Sign Up Now
Get instant access to over 1 million+ study documents
OR
Already registered? click here to login
By creating your account, you agree to our terms of service, privacy policy and student honor code.
The results indicated that there is no significant difference between group 1 and group 2 with respect to their GPA, t (172) = .623, p =.534.
Part 3
The results of the analysis for hypothesis one did not support the hypothesis. It was predicted that individuals who received greater amounts of sleep would have correspondingly higher GPAs. The results of the correlation analysis were not significant, nor did they approach significance in any way. This means that, for individuals in this sample, the amount of sleep one gets is not related to one's GPA. Whether one sleeps for 4 hours during a week or for 30, there appears to be no relation to one's GPA. These results are surprising, as one would generally believe that receiving an adequate amount of sleep would contribute to an individual's ability to function well, and thereby get good grades. There are a few factors, which could have influenced the results of this study. It could be that the relationship between these two variables is not linear, which would therefore not allow a significant correlation to be found. What this might mean is that if one gets either too little sleep or too much sleep, their GPA may suffer, and that what truly predicts a good GPA would be getting a specific amount of sleep, such as 8 hours per night. This would create a U. shaped curve in which performance is reduced at each end of the U. But optimized in the centre of the U. The inability of the correlation analysis to detect this kind of a relationship represents one of the limitations of this study. Future analyses could address this issue by conducting separate analyses that allow for curvilinear relationships...
To conduct the analyses in a more simple fashion, the data could be divided into separate categories, those who received less than 6 hours of sleep per night, those who received more than 12 hours of sleep per night, and those that fall in between. Correlations could then be calculated separately for each of these three groups and the correlations could then be compared.
The lack of correlation between these variables may also be due to an error in the data collection process. The Amount of Sleep variable is supposed to represent the average number of hours a participant slept during each week, but the distribution of scores suggests that participants may have answered incorrectly, as the majority reported less than 10 hours of sleep, which, when being measured on the scale of a week, is a significant lack of sleep. It appears that the data look more like they represent the hours per night, and thus this may be influencing the results.
The results of the analysis for the second hypothesis demonstrate that there are no group differences in average GPA based on bedtime.
Another limitation that applies in general to both hypotheses is that the data used is self-report data. Self-report data is always subject to potential errors related to biases, as individuals do not always accurately remember the true responses and sometimes may deliberately alter their responses to appear one way or another. Thus, all data here should be taken with the knowledge that it was provided by the participants themselves and was therefore not corroborated in anyway by objective measurement. To address this limitation…
Sleep Questionnaire (RCSQ) Instrument Analysis Research to evaluate interventions to promote sleep in critically ill patients has been restricted by the lack of brief, inexpensive outcome measures (Richards, O'Sullivan, & Phillips, 2000). Usually the critically ill are given different medications that help them sleep. However, in many cases this is insufficient to achieve enough rest and sleep periods are generally fragmented and with decreased restrictiveness. Most researchers believe that a few
Sleep deprivation is frequently a direct result of the need for intensive care, constant surveillance and monitoring that combine to limit the opportunities for uninterrupted sleep in the intensive care unit (ICU). The problem is multifactorial, with patients' chronic underlying illness, pain, pharmacological interventions used for the treatment of the primary illness, as well as the ICU environment itself have all been shown to be contributing factors to the process
Introduction The purpose of this study was two-fold: 1) it aimed to identify relationships between sleep and other aspects of human functioning/performance; and 2) it sought to understand how sleep-wake patterns impact daytime functioning. The subject of this research was the researcher himself. The researcher kept a 4 week sleep diary with which to record information pertaining to sleep habits and daily life habits in order to test the conclusions of
126). Although there are an increasing number of elderly in the United States today with many more expected in the future, the study of elder abuse is of fairly recent origin. During the last three decades of the 20th century, following the "discovery" of child abuse and domestic violence, scholars and professionals started taking an active interest in the subject of elder abuse. This increased attention from the academic
Temperament Correlate to Physical health and Longevity? This research project explores if an individual's temperament is correlated with longevity or physical health. Temperament, "…refers to those aspects of an individual's personality…" (Kagan, 2005). The traits of temperament are considered more innate, and less learned. If a specific temperament could be labeled as associated with increased physical health or longevity, perhaps researchers could aid individuals who become ill earlier. This research
Sleep Deprivation on the Brain Studies on sleep deprivation continually display an inconsistent (negative) effect on mood, cognitive behaviour, and motor function as a result of a rising propensity for sleep as well as the destabilization of the wake condition. Unique neurocognitive domains such as executive attention, functioning memory, and conflicting higher cognitive behaviours are specifically apt to loss of sleep. In human beings, functional neurophysiological and metabolic studies prove