What is probabilistic equivalence why is it important

The success of every organization depends on attracting and retaining customers. Although the marketing concepts for doing so are well established, digital technology has empowered customers, while producing massive amounts of data, revolutionizing the processes through which organizations attract and retain customers. In this course, students will learn how to identify new opportunities to create value for empowered consumers, develop strategies that yield an advantage over rivals, and develop the data science skills to lead more effectively, allocate resources, and to confront this very challenging environment with confidence.

Advertising, Data Analysis, Analytics, Marketing. I really enjoyed this class. I found it challenging to my current thinking and several of the scenarios were very similar to things that I am facing in my actual business today. Well done! The first half was interesting, but the second one was very dry. The second half contained more statistical related content, but it was not presented in an engaging manner.

Get started with a Working Knowledge of Data Science by learning a simple framework that will help you catch a large fraction of the bad analytics you encounter on a regular basis. Nancy L. The control group is a useful way of eliminating extraneous variables and reducing noise. Experiments that apply some kind of treatment can apply a test or measurement in two places: before the treatment, which is a pre-test and after the treatment, which is a post-test.

This allows for identifying change caused by the treatment by comparing before and after results from a similar test for example a change in skill, attitude, etc. A post-test only may be used sometimes, for example in a 'taste-test', where the subject is asked about their experience in the treatment. The term 'pre-test' is also used to describe a trial of a test before it is applied 'for real'. Showing something to be true does not make it always true, even though you may repeat the experiment many times.

If, however, you can show that it cannot be false , then you need go no further. Thus, if you can show that the null hypothesis is false, then you have also proven that the primary hypothesis is true. Proving truth , Sampling terminology. Quotes Guest articles Analysis Books Help. More Kindle book s: And the big paperback book. Look inside. Please help and share:. More Kindle book s:. Home Top Menu Quick Links. Bias minimization Researchers can easily introduce bias into results by accidental, subconscious or otherwise reduce the validity of the methods used.

Sampling It is seldom possible to research an entire population , so a sample must be selected to represent the population. Randomization If a random sample can be selected, then statistics can be used to generalize , drawing conclusions about the entire population.

Selection and assignment Randomization starts with selection of target random selection. Probabilistic equivalence Randomization creates probabilistic equivalence , where multiple test groups are declared statistically equivalent two groups of people are never equal in all respects. Noise reduction In electronics theory, a signal is made up of the original signal plus added unwanted noise, such as hissing on a radio.

Comparison Comparison is a common way of eliminating noise. Groups Experiments often use multiple groups, with each group forming a mini-experiment on its own, and with the findings from each group then being compared for further comparison, analysis and conclusion. Why would anyone ever want more than two 2 levels of an independent variable? Hint: StatisticsMain advantage of designs which use more than two levels of an independent variable is tha..

What is the purpose of a post-hoc test with analysis of variance? Hint: StatisticsWe use post hoc tests to tell which groups differ from the rest.

There are many algorithms.. Ask a Question. It means that we know perfectly the odds that we will find a pretest difference between the two groups.