Draft Results: analyze data (statistically) and present you results (data and analysis) and do not interpret what it means. Include a statistical analysis for each hypotheses and in the analysis yielded significant results. Use Figures and/or Graphs and Tables in the results section is also an effective addition to the written presentation. 
Draft Discussion: The Discussion is where you interpret the results of you study. In the Discussion present results in word not statistics. Present hypotheses again and state if they were supported or rejected and what that result indicates. Describe how results relate to past research on the problem. Refer to the results others have reported (presented in introduction) and how results agree or refute their results and why you think your results are the same or different. Finally discuss any limitations to study (what maybe should have been done differently or issues encountered {needed a more equal distribution of male and female participants} and what future research you would like to see done in this area. 

Relationship Between Hours Work & Sleep

Relationship Between Hours Worked and Sleep

Erica K. Fernandez
Louisiana State University Alexandria
PSYCH: 3017
Dr. Richard Elder


While sleep is one of the most important factors of physical, psychological, and mental health, its contributions are still widely taken for granted. Sleep has the potential of significantly improving or drastically diminishing one’s productivity. As such, it is necessary for sleep to be studied more deeply to understand how it affects employees. This study seeks to bring out the connection between the number of hours worked and the total number of hours slept per night, while putting into consideration variables such as full-time or part-time employment, and gender. According to the first hypothesis, individuals working less hours sleep longer than those working longer hours. As such, the variables of interest here are job hours and hours of sleep per night. Further, the second hypothesis connects gender (independent variable) with the aforementioned dependent variable. If there is a substantial correlation between the two, the Pearson Correlation should be applicable. Using Factorial ANOVA, I would change the second independent variable to the current position of the employee to make a lead to null hypothesis acceptance.
A literature review will be conducted highlighting existing literature in the contributions of sleep to productivity, and the severity of the consequences of failing to get enough sleep. Further, the differences in sleeping habits between men and women will also be highlighted, in addition to how longer working hours can result in fewer hours of sleep and diminish productivity. A 9-part questionnaire will also be distributed among students to select a target group of 30 individuals, 15 of each gender, to provide the primary source from which correlation between the dependent and independent variables will be derived using the correlation coefficient. The filled questionnaires will be compiled and grouped in terms of gender to allow for a pattern to be established either in agreement with or contrary to the proposed hypotheses.

Key words:

sleep, productivity, longer working hours, fewer hours of sleep


Studies of the brain have been around for centuries now, but the progress on our knowledge regarding its inner workings advances at a very slow pace. However, one of the main achievements in neurology – the study of the brain – is the determination of the role of sleep in improving mental acuity and alertness in tackling day-to-day tasks. It is unfortunate that despite the importance of sleep in keeping things in our bodies running smoothly, it is one of the most neglected aspects of leading healthy lives. This study intends to establish a connection between the number of hours worked per day and the number of hours slept at night. Shedding light on this area might help the corporate world to put more stake in ensu

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