ANALYTICAL CONSULTING

Analytical Consulting

Executive Summary

The purpose of this paper is to construct a consultancy report for Central Government Finance Department on the basis of which the department will allocate the budget among 4 regions as per their needs. According to the analysis of the case, it can be interpreted that authorities concerned with each regions are striving for optimal share of the budget. Therefore, Central Government Finance Department requires consultancy services on the basis of which the budget will be allocated among the regions. In order to assist Central Government Finance Department diverse statistical tests were applied on the data representing sample of 72 districts. On the basis of this data conclusion was to be drawn for allocating budget among 4 regions.

The first part of the report includes analysis of the data; nonetheless, the second part of the report provides consultancy recommendations to Central Government Finance Department. According to the analysis of data representing sample of 72 districts, it can is recommended that Central Government Finance Department must allocate budget among regions equally as they require similar proportion of the budget. Nonetheless, it can be asserted that the methodology used in the analysis was adequate to assist data advocacy. Hence, Central Government Finance Department must distribute the budget equally as it would be an optimal decision.

Analytical Consulting

The Analytical Report

Correlation Analysis

Correlation between Day Care Calls and Population

According to the statistical analysis of the data gathered from the sample, it can be interpreted that there is significant correlation between day care calls per day and population of the districts as the sig represented by the analysis is less than 0.05 (0.000).

Correlations

Total Population

Day care Calls Per Day

Total Population

Pearson Correlation

1

.983**

Sig. (2-tailed)

.000

N

72

72

Day care Calls Per Day

Pearson Correlation

.983**

1

Sig. (2-tailed)

.000

N

72

72

**. Correlation is significant at the 0.01 level (2-tailed).

Correlation between Day Care Calls and Elderly Population

According to the statistical analysis of the data gathered from the sample, it can be interpreted that there is significant correlation between day care calls per day and elderly population of the districts as the sig represented by the analysis is less than 0.05 (0.000).

Correlations

Day Care Calls Per Day

Elderly Population

Day care Calls Per Day

Pearson Correlation

1

.993**

Sig. (2-tailed)

.000

N

72

72

Elderly Population

Pearson Correlation

.993**

1

Sig. (2-tailed)

.000

N

72

72

**. Correlation is significant at the 0.01 level (2-tailed).

Correlation between Day Care Calls and Client Need Index

According to the statistical analysis of the data gathered from the sample, it can be interpreted that there is significant correlation between day care calls per day and client need index of the districts as the sig represented by the analysis is less than 0.05 (0.000).

Correlations

Day care Calls Per Day

Potential Client Need Index

Day care Calls Per Day

Pearson Correlation

1

1.000**

Sig. (2-tailed)

.000

N

72

72

Potential Client Need Index

Pearson Correlation

1.000**

1

Sig. (2-tailed)

.000

N

72

72

**. Correlation is significant at the 0.01 level (2-tailed).

Correlation between Day Care Calls and Population Concentration Index

According to the statistical analysis of the data gathered from the sample, it can be interpreted that there is significant correlation between day care calls per day and population concentration index of the districts as the sig represented by the analysis is less than ...