Quantitative data analysis is widely used in economics, sociology, marketing research and other branches of science ✅
Quantitative data are usually more reliable than qualitative data, and good analysis relies on good data. Quantitative data refers to numbers and statistics and is very useful for identifying patterns of behavior or underlying themes ✔️
This is more useful than qualitative research, which can be very uncertain depending on the methods used to collect it.
Quantitative data is littered with a numerical reflection of performance. It is possible to highlight percentages and statistics and analyze the results using graphs and charts.
📌 Most quantitative data are less prone to bias and can generate large amounts of #data. Quantitative data analysis usually begins with sample size and minimum / maximum values in addition to any preliminary tables that have been compiled.
Based on this, statisticians often create averages and calculate the deviation from the expected result - and this helps to determine if the hypotheses are correct 🔖
Variance is a very important part of data analysis, along with the averages mentioned above.
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