Biznes statistikası

Kamal Mirzəyev Təlimçi : Kamal Mirzəyev

Təlimin başlama tarixi: 00-00-0000



36 saat



Proqramın qısa məzmunu

Module 1: Introduction to Statistics

  • Introduction to Business Statistics
  • Different Types of date for business Statistics
  • Basic Statistical Concepts

Module 2: R Fundamentals for Analyzing and Interpret Row Data

  • Install R and R Studio and engage in a basic R session 
  • Be able to read in data and write out data files from various sources 
  • Create and execute their own user-defined functions in an R session 
  • Understand the characteristics of different data types and structures in R
  • Sort, select, filter, subset, and manipulate tables of data in R 
  • Understand how to use the apply() family of functions to execute various actions against different R data structures
  • Know how to use reshaping and recoding "short cuts" for changing data types and for rearranging data structures.
  • Basic visualization and share reports in R

Module 3: Applying Descriptive and Diagnostic Statistics in Real Business

  • Visualizing and Exploring Data (EDA) 
    • Chart absolute frequency, relative frequency, cumulative absolute frequency and cumulative relative frequency histograms, etc.
  • Descriptive Statistical Measures for Business
    • Estimate sample skewness, sample kurtosis frequency distribution shape measures and samples correlation, samples covariance association measures, etc.
  • Probability Distributions 
    • Evaluate probability distribution goodness of fit through quantile-quantile plots and normality test, etc.
  • Sampling and Estimation for Decision Making
    • Estimate population mean and population proportion confidence intervals assuming known or unknown population variance, etc.
  • Statistical Inference for Data Mining
    • Capstone project from Real Business Environment

Module 4: Statistical Decision Making under Uncertainty for Business

  • Trendlines and Regression Analysis with Data
    • with real business cases
  • Forecasting Techniques for Business
    • with real business cases
  • Monte Carlo Simulation and Risk Analysis Process
    • with real business cases
  • Statistical Decision Analysis for Driving Consumer Experience.
    • with real business cases
  • Statistical Clustering Analysis for Customer Behavioral Segmentation 
    • with real business cases