|
Dòng
|
Nội dung
|
|
1
|
Analyzing qualitative data with MAXQDA : text, audio, and video / Udo Kuckartz; Stefan Rädiker
Cham, Switzerland : Springer, 2019.
293 pages. : illustrations
Ký hiệu phân loại (DDC): 001.42
This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics
Số bản sách:
(0)
Tài liệu số:
(1)
|
|
2
|
|
|
3
|
HBR guide to data analytics basics for managers.
Boston, Massachusetts : Harvard Business Review Press,2018
x, 231 p. ; 23 cm.
Ký hiệu phân loại (DDC): 658.4033
Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data, but leaving the analysis to others in your company just won't cut it. Now more than ever, managers must know how to tease insight from data--to understand where it comes from, make sense of the numbers, and use those findings to inform their toughest decisions. But how do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes a three-step process to get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Formulate hypotheses and test against them Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes--
Số bản sách:
(1)
Tài liệu số:
(1)
|
|
4
|
Introduction to data science : a Python approach to concepts, techniques and applications / Laura Igual; Santi Seguí
Cham, Switzerland : Springer, 2017
227 pages. : illustrations
Ký hiệu phân loại (DDC): 006.312
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: Provides numerous practical case studies using real-world data throughout the book Supports understanding through hands-on experience of solving data science problems using Python Describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming Reviews a range of applications of data science, including recommender systems and sentiment analysis of text data Provides supplementary code resources and data at an associated website Số bản sách:
(0)
Tài liệu số:
(1)
|
|
5
|
|
|
|
|
|