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What do significance levels and P values mean in hypothesis tests?
We want to determine whether our sample mean (330.6) indicates that this year's average energy cost is significantly different from last year’s average energy cost of $260.
The probability distribution plot above shows the distribution of sample means we’d obtain under the assumption that the null hypothesis is true (population mean = 260) and we repeatedly drew a large number of random samples.
I left you with a question: where do we draw the line for statistical significance on the graph? Now we'll add in the significance level and the P value, which are the decision-making tools we'll need.
We'll use these tools to test the following hypotheses:
Null hypothesis: The population mean equals the hypothesized mean (260).
Alternative hypothesis: The population mean differs from the hypothesized mean (260).
P-values are the probability of obtaining an effect at least as extreme as the one in your sample data, assuming the truth of the null hypothesis. Please let me know if you need any clarification. I'm always happy to answer your questions.
Jul 18th, 2015
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