Question

In: Statistics and Probability

Accounting and Machiavellianism. A study of Machiavellian traits in accountants was published in Behavioral Research in...

Accounting and Machiavellianism. A study of Machiavellian traits in accountants was published in Behavioral Research in Accounting (January 2008). Recall (from Exercise 1.6, p. 4) that Machiavellian describes negative character traits such as manipulation, cunning, duplicity, deception, and bad faith. A Machiavellian ("Mach") rating score was determined for each in a sample of accounting alumni of a large southwestern university. The accountants were then classified as having high, moderate, or low Mach rating scores. For one portion of the study, the researcher investigated the impact of both Mach score classification and gender on the average income of an accountant. For this experiment, identify each of the following:

(a) experimental unit

(b) response variable

(c) factors

(d) level of each factor

(e) treatments

Solutions

Expert Solution

Here we basically want to see the effect of machiavellianism and gender of an accountant on his/her income.

In statistical language we want to see the simultaneous effect of mach and gender of an accountant on his/her income and for that matter there exist a design called Factorial design.

Now,we will define some terminology based on the above description of the survey:

(a) EXPERIMENTAL UNIT-(the units on which we will perform our experiment)

i.e accounting alumni of southwest university

(b)RESPONSE VARIABLE- (dependent variable i.e on which we want observation)

i.e income of accountants

(c) FACTORS-( Independent variable i.e which affects the response variable)

i.e 1) mach

2) gender

(d) LEVEL OF EACH FACTOR- (factors can further may breach in some branches in terms of amount,quality, characteristic)

in this case- 1) mach: HIGH,MODERATE,LOW

2) gender: MALE , FEMALE

(e) TREATMENTS- treatment combinations like- 1)effect of high mach-male

2) high mach-female

3)low-male

4)moderate-female

and so on based on what factorial design you are using.


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