Homeownership vs Renting Comparisons of Males, Females, Couples, and Singles - Statistics Project Example

Homeownership vs. renting comparisons of males, females, couples and singles and other trends in real e Homeownership vs. renting comparisons of males, females, couples and singles and other trends in real estate Introduction Home ownership has over the years been considered an important fabric of the society. As a matter of fact, many associate home ownership with success. Many studies have as well been conducted if only to understand the housing dynamics in depth. The modern housing market is however weak and a number of markets have been faced with foreclosures making it preferable to rent a house rather than buy one (Mulder, 2006). An American president, Abraham Lincoln once said, “The strength of a nation lies in the homes of its people.” Contrary to popular belief that those who own homes are better than those who rent their residences has been found to lack basis. This is however not the focus of this paper; rather the paper looks into homeownership vs. renting comparisons of males, females, couples and singles and other trends in real estate. Home ownership is an important aspect of people’s life quality. More often than not, buying a home requires a huge financial investment, which makes it a very important step in life. Planners and policy makers find it important to not just understand the market demographics but also the trends surrounding tenant-ship. Previous researches have revealed that individual characteristics, resources as well as household situations are amongst the important factors which influence housing tenure (Arimah, 2009). One research revealed that the number of single people buying homes has immensely increased and as such there is increased chance the single people will become a majority of homebuyers soon. According to the report, number of single mortgage borrowers, as opposed to couples, has undergone steady growth as a part of mortgage financing since 1990s, when they constituted a meager 26.7% of home purchasing market. Singles currently stand at over 45% of homebuyers with financing (Chiuri & Jappelli, 2012). Such a statistic is not just important to policymakers but also to real estate companies who use it to know which segment of the market to direct their marketing resources to. Additionally, while there is a large literature on analysis of housing tenure choices, few studies have incorporated into their empirical analysis, whether the household is headed by a man or a woman. As a matter of fact, taking into consideration the correlation between various determinants of housing tenure leads to an endogeneity problem and hence inconsistent and counterintuitive results (Hannan, Tuma, & Groeneveld, 2010). Generally, the study of housing trend can take an extremely widened point of view. However, this paper has narrowed down it choices to compare two kinds of housing tenor, homeownership and rental while taking into consideration three study groups, namely, single women, single men, and couples in order to understand market trends. This limits the findings of the study to trend study rather than an in-depth evaluation of the market dynamics. ANOVA is used to achieve this. Research procedure As already mentioned the study takes a multifaceted approach and tests the equality of various means using variance. This is through ANOVA analysis that is based on a number of assumptions including: independence of the samples, equal variance in populations and that the population from which the sample is extracted has a normal or near normal distribution. This paper therefore applies ANOVA analysis in development of statistical assumptions defining the situation homeownership vs. rental between couples, single women, and single men. It explores the impact of marital status on the kind of home tenor trends in the study market. Using selected variables, this paper will successfully illustrate how ANOVA analysis is applicable in analysis of such scenario. To achieve this, a null and an alternative hypothesis will be developed and tested with the help of SPSS statistical analysis tool. The null and alternative hypothesis provides a rational basis upon which conclusions are drawn. In comparing the relationship between home ownership and rental housing amongst people with different marital statuses, the paper will seek to establish whether the means of several groups are equal as well as determine if there exist any significant differences. In general, this paper aims to illustrate the logic used in ANOVA. The null hypothesis evaluated by one way ANOVA is that the mean of two or more populations are equal. As a matter of fact, the paper questions whether (H0) the population means for all groups bear equality and that the differences observed are a result of variations from random sampling (Brian, 2009). When null hypothesis is not true, the alternative hypothesis (Ha) supposes that the observed differences between means of sample being evaluated are real differences in the mean of the populations. The logic applied in ANOVA in mean comparison is similar to comparison of means adopted in t-tests. The data set used in this study is based on three marital statuses. One is constituted of single females; the other group is constituted of single males, while the last group is comprised of couples. Couples in this case refers to all forms of persons who leaving together on basis of marriage. The data used is obtained from the General Social Survey disk. The data measures the residential choice average levels for people in respective groups whether ownership or rental. In order to determine the impact of different marital statuses in the kind of tenancy, an analysis scheme is designed and implemented with the help of SPSS analysis tool. The null hypothesis states that there is no significant difference in means of different marital statuses in assessing the kind of tenancy preferred while the alternative hypothesis states the opposite, that there is a significant difference in the means of in means of different marital statuses in assessing the kind of tenancy preferred. Mathematically, the expressions are expressed as follows: , are the means for single women, single men, and couples respectively. To further evaluate the significance of the test, the statistic F value is obtained. The F value is tested with a P value of 0.05 and as such an F value less than the p value will lead to outright rejection of the hypothesis being evaluated. Given that the primary ANOVA analysis does not give the actual mean differences for the groups evaluated, this study conducts further post-hoc studies to define the group differences. Tukey B is adopted for this study. Results The SPSS output displays the findings established based on the criteria defined earlier in the study. Descriptives MARITAL STATUS OF 1ST PERSON N Mean Std. Dev. Std. Error 95% Confidence Interval for Mean Min. Max. Lower Bound Upper Bound OWN OR IS BUYING 1312 1.89 1.344 .037 1.82 1.96 1 5 PAYS RENT 625 3.07 1.671 .067 2.94 3.20 1 5 OTHER 32 2.50 1.524 .269 1.95 3.05 1 5 Total 1969 2.27 1.558 .035 2.21 2.34 1 5 Table 1: Descriptive statistics From the research study, each dependent variable i.e. house tenor there is an associated mean as well as a standard deviation. As earlier mentioned two scenarios are evaluated: firstly, the state prior to treatment and secondly, the state after treatment. The respective means and variances are shown in table 1 attached. The returned means, for instance after treatment administration shows that the means fail to satisfy the criteria defined by the null hypothesis i.e. Whereby are 1.89, 3.07, and 2.50 respectively. However, the null hypothesis is not immediately rejected. Rather a further evaluation for statistical significance is sought. Table 2: Test for homogeneity of variances Test of Homogeneity of Variances MARITAL STATUS OF 1ST PERSON Levene Statistic df1 df2 Sig. 49.386 2 1966 .000 To reject the findings of the null, the F statistic value is determined. ANOVA MARITAL STATUS OF 1ST PERSON Sum of Squares df Mean Square F Sig. Between Groups 596.760 2 298.380 140.233 .000 Within Groups 4183.144 1966 2.128 Total 4779.905 1968 Given the F value of 140.233 obtained between groups, it is sufficient to reject the null hypothesis (see table 2). The F values shows that the result are statistically significant because they are larger than the p value of .00 earlier stated. There is a strong evidence suggesting that the there is a significant difference between the means of variables being evaluated. ANOVA MARITAL STATUS OF 1ST PERSON Sum of Squares df Mean Square F Sig. Between Groups 596.760 2 298.380 140.233 .000 Within Groups 4183.144 1966 2.128 Total 4779.905 1968 The ANOVA results further reinforce the earlier defined results. It provides the results between groups as well as within groups. Multiple Comparisons MARITAL STATUS OF 1ST PERSON LSD (I) DOES R OWN OR RENT HOME? (J) DOES R OWN OR RENT HOME? Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound OWN OR IS BUYING PAYS RENT -1.186* .071 .000 -1.32 -1.05 OTHER -.612* .261 .019 -1.12 -.10 PAYS RENT OWN OR IS BUYING 1.186* .071 .000 1.05 1.32 OTHER .574* .264 .030 .06 1.09 OTHER OWN OR IS BUYING .612* .261 .019 .10 1.12 PAYS RENT -.574* .264 .030 -1.09 -.06 *. The mean difference is significant at the 0.05 level. In both cases, the results reveal that there are indeed differences between the groups as well as within groups. This is further revealed in the graph below, Conclusion The results reveal interesting findings. It comes as no surprise that while most single persons rent the places they live, apparently, they seek home ownership as well as this is evidence by the high percentage of single women and men who own homes. The results provide sufficient evidence to conclude that singles prefer to own homes just like couples do. However, couples record slightly higher value of home ownership largely attributed to their preference to settle in a single location and make a life. This is unlike singles who, may opt to change locations easily. It is however evident based on the F value that there is a difference in ownership between the study groups in essence implying that the group within which one falls, dictate the kind of residence they prefer and ultimately own. References Arimah, B. (2009). The Determinants of Housing Tenure Choice in Ibadan, Nigeria, Urban Studies, 34(1), 105-124. Chiuri, M., & Jappelli, T. (2012). Financial Market Imperfections and Home Ownership: a Comparative Study, European Economic Review, 47(5), 857-875. Hannan, M., Tuma, N., & Groeneveld, L. (2010). Income and Marital Events: Evidence from an Income-Maintenance Experiment, American Journal of Sociology, 82(6), 1186-1191 Kurz, K & Blossfeld, H. (2008). Homeownership and social Inequality in comparative perspective. Stanford: University Press. Mulder, C.H. (2006). Home-ownership and family formation. Journal of Housing and the Built Environment, 21, pp. 281-298. Appendix: The overall SPSS and syntax files illustrating the discussion illustrated in the study are attached hereafter: SPSS Syntax and output Your trial period for SPSS Statistics will expire in 21 days. GET FILE=C:\Users\chris\Desktop\data.sav. >Warning # 67. Command name: GET FILE >The document is already in use by another user or process. If you make >changes to the document they may overwrite changes made by others or your >changes may be overwritten by others. >File opened C:\Users\chris\Desktop\data.sav ONEWAY mar1 BY dwelown /STATISTICS DESCRIPTIVES HOMOGENEITY /MISSING ANALYSIS /POSTHOC=LSD ALPHA(0.05). Oneway Notes Output Created 18-Apr-2014 15:19:31 Comments Input Data C:\Users\chris\Desktop\data.sav Active Dataset DataSet1 Filter Weight Split File N of Rows in Working Data File 4510 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics for each analysis are based on cases with no missing data for any variable in the analysis. Syntax ONEWAY mar1 BY dwelown /STATISTICS DESCRIPTIVES HOMOGENEITY /MISSING ANALYSIS /POSTHOC=LSD ALPHA(0.05). Resources Processor Time 0:00:00.359 Elapsed Time 0:00:00.577 [DataSet1] C:\Users\chris\Desktop\data.sav Descriptives MARITAL STATUS OF 1ST PERSON N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Max Lower Bound Upper Bound OWN OR IS BUYING 1312 1.89 1.344 .037 1.82 1.96 1 5 PAYS RENT 625 3.07 1.671 .067 2.94 3.20 1 5 OTHER 32 2.50 1.524 .269 1.95 3.05 1 5 Total 1969 2.27 1.558 .035 2.21 2.34 1 5 Test of Homogeneity of Variances MARITAL STATUS OF 1ST PERSON Levene Statistic df1 df2 Sig. 49.386 2 1966 .000 ANOVA MARITAL STATUS OF 1ST PERSON Sum of Squares df Mean Square F Sig. Between Groups 596.760 2 298.380 140.233 .000 Within Groups 4183.144 1966 2.128 Total 4779.905 1968 Post Hoc Tests Multiple Comparisons MARITAL STATUS OF 1ST PERSON LSD (I) DOES R OWN OR RENT HOME? (J) DOES R OWN OR RENT HOME? Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound OWN OR IS BUYING PAYS RENT -1.186* .071 .000 -1.32 -1.05 OTHER -.612* .261 .019 -1.12 -.10 PAYS RENT OWN OR IS BUYING 1.186* .071 .000 1.05 1.32 OTHER .574* .264 .030 .06 1.09 OTHER OWN OR IS BUYING .612* .261 .019 .10 1.12 PAYS RENT -.574* .264 .030 -1.09 -.06 *. The mean difference is significant at the 0.05 level. Read More