HypothesisTesting
Independentvariable (IV)= Basic salary of a particular workforce of any firm. ConditionA=Increments in the overtime hours ConditionB =Increase in productivity levels.Dependentvariable (DV)= Income allowances
Howdo you know this DV is measured on a continuous scale?
Thedependent variable would continue to change as hours rolls by. It iscontinuous in the sense that the overtime hours are given in a rangeof intervals and can be in the form of fractions or decimals or anyother denominations that are not distinct and have whole valueintegers. It can be 1.67, 1.04. 0.98 hours or ½, ¼, ¾ofovertime hours and so forth (Ruxton& Neuhäuser, 2010).Therefore, in this hypothesis testing, the total DV, which is thetotal income on only the dynamic allowances, would have it in numberof overtime hours any given employee multiplied by its standard priceper overtime hour provided by
Total dependent variable salary = overtime hours * standard price per overtime hour.
Now,how would you word the null hypothesis for your sample study?
Thenull hypothesis is the part that disapproves what the researcher isundertaking, and it is usually on negatively stated (Haspelmath,2014).
H0– There are no overall increases in the productivity level of afirm if employees are allowed to work for overtime hours
Howwould you word the alternative hypothesis for your sample study?
Onthe other hand, the alternative hypothesis is the positive part whichmainly includes the research problem of the researcher (Zaslavsky,2012).
H1–There are noticeable increases in the overall productivity levels ofwhen the workforces of a particular company work in overtime hours.
Whatalpha level would you set to test your hypothesis? Why?
Ifat all the null hypothesis is true, the probability of undertakingwrongful decisions is termed as the significance level, α. A 0.05 0r5% would be the ideal alpha level for this hypothesis testing sincethe possibility of rejecting the null hypothesis is small. Usually,the smaller the area under study, the smaller the alpha and thus thepossibility of rejecting null will not be increased (Zaslavsky,2012).
References
Haspelmath,M. (2014). Descriptive hypothesis testing is distinct fromcomparative hypothesis testing: Commentary on Davis, Gillon, andMatthewson. Language,90(4),e250-e257. http://dx.doi.org/10.1353/lan.2014.0071
Ruxton,G. & Neuhäuser, M. (2012). When should we use one-tailedhypothesis testing?. MethodsIn Ecology And Evolution,1(2),114-117. http://dx.doi.org/10.1111/j.2041-210x.2010.00014.x
Zaslavsky,B. (2012). Bayesian in Two-Arm Trials withDichotomous Outcomes. Biometrics,69(1),157-163. http://dx.doi.org/10.1111/j.1541-0420.2012.01806.x