This argument features issues with two extremely common logical fallacies: 1) correlation vs. causation and 2) data pools that aren't necessarily comparable. If you see these elements in the gap in logic, you can anticipate the right answer.

First, notice that in the 20 years between arrest statistics that the official cites, many things could have occurred other than the laws she cites. What if, for example, alcohol tariffs made the price so exorbitant that everyone just quit drinking? Or the city built a system of canals and everyone just kayaks around town now? There could well be other causes for the statistic - the laws might be correlated with the time period, but did they really cause the outcome?

Second, notice that the use of actual-number data (25,000 arrests vs. 18,000 arrests) doesn't necessarily tie to the conclusion. Yes the number of arrests down (and the total population is up), but the conclusion is that the legislation was successful in "preventing motorists from driving under the influence." Since "motorists" is a subset of the total population, you'd really want to see a statistic that isn't just total number of arrests, but something more like arrests per 1,000 motorists" - a statistic that accounts for the fact that the number of motorists could be way down (in which case "motorists" - those who still drive - might still be driving under the influence quite frequently, but the overall statistic is down because there are simply much fewer drivers).

Given those errors in the argument, choice "Increased access to public transportation and ride-sharing applications has cut the number of drivers in the province by more than half." is correct - it shows that the number of motorists is down, and supplies an alternate cause for the drop in the number of arrests. People are using Lyft and taking the train, not driving anymore.

Among the other choices:

"The population in her province has increased at a lower rate than the populations of neighboring provinces." is irrelevant, as whether the population has grown at a high or low rate compared to other provinces, the fact remains that the population has still increased. (And really what you want to know is the number of drivers/motorists)

"The new legal measures have increased the province's law enforcement costs at nearly twice the rate that tax receipts have increased." seems like it should matter (is this a good use of money?) but remember that the specific conclusion is only about whether the laws worked, not about whether they were a wise use of funding. Always stay within the specific scope of the conclusion!

"Since 1998, the number of lawyers focusing on defending those arrested for driving under the influence has more than doubled." misses the mark because of its timing - the statistic used in the argument is about arrests, and notes that this intervention of lawyers occurs after the arrests have already taken place. If lawyers were acting before the arrests, that might suggest that the lawyers are causing the reduction in the number even though people are still drinking and driving, but that's not the case here - the lawyers in "Since 1998, the number of lawyers focusing on defending those arrested for driving under the influence has more than doubled." don't come into the picture early enough to explain away the number of arrests.

And "The number of restaurants and pubs permitted to sell alcohol in the province has increased since 1998 at approximately the same rate of the province's population." is similar - if the number of establishments serving alcohol were way down that might be part of an alternate explanation for the reduction in arrests, but with the number of restaurants and pubs serving alcohol increasing, that's not the case.

As with any weaken question, your first goal should be to understand the argument presented and find the gap between the information given and the conclusion presented. In this argument, you are told that a study claims that not eating genetically modified foods (GMOs) leads to lower rates of type 2 diabetes and heart disease because people who didn't eat GMOs tend to develop type 2 diabetes and heart disease at a lower rate than do people who do eat GMOs.

The gap here is in the difference between correlation and causation. While there is a correlation between the behavior (not eating GMOs) and the outcome (not getting type 2 diabetes or heart disease), there is nothing that proves the outcome is due to the behavior. What if non-GMO foods were only available to individuals who were wealthy or who belonged to a specific ethnic group that developed both diseases at lower rates? The correct answer will exploit the gap between correlation and causation.

The only answer choice to do this is "Individuals who do not eat genetically modified foods also tend to exercise and make other healthy lifestyle choices associated with a decreased risk of both diseases.". If individuals who don't eat GMOs also engage in other activities known to lower the risk of both diseases, then it's impossible to tell if their decreased risk is due to the fact that they don't eat GMOs or the fact that they engage in these other activities. Maybe the cause of both (not eating GMOs and decreased risk) is their lifestyle, and those two effects are just correlated.

Among the other answers, "Genetically modified foods also tend to be organically grown, a process that uses fewer pesticides and artificial fertilizers than does conventional agriculture." can be eliminated because there is no way to link the practice of using pesticides or artificial fertilizers to diabetes or heart disease. Choice "Type II diabetes and heart disease are often exacerbated or triggered by poor diets, especially those high in processed grain-based foods and fat-heavy meat products." can be eliminated since it does not address anything to do with the conclusion, which is specifically about genetically modified foods. Choice "It is possible that some individuals could be naturally resistant to developing both type 2 diabetes and heart disease regardless of diet." can also be eliminated for the same reason - there is no reason that these individuals wouldn't have shown up in both groups. Choice "Other studies have examined the effects of organic food on the risk of developing both diseases, but not on the effects of genetically modified food." can be eliminated as well since whether other studies have looked at this issue doesn't impact whether or not the conclusion is correct.

If you look for the logical flaw in the argument of this Strengthen question, you should see that it is one of generalization. Based on exactly one data point - a particular soccer star is less famous than 20 different basketball players - the argument draws the general conclusion that soccer players are not the most well-known athletes in the world. But Fabricio is only one player: if this were a Strengthen question you would want to show that he is an outlier on the less-famous side (meaning that most players are far more famous than he is, so this one data point is less relevant). But since this is a Weaken question, you want to show that Fabricio is one of the most famous soccer players, so that all other players are even less famous.

Choice "Fabricio is the most well-known soccer player in the world." does exactly that, and is therefore correct: if Fabricio is the most famous soccer player, and he's less famous than 20 basketball players, then the conclusion that soccer players are not the most famous athletes is a lot more likely - Fabricio isn't the one not-famous outlier while all the others are very famous. "Fabricio is the most well-known soccer player in the world." is correct.

Among the other answer choices: choice "AC Camarillo has won its league's championship the past three consecutive seasons." doesn't link Fabricio or AC Camarillo to being well-known. If AC Camarillo is a champion in a lesser-known league, then Fabricio isn't necessarily a particularly well-known player; if the team is the champion of an extremely popular league, then it's more likely that he's among the most well-known (but you still don't know for sure).

Choice "Fabricio is less well-known than the stars of several other professional soccer teams." weakens the argument by going the opposite direction of "Fabricio is the most well-known soccer player in the world." and saying that Fabricio isn't among the most famous players in the world. Choice "The most well-known basketball players are not always the best players on their teams." would slightly strengthen the argument if it were specific to the 20 players more famous than Fabricio, as then there would be even more basketball players who are more famous than Fabricio. But since it's a generic "the most famous players are not always the best on their teams" it doesn't add any more players more famous than Fabricio and therefore has no direct bearing on the argument. And choice "No professional basketball players are also professional soccer players.​" is similarly generic and therefore doesn't add any new data to further the argument (if it were that the most famous basketball players ARE also soccer players then it would have a direct bearing, but as written it does not).

This weaken problem features a common gap in logic: a fact is given (the cross-country GPA is higher than the average GPA) and then one plausible explanation is given as the only explanation for why that fact is true. This is essentially mixing correlation for causation: because two things occur together (runners have a lot of time to think, and runners have high GPAs, the time to think must cause the GPA). The best ways to weaken one of these arguments are to find an alternate explanation or to show that the causation is reversed (it's not that time spent running causes the high GPA, but rather the high GPA leads people to run).

And choice "The cross-country team is among the few teams that do not require a tryout, making it a popular activity for high-achieving students who want to list a sport on their college applications." does exactly that - it suggests that students with high GPAs are more likely to join the cross-country team. It's not that the running makes them better students, but instead good students tend to go toward running as a way to add an extracurricular activity to their application profile. That's why choice "The cross-country team is among the few teams that do not require a tryout, making it a popular activity for high-achieving students who want to list a sport on their college applications." is correct.

Among the wrong choices:

Choice "Cross-country running is more strategic than many realize, requiring runners to expend mental energy thinking about race tactics." should be tempting, but it does not directly attack the notion that runners have a lot of time to think. An activity can be strategic and still allow time to think. Choices "Many cross-country runners are also members of the track-and-field team, for which the average grade point average is actually lower than that of the school as a whole.", "Because the nearest cross-country trails are a long distance from the school, cross-country is one of the most time-consuming activities the school offers.", and "The cross country team's average grade point average has dropped each of the last three years." each try to attack the premise, making you think that the GPA shouldn't be as high as it is. "Many cross-country runners are also members of the track-and-field team, for which the average grade point average is actually lower than that of the school as a whole." does this by grouping cross-country runners with the other track-and-field athletes, for whom the GPA is lower. But we already know that the cross-country GPA is high, so it doesn't matter which other groups you could pool them with to lower their grades. Choice "Because the nearest cross-country trails are a long distance from the school, cross-country is one of the most time-consuming activities the school offers." similarly tries to provide a reason why you wouldn't think that the GPA would be high (it's such a time-consuming activity!) but again that doesn't matter - the GPA is high, so we're just trying to determine the cause. And choice "The cross country team's average grade point average has dropped each of the last three years." tries to do this by showing that the GPA is dropping, but again it's already been established that it's higher than average, and your only job is to determine why.

In this argument, there is a correlation between brain size and activity of the ant – those ants that gather nourishment (which tend to be older) have larger brains than those ants that nurture larvae (which tend to be younger ants). Because of this correlation, the author concludes that the cause for this difference in size must be the increased cognitive skills required for gathering. But where is the proof for this? Perhaps there is some other attribute relating to the ants that perform these different tasks and that is the reason for the difference. What if quite simply, older ants (which perform the gathering) have larger brains than younger ants (which perform the nurturing)? Then it simply has to do with age NOT the tasks they are performing. To weaken this argument, you are looking for some other plausible explanation for the different size brains and "The brains of older ants that are not involved in gathering nourishment are the same size as those counterparts of the same age that do gather nourishment." gives that perfectly, as it suggests that indeed the difference might be explained by age alone.

For "Ants that have spent more time gathering nourishment do not have considerably larger brains than do ants that have spent a much shorter time gathering." – this does not necessarily weaken the argument. The activity the ant performs could indeed be causing the difference, but at a certain threshold, more gathering does not further increase brain size. "Ants that have spent more time gathering nourishment do not have considerably larger brains than do ants that have spent a much shorter time gathering." can be true and it does not hurt the core position of the argument. Likewise for "The brains of older ants that stop gathering nourishment to take on other tasks do not become smaller.", the author is just stating that the INCREASE in brain size is caused by the different activities – if the brain doesn’t decrease in size after stopping the activities it does not affect this conclusion. For "In many species of ants, the brains of older ants are only minimally larger than the brains of younger ants.", the degree of the difference in size is not addressed in the argument so this choice has no impact on the quality of the author’s conclusion. Similarly for "Ants that have to travel farther to gather nourishment do not have considerably larger brains than do ants that do not have to travel far.", the distance traveled is not addressed in the argument, simply what activity the ants engage in. Correct answer is "The brains of older ants that are not involved in gathering nourishment are the same size as those counterparts of the same age that do gather nourishment.".

The key in this problem is to consider some flaw with the trend that the sociologist cites. In other words, what might indicate that the trend will not continue? Consider the following scenario: 10 years ago, most women who would normally have married at 22 start waiting to get married until they are forty. Over the next twenty years, the marriage rate would go down dramatically because women are waiting to get married (and the average marriage age is going up). However, when they do decide to get married, the rate will go back up again. If this were true it would show a huge flaw in the sociologist’s reasoning so "The average age of marriage has increased dramatically in the past 20 years." is correct. For "Today’s divorce rates are expected to rise dramatically over the next 40 years." and "More women are expected to get married for a second and third time in the next 40 years." divorce rates and second/third time marriages are unimportant because the argument is only about first time marriages. "Many women are deciding to simply live with their partners rather than get married." and "Marriage is much less likely to occur today for the first time than it was in the 1960’s." would not indicate a flaw as they both seem to support the sociologist (that is the trend that marriage is disappearing). Answer is "The average age of marriage has increased dramatically in the past 20 years."

The epidemiologist’s argument improperly assumes that the cancer death rates were similar in the two towns ten years ago. While the rates in Maple Grove have INCREASED much more than in Fernland, what if they were much lower to begin with. Just because the rate has increased more in Maple Grove, it could easily be lower today than in Fernland. Answer choice "Whether Fernland and Maple Grove had similar cancer death rates 10 years ago." properly points out this assumption and is thus the correct answer. For "Whether the population in Maple Grove has increased dramatically in the past decade.", population growth is unimportant because it is a per capita rate. The smoking issue is a red herring in this problem (tries to steal your attention from the major data problem), so "Whether smoking is the primary cause of cancer in Fernland." and "Whether Maple Grove has ever introduced an anti-smoking initiative." are both wrong. For "Whether most cancer victims in Maple Grove survive more than 10 years.", the length of survival is also immaterial to the major data problem isolated above. Answer is "Whether Fernland and Maple Grove had similar cancer death rates 10 years ago.".

As you deconstruct this argument, you should notice a classic case of mistaking correlation (two things occur together) for causation (one causes the other). Here you're told that people who exercise regularly have a lower incidence of respiratory illness, and then the conclusion is that regular exercise helps prevent respiratory illness.

But why can't that be the other way around? Whenever a question is structured as "X and Y happen together, so X likely causes Y" you should be on the lookout for an answer choice that suggests that, actually, Y is the thing that causes X.

Answer choice "People with respiratory illnesses are generally told by doctors that they must limit or cease their aerobic exercise routines." here supplies exactly that: if people who have respiratory illness are unable to exercise, that's a possible reason for the statistics (exercise and respiratory health occur together) to be true. So by providing an alternate explanation for the premises, "People with respiratory illnesses are generally told by doctors that they must limit or cease their aerobic exercise routines." shows that the conclusion is not necessarily true. "People with respiratory illnesses are generally told by doctors that they must limit or cease their aerobic exercise routines." is correct.

"Some respiratory illnesses are hereditary and therefore minimally affected by lifestyle choices." is incorrect because the conclusion is so soft, that exercise "can be helpful in preventing" respiratory illness. Even if some respiratory illnesses cannot be prevented, choice "Some respiratory illnesses are hereditary and therefore minimally affected by lifestyle choices." does not prohibit exercise from preventing other respiratory illnesses. Note also that "Some respiratory illnesses are hereditary and therefore minimally affected by lifestyle choices." says that the hereditary respiratory illnesses are minimally affected by lifestyle choices. "Minimally affected" still allows for lifestyle choices to have an impact, which is consistent with "can be helpful" in preventing these illnesses.

"The amount of air pollution, a common cause of respiratory illness, has increased dramatically since the 1950s." and "The lengths of the average workday and commute have increased markedly since the 1950s, leaving the average person with less time for aerobic exercise." are wrong for similar reasons: they are each overruled by the facts, which state that exercise and a lack of respiratory illness have remained correlated over time, even if respiratory illness is increasing due to pollution "The amount of air pollution, a common cause of respiratory illness, has increased dramatically since the 1950s." or people in general are exercising less "The lengths of the average workday and commute have increased markedly since the 1950s, leaving the average person with less time for aerobic exercise.". You still have facts from the argument that those who do find time to exercise have less respiratory illness than those who do not, so "The amount of air pollution, a common cause of respiratory illness, has increased dramatically since the 1950s." and "The lengths of the average workday and commute have increased markedly since the 1950s, leaving the average person with less time for aerobic exercise." are countered by the given information.

"Recent studies have debunked the conventional wisdom that aerobic exercise is an effective preventer of heart disease." misses the specific scope of the conclusion, which is only about respiratory illness. The fact that exercise doesn't prevent heart disease doesn't factor in to a discussion about respiratory issues. Because heart issues and respiratory issues are two completely different categories, "Recent studies have debunked the conventional wisdom that aerobic exercise is an effective preventer of heart disease." does not directly address the conclusion about respiratory issues.