MG 3117 Issues and Controversies in Accounting 8

MG 3117 Issues and Controversies in Accounting 8. Analysing data using descriptive statistics Seminar progress test Ø Close your books and files Ø You will need a blank sheet of paper and a pen Ø Don’t share your answers with anyone else! Ø 15 questions in 15 minutes © Jill Collis and Roger Hussey, 2009 Business Research 1

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. . . 3. 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 2

True or false 6. The alternative hypothesis is written as H 0. 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 3

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

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

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

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

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

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 9

True or false 6. The alternative hypothesis is written as H 0. 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 10

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

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

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

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

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