After reviewing the five basic types of reliability on page 154 of the textbook, comment on each as it relates to your research.

Review the four different subtypes of measurement validity on page 155 of the textbook. Identify which subtypes you will include in your research and provide a rationale for each included.

SOC 480 Topic 7 Data Collection & Analysis Rubric GCU

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ADDITIONAL DETAILS

Data Collection & Analysis

Data is collected for all sorts of reasons. Sometimes it’s to track progress, to find trends, or simply to compare one thing against another. No matter the reason, data is a valuable tool that can give you insights you never would have thought of on your own. But collecting data is only half the battle. Once you have it, you need to know what to do with it. That’s where data analysis comes in. By understanding how to analyze data, you can glean valuable insights that can help you make better decisions in the future. In this blog post, we’ll explore the basics of data collection and analysis. You’ll learn about different methods of data collection and how to properly analyze your data to get the most out of it.

Defining the goals of the data collection process

The first step in any data collection process is to define the goals of the data collection. This step is important because it will help to determine the type of data that needs to be collected, as well as how the data should be collected.

There are a variety of different goals that can be achieved through data collection, such as:

-Understanding the current state of a system or process
-Identifying areas for improvement
-Measuring progress over time
-Comparing results against a baseline or target

Once the goals of the data collection process have been defined, the next step is to determine the type of data that needs to be collected. This will be based on the specific goals that have been set. For example, if the goal is to understand the current state of a system, then data on how the system is being used currently would need to be collected. On the other hand, if the goal is to identify areas for improvement, then data on how well the system is performing would need to be collected.

Determining the methods of data collection

There are a number of ways to collect data for analysis. The most common methods are surveys, interviews, focus groups, and observations.

Surveys are a great way to collect data from a large number of people quickly and efficiently. They can be administered in person, by mail, or online.

Interviews are another popular method of data collection. They provide a more in-depth look at a particular subject than surveys. interviews can be conducted over the phone, in person, or online.

Focus groups are small groups of people that discuss a particular topic in depth. They can be an excellent way to generate new ideas and gather feedback on a product or service.

Observations are another valuable method of data collection. By observing people in their natural environment, you can learn a lot about their behavior and preferences.

Executing the data collection process

The data collection process is the first step in conducting a data analysis. This process can be executed in a number of ways, but the most common method is to collect data from a sample of individuals or objects. This sample can be chosen randomly or selected purposefully, and it should be representative of the population of interest.

Once the data has been collected, it must be organized and cleaned before any analysis can take place. This includes checking for errors, outliers, and missing values. Once the data is ready, it can be entered into a statistical software program for analysis.

Analyzing the collected data

After the data has been collected, it is then time to analyze it. This can be done in a number of ways, but some common methods include statistical analysis, data mining, and business intelligence.

Statistical analysis is a process of using mathematical and statistical methods to help make decisions based on data. This type of analysis can be used to understand trends, predict future events, and test hypotheses.

Data mining is a process of extracting valuable information from large data sets. This information can be used to improve business decision making or for other purposes such as marketing or fraud detection.

Business intelligence is a process of turning data into actionable insights. This can be done through various means such as dashboards, reports, and analytics. Business intelligence can help organizations make better decisions by providing them with timely and relevant information.

Presenting the findings

Once the data has been collected, it’s time to start analyzing it. This is where you will start to see some patterns and trends emerge.

There are a few different ways to go about analyzing your data. You can do it manually, by looking at each piece of data and making note of any patterns or trends you see. Or, you can use a software program to help you analyze the data.

Whichever method you choose, make sure you take your time and really dig into the data. The more you know about your audience, the better equipped you’ll be to create content that resonates with them.

Conclusion

Data collection and analysis is a critical part of any research project. Without accurate data, it is impossible to draw valid conclusions. There are many different methods of data collection and analysis, so it is important to choose the one that best suits your needs. With careful planning and execution, you can ensure that your data collection and analysis will be successful.