Learn how to apply factor analysis.
- [Instructor] Moving in to factor analysis.…Factor analysis is a regression method you apply…to discover root causes or hidden factors that are…present in the data set but not observable.…For example, imagine you're a marketing data scientist,…and you must identify actionable customer segments…for use in strategic marketing planning.…You've got response data from a customer survey,…you can apply factor analyis as a simple way…to group respondents into meaningful customer segments…based on similarities in how respondents answered…a specific subset of survey questions.…
Factor analysis is a method you used to regress on features…in order to discover factors that you can use…as variables to represent the original data set.…These factors are actually synthetic representations…of your data set with the extra dimensionality…and information redundancy stripped out.…Factors are also called latent variables.…Latent variable are variables that are meaningful…but that are inferred and not directly observable.…There are several assumptions you should know about…
AuthorLillian Pierson, P.E.
- Getting started with Jupyter Notebooks
- Visualizing data: basic charts, time series, and statistical plots
- Preparing for analysis: treating missing values and data transformation
- Data analysis basics: arithmetic, summary statistics, and correlation analysis
- Outlier analysis: univariate, multivariate, and linear projection methods
- Introduction to machine learning
- Basic machine learning methods: linear and logistic regression, Naïve Bayes
- Reducing dataset dimensionality with PCA
- Clustering and classification: k-means, hierarchical, and k-NN
- Simulating a social network with NetworkX
- Creating Plot.ly charts
- Scraping the web with Beautiful Soup
Skill Level Beginner
1. Data Munging Basics
2. Data Visualization Basics
3. Basic Math and Statistics
4. Dimensionality Reduction
Explanatory factor analysis6m 39s
5. Outlier Analysis
6. Cluster Analysis
7. Network Analysis with NetworkX
8. Basic Algorithmic Learning
9. Web-based Data Visualizations with Plotly
10. Web Scraping with Beautiful Soup
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.