Quantitative Methods For Economic Analysis 1 Set 4
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This set of Quantitative Methods for Economic Analysis 1 Multiple Choice Questions & Answers (MCQs) focuses on Quantitative Methods For Economic Analysis 1 Set 4
Q1 | The type of sampling in which each member of the population selected for the sample isreturned to the population before the next member is selected is called _________
- sampling without replacement
- sampling with replacement
- simple random sampling
- systematic sampling
Q2 | Which of the following is not a type of nonrandom sampling
- cluster sampling
- convenience sampling
- quota sampling
- purposive sampling
Q3 | ___________ is a set of elements taken from a larger population according to certainrules
- sample
- population
- statistic
- element
Q4 | Questionnaires can address events and characteristics taking place ______
- in the past (retrospective questions)
- in the present (current time questions)
- in the future (prospective questions)
- all of the above
Q5 | Which of the following terms best describes data that were originally collected at anearlier time by a different person for a different purpose
- primary data
- secondary data
- experimental data
- field notes
Q6 | Which of the following is true concerning observation method of data collection
- it takes less time than self-report approaches
- it costs less money than self-report approaches
- it is often not possible to determine exactly why the people behave as they do
- all of the above
Q7 | Correlation refers to
- the causal relationship between two variables
- the association between two variables
- the proportion of variance that two variables share
- a statistical method that can only be used with a correlational research design
Q8 | If two variables are highly correlated, what do you know
- that they always go together
- that high values on one variable lead to high values on the other variable
- that there are no other variables responsible for the relationship
- that changes in one variable are accompanied by predictable changes in the other
Q9 | A researcher finds a correlation of 0.40 between personal income and the number ofyears of college completed. Based upon this finding he can conclude that
- a person who attended four years of college will have an annual income of rs. 40,000
- more years of education causes higher income
- personal income is a positively skewed variable
- more years of education are associated with higher income
Q10 | Which of the following would not allow you to calculate a correlation?
- a negative relationship between x and y
- a positive relationship between x and y
- a curvilinear relationship between x and y
- a linear relationship between x and y
Q11 | Correlation relates the relative position of a score in one distribution to
- the relative position of a score in another distribution
- the mean of the z-scores from another distribution
- the total variance of all scores in both distributions
- the standard deviation of the z-scores for both distributions
Q12 | If a positive correlation exists between height and weight, a person with above averageheight is expected to have above average weight
- true
- false
- insufficient information to draw a conclusion
- all of the above
Q13 | Regression analysis:
- measures the demand for a good
- measures growth
- establishes cause and effect
- establishes a relationship between two variables
Q14 | In the equation of a straight line, Y = mX + c the term, m is the:
- independent variable
- intercept
- dependent variable
- slope
Q15 | In the equation of a straight line, Y = mX + c , if c is equal to zero then:
- the line of best fit passes through the origin
- the line of best fit cuts the x axis to the right of the y axis
- does not cross the x axis
- the line of best fit cuts the x axis to the left of the y axis
Q16 | In the equation of a straight line, Y = mX + c , if m is equal to −2 then:
- there is a positive relationship between the two variables
- there is no relationship between the two variables
- there is a negative relationship between the two variables
- the relationship between the two variables is perfect
Q17 | In the equation of a straight line, Y = mX + c , if m is equal to zero then when:
- x increases y decreases
- y increases x increases
- x increases y increases
- x increases y remains constant
Q18 | If the Pearson correlation co-efficient R is equal to 1 then:
- there is a perfect positive relationship between the two variables
- there is a positive relationship between the two variables
- there is no relationship between the two variables
- there is a negative relationship between the two variables
Q19 | The mathematical notation R2is for:
- the co-efficient of determination
- the co-efficient of variation
- spearman’s co-efficient of rank correlation
- pearson’s co-efficient of correlation
Q20 | If the slope of the regression line is calculated to be 2.5 and the intercept 16 then thevalue of Y when X is 4 is:
- 16
- 66.5
- 2.5
- 26
Q21 | If Spearman’s co-efficient of rank correlation is equal to one, then:
- all the ‘total variation’ is ‘explained’ by the regression line
- the rankings of the two variables partially agree
- the rankings of the two variables is totally different
- the rankings of the two variables totally agree
Q22 | The correlation coefficient is used to determine:
- a specific value of the y-variable given a specific value of the x-variable
- a specific value of the x-variable given a specific value of the y-variable
- the strength of the relationship between the x and y variables
- none of these
Q23 | If there is a very strong correlation between two variables then the correlationcoefficient must be
- any value larger than 1
- much smaller than 0, if the correlation is negative
- much larger than 0, regardless of whether the correlation is negative or positive
- none of these alternatives is correct
Q24 | In regression, the equation that describes how the response variable (y) is related to theexplanatory variable (x) is:
- the correlation model
- the regression model
- used to compute the correlation coefficient
- none of these alternatives is correct
Q25 | Regression modelling is a statistical framework for developing a mathematical equationthat describes how
- one explanatory and one or more response variables are related
- several explanatory and several response variables response are related
- one response and one or more explanatory variables are related
- all of these are correct