The biggest mistake in research work is choosing the correct strategy. Can it be claimed that the choice of the statistical community is effective in choosing the strategy? For example, interviewing experts creates a document that we should use the content analysis strategy as a strategy, or interviewing the individuals themselves provides their personal experience in the form of a document that we are inevitably choosing phenomenological strategy.
Before choosing the correct strategy, I think that there is a need to collect information about the other successful strategies that are currently being applied in other communities. By this, there is no need to reinvent the wheel.
We should not forget that the working teams might need to be trained enough before making the change process.
For more information, please have a look at the following link:
https://www.health.ny.gov/statistics/chac/chstrategy.htm
Describing data in itself is not an analytical task. The task of describing data is to organize and compact the data. Descriptive statistics methods are directly dependent on the type of data we are dealing with. Previously, we have already subdivided our data into quantitative and qualitative ("Data types"), studied ways of describing them depending on the types of characteristics and types of distribution ("Descriptive statistics" and "Types of distributions"). For the variational series that have a normal distribution, we calculated certain parameters that can be used to describe the variational series. For a normal distribution, this is the mean and standard deviation. In the case of a distribution other than normal, the median and interquartile range are used, which could describe most of the data. For qualitative data, the description consists in finding frequencies, shares, proportions, representation in the form of absolute and relative values.
Regards, Sergey
choosing the correct strategy highly depends on statistical community since we are looking for quality.
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