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# Resources

Find selected resources to help you with math, stats, and data software. You can find informative LinkedIn Learning modules, YouTube playlists and other online tools that provide helpful clarifications. Join a short-course or watch a short video on a single topic. These resources will help you prepare for your next class.

LinkedIn Learning is an online learning library available to current York University students, faculty, and staff, that offers thousands of high-quality instructional videos and non-credit courses.

## Math Resources

View various online resources designed to assist you in a wide variety of topics.

## Stats Resources

Check out our online resources designed to assist you with concepts from basic probabilities to deriving a mean.

## Excel & Software Resources

Learn about Excel, R, Stata. SAS and Python and how these various programs/language can help in Data Analysis and create a variety of programs.

## Search our Resources

### Advanced and Specialized Statistics with Stata (Intermediate)

Stata is agile, easy to use, and fast, with the ability to load and process up to 120,000 variables and over 20 billion observations. In this course, take a deeper dive into the popular statistics software.

### Data, Economic Modeling, and Forecasting with Stata

Working with data is an important part of many jobs, and in the future, it will be important for even more.

### Excel

Excel is a software program created by Microsoft that uses spreadsheets to organize numbers and data with formulas and functions. Excel analysis is ubiquitous around the world and used by businesses of all sizes. It helps companies accurately assess situations and make better business decisions.

### Excel 2021 Essential Training

Excel, the popular spreadsheet program from Microsoft, is an essential tool for many professional roles. Learn how to navigate Excel and how to create, open, and save a file; how to enter, format, autofill, and edit text, as well as how to copy and delete cell data, merge cells, and more.

### Excel Essential Training

Learn how to enter and organize data, perform calculations with simple functions, and format the appearance of rows, columns, cells, and data. Other lessons cover how to work with multiple worksheets, build charts and PivotTables, sort and filter data, use the printing capabilities of Excel, and more.

### Excel: Advanced Formulas and Functions (Intermediate)

Learn about hundreds of formulas and functions available in Excel. Note that this course is recorded in Excel for Office 365 but anyone using a recent version—including 2019, 2016, and 2013—will be able to follow along.

### Excel: Tips and Tricks (Intermediate)

Learn time-saving tricks for creating formulas rapidly, accelerating data entry, and navigating within worksheets efficiently. Plus, discover drag and drop techniques, formatting shortcuts, charting and PivotTable tips, and much more.

### Introduction to Stata

Stata is agile and easy to use, automate, and extend, helping you perform data manipulation, visualization, and modeling for extremely large data sets. Explore the practical application—and interpretation—of commonly used statistical techniques such as distributional analysis and regression on real-life data.

### Learning Excel: Data Analysis (Intermediate)

This course helps you unlock the power of your organization's data using the data analysis and visualization tools built into Excel.

### Learning Python

Python—the popular and highly readable object-oriented language—is both powerful and relatively easy to learn. This course provides an overview of the installation process, basic Python syntax, and an example of how to construct and run a simple Python program.

### Learning R

The lessons explains how to get started with R, including installing R, RStudio, and code packages that extend R’s power and understand how to leverage this tool to explore and analyze a wide variety of data.

### Machine Learning with Python: Foundations (Intermediate)

This course introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python.

### Python Data Structures and Algorithms (Intermediate)

This course, leveraging the Python programming language, explains concepts in a fun and accessible way.

### Python Essential Training

Python is one of the most used dynamic languages for many large organizations, including Google, Yahoo, and IBM. Learn day-to-day programming in Python, including data types, data structures, operators and statements, control flow, loops, functions, classes, exception handling, and file management.

### Python Object-Oriented Programming (Intermediate)

In this course, you can learn how to apply core OOP principles like inheritance and composition along with some Python-specific features like “magic” methods and data classes to build programs that are extensible and efficient.

### Python Quick Start

Get a fast-paced introduction to Python. In this course, you can learn what Python is and why it's become such a powerful and in-demand programming language.

### R Essential Training: Wrangling and Visualizing Data

This training series provides a thorough introduction to R, with detailed instruction for installing and navigating R and RStudio and hands-on examples, from exploratory graphics to neural networks.

### R for Data Science (Intermediate)

This training series provides a thorough introduction to R, with detailed instruction for working with R and RStudio and hands-on examples, from exploratory graphics to neural networks.

### R for Data Science: Lunchbreak Lessons (Intermediate)

Review language basics, discover methods to improve existing R code, explore new and interesting features, and learn about useful development tools and libraries that will make your time programming with R that much more productive.

### R for Excel Users

Data scientists who use Excel realize that R is emerging as the new standard for statistical wrangling (especially for larger data sets). This course serves as the perfect bridge for the many Excel-reliant data analysts and business users who need to update their data science skills by learning R.

### SAS Essential Training: 1 Descriptive Analysis

Learn how to import a dataset from SAS *.xpt format using the XPORT command; edit datasets to add new categorical and continuous variables; conduct chi-square tests, t-tests, and analyses of variance (ANOVAs); generate a descriptive analysis with either a categorical and a continuous dependent variable; and more.