Statistical Inference

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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 [...]

Statistics and R (edX)

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences. We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a [...]

Introductory Statistics : Basic Ideas and Instruments for Statistical Inference (edX)

This course utilizes real-life applications of Statistics in an exploration of the Statistical Inferenceprocess. Statistical Inference is the process by which data is used to draw a conclusionoruncover ascientific truthabout a population from asample. This course aims to familiarize the student with several ideas and instruments for statistical inference. [...]

Introductory Statistics : Sample Survey and Instruments for Statistical Inference (edX)

The purpose of this course is to introduce basic concepts of sample surveys and to teach statistical inference process using real-life examples. In this course, you will learn about sample surveys with the concepts of samples and populations. In addition, we will discuss possible problems(bias) of the surveys based [...]

Statistical Inference for Estimation in Data Science (Coursera)

This course introduces statistical inference, sampling distributions, and confidence intervals. Students will learn how to define and construct good estimators, method of moments estimation, maximum likelihood estimation, and methods of constructing confidence intervals that will extend to more general settings. [...]

Data Modeling and Regression Analysis in Business (Coursera)

The course will begin with what is familiar to many business managers and those who have taken the first two courses in this specialization. The first set of tools will explore data description, statistical inference, and regression. We will extend these concepts to other statistical methods used for prediction [...]

Inferential Statistical Analysis with Python (Coursera)

In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. We will learn how to construct confidence intervals. We will [...]

Data Science in Real Life (Coursera)

Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The [...]

Statistical Inference (Coursera)

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and [...]

Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera)

This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, [...]