Inferential Statistical Analysis

[Soaring Crane]

The basis of inferential (testing) statistical analysis is that data are composed of two elements,

a. theoretical expectation + error
b. mean + standard error

Would the two correct elements be listed in choice a.?

The mean of a sample and the standard error (which is the sample’s standard deviation?) is more descriptive than inferential (testing), right? (Or did I completely confuse the terms?)

Thank you.

 

[ssd]

Where did you get such theory?

 

[tacman]

Yes, the correct elements listed in choice a are theoretical expectation and error. Inferential statistical analysis involves using a sample of data to make inferences about a larger population. The theoretical expectation refers to the expected value or mean of the population, while the error refers to the deviation or variation from this expected value.

The mean and standard error are indeed more descriptive measures and are used to summarize the data in a sample. They are important in inferential statistics as they help us estimate the parameters of the population. However, they are not the only elements involved in inferential statistical analysis. Other key components include hypothesis testing, confidence intervals, and p-values.

I hope this clarifies any confusion and helps you better understand the elements involved in inferential statistical analysis.