Amanda Rosemary

QA/G-1 Developing quality systems for environmental standards

1. Summarize what quality systems is, purpose and scope and what the benefits are

Quality systems are a collection of business processes directed to meeting the customer requirements. Its purpose is to meet the tastes and preferences of customers for satisfaction. This is beneficial to the business as it allows for increasing its customer base and meeting the goals of an organization.

2. Summarize the specifications for EPA organizations and non-EPA organizations (summarize which codes)

EPA organizations are faced with the requirement of fulfilling the environmental compliance procedures so as to be considered as EPA compliant organizations. On the other hand, non-EPA organizations have the requirement of ensuring that they meet the set standards placed by EPA.

3. What are the elements of environmental data of the quality system standards?

The quality system standards elements of environmental data are precise, clear, reliable and timely in addressing the various environmental issues.

4. What are the phases of QS development and provide a brief summary of each

The development phases include seven important steps which include: system investigation which includes an identification of the appropriate system, system analysis involving an in-depth investigation its functionality, Design which determines the components of the system. Environments are the specifics application areas for the system; testing involves measuring the applicability of the QS, operation and maintenance involves continuous quality checks for the functionality of the QS and finally evaluation that determines the effectiveness of the QS.

5. What is the Shewhart cycle

This is a step by step management strategy involving four major steps for effective business control and management for continuous improvement of processes and products.

QA/G-3 Assessing quality systems

1. Summarize the purpose of AQS

Assessment of quality systems is conducted with the main purpose of ensuring that the various programs implemented under the funding of the U.S environmental protection agency meet the quality standards for operation.

QA/G-4 Systematic planning using the data quality objectives process

1. What is the purpose of the DQO process?

DQO process is designed to provide guidance on the systematic planning process that needs to be implemented based on some logical steps that allow for appropriate data collection of environmental information for managers and staff in an organization.

2. What are the elements of systematic planning?

The element of systematic planning are the strategic processes within an organization, and these include organization regarding human resources, project goal, schedule, data needs, data measuring criteria, data collection, quality assurance and data analysis.

3. Explain the seven steps of the DQO process

The DQO process steps include; formulation of the problem statement, identification of the goal of the study, identification of information inputs, the definition of the scope of study regarding the target information, analysis approach development, specification for performance criteria and establishing a plan for obtaining data.

4. Explain DQO iteration

This involves the repetition of reviewing the data objective process to ensure that it is in line with the set standards to meet the environmental data collection standards.

QA/G-5 Quality assurance project plans (QAPP)

1. What is QAPP and what is the purpose?

QAPP is a project modeling plan that provides the appropriate steps, procedures, and activities to be involved in a project. Its purpose is to guide the project personnel on the most appropriate steps for implementing the project to yield better results.

2. What is the difference between QAPP and quality management plans?

QAPP seeks to ensure that an appropriate plan for project implementation is rightfully put in place to bring about better results in the implementation process. On the other hand, quality management plans are focused on the plans that have been put in place to ensure that effectiveness is achieved.

3. What are the 24 elements of QAPP? Summarize each element

QA/G-5M QAPP for modeling

1. What does the QAPP for modeling document help you develop?

QAPP helps in the development of appropriate environmental data collection plan for various environmental projects. It provides a workable model for the implementation for an effective procedural and implementation steps for effective data collection.

2. Why is this document important?

The document is important in informing project managers and staff of the various data collection models that ensure quality data information is gathered for effective project implementation.

QA/G-5S choosing a sampling design for environmental data collection

1. Why is selecting a sampling plan important?

Having an effective sampling plan in environmental data collection allows for gathering the most appropriate and relevant information from the target group. This enables for meeting of the project goals and objectives.

2. What does sampling plan consist of?

A sampling plan consists of the steps that will be involved in the sampling procedure including the identification of the target population, determining the sample size, determination of the sampling design, review of the systematic planning outputs and documenting the sampling design in the quality assessment project plan.

3. Summarize the following sampling methods. Include when each would be appropriate to be used.

Judgmental sampling

Based on the condition under investigation and the professional judgment rather than the application of the scientific theory of the same. Used when the features of the subject under investigation are well understood.

Simple random sampling

Sampling units are selected randomly using random numbers. Used when the subject under investigation is straightforward.

Stratified sampling

The target population is separated into subpopulations that have more or less similar characteristics. Used when the population is heterogeneous.

Systematic and grid sampling

Done at a regularly spaced interval regarding distance or time after selecting the specific time or point of reference. Applied when there is need to estimate spatial patterns as well as trends over time.

Ranked set sampling

Sample method is incorporating professional judgment of a field investigator for picking samples in specific field points for higher probability of accuracy. It is applied when the area to be sampled is big, and there is need to cut down on the financial expenditure for the sampling procedure.

Adaptive cluster sampling

Combines the application of simple random sampling and the use of high-value samples in order to achieve a higher probability of accuracy. This is well applied when estimating rare characteristics in a population.

Composite sampling

Portions of sample materials from various sampling points are mixed to form a homogenous sample. Applied when there is need to estimate the population mean regarding a rare trait that exists among them.

QA/G-6 Preparing standards operating procedures (SOPs)

1. What are SOPs? Explain thoroughly do not just expand the acronym

The standard operating procedures are documented for the purpose of a routine implementation by an organization for the achievement of a successful quality system. This is achieved through effective job accomplishment by staff in an organization.

2. What are the benefits of using SOPs?

The application of SOPs in an organization ensures that the quality standards of service delivery in an organization are not compromised in any particular way. This is keenly followed by continually referring to the document.

3. What are the different types of SOPs?

There are two different types of SOPs depending on the purpose that they fulfill. These include technical SOPs and administrative SOPs.

QA/G-8 Data Verification and Data Validation

1. What is data validation?

Validation is the employment of critical mechanisms to evaluate the quality of the data used in the study through establishing its credibility.

2. What is data verification?

Verification is the process of checking the completeness, compliance, and correctness of the data being handled against the required standards.

3. What is data integrity?

Data integrity is a situation where all the stakeholders adhered to the set specification during the process of handling the data.

QA/G-9SDQA: Statistical Methods for Practitioners

1. By using DQA, what four questions can the user be able to answer

When using DQA, one can be in a position to answer questions pertaining the type of data, quality of the data collected, quantity and credibility of the environmental data collected.

2. What are the five steps included in the DQA

The five steps included in the DQA are the reviewing of the Data quality objectives and sampling design, conducting preliminary data review, selecting the statistical test, verifying the assumptions of the statistical test and drawing conclusions from the data.

3. Discuss measures of association

These are the methods used to measure the levels of coefficient amongst different variables through the observation of statistical strength.

4. Discuss Pearson’s correlation coefficient

This is a formula used to measure the strength of different variables and their relationships. The formula works in a way that finding the nature of a relationship between two variables requires the finding of the coefficient value between -1.00 and 1.00.

5. What other correlations are discussed in this document?

The other types discussed in the document are Spearman’s Rank Correlation Coefficient and Serial Correlation Coefficient.

6. Discuss the different graphical representation methods

The different graphs (Histogram and stem and leaf plots) are used to represent data as collected for easier interpretation where both numerical and alphabetical data are represented effectively.

7. Discuss Posting plots, Symbol plots and Bubble plots and Geographic information System (GIS) applications

Posting plot is used to indicate various errors in the data collected by pointing out the specific areas of concern. Symbol plot works in situations where Posting plot cannot handle a large amount of data thus including the use of a range of data instead of basing on individual data as it is the case in Posting plot. Bubble plot can handle the data in either way depending on the scenario presented. Geographic Information system is used in providing important information as far as the locations are concerned.

8. Briefly, discuss and compare probability distributions. I.e. when can we use them in environmental data analysis?

Probability distributions can be used when handling data that occur as a result of natural patterns for a normal distribution to occur. T-distribution deals with exact data while lognormal distribution handles skewed data thus having skewed shapes.

9. How do we select a statistical method?

The statistical method is selected based on the data user's objectives and the results obtained during the preliminary data review.

10. Discuss the different population size

Different population sizes are used to determine the nature of the outcomes during the data collection process where the mean, percentile and variance are calculated. The sample size determines the method used in calculating the parameters.

11. Discuss distributional assumptions

The assumption made during the distribution process is that the data presented for analysis is a normal data.

12. Discuss testing for trends

This the process of observing certain trends during the distribution process to understand the reason for different behaviors.

13. Discuss outliers

Outliers are extreme measurements that are either too large or too small as compared to the other measurements. They occur as a result of errors in the process of data collection and recording through the coding processes.

14. Discuss dispersion

Dispersion is an assumption made when testing the samples where data is spread across different factors.

15. Discuss Transformations

Transformations are the different types of functions used in calculating the variance in the data collected from the field and converting it to useful information.

16. Discuss Independence

Independence is where the data used are independent, and correlations are zero.

17. Values below detection limits

These are values that are not measurable according to the set standards. The results are not recorded for such values since they cannot be captured by the measuring instrument that has standard measurement units.