Accommodation Report On Australian Cities - Myassignmenthelp.Com

Question: Discuss about theAccommodation Report On Australian Cities. Answer: INTRODUCTION This survey report is focused on giving information after an analysis about rent in different parts of Australia. This information is helpful to international travellers and more so international students who seek education in various cities in Australia. It forms a basis of decision making when it comes to choosing the type of accommodation that is suitable for any particular individual. This research depended entirely on secondary data as it did not collect its own information. The data was sourced from department of finance services and innovation of Australia. The data had both numerical variables and nominal variables. Some of the numerical variables were bond amount in dollars and weekly rent in dollars. The sample obtained for this report was not biased but large enough to representative the entire population. The sample size was 400. INTERNATIONAL STUDENTSWEEKLYRENT Descriptive summary of students weekly rent descriptive statistics for weekly rent Mean 18197.98992 Standard Error 17785.78627 Median 395 Mode 0 Standard Deviation 354379.2809 Sample Variance 1.25585E+11 Kurtosis 396.9994654 Skewness 19.92483878 Range 7061367 Minimum 0 Maximum 7061367 Sum 7224602 Count 397 Table 1 As can be observed from the table above, the mean weekly rent in dollars is 18197.99. The maximum rent charged weekly in dollars is 7,061,367 Distribution The data set is skewed to the right so much. This is because it has a skewness value of 19.92. It can also be seen that the distribution is highly kurtic. This means that it has a very sharp apex on its curve. This could be due to having very extreme high values like outliers which then affect the measures of central tendencies of the data such as mean, mode and median. To check for the presence of outliers, a scatter plot of the data was generated and is as below. Figure 1 As can be observed from figure 1 above, there is an extremely large value in the data set. This value is 7,061,367 dollars. This value makes the measures of central tendencies such as the mean not to depict the real picture of the data since they are adversely affected by this extreme value. Therefore the mean rent could be much lower than what is given in the descriptive table. To get the real mean rent that can be used as a basis of making decision for students who want accommodation, then this extreme value is omitted. Rental dwelling type Summary table and graph for rental dwelling type Row Labels Count of Premises wellingType 1 F 123 H 132 NULL 106 O 7 T 31 Grand Total 400 Table 2 The table above shows the number of different types of accommodation spread in Australia cities. It can be observed that most of them are houses (H). They are 132 in number followed by flats (F) which are 123 out of 400. The least number of residential were of type T which was 31 in number. These numbers could be informed by the interest by the demand of those types of residential. Figure 2 The graph above is a pictorial view of the distribution of various residential in Australia. It is just to complement the table above. Hypothesis for proportion of house dwelling type. Hypothesis H0: The proportion of house dwelling type is less than 10%. Versus H1: The proportion of house dwelling type is not less than 10%. From the established proportion above, it can be seen that the proportion of house dwelling type is 33%. We are therefore guided to reject the null hypothesis and accept the alternative that the proportion of house dwelling type is not less than 10%. Relationship between dwelling place and suburb Count of Premises_Suburb Column Labels Row Labels AUBURN PARRAMATTA RANDWICK SIDNEY Grand Total 1 1 F 33 12 34 44 123 H 32 18 35 47 132 NULL 28 20 21 37 106 O 1 2 2 2 7 T 12 3 8 8 31 Grand Total 107 55 100 138 400 Table 3 Figure 3 The table and graph above show the distribution of various types of houses spread in various cities in Australia. It can be observed that most of them were found to be in the city of Sidney (138). This is followed by the number of residential in Auburn. The city that had the least number of accommodations was Parramatta. This could be due to the fact that the houses were expensive though further research is needed to establish the same. Suggestions I would suggest to anyone who want to rent a house instead of a flat to rent in the city of Sidney. This is because there are more houses there compared to the other cities. This could be explained by reasons such as presence of cheap houses and security. 2-bedroom rent analysis Average weekly rent for 2-bedrooms across the suburbs SUBURB AVERAGE WEEKLY RENT AUBURN $365 PARRAMATTA $410 RANDWICK $370 SIDNEY $362 Table 4 Graphical representation of average weekly rent in the four suburbs Figure 4 The table and graph above show the average weekly rent for various accommodation across the cities in Australia. It can be observed that the highest mean accommodation was being charged in Parramata (410 dollars) while the least was being charged in Auburn (365 dollars). Hypothesis test for difference in weekly rent for 2-bedrooms across the four suburbs Since the variables are more than two, an ANOVA test is employed instead of t-test to test for the difference in the means. Hypothesis H0: There is no difference in weekly rent for 2-bedrooms in the 4 suburbs Versus H1: There is a significant difference in the weekly rent for 2-bedrooms in the 4 suburbs At 5% level of significance Anova: Single Factor SUMMARY Groups Count Sum Average Variance AUBURN 31 11325 365.3226 31671.56 PARRAMATTA 16 6560 410 16856.67 RANDWICK 30 11090 369.6667 24165.4 SIDNEY 46 16655 362.0652 13228.42 ANOVA Source of Variation SS df MS F P-value F crit Between Groups 29060.68 3 9686.894 0.461267 0.70986 2.680811 Within Groups 2499072 119 21000.61 Total 2528133 122 Table 5 From the analysis of variance results in the table above, it can be observed that the p-value (.71) is greater than the confidence level. We are guided therefore to reject the alternative and accept the null hypothesis. The conclusion is that there is no significant difference in weekly rent for the 2-bedroom houses across the 4 suburbs. Suggestion on renting in the 4 suburbs Any new student can be advised to rent accommodation in the city of Sidney since it appears cheaper there compared to the rates in the other three cities. This is confirmed by the averages calculated in table 4. Relationship and correlation weekly rent and bond amount Test for relationship between weekly rent and bond amount. Figure 4 Test for correlation between bond amount and weekly rent Bond Amount Premises Weekly Rent Bond Amount 1 Premises Weekly Rent 0.05942873 1 Table 6 The correlation test above between bond amount and weekly rent shows that there is insignificant relationship between the two variables. This is explained by the correlation coefficient which is .06. This could mean that the two variables are independent of each other. Conclusion From the analyses above, it can be concluded that weekly accommodation rates are almost the same in all the four cities in Australia. This is so since there was no wide variance among them. An analysis of variance performed on the rates of 2-bedrooms also suggested that there is no significant difference in the rates of the same 2-bedrooms across the four cities in Australia. The research has also informed that bond amounts and weekly rents do not affect each other and that they are independent.