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Can Positive Values of Observations imply Population Positive Mean?

First, you usually can't prove much from samples, since any sample is possible to happen, and a proof is for something that must always be true regardless of what happens. Second, your intuition would ...
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Can Positive Values of Observations imply Population Positive Mean?

No. A sample generally does not allow you to "prove" anything about the underlying population with 100% certainty, it just allows you to infer it with varying levels of confidence. Suppose ...
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4 votes

Can Positive Values of Observations imply Population Positive Mean?

PROVE? NO set.seed(21) N <- 3 # Sample size x <- rnorm(N, -0.1, 1) I get three positive numbers, resulting in a positive sample mean, yet the population mean ...
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3 votes

Can Positive Values of Observations imply Population Positive Mean?

You can't prove it, but you can calculate a confidence interval for the population mean given the sample. This requires an assumption on the population distribution. More information is required for a ...
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Comparing values to detect statistically significant difference

You want to "see if there is considerable significant different between them". With a sample size of 3500, your difference will very likely be significant. You could check using some ...
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Geometric vs. arithmetic mean

There are lots of possible aggregations besides the arithmetic and geometric mean, popular other choices are e.g. the harmonic mean or the generalized mean, or, as a robust alternative, the median. ...
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1 vote

Geometric vs. arithmetic mean

As with many things, it depends on what you want to get out of it. The neat thing about the arithmetic average is that if you have one, and you know the total number of values, you can multiply the ...
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Can a set of means be used as the dependent variable in a correlation?

Spearman correlation I will assume that you want to treat your intervals as ordered categories (think as 0, 1, 2, 3, 4) and check if this order coincides with the order of the average answers. Then, ...
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