Online courses directory (44)

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99 votes
Khan Academy Free Closed [?] Mathematics Algebra II California Standards Test

California Standards Test: Algebra II. California Standards Test: Algebra II (Graphing Inequalities). CA Standards: Algebra II (Algebraic Division/Multiplication). CA Standards: Algebra II. Algebra II: Simplifying Polynomials. Algebra II: Imaginary and Complex Numbers. Algebra II: Complex numbers and conjugates. Algebra II: Quadratics and Shifts. Examples: Graphing and interpreting quadratics. Hyperbola and parabola examples. Algebra II: Circles and Logarithms. Algebra II: Logarithms Exponential Growth. Algebra II: Logarithms and more. Algebra II: Functions, Combinatorics. Algebra II: binomial Expansion and Combinatorics. Algebra II: Binomial Expansions, Geometric Series Sum. Algebra II: Functions and Probability. Algebra II: Probability and Statistics. Algebra II: Mean and Standard Deviation.

No votes
OLI. Carnegie Mellon University Free Mathematics Carnegie Mellon University Open Learning Initiative

This course provides an introduction to causal and statistical reasoning. After taking this course, students will be better prepared to make rational decisions about their own lives and about matters of social policy. They will be able to assess criticallyeven if informallyclaims that they encounter during discussions or when considering a news article or report. A variety of materials are presented, including Case Studies where students are given the opportunity to examine a causal claim, and the Causality Lab, a virtual environment to simulate the science of causal discovery. Students have frequent opportunities to check their understanding and practice their skills. This course is meant to serve students in several situations. One, it is meant for students who will only take one such research methods course, and are interested in gaining basic skills that will help them to think critically about claims they come across in their daily lives, such as through a news article. Two, it is meant for students who will take a few statistics courses in service of a related field of study. Three, it is meant for students interested in the foundations of quantitative causal models: called Bayes Networks.

No votes
Study.com Free Closed [?] Mathematics Common Core EPA

Build your earth science vocabulary and learn about cycles of matter and types of sedimentary rocks through the Education Portal course Earth Science 101: Earth Science. Our series of video lessons and accompanying self-assessment quizzes can help you boost your scientific knowledge ahead of the Excelsior Earth Science exam . This course was designed by experienced educators and examines both science basics, like experimental design and systems of measurement, and more advanced topics, such as analysis of rock deformation and theories of continental drift.

13 votes
Udemy Free Closed [?] Mathematics Math and Science

Lectures by Prof. S.K.RayrnDepartment of Mathematics and StatisticsrnIIT Kanpur

5 votes
Saylor.org Free Closed [?] Mathematics Computer Science Math and Science Statistics Statistics and Data Analysis

In this course, you will look at the properties behind the basic concepts of probability and statistics and focus on applications of statistical knowledge.  You will learn about how statistics and probability work together.  The subject of statistics involves the study of methods for collecting, summarizing, and interpreting data.  Statistics formalizes the process of making decisions, and this course is designed to help you use statistical literacy to make better decisions.  Note that this course has applications for the natural sciences, economics, computer science, finance, psychology, sociology, criminology, and many other fields. We read data in articles and reports every day.  After finishing this course, you should be comfortable evaluating an author's use of data.  You will be able to extract information from articles and display that information effectively.  You will also be able to understand the basics of how to draw statistical conclusions. This course will begin with descriptive statistic…

19 votes
ALISON Free Mathematics Course Type: diploma Free to Access Mime Type - Scorm 1.2

ALISON.com's free online Diploma in Mathematics course gives you comprehensive knowledge and understanding of key subjects in mathematics. This course covers calculus, geometry, algebra, trigonometry, functions, vectors, data distributions, probability and probability and statistics. Math qualifications are in great demand from employers and this math course will greatly enhance your career prospects.<br />

13 votes
ALISON Free Mathematics Course Type: diploma Free to Access Mime Type - Scorm 1.2

Statistics and statistical methods play a major role in the work environment in areas such as business, science, finance, economics, engineering to mention just a few. It is very important that people are comfortable with reading statistics and using statistical methods. This free online Diploma in Statistics will give you the knowledge and understanding of basic statistical methods such as sampling and collecting data, probability, distributions, regression analysis. By completing this course you will gain the knowledge and understanding to confidently read statistics and apply statistical methods within your daily working environment.

282 votes
Udacity Free Popular Closed [?] Computer Sciences Data Science

Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.

Starts : 2009-09-01
18 votes
MIT OpenCourseWare (OCW) Free Computer Sciences Electrical Engineering and Computer Science MIT OpenCourseWare Undergraduate

This course aims to give students the tools and training to recognize convex optimization problems that arise in scientific and engineering applications, presenting the basic theory, and concentrating on modeling aspects and results that are useful in applications. Topics include convex sets, convex functions, optimization problems, least-squares, linear and quadratic programs, semidefinite programming, optimality conditions, and duality theory. Applications to signal processing, control, machine learning, finance, digital and analog circuit design, computational geometry, statistics, and mechanical engineering are presented. Students complete hands-on exercises using high-level numerical software.

Acknowledgements

The course materials were developed jointly by Prof. Stephen Boyd (Stanford), who was a visiting professor at MIT when this course was taught, and Prof. Lieven Vanderberghe (UCLA).

Starts : 2014-02-01
9 votes
MIT OpenCourseWare (OCW) Free Mathematics MIT OpenCourseWare Undergraduate

This course provides an elementary introduction to probability and statistics with applications. Topics include: basic combinatorics, random variables, probability distributions, Bayesian inference, hypothesis testing, confidence intervals, and linear regression.

The Spring 2014 version of this subject employed the residential MITx system, which enables on-campus subjects to provide MIT students with learning and assessment tools such as online problem sets, lecture videos, reading questions, pre-lecture questions, problem set assistance, tutorial videos, exam review content, and even online exams.

No votes
ed2go $149.00 Mathematics Ed2go

Improve your understanding of data and learn how to develop graphs and charts so you can use this information to make better decisions.

Starts : 2014-02-24
105 votes
edX Free Closed [?] Mathematics English Data Analysis & Statistics EdX Math UC BerkeleyX

We are surrounded by information, much of it numerical, and it is important to know how to make sense of it. Stat2x is an introduction to the fundamental concepts and methods of statistics, the science of drawing conclusions from data.

The course is the online equivalent of Statistics 2, a 15-week introductory course taken in Berkeley by about 1,000 students each year. Stat2x is divided into three 5-week components. Stat2.1x is the first of the three.

The focus of Stat2.1x is on descriptive statistics. The goal of descriptive statistics is to summarize and present numerical information in a manner that is illuminating and useful. The course will cover graphical as well as numerical summaries of data, starting with a single variable and progressing to the relation between two variables. Methods will be illustrated with data from a variety of areas in the sciences and humanities.

There will be no mindless memorization of formulas and methods. Throughout Stat2.1x, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.

FAQ

  • What is the format of the class?
    • Instruction will be consist of brief lectures and exercises to check comprehension. Grades (Pass or Not Pass) will be decided based on a combination of scores on short assignments, quizzes, and a final exam.
  • How much does it cost to take the course?
    • Nothing! The course is free.
  • Will the text of the lectures be available?
    • Yes. All of our lectures will have transcripts synced to the videos.
  • Do I need to watch the lectures live?
    • No. You can watch the lectures at your leisure.
  • Can I contact the Instructor or Teaching Assistants?
    • Yes, but not directly. The discussion forums are the appropriate venue for questions about the course. The instructors will monitor the discussion forums and try to respond to the most important questions; in many cases response from other students and peers will be adequate and faster.
  • Do I need any other materials to take the course?
    • If you have any questions about edX generally, please see the edX FAQ.

Starts : 2014-06-02
No votes
edX Free Closed [?] Mathematics English Data Analysis & Statistics EdX Math UC BerkeleyX

Statistics 2 at Berkeley is an introductory class taken by about 1,000 students each year. Stat2.3x is the last in a sequence of three courses that make up Stat2x, the online equivalent of Berkeley's Stat 2. The focus of Stat2.3x is on statistical inference: how to make valid conclusions based on data from random samples. At the heart of the main problem addressed by the course will be a population (which you can imagine for now as a set of people) connected with which there is a numerical quantity of interest (which you can imagine for now as the average number of MOOCs the people have taken). If you could talk to each member of the population, you could calculate that number exactly. But what if the population is so large that your resources will not stretch to interviewing every member? What if you can only reach a subset of the population?

Stat 2.3x will discuss good ways to select the subset (yes, at random); how to estimate the numerical quantity of interest, based on what you see in your sample; and ways to test hypotheses about numerical or probabilistic aspects of the problem.

The methods that will be covered are among the most commonly used of all statistical techniques. If you have ever read an article that claimed, "The margin of error in such surveys is about three percentage points," or, "Researchers at the University of California at Berkeley have discovered a highly significant link between ...," then you should expect that by the end of Stat 2.3x you will have a pretty good idea of what that means. Examples will range all the way from a little girl's school science project (seriously – she did a great job and her results were published in a major journal) to rulings by the U.S. Supreme Court.

The fundamental approach of the series was provided in the description of Stat2.1x and appears here again: There will be no mindless memorization of formulas and methods. Throughout the course, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.

Starts : 2014-04-14
13 votes
edX Free Closed [?] Mathematics English Data Analysis & Statistics EdX Math UC BerkeleyX

Statistics 2 at Berkeley is an introductory class taken by about 1000 students each year. Stat2.2x is the second of three five-week courses that make up Stat2x, the online equivalent of Berkeley's Stat 2.

The focus of Stat2.2x is on probability theory: exactly what is a random sample, and how does randomness work? If you buy 10 lottery tickets instead of 1, does your chance of winning go up by a factor of 10? What is the law of averages? How can polls make accurate predictions based on data from small fractions of the population? What should you expect to happen "just by chance"? These are some of the questions we will address in the course.

We will start with exact calculations of chances when the experiments are small enough that exact calculations are feasible and interesting. Then we will step back from all the details and try to identify features of large random samples that will help us approximate probabilities that are hard to compute exactly. We will study sums and averages of large random samples, discuss the factors that affect their accuracy, and use the normal approximation for their probability distributions.

Be warned: by the end of Stat2.2x you will not want to gamble. Ever. (Unless you're really good at counting cards, in which case you could try blackjack, but perhaps after taking all these edX courses you'll find other ways of earning money.)

The fundamental approach of the series was provided in the description of Stat2.1x and appears here again: There will be no mindless memorization of formulas and methods. Throughout the course, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.

FAQ

  • What is the format of the class?
    • Instruction will be consist of brief lectures and exercises to check comprehension. Grades (Pass or Not Pass) will be decided based on a combination of scores on short assignments, quizzes, and a final exam.
  • How much does it cost to take the course?
    • Nothing! The course is free.
  • Will the text of the lectures be available?
    • Yes. All of our lectures will have transcripts synced to the videos.
  • Do I need to watch the lectures live?
    • No. You can watch the lectures at your leisure.
  • Will certificates be awarded?
    • Yes. Online learners who achieve a passing grade in a course can earn a certificate of achievement. These certificates will indicate you have successfully completed the course, but will not include a specific grade. Certificates will be issued by edX under the name of BerkeleyX, designating the institution from which the course originated.
  • Can I contact the Instructor or Teaching Assistants?
    • Yes, but not directly. The discussion forums are the appropriate venue for questions about the course. The instructors will monitor the discussion forums and try to respond to the most important questions; in many cases response from other students and peers will be adequate and faster.
  • Do I need any other materials to take the course?
    • If you have any questions about edX generally, please see the edX FAQ.

4 votes
Saylor.org Free Closed [?] Computer Sciences Computer Science Math and Science Mathematics Statistics Statistics and Data Analysis

If you invest in financial markets, you may want to predict the price of a stock in six months from now on the basis of company performance measures and other economic factors. As a college student, you may be interested in knowing the dependence of the mean starting salary of a college graduate, based on your GPA. These are just some examples that highlight how statistics are used in our modern society. To figure out the desired information for each example, you need data to analyze. The purpose of this course is to introduce you to the subject of statistics as a science of data. There is data abound in this information age; how to extract useful knowledge and gain a sound understanding in complex data sets has been more of a challenge. In this course, we will focus on the fundamentals of statistics, which may be broadly described as the techniques to collect, clarify, summarize, organize, analyze, and interpret numerical information. This course will begin with a brief overview of the discipline of stat…

1 votes
Saylor.org Free Closed [?] Mathematics

This course will introduce you to a number of statistical tools and techniques that are routinely used by modern statisticians for a wide variety of applications. First, we will review basic knowledge and skills that you learned in MA121: Introduction to Statistics [1]. Units 2-5 will introduce you to new ways to design experiments and to test hypotheses, including multiple and nonlinear regression and nonparametric statistics. You will learn to apply these methods to building models to analyze complex, multivariate problems. You will also learn to write scripts to carry out these analyses in R, a powerful statistical programming language. The last unit is designed to give you a grand tour of several advanced topics in applied statistics. [1] http://www.saylor.org/courses/ma121/…

14 votes
Study.com Free Closed [?] Mathematics ACT Math College Mathematics EPA Math

Prepare for the College Mathematics CLEP Exam through Education Portal's brief video lessons on mathematics. This course covers topics ranging from real number systems to probability and statistics. You'll learn to use the midpoint and distance formulas, graph inequalities and multiply binomials. You'll also explore the properties of various shapes and learn to determine their area and perimeter. Our lessons are taught by professional educators with experience in mathematics. In addition to designing the videos in this course, these educators have developed written transcripts and self-assessment quizzes to round out your learning experience.

15 votes
Study.com Free Closed [?] Mathematics EPA Math Precalculus Precalculus Algebra

Prepare for the College Mathematics CLEP Exam through Education Portal's brief video lessons on mathematics. This course covers topics ranging from real number systems to probability and statistics. You'll learn to use the midpoint and distance formulas, graph inequalities and multiply binomials. You'll also explore the properties of various shapes and learn to determine their area and perimeter. Our lessons are taught by professional educators with experience in mathematics. In addition to designing the videos in this course, these educators have developed written transcripts and self-assessment quizzes to round out your learning experience.

16 votes
Study.com Free Closed [?] Mathematics Calculus Calculus I EPA Math Math and Science

Prepare for the College Mathematics CLEP Exam through Education Portal's brief video lessons on mathematics. This course covers topics ranging from real number systems to probability and statistics. You'll learn to use the midpoint and distance formulas, graph inequalities and multiply binomials. You'll also explore the properties of various shapes and learn to determine their area and perimeter. Our lessons are taught by professional educators with experience in mathematics. In addition to designing the videos in this course, these educators have developed written transcripts and self-assessment quizzes to round out your learning experience.

Starts : 2015-07-13
99 votes
Coursera Free Closed [?] Computer Sciences English Biology & Life Sciences Health & Society Mathematics Statistics and Data Analysis

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

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