¶ … Linear, Logistic or Multiple Correlation/Regression Proposal
Objective of this paper is to use the statistical test to investigate whether the middle income earners in developing countries are capable of becoming home owners. The paper uses Nigeria as a case study. Unlike the developed countries such as the United States and United Kingdom where middle income earners can become house owners, however, the issues are different in developing countries because various factors prevent middle income earners from purchasing housing units compared to middle income earners in developing countries. Typically, a level of income plays a critical role in homeownership. While different governments in developing countries have implemented various policies in assisting people to become homeowners, nevertheless, factors such as corruption, inflation, and poor implementations have made the policy non-realizable. In Sub-Sahara African countries, nearly 62% of people live in slums, and per capital income of most developing countries are less than $300.(Chica, 2008). Moreover, more than 87% of individual households fund are used to fund the housing units since there are little or no support from the governments and mortgage financial institutions. Moreover, economic and social factors also prevent people from becoming home owners in developing countries. For example, majority of households in developing countries have large families, high price of building materials and low propensity to save inhibit home ownership in developing countries.
Research Question
Can middle income earners in Nigeria able to 1 finance homeownership by using 10-year personal savings amount to N2,400,00?
The study multiple linear regression as a major statistical technique to determine whether middle income earners are able to finance homeownership by using o N2,400,000 of their personal savings.
Two types of linear regressions are available they are multiple linear regression, and simple linear regression. A simple linear regression uses the singe independent variable to predict the dependent variables. In other words, simple linear regression assists in predicting the value of a dependent variable.
A multiple linear regression refers to two or more independent variables that are used to predict a dependent variable. The difference between the linear and multiple regressions there is only one dependent variables however, the independent variables are different in both cases.(Trochim, 2006). The proposal selects the multiple linear regression for the analysis because it is able to use multiple independent variables to analyze the dependent variable. (Sukal, 2013).
The statistical notations for this research are as follows:
Ho = null hypothesis.
H1 = alternative hypothesis.
= significance level.
= probability of Type II error.
x =sample mean.
s = standard deviation of a sample.
Research Hypotheses
H1: Middle income in developing countries are likely to purchase homes using their personal savings. The dependent variable is Income, while independent variables are Employment. Status, Age Range, Housing Size, and Rent.
Ho: Middle income in developing countries are not likely to purchase homes using their personal savings. The dependent variable is Income, while independent variables are Employment. Status, Age Range, Housing Size, and Rent.
2. Methods
The study collects data from respondents, who are middle income earners using the survey method. The quantitative technique is used for data collection and analysis, and the study uses the SSPS Version 19 for the analysis. The study collects data from both male and female participants, and the age of participants are between 21 and 60. The participants will be selected based on their ages, and income level. Participants below 21 years of age will be excluded from the survey and participants earning income below N60, 000 will be...
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