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The Housing Market in the UK - Research Paper Example

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The report “The Housing Market in the UK” gives a detailed statistical description of different types of houses that are sold in the UK. There four types of houses that one can buy in the UK. These are flat, terraced, detached and semi-detached…
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The Housing Market in the UK
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The Housing Market in the UK Introduction The report gives a detailed statistical description of different types of houses that are sold in the UK. There four types of houses that one can buy in the UK. These are flat, terraced, detached and semi detached. All these types of house have various numbers of rooms. Statistical analysis shows that the size of most houses is determined by the number of bedrooms therein. There are other factors which determine the price house houses. These include the proximity to the key infrastructure such as railway. Considering the fact that most people, who works in the cities, travel by train, it is very crucial for them to reside in places where the railway line passes near. The primary aim of my analysis is to determine if the size of the house the only factor that determines the prices? In other words, I am analyzing how the dependent variable is affected by the independent variable. My investigation is in B9. In my study, the dependent variable is number of bedroom while the independent variable is the price. The data that I use in this report are first hand data that I collected in the field. I visited over 100 houses of different types located in different places in the UK. My study covered different places in the UK. These include, west London, hull city, North London and Westham Though I didn’t find the prices of some houses, I was able to find them on the agents' websites. The agents post the photographs and information about the houses on their websites for the potential buyers from different places to see them. I also visited the agent’s offices to find out some information which was not available in the internet. I u obtain questionnaires to obtain information from all the respondents that I met. Analysis New homes have become more popular in the present age than ever. Developers have made efforts to create new homes that are boast fabulous designs , energy saving and with excellent building qualities. Thousands of houses are now on sale by these new home owners in the UK. A study has hence been carried out to obtain the general view of the housing market focusing on the housing prices, type and size of house for sale. The collected data is analyzed using different SPSS. The statistical aspects that the analysis look into include mean, media, skewness, price kurtosis, variance and standard deviation of the collected information. The sample data of my collected information is tabulated below: Type of house Number of bedrooms Price in million Euros Flat 4 30.0 Detached 4 17.6 Detached 4 15.7 Semi detached 4 7.7 Detached 4 12.6 Terrace 4 10.7 Detached 4 6.6 detached 4 10.7 People or companies that own houses advertise them in the UK’s number one property website to ensure that their potential clients get to see them more and they are able to receive millions of visits a month from active buyers. There are different types of houses in the UK; they include flats, terraced, detached, and semi detached. Prices of different houses depend on the type, the location and the sizes of houses for sale. The first analysis that I carried out was the relationship between number of bedrooms and the prices of the houses. From the sample,I found out that the prices of houses are directly proportional to the number of bedrooms. For example, a 4 bedroom semi detached house cost 3.5 million Euros, 3 bedroom cost 2.6 million Euros (Churchill & Iacobucci, 2009). While a 2 bedroom house of the same type goes for 1 million. The graph below shows the cost of different types of 4 bedroom house in west London. The prices are in million Euros. To make the information collected more clear, a histogram is also drawn. If less than two thirds of the questions are answered, then the questionnaire will be discarded since it can’t provide accurate information that is substantial for the analysis. I assumed that every variable in each set of the population is independent so that I get a correlation coefficient. The reference point of checking the skewness and kurtosis is 96% confidence interval. The calculation of the correlation matrix is only done if the data collected is free of errors. This will also give way for doing hypothesis test. The analysis will proceed if the correlation reveals that the variable correlates. The next analysis to carry out is regression. This is also conducted after the data is checked and errors eliminated. First, the dominant form of correlation is specified. This is followed by checking the data to ensure that there are no errors that accrue. Both the residual and predicted values are then plotted on a scatter diagram. Any violation found will lead to the transformation of the data to produce a relationship that is linear. Levene’s test is also used to to check similarity of the variance. A levene’s test is a situation whereby the values used are evaluated to check consistency of the variance. Any error found will lead to application of regression analysis. Another assumption is an evaluation of the error normalcy. In this can see the 95% intervals of kurtosis and skewness and QQ-plot is implemented. Graphical representation of the house information at B91 I also conducted a study on the relationship between the price of the house and the distance from the transport infrastructure such as railway line. The sample of by finding is shown in the table below Distance from the railway line Number of bedroom Price in a million Euros 50 m 2 3.0 100m 2 2 200m 2 1.5 300m 2 1.1 400 m 2 0.7 450 m 2 0.5 A scatter diagram representation of the relationship between the distance from the railway line and the price of the houses is show below. Discussion & Limitation The exercise wad tedious and I encountered many difficulties. For example, some houses that I visited were being sold by the agents. There was nobody around and when I tried to contact them, they were unwilling to give us substantial information about the houses. For example, the houses were locked and therefore I could not get the opportunity to assess the interior design of the houses. Other issues arise when it comes to calculating the values of houses that have stayed for a long time. I was not able to determine the price that it would have gone for if they were new. In addition, the houses that were sold by the agents were relatively more expensive compared to those sold by the owners. This became a big challenge when determining the exact value of the house. On the relationship between the prices of the houses and the distance from the transport infrustucture, particularly the railway line, the analysis shown by the scatter diagram shows that the prices is also determined by the distance from the railway. As you move away from the railway line, the price becomes cheaper (Cleland 2006). Summary From the analysis of the data that I collected, it was very evident that people would prefer flat houses. As such, the prices are relatively high compared to other types of houses. This information was captured after critical analysis the information using regression and correlation. The method facilitated collection of information that could give relevant analysis. Since the methods used to collect the information were different, the time spend in collecting information ws reduced. This gave more time for analyzing the data collected. In some circumstances, the respondents were willing to give detailed information about the houses which made the whole process simple. References Bradley, N., 2007. Marketing research: Tools & Techniques. Oxford University Press. Churchill, G., & Iacobucci, D., 2009. Marketing research: Methodological foundations. Cengage Learning. Cleland, D. I., and Ireland, L. R., 2006. Project management: strategic design and implementation. USA: McGraw-Hill Professional. Read More
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