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SDS 302 Data Analysis for Health

  • School:
    *
  • Professor:
    {[ professorsList ]}
    Harvey, Gobluski, LindseySmith, SUSSMAN,HARVEYM, Christopher Golubski, Kristin Harvey, Lin Lizhen, SPARKS, GuyCole, kyongjoo hong, harvery, ROBBINS,JILL, ROBINSSTEPHEN, Robbins, STACY, Raley
  • Average Course Rating (from 31 Students)

    4.3/5
    Overall Rating Breakdown
    • 31 Advice
    • 5
      58%
    • 4
      29%
    • 3
      10%
    • 2
      3%
    • 1
      0%
  • Course Difficulty Rating

    • Easy 42%

    • Medium 52%

    • Hard 6%

  • Top Course Tags

    Great Intro to the Subject

    Many Small Assignments

    Go to Office Hours

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    • Profile picture
    Dec 13, 2017
    | Would highly recommend.

    Pretty easy, overall.

    Course Overview:

    This professor is so funny! The course is fairly easy.

    Course highlights:

    The course was easy. Two days of lecture and one lab day.

    Hours per week:

    6-8 hours

    Advice for students:

    Do not miss class or your lab time.

    • Fall 2017
    • Robbins
    • Yes
    • Math-heavy Great Intro to the Subject Many Small Assignments
    • Profile picture
    Dec 02, 2017
    | Would recommend.

    Pretty easy, overall.

    Course Overview:

    This course is quite easy and engaging

    Course highlights:

    Basic statistics with parallels to human health. I have already taken a stats class so it was like a reiteration of that class.

    Hours per week:

    3-5 hours

    Advice for students:

    The powerpoint and practice tests are your friend when exams are coming up

    • Fall 2017
    • Raley
    • Yes
    • Many Small Assignments Requires Presentations Final Paper
    • Profile picture
    Oct 07, 2017
    | Would recommend.

    Not too easy. Not too difficult.

    Course Overview:

    It was like the best parts of math and easier than calculus

    Course highlights:

    I learned how to record and analyze data. The best part was being able to carry out our own investigations into research topics we chose

    Hours per week:

    3-5 hours

    Advice for students:

    You should master how to use the program R, watch the videos, do the readings and go for office hours

    • Fall 2016
    • STACY
    • Yes
    • Great Intro to the Subject Always Do the Reading A Few Big Assignments

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