Resolved: is it was really free ! !!!

Hi D.M.Rezone Hossain Rabbi,

Thanks for reaching out.

Can you please be more specific? What plan did you subscribe to prior to completing the Business Intelligence (BI): Techniques lesson?

Looking forward to your answer.
Best,
Martin

why it is not free?

Hi Marwa!

We are happy to provide part of our content for free but in general, our paid content is a lot richer and complete. Please visit the following page from our site for more information. Thank you!
https://365datascience.com/pricing/

Kind regards,
Martin

Hi, can you please elaborate more on the differences between Cluster analysis, Factor analysis, and time-series analysis using examples? 

Hi Youssef!

Thanks for reaching out.

These are all subjects that we cover in detail (with examples) in other courses; here we are only making an introduction to the topics.

Nevertheless, in a nutshell, cluster analysis and factor analysis are two statistical techniques, often studied together. Cluster analysis is about grouping objects in a group (called a "cluster) in a way that they are more similar between each other with respect to objects from other groups. An example here is grouping customers of a company to identify their common traits such as common spending behaviour or product preferences. This could help the company allocate certain marketing strategies to a different demographic regions, for instance, to optimize profit.

Factor analysis is about revealing an underlying structure in a certain data. For example, if a researcher collects the scores of a certain amount of people who completed their survey, they could explain the scores (or some of the scores) by certain factors. For instance, they may combine the scores into larger groups labelled "responses of professional workers", "students' answers" etc.

Time-series analysis is a discipline that applies statistical knowledge/observation over a period of time. In other words, on a Cartesian plane, one of the axes (the horizontal one) is "time" (as indicated by days, months, years etc.). A brilliant example is stock-market data. One can plot the stock price of a company (on the vertical axis) against time (each trading day as marked on the horizontal axis).

Hope this helps.

Best,
Martin