Exam 1

  1. Question

    For the 47 observations of the variable x in the data file boxhist.csv draw a histogram, a boxplot and a stripchart. Based on the graphics, answer the following questions or check the correct statements, respectively. (Comment: The tolerance for numeric answers is ±0.3, the true/false statements are either about correct or clearly wrong.)
    The distribution is unimodal: true / false
    The distribution is: symmetric / right-skewed / left-skewed
    The boxplot shows outliers: true / false
    A quarter of the observations is smaller than:
    A quarter of the observations is greater than:
    Half of the observations are greater than:


    Solution

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

    1. True. / False.
    2. False. / False. / True.
    3. True. / False.
    4. 2.54.
    5. 3.9.
    6. 3.72.