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Poor Numbers: How We Are Misled by African Development Statistics and What to Do About It rogers l willoughby d numbers data and statistics for the non specialist
One of the most urgent challenges in African economic development is to devise a strategy for improving statistical capacity. Reliable statistics, including estimates of economic growth rates and per-capita income, are basic to the operation of governments in developing countries and vital to nongovernmental organizations and other entities that provide financial aid to them. Rich countries and international financial institutions such as the World Bank allocate their development resources on the basis of such data. The paucity of accurate statistics is not merely a technical problem; it has a massive impact on the welfare of citizens in developing countries. Where do these statistics originate? How accurate are they? POOR NUMBERS is the first analysis of the production and use of African economic development statistics. Morten Jerven's research shows how the statistical capacities of sub-Saharan African economies have fallen into disarray.
1089 RUR
INTRODUCTION TO STATISTICS rogers l willoughby d numbers data and statistics for the non specialist
To most people the word statistics conjures up images of vast tables of confusing numbers, volumes and volumes of figures pertaining to births, deaths, taxes, populations, and so forth, or figures indicating baseball batting averages or football yardage gained flashing across television screens. This is so because in common usage the word statistics is synonymous with the word data. In a sense this is a reasonably accurate impression because the discipline of statistics deals largely with principles and procedures for collecting, describing, and drawing conclusions from data. Therefore it is appropriate for a text in statistics to start by discussing the nature and scope of statistics. Chapter Two discusses data collection. The purpose of this chapter is to provide the definition of a set of data, define the components of such a data set, present tools that are used to describe a data set, and briefly discuss methods of data collection. Chapter Three presents diagrams, charts and graphs. Chapter Four discusses measure of central tendency. Chapter Five presents measure of dispersion and some practice questions.
4631 RUR
SPSS Statistics for Data Analysis and Visualization rogers l willoughby d numbers data and statistics for the non specialist
Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.
4629 RUR
Statistical Techniques for Data Analysis rogers l willoughby d numbers data and statistics for the non specialist
The Statistical Techniques for Data Analysis contains, • Meaning and Definition of Statistics • Measurement and Enumeration • Statistical Frequency Distributions • Measures of Central Tendency • Measures of Variability • Deciles, Percentiles, Percentile Ranks and Standard Scores • Normal Curve • Correlation • Regression • Statistical Inference and Significance of Statistics • Difference Between Means and Other Statistics • Chi-square Test • Non-Parametric Tests • Special Methods of Correlation • ANOVA • Analysis of Variance and Factorial Designs • ANCOVA • Partial and Multiple Correlations • Scaling of Tests • Item Analysis • Reliability and Validity • Factor Analysis • Use of Computer in Educational Research. The book provide the clear understanding of basic descriptive and inferential statistics. It shows the practical understanding of statistics, in data analysis. It contains enough suitable illustrations for manual computation. This book will be useful for new researchers of M.Ed., M.Phil. and Ph.D., to choose the suitable techniques for data analysis.
7466 RUR
A Casebook for a First Course in Statistics and Data Analysis rogers l willoughby d numbers data and statistics for the non specialist
Designed to engage students in the ``how'' and ``why'' of the data analyzing process rather than merely the ``what.'' Uses actual examples of analyses of real data. Each case is motivated by a question which needs to be answered and is presented with complete background material. The statistical analysis flows naturally from the question, encouraging students to understand the methods in order to reach a meaningful conclusion.
10179 RUR
Alan  Anderson Statistics for Big Data For Dummies rogers l willoughby d numbers data and statistics for the non specialist
The fast and easy way to make sense of statistics for big data Does the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word «statistics» alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining—without losing your cool. Helps you to identify valid, useful, and understandable patterns in data Provides guidance on extracting previously unknown information from large databases Shows you how to discover patterns available in big data Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed.
1321.79 RUR