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