LibGuides: TIM-8501 V4: Week 2 Resources

Week 2 Resources

Reminder: Please complete the O’Reilly login steps (See the Accessing O’Reilly link in the Week 1 Resources area) where you get an email that will allow your browser to keep your password, solving future access limitations.

Statistics for Data Science and Business Analysis
365 Careers. (2018). Statistics for data science and business analysis. Packt Publishing.
Watch Chapter 4: Measures of Central Tendency, Asymmetry, and Variability.
This video describes the different measures of central tendency, measuring skewness, calculating variance, standard deviation, and the correlation coefficient.
Watch Chapter 5: Practical Example: Descriptive Statistics.
This video details a practical example of descriptive statistics.
RapidMiner Studio
RapidMiner, Inc. (2021). RapidMiner educational license program. RapidMiner, Inc.
This web page provides access to registration and downloads for a 1-year renewable educational license for RapidMiner Studio. Students must apply using their NU email address and follow instructions sent to them via email.
R Programming for Statistics and Data Science
365 Careers. (2018). R Programming for statistics and data science. Packt Publishing.
Watch Chapter 1: Introduction and Getting Started.
This video demonstrates how to download and install R and R Studio, how to install packages, how to maintain those packages use the library, and navigate the graphical user interface.
Python Data Analysis
Fandango, A., Idris, I., & Navlani. A. (2021). Python data analysis (3rd ed.). Packt Publishing.
Read all sections between Statistics and Summary
These sections describe different statistic principles, including central tendency, dispersion, skewness, kurtosis, and more.
Anaconda Individual Edition
Anaconda, Inc. (2021). Anaconda | Individual Edition.
This open-source individual edition is a valuable resource for the data scientist's toolkit and includes Python and R.

Data Repository

Rooftop Drinking Water Task Inspection Results
Instructions:

Review the dataset information and the data dictionary provided.
Click the Export button and select CSV.
School Nutrition Programs – Meal Reimbursement Information
Instructions:

Review the dataset information and the data dictionary provided.
Click the Export button and select CSV.