Data Analyst

Data Analysis Tips

Since I created my facebook page, I have posted seven small tips that can help data analysis beginners. I decided to post all of them together in one post so they become more beneficial. Here are they:

Tip 1: Collect More Data

You should collect more data . . . and then be good about storing and saving the data you do collect. In order words, don’t sloppily discard or carelessly lose or foolishly throw away the data we already collect or have. That data could be priceless. And if it isn’t priceless today, who knows? It might be at some point in the future. Face it. The richer the data set, the better the chances some cool insight will jump out at you.

Tip 2: Create More Data

Work to create more data. Okay, that maybe sounds silly. But in some cases, useful data can be created very economically. Here’s a simple example: If you run a business, ask clients how they came to find you. You’ll great insights into your marketing efforts as a result. You probably have other interesting ways to create more data.

Tip 3: Define Your Questions

In your organizational or business data analysis, you must begin with the right question(s). Questions should be measurable, clear and concise. Design your questions to either qualify or disqualify potential solutions to your specific problem or opportunity.

Tip 4: Determine your Sample Size

When measuring a large data set or population, like a workforce, you don’t always need to collect information from every member of that population – a sample does the job just as well. The trick is to determine the right size for a sample to be accurate. Using proportion and standard deviation methods, you are able to accurately determine the right sample size you need to make your data collection statistically significant.

Tip 5: Form clear, specific, and concise hypothesis BEFORE analysis

It is much easier to test a theory if you know exactly what you expect to see happen (or not happen).

Tip 6: Learn about Data Measurement Levels

Before creating your survey (or questionnaire), you should understand the four levels of measurement. These levels determine how survey questions should be measured and what statistical analysis should be performed.

Tip 7: Learn Variable Types

If you know well the variables in your research or study, you will avoid wasting time and effort later in your data analysis process. You will also set up your data collection instrument easily and correctly so that data is collected correctly that will save you time of cleaning your data. It will also help you formulate your study questions and objectives.

In some cases, the researcher forgets to measure a key variable while collecting the data. After the data is collected, the missing variable cannot be obtained any more and in this case, the researcher will have to apply different statistical methods, which is not related to his/her study purpose.

Want more..?

Follow my facebook page, twitter, or linkedin to see daily tips and helpful insights about data analysis. Follow my blog to get all updates regarding this topic. I will appreciate your comments and inquiries about data analysis and statistics. More helpful posts are coming.

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