Introduction to Statistics
Offered By: Bioinformatics Institute via Stepik
Course Description
Overview
This course is designed to explain the fundamental of statistics. The course contains four weeks or four modules. The first module is devoted to the main concepts of statistics and data analysis. First of all we will introduce the concepts of sample, general population, descriptive statistics and normal distribution. At the end of the first module we will discuss the idea of statistical inference, one of the most important topics of our course. If you have just started to study statistics look more closely at the first week. All the lessons of the first module are extremely important to enable you to understand the rest of the course and more complicated concepts and methods of statistics. Each module contains lessons with short theoretical video lectures mixed with practical problems.
Syllabus
Introduction to Hypothesis Testing
1.1 Introduction
1.2 Sample and Population
1.3 Types of Variables in Statistics
1.4 Descriptive Statistics (Central Tendency Measures)
1.5 Descriptive Statistics (Variance and Quantiles)
1.6 Normal Distribution
1.7 Central Limit Theorem
1.8 Confidence Intervals
1.9 Statistical Hypothesis Testing
Categorical Data Analysis
2.1 Introduction. Categorical Data in Statistics
2.2 Chi-Squared Distance
2.3 Pearson Distribution, Degrees of Freedom and Chi-Squared Test
2.4 Contingency Table Analysis
2.5 P-value Calculation
2.6 Fisher's Exact Test
T- test and Analysis of Variance
3.1 Student's t-Distribution
3.2 Student's t-Test
3.3 One-Way ANOVA
3.4 Post Hoc Analysis
Correlation and Linear Regression
4.1 Definitions of Covariance and Correlation
4.2 Simple Linear Regression. Least Squares. Residuals.
4.3 Predictions from Linear Regression. Assumptions.
4.4 Multiple Linear Regression
Taught by
Anatoliy Karpov and Polina Drozdova
Tags
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