The Relationship between Age - Report Example

6 May Statistics Project Introduction to the Study This report is about the relationship between age and wish to obtain the ideal mate. It is commonly observed that youngsters develop the image for their life partner in their tender minds. In the initial years of youth, they are optimistic about having the perfect mate and they reject many other options which do not match with their ideal image. With the passage of time, after repeated failures, the ambitions go down and they tend to compromise over somebody who does not match with ideal image. The purpose of this study is to validate this relationship and see if it exists and up to what extent it is influential. The research question of the paper is; does age cause one to compromise our goals and expectations of obtaining your “ideal mate”? The hypothesis to be tested is; there is a negative relationship between the age and wish to get the ideal mate and this relationship is quite strong. The reason for this anticipated relationship is mentioned in the above paragraph that repeated failures lead the people to compromise over their strict standards. Population of the Study The population of this study consists of all the individuals who have liberty to choose their mate on their own. Their marital status can be married or unmarried but it is mandatory that they have remained unmarried till the age of 25 years. Variables of Study There are two core variables studied in analysing this relationship. These are age and gender. These variables will show the varying level of expectations about getting the ideal mate. The age will range from 20-35 years while the gender can take only two mutually exclusive values of male and female. As mentioned earlier, the population consist of both married and unmarried individuals; the age bracket of 20-35 will considerably show the phases of expectations about getting the ideal mate. Data Collection The data is collected mainly through primary sources i.e. interviews and questionnaires. The main locations visited for the purpose of data collection are the university and the nearby restaurant which people from various background visit for dining in. The university students, faculty members and the administrative staff were consulted to provide answers to the questions. The questionnaire along with responses of people is attached with report. Since data was collected from the two locations which are entire different in nature i.e. university and restaurant, it is evident that the data is free from bias. The respondents were true representation of the population as they were different in their age groups and have experience of various phases of expectations about obtaining the ideal mate. Questionnaire 1) What is your age and gender? 2) What is your marital status? If single, skip the next question. 3) What was your age at the time of first marriage? 4) How many proposals you have had by now? 5) Did you have an image of ideal mate when you were in late teens? 6) How sure you were at that time that you will get the ideal mate? 7) Did you look for the exact match of your ideal mate or were of the view to accept the one close to it? 8) Did the expectation to have ideal mate remained the same in the early 20s or you skipped the few expectations? 9) By the age of 25, was there any further decrease in the hope that you will get the ideal mate? 10) Does the further increase in age, reduced the hope any more? Sampling Strategy The population size is huge and keeping in view the project constraints, the sample size is limited to 100. Individuals from both genders are equally represented in the sample. The researchers collected info about the current age of the respondent and the age at which he or she made his first marriage. Only the people who are in the age bracket of 20-35 years and did not marry before the age of 25 years are not included in the sample randomly. Study Design As mentioned earlier, there are two input variables related to the study. These variables are age and gender of the respondent. The output variable is the level of optimism about having ideal mate. It is an analytical study whereby the relationship between input and output variable is determined by the correlation coefficient. As evident from the nature of variables, there can be combined effect of input variable to the output variable. In simpler terms, it means it is quite possible that men and women experience different level of optimism about ideal mate at different stage of growing age. Keeping in view this possibility, the interaction between input variables is also studied. Before conducting the analysis, there is expected possibility of strong negative relationship among the input and output variables. The null hypothesis is: there is no relationship between the age and wish to get the ideal mate. Ho: rxy = 0 The alternative hypothesis is: there is strong negative relationship between the age and wish to get the ideal mate. HA: rxy ≠ 0 Results Summary Statistics Gender Male Female Same Expectations with the growing Age 33 10 Expectations Changed with the growing Age 17 40 Descriptive Statistics Sample Size 100 Mean 63.78 Standard Deviation 32.18 5-Number Summary Min 33 Max 100 Upper Quartile 100 Median 49.5 Lower Quartile 33   Statistical Analysis Correlation -- Females -0.653 Correlation -- Males -0.162 The analysis shows there is strong negative relationship between the level of optimism to get the ideal mate and the growing age for females. In case of males, the relationship is negative but it is weak. It means males remain optimistic about getting the ideal mate even if their age increases. Equation of regression line for females: y = 146.57 – 3.55x Equation of regression line for males: y = 106.32 – 1.04x Prediction of male’s level of optimism at the age of 38: 11.67 (Negligible) Prediction of female’s level of optimism at the age of 38: 66.8 (Moderately strong) The slope of regression line in both the equation is less than 1. It indicates there is negative change in the level of optimism in relation to the change in age. R2 for females is 0.426 which means regression model is fit in the data series and 42% of the optimism is explained by age. R2 for males is 0.026 which means regression model is weakly fit in the data series and only 2% of the optimism is explained by age. Since the data consists of 100 elements in the sample, it is evident that the correlation is significant (Spatz, 191). Findings The analysis shows that the data supports the alternate hypothesis and confirms that there is relationship between the age and level of optimism to have ideal mate. This relation is strong and negative. The analysis supports the expected findings in the case of females, however, in case of males; there is not the strong evidence about it. Discussion As a result of this study, it can be concluded that the growing age has a considerable impact upon one’s expectation in getting the ideal mate. Particularly in case of females, the age has strong impact. It is because they usually want to marry for the sake of protection in society and this need becomes more and more important with the passage of time. In order to fulfil this need, they tend to come out of the world of idealism. On the other hand, men remain optimistic to get the ideal mate and it is mainly because of the status they acquire in the society. Their financial position is strengthened hence they believe their dreams about ideal mate can come true. The population of the project is good enough to draw general conclusions from the research. The research variables are important in the regard of their interaction and the statistical analysis throws light with various angels at the points to ponder. Works Cited Spatz, Chris. Basic Statistics Tales of Distributions. California: Cengage Learning, 2011. Print. Appendix : Responses Respo ndent # Age Gender Marital Status Age at the time of Marriage Proposals Had Image Surity Exact Match Early 20s 25 Years Age Increased Level of Optimism 1 20 Female Single   2 Yes Yes Exact Same - Same 100 2 20 Female Single   2 Yes Yes Exact Same - Same 100 3 21 Female Single   3 Yes Yes Exact Same - Same 100 4 21 Female Single   2 Yes Yes Exact Same - Same 100 5 22 Female Single   3 Yes Yes Exact Same - Same 100 6 22 Female Single   2 Yes Yes Exact Same - Same 100 7 23 Female Single   4 Yes Yes Exact Changed - Changed 33 8 23 Female Single   3 Yes Yes Exact Changed - Changed 33 9 24 Female Single   5 Yes Yes Close Changed - Changed 33 10 24 Female Single   6 Yes Yes Close Changed - Changed 33 11 25 Female Single   7 Yes Yes Close Changed Changed Changed 33 12 25 Female Single   8 Yes Yes Close Same Changed Changed 66 13 26 Female Single   6 Yes Yes Close Same Changed Changed 66 14 26 Female Married 25 8 Yes Yes Close Same Changed Changed 66 15 27 Female Married 25 9 Yes Yes Close Same Changed Changed 66 16 27 Female Married 25 8 Yes Yes Close Changed Changed Changed 33 17 28 Female Married 23 10 Yes Yes Close Changed Changed Changed 33 18 28 Female Married 24 10 Yes Yes Close Changed Changed Changed 33 19 29 Female Married 25 10 Yes Yes Close Changed Changed Changed 33 20 29 Female Married 25 10 Yes Yes Exact Changed Changed Changed 33 21 30 Female Married 27 10 Yes Yes Exact Changed Changed Changed 33 22 30 Female Married 28 9 Yes Yes Exact Changed Changed Changed 33 23 31 Female Married 25 9 Yes Yes Exact Changed Changed Changed 33 24 31 Female Married 25 11 Yes Yes Exact Changed Changed Changed 33 25 32 Female Married 27 12 Yes Yes Exact Changed Changed Changed 33 26 32 Female Married 27 13 Yes Yes Exact Changed Changed Changed 33 27 33 Female Single   14 Yes Yes Exact Changed Changed Changed 33 28 33 Female Single   15 Yes Yes Close Changed Changed Changed 33 29 34 Female Single   14 Yes Yes Close Changed Changed Changed 33 30 34 Female Single   15 Yes Yes Close Changed Changed Changed 33 31 35 Female Single   13 Yes Yes Close Changed Changed Changed 33 32 35 Female Single   15 Yes Yes Close Changed Changed Changed 33 33 20 Female Single   1 Yes Yes Close Changed Changed Changed 33 34 26 Female Single   5 Yes Yes Close Same Changed Changed 66 35 21 Female Single   2 Yes Yes Close Same - Same 100 36 22 Female Single   3 Yes Yes Close Same - Same 100 37 23 Female Single   2 Yes Yes Close Same - Same 100 38 24 Female Single   3 Yes Yes Close Same - Same 100 39 25 Female Single   6 Yes Yes Exact Changed Changed Changed 33 40 27 Female Single   8 Yes Yes Exact Changed Changed Changed 33 41 28 Female Single   9 Yes Yes Exact Changed Changed Changed 33 42 29 Female Single   10 Yes Yes Exact Changed Changed Changed 33 43 30 Female Married 29 12 Yes Yes Exact Changed Changed Changed 33 44 31 Female Married 29 12 Yes Yes Exact Changed Changed Changed 33 45 32 Female Married 29 12 Yes Yes Exact Changed Changed Changed 33 46 33 Female Married 30 12 Yes Yes Exact Changed Changed Changed 33 47 34 Female Married 30 10 Yes Yes Close Changed Changed Changed 33 48 35 Female Married 30 12 Yes Yes Close Changed Changed Changed 33 49 20 Female Married 19 1 Yes Yes Close Changed - Changed 33 50 21 Female Married 19 1 Yes Yes Close Changed - Changed 33 51 20 Male Single   2 Yes Yes Exact Same - Same 100 52 20 Male Single   2 Yes Yes Exact Same - Same 100 53 21 Male Single   3 Yes Yes Exact Same - Same 100 54 21 Male Single   2 Yes Yes Exact Same - Same 100 55 22 Male Single   3 Yes Yes Exact Same - Same 100 56 22 Male Single   2 Yes Yes Exact Same - Same 100 57 23 Male Single   4 Yes Yes Exact Changed - Changed 33 58 23 Male Single   3 Yes Yes Exact Changed - Changed 33 59 24 Male Single   5 Yes Yes Close Same - Same 100 60 24 Male Single   6 Yes Yes Close Same - Same 100 61 25 Male Single   7 Yes Yes Exact Same Same Same 100 62 25 Male Single   8 Yes Yes Exact Same Same Same 100 63 26 Male Single   6 Yes Yes Exact Same Same Same 100 64 26 Male Married 25 8 Yes Yes Close Same Same Same 100 65 27 Male Married 25 9 Yes Yes Close Same Same Same 100 66 27 Male Married 25 8 Yes Yes Close Changed Same Changed 33 67 28 Male Married 23 10 Yes Yes Close Changed Same Changed 33 68 28 Male Married 24 10 Yes Yes Close Changed Changed Changed 33 69 29 Male Married 25 10 Yes Yes Close Same Changed Changed 66 70 29 Male Married 25 10 Yes Yes Exact Same Same Same 100 71 30 Male Married 27 10 Yes Yes Exact Same Same Same 100 72 30 Male Married 28 9 Yes Yes Exact Same Same Same 100 73 31 Male Married 25 9 Yes Yes Exact Same Same Same 100 74 31 Male Married 25 11 Yes Yes Exact Same Same Same 100 75 32 Male Married 27 12 Yes Yes Exact Changed Same Changed 33 76 32 Male Married 27 13 Yes Yes Exact Changed Same Changed 33 77 33 Male Single   14 Yes Yes Exact Same Same Same 100 78 33 Male Single   15 Yes Yes Close Same Same Same 100 79 34 Male Single   14 Yes Yes Close Same Same Same 100 80 34 Male Single   15 Yes Yes Exact Same Same Same 100 81 35 Male Single   13 Yes Yes Exact Same Same Same 100 82 35 Male Single   15 Yes Yes Exact Same Same Same 100 83 20 Male Single   1 Yes Yes Close Same Same Same 100 84 26 Male Single   5 Yes Yes Close Same Changed Same 66 85 21 Male Single   2 Yes Yes Close Changed - Changed 33 86 22 Male Single   3 Yes Yes Exact Changed - Changed 33 87 23 Male Single   2 Yes Yes Exact Changed - Changed 33 88 24 Male Single   3 Yes Yes Exact Same - Same 100 89 25 Male Single   6 Yes Yes Exact Same Same Same 100 90 27 Male Single   8 Yes Yes Exact Same Same Same 100 91 28 Male Single   9 Yes Yes Exact Same Same Same 100 92 29 Male Single   10 Yes Yes Exact Same Same Same 100 93 30 Male Married 29 12 Yes Yes Exact Same Same Changed 66 94 31 Male Married 29 12 Yes Yes Exact Changed Same Changed 33 95 32 Male Married 29 12 Yes Yes Exact Changed Same Changed 33 96 33 Male Married 30 12 Yes Yes Exact Same Changed Changed 33 97 34 Male Married 30 10 Yes Yes Close Same Changed Changed 33 98 35 Male Married 30 12 Yes Yes Exact Same Changed Changed 33 99 20 Male Married 19 1 Yes Yes Exact Same - Same 100 100 21 Male Married 19 1 Yes Yes Exact Same - Same 100 Read More