Introduction to Business Administration and Analytics (Internship guarantee program)

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About this course

With the current shifting paradigm of businesses globally, there’s a need to identify these changing trends and devise efficient solutions for better business productivity. Businesses right now require a robust strategy of growth that involves qualities like quick thinking, unique problem-solving approaches and multitasking.

This course is going to walk you through the national and international business environments to help you set foot in the creative and entrepreneurial directions of a business while being comprehensively familiar with the fundamentals of a business.

Assignments - Our training program consists of a variety of assignments that slowly test your learning and expose you to real-world problems.

Instructors - Handpicked by the best, our instructors have been deployed to assist and counsel every student whenever needed.

Learning methods - Live classes and recorded videos, everything crafted to match your preferences.

Certificates - Provided at the end of every training program, authorized by some of the best learning institutions.

What you’ll learn

  • Learn about products vs services, and the importance of B2B vs B2C

  • Learn the essentials of business economics and its implementation

  • Understand the importance of a solidified business model

  • Learn how to take your business online and solidify yourself as an eCommerce business

  • Understand the techniques of the right marketing

  • Learn about data mining techniques, warehousing, databases, visualization, collection of data, and a lot more.

About this class

What you’ll learn

• What is Business Analytics?

• Descriptive or Univariate Statistics

• Measures of Central Tendency

• Measures of Dispersion

• Measures of Location

• Measures of Asymmetry

• Line Plot

• Bivariate Correlation

• Scatterplots

• Significance Testing

• Confidence Intervals

• Assumptions of Correlation Analysis

• Partial Correlation

• Multivariate Correlation

• Correlation vs. Causation

• Regression Basics

• Regression Example

• Binary Logistic Regression

• How to download Rstudio ?

• Rstudio

• Rstudio - aggregate function and t-Test

• Linear Regression using R

• Binary Logistic Regression using R

• Data Import and Manipulation

• Descriptive Statistics

• Inferential Statistics

• Data Visualization

• Predictive Analytics

• Customization and Automation

• Data Mining

• Null and Alternative Hypotheses

• Type I and Type II Errors

• Test Statistics and P-values

• Statistical Significance and Confidence Intervals

• Power and Sample Size

• Simple Linear Regression

• Multiple Linear Regression

• Logistic Regression

• Polynomial Regression

• Stepwise Regression and Model Selection

• Understanding PCA

• Data Preprocessing

• Calculation of Principal Components

• Variance Explained and Scree Plot

• Interpreting Principal Components

• Latent Constructs and Indicators

• Model Specification

• Model Fit Assessment

• Model Modification

• Assessing Measurement Properties

• Independent Samples t-test

• Paired Samples t-test

• One-Sample t-test

• Assumptions of the t-test

• Effect Size and Power Analysis

• Series Analysis Using R - Part 1

• Time Series Analysis Using R - Part 2

• Chi-square Test of Independence

• Contingency Tables

• Goodness-of-Fit Chi-square Test

• Chi-square Test for Homogeneity

• Assumptions and Limitations

• One-Way ANOVA

• Two-Way ANOVA

• Factorial ANOVA

• Assumptions of ANOVA

• ANCOVA

• Repeated Measures ANOVA

• How to install Power Bl ?

• Power BI- Line Plot

• Power BI- Bar Plot

• Power Bl- Scatterplot and Waterfall Chart

• Power BI- Cards

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