This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester of such a course. It is freely available under the Creative Commons License, and includes a software library in Python for making some of the calculations and visualizations easier.

This is a list of terms and their definitions related to statistics provided by the Australian Bureau of Statistics, an organ of the government of the Commonwealth of Australia.

Statistical thinking is a way of understanding a complex world by describing it in relatively simple terms that nonetheless capture essential aspects of its structure, and that also provide us some idea of how uncertain we are about our knowledge. The foundations of statistical thinking come primarily from mathematics and statistics, but also from computer science, psychology, and other fields of study.

Introductory statistics course developed through the Ohio Department of Higher Education OER Innovation Grant. The course is part of the Ohio Transfer Module and is also named TMM010. For more information about credit transfer between Ohio colleges and universities please visit: www.ohiohighered.org/transfer.

I hope you find this book useful in teaching statistics. When writing this book, I tried to follow the GAISE Standards (GAISE recommendations. (2014, January 05). Retrieved from http://www.amstat.org/education/gaise/GAISECollege_Recommendations.pdf), which are:

1.) Emphasis statistical literacy and develop statistical understanding.
2.) Use real data.
3.) Stress conceptual understanding, rather than mere knowledge of procedure.
4.) Foster active learning in the classroom.
5.) Use technology for developing concepts and analyzing data.

To this end, I ask students to interpret the results of their calculations. I incorporated the use of technology for most calculations. Because of that you will not find me using any of the computational formulas for standard deviations or correlation and regression since I prefer students understand the concept of these quantities. Also, because I utilize technology you will not find the standard normal table, Student’s t-table, binomial table, chi-square distribution table, and F-distribution table in the book. The only tables I provided were for critical values for confidence intervals since they are more difficult to find using technology. Another difference between this book and other statistics books is the order of hypothesis testing and confidence intervals. Most books present confidence intervals first and then hypothesis tests. I find that presenting hypothesis testing first and then confidence intervals is more understandable for students. Lastly, I have deemphasized the use of the z-test. In fact, I only use it to introduce hypothesis testing, and never utilize it again. You may also notice that when I introduced hypothesis testing and confidence intervals, proportions were introduced before means. However, when two sample tests and confidence intervals are introduced I switched this order. This is because usually many instructors do not discuss the proportions for two samples. However, you might try assigning problems for proportions without discussing it in class. After doing two samples for means, the proportions are similar. Lastly, to aid student understanding and interest, most of the homework and examples utilize real data. Again, I hope you find this book useful for your introductory statistics class.

I want to make a comment about the mathematical knowledge that I assumed the students possess. The course for which I wrote this book has a higher prerequisite than most introductory statistics books. However, I do feel that students can read and understand this book as long as they have had basic algebra and can substitute numbers into formulas. I do not show how to create most of the graphs, but most students should have been exposed to them in high school. So I hope the mathematical level is appropriate for your course.

The technology that I utilized for creating the graphs was Microsoft Excel, and I utilized the TI-83/84 graphing calculator for most calculations, including hypothesis testing, confidence intervals, and probability distributions. This is because these tools are readily available to my students. Please feel free to use any other technology that is more appropriate for your students. Do make sure that you use some technology.

The law of demand states that quantity demanded increases when price decreases, but why? Two reasons why the demand curve slopes downward are the substitution effect and the income effect. The income effect states that when the price of a good decreases, it is as if the buyer of the good's income went up. The substitution effect states that when the price of a good decreases, consumers will substitute away from goods that are relatively more expensive to the cheaper good. Learn about the role of the income effect and the substitution effect on the shape of the demand curve in this video.

The Digital textbook for Survey of Chemistry I eBook is supported by Textbook Transformation Grant #383 Round#12 of Affordable Learning Georgia Initiative, WPLMS learning management platform for Word Press. We also acknowledge Physical Science Perimeter College GSU for supporting implementation. Unless otherwise noted, this eBook’s content is licensed by CC BY-NC-SA 3.0.

When a tax is imposed in a market this is another example of government intervention. In this video, we explore the effect of imposing a tax on the price and quantity in a market. Created by Sal Khan.

An interesting case of taxes and tax incidence is when one of the curves is perfectly elastic. Explore what happens when demand is perfectly elastic in this video. Created by Sal Khan.

The burden of a tax falls most heavily on someone who can't adjust to a price change. That means buyers bear a bigger burden when demand is more inelastic, and sellers bear a bigger burden when supply is more inelastic. Created by Sal Khan.

Texas Government OER textbook. Written by Dr. Daniel M. Regalado. Originally written in Fall 2017, reformatted May 2022. This EBook is the first OER Texas Government textbook ever written in the United States.

When a demand curve is linear, calculating consumer surplus becomes relatively simple: calculate the area of a triangle. In this video we walk through calculating consumer surplus. Created by Sal Khan.

The short-run production function describes the relationship between output and inputs when at least one input is fixed, such as out output varies based on the amount of labor used. We can use this production function to find the total product of labor, the marginal product of labor, and the average product of labor.

One of the most practical applications of price elasticity of demand is its relationship to total revenue. A seller who knows the price elasticity of demand for their good can make better decisions about what happens if they raise or lower the price of their good. Explore the relationship between total revenue and elasticity in this video. Created by Sal Khan.

When governments impose restrictions on international trade, this affects the domestic price of the good and reduces total surplus. One such imposition is a tariff (a tax on imported or exported goods and services). See how a tariff impacts price, consumer surplus, producer surplus, tax revenue, and deadweight loss in this video.

The tragedy of the commons occurs when goods are rival but not excludable. In this video, we explore the intuition, and consequences, behind such goods. Created by Sal Khan.

The main objective of this course is to give broad insight into the different facets of transportation systems, while providing a solid introduction to transportation demand and cost analyses. As part of the core in the Master of Science in Transportation program, the course will not focus on a specific transportation mode but will use the various modes to apply the theoretical and analytical concepts presented in the lectures and readings. Introduces transportation systems analysis, stressing demand and economic aspects. Covers the key principles governing transportation planning, investment, operations and maintenance. Introduces the microeconomic concepts central to transportation systems. Topics covered include economic theories of the firm, the consumer, and the market, demand models, discrete choice analysis, cost models and production functions, and pricing theory. Application to transportation systems include congestion pricing, technological change, resource allocation, market structure and regulation, revenue forecasting, public and private transportation finance, and project evaluation; covering urban passenger transportation, freight, aviation and intelligent transportation systems."

In imperfect competition, firms have some control over the price they charge, so the individual firm's demand curve is not horizontal. Learn how that fact also changes the marginal revenue curve in this video.