Question

The weekly Hotel bi HB) per traveller for COVID-19 mandatory qua rantine accommodation and centres are in high demand in Accra due to the limited accommodation facilities for these persons. Government may withdraw from taking care of the costs as expert say that the COVID- 19 has come to stay with us similar to other diseases. For this reason, it has become imperative for travellers to carefully plan for their accommodation Information has been gathered to help travellers predict hotel bill based on the following elements: number of people in a hotel (AA) number of rooms in a hotel (AB), Hotel age (AC), number of bedy in a room (AD), Internet connection (AE). Availability of was hroom in a room (AF), Distance from hotel to airport (AG) and Traveller type (AH). The study primarily used primary data obtained from 84 travellers sampled for the process. Data was analysed using the correlation and regression analysis. The results from the correlation and regressions analysis are displayed in tables 1 and 2 respectively. Page 2 of 4 Table 1 : Correlation Analysis of Variables HB AA AB AC AD AE AF AG AH HB - AA .009 1 AB 351" -.069 - AC 411" .036 249" 1 WAD 398" .062 492" 634" 1 AE 374" .052 533" 566" 611" 1 AF ,021 .035 189 .141-161-293" AG .159 .047 .078 241 559" 329" 154 AH ..071 -643" -,004 -185 -083 203) .009 .140 Correlation is significant at the 0.05 level "Correlation is significant at the 0.01 level

the first photo is the beginning of the question and the next photo which begins with table 2: regression....., is the continuation of the question

Answer 1

Answer to the question:

A]. In this case, the weekly hotel bill (HB) per traveller is considered as dependent variable and the variables such as, number of people in hotel (AA), number of rooms in a hotel (AB), Hotel age (AC), number of beds in a room (AD), Internet Connection (AE), Availability of washroom in a room (AF), Distance from hotel to airport (AG) and Traveller type (AH) are considered as independent variables.

B]. In this study, the weekly hotel bill (HB) per traveller is considered as dependent variable; because, in the regression, the variable of weekly hotel bill (HB) is regressed on the other independent variables; which includes number of people in hotel (AA), number of rooms in a hotel (AB), Hotel age (AC), number of beds in a room (AD), Internet Connection (AE), Availability of washroom in a room (AF), Distance from hotel to airport (AG) and Traveller type (AH).

C]. Yes, this study represents a case study. It basically deals with the case of higher demand of hotel bills during COVID-19 in Accra.

D]. In the regression analysis of this study, the variable- Availability of washroom in a room (AF) is significant at 1% level of significance.

E]. From the correlation matrix, it is seen that the variables of number of rooms in a hotel (AB) and Availability of washroom in a room (AF) has the weakest negative correlation (-0.189) at 5 per cent level of significance.

F]. The fitness of this model is not so sound as the value of R² and adjusted R² is very low; which are 38 and 31.4 respectively.

G]. The value of R² in a regression model generally reflects how well the responsiveness of dependent variable is represented by the independent variables in a regression model. But it is observed that if we include more and more independent variables in a regression model, the value of R² tends to get higher and higher. But it definitely reduces the degree of freedom in a model. Therefore the measure of adjusted R² is introduced to address this issue. Adjusted R² also reflects the fitness of a model by taking into considerations the number of independent variables.

However, as the values of R² and adjusted R² of the model are very low (38 and 31.4); thus we cannot say that the model is fitted very well.

H] Use of multiple regressions will be more appropriate in this case as this technique will serve the objective of the study more appropriately. This is because; correlation analysis between any two variables simply measures the degree of relationship between them but not the cause and effect relationship. But with the use of regression analysis, we can trace the cause and effect relationship between the variables. As the travellers want to know the impacts of various factors on weekly hotel bill, thus the use regression will be more useful than the use of correlation analysis.

I]. A suitable title could be given as “High demand of weekly hotel bills and COVID-19: Evidence from Accra”

J]. As this study incorporates various variables in its analysis, hence, there would be more than one null and alternative hypotheses. The null hypotheses are mentioned below:

H₀₁: There exists no relation between HB and AA

H₀₂: There exists no relation between HB and AB

H₀₃: There exists no relation between HB and AC

H₀₄: There exists no relation between HB and AD

H₀₅: There exists no relation between HB and AE

H₀₆: There exists no relation between HB and AF

H₀₇: There exists no relation between HB and AG

H₀₈: There exists no relation between HB and AH

Similarly, the alternative hypotheses are mentioned as follows:

H_A1: There exist a relation between HB and AA

H_A2: There exist a relation between HB and AB

H_A3: There exist a relation between HB and AC

H_A4: There exist a relation between HB and AD

H_A5: There exist a relation between HB and AE

H_A6: There exist a relation between HB and AF

H_A7: There exist a relation between HB and AG

H_A8: There exist a relation between HB and AH

K]. The hypotheses are non-directional as they do not take into consideration the direction of relationship between the variables; that is who will affect whom?

L]. The regression result shows us that the null hypotheses H_01, H₀₂ and H₀₈ could not be rejected; or in other words, the variables AA, AB and AG has no significant relation with HB.

M]. On the basis of null and alternative hypotheses; we can conclude that the variables such as Hotel age (AC), number of beds in a room (AD), Internet Connection (AE), Availability of washroom in a room (AF) and Distance from hotel to airport (AG) has a significant relationship with the dependent variable of weekly hotel bill (HB). While, the variables such as number of people in hotel (AA), number of rooms in a hotel (AB) and Traveller type (AH) has no significant relationship with the variable of weekly hotel bill (HB).

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