Introduction:
The main purpose of the report is to statistically analyse the secondary data of the Australian Tourism Industry. For the simplicity of the analysis, the report collets data from five cities which are Adelaide, Brisbane, Gold Cost, Melbourne and Sydney. After collecting 350 data, the study selects 250 responses as sample by applying simple random sampling technique. The study also considers 16 variables including customer ID, gender, age of customers, location of hotels, room type and so on. The following section discusses the outcome of data analysis based on which further discussion on finding and recommendations are conducted.
Question 1:
The sample data of the study consists of 250 samples where, ID numbers of customers are arranged in ascending order. The following table represents the summary of 16 variables under the heading of variable name, variable description and variable type as given in Appendix A.
Table 1:- Data List
Question 2
The variable is divided based on whether the quantitative variable is discrete, categorical or continuous in nature or not. When a quantitative variable takes values of specific points on a scale, it is called a discrete variable. On the contrary, if a quantitative variable takes any value within a certain range then it is called a continuous variable.
Table 2: Summary of each variable
Here in the sample data, the qualitative variables are constituted to be categorical variable type whereas quantitative variables are divided between discrete and continuous variables because categorical data cannot be analysed using summary statistics. Categorical variables are given values for analysis to be done further.
Question 3a
The following table represents the outcome of descriptive statistical analysis for the variable “Employee Average Annual Salary” in order to determine mean, median, mode and range. The output table is as below:
Table 3: Descriptive Analysis
The above table shows that the annual salary of employees on an average is $ 100000.748 per year. Standard deviation is 22481.074, which is quite high and shows large variation from mean. The data is negatively skewed as median is higher than mean. From the above analysis, it is observed that the annual salary of employees of hotels deviate significantly.
Question 4a
The following figure 1 of histogram represents a histogram of the variable “Customer Annual Income per Year” for showing the distribution. The histogram in figure 1 shows the positive skewness in the data
Figure 1: Histogram
Question 4b
The following diagram in figure 2 represents the histogram of “Employee Average Annual Salary ($/Year)”. The histogram shows negatively skewed data as median > mean.
Figure 2: Histogram
From histograms, it is observed that customer annual income per year is positively skewed that means mean value is higher than median and mode.
Question 5a and 5b
The following table represents standard deviation and skewness of average annual salary of hotel employees based on different hotel locations.
Table 4: Standard Deviation and Variation of Average Annual Salary of Employees in Adelaide
In normal distribution, the value of mean, median and mode become equal with each other. However, from table 4 it is seen that median is higher than mean while mode is unknown. Hence, the distribution is not normal rather it has negatively skewed.
Table 5 : Standard Deviation and Variation of Average Annual Salary of Employees in Brisbane
From table 5 it is also observed that median is higher than mean while mode is unknown. Hence, the distribution is negatively skewed.
Table 6: Standard Deviation and Variation of Average Annual Salary of Employees in Gold Coast
From table 6 also depicts the same picture. Here, it is also observed that median is higher than mean and mode is unknown. Hence, the distribution is negatively skewed.
Table 7: Standard Deviation and Variation of Average Annual Salary of Employees in Melbourne
Table 7 also represents that median is higher than mean and mode is unknown. Hence, the distribution is negatively skewed.
Table 8: Standard Deviation and Variation of Average Annual Salary of Employees in Sydney
Table 8, moreover, represents that median is higher than mean and mode is unknown. Hence, the distribution is negatively skewed. As per the analysis the minimum standard deviation is shown in Adelaide depicting that the deviation from the annual income is less as compared to all other hotel locations.
It implies that most of the income of customers is low while average income of employees is high. From standard deviation and variation of employees’ average annual salary it can be observed that the salary of employees in 5 cities is more or less same. However, the salary deviates heavily for different hotels.
Question 6a
The following table represents the summary table for Employee Work Load Satisfaction based on three indicators, which are hotel type, hotel location and room type.
Table 9: Single Summary output for Employee Work Load Satisfaction data
The table 9 shows that maximum 3 and 4 star hotels are preferred and the mainly Melbourne, Brisbane and Sydney refers to 3 star hotel whereas Adelaide and Gold Coast shows more 4 star hotels. However, the least number of hotels are of one star irrespective of the hotel location. Also, medium room type is preferred more across all hotel locations.
Question 6b
The following table represents the summary table for Customer Annual Income per Year according Hotel Type, Hotel Location.
Table 10: Single Summary output for Customer Annual Income per Year data
The table 10 shows that maximum 5 star hotels are preferred as per customer annual income and mainly in Sydney and Brisbane. Followed by 4 star hotel with maximum current annual per year income in Adelaide and Melbourne. However, the least number of hotels as per customer annual income are of one star irrespective of the hotel location.
Question 7a and 7b
hypothesis testing by applying t-test for pared two sample for means to observe whether the average cost for low season room per night has any difference with high season room cost per night or not.
Hence, the null hypothesis is:
H0: the average cost for low season room per night has no difference with high season room cost per night
The alternative hypothesis (H1): the average cost for low season room per night has difference with high season room cost per night
The obtained output table is as follow:
Table 11: Hypothesis Testing
Here, the mean difference is considered as 0 and the test is conducted at 95% confidence interval. From the analysis it is observed that the t state is 25.21 which is higher than critical value. Hence, the null hypothesis is rejected.
Moreover, the satisfaction level does not differ much. The analysis also shows that the average cost of room for low season and high season are not same.
Recommendations:
After the analysis, it can be recommended that hotel cost need to reduce as the average annual income of customers is low. Moreover, hotels can charge almost same price for rooms in different seasons to maintain a normal profit margin.
Conclusion:
The report discusses the tourism industry in Australia considering hotels in 5 cities. The study takes 250 hotels as sample for analysing statistical analysis. The report measures descriptive statistics, histogram and t-test for different variables. From the analysis, it is observed that average income of employees is around $100000.748. Moreover, the salary of employees deviates significantly. Average income of customers is low compared to that of employees. The average salary of hotels is more or less same for 5 cities.
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