EdX

MathTrackX: Statistics (edX)

MathTrackX: Statistics (edX)

Understand fundamental concepts relating to statistical inference and how they can be applied to solve real world problems. This course will build on probability and random variable knowledge gained from previous courses in the MathTrackX XSeries with the study of statistical inference, one of the most important parts of statistics.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

This course is part six of the MathTrackX XSeries Program which has been designed to provide you with a solid foundation in mathematical fundamentals and how they can be applied in the real world.
Guided by experts from the School of Mathematics and the Maths Learning Centre at the University of Adelaide, this course will cover random sampling, sample means and proportions, confidence intervals for sample means and proportions and one-sample tests of proportions and means.
Join us as we provide opportunities to develop your skills and confidence in applying mathematics to solve real world problems.

What you'll learn

  • The concept of a random sample, sources of bias in samples, and procedures to ensure randomness
  • The concept of the sample proportion as a random variable
  • The approximate normality of the distribution of proportions for large samples
  • The concept of an interval estimates for a parameter associated with a random variable
  • How to define the approximate margin of error for proportions.
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Advanced Linear Algebra: Foundations to Frontiers (edX) EdX
University of Texas at Austin,UTAustinX

Advanced Linear Algebra: Foundations to Frontiers (edX)

Learn advanced linear algebra for computing. Linear algebra is one of the fundamental tools for computational and data scientists. In Advanced Linear Algebra: Foundations to Frontiers (ALAFF), you will build your knowledge, understanding, and skills in linear algebra, practical algorithms for matrix computations, and the analysis of the effects of floating-point arithmetic as performed by computers.

Self Paced
Self-Paced
Probability and Statistics IV: Confidence Intervals and Hypothesis Tests (edX) EdX
Georgia Institute of Technology,GTx

Probability and Statistics IV: Confidence Intervals and Hypothesis Tests (edX)

This course covers two important methodologies in statistics – confidence intervals and hypothesis testing. Confidence intervals allow us to make probabilistic statements such as: “We are 95% sure that Candidate Smith’s popularity is 52% +/- 3%.” Hypothesis testing allows us to pose hypotheses and test their validity in a statistically rigorous way. For instance, “Does a new drug result in a higher cure rate than the old drug”?

Self Paced
Self-Paced
Statistical Inference and Modeling for High-throughput Experiments (edX) EdX
HarvardX,Harvard University

Statistical Inference and Modeling for High-throughput Experiments (edX)

A focus on the techniques commonly used to perform statistical inference on high throughput data. In this course you’ll learn various statistics topics including multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. We then introduce statistical modeling and how it is applied to high-throughput data. In particular, we will discuss parametric distributions, including binomial, exponential, and gamma, and describe maximum likelihood estimation.

Self Paced
Self-Paced
BioStatistics (edX) EdX
DoaneX,Doane University

BioStatistics (edX)

This college-level, credit-eligible Biostatistics course will teach you the skills required for success in future analytical studies in biology. In this undergraduate-level biostatistics course, the learners will be introduced to the use of statistics and study designs in biology. Upon successful completion of this course, learners will be able to design experimental, quasi-experimental and observational studies that will meet regulatory guidelines; collect, analyze, and interpret data using appropriate statistical tools.

Self Paced
Self-Paced
Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD (edX) EdX
Georgia Institute of Technology,GTx

Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD (edX)

This course takes you through roughly five weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. In the first part of this course you will explore methods to compute an approximate solution to an inconsistent system of equations that have no solutions. Our overall approach is to center our algorithms on the concept of distance.

Self Paced
Self-Paced
MathTrackX: Differential Calculus (edX) EdX
University of Adelaide,AdelaideX

MathTrackX: Differential Calculus (edX)

Discover concepts and techniques relating to differentiation and how they can be applied to solve real world problems. This course will cover basic concepts and techniques relating to differentiation; a fundamental tool of calculus. Derivatives are key to the understanding of rates of change, that is the extent to which a function responds to changes in a dependent variable.

Self Paced
Self-Paced
MathTrackX: Integral Calculus (edX) EdX
University of Adelaide,AdelaideX

MathTrackX: Integral Calculus (edX)

Discover concepts and techniques relating to integration and how they can be applied to solve real world problems. This course is part four of the MathTrackX XSeries Program which has been designed to provide you with a solid foundation in mathematical fundamentals and how they can be applied in the real world.

Self Paced
Self-Paced
Maths Essentials (edX) EdX
Imperial College Business School,Imperial College London

Maths Essentials (edX)

Discover and acquire the fundamental maths skills that you will need to use while studying an MBA program, from algebra to differentiation and geometric series. Planning to study for an MBA but unsure of your basic maths skills? All MBA programs, and in business generally require some maths, particularly on quantitative subjects such as Accounting, Economics and Finance.

Self Paced
Self-Paced
Basics of Statistical Inference and Modelling Using R (edX) EdX
University of Canterbury,UCx

Basics of Statistical Inference and Modelling Using R (edX)

Learn why a statistical method works, how to implement it using R and when to apply it and where to look if the particular statistical method is not applicable in the specific situation. Basics of Statistical Inference and Modelling Using R is part one of the Statistical Analysis in R professional certificate.

Self Paced
Self-Paced
Probability and Statistics II: Random Variables – Great Expectations to Bell Curves (edX) EdX
Georgia Institute of Technology,GTx

Probability and Statistics II: Random Variables – Great Expectations to Bell Curves (edX)

This course discusses properties and applications of random variables. For instance, how many customers are likely to arrive in the next hour? What’s the probability that a lightbulb will last more than a year? When you’re done with this course, you’ll have enough firepower to undertake a wide variety of modeling and analysis problems; and you’ll be well-prepared for the upcoming Statistics courses.

Self Paced
Self-Paced
Public Sector Debt Statistics (edX) EdX
International Monetary Fund - IMF,IMFx

Public Sector Debt Statistics (edX)

The course examines coverage and accounting rules for public sector debt, valuation, classification, important methodological issues, and the sources and methods used for compiling the statistics. This course, presented by IMF Statistics Department, covers the fundamentals needed to compile and disseminate comprehensive public sector debt statistics (PSDS) that are useful for policy- and decision-makers, as well as other users.

Self Paced
Self-Paced