Please Help !!!

In the Freakonomics video, what example did Stephen Dubner use to illustrate the idea that correlation does not necessarily prove a cause?

Question 1 options:

Rates of drowning going up or down simultaneously with the number of Nicholas Cage movies made that year

Thunder roaring just after lightning strikes

Rates of drowning increasing at the same time as ice cream consumption

Polio rates spiking at the same time as ice cream consumption

In the TED video "The Danger of Mixing Up Causality and Correlation", Ionica Smeets states that which of the following is "the most often made logical mistake"?

Question 2 options:

	Attributing intent to someone who did something when really it was an accident
	Making a hasty generalization that a correlation exists
	Jumping to an incorrect conclusion about causality when you see a correlation
	Thinking that something is a coincidence when really it is not

What was Smeets' explanation for why there is a correlation between children who sleep with the lights on and children who are short-sighted later in life?

Question 3 options:

It is just a coincidence that children who sleep with the lights on end up being more likely to be short-sighted later in life.

There is no correlation between being short-sighted later in life and sleeping with the lights on later in life.

The fear of becoming short-sighted later in life causes children to sleep with the lights on.

Some third cause is causing both children to sleep with the lights on and children to be short-sighted later in life, namely their short-sighted parents leave the light on so that they can walk around with stubbing a toe and pass on their gene for short-sightedness.

Sleeping with the lights on causes children to become short-sighted later in ln life

Question 4 (1 point)

Listen

What does it mean for an argument to be 'inductive'?

Question 4 options:

It means that the argument is either valid or invalid.

It means that it starts with general principles and derives specific examples.

It means that the conclusion is guaranteed, as long as the premises are true.

It means that the conclusion is a matter of probability, never a guarantee.

Mill had 5 Methods for determining if one thing causes another. Below are the names of 4 of these 5 along with their descriptions. Match the name of each method with its description.

Question 7 options:

1234

When we want to find the cause of something, we remove a factor and see if that something still happens

1234

This is a fancy way of saying that things change, but if they change together in predictable ways, then it is likely that there is a causal relationship between them

1234

When you want to find the cause of something, but there are multiple causes which account for almost all of the results except for a last little bit

When we want to find the cause of something, we look for the common factor in all of the observed cases of when that thing occurs

Match each of the following term to an example that illustrates that term.

Question 8 options:

12	When one eats more food, one weighs more (all other things being the same)
12	When one exercises more, one weights less (all other things being the same)

The Parable of the Drunken Logician is given as a caution that we need to be careful with correlation. In this parable, what did the logician mistakenly say was the cause of his drunkeness?

Question 9 options:

	Whiskey
	Brandy
	Alcohol
	7up

1.	Direct correlation
2.	Inverse correlation

1.	Method of Agreement
2.	Method of Difference
3.	Method of Residues
4.	Method of Concomitant Variation