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Hypothesis Tests - Statistics and Probability

Date of publication: 2017-08-27 22:26

The two shaded areas each have a probability of , which adds up to a total probability of . This time our sample mean does not fall within the critical region and we fail to reject the null hypothesis. This comparison shows why you need to choose your significance level before you begin your study. It protects you from choosing a significance level because it conveniently gives you significant results!

Comparing slopes independent samples | Real Statistics

P-value. The strength of evidence in support of a null hypothesis is measured by the P-value. Suppose the test statistic is equal to S. The P-value is the probability of observing a test statistic as extreme as S , assuming the null hypotheis is true. If the P-value is less than the significance level, we reject the null hypothesis.

New View of Statistics: P Values - Sportsci

in Figure 7, cell V65 the code cites: 8775 = Sres 8776 does that refer to the sqrt of cell V9? Because cell S9 refers to the parameter 8775 Sres^7 8776 and elsewhere small details such these are called out quite explicitly, I don 8767 t know for certain which way to go [., use the 8775 Sres^7 8776 or sqrt(Sres^7)].

Significance Testing - Free Statistics Book

Sorry that it has taken me so long to respond to your question. I seemed to have missed your response. I am not very familiar with Mediation models and so I am reluctant to answer your question. I plan to look into these sorts of models later this year.

Hi Dirk,
You are probably using the German version of Excel, which uses semi-colons instead of commas to separate arguments in a function. The SlopesTest function is what Excel calls an array function. In this case you must highlight the range where the output will go (not just a single cell) and then press Ctrl-Shift-Enter. See the webpage Array Formulas and Functions for more details about how to use array functions.

Alternatively you can first highlight a 9 x 7 range, then enter a formula of form SlopesTest(R6, R7, R8, R9, b, TRUE) and finally press Ctrl-Shift-Enter. This will fill the second highlighted column with the same values as described above and fill the first column with the appropriate labels.

The probability distribution plot above shows the distribution of sample means we&rsquo d obtain under the assumption that the null hypothesis is true (population mean = 765) and we repeatedly drew a large number of random samples.

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I 8767 ve used both methods on my data and have found that the two conclusions are different. Since the calculated standard error on the coefficient is different, and since the coefficient itself is the same, the t-statistic is different. The null hypothesis can be rejected in only one of the two methods (not yours).

SlopesTest is not a standard Excel function. It is part of the Real Statistics Resource Pack. You need to download and install the resource pack to use this function. This is free.

If you plan to use inferential statistics (., t-tests, ANOVA, etc.) to analyze your evaluation results, you should first conduct a power analysis to determine what size sample you will need. This page describes what power is as well as what you will need to calculate it.

I've already defined statistical significance in terms of confidence intervals. The other approach to statistical significance--the one that involves p values--is a bit convoluted. First you assume there is no effect in the population. Then you see if the value you get for the effect in your sample is the sort of value you would expect for no effect in the population. If the value you get is unlikely for no effect, you conclude there is an effect, and you say the result is "statistically significant".

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