SocialBehaviour and Human Relationships
Mostsocial scientists study the economic, political and social worldsurrounding them when they want to develop theories concerning thehuman social relationships. Some of them examine their lifeexperience, as well as, their day-to-day activities in search forinformation required in answering the research question (Giddens 45).In this paper, I will explain three major events that occurred duringa two-day tracking period in different contexts. The events occurredin a public park near our home, the supermarket and the schoollibrary.
Wehad visited the public as a group of fifty students. Right at thepark, the students engaged in many activities such as holdingdiscussions, walking around the nice places and playing hide and seekgames. Back at school, no one could have noticed that students haddiverse cultures, but, the park revealed the human social behavioursespecially when they were playing hide and seek. They separatedthemselves in social groups despite their awareness of the negativeimpacts of segregation of social relationships. I found that besidesthe collective human behaviours in a group, individuals withholdcertain beliefs and perceptions among themselves. The researchinvolved finding out the underlying human behaviours that preventindividuals from interacting with other people. The research would beinteresting because it would involve the students who would expresstheir opinions without fearing. Some of the possible answers thequestion can be related to the psychological processes, changingenvironments and stereotypes.
Secondly,at the supermarket, I observed how the customers reacted to thedirections given by shop attendants. A particular section wasundergoing reconstruction and, therefore, the attendants kept thecustomers away from that place. In return, they directed them to asafe path to use. These shop attendants seemed to be very tired asthey controlled the customers. In this context, I was concerned aboutthe consumers’ behaviour that made them scrabble to use the unsafespace instead using the safe one.The behaviour was worth studying inorder to define what make people sometimes love doing some wrongthings instead of the right ones. In this case, the speculatedanswers for the research question could be because the customers wereused to that path or they wanted to explore the unseen.
Duringa visit in the library, I observed that most students asked questionswhen the librarian was uttering some words. Before she startedspeaking, many students remained quiet even if they had questions.The best research question could be, “What makes people fear theauthority figures even when they have enough confidence?” Thebehaviour is interesting to study because one would get an overviewof the nature of human behaviour at a personal level. The possibleanswers could be related to preconceived perception about a leader,for example, a leader may be considered commanding or authoritative.
Iagree that all of us can be sober-minded and mild-minded, whereby onecan be passionate, but, at other times, becomes morallyirresponsible(Giddens 45). On my part, I can imagine the thoughtsthat would be streaming through my mind in both states. In a sobermood, I think of how I can share views with other like-minded people.However, when the people become unfair, I think of how I can outdothem so as to retain my personal identity. Ariely’s findings, whichsuggest that all of us are a Dr.Jeykll and a Mr.Hydeare credible andtrue. I can also justify the stated conclusions by exploring mythoughts and feelings that define me in passionate state. When I amnot angry, I am very warm and generous, but, these characters usuallyturn to violent and aggressive behaviours when I get angry (Sharma90).
Therecommendation generating algorithm, Netflix, is used to control thevideos and television shows that people watch especially in theUnited States. The Netflix suggestions have been facilitated by thenumerous invisible arrays of algorithms. Most viewers depend on theNetflix estimates (Marx 345). These automated approaches utilize theusers’ behaviour, for example, playing, browsing and searching.Similarly, those people who would give recommendations on the showsand videos that one can watch will also rely on the users’behaviours. The difference between the two approaches is thatthemouth-to-mouth recommendationdepends on the people’s behaviourwhereas the algorithm approach is accurate. Therefore, algorithms aremore effective as compared to the “word-of-mouth”recommendations. The algorithms should incorporate the wide rangingvariables that exist in the huge masses of people. For example, inthe film industry, the Netflix engineers should incorporate theviewers’ opinions in developing the algorithms (Marx 347).
Descriptivestatistics involves analysis of raw data in the study. The statisticsprovide simple summaries of the sample using the measures ofdispersion and central tendency (Devore and Kenneth 86). Other thanusing the statistic in sports and analysis of marks, it can be usedin summarising the spending of money while at school and home.Thedescriptive statistic seeks to describe how money is spent on amonthly basis when at home or school. The statistics cover themeasures of central tendency, that is, the mean, median and the mode(Sirkin 146). However, the mean amount of spending is the mostreliable statistic parameter that can be used to analyse the spendingin a month and a year.
Thestatistic is constructed by summing up the money spent during oneperiod of three months while in school. The total can be labelled asT.Then the total is divided by the three periods in order to get theaverage amount of money spent while in school. Note that the numberof periods can vary and, therefore, the most appropriate symbol forthe number of periods should ben.Then, the statistic can be calculated using the function T/n(Devoreand Kenneth 88).Thestatistic can be applied to analyse the spending on books, clothesand food. Also, it can be used to approximate the amount of muchmoney spent on leisure. In this way, one can identify when there ismore spending whether at home or school.
Thestatistic well accounts for the money spent and, therefore, give thebest analysis or summaries of the sample data. The statistic isreliable in estimating the amount of money that one needs in onemonth. However, the statistic failed to account for the disparitiesof money spending that might occur during that time. In other words,it gives rough estimates of the total amount spent by an individual,but, not the actual values (Sirkin 149). The statistic can besupplemented by other descriptive statistics that accounts for thedispersion and variation of the amount of money spent in a specifiedtime.
Devore,Jay, and Kenneth, Berk. ModernMathematical Statistics with Applications.New York, NY: Springer, 2012. Print.
Giddens,Anthony. Introductionto Sociology.New York: W.W. Norton, 2012. Print.
Marx,Paul. ProvidingActionable Recommendations: A Movie Recommendation Algorithm withExplanation Capability.Lohmar:Eul, 2012. Print.
Sharma,Rajendra K. SociologicalMethods and Techniques.New Delhi [India: Atlantic Publishers and Distributors, 1997. Print.
Sirkin,Raphael. Statisticsfor the Social Sciences.Thousand Oaks [etc.: SAGE, 2006. Print.