Question: The background information (BI) lists seven steps to hypothesis testing. In brief, they are:

i. Specify a null hypothesis.
ii. Specify an alternative hypothesis.
iii. Specify a confidence interval or, equivalently, a level of significance (LOS).
iv. Calculate an appropriate statistic (e.g., Student t or Pearson Correlation Coefficient).
v. Compare the statistic value with a critical value (CV) or p value.
vi. Reject or accept the null hypothesis accordingly.
vii. Explain the results in terms that even management can understand.

Steps 1 and 2 are critical to the hypothesis testing procedure. If I guess "It's raining outside," I've specified a null hypothesis...a guess.

At this point, I have no clue if it's raining or not...that's why it's a guess...a hypothesis. If I saw water seeping through my ceiling, I could pose a theory, rather than a hypothesis, because there would be some empirical evidence, the seeping water, to support my statement "It's raining outside."

The point is this...one does not presume an answer to the null hypo when positing it. We specify the null that is easiest to prove or disprove. That means, in almost every case, we posit THAT THERE IS NO DIFFERENCE between a characteristic of the population and of the sample we use when doing the test. That is, we specify that the characteristics of the population and the sample are statistically the same.

NO DIFFERENCE is like us specifying that a water glass is empty. That's easy to prove or disprove, and most everyone will agree to it.

But specifying that a glass is half full, for example, is harder to prove or disprove. You might find a lot of people who are skeptical about your conclusions in this case. So, when you have a choice, specifying no difference (which is the same as saying they, the population and sample characteristics, are the SAME) is the right thing to do.

So hypothesis testing is about guessing when there is no empirical evidence one way or the other to support that guess or not. So my null hypothesis is "It's raining outside." What's the alternative hypothesis? That's right..."It's NOT raining outside."

It's that simple...to specify an alternative hypothesis, just use the null hypothesis and restate it as the LOGICAL OPPOSITE and you have the alternative hypothesis. The logical opposite of "is" is "is not." The logical opposite of "will" is "will not." The logical opposite of "is the same as" is "is not the same as." The logical opposite of "is not" is "is." The logical opposite of "will not" is "???."

THE BEST WAY to specify the alternative is by simply copying and pasting your null hypothesis into your Word or Excel document. Then you edit the copied null to make it the logical opposite and, therefore, the alternative of the null. So...COPY, PASTE, and EDIT your null to get the alternative.

So here are your questions to answer for this TD:

The background information (BI) lists seven steps to hypothesis testing. In brief, they are:

i. Specify a null hypothesis.
ii. Specify an alternative hypothesis.
iii. Specify a confidence interval or, equivalently, a level of significance (LOS).
iv. Calculate an appropriate statistic (e.g., Student t or Pearson Correlation Coefficient).
v. Compare the statistic value with a critical value (CV) or p value.
vi. Reject or accept the null hypothesis accordingly.
vii. Explain the results in terms that even management can understand.

Steps 1 and 2 are critical to the hypothesis testing procedure. If I guess "It's raining outside," I've specified a null hypothesis...a guess.

At this point, I have no clue if it's raining or not...that's why it's a guess...a hypothesis. If I saw water seeping through my ceiling, I could pose a theory, rather than a hypothesis, because there would be some empirical evidence, the seeping water, to support my statement "It's raining outside."

The point is this...one does not presume an answer to the null hypo when positing it. We specify the null that is easiest to prove or disprove. That means, in almost every case, we posit THAT THERE IS NO DIFFERENCE between a characteristic of the population and of the sample we use when doing the test. That is, we specify that the characteristics of the population and the sample are statistically the same.

NO DIFFERENCE is like us specifying that a water glass is empty. That's easy to prove or disprove, and most everyone will agree to it.

But specifying that a glass is half full, for example, is harder to prove or disprove. You might find a lot of people who are skeptical about your conclusions in this case. So, when you have a choice, specifying no difference (which is the same as saying they, the population and sample characteristics, are the SAME) is the right thing to do.

So hypothesis testing is about guessing when there is no empirical evidence one way or the other to support that guess or not. So my null hypothesis is "It's raining outside." What's the alternative hypothesis? That's right..."It's NOT raining outside."

It's that simple...to specify an alternative hypothesis, just use the null hypothesis and restate it as the LOGICAL OPPOSITE and you have the alternative hypothesis. The logical opposite of "is" is "is not." The logical opposite of "will" is "will not." The logical opposite of "is the same as" is "is not the same as." The logical opposite of "is not" is "is." The logical opposite of "will not" is "???."

THE BEST WAY to specify the alternative is by simply copying and pasting your null hypothesis into your Word or Excel document. Then you edit the copied null to make it the logical opposite and, therefore, the alternative of the null. So...COPY, PASTE, and EDIT your null to get the alternative.

So here are your questions to answer for this TD:

The alternative hypothesis of "The vitamin C content of genetically modified corn is the same as that of non-genetically modified corn" is what?

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