Scaffolding Technology, Educational Blog for Teachers and Learners

1. The standard error of estimate measures the ……………. of the observed values around the regression line

A. Variability

B. Spread

C. Both (a) and (b)

D. None of the above

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2. The larger the value of Standard Error, the ………….. the spread of data points around the regression line.

A. Greater

B. Lower

C. Either (a) or (b)

D. None of the above

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3. If Standard error is…………….., then all data points would lie exactly on the regression line.

A. Zero

B. One

C. Negative

D. None of the above

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4. Which of the following statement is true?

A. Correlation need not imply cause and effect relationship between the variables under study

B. But regression analysis clearly indicates the cause and effect relationship between the variables.

C. The variable corresponding to cause is taken as independent variable and the variable corresponding to effect is taken as dependent variable

D. All of the above

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5. bxy is the regression coefficient of the regression equation

A. Y on X

B. X on Y

C. Either (a) or (b)

D. None of the above

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6. Which is an absolute measure?

A. Correlation coefficient

B. Regression coefficient

C. Both (a) and (b)

D. Neither (a) nor (b)

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7. There may be spurious ……………… between two variables which is due to pure chance and has no practical relevance

A. Correlation

B. Regression

C. Both (a) and (b)

D. Neither (a) nor (b)

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8. Regression analysis studies …………… relationships between the variables.

A. Linear

B. Non-linear

C. Both (a) and (b)

D. Neither (a) nor (b)

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9. The regression coefficient and correlation coefficient of the two variables will be the same if their ………………………..are same

A. Arithmetic mean

B. Standard deviation

C. Geometric mean

D. Mean deviation

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10. …………………. analysis aims at establishing the functional relationship between the two variables under study, and then using this relationship to predict the value of the dependent variable for any given value of the independent variable.

A. Regression

B. Correlation

C. Both (a) and (b)

D. None of the above

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11. A set of any quantitative data collected and arranged on the basis of time

A. Time series

B. Ratio analysis

C. Series

D. None of the above

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12. Depending on the research objective, the unit of time may be

A. A decade

B. A year

C. A month

 D. Any of the above

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13. Which of the following statement is true?

A. Forecasting any event helps in the process of decision making.

B. Forecasting is possible if we are able to understand the past behaviour of that particular activity.

C. For understanding the past behaviour, a researcher needs not only the past data but also a detailed analysis of the same.

D. All of the above

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14. The analysis of time series is of great utility for

A. Researchers

B. Economists

C. Businessmen

D. All of the above

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15. A time series consists of statistical data which are ……………. over successive increments

A. Collected

B. Recorded

C. Both (a) and (b)

D. Neither (a) nor (b)

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16. Which of the following statement is false in relation to time series?

A. It is helpful to make comparisons between different time series

B. It consists of statistical data which are collected, recorded over successive increment

C. It does not help in planning future course of action

D. It helps in understanding past behaviour of the variables under study

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17. When quantitative data are arranged in the order of their occurrence, the resulting statistical series is called

A. Data analysis

B. Time series

C. Ratio analysis

D. None of the above

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18. What is the need of time series analysis?

A. For understanding the behaviour of the variables under study

B. For knowing the expected quantitative changes in the variable under study

C. For estimating the effect of various causes in quantitative terms

D. All of the above

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19. When ……………… data are arranged in the order of their occurrence, the resulting statistical series is called a time series

A. Qualitative

B. Quantitative

C. Both (a) and (b)

D. None of the above

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20. The analysis of time series is of great utility because

A. It helps in understanding past behaviour of the variables under study

B. It facilitates in forecasting the future behaviour with the help of the changes that have taken place in the past.

C. It is helpful to make comparisons between different time series and significant conclusions drawn therefrom

D. All of the above

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