11. Match the following.
List-I (Terms)
List-II (Definitions)
a. Simple regression
1. Process of predicting one variable from another
b. Multiple regression
2. Single variable is used to predict another variable on the assumption of linear relationship between the given variables
c. Simple linear regression analysis
3. Involves two or more independent variables and one dependent variable
| List-I (Terms) | List-II (Definitions) |
| a. Simple regression | 1. Process of predicting one variable from another |
| b. Multiple regression | 2. Single variable is used to predict another variable on the assumption of linear relationship between the given variables |
| c. Simple linear regression analysis | 3. Involves two or more independent variables and one dependent variable |
12. By which of the following methods, the sampling error, in comparison to biased approach, can be reduced?
13. The significance of the difference between two means of the populations, when σ2 values are known and equal, is tested by
14. The . . . . . . . . is less sensitive to extreme scores than the . . . . . . . .
15. If a frequency distribution is positively skewed, the mean of the distribution is:
16. The joint probability is:
17. If a perpendicular on X-axis from the point of intersection of both 'less than' and 'more than' frequency curves is drawn, it gives the value of
18. Match the items of List-I with the items of List-Il and denote the option of correct matching.
List-I
List-II
a. Hypothesis of Sales Revenue Maximization
1. W. J. Baumol
b. Hypothesis of Maximization of Firm's Growth Rate
2. Robin Marris
c. Hypothesis of Maximization of Managerial Utility Function
3. O. E. Williamson
d. Hypothesis of Satisfying Behaviour
4. Cyert and March
| List-I | List-II |
| a. Hypothesis of Sales Revenue Maximization | 1. W. J. Baumol |
| b. Hypothesis of Maximization of Firm's Growth Rate | 2. Robin Marris |
| c. Hypothesis of Maximization of Managerial Utility Function | 3. O. E. Williamson |
| d. Hypothesis of Satisfying Behaviour | 4. Cyert and March |
19. Consider the following statements.
Statement I: The absolute value of the difference between an unbiased estimate and the corresponding population parameter is called sampling error.
Statement II: Multi-stage sampling is a restricted non-probability-based sampling technique.
Statement I: The absolute value of the difference between an unbiased estimate and the corresponding population parameter is called sampling error.
Statement II: Multi-stage sampling is a restricted non-probability-based sampling technique.
20. Which one is not the method of collecting primary data?
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- Business Statistics and Research Methods - Section 12