
About Course
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:
- Measurements of Data
- Mean, Median, and Mode
- Variance and Standard Deviation
- Co-variance and Correlation
- Permutations and Combinations
- Unions and Intersections
- Conditional Probability
- Bayes Theorem
- Binomial Distribution
- Poisson Distribution
- Normal Distribution
- Sampling
- Central Limit Theorem
- Hypothesis Testing
- T-Distribution Testing
- Regression Analysis
- ANOVA
- Chi-Squared
- and much more!
So what are you waiting for? Enroll today and we’ll see you inside the course!
Who this Probability and Statistics course is for:
- Someone interested in learning how to apply probability and statistics to business or data science
Course Content
Probability and Statistics for Business and Data Science
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Chi Squared Analysis Exercise Example
00:00 -
Students T Distribution
00:00 -
Type 1 and Type 2 Errors
00:00 -
Hypothesis Testing Example Exercise 2
00:00 -
Hypothesis Testing Example Exercise 1
00:00 -
Standard Error
00:00 -
Central Limit Theorem
00:00 -
Sampling
00:00 -
What is Statistics
00:00 -
Students T Distribution Example Exercise
00:00 -
Introduction to ANOVA
00:00 -
ANOVA Analysis of Variance
00:00 -
Chi Square Analysis
00:00 -
Multiple Regression
00:00 -
Regression Example
00:00 -
Linear Regression
00:00 -
Two Way ANOVA with Replication
00:00 -
Two Way ANOVA Example Exercise
00:00 -
Two Way ANOVA Overview
00:00 -
F Distribution
00:00 -
Normal Distribution Formulas and Z Scores
00:00 -
Normal Distribution
00:00 -
What is Probability
00:00 -
Pearson Correlation Coefficient
00:00 -
Bi variate Data and Covariance
00:00 -
Measurements Quartiles
00:00 -
Measurements of Dispersion
00:00 -
Measurements of Central Tendency
00:00 -
Measuring Data
00:00 -
What is Data
00:00 -
Permutations
00:00 -
Combinations
00:00 -
Intersections Unions and Complements
00:00 -
Poisson Distribution
00:00 -
Binomial Distribution
00:00 -
Uniform Distribution
00:00 -
Introduction to Distributions
00:00 -
Bayes Theorem
00:00 -
Addition and Multiplication Rules
00:00 -
Conditional Probability
00:00 -
Independent and Dependent Events
00:00 -
001 Course Overview Lecture
00:00