Match List - I with List - II.

List – I

List - II

A.

Q Methodology 

I.

Hartshorne and May (1929) 

B.

‘Guess Who’ 

II.

Bradley Efron

C.

Student's distribution 

III.

Stephenson (1953) 

D.

Bootstrap Method 

IV.

William Sealy Gosset 

Choose the correct answer from the options given below : 

  1. A - II, B - III, C - IV, D - I
  2. A - III, B - I, C - IV, D - II
  3. A - IV, B - III, C - II, D - I
  4. A - III, B - IV, C - I, D - II

Answer (Detailed Solution Below)

Option 2 : A - III, B - I, C - IV, D - II

Detailed Solution

Download Solution PDF

The correct answer is - A - III, B - I, C - IV, D - II

Key Points

  • Q Methodology
    • Developed by William Stephenson in 1953.
    • This method is used to study people's "subjectivity"—that is, their viewpoint.
  • 'Guess Who'
    • Associated with Hartshorne and May (1929).
    • It is a sociometric technique used to study children's social relationships and attitudes.
  • Student's distribution
    • Created by William Sealy Gosset, who published under the pseudonym "Student".
    • Used in small sample size statistics to estimate the mean of a normally distributed population.
  • Bootstrap Method
    • Introduced by Bradley Efron in 1979.
    • It is a resampling method that involves repeatedly drawing samples from a dataset to estimate the distribution of a statistic.

Additional Information

  • Q Methodology
    • Combines both qualitative and quantitative research techniques.
    • Participants sort statements according to their level of agreement, providing a basis for understanding their perspectives.
  • 'Guess Who'
    • Used to measure social traits such as leadership, popularity, and aggression among children.
    • Helps in identifying peer relationships and social structures within groups.
  • Student's t-distribution
    • Critical in small-sample hypothesis testing.
    • Provides a basis for t-tests, which are used to determine if there are significant differences between groups.
  • Bootstrap Method
    • Useful in estimating the sampling distribution of almost any statistic.
    • Does not rely on the assumption of normality, making it versatile for various types of data.

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