Data Analysis

Data Analysis

Describe the purpose of data analysis.

Data refers to assets of the variables in terms of quality and quantity (Lavrakas, 2008). Data analysis refers to a process that involves the application of the various statistical data in the organization, evaluation, and interpretation of the data. The organization of data for easy manipulation,  access to the information, is referred to as the data analysis.

Data analysis has several requirements.

1. Data establishment

The specific entity from which the data is being collected. Before the analysis of the data, there should be a source for the information that needs to be analyzed. The data variables need to get received in the manner that the analysis methodologies efficiently analyze the data.

2. Data collection

After the establishment of the data, the data needs to be collected. The selection that is to be employed varies with the type of information that is to be collected.  The various data collection methods that need to be used include; traffic cameras in the case of the road statistics, satellite light and, recording devices. Others include interviews, downloads from various online sources, among others.

3. Data processing

After the data has gets collected, the processing of the data then follows. The raw information that has been received needs to be processed to ensure that the analysis process s effective and easy to carry out. Some steps may be involved in the processing of the data. These steps may include placing the data in rows and columns for easy analysis. The tables, once they have been constructed either in spreadsheets or in any other statistical software, can then be analyzed using the various analysis methodologies.

4. Data cleaning

It is a step that is involved in the elimination of possible errors. That may have occurred during the collection of the data. For instance, during the selection of the data, that data may have been duplicated, or incomplete in some manner. This step, therefore, ensures that these errors are collected before the data can be analyzed. The collection of the mistakes may involve counter checking the records and, reduplicating any data that may have been mistakenly duplicated. Others include column segmentation, among other techniques that may serve eliminate the errors.

5. Data analysis

Once that data is clean, it can now be analyzed. The data may be explained in terms of descriptive statistics, for instance, average or median. The data may as well be disclosed through data visualization, for example, through graphical formats.

Purpose of data analysis

• Data analysis allows for the discovery of certain usage information.
• The analysis as well supports making of certain informed conclusions on the subject matter (Haining, 1993).
• The tool as well allows room for making various decisions.

purpoWhy do researchers need to interpret their results?

Data interpretation is the act of explaining or showing one’s understanding od a specific type of data. Data interpretation ensures that the data gets well understood. The person carrying out the research may know the content in the investigation but needs to make the rest who were not part of the study to understand the findings. Again, in the implementation of the research findings, the person carrying out the research has to ensure that the results get well recognized. It is for those who ought to implement the results to be in a position to do it.

What does hypothesis mean in research? Discuss the importance of interpretation in a

research.

A conditional statement of the interaction between two different variables gets referred to as a hypothesis. May also be related to like a specific prediction that is testable in any given experiment (Beri, 2008). In any given research, there is a need for a hypothesis whereby the hypothesis helps to predict the various challenges. That may be associated with the study and how the analysis could be effectively carried out. The explanation helps the person to research to determine how the research has to get carried out, the various steps to be followed, and those that ought to get skipped. The hypothesis, as well, is essential for the effective processing and analysis of the data that gets collected from the research.

Discuss the steps involved in hypothesis testing.

Step 1: Statement of the Null Hypothesis

This hypothesis states that there is no much difference between the two given variables. The researcher tries to disapprove of the theory. In statistical terms, the explanation may be said to be one that has the means being the same.

Step 2: Stating the alternative hypothesis

This hypothesis states that there is some similarity between the two variables. In statistics, the means of different variables are different, meaning that there are probabilities that of the hypothesis occurring.

Step3 Set alpha

Considering what might happen from the hypothesis, we may come up with the table below;

Step 4: Collection of the data

The data is then collected through the appropriate methodologies. The methods may be experimental or observational.

Step 5: Test statistic calculation

An F statistic is used for a particular treatment level means.

Step 6: construction of the acceptance/ the rejection regions

It involves the establishment of the critical value of F. The value can be obtained from the various statistical tables. The significant value refers to the minimum amount of the test