20 practical tips for data analysis to make various researches in Excel easier
1. Think of research as a way to find treasure
Analyzing the data is like finding a treasure. In other words, collecting data is like collecting treasure and gold. Although the research process can be tedious, you end up with good results.
For this reason, you should consider the research process as a golden opportunity and make the most of it.
2. Collect more data
First of all, you need to collect data for your research and then keep the collected data well so that you do not lose it. Remember, it’s the data that ultimately gives you valuable information.
3. Create more data
This may sound a little strange, but in some cases you can create valuable information for your research with the least facilities and cost. For example, if you are a manager of a company or organization, you can ask customers how they got to know your company or organization. By doing this, you will gain valuable information in the field of marketing.
4. Experiment and test regularly
Creating data through methods such as preliminary review and two-choice questions and answers can provide valuable information at a lower cost. For example, Timothy Ferris, author of the best-selling book “4 Hours a Week,” used click-through ads for his book to gauge his book’s accessibility on various sites.
5. Consider your statistical population and samples large
In the past, judgments and decisions based on a small statistical population were justifiable due to the lack of computers, but today you can easily consider a large statistical population and sample to bring your analysis closer to reality.
6. Do not forget to analyze the data
For some managers and business owners, having a data collection team can play an important role in data analysis, but it is best to have a strong data analysis team to get good results in your research.
7. Do not feel sorry for irrelevant data
This may sound a little strange, but it can sometimes be that while collecting data for your research, you spend your time collecting irrelevant and useless data. Do not forget that you can get valuable information even from irrelevant data.
8. Turn your data into an internal source of information
By turning data into an internal source of information, you can easily use it when needed. This also prevents data loss.
9. Provide a library for external data
In cases where your data is external, we suggest dedicating a portion of the library to that data. By doing this, you can sell that information to other companies and institutions in the future.
10. Protect your sources of information
Data and information resources are very valuable, so you need to protect them well. Data protection means safe storage of data.
11. In data analysis, first refer to the Descriptive menu
Before analyzing the data in SPSS software, you can get valuable and interpretable information about your data by referring to the Descriptive menu.
12. Prioritize your data
By prioritizing the data and eliminating unnecessary variables, the process of analyzing the data becomes easier.
13. Never analyze duplicate data
In general, it is rare for you to get into trouble while analyzing data, but remember to never analyze copied data.
14. Your hypotheses are based on theories, not emotions (or data).
This is very simple, do not waste your time analyzing false and baseless hypotheses.
15. Accept that your hypotheses may be unanswered
Sometimes at the end of statistical tests you may find that your research does not have a meaningful answer. This is very normal in statistical tests, so do not despair.
16. Before analyzing the data, check the correctness of the hypotheses
By doing so, you are actually saving time. If you do your research with wrong hypotheses, you may end up with irrational and unrealistic results.
17. Choose your analyzes carefully
To find the best answer to your research question, we recommend that you talk to a counselor or professor about it or read various articles about it to get the best analysis out of the research.
18. Do not forget that there is no such thing as a “bad result”
This may sound more like advice, but at the end of the research you may find that the result you thought was right turned out to be wrong. It is better to come to terms with this fact and not try to argue the wrong result correctly.
19. Use Syntax for duplicate analysis
Using this feature saves time and reduces the possibility of errors in the analysis.
20. Before statistical analysis, be sure to write correct, clear and concise hypotheses
Of course, if you know what you are (or are not) looking for in research, your job will be much easier. This will make your research purposeful and you will finally get acceptable results.
