This textbook is part of the OpenIntro Statistics series and offers complete coverage of the high school AP Statistics curriculum. Real data and plenty of inline examples and exercises make this an engaging and readable book. Links to lecture slides, video overviews, calculator tutorials, and video solutions to selected end of chapter exercises make this an ideal choice for any high school or Community College teacher. In fact, Portland Community College recently adopted this textbook for its Introductory Statistics course, and it estimates that this will save their students $250,000 per year. Find out more at: openintro.org/ahss

View our video tutorials here:
openintro.org/casio
openintro.org/TI

In Basic Engineering Data Collection and Analysis, Stephen B. Vardeman and J. Marcus Jobe stress the practical over the theoretical. Step by step, students get real engineering data and scenario examples along with chapter-long case studies that illustrate concepts in realistic, thoroughly detailed situations. This approach encourages students to work through the material by carrying out data collection and analysis projects from problem formulation through the preparation of professional technical reports—just as if they were on the job.

Living in a big city like New York can be very challenging. City planning is an interdisciplinary enterprise where social scientists, humanists, psychologists, scientists, statisticians, citizens, politicians, etc. come together to offer solutions to improve quality of life in the city. To find such solutions, these people need clear and reliable (qualitative and quantitative) information about specific challenges that residents and visitors face For the variety of stakeholders in the city, many different things might be considered worthy of study, depending on their interests and needs regarding, e.g., employment, financial status, family size, healthcare, mobility, and education.
For example, do you know whether your neighborhood issufficiently protected from a fire? What about other neighborhoods in the city? To what extent does a CUNY degree help a person gain employment in the City? In which ways do race or gender or sexual preference play a role in how people experience city life? Can these be quantified in dollar terms? Once you have identified a problem, write an essay that describes a question
about city life that you believe is worthy of a statistical study.

This course blends Introductory Statistics from OpenStax with other OER to offer a first course in statistics intended for students majoring in fields other than mathematics and engineering. This course assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it.The foundation of the OpenStax text is Collaborative Statistics, by Barbara Illowsky and Susan Dean. The development choices for this textbook were made with the guidance of many faculty members who are deeply involved in teaching this course. These choices led to innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful, so that students can draw from it a working knowledge that will enrich their future studies and help them make sense of the world around them.

This textbook instructs on the uses of applied statistics within the field of psychology.

This is the website for Introduction to Modern Statistics, First Edition by Mine Çetinkaya-Rundel and Johanna Hardin. Introduction to Modern Statistics, which we’ll refer to as IMS going forward, is a textbook from the OpenIntro project.
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Copyright © 2021.
First Edition.
Version date: June 27, 2021.

This textbook and its supplements, including slides, labs, and interactive tutorials, may be downloaded for free at
openintro.org/book/ims.

This textbook is a derivative of OpenIntro Statistics 4th Edition and Introduction to Statistics with Randomization and Simulation 1st Edition by Diez, Barr, and Çetinkaya-Rundel, and it’s available under a Creative Commons Attribution-ShareAlike 3.0 Unported United States License. License details are available at the Creative Commons website: creativecommons.org.

Source files for this book may be found on GitHub at github.com/openintrostat/ims.

This work has been superseded by Introduction to Statistics in the Psychological Sciences available from https://irl.umsl.edu/oer/25/.

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We are constantly bombarded by information, and finding a way to filter that information in an objective way is crucial to surviving this onslaught with your sanity intact. This is what statistics, and logic we use in it, enables us to do. Through the lens of statistics, we learn to find the signal hidden in the noise when it is there and to know when an apparent trend or pattern is really just randomness. The study of statistics involves math and relies upon calculations of numbers. But it also relies heavily on how the numbers are chosen and how the statistics are interpreted.

This work was created as part of the University of Missouri’s Affordable and Open Access Educational Resources Initiative (https://www.umsystem.edu/ums/aa/oer). The contents of this work have been adapted from the following Open Access Resources: Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University. Changes to the original works were made by Dr. Garett C. Foster in the Department of Psychological Sciences to tailor the text to fit the needs of the introductory statistics course for psychology majors at the University of Missouri – St. Louis. Materials from the original sources have been combined, reorganized, and added to by the current author, and any conceptual, mathematical, or typographical errors are the responsibility of the current author.

The book is intended as an upper level undergraduate or introductory graduate textbook in statistical thinking with a likelihood emphasis for students with a good knowledge of calculus and the ability to think abstractly. By "statistical thinking" is meant a focus on ideas that statisticians care about as opposed to technical details of how to put those ideas into practice. The book does contain technical details, but they are not the focus. By "likelihood emphasis" is meant that the likelihood function and likelihood principle are unifying ideas throughout the text.

Another unusual aspect is the use of statistical software as a pedagogical tool. That is, instead of viewing the computer merely as a convenient and accurate calculating device, the book uses computer calculation and simulation as another way of explaining and helping readers understand the underlying concepts. The book is written with the statistical language R embedded throughout. R and accompanying manuals are available for free download from http://www.r-project.org.

Psychology students often find statistics courses to be different from their other psychology classes. There are some distinct differences, especially involving study strategies for class success. The first difference is learning a new vocabulary—it is similar to learning a new language. Knowing the meaning of certain words will help as you are reading the material and working through the problems. Secondly, practice is critical for success; reading over the material is not enough. Statistics is a subject learned by doing, so make sure you work through any homework questions, chapter questions, and practice problems available. Lastly, we recommend that you ask questions and get help from your instructor when needed. Struggling with the course material can be frustrating, and frustration is your enemy. Often your instructor can get you back on track quickly.

"Introductory Business Statistics with Interactive Spreadsheets - 1st Canadian Edition" is an adaptation of Thomas K. Tiemann's book, "Introductory Business Statistics". In addition to covering basics such as populations, samples, the difference between data and information, and sampling distributions, descriptive statistics and frequency distributions, normal and t-distributions, hypothesis testing, t-tests, f-tests, analysis of variance, non-parametric tests, and regression basics, the following information has been added: the chi-square test and categorical variables, null and alternative hypotheses for the test of independence, simple linear regression model, least squares method, coefficient of determination, confidence interval for the average of the dependent variable, and prediction interval for a specific value of the dependent variable. This new edition also allows readers to learn the basic and most commonly applied statistical techniques in business in an interactive way -- when using the web version -- through interactive Excel spreadsheets. All information has been revised to reflect Canadian content.

This textbook is an introduction to Psychology. It covers how psychologists think, principles of memory, learning, and thinking; human nature, human development, the social world, and wellbeing.

Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs.

Introductory Statistics is intended for the one-semester introduction to statistics course for students who are not mathematics or engineering majors. It focuses on the interpretation of statistical results, especially in real world settings, and assumes that students have an understanding of intermediate algebra. In addition to end of section practice and homework sets, examples of each topic are explained step-by-step throughout the text and followed by a Try It problem that is designed as extra practice for students. This book also includes collaborative exercises and statistics labs designed to give students the opportunity to work together and explore key concepts. While the book has been built so that each chapter builds on the previous, it can be rearranged to accommodate any instructor’s particular needs.

"An Intuitive, Interactive Introduction to Biostatistics" is an introductory statistics textbook oriented towards towards undergraduate students in the health sciences. While covering the breadth of material typically presented in a first semester statistics course, including introductions to probability and distributions, study design, CLT, hypothesis testing, and inference, IIIB distinguishes itself with its focus on cultivating student intuition through the use of guided questions and interactive simulation-based applets. Written in R, this open-source text has been created with customizability in mind, offering instructors maximal flexibility in arranging and modifying the content.

The book is associated with the lsr package on CRAN and GitHub. The package is probably okay for many introductory teaching purposes, but some care is required. The package does have some limitations (e.g., the etaSquared function does strange things for unbalanced ANOVA designs), and it has not been updated in a while.

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. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts.

Mathematical Reasoning and Investigation is designed to help you develop the ability to use mathematics to solve the kinds of problems that don't come with answers in the back of the book. We like to think of it as a mathematics book for people who think they're not good at mathematics. The work will be useful for anyone wanting to develop their own skills in reasoning and problem solving using mathematics, and for teachers and preservice teachers hoping to help their students to develop these same skills.

This text is for an introductory level course in probability and statistics.

This work, "Mostly Harmless Probability and Statistics for NMC", is a derivative of "Mostly
Harmless Statistics" by Rachel Webb used under CC BY-NC 4.0. "Mostly Harmless Probability
and Statistics for NMC" is licensed under CC BY-NC 4.0 by Briana Mills.

Rachel Webb’s original text was a combination of Webb’s work, Statistics
Using Technology by Kathryn Kozak, and OpenIntro Statistics by Diez, Barr, Çetinkaya-Rundel.
All texts are licensed under CC BY-SA 4.0. Additional problem sets provided by Whitney Cave.
It has been updated by Briana Mills with help from Nate Butler and Tony Jenkins to match the
curriculum at NMC.

The textbook solutions for this book are available at: https://drive.google.com/drive/u/1/folders/1BTXchIplWzk0mjohao2xrE4cfeOOUsvI

Review of Answering Questions with Data
https://drive.google.com/open?id=15lxoO1g39m6JICO7eKhiLR_pQqB4iOoJJtcylZJgp2E