support of IRIA and the Institut de Programmation. VII TABLE OF CONTENTS William K. Pratt Two dimensional unitary transforms 1 T. S. Huang Two-dimensional Fourier transform 23 T. S. Huang Algebraic methods of image restoration 41 S. Castan Image enhancement and restoration 47 T. S. Huang Film grain noise 63 K. G. Beauchamp Two-dimensional recursive digital filtering 69 S. Attasi A new approach to 2D-recursive filtering 81 V. Cappellini Some efficient two-dimensional recursive digital filters 87 T. S. Durrani and C. E.
R 1,593.40
R 1,374.00
R 3,293.00
R 5,983.82
R 5,884.00
