Introduction to Statistics

Description

This course introduces learners to the fundamental concepts of statistical thinking, enabling them to learn from data and communicate insights effectively. Learners gain foundational skills in exploratory data analysis, probability, statistical inference, hypothesis testing, and regression, preparing them for more advanced statistical studies and applications in machine learning.

Learning Outcomes

By the end of this course, learners will be able to:

• Perform exploratory data analysis to summarize and visualize data.

• Understand sampling methods and design of experiments.

• Apply probability concepts and sampling distributions, including the Central Limit Theorem.

• Conduct regression analysis and interpret results.

• Select and perform appropriate tests of significance in multiple contexts.

• Use resampling techniques and handle multiple comparisons.

Skills You’ll Gain

• Statistics

• Data Analysis

• Statistical Modeling

• Statistical Inference

• Probability

• Exploratory Data Analysis

• Statistical Hypothesis Testing

• Statistical Analysis

Tools and Methods

• Data visualization and exploratory analysis

• Probability and sampling frameworks

• Regression analysis and significance testing

• Statistical modeling approaches

Modules in the Course

Career Relevance

Provides foundational statistical skills essential for data analysis, research, and machine learning.
Prepares learners for roles in data science, analytics, research, and other data-driven fields.
Certificate from Stanford University can be added to LinkedIn and professional profiles.