It is impossible to underestimate the role of the sleep on the human organism. This biological process determines the working attitudes of a particular individual and brings a sufficient impact on the everyday life. The study collected is associated with exploration of the prevalence and impact of sleep problems on various aspects of people's lives.
First of all, it is essential to figure out, what is the average health rate. The sample size if entire survey is 271, and for the question of “Overall how would you rate your general health” (Pallant, 2010) there is one person, who did not answer. In this case, 1 is a symbol of really poor health and 10 – of very good one (Fig.1).
“The bell-shaped curves, called normal curves, summarize the overall patterns in each of the data sets. Because normal curves are symmetric, the mean μ and median are the same point, at the line of symmetry for the curve” (Student Guide, n.d.).
Hypothesis #1 - the quality of sleep is determined by the health condition of the person.
With this purpose one has to make the correlation analysis between the general health, physical fitness and current weight rate and then complete the regression equation.
The first step requires to chose bivariate correlations and there is the results received (Fig.3)
The second step requires the completing the equation. Since three variables do not covariate, it is possible to include all of them. In SPSS, “Regression is used to predict a categorical (usually dichotomous) variable from a set of predictor variables” (Kilic, 2015). For this case the regression analysis is presented in the Fig.4
The equality will look like QS (quality of sleep) = 0, 1 + 0, 03 – 0, 05, where R squared (which is the coefficient of determination) is 0,016. R square “is an overall measure of the strength of association and does not reflect the extent to which any particular independent variable is associated with the dependent variable” (Ats.ucla.edu, 2012). This means that R (0;1) makes the hypothesis weak as R gets closer to the zero. In this case the hypothesis is declined, since the quality of sleep is not affected by the general health, weight and physical fitness (together).
Hypothesis #2 (a particular reverse of the hypothesis #1) – the general health is determined by the quality of sleep. As one can see on the Fig.5 , the correlation is pretty weak.
The same fact happened to the regression analysis (Fig.6)
The hypothesis is declined, because R square is not sufficient.
Hypothesis #3. Females are more tended to have problems with sleep, rather than males.
This hypothesis could be easily checked and approved thanks to crosstabs (Fig.7)
This was proved by various studies and this hypothesis could be called as truthful one “Liljenberg surveyed randomly selected members of the population aged 30–65 years from two geographically different rural parts of central Sweden: 7.1% of the women and 5.1% of the men reported diffi culty in falling asleep; 8.9% of women and 7.7% of men reported trouble with nocturnal awakenings “ (Attarian, 2000). In this study 7-8% difference showed that women have more troubles with falling asleep and staying awake.
References
Kilic, S. (2015). Binary logistic regression analysis. JMOOD, p.191.
Ats.ucla.edu. (2012). Annotated SPSS Output: Regression. [online] Available at:
http://www.ats.ucla.edu/stat/spss/output/reg_spss.htm [Accessed 14 Apr. 2016].
https://www.learner.org/courses/againstallodds/pdfs/AgainstAllOdds_StudentGuide_Unit07.pdf [Accessed 14 Apr. 2016].
Attarian, H. (2000). Sleep and neuromuscular disorders. Sleep Medicine, 1(1), pp.3-9.
Pallant, J. (2010). SPSS survival manual. Maidenhead: Open University Press/McGraw-Hill.
