Statistics - Foundational And Intermediate Level

Foundational and Intermediate Level

What you'll learn

Research Interpretations and Conclusions

Meta-Analysis of Literature Reviews

Clinical Trial Design

Designing Surveys

Epidemiological Studies

Statistical Modeling

Requirements

Basic Maths knowledge

Description

Statistics is the branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It is essential for understanding patterns, making predictions, and making informed decisions across various domains like business, healthcare, and research.This course introduces and explains key components of the following statistics topics:Descriptive Statistics:Measures of central tendency: mean, median, modeMeasures of dispersion: variance, standard deviation, range, interquartile rangeSkewness and kurtosisProbability:Basic concepts: sample space, events, probability axiomsConditional probability and independenceBayes' theoremProbability distributions: discrete and continuousInferential Statistics:Sampling methods: random sampling, stratified sampling, cluster sampling, etc.Estimation: point estimation, interval estimationHypothesis testing: null and alternative hypotheses, p-values, type I and type II errorsConfidence intervalsProbability Distributions:Probability Mass Function (PMF)Probability Density Function (PDF)This course provides numerous examples and practice testsImportance of StatisticsDecision-Making: Used in business to predict trends, in medicine for clinical trials, and in government for policy decisions.Data Analysis: Provides tools to analyze large datasets effectively.Predictive Modeling: Helps predict future outcomes based on historical data.Quality Control: Ensures products meet specified standards.Statistics is the cornerstone of data-driven decision-making. By understanding measures of central tendency, dispersion, probability distributions, mathematical expectation, and inferential methods, we gain valuable insights into datasets and use them to solve real-world problems. This combination of theory and application makes statistics indispensable in today’s data-rich world.

Overview

Section 1: Introduction

Lecture 1 Introduction to Statistics

Section 2: Arithmetic Mean

Lecture 2 Arithmetic mean for individual, discrete and Continuous Series

Section 3: Measures of central tendency 2

Lecture 3 Mode, Median, Geometric Mean, Harmonic Mean, Weighted and combined Mean

Section 4: Measures of dispersion

Lecture 4 Measures of dispersion

Section 5: Probability

Lecture 5 Probability

Section 6: Probability Distribution

Lecture 6 Probability Distribution

Section 7: Mathematical Expectation and Moments

Lecture 7 Mathematical Expectation and Moments

Section 8: Inferential Statistics

Lecture 8 Inferential Statistics

Statisticians are employed in various fields ranging from advertising, medicine, sports, social workers, corporate companies, banks, politicians to scientific research. A course in statistics includes analysis, probability theory, learning statistical methods and database management systems.