In-depth R Programming Using Coursera (with 1-on-1 expert help)

  • August 23, 2014 · 1:00 PM

Note: Our past experience is that 20% of the RSVP shows up in the weekend meetings. Considering that, unless we have about 50 RSVPs, we cannot have a face to face meeting. Please use the questions / answers / discussions below for now.  

Cousera offers the following classes towards obtaining highly valuable knowledge/skills in Data Science Specialization. It is sometimes hard to work on the exercises and homework without the help of an expert.  Receiving one-on-one help from an expert can improve the commitment of finishing the program with accelerated learning. With that in mind, we are experimenting with the following service.

An expert (MS or PhD in Statistics) will answer any question free that takes less than 10 minutes to solve. There are nominal fees for one-on-one interactive help.  Please use the following link to request for help, or just email [masked] or call[masked]-8864. 

You can get help for the following Data Science Specialization Classes:  (from )

The Data Scientist’s Toolbox

R Programming

Getting and Cleaning Data

Exploratory Data Analysis

Reproducible Research

Statistical Inference

Regression Models

Practical Machine Learning

Developing Data Products

Data Science Capstone

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  • A former member
    A former member

    Can we review survival analysis? I am interested in overall survival for a binary outcome using Cox Proportional Hazards (coxph) regression model or other Survival Analysis methods in R. Thank you!

    August 23

    • Subhankar R.

      Aditi, Are you trying to do any specific exercise from Coursera?

      August 23

  • sung jin c.

    Is this meetup still going today? I will definitely show up but just want to make things clear.

    August 23

    • Subhankar R.

      No face to face meetup this week. We may have to wait until after the labor day weekend to get more RSVPs. Until then, please ask your questions here, or use emails link above.

      August 23

  • Subhankar R.

    Greetings all,

    We need specific questions from specific courses to make this thing work. Please, submit your questions via above links/emails or here before the meetup. Regards,

    August 19

    • Subhankar R.

      @Drew Kelly Yes, it can be done. First plot the data.

      plot (height ~ age, data=test)

      Check how loop are there I.e. how many change in trend of data. If data increases first then suddenly get decreases after few points it again increases. So note down such changes. These changes will give the degree of polynomial. Number of changes in data trend = degree of polynomial.

      fit=lm (height ~ age + I (age^2), data = test)
      summary (fit)
      plot(height~age, data=test)
      lines (test $ age, fitted (fit))

      you can use this command also
      lines (spline (test $ age, fitted (fit)), lwd =2)

      August 21

    • Subhankar R.

      @Jim Doherty Can you email the data in .csv format? My email is [masked] You have mentioned 5 times elapsed stilling well but in data there are 6 depths.

      August 22

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