There is no “mantra” to simplify statistics and data analysis for learning; however; statisticians at Statswork offer some keys to circumvent pitfalls and ensure smooth flow of your research work. Here are some top tips to ease your research phase.
First Review Descriptive Stats
Many folks do things the other way round; for example, they do complex analysis prior to analyzing the data. Most of the time, descriptive statistics provide pivotal background for advanced analysis thereby providing clarity of interpretation .
Second, Prune Data Before Analysis
Doing this helps you focus on analysis; you can manually delete unwanted variables after taking a backup or leverage the “Define Variable Sets” feature.
Third, Refrain Analyzing The Master File
Ensure you work on a copy of the data. Normally, things may not go wrong but better be safe than sorry. You never know what can happen; hence, backup your master copy of data.
Fourth, Anchor Hypothesis On Theory
Don’t explain statistical anomaly that isn’t supported by the literature. There might a random error.
Fifth, Seeking The Elusive “Significance”
Significance may elude your research; hence, dedicate some time pondering about what that might imply. Occasionally, intriguing stories arise from something that never happened.
Sixth, Verify Assumptions
Prior to data analysis, you must double check your assumptions; although tedious, verifying assumptions saves lots of time, because deviations from assumptions can lead you (astray) to explain invalid findings.
Seventh, Choose Analysis Wisely
Read, review, and talk your university help guide or discuss with a statistician ; pick the apt analysis to answer research questions. A time saver indeed.
Eighth, Bad Results? No Worries
There’s no such concept as bad results; allow the stats show your data’s results. You may have a tendency to rationalize results with your preconceived notions about the results. But allow the data results to do the talking and you will save a lot of time.
Ninth, Automate Repetitive Analysis
Use syntax for automation; save plethora of time and reduce probability of analysis errors manually.
And finally (tenth), the last point is to craft a clear, specific, and succinct hypothesis. Before start of analyses, write a clear hypothesis; simpler to test a theory if you know precisely what you expect and don’t expect.