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Yes, it is easier to see the mean difference between two samples if the sample variances are small. Smaller variances indicate that the data points are closer to the mean, which enhances the clarity of the difference between the two sample means. This increased precision reduces the overlap between the distributions of the two samples, making the mean difference more pronounced and easier to detect statistically.

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1mo ago

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How would the distributions change if the difference between the means was the same as the MAD for each distribution?

If the difference between the means of two distributions is equal to the Mean Absolute Deviation (MAD) for each distribution, this would indicate that the overlap between the two distributions is minimized. As a result, the distributions would likely be more separated, leading to a clearer distinction in their central tendencies. The spread of the data would remain unchanged, but the relative positioning of the distributions would be such that they are farther apart, making it easier to identify differences between the two populations.


What is the difference between data driven and goal driven?

Goal driven reasoning or backward chaining - an inference technique which uses IF THEN rules to repetitively break a goal into smaller sub-goals which are easier to prove. Data driven reasoning or forward chaining - an inference technique which uses IF THEN rules to deduce a problem solution from initial data.


Which is more useful between bar graph and pictograph?

This is like the chicken and the egg question, which came first. Bar graphs make some information easier to understand, progressions. Pictographs make other information easier to understand, percentages


What are the Difference between Probabilistic sampling methods and non probabilistic sampling methods?

With a probabilistic method, each member of the population has the same probability of being selected for the sample. Equivalently, given a sample size, every sample of that size has the same probability of being the sample which is selected. With such a sample it is easier to find an unbiased estimate of common statistical measures. None of this is true for non-probabilistic sampling.


Is it easier to increase internal validity than external validity?

No it is not easier because of the external flow.

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