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Bipartisan Agenda For Change Case Study Part Ii

1479 words - 6 pages

MANAGERIAL REPORT
Part II
“New York Reforms”

MBA Advanced Statistics
Fall 2014

Table of contents

Introduction. Given data ………………………………………………………………………………… 3
With regard to question 1, test for the independence of the response (yes and no) and party affiliation. Use α = 0.05 ………………………………………………………………..…………………….....….. 4
With regard to question 2, test for the independence of the response (yes and no) and party affiliation. Use α = 0.05 …………………………………………………………………………………..……...… 6
With regard to question 3, test for the independence of the response (yes and no) and party affiliation. Use α = 0.05 …………………………………………………………………………………..……..…. 8
Does it appear a broad support for ...view middle of the document...

 
We were asked to prepare a managerial report, based on the part I of our study, which would outline the following:
1) With regard to question 1, test for the independence of the response (yes and no) and party affiliation. Use α = 0.05.
2) With regard to question 2, test for the independence of the response (yes and no) and party affiliation. Use α = 0.05.
3) With regard to question 3, test for the independence of the response (yes and no) and party affiliation. Use α = 0.05.
4) Does it appear a broad support for change across all political lines?
5) Do these results support your assumptions made in Part I of the project?

To perform the second part of this study, we decided to use a Chi-Squared Test. The reasons are:
1. The sampling method is simple random sampling.
2. Each population is at least 10 times as large as its respective sample.
3. The variables under study are each categorical.
4. If sample data are displayed in a contingency table, the expected frequency count for each cell of the table is at least 5.
Since all these conditions are satisfied, it is possible use this test for our analysis.
Should legislative pay be cut for every day the state budget is late?
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Observed Values Table | | | | |
Pay Cut? | Yes | No | Total | |
Democrats | 22 | 14 | 36 | |
Independent | 10 | 9 | 19 | |
Republical | 39 | 6 | 45 | |
Total | 71 | 29 | 100 | |

Contingency table | (What would the situation look like if the variables were really independent) |
Pay Cut? | Yes | No | Total | | |
Democrats | 25,56 | 10,44 | 36 | | | |
Independent | 13,49 | 5,51 | 19 | | | |
Republical | 31,95 | 13,05 | 45 | | | |
Total | 71 | 29 | 100 | | | |

The solution to this problem is the following:
1. H0: The responses to the question about "Pay Cut" are independent of political party affiliation.
Ha: The responses to the question about "Pay Cut" depend on party affiliation.
2. For this analysis, the significance level is 0.05. Using sample data, we will conduct a chi-square test for independence.
3. Applying the chi-square test for independence to sample data, we compute the degrees of freedom, the expected frequency counts, and the chi-square test statistic. Based on the chi-square statistic and the degrees of freedom, we determine the P-value.
Rejection Rule: if the P-Value<=Alpha, Reject H0; if Chi-value> than critical value, reject H0.

Pearson's chi-squared test |
Alpha | 0,05 | | |
Degrees of Freedom | 2 | | |
Critical Value | 5,991464547 | | |
P-Value | 0,006135029 | | |
Test Statistics | 10,18748101 | | |
Conclusion: | Reject | |

We reject the assumption that the responses to the question about "Pay Cut" are independent of party affiliation at 5% level of significance....

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