Statistical Techniques Of Hypothesis Testing †MyAssignmenthelp.com

Question: Discuss about the Statistical Techniques Of Hypothesis Testing. Answer: Introduction A two-bedroom apartment is to be rented in Sydney. The person has a preference of staying in two specific suburbs in Sydney. The suburbs are Newtown and Hurstville. The person wants to check the average rent that these two suburbs are offering for the two bedroom apartments. He also wants to find out which suburb is comparatively cheaper. To test these results, statistical techniques of hypothesis testing and estimation has been used. Analysis and Discussion From all the two bedroom apartments available in the two selected suburbs, Newtown and Hurstville, a sample of 50 apartments has been selected at random from each of the two suburbs. Their rents per week have been recorded. Thus, the dataset now has 100 observations, 50 from each of the selected suburbs. The population that the person is interested in is all the two bedroom apartments available in the two selected suburbs. From the samples selected, the estimate of the population will be calculated. Here, according to the preference of the person, the first suburb is Newtown and the second suburb is Hurstville. To test whether the average rent of the two bedroom apartments in Newtown is significantly higher than $450, the population of interest is considered as all the two bedroom apartments available for rent in Newtown. The null hypothesis (H01) and alternate hypothesis (HA1) for this test are given as, H01: The average rent is less than $450 per week HA1: The average rent is higher than or equal to $450 per week. To test the above stated hypothesis, one sample t-test technique has been used (Gregory et al., 2015). The test results (Table 2.1) show that the p-value (one tail) is less than the 95% level of significance (0.05). Thus, the null hypothesis is rejected. Hence, it can be said that the average rent of the suburb Newtown is not less than $450 per week. Now, in order to test the cheaper rent of apartments from the two selected households, Newtown and Hurstville, two-sample t-test has to be computed (Slezk et al., 2014). The null hypothesis (H02) and alternate hypothesis (HA2) for this test are given as, H02: The average rent per week of two suburbs are equal HA2: The average rent per week of Newtown is higher than Hurstville. The test results (Table 2.2) show that the p-value (one tail) is less than the 95% level of significance. Thus, the null hypothesis is rejected. Hence, it can be said that the average rent per week for two bedroom apartments in Newtown is significantly higher than the average rent per week for two bedroom apartments in Hurstville. Conclusion The person would thus be rejecting his first priority, which is Newtown if he wants a cheaper apartment in the suburbs. According to the analysis it is clear that Newtown is significantly in terms of weekly rent for 2 bedroom apartments. It has also been seen that the average rent of apartments per week in Newtown is higher than $450, which is probably higher than the weekly budget. Hence, the person has to rent an apartment in Hurstville though his first preference was Newtown. References Gregory, K. B., Carroll, R. J., Baladandayuthapani, V., Lahiri, S. N. (2015). A two-sample test for equality of means in high dimension.Journal of the American Statistical Association,110(510), 837-849. Slezk, P., Bokes, P., Nmer, P., Waczulkov, I. (2014). Microsoft Excel add-in for the statistical analysis of contingency tables.International Journal for Innovation Education and Research,2(5), 90-100.