In short, the left prefrontal cortex is intimately connected to the cingulate cortex, the source of attentional ability (e.g. Kalish, Wiech, Hermann, & Dolan, 2006), whilst simultaneously serving as site for happiness. The hypothesis of this essay, therefore is, that the greater the span of attention accorded an activity, the more positive and more intense the level of serenity experienced.

Although Csikszentmihalyi has conducted research on 'flow' and shown that the experience of flow associated with mindfulness and attentionality has been identified as the highest level of well being (Csikszentmihalyi, 2000), little if any research seems to exist on the connection between hobbies and serenity. It may be assumed that hobbies indicate a sense of flow, implicating mindfulness or attentioanlity, therefore, as per the left prefrontal cortex, sense of pleasure and serenity should be sharpened and participants should feel more serenity. Hobbies, however, are a huge field and their spectrum ranges from reading casual literature and stamp collecting (where it may be assumed that little focus is required) to the more thrilling and absorbing venues of, say, mountain climbing and cliff-jumping where optimum attention is required. This essay hypothesis that the more extreme the hobby, the more left prefrontal cortex involvement hence the more attention and serenity the result. In other words, the more attention accorded the hobby, the greater the serenity as a neurological response.

Dividing the hobbies in to different categories of attenionality is not so easy, particularly since individual differences exist and a hobby that may demand more attention from one, demands less attention from another. On the other hand, generalizations can be hesitatingly articulated in that some hobbies are known to be more thrilling than others therefore demanding more attention, whilst other hobbies, although pleasurable, can be performed almost as a matter of routine. Hobbies in the first category would include activities such as mountain climbing and sky-diving and even others such as yoga, butterfly watching and Ti Chi which although not considered 'thrilling' nonetheless need attention in order to performed well. With many, one misstep would result in danger or in distortion of the exercise or operation. Hobbies involving more moderate attention would include swimming, ice-skating and roller-skating depending again on the length f time that one has been involved in these hobbies. Presumably the more time, the more habituated one is in their activity. These hobbies may not demand the maximum attention that those in the most thrilling category do; yet, they demand more attention than does the last category, which includes hobbies such as stamp-collecting and casual reading of literature where little attention is required. Inclusive here, too, would be crafts such as camping, planting bonsai trees, and doll-collecting, carpet-working, and embroidery, as well as sports such as hiking, bicycling, and jogging where attention is so minimal that one jogs, for instance, with music or accompanies it with conversation as means of distraction.

The study that follows, therefore, examine the operation of this explanation mechanism in that intensity of attention to a task induces serenity and the study connects this premise to hobbies. In the study, the explanation task was introduced to all subjects. They had been previously tested for serenity according to the Brief Serenity Scale and a survey had been applied to them whereby participants had described their favorite hobby. The study here tested for differences between the hobbies and tested whether correlation could be traced between recorded levels of serenity (as coded by the Brief Serenity Scale) and the chosen hobby. Our interest in the study focused on 2 main questions: First, would participants that indulge in hobbies that demand more attention indicate greater serenity levels on a general scale? Second, would there be gender differentiation between groups of hobbies?

Our first hypothesis states that the more demanding the hobby and the greater the level of attention accorded it, the higher the index of serenity will be accorded to that individual.

The second hypothesis states that there will be no or little gender differentiation indicated between categories of hobbies

The first null hypothesis states that little or no difference will be remarked between the different levels of hobbies. In other words, that even though some hobbies may demand greater level of attention than others no correlation will be discovered between the intensity of attention accorded the hobby and between the individual's score of serenity.

The second null hypothesis states that gender differentiation will be...

All subjects had been applied the Brief Serenity Scale that tested general serenity levels as a personality trait. They had also been surveyed regarding their favorite hobby. Data was then entered in an SPSS data set and regression performed to test for correlation. Although there was no need to divide this group into subgroups since the focus was on whether a correlation could be traced between one variable and another not between one comparison group and the other, SRS had been performed in selecting the initial people. This was so in order to gain as diversified a sample as possible (from 'high', "medium', and 'low' socio-economic sectors (since some students come from stressed backgrounds and this may reflect attention dedicated to their hobbies). I chose stratified random sampling since it addresses the problems of the simple random sampling approach and best models the original population.
Categorization of hobbies itself was divided into three groups and distinguished by their coding;

1-5 referred to hobbies that demanded low attention (such as singing, cooking, and eating); 5-10 referred to the mediate category where more moderate attention was accorded hobbies. Hobbies in this category included bicycling, swimming, and shopping. 10+ referred to hobbies that demanded high attention, the category including tennis, golf, and aviation.

Categorization and coding of hobbies was designed by 4 objective double-blind researchers who were non-cognizant of the characteristics of the research. Disputes were arbitrated by one other objective individual. Hobbies that could not be agreed upon were dropped and participants were asked to select another hobby.

Stratified random sampling

I used a sampling interval where I selected potential respondents from a sampling frame of 1303 students, but unlike simple random sampling, the JCC Business students had already been divided into strata (i.e. separate subpopulations), since I wanted these individuals to represent all sectors of the socio-economic population. I relied upon their stated demographics when doing so (i.e. students had been asked to record their socioeconomic strata when filling out their brief serenity survey according to class / salary / profession that they approximated their parents to belong to. (Alternatives of salary ranges had been supplied and students had been asked to check the box that they felt best simulated their situation). The strata had been divided into 'high', 'medium', and 'low' income backgrounds. Each stratum had 434 names. I then proceeded using simple random sampling from each stratum. The sampling interval here was 434/100 = 4.34 (round number, 4). Using random number tables, I selected a number between 1 and 4 to give the seed number to start with. It was 2. I then selected every 2nd person on the list, then the 6th (2 +4), the 8th (6+2) and so forth. The three strata ended up not contributing an equal number to both gender, but the number was in proportion to the expected sizes of strata in the population. There are proportionately fewer high earning people than low earners and the eventual sample reflected these proportions.

Explanation for sample size

It is usually the case that the bigger the sample the better the estimate since standard error decreases with increase of sample size. Three considerations are involved in sample size: level of precision (or margin of error), confidence level, and degree of variability. The margin of error is the amount of error that I can tolerate: a lower margin of error requires a larger sample size. For level of precision, or sampling error (otherwise known as margin of error), I chose 6.16.

The confidence level refers to the amount of uncertainty that I can tolerate. Higher confidence levels require a larger sample size. For confidence level I chose 80%,

The degree of variability or response distribution refers to the variance of the population. Since the population is a normal bell-shaped distribution, I chose 50%.

The calculation was performed on the sample size calculator provided by Raosoft (http://www.raosoft.com/samplesize.html)

A good-sized sample is needed for multiple regressions, although for the second study where it is descriptives that are being analyzed (i.e. mean, frequencies, standard deviation and so forth) any sort of sample size (of course with conditions) would suffice. Sudamn (1976) suggests that a minimum of 100 participants would be adequate for each major group or subgroup in the sample (and that a sample of 20 to 50 elements is necessary). Similarly, Kish (1965) says that 30 to 200 elements are sufficient when the attribute is repent 20 to 80% of the time (i.e. The distribution approaches normality).

Method

Subjects

The participants were 100…