1. MG3117 Issues and Controversies in Accounting
Understanding research
MG3117 Issues and Controversies in Accounting
9. Analysing data using inferential statistics
Seminar progress test
Close your books and files
You will need a blank sheet of paper and a pen
Don’t share your answers with anyone else!
15 questions in 15 minutes
© Jill Collis and Roger Hussey, 2009
Business Research
© Jill Collis and Roger Hussey, 2009

2. Fill the gaps
1. A random sample is a representative subset drawn from the A number that describes a is called a statistic 3. A number that describes a is called a parameter. 4. Parametric tests are underpinned by four assumptions about the characteristics of the distribution of the The analysis of more than two variables together is known as analysis.
© Jill Collis and Roger Hussey, 2009
Business Research

3. True or false
6. A normality test compares the distribution of the research data with that of a theoretical sample. 7. A test of difference can only be carried out with parametric data. 8. A chi-square test can only be carried out between nominal variables. 9. Regression analysis can only be carried out if the correlation between dependent and the independent variables is linear. 10. Regression analysis can only be carried out if there is no perfect multicollinearity between the independent variables.
© Jill Collis and Roger Hussey, 2009
Business Research

4. Multiple choice 11. A t test is a parametric test of difference for:
ratio or interval variables
ordinal or nominal variables
dependent or independent variables
dependent or independent samples
© Jill Collis and Roger Hussey, 2009
Business Research

5. Multiple choice 12. A Mann-Whitney test is a non-parametric test of:
association
difference
multicollinearity
normality
© Jill Collis and Roger Hussey, 2009
Business Research

6. Multiple choice 13. A chi-square test is a non-parametric test of:
association
difference
multicollinearity
normality
© Jill Collis and Roger Hussey, 2009
Business Research

7. Multiple choice
14. Measures of correlation are needed to evaluate potential problems with:
kurtosis
multicollinearity
normality
skewness
© Jill Collis and Roger Hussey, 2009
Business Research

8. Multiple choice 15. Logistic regression is used where:
the dependent variable is a dummy variable
the independent variable is a dummy variable
there is only one predictor variable
there is more than one predictor variable
© Jill Collis and Roger Hussey, 2009
Business Research

9. Fill the gaps
1. A random sample is a representative subset drawn from the population. 2. A number that describes a sample is called a statistic 3. A number that describes a population is called a parameter. 4. Parametric tests are underpinned by four assumptions about the characteristics of the distribution of the population. 5. The analysis of more than two variables together is known as multivariate analysis.
© Jill Collis and Roger Hussey, 2009
Business Research

10. True or false
6. A normality test compares the distribution of the research data with that of a theoretical sample. False 7. A test of difference can only be carried out with parametric data. False 8. A chi-square test can only be carried out between nominal variables. True 9. Regression analysis can only be carried out if the correlation between dependent and the independent variables is linear. True 10. Regression analysis can only be carried out if there is no perfect multicollinearity between the independent variables. True
© Jill Collis and Roger Hussey, 2009
Business Research

11. Multiple choice 11. A t test is a parametric test of difference for:
ratio or interval variables
ordinal or nominal variables
dependent or independent variables
dependent or independent samples
© Jill Collis and Roger Hussey, 2009
Business Research

12. Multiple choice 12. A Mann-Whitney test is a non-parametric test of:
association
difference
multicollinearity
normality
© Jill Collis and Roger Hussey, 2009
Business Research

13. Multiple choice 13. A chi-square test is a non-parametric test of:
association
difference
multicollinearity
normality
© Jill Collis and Roger Hussey, 2009
Business Research

14. Multiple choice
14. Measures of correlation are needed to evaluate potential problems with:
kurtosis
multicollinearity
normality
skewness
© Jill Collis and Roger Hussey, 2009
Business Research

15. Multiple choice 15. Logistic regression is used where:
the dependent variable is a dummy variable
the independent variable is a dummy variable
there is only one predictor variable
there is more than one predictor variable
© Jill Collis and Roger Hussey, 2009
Business Research