Descriptive and Inferential Statistics

2333 Words Jan 15th, 2018 9 Pages
Statistical analysis can also involve much time and effort, and therefore an understanding of the proper structure of descriptive and inferential statistics is crucial before expensive investments of time and resources are wasted because data is not collected using proper methods. Many surveys are reported every day in business, government and the media that are questionable because data was not collected and analyzed accurately. For the most robust inferential results, random data must be gathered, there must be enough sample points relative to the size of the population the sample is claimed to infer characteristics about, and the most robust inferences are made by applying a 'test' condition to one or more groups compared to an untested group that did not get the treatment, to see how likely the condition of interest would appear in a control group by chance. If the population is small enough or there are enough resources to survey them all, that is optimal and therefore no inferential statistics need be performed because descriptive statistics include all group members and therefore accuracy is 100% or very high, but this is often not possible There are many statistical techniques that can handle non-normal or random data, but if the consequences carry high risk of say loss of life, or irreversible damage, then the best effort is required to ensure the highest accuracy.…
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