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Olin [163]
2 years ago
10

If p → q is true, then ~ p → ~ q is __________ true. Sometimes Always Never

Mathematics
1 answer:
Alecsey [184]2 years ago
4 0

Answer:

1. If p is true and q is false, the p -> q is never true.

2. When p is false and q is true, then p or q is always true.

3. If p is true and ~ q is false, then p -> ~ q

N

is never false.

4. If p is true and q is true, then ~ p -> ~ q is always true.

5. If p->q is true and q is true, then p is

always true.

Further Explanation:

The logic gates are used here.

Here, the symbol -> is for implication. Implication p-> q means that if p is true then q must be true.

So let us look at all the questions one by one.

1. p is true and q is false, the p -> q is always, sometimes, never true.

p-> q

true -> false

The true should imply true so the given statement will never be true.

2. When p is false and q is true, then p or q is always, sometimes, never true.

false or true

We know that in or gate even if one input is true, the whole output is true. So this statement will be always true given p is false and q is true.

3. If p is true and~q is false, then P q is always, sometimes, never false.

This translates to:

true -> true

So it will never be false.

4. If p is true and q is true, then ^p -> ~q is always, sometimes, never true.

This translates to:

false false

This will always be true.

5. If p->q is true and q is true, then p is always, sometimes, never true.

If p->q is true and q is true then will always be true. "Implies to" states that in p->q, in order for q to be true p has to be true. So p will always be true.

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Answer:

1. B

2. A

3. A

4. A

Step-by-step explanation:

Hello!

The study claimed that subjects who suffer depression are more likely to have a heart attack than those who are not depressed.

1551 persons were interviewed as part of the experiment and classified according to their answers in two groups "suffered depression" and "didn't suffer depression"

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1.

An observational study is one where the researcher only determines the variables he wants to study without controlling or influencing any factor of the population of interest. Because there is no interference from the researchers, there is a high risk that confounding factors may affect the conclusions of it. These studies are usually precursors to experimental tests, it allows the researcher to have an idea of the association between the two variables but you cannot establish causal relationships from them.

This is an example of an observational study, the researcher merely recorded the variables of interest without interfering with any aspects that may influence them. (For example diet or exercise habits of the subjects)

2. and 3.

The objective of the study is to determine if "depression" causes "disposition to heart attacks"

The explanatory variable is "depression status of the subject" since it is what is suspected to influence over the heart condition of said subject and "heart attack status" is the response variable.

4.

Of the 1551 subjects originally studied, 444 were classified as depressed, of these 27 had heard attacks. You can calculate the "proportion of subjects that suffered depression and had heart attacks" as:

p': 27/444= 0.06 ⇒ 6%

Since this value was obtained from the sample, it is an estimation of the population parameter, also called statistic.

I hope it helps!

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