...Sample Master Test Plan TEST PLAN IDENTIFIERRS-MTP01.3 REFERENCES None Identified. INTRODUCTION This is the Master Test Plan for the Reassigned Sales Re-write project. This plan will address only those items and elements that are related to the Reassigned Sales process, both directly and indirectly affected elements will be addressed. The primary focus of this plan is to ensure that the new Reassigned Sales application provides the same level of information and detail as the current system while allowing for improvements and increases in data acquisition and level of details available (granularity). The project will have three levels of testing, Unit, System/Integration and Acceptance. The details for each level are addressed in the approach section and will be further defined in the level specific plans. The estimated time line for this project is very aggressive (six (6) months), as such, any delays in the development process or in the installation and verification of the third party software could have significant effects on the test plan. The acceptance testing is expected to take one (1) month from the date of application delivery from system test and is to be done in parallel with the current application process. TEST ITEMS The following is a list, by version and release, of the items to be tested: A. EXTOL EDI package, Version 3.0 If a new release is available prior to roll-out it will not be used until after installation. It will be a separate upgrade/update...
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...interpretation of data. Sample characteristics One hundred three Fourth Year Nursing Students of Laguna College Batch 2010-2011, sixty July 2010 Nursing Licensure Examination passers and twenty Clinical Instructors and Administrators completed the questionnaires. Participant characteristics are shown in Figures 4.1, 4.2, 4.3, 4.4 and __________. [pic] Figure 4.1. Age Distribution of the 4th Year Laguna College Nursing Students According to Figure 4.1 the age distribution profile of 4th year nursing students of Laguna College batch 2010 -2011 with a total of 103 taken as population sample has 44% or 45 respondents of age 19 years old and below, 50% or 52 respondents from age 20-25 years old and 6% or 6 respondents from age 26 years old and above. [pic] Figure 4.2. Gender Distribution of the 4th Year Laguna College Nursing Students Figure 4.2 shows that out of the 103 fourth year nursing students taken as sample population, 73 respondents or 75% of the sample population are female and 30 respondents or 25% of the sample populations are male. [pic] Figure 4.3. Age Distribution of the July 2010 Nursing Licensure Examination passers According to Figure 4.3 the age distribution profile of the July 2010 Nursing Licensure Examination passers with a total of 60 respondents taken as population sample has 5% or 3 respondents of age 19 years old and below, 87% or 52 respondents...
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...Task ID WBS ID Task Name Work Est (days) Leveling Delay Predecessors Resource Name 1 1 Overall Project 0 edays 2 1.1 Project Management 0 edays 3 1.1.1 Manage Project 127 0 edays Chris Johnson (Project Manager) 4 1.2 System Requirements 0 edays 5 1.2.1 Gather Business Requirements 8 0 edays Ryan Neff (Functional Lead),Stacy Lyle (Functional Analyst) 6 1.2.2 Design Business Process Flows 4 0 edays 5 Ryan Neff (Functional Lead),Stacy Lyle (Functional Analyst) 7 1.2.3 Finalize Technical Requirements 6 0 edays Rick Burke (Infrastructure Lead) 8 1.2.4 Create Operational Requirements 15 0 edays 5,6 Ryan Neff (Functional Lead),Stacy Lyle (Functional Analyst),Rick Burke (Infrastructure Lead) 9 1.2.5 Identify Technical Infrastructure Needs 2 0 edays 7,8 Rick Burke (Infrastructure Lead) 10 1.3 Software Requirements 0 edays 11 1.3.1 Create Functional Requirements 0 edays 5,6,8 12 1.3.1.1 Capture Customer Profile 4 0 edays Ryan Neff (Functional Lead) 13 1.3.1.2 View and Search Product Catalog 6 5 edays Ryan Neff (Functional Lead) 14 1.3.1.3 Updating and Calculating Shopping Cart 3 0 edays 13 Ryan Neff (Functional Lead) 15 1.3.1.4 Taking Payments 6 6 edays Stacy Lyle (Functional Analyst) 16 1.3.1.5 Submit Order 4 0 edays 12,13,14,15 Ryan Neff (Functional Lead) 17 1.3.1.6 Check Order History & Order Status 3 0 edays 16 Ryan Neff (Functional Lead) 18 1.3.2 Create Data Requirements 3 0 edays 12,13 Stacy Lyle (Functional Analyst) 19 1.3.3 Create ERP Interface...
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...Sample Scheme of work (Level 2) Week Objectives No. 1 To introduce students to key skill requirements, evidence collation and portfolio building Content Introduction to IT Key Skills • Read through Chapter 1 • Distribute log books and explain • Show sample portfolio and discuss • Discuss opportunities for collecting different types of evidence Housekeeping – Windows • Use slides to explain basic principles • Work through activity in Chapter 2 • Complete sample test questions and discuss Word Processing • Use slides to explain basic principles • Work through activity in Chapter 3 • Complete sample test questions and discuss Spreadsheets • Use slides to explain facilities • Work through activity in Chapter 4 • Complete sample test questions and discuss Databases • Use slides to explain facilities • Work through activity in Chapter 5 • Complete sample test questions and discuss Research Techniques • Use slides to explain facilities • Work through activity in Chapter 6 • Complete sample test questions and discuss Health & Safety • Use slides to explain basic principles • Work through Chapter 7 • Complete sample test questions and discuss Legislation • Go through chapter 7 plus additional information on sample cases • Use slides to discuss: o Copyright o Data Protection Act o Computer Misuse Act • Complete sample test questions and discuss Sample test paper • Use sample paper in Appendix B or from the Payne-Gallway web site (to be marked by teacher/lecturer from answers provided on...
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...SAMPLE WORK BREAKDOWN STRUCTURES VARIOUS TYPES OF PROJECT Applications Development Project Sample WBS Management and support Provide project management Provide quality control Conduct meetings and reviews Materials and supplies Travel and living costs Miscellaneous costs Consulting fees and subcontractor costs Contingency Systems development Requirements specifications Conduct information-gathering sessions Prepare logical data model Prepare logical process model Physical design Prepare physical data model Prepare physical process model Online system Prepare detailed design Program and unit test Document Batch system Prepare detailed design Batch update facility Program and unit test Document Reporting system Program and unit test Document Integration Prepare integration plan System integration and test Integrate batch update and reporting system Conduct systems test on batch systems Integrate batch and online systems Conduct systems test on complete system Prepare user documentation Customer Conduct milestone reviews Review and approve deliverables Conduct user training Acceptance testing Page 1 Printed on: January 27, 2010 SAMPLE WORK BREAKDOWN STRUCTURES VARIOUS TYPES OF PROJECT Prepare acceptance tests Conduct acceptance tests Prepare revisions from acceptance tests Hand over to customer Implementation Prepare implementation plan Provide support for implementation Conduct post-implementation review Page 2 Printed on: January 27, 2010 SAMPLE WORK BREAKDOWN STRUCTURES...
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...Hypothesis Test for a Proportion This lesson explains how to conduct a hypothesis test of a proportion, when the following conditions are met: * The sampling method is simple random sampling. * Each sample point can result in just two possible outcomes. We call one of these outcomes a success and the other, a failure. * The sample includes at least 10 successes and 10 failures. (Some texts say that 5 successes and 5 failures are enough.) * The population size is at least 10 times as big as the sample size. This approach consists of four steps: (1) state the hypotheses, (2) formulate an analysis plan, (3) analyze sample data, and (4) interpret results. State the Hypotheses Every hypothesis test requires the analyst to state a null hypothesis and an alternative hypothesis. The hypotheses are stated in such a way that they are mutually exclusive. That is, if one is true, the other must be false; and vice versa. Formulate an Analysis Plan The analysis plan describes how to use sample data to accept or reject the null hypothesis. It should specify the following elements. * Significance level. Often, researchers choose significance levels equal to 0.01, 0.05, or 0.10; but any value between 0 and 1 can be used. * Test method. Use the one-sample z-test to determine whether the hypothesized population proportion differs significantly from the observed sample proportion. Analyze Sample Data Using sample data, find the test statistic and its associated P-Value...
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...SAMPLE WORK BREAKDOWN STRUCTURES VARIOUS TYPES OF PROJECT Page 1 Printed on: January 27, 2010 Applications Development Project Sample WBS Management and support Provide project management Provide quality control Conduct meetings and reviews Materials and supplies Travel and living costs Miscellaneous costs Consulting fees and subcontractor costs Contingency Systems development Requirements specifications Conduct information-gathering sessions Prepare logical data model Prepare logical process model Physical design Prepare physical data model Prepare physical process model Online system Prepare detailed design Program and unit test Document Batch system Prepare detailed design Batch update facility Program and unit test Document Reporting system Program and unit test Document Integration Prepare integration plan System integration and test Integrate batch update and reporting system Conduct systems test on batch systems Integrate batch and online systems Conduct systems test on complete system Prepare user documentation Customer Conduct milestone reviews Review and approve deliverables Conduct user training Acceptance testing SAMPLE WORK BREAKDOWN STRUCTURES VARIOUS TYPES OF PROJECT Page 2 Printed on: January 27, 2010 Prepare acceptance tests Conduct acceptance tests Prepare revisions from acceptance tests Hand over to customer Implementation Prepare implementation plan Provide support for implementation Conduct post-implementation...
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...Lecture 5 Audit of the Sales and Collection Cycle Summary of the Audit Process Phase 1 Plan and design an audit approach 1. Accept client and perform initial planning 2. Understand client’s business and industry 3. Assess client business risk 4. Perform preliminary analytical procedures 5. Set materiality & assess acceptable audit risk and inherent risk 6. Understand internal control and assess control risk 7. Gather information to assess fraud risk 8. Develop overall audit plan and audit program Phase 2 Perform tests of controls & substantive tests of transactions Plan to reduce assessed level of control risk? No Yes Phase 3 Perform analytical procedures and tests of details of balances 1. Perform analytical procedures 2. Perform tests 3. Perform additional tests of details of balances Phase 4 Complete the audit & issue an audit report 1. Perform tests for presentation & disclosure 2. Accumulate final evidence 3. Evaluate results 4. Issue Audit Report 5. Communicate with audit committee & management 1. Perform test of controls 2. Perform substantive tests of transactions 3. Assess likelihood of misstatements in financial statements Accounts in the Sales and Collection Cycle 14-3 Sales and Sales returns Transaction 4 Accounts Sales Accounts receivable Business Functions Processing customer orders Granting credit Shipping goods Billing customers and recording sales Documents & Records Customer order Sales order Customer or sales order Shipping...
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...They race over a part of the course several times. The sample times in minutes for the Prada were: 12.9, 12.5, 11.0, 13.3, 11.2, 11.4, 11.6, 12.3, 14.2, and 11.3. The sample times in minutes for the Oracle were: 14.1, 14.1, 14.2, 17.4, 15.8, 16.7, 16.1, 13.3, 13.4, 13.6, 10.8, and 19.0. For data analysis, the appropriate test is the t-Test: Two-Sample Assuming Unequal Variances. The next table shows the results of this independent t-test. At the .05 significance level, can we conclude that there is a difference in their mean times? Explain these results to a person who knows about the t test for a single sample but is unfamiliar with the t test for independent means. Hypothesis Test: Independent Groups (t-test, unequal variance) Prada Oracle 12.170 14.875 mean 1.056 2.208 std. dev. 10 12 n 16 df -2.7050 difference (Prada - Oracle) 0.7196 standard error of difference 0 hypothesized difference -3.76 t .0017 p-value (two-tailed) -4.2304 confidence interval 95.% lower -1.1796 confidence interval 95.% upper 1.5254 margin of error 2. The Willow Run Outlet Mall has two Haggar Outlet Stores, one located on Peach Street and the other on Plum Street. The two stores are laid out differently, but both store managers claim their layout maximizes the amounts customers will purchase on impulse. A sample of ten customers at the Peach Street store revealed...
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...different usages of the term ‘sample’ and ‘test material’. Sample is used for the part of a larger “lot”(e.g a consignment, batch, carton, container and load ) which is sent to the Laboratory for analysis. When the sample is received by the laboratory it becomes a “test material”(Codex Alimentarius, AOAC International & IUPAC) . The Laboratory is responsible for its “traceability” and for its “integrity”. Sampling & Analysis “QA is the sum of all the activities taken to ensure that the information generated by the Laboratory is correct ( Wilcox et al., 1978 )” It is important that Laboratory is involved in discussions on sampling plans and in determining the sample sizes. Confidence in the decision meets/fails to meet a specification is dependent both on (a) the effectiveness of the sampling plan in obtaining a sample which is representative of the lot (b) the quality of the analysis carried out on it. Quality Assurance Program “Without a defined Quality Assurance program all analytical result must be suspect. ( Harnly & Wolf 1984 ).” The identity and integrity of materials being handled by the Laboratory must be ensured throughout the time when they are under the control of the Laboratory, e.g. from sample receipt to data report and authorized disposal of surplus material. Analyses provide reliable values for the composition of representative samples of the food. The analytical data reported must reflect the composition of the received sample as a whole. The QA program...
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...voluntary changes in accounting procedures on earning is also used to test the implications of the theory. Reported changes in accounting procedures are available from two sources: the sample of depreciation switches used by Holthausen and changes reported by accounting trends and techniques. Accounting changes are collected from these sources for the sample companies. Procedure changes are decomposed according to the type of change. This table presents for the full sample 342 changes. There were 242 changes disclosed in the footnotes about changes on effect on earning , but the other 100 cases described the effect of the change as immaterial or not disclosed. These are coded to indicate whether the effect is positive or negative. We had 2 tests to certify the theory, the first one is contingency tests. The contingency tests are replicated using the effect of changes in accounting procedures on earnings available for bonuses as a proxy for discretionary accounting decisions. If the effect of the accounting change on this variable is positive, the change is classified as income-increasing. According to analysis, the results don't support the theory. However, there are several potential explanations of this findings: 1. It is more costly for managers to transfer earnings between periods by changing accounting procedures than by changing accruals, and 2. Changes in accounting procedures affect earnings and the bonus plan lower bound in the current and future years. However, the effect...
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...increase their compensation. The empirical results of these studies are conflicting. This paper analyzes the format of typical bonus contracts, providing a more complete characterization of their accounting incentive effects than earlier studies. The test results suggest that (1) accrual policies of managers are related to income-reporting incentives of their bonus contracts, and (2) changes in accounting procedures by managers are associated with adoption or modification of their bonus plan. 1. Introduction Earnings-based bonus schemes are a popular means of rewarding corporate executives. Fox (1980) reports that in 1980 ninety percent of the one thousand largest U.S. manufacturing corporations used a bonus plan based on accounting earnings to remunerate managers. This paper tests the association between managers' accrual and accounting procedure decisions and their incomereporting incentives under these plans. Earlier studies testing this relation postulate that executives rewarded by bonus schemes select income-increasing accounting procedures to maximize their bonus compensation. 1 Their empirical results are conflicting. These tests, however, have several problems. First, they ignore the earnings' definitions of the plans; earnings are often defined so that certain accounting decisions do not affect bonuses. For exam* I am indebted to Ross Watts for many valuable discussions and for his insightful remarks on this paper. I also wish to thank the remaining...
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...| |UNIVERSITI TUNKU ABDUL RAHMAN (UTAR) | | | | | |FACULTY OF BUSINESS AND FINANCE (FBF) | Teaching Plan | |Unit Code & |UBEQ1123 QUANTITATIVE TECHNIQUES II | | |Unit Title: | | | |Course of Study: |Bachelor of Commerce (Hons) Accounting | | | |Bachelor of Business Administration (Hons) | | | |Bachelor of Business Administration (Hons) Banking and Finance | | | |Bachelor of Business Administration (Hons) Entrepreneurship ...
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...alternative hypotheses in this scenario (4 pts): A new sales force bonus plan is developed in an attempt to increase sales. Null hypothesis: New bonus plan does not increase sales. Alternative hypothesis:--New bonus plan increases sales. 2. For this question refer to Case Problem 1 (Quality Associates Inc.) on page 410 of your text (30 pts) Sample 1 1) H0: μ = 12 Ha: μ ≠ 12 2) α = .01, but for two-tail test will = .005 3) Z = (x-bar – μ) / (σ/√n) 4) Z Critical value at .005 = 2.575 5) Z = (11.9587 – 12) / (.21/√30) = -1.077187 The observed value lies outside the rejection region, so we fail to reject H0. 6) P –value is between .2814 for a two-tailed test Sample 2 1) H0: μ = 12 Ha: μ ≠ 12 2) α = .01, but for two-tail test will = .005 3) Z = (x-bar – μ) / (σ/√n) 4) Z Critical value at .005 = 2.575 5) Z = (12.0287 – 12) / (.21/√30) = .74855 The observed value lies outside the rejection region, so we fail to reject H0. 6) P-value is 0.4541 for a two-tailed test Sample 3 1) H0: μ = 12 Ha: μ ≠ 12 2) α = .01, but for two-tail test will = .005 3) Z = (x-bar – μ) / (σ/√n) 4) Z Critical value at .005 = 2.575 5) Z = (11.889 – 12) / (.21/√30) = - 2.895 The observed value lies inside the rejection region, so we reject H0. 6) P-Value is .0038 for a two-tailed test Sample 4 1) H0: μ = 12 Ha: μ ≠ 12 2) α = .01, but for two-tail test will = .005 3) Z = (x-bar – μ) / (σ/√n) 4) Z Critical value at .005 = 2...
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...DQ1 Distinguish between a Z test and a t-test. Provide an example of each one that might be appropriate for your current or previous place of employment Similarities o A Z test and a t-test are each a type parametric tests. o Parametric tests are resultant data from the given ranges which have given the consumers to choose from intervals, such as 1-5. o Parametric tests such as the Z test and t test are used to “conclude if there is a statistical significance among the sample distribution average and a parameter (Cooper, D. & Schindler, P., 2011). o A Z test and a t-test could be opted as one sample test. One sample tests are opted when one sample is derived from a populace and a hypothesis “from the specified population” (Cooper, D. & Schindler, P., 2011), is tested o A Z test and a t-test could be used as a two sample test with each of its sample being independent. o The Z test and t tests are matching while the sampling size is more than 120. · Differences o The Z test and t test differ when the sample size is lower than 120. o The t test is suitable for minute sample sizes. o The Z test is suitable for huge or minute sample sizes. o A t test can be opted as a two sample test by pairing the samples. o A t test has more tail area, means most results that are lesser and greater than the central are rejected. It implies a t test would give a improved sample average since most results which diverge away from the mean...
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