Question 1

Which of the following, if left to stand alone, is the weakest evidence of a possible causal connection?
A)There is a reasonable explanation for a cause and effect relationship.
B)The data appear to have a pattern on the scatterplot.
C)The connection was shown to hold under varying conditions.
D)Potential confounding variables have been ruled out.

Accepted Answer

A pattern on a scatterplot can suggest a possible correlation, but it does not necessarily prove a causal connection. Other factors could also be at play.

Question 2

Give an example where a randomized experiment cannot be done, even though we know that is the best way to try to establish a causal connection between two measurement variables.

Accepted Answer

The answer of Give an example where a randomized experiment...

Question 3

Suppose within a short span of time, people in a certain town realize that there is an unusually high rate of leukemia among children in their town.Suppose someone calculated the odds of having that many cases in such a short time to be 1 in 15,000.Which of the following immediate conclusions would not be correct?
A)Since the chance is only 1 out of 15,000, something in this town has to be causing our children to get sick.We need to take immediate action.
B)We should expect this phenomenon to happen in about 1 out of every 15,000 towns similar to this one, just by chance.There is no cause for alarm just yet.
C)It would be unusual if we did not occasionally see clusters of disease such as this one; this town may just be unlucky.Let's wait until more data is collected.
D)We should keep an eye on the situation but there is no reason to panic.This could very well be just a coincidence.

Accepted Answer

The conclusion that "something in this town has to be causing our children to get sick. We need to take immediate action" is not necessarily correct based solely on the odds calculation. While the odds of such a high rate of leukemia may be low, it is still possible that it occurred by chance. More data and investigation would be needed to determine if there is a causal factor in the town.

Question 4

One of the ways two variables could be related without a causal connection is the existence of __________ variables.

Accepted Answer

The answer of One of the ways two variables could...

Question 5

If a randomized experiment cannot be done, then four non-statistical considerations must be used (all together) to establish evidence of a possible causal connection between two measurement variables.Name them.

Accepted Answer

The answer of If a randomized experiment cannot be done,...

Question 6

Which of the following is a confounding variable for the relationship between happiness and length of life?
A)Happiness level
B)Length of life
C)Emotional support
D)Age at death

Accepted Answer

Emotional support could be a confounding variable because it could also affect both happiness and length of life independently. For example, emotional support could lead to higher happiness levels as well as longer life span. Therefore, it is important to control for emotional support when studying the relationship between happiness and length of life.

Question 7

If two measurement variables are both found to be changing over time, what does this mean?
A)It means there is a causal link between the two variables.
B)It means there is a common cause of the changes in both variables (possibly other than time).
C)It means that even though the two variables may be highly correlated, they could be completely unrelated in terms of cause and effect.
D)None of the above.

Accepted Answer

Two variables changing over time may be correlated due to a common trend or external factor, but this does not imply a causal relationship.

Question 8

There is a strong correlation between verbal SAT scores and college GPAs.This does not mean however, that higher SAT scores cause higher grades in college.But what could explain this relationship?
A)The confounding variable gender.
B)The high (low) SAT scores and high (low) GPAs both result from a common cause.
C)Both SAT scores and GPAs change over time.
D)The relationship is purely coincidental.

Accepted Answer

The correlation between verbal SAT scores and college GPAs could be due to a common cause, such as general intelligence or socioeconomic background, which influences both academic achievement and standardized test performance. It is also possible that students who score highly on the SAT may possess certain personality traits or study habits that contribute to success in college. However, it cannot be concluded that higher SAT scores directly cause higher grades in college without further research.

Question 9

What is the only legitimate way to try to establish a causal connection statistically between two measurement variables?

Accepted Answer

The answer of What is the only legitimate way to...

Question 10

It is very difficult to establish a causal connection between two variables without the use of anything except a __________.

Accepted Answer

The answer of It is very difficult to establish a...

Question 11

Which of the following will strengthen the evidence for a causal connection?
A)Many observational studies conducted under different conditions all find the same link between two variables.
B)Many observational studies with different confounding variables all find the same link between the two variables.
C)The same type of relationship holds when the explanatory variables fall into different ranges for different studies.
D)All of the above.

Accepted Answer

All of the given options would strengthen the evidence for a causal connection.

Option A suggests that the correlation between two variables is consistent across numerous observational studies, despite different conditions. This consistency would make it less likely that the observed relationship is due to chance.

Option B states that multiple observational studies with different extraneous variables (confounders) all find the same link between two variables. This would imply that the observed relationship is not simply due to some other factor that is different between the studied groups.

Option C notes that the same type of relationship occurs in different ranges of the explanatory variable. This would suggest that the relationship between the two variables is generalizable and not just specific to certain ranges of one of the variables.

Together, all of these criteria would make a causal connection more likely.

Question 12

The __________ the number of confounding factors that can be ruled out, the __________ convincing the evidence for a causal connection.

Accepted Answer

The answer of The __________ the number of confounding factors...

Question 13

Suppose you heard on the radio that women who overuse antibiotics have a higher chance of developing breast cancer.You look into the literature on this, and find ten observational studies done by different researchers under different conditions, all of which confirm the results that you heard on the radio.What do you conclude?
A)The evidence for a causal connection between overuse of antibiotics and increased risk of breast cancer is strengthened by these varying studies.
B)These studies have too many different confounding variables that together weaken the evidence for a causal connection.
C)Since the studies were all done under different conditions, there is not enough information to make a conclusion.
D)None of the above.

Accepted Answer

The fact that different studies, conducted under different conditions, have all found a positive association between overuse of antibiotics and increased risk of breast cancer strengthens the evidence for a causal connection between the two variables. This consistency in results suggests that the relationship is not just due to chance, but rather a true effect. It is important to note that observational studies cannot prove causation, but the consistency in results across multiple studies can provide strong support for a causal relationship.

Question 14

Sometimes an association between two variables is due to __________, even though the odds of it happening appear to be very small.

Accepted Answer

The answer of Sometimes an association between two variables is...

Question 15

Even in a well designed experiment, there will always be confounding variables that we have neglected to measure.How can we reduce the chances that an observed association is due to those confounding variables? Name two ways.

Accepted Answer

The answer of Even in a well designed experiment, there...

Question 16

Which of the following cannot be obtained from observational studies?
A)Definitive evidence of a causal connection.
B)A reasonable explanation for a causal connection.
C)Any evidence of a causal connection.
D)Definitive evidence of a correlation.

Accepted Answer

Observational studies can show evidence of correlation, but cannot definitively prove causality. Other factors, such as confounding variables, may be influencing the relationship between the two variables being studied.

Quiz 11: Relationships Can Be Deceiving

Which of the following, if left to stand alone, is the weakest evidence of a possible causal connection?

Give an example where a randomized experiment cannot be done, even though we know that is the best way to try to establish a causal connection between two measurement variables.

One of the ways two variables could be related without a causal connection is the existence of __________ variables.

If a randomized experiment cannot be done, then four non-statistical considerations must be used (all together) to establish evidence of a possible causal connection between two measurement variables.Name them.

Which of the following is a confounding variable for the relationship between happiness and length of life?

If two measurement variables are both found to be changing over time, what does this mean?

There is a strong correlation between verbal SAT scores and college GPAs.This does not mean however, that higher SAT scores cause higher grades in college.But what could explain this relationship?

What is the only legitimate way to try to establish a causal connection statistically between two measurement variables?

It is very difficult to establish a causal connection between two variables without the use of anything except a __________.

Which of the following will strengthen the evidence for a causal connection?

The the number of confounding factors that can be ruled out, the convincing the evidence for a causal connection.

Sometimes an association between two variables is due to __________, even though the odds of it happening appear to be very small.

Even in a well designed experiment, there will always be confounding variables that we have neglected to measure.How can we reduce the chances that an observed association is due to those confounding variables? Name two ways.

Which of the following cannot be obtained from observational studies?