Recorded Skills Training: Quantitative Methods 3 [QM3]

On this page, you can find the recording of the Exam practice for Quantitative Methods 3. Feel free to ask questions in the comment section below, we will answer them 🙂

Recording

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16 thoughts on “Recorded Skills Training: Quantitative Methods 3 [QM3]”

  2. At 48:00 shouldn’t the Grade variable be identical? Why is the first one 5 and the second 1, did you ignore it for example purposes or are they (and can they) actually be different?

    My assumption was that it should’ve been 10 + 8 * 5 + (-2) * 5 * 1.

    1. Hi Walid,

      It was for example purposes! So the grade itself would be the same, however, the coefficient of grade and grade with a dummy (Interaction term) will most likely differ!

      I hope that helps!

  3. For the paired t-test, I thought that when you use it what you are testing has to be the same thing and asked at another time period to see if the mean was still the same.I do not know how I passed QM because I still do not get it. So should we not test on one of Q6 ? How come we can compare two different questions?

    1. Hi 🙂

      So you have your three main t-tests:

      One sample t-test tests the mean of a single group against a known mean –> COmpare SBE students to an average GPA as an example
      An Independent Samples t-test compares the means for two groups –> Compare the GPA of SBE and FPN students as an example
      A Paired sample t-test compares means from the same group at different times (say, one year apart) or two paired questions with a questionnaire for the same group

      I hope that helps, otherwise please let me know and I try to rephrase it!

    1. Hi 🙂

      If the value is between 2.5 and 1 percent, then it is for sure below the value of the 5 percent. As a result, we can reject at 5% but not at 1%.

      Hope that helps 🙂

  6. Hi Florian,
    concerning the equal variance assumption, <3 counts for any sample that I am checking? Meaning it would also have to be smaller than 3 if I would have a completely different case?
    thanks in advance

    1. Hi Johannes,

      its mostly found in quantitative tests (t-tests and Anova) but technically yes. In a pooled t-test, you also see it in the output via the levene’s test for equality of variances.

      I hope that answers the question, otherwise let me know!

      Best
      Florian

  8. Hi, for the question on slide 16, we want to compare 2 likert-scale variables, which by definition from Kerckhoffs are ordinal & therefore qualitative. He said that those likert scale variables are the only ones who could possibly “upgraded” to pseudo-interval data, and therefore would be quantitative then. In this case you just decided that the likert-scale variables are quantitative, but any tips on how to handle this in the exam, since it could be both, depending on how you interpret it?

    1. Generally you always try to treat the data in its highest form (here quantitative, since you can always downgrade but it’s not optimal). But only in the case of the likert is „upgrading“ possible. Does that make sense :)?

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