Factorial Design
Factorial tests involve four treatment combinations in total. It allows the researcher to investigate the effect of each element in the study on the response variable and their interactions between these elements. This is similar to the information presented in table 2. In table 2, the treatments involve weight status composing individual factors, for instance, lean 1, lean 2, obese 1, and obese 2 totalling to four combinations. The elements allow the researcher to evaluate individual factor on response factor and the relationship between them
Possible Research Questions for the Study
The research could be based on the following questions
Measurement of Obesity
In this study, Obesity was measured in t ways. First, the experimenters evaluated obesity as the weight corresponding to a height greater than 20% of the mean weight for the particular age and sex of the subjects. Secondly, obesity was evaluated by measuring the triceps and subscapular skinfold thicknesses greater or equal to the 85th percentile. The data was recorded as a percentage of body weightto be classified as obese. Thus, the investigators changed obesity from an independent variable to a dependent variable.
Apparatus and Measures:
Energy expenditure was a dependent variable and varied based on independent variable of television condition.
Results
The study used Standard Deviation for statistical analysis. For instance, obese children had higher resting energy expenditures compared to their normal-weight counterparts. The scenario was represented with standard deviation of (mean ± SD = 1522.91 kcal/d ± 284.33 and mean ± SD = 1344.94 kcal/d ± = 235.92) respectively.
Conclusion
In general, the findings indicated that children who spend too much of their time viewing TV are likely to be more obese than their counterparts who spend less time watching TV. The study, therefore, suggests for parents to monitor and control the TV viewing trend of their children to reduce the risks of obesity.