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Advanced High School Statistics
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CC BY-SA
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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

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
OpenIntro
Author:
Christopher Barr
David Diez
Leah Dorazio
Mine Cetinkaya-Rundel
Date Added:
05/22/2019
Applied Statistics, Spring 2009
Only Sharing Permitted
CC BY-NC-ND
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I designed the course for graduate students who use statistics in their research, plan to use statistics, or need to interpret statistical analyses performed by others. The primary audience are graduate students in the environmental sciences, but the course should benefit just about anyone who is in graduate school in the natural sciences. The course is not designed for those who want a simple overview of statistics; we’ll learn by analyzing real data. This course or equivalent is required for UMB Biology and EEOS Ph.D. students. It is a recommended course for several of the intercampus graduate school of marine science program options.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
UMass Boston
Provider Set:
UMass Boston OpenCourseWare
Author:
Eugene Gallagher
Date Added:
05/23/2019
The Art of the Probable: Literature and Probability, Spring 2008
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CC BY-NC-SA
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The Art of the Probable" addresses the history of scientific ideas, in particular the emergence and development of mathematical probability. But it is neither meant to be a history of the exact sciences per se nor an annex to, say, the Course 6 curriculum in probability and statistics. Rather, our objective is to focus on the formal, thematic, and rhetorical features that imaginative literature shares with texts in the history of probability. These shared issues include (but are not limited to): the attempt to quantify or otherwise explain the presence of chance, risk, and contingency in everyday life; the deduction of causes for phenomena that are knowable only in their effects; and, above all, the question of what it means to think and act rationally in an uncertain world. Our course therefore aims to broaden students’ appreciation for and understanding of how literature interacts with--both reflecting upon and contributing to--the scientific understanding of the world. We are just as centrally committed to encouraging students to regard imaginative literature as a unique contribution to knowledge in its own right, and to see literary works of art as objects that demand and richly repay close critical analysis. It is our hope that the course will serve students well if they elect to pursue further work in Literature or other discipline in SHASS, and also enrich or complement their understanding of probability and statistics in other scientific and engineering subjects they elect to take.

Subject:
Arts and Humanities
English Language Arts
Literature
Mathematics
Philosophy
Religious Studies
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Jackson, Noel
Kibel, Alvin
Raman, Shankar
Date Added:
01/01/2008
Behavior of Sample Mean (1 of 3)
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CC BY-NC-SA
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Apply the sampling distribution of the sample mean as summarized by the Central Limit Theorem (when appropriate). In particular, be able to identify unusual samples from a given population.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
05/22/2019
Biological Engineering II: Instrumentation and Measurement, Fall 2006
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course covers sensing and measurement for quantitative molecular/cell/tissue analysis, in terms of genetic, biochemical, and biophysical properties. Methods include light and fluorescence microscopies; electro-mechanical probes such as atomic force microscopy, laser and magnetic traps, and MEMS devices; and the application of statistics, probability and noise analysis to experimental data.

Subject:
Biology
Electronic Technology
Life Science
Mathematics
Professional Studies
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
So, Peter
Date Added:
01/01/2006
Business Statistics
Unrestricted Use
CC BY
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Introductory survey of quantitative methods (QM), or the application of statistics in the workplace. Examines techniques for gathering, analyzing, and interpreting data in any number of fieldsĺÎĺ from anthropology to hedge fund management.

Subject:
Business and Finance
Management
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Full Course
Homework/Assignment
Reading
Syllabus
Provider:
The Saylor Foundation
Date Added:
10/24/2019
The Central Limit Theorem
Conditional Remix & Share Permitted
CC BY-NC-SA
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The applets in this section of Statistical Java allow you to see how the Central Limit Theorem works. The main page gives the characteristics of five non-normal distributions (Bernoulli, Poisson, Exponential, U-shaped, and Uniform).

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
05/23/2019
City Life - Inquiry and Problem Solving Exercise
Unrestricted Use
CC BY
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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.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
CUNY Academic Works
Provider Set:
LaGuardia Community College
Author:
Milena Cuellar
Date Added:
01/01/2017
Computation for Biological Engineers, Fall 2006
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course covers the analytical, graphical, and numerical methods supporting the analysis and design of integrated biological systems. Topics include modularity and abstraction in biological systems, mathematical encoding of detailed physical problems, numerical methods for solving the dynamics of continuous and discrete chemical systems, statistics and probability in dynamic systems, applied local and global optimization, simple feedback and control analysis, statistics and probability in pattern recognition.

Subject:
Genetics
Life Science
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Alm, Eric
Date Added:
01/01/2006
Confidence Intervals
Conditional Remix & Share Permitted
CC BY-NC-SA
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The applets in this section of Statistical Java allow you to see how levels of confidence are achieved through repeated sampling. The confidence intervals are related to the probability of successes in a Binomial experiment.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C.Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S.Dorai-Raj
T.Robinson
Date Added:
05/23/2019
Control Charts
Conditional Remix & Share Permitted
CC BY-NC-SA
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The applets in this section allow you to see how the common Xbar control chart is constructed with known variance. The Xbar chart is constructed by collecting a sample of size n at different times t.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Doria-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
05/23/2019
Correlation
Conditional Remix & Share Permitted
CC BY-NC-SA
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The applets in this section allow you to see how different bivariate data look under different correlation structures. The Movie applet either creates data for a particular correlation or animates a multitude data sets ranging correlations from -1 to 1.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
05/23/2019
Criminal Justice Statistics
Conditional Remix & Share Permitted
CC BY-NC-SA
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This lab uses statistics and demographic data on the City of Baltimore. We will enter, format, and analyze that data in Microsoft Excel.
Please note: this lab is written for a beginner in Excel and meant to introduce you to various capabilities of Excel. You may feel the need to skip through some steps if you are experienced with Excel, and that is fine. Just make sure you understand the content of the lab! Future work will build on these skills.

Subject:
Criminal Justice
Mathematics
Social Science
Statistics and Probability
Material Type:
Activity/Lab
Data Set
Homework/Assignment
Author:
Elias Nader
Date Added:
05/10/2021
Data Analysis
Conditional Remix & Share Permitted
CC BY-NC-SA
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The applet in this section allows for simple data analysis of univariate data. Users can either generate normal or uniform data for k samples or copy and paste data from another source to a text box. A univariate analysis is performed for all k samples.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
C. Anderson-Cook, S. Dorai-Raj, T. Robinson, Virginia Tech Department of Statistics
Date Added:
05/23/2019
Design of Electromechanical Robotic Systems, Fall 2009
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course covers the design, construction, and testing of field robotic systems, through team projects with each student responsible for a specific subsystem. Projects focus on electronics, instrumentation, and machine elements. Design for operation in uncertain conditions is a focus point, with ocean waves and marine structures as a central theme. Topics include basic statistics, linear systems, Fourier transforms, random processes, spectra, ethics in engineering practice, and extreme events with applications in design.

Subject:
Applied Science
Environmental Science
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Chin, Harrison
Hover, Franz
Date Added:
01/01/2010
Estimation
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CC BY-NC-SA
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Learning Objectives: 1).Determine point estimates in simple cases, and make the connection between the sampling distribution of a statistic, and its properties as a point estimator.
2). Explain what a confidence interval represents and determine how changes in sample size and confidence level affect the precision of the confidence interval.
3). Find confidence intervals for the population mean and the population proportion (when certain conditions are met), and perform sample size calculations.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
05/22/2019
Examining Distributions
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CC BY-NC-SA
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1). Summarize and describe the distribution of a categorical variable in context.
2). Generate and interpret several different graphical displays of the distribution of a quantitative variable (histogram, stemplot, boxplot).
3). Summarize and describe the distribution of a quantitative variable in context: a) describe the overall pattern, b) describe striking deviations from the pattern.
4). Relate measures of center and spread to the shape of the distribution, and choose the appropriate measures in different contexts.
5). Compare and contrast distributions (of quantitative data) from two or more groups, and produce a brief summary, interpreting your findings in context.
5). Apply the standard deviation rule to the special case of distributions having the "normal" shape.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
05/22/2019
Exponential Probabilities
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CC BY-NC-SA
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The applet in this section allows you see how probabilities are determined from the exponential distribution. The user determines the mean of the distribution and the limits of probability. Three different probability expressions are available.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
05/23/2019
Foundations of Mathematics
Unrestricted Use
CC BY
Rating
0.0 stars

This course focuses on algebraic and numerical skills in a context of applications and problem-solving to prepare students for Statistics. Topics will include quantitative relationships, patterning and algebraic reasoning, functional reasoning, probabilistic and statistical reasoning, incorporating quantitative communication skills and technology

Subject:
Algebra
Mathematics
Statistics and Probability
Material Type:
Assessment
Full Course
Homework/Assignment
Author:
Cassandra Frandsen
Date Added:
12/16/2021
How to Process, Analyze and Visualize Data, January IAP 2012
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course is an introduction to data cleaning, analysis and visualization. We will teach the basics of data analysis through concrete examples. You will learn how to take raw data, extract meaningful information, use statistical tools, and make visualizations. This was offered as a non-credit course during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Adam Marcus
Eugene Wu
Date Added:
01/01/2012