Students apply pre-requisite statistics knowledge and concepts learned in an associated lesson …
Students apply pre-requisite statistics knowledge and concepts learned in an associated lesson to a real-world state-of-the-art research problem that asks them to quantitatively analyze the effectiveness of different cracked steel repair methods. As if they are civil engineers, students statistically analyze and compare 12 sets of experimental data from seven research centers around the world using measurements of central tendency, five-number summaries, box-and-whisker plots and bar graphs. The data consists of the results from carbon-fiber-reinforced polymer patched and unpatched cracked steel specimens tested under the same stress conditions. Based on their findings, students determine the most effective cracked steel repair method, create a report, and present their results, conclusions and recommended methods to the class as if they were presenting to the mayor and city council. This activity and its associated lesson are suitable for use during the last six weeks of the AP Statistics course; see the topics and timing note for details.
Working as if they are engineers aiming to analyze and then improve …
Working as if they are engineers aiming to analyze and then improve data collection devices for precision agriculture, students determine how accurate temperature sensors are by comparing them to each other. Teams record soil temperature data during a class period while making changes to the samples to mimic real-world crop conditions—such as the addition of water and heat and the removal of the heat. Groups analyze their collected data by finding the mean, median, mode, and standard deviation. Then, the class combines all the team data points in order to compare data collected from numerous devices and analyze the accuracy of their recording devices by finding the standard deviation of temperature readings at each minute. By averaging the standard deviations of each minute’s temperature reading, students determine the accuracy of their temperature sensors. Students present their findings and conclusions, including making recommendations for temperature sensor improvements.
This is a new approach to an introductory statistical inference textbook, motivated …
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 course focuses on the problem of supervised learning from the perspective …
This course focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. It develops basic tools such as Regularization including Support Vector Machines for regression and classification. It derives generalization bounds using both stability and VC theory. It also discusses topics such as boosting and feature selection and examines applications in several areas: Computer Vision, Computer Graphics, Text Classification and Bioinformatics. The final projects and hands-on applications and exercises are planned, paralleling the rapidly increasing practical uses of the techniques described in the subject.
Statistical Mechanics is a probabilistic approach to equilibrium properties of large numbers …
Statistical Mechanics is a probabilistic approach to equilibrium properties of large numbers of degrees of freedom. In this two-semester course, basic principles are examined. Topics include: thermodynamics, probability theory, kinetic theory, classical statistical mechanics, interacting systems, quantum statistical mechanics, and identical particles.
This course discusses the principles and methods of statistical mechanics. Topics covered …
This course discusses the principles and methods of statistical mechanics. Topics covered include classical and quantum statistics, grand ensembles, fluctuations, molecular distribution functions, other concepts in equilibrium statistical mechanics, and topics in thermodynamics and statistical mechanics of irreversible processes.
This course is an introduction to statistical data analysis. Topics are chosen …
This course is an introduction to statistical data analysis. Topics are chosen from applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and nonparametric statistics.
Statistical thinking is a way of understanding a complex world by describing …
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.
This 13-minute video lesson provides analysis of variance 2: Calculating SSW and …
This 13-minute video lesson provides analysis of variance 2: Calculating SSW and SSB (total sum of squares within and between). [Statistics playlist: Lesson 76 of 85]
This 12-minute video lesson plays with the formula for variance of a …
This 12-minute video lesson plays with the formula for variance of a population. And looks at alternate variance formulas. [Statistics playlist: Lesson 16 of 85]
This 8-minute video lesson takes problems from CK12.org to discuss using the …
This 8-minute video lesson takes problems from CK12.org to discuss using the Empirical Rule with a standard normal distribution. [Statistics playlist: Lesson 33 of 85]
This 10-minute video lesson takes some problems from CK12.org and uses the …
This 10-minute video lesson takes some problems from CK12.org and uses the empirical rule (or 68-95-99.7 rule) to estimate probabilities for normal distributions. [Statistics playlist: Lesson 32 of 85]
This 11-minute video lesson takes some problems from CK12.org and discusses of …
This 11-minute video lesson takes some problems from CK12.org and discusses of how "normal" a distribution might be. [Statistics playlist: Lesson 30 of 85]
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