Drawing A Hypothesis

Drawing a Hypothesis is an exciting reader on the ontology of forms of visualizations and on the development of the diagrammatic view and its use in contemporary art, science and theory. In an intense process of exchange with artists and scientists, Nikolaus Gansterer reveals drawing as a media of research enabling the emergence of new narratives and ideas by tracing the speculative potential of diagrams. Based on a discursive analysis of found figures with the artists' own diagrammatic maps and models, the invited authors create unique correlations between thinking and drawing. Due to its ability to mediate between perception and reflection, drawing proves to be one of the most basic instruments of scientific and artistic practice, and plays an essential role in the production and communication of knowledge. The book is a rich compendium of figures of thought, which moves from scientific representation through artistic interpretation and vice versa.

Statistics: A Short, Clear Guide is an accessible, humorous and easy introduction to statistics for social science students. In this refreshing book, experienced author and academic Neil Burdess shows that statistics are not the result of some mysterious "black magic", but rather the result of some very basic arithmetic. Getting rid of confusing x′s and y′s, he shows that it′s the intellectual questions that come before and after the calculations that are important: (i) What are the best statistics to use with your data? and (ii) What do the calculated statistics tell you? Statistics: A Short, Clear Guide aims to help students make sense of the logic of statistics and to decide how best to use statistics to analyse their own data. What′s more, it is not reliant on students having access to any particular kind of statistical software package. This is a very useful book for any student in the social sciences doing a statistics course or needing to do statistics for themselves for the first time.

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

The Simulation Hypothesis, by best-selling author, renowned MIT computer scientist and Silicon Valley video game designer Rizwan Virk, is the first serious book to explain one of the most daring and consequential theories of our time. Riz is the Executive Director of Play Labs @ MIT, a video game startup incubator at the MIT Game Lab. Drawing from research and concepts from computer science, artificial intelligence, video games, quantum physics, and referencing both speculative fiction and ancient eastern spiritual texts, Virk shows how all of these traditions come together to point to the idea that we may be inside a simulated reality like the Matrix. The Simulation Hypothesis is the idea that our physical reality, far from being a solid physical universe, is part of an increasingly sophisticated video game-like simulation, where we all have multiple lives, consisting of pixels with its own internal clock run by some giant Artificial Intelligence. Simulation theory explains some of the biggest mysteries of quantum and relativistic physics, such as quantum indeterminacy, parallel universes, and the integral nature of the speed of light. Recently, the idea that we may be living in a giant video game has received a lot of attention: “There’s a one in a billion chance we are not living in a simulation” -Elon Musk “I find it hard to argue we are not in a simulation.” -Neil deGrasse Tyson “We are living in computer generated reality.” -Philip K. Dick Video game technology has developed from basic arcade and text adventures to MMORPGs. Video game designer Riz Virk shows how these games may continue to evolve in the future, including virtual reality, augmented reality, Artificial Intelligence, and quantum computing. This book shows how this evolution could lead us to the point of being able to develop all encompassing virtual worlds like the Oasis in Ready Player One, or the simulated reality in the Matrix. While the idea sounds like science fiction, many scientists, engineers, and professors have given the Simulation Hypothesis serious consideration. Futurist Ray Kurzweil has popularized the idea of downloading our consciousness into a silicon based device, which would mean we are just digital information after all. Some, like Oxford lecturer Nick Bostrom, goes further and thinks we may in fact be artificially intelligent consciousness inside such a simulation already! But the Simulation Hypothesis is not just a modern idea. Philosophers like Plato have been telling us that we live in a “cave” and can only see shadows of the real world. Mystics of all traditions have long contended that we are living in some kind of “illusion “and that there are other realities which we can access with our minds. While even Judeo-Christian traditions have this idea, Eastern traditions like Buddhism and Hinduism make this idea part of their core tradition — that we are inside a dream world (“Maya” or illusion, or Vishnu’s Dream), and we have “multiple lives” playing different characters when one dies, continuing to gain experience and “level up” after completing certain challenges. Sounds a lot like a video game! Whether you are a computer scientist, a fan of science fiction like the Matrix movies, a video game enthusiast, or a spiritual seeker, The Simulation Hypothesis touches on all these areas, and you will never look at the world the same way again!

Choreo-graphic Figures: Deviations from the Line stages a beyond-disciplinary, inter-subjective encounter between the lines of choreography, drawing and writing, for exploring those forms of thinking-feeling-knowing produced through collaborative exchange, in the slippage and deviation, as different modes of practice enter into dialogue, overlap, collide. The publication is conceived as a studio-laboratory in itself, drawing together critical reflections and experimental practices that focus on the how-ness -- the qualitative-procedural, aesthetic-epistemological and ethical-empathetic dynamics -- within shared artistic exploration, directing attention to an affective realm of forces and intensities existing before, between and beneath the more readable gestures of artistic practice.

This core textbook introduces psychology students to research methods. The author's principal goal is to present methods in a way that will lend coherence to the material. He does this by providing a meaningful framework based around Campbell and Stanley's "threats to validity" and by organizing the book around the phases of the research process. In addition, in his approach and via boxed features, the author encourages and models a process of critical thinking for students.

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.

One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.