1. MG3117 Issues and Controversies in Accounting
Understanding research
MG3117 Issues and Controversies in Accounting
8. Analysing data using descriptive 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 is the number of observations for a particular data value in a variable. 2. A descriptive statistic that summarizes a frequency as a proportion of 100 is called a A is a display that summarizes the frequencies for all the data values in a particular variable. 4. The analysis of two variables together is known as analysis. 5. A variable that is coded 1 if the characteristic is present and 0 otherwise is known as a variable.
© Jill Collis and Roger Hussey, 2009
Business Research

3. True or false
6. The alternative hypothesis is written as H0. 7. A pie chart is suitable for summarising frequency distributions from nominal or ordinal variables. 8. A histogram is suitable for summarising frequency distributions from ratio or interval variables. 9. The mean should only be calculated for nominal or ordinal variables. 10. The standard deviation should only be calculated for ratio or interval variables.
© Jill Collis and Roger Hussey, 2009
Business Research

4. Multiple choice 11. A number that describes a sample is called: a code
a data value
a parameter
a statistic
© Jill Collis and Roger Hussey, 2009
Business Research

5. Multiple choice 12. A number that describes a population is called:
a code
a data value
a parameter
a statistic
© Jill Collis and Roger Hussey, 2009
Business Research

6. Multiple choice
13. The mid-value of a set of data arranged in size order is:
the mean
the median
the mode
the rank
© Jill Collis and Roger Hussey, 2009
Business Research

7. Multiple choice
14. The measure used to describe the asymmetry of a frequency distribution is:
deviation
kurtosis
normality
skewness
© Jill Collis and Roger Hussey, 2009
Business Research

8. Multiple choice 15. A Type I error is where:
the null hypothesis is true, but the test leads to its rejection
the null hypothesis is true and the test leads to its acceptance
the alternative hypothesis is true, but the test leads to the acceptance of the null hypothesis
the significance level is set too high
© Jill Collis and Roger Hussey, 2009
Business Research

9. Fill the gaps
1. A frequency is the number of observations for a particular data value in a variable. 2. A descriptive statistic that summarizes a frequency as a proportion of 100 is called a percentage. 3. A frequency distribution is a display that summarizes the frequencies for all the data values in a particular variable. 4. The analysis of two variables together is known as bivariate analysis. 5. A variable that is coded 1 if the characteristic is present and 0 otherwise is known as a dummy variable.
© Jill Collis and Roger Hussey, 2009
Business Research

10. True or false
6. The alternative hypothesis is written as H0. False 7. A pie chart is suitable for summarising frequency distributions from nominal or ordinal variables. True 8. A histogram is suitable for summarising frequency distributions from ratio or interval variables. True 9. The mean should only be calculated for nominal or ordinal variables. False 10. The standard deviation should only be calculated for ratio or interval variables. True
© Jill Collis and Roger Hussey, 2009
Business Research

11. Multiple choice 11. A number that describes a sample is called: a code
a data value
a parameter
a statistic
© Jill Collis and Roger Hussey, 2009
Business Research

12. Multiple choice 12. A number that describes a population is called:
a code
a data value
a parameter
a statistic
© Jill Collis and Roger Hussey, 2009
Business Research

13. Multiple choice
13. The mid-value of a set of data arranged in size order is:
the mean
the median
the mode
the rank
© Jill Collis and Roger Hussey, 2009
Business Research

14. Multiple choice
14. The measure used to describe the asymmetry of a frequency distribution is:
deviation
kurtosis
normality
skewness
© Jill Collis and Roger Hussey, 2009
Business Research

15. Multiple choice 15. A Type I error is where:
the null hypothesis is true, but the test leads to its rejection
the null hypothesis is true and the test leads to its acceptance
the alternative hypothesis is true, but the test leads to the acceptance of the null hypothesis
the significance level is set too high
© Jill Collis and Roger Hussey, 2009
Business Research