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Question

A student appearing for an exam is declared to have failed the exam if his/her score is less than half the median score. This implies

The correct answer is
it is possible that no one fails.

The condition for failing the exam is defined as having a score less than half the median score.

Mathematically, a student fails if:
Score < Median Score / 2

Analyzing the Failing Condition Implications

Let's analyze the options based on this condition:

  • Option 1 & 2 state specific fractions ($1/4$) of students or scores relative to the maximum score. The failing condition, however, depends solely on the median score, not a fixed fraction of students or the maximum score. Therefore, these statements are not necessarily true.
  • Option 3 relates passing to scoring more than half the maximum score. This is incorrect because the passing/failing threshold is determined by the median, not the maximum score. A student could score above half the maximum but still fail if the median is very high.
  • Option 4 states that it is possible that no one fails. This is plausible. Consider a scenario where all students achieve the same score, say $S$. In this case, the median score is also $S$. The failing condition becomes Score < $S$ / 2. Since every student scored $S$, and $S \ge S/2$ (for non-negative scores), no student's score is less than half the median. Thus, no one fails.

Conclusion on Possibility of No Failures

Since we can construct a scenario (e.g., all students scoring the same) where the condition Score < Median Score / 2 is not met by any student, it is indeed possible that no one fails the exam.

Therefore, the correct implication is that it is possible that no one fails.

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Important Questions from Elementary Statistics (Notes)

  1. Let $X_1, X_2, X_3$ be a random sample of size 3 from an absolutely continuous distribution that is symmetric about 0. For $i=1,2,3$, let $R_i$ denote the rank of $|X_i|$ among $|X_1|, |X_2|$ and $|X_3|$. 

    If $T^+ = \sum_{i=1, X_i>0}^3 R_i$

     is the Willcoxon signed-rank statistic, then which of the following statements are true?, 

  2. What is the geometric mean of 2, 4 and 8?
  3. In correlation analysis, the two variables

    1. Are treated with distinction.
    2. Are treated differently based on individual characteristics.
    3. Are treated symmetrically.
    4. Are regressed.
  4. In statistics, standard error measures the

    1. Specification error of the model.
    2. Autocorrelation in the regression model.
    3. Correlation between dependent and independent variables.
    4. Precision of an estimate.
  5. Linear regression model is

    1. linear in explanatory variables but may not be linear in parameters
    2. non-linear in parameters and must be linear in variables
    3. linear in parameters and must be linear in variables
    4. linear in parameters and may be linear in variables
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