Probability and Statistics for Business and Data Science

Welcome to Probability and Statistics for Business and Data Science!

In this course, we cover what you need to know about probability and statistics to succeed in business and the data science field!

This hands-on course would cover the philosophy of statistics as well as how to apply it to real-world problems. Example challenges, in-class quizzes, and appraisal assessments are included in each segment.

We’ll begin by discussing the fundamentals of data, including how to examine it using measures of central propensity and dispersion, as well as how bivariate data sources can be related to one another.

We’ll then go on to probability, where we’ll hear about combinations and permutations, as well as conditional probability and how to use Bayes’ theorem.

After that, we’ll go over the most popular statistical distributions, giving you a firm basis on how to deal with regular, binomial, Poisson, and regular distributions.

First, we’ll discuss numbers, like hypothesis testing and the student’s T distribution, and how to adapt what we’ve experienced so far to real-world market situations.

We’ll wrap up the course with three parts on specialized subjects, including ANOVA (analysis of variance), regression analysis, and chi-squared analysis.

The sections are modular and organized by topic, so you can reference what you need and jump right in!

Our course provides HD video with concise illustrations and high-quality animations, as well as detailed case studies that demonstrate how to adapt what you’ve learned in the classroom to real-world situations.

We’ll cover everything you need to know about statistics and probability to clearly tackle real-world business and data science problems!

Including:

1. Measurements of Data
2. Mean, Median, and Mode
3. Variance and Standard Deviation
4. Co-variance and Correlation
5. Permutations and Combinations
6. Unions and Intersections
7. Conditional Probability
8. Bayes Theorem
9. Binomial Distribution
10. Poisson Distribution
11. Normal Distribution
12. Sampling
13. Central Limit Theorem
14. Hypothesis Testing
15. T-Distribution Testing
16. Regression Analysis
17. ANOVA
18. Chi-Squared
19. and much more!

 

So what are you waiting for? Enroll today and we’ll see you inside the course!