Deborah Nolan – författare
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20 produkter
20 produkter
E-bok
PDF, Engelska, 2017480 kr
Läs direkt efter köp
Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active studentparticipation.Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as ''First week of class''— with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn''t, how to set up effective demonstrations, how to encourage students to participate inclass and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and datascience.
E-bok
Engelska, 2017480 kr
Läs direkt efter köp
Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active studentparticipation.Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as ''First week of class''— with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn''t, how to set up effective demonstrations, how to encourage students to participate inclass and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and datascience.
E-bok
PDF, Engelska, 2021537 kr
Läs direkt efter köp
Communication is a critical yet often overlooked part of data science. Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data. General advice on science writing is also provided, including how to distill findings into a story and organize and revise the story, and how to write clearly, concisely, and precisely. This is an excellent resource for students who want to learn how to write about scientific findings, and for instructors who are teaching a science course in communication or a course with a writing component. Communicating with Data consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities. This book also provides 22 portfolio prompts that extend the guidance and examples in the earlier parts of the book and help writers build their portfolio of data communication.
Inbunden, Engelska, 2017
2 314 kr
Skickas inom 3-6 vardagar
Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as 'First week of class'-- with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn't, how to set up effective demonstrations, how to encourage students to participate in class and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and data science.
Häftad, Engelska, 2017
707 kr
Skickas inom 5-8 vardagar
Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as 'First week of class'-- with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn't, how to set up effective demonstrations, how to encourage students to participate in class and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and data science.
Inbunden, Engelska, 2021
1 338 kr
Skickas inom 5-8 vardagar
Communication is a critical yet often overlooked part of data science. Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data. General advice on science writing is also provided, including how to distill findings into a story and organize and revise the story, and how to write clearly, concisely, and precisely. This is an excellent resource for students who want to learn how to write about scientific findings, and for instructors who are teaching a science course in communication or a course with a writing component. Communicating with Data consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities. This book also provides 22 portfolio prompts that extend the guidance and examples in the earlier parts of the book and help writers build their portfolio of data communication.
Häftad, Engelska, 2021
686 kr
Skickas inom 7-10 vardagar
Communication is a critical yet often overlooked part of data science. Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data. General advice on science writing is also provided, including how to distill findings into a story and organize and revise the story, and how to write clearly, concisely, and precisely. This is an excellent resource for students who want to learn how to write about scientific findings, and for instructors who are teaching a science course in communication or a course with a writing component. Communicating with Data consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities. This book also provides 22 portfolio prompts that extend the guidance and examples in the earlier parts of the book and help writers build their portfolio of data communication.
E-bok
PDF, Engelska, 20061 250 kr
Läs direkt efter köp
This book uses a model we have developed for teaching mathematical statistics through in depth case studies. Traditional statistics texts have many small numer ical examples in each chapter to illustrate a topic in statistical theory. Here, we instead make a case study the centerpiece of each chapter. The case studies, which we call labs, raise interesting scienti?c questions, and ?guring out how to answer a question is the starting point for developing statistical theory. The labs are substan tial exercises; they have nontrivial solutions that leave room for different analyses of the data. In addition to providing the framework and motivation for studying topics in mathematical statistics, the labs help students develop statistical thinking. We feel that this approach integrates theoretical and applied statistics in a way not commonly encountered in an undergraduate text. The Student The book is intended for a course in mathematical statistics for juniors and seniors. We assume that students have had one year of calculus, including Taylor series, and a course in probability. We do not assume students have experience with statistical software so we incorporate lessons into our course on how to use the software.
Häftad, Engelska, 2000
971 kr
Skickas inom 10-15 vardagar
This book uses a model we have developed for teaching mathematical statistics through in depth case studies. Traditional statistics texts have many small numer ical examples in each chapter to illustrate a topic in statistical theory. Here, we instead make a case study the centerpiece of each chapter. The case studies, which we call labs, raise interesting scienti?c questions, and ?guring out how to answer a question is the starting point for developing statistical theory. The labs are substan tial exercises; they have nontrivial solutions that leave room for different analyses of the data. In addition to providing the framework and motivation for studying topics in mathematical statistics, the labs help students develop statistical thinking. We feel that this approach integrates theoretical and applied statistics in a way not commonly encountered in an undergraduate text. The Student The book is intended for a course in mathematical statistics for juniors and seniors. We assume that students have had one year of calculus, including Taylor series, and a course in probability. We do not assume students have experience with statistical software so we incorporate lessons into our course on how to use the software.
E-bok
Engelska, 2023809 kr
Läs direkt efter köp
As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it''s for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data.
Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It''s aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you''ll learn how to work with data using industry-standard tools like pandas.
Refine a question of interest to one that can be studied with dataPursue data collection that may involve text processing, web scraping, etc.Glean valuable insights about data through data cleaning, exploration, and visualizationLearn how to use modeling to describe the dataGeneralize findings beyond the data
E-bok
PDF, Engelska, 2023807 kr
Läs direkt efter köp
As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it''s for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data.
Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It''s aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you''ll learn how to work with data using industry-standard tools like pandas.
Refine a question of interest to one that can be studied with dataPursue data collection that may involve text processing, web scraping, etc.Glean valuable insights about data through data cleaning, exploration, and visualizationLearn how to use modeling to describe the dataGeneralize findings beyond the data
Häftad, Engelska, 2023
646 kr
Skickas inom 5-8 vardagar
As an aspiring data scientist, you appreciate why organizations rely on data for important decisions—whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data.Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas.Refine a question of interest to one that can be studied with dataPursue data collection that may involve text processing, web scraping, etc.Glean valuable insights about data through data cleaning, exploration, and visualizationLearn how to use modeling to describe the dataGeneralize findings beyond the data
Inbunden, Engelska, 2017
2 940 kr
Skickas inom 10-15 vardagar
Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book‘s collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standard, complex data formats, such as robot logs and email messages Text processing and regular expressions Newer technologies, such as Web scraping, Web services, Keyhole Markup Language (KML), and Google Earth Statistical methods, such as classification trees, k-nearest neighbors, and na Bayes Visualization and exploratory data analysis Relational databases and Structured Query Language (SQL) Simulation Algorithm implementation Large data and efficiencySuitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data.Blending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers computational reasoning of real-world data analyses.
Häftad, Engelska, 2013
1 110 kr
Skickas inom 10-15 vardagar
Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays. The XML and JSON data formats are widely used in Web services, regular Web pages and JavaScript code, and visualization formats such as SVG and KML for Google Earth and Google Maps. In addition, scientists use HTTP and other network protocols to scrape data from Web pages, access REST and SOAP Web Services, and interact with NoSQL databases and text search applications. This book provides a practical hands-on introduction to these technologies, including high-level functions the authors have developed for data scientists. It describes strategies and approaches for extracting data from HTML, XML, and JSON formats and how to programmatically access data from the Web. Along with these general skills, the authors illustrate several applications that are relevant to data scientists, such as reading and writing spreadsheet documents both locally and via Google Docs, creating interactive and dynamic visualizations, displaying spatial-temporal displays with Google Earth, and generating code from descriptions of data structures to read and write data. These topics demonstrate the rich possibilities and opportunities to do new things with these modern technologies. The book contains many examples and case-studies that readers can use directly and adapt to their own work. The authors have focused on the integration of these technologies with the R statistical computing environment. However, the ideas and skills presented here are more general, and statisticians who use other computing environments will also find them relevant to their work.Deborah Nolan is Professor of Statistics at University of California, Berkeley.Duncan Temple Lang is Associate Professor of Statistics at University of California, Davis and has been a member of both the S and R development teams.
E-bok
PDF, Engelska, 20131 413 kr
Läs direkt efter köp
Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays. The XML and JSON data formats are widely used in Web services, regular Web pages and JavaScript code, and visualization formats such as SVG and KML for Google Earth and Google Maps. In addition, scientists use HTTP and other network protocols to scrape data from Web pages, access REST and SOAP Web Services, and interact with NoSQL databases and text search applications. This book provides a practical hands-on introduction to these technologies, including high-level functions the authors have developed for data scientists. It describes strategies and approaches for extracting data from HTML, XML, and JSON formats and how to programmatically access data from the Web.
Along with these general skills, the authors illustrate several applications that are relevant to data scientists, such as reading and writing spreadsheet documents both locally and via Google Docs, creating interactive and dynamic visualizations, displaying spatial-temporal displays with Google Earth, and generating code from descriptions of data structures to read and write data. These topics demonstrate the rich possibilities and opportunities to do new things with these modern technologies. The book contains many examples and case-studies that readers can use directly and adapt to their own work. The authors have focused on the integration of these technologies with the R statistical computing environment. However, the ideas and skills presented here are more general, and statisticians who use other computing environments will also find them relevant to their work.
Deborah Nolan is Professor of Statistics at University of California, Berkeley.
Duncan Temple Lang is Associate Professor of Statistics at University of California, Davis and has been a member of both the S and R development teams.
Häftad, Engelska, 2015
1 390 kr
Skickas inom 10-15 vardagar
Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book’s collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standard, complex data formats, such as robot logs and email messagesText processing and regular expressionsNewer technologies, such as Web scraping, Web services, Keyhole Markup Language (KML), and Google EarthStatistical methods, such as classification trees, k-nearest neighbors, and naïve BayesVisualization and exploratory data analysisRelational databases and Structured Query Language (SQL)SimulationAlgorithm implementationLarge data and efficiencySuitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data.Blending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers’ computational reasoning of real-world data analyses.
E-bok
Engelska, 202356 kr
Läs direkt efter köp
SECOND ACT FOR CARRIE ARMSTRONG is a lighthearted and sweet romance with elements of suspense.Carrie Armstrong is a widow and single mother of four children. She's back working full time in the city while raising her kids in suburban New Jersey. She wants a calm life and a manageable job so she can make enough money to be able to focus on raising her kids.Ian Gordon is an ambitious prosecutor and Carrie's boss. He's never let anyone or anything get in the way of his goals. He aims to wrap up the child abuse case he's been recruited to prosecute so he can return to Washington, D.C. to continue to prosecute high profile cases on his journey to the top of his profession.Carrie is the only lawyer in the office with the expertise to help Ian solve the child abuse case. He assigns her to the case in spite of her reservations, promising to make allowances for the time she needs to care for her kids.Ian finds himself sucked up into the crazy world of Carrie Armstrong and her four kids and despite reservations he is soon immersed with all of it. Carrie doesn't trust him or his intentions, afraid he'll break her heart as well as her kids'.
E-bok
Engelska, 202355 kr
Läs direkt efter köp
Are we more than the roles we're expected--or even willingly--to fill?In her forties, Cassie McBride has come to the realization that she lost herself in marriage and trying to be a good mother to her two children, both now in college. While she loved her job as a family court lawyer, she can no longer separate what made her happy and what she did because she believed she was supposed to in order to be fulfilled.After her husband cheats on her with a neighbor in a scandalous affair that the entire New Jersey community they live in is witness to, she divorces him and moves to Scottsdale, Arizona to start over. With a new job at a nonprofit foundation, she buys herself a "e;makeover"e; wardrobe, determined to reinvent herself and figure out what truly makes her happy. With choices available that feel strange and exciting to her, she begins dating and exploring a whole new life.Just when things begin to settle down, her ex-husband suffers a massive heart attack. Barely hanging on, he has no one to care for him with his new girlfriend uninterested in playing nursemaid to him. Can Cassie allow either of her children to leave college to be there for their father...or will she have to fall back into an existence where her own needs are constantly overshadowed by others?
Häftad, Engelska, 2023
220 kr
Skickas inom 5-8 vardagar
Häftad, Engelska, 2023
220 kr
Skickas inom 5-8 vardagar