Statistics For Data Science And Business Decisions

What you'll learn
Master the fundamentals of Statistics for making effective business decisions
Requirements
No
Description
The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is required to make correct and relevant interpretations of data. Lack of this knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics.Course Contents include:Basic Data DescriptorsCategories of descriptive dataMeasures of central tendencyMeasures of DispersionStandard deviation measure and Chebyshev's theoremDescriptive Measures of Association, Probability, and Statistical DistributionsMeasures of association, the covariance and correlation measuresCausation versus correlationProbability and random variablesDiscrete versus continuous dataIntroduction to statistical distributionsThe Normal DistributionWorking with Distributions, Normal, Binomial, PoissonApplications of the Normal distributionThe Binomial and Poisson distributionsSample versus population dataCentral Limit TheoremRegression AnalysisWelcome to this course.
Overview
Section 1: Introduction
Lecture 1 Course Overview
Section 2: Descriptive Statistics
Lecture 2 Introduction to Descriptive Statistics
Section 3: Descriptive Statistics: Measures of Central Tendency
Lecture 3 Mean, Median and Mode
Lecture 4 Mean vs Median
Section 4: Descriptive Statistics: Measures of Dispersion
Lecture 5 Measures of Dispersion - Range and IQR
Lecture 6 Box Plots
Lecture 7 Standard Deviation
Lecture 8 Chebyshev's Theorem
Section 5: Descriptive Statistics: Measures of Association
Lecture 9 Measures of Association
Lecture 10 Covariance
Lecture 11 Correlation
Section 6: Probability and Random Variables
Lecture 12 Probability
Lecture 13 Random Experiment and Random Variables
Lecture 14 Probability Distributions
Section 7: Normal Distribution
Lecture 15 Understanding Normal Distribution
Lecture 16 Visualizing effect of mean and standard deviation for Normal Distribution
Lecture 17 Notation and Standard Normal Distribution
Lecture 18 Using Normal Distribution in Excel and Python
Lecture 19 NORM.INV and norm.ppf functions
Section 8: Case Study: Business decision on choosing production process
Lecture 20 Question: Business Decision using Normal Distribution
Section 9: Sampling and Central Limit Theorem
Lecture 21 Why Sampling?
Lecture 22 Random Sampling
Lecture 23 Central Limit Theorem
Section 10: Discrete Probability Distributions
Lecture 24 Bernoulli Process
Lecture 25 Binomial Distribution
Lecture 26 Poisson Distribution
Lecture 27 Poisson Distribution - Examples
Section 11: Regression Analysis
Lecture 28 Regression - Introduction
Lecture 29 Regression - Building the Model
Lecture 30 Estimating model parameters - Python
Lecture 31 Estimating model parameters - Excel LINEST() (Optional)
Lecture 32 Interpreting estimated model
Lecture 33 Prediction on new data
Lecture 34 Errors, Residuals and R-square
Data scientists, Business analysts, statistics students
Homepage

https://www.udemy.com/course/statistics-for-business-decisions/