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The statement that is FALSE among the given options on hypothesis testing is;
Option D; Reducing the significance level (α) can increase a test's effectiveness.
This is about hypothesis testing.
Let us look at each of the options.
- A) When we increase the sample size, it means the testing becomes more sensitive and as such we are more likely to reject the null hypothesis. Thus, it increases the effectiveness.
- B) Alpha (α) is defined as the probability of rejecting the null hypothesis. Thus it is the probability of making a Type I error.
- C) Expanding the sample size makes the hypothesis test to be more sensitive. That is makes it more likely to reject the null hypothesis when it is false and as such it increases the power of the test.
- D) The lower the significance level, the lower the power of the test and as such the lesser the tests effectiveness.
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The pH where you might be able to precipitate as much Cu2 as possible will be any value that is less than 5.85.
<h3>How to illustrate the information?</h3>
The solubility product of salt is defined as the product of molar concentrations of ions in a saturated solution of it.
An ion will be precipitated if the ionic product exceeds the solubility product of the cation. In the case of Cu and Zn, the solubility product is greater for Zinc than Copper.
Also Cu will be precipitated in an acidic medium while Zn is precipitated in an alkaline medium. We have for CuS, K= S2 so S = 2.4495*10-8. For ZnS, S = 0.1414. So the lower the pH higher will be the amount of CuS precipitated.
If we are starting with 0.075M CuS and ZnS solution it will have 0.075 moles each of Cu2+, Zn2+, and S2. Since the anion concentration can be equated to POH, POH for Cus and Zns are 14.096 and 5.85.
The maximum precipitation will take place is any value which is less than 5.85.
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