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A medical article once pointed with great alarm to an increase in cancer among milk drinkers. Cancer, it seems, was becoming increasingly frequent in New England, Minnesota, Wisconsin, and Switzerland, where a lot of milk is produced and consumed, while remaining rare in Ceylon, where milk is scarce. For further evidence it was pointed out that cancer was less frequent in some states of the southern United States where less milk was consumed. Also, it was pointed out, milk-drinking English women get some kinds of cancer eighteen times as frequently as Japanese women who seldom drink milk.
A little digging might uncover quite a number of ways to account for these figures, but one factor is enough by itself to show them up. Cancer is predominantly a disease that strikes in middle life or after. Switzerland and the states of the United States mentioned first are alike in having populations with relatively long spans of life. English women at the time the study was made were living an average of twelve years longer than Japanese women.
Professor Helen M. Walker has worked out an amusing illustration of the folly in assuming there must be cause and effect whenever two things vary together. In investigating the relationship between age and some physical characteristics of women, begin by measuring the angle of the feet in walking. You will find that the angle tends to be greater among older women. You might first consider whether this indicates that women grow older because they toe out, and you can see immediately that this is ridiculous. So it appears that age increases the angle between the feet, and most women must come to toe out more as they grow older.
Any such conclusion is probably false and certainly unwarranted. You could only reach it legitimately by studying the same women—or possibly equivalent groups—over a period of time. That would eliminate the factor responsible here, which is that the older women grew up at a time when a young lady was taught to toe out in walking, while the members of the younger group were learning posture in a day when that was discouraged.
When you find somebody—usually an interested party—making a fuss about a correlation, look first of all to see if it is not one of this type, produced by the stream of events, the trend of the times. In our time it is easy to show a positive correlation between any pair of things like these: number of students in college, number of inmates in mental institutions, consumption of cigarettes, incidence of heart disease, use of X-ray machines, production of false teeth, salaries of California school teachers, profits of Nevada gambling halls. To call some one of these the cause of some other is manifestly silly. But it is done every day.
1) The author’s conclusion about the relationship between age and the ways women walk indicates he believes that
(A) toeing out is associated with aging
(B) toeing out is fashionable with the younger generation
(C) toeing out was fashionable for an older generation
(D) studying equivalent groups proves that toeing out increases with age
(E) studying the same women over a period of time proves that toeing out increases with age
2) The author describes the posited relationship between toeing out and age (lines 29-40) in order to
(A) illustrate a folly
(B) show how social attitudes toward posture change
(C) explain the effects of aging
(D) illustrate a medical problem
(E) offer a method to determine a woman’s age from her footprints
3) Given the author’s statements in the passage, his advice for evaluating statistics that show a high positive correlation between two conditions could include all the following statements EXCEPT
(A) look for an explanation in the stream of events
(B) consider some trend of the times as the possible cause of both conditions
(C) account for the correlations in some way other than causality
(D) determine which of the two conditions is the cause and which is the effect
(E) decide whether the conclusions have been reached legitimately and the appropriate groupings have been made
4) Assume that there is a high statistical correlation between college attendance and individual earnings. Given this, the author would most probably agree with which one of the following statements about the cause-effect relationship between college attendance and income?
(A) Someone’s potential earnings may be affected by other variables, like wealth or intelligence, that are also associated with college attendance.
(B) Someone who attends graduate school will be rich.
(C) Someone who attends graduate school will earn more money than someone who does not.
(D) Someone who attends college will earn more money than someone who does not attend college.
(E) Someone who attends college will earn more money only because she does attend college.
5) According to the author, Professor Walker believes that
(A) women who toe out age more rapidly than women who do not
(B) most women toe out as they grow older because age increases the angle between the feet
(C) older women tend to walk with a greater angle between the feet
(D) toeing out is the reason why women grow old
(E) a causal relationship must exist whenever two things vary together
6) The author would reject all the following statements about cause-effect relationships as explanations for the statistics that show an increase in cancer rates EXCEPT that the
(A) Ceylonese drink more milk than the English
(B) Swiss produce and consume large quantities of dairy products
(C) Women of New England drink more milk than the women who live in some states of the southern United States
(D) People of Wisconsin have relatively high life expectancies
(E) People who live in some states of the southern United States have relatively high life expectancies
7) How would the author be most likely to explain the correlation between the “salaries of California school teachers [and the] profits of Nevada gambling halls” (Lines 63-64)?
(A) There is a positive correlation that is probably due to California teachers’ working in Las Vegas on weekends to increase both their salaries and increase both their salaries and Nevada’s gambling profits.
(B) There is a positive correlation that is probably linked to general economic trends, but no direct causal relationship exists.
(C) There is a negative correlation that is probably linked to general economic trends, but no direct causal relationship exists.
(D) There is a negative correlation because the element that controls Las Vegas gambling probably has agents in the California school system.
(E) The author would deny the existence of any correlation whatsoever.
A little digging might uncover quite a number of ways to account for these figures, but one factor is enough by itself to show them up. Cancer is predominantly a disease that strikes in middle life or after. Switzerland and the states of the United States mentioned first are alike in having populations with relatively long spans of life. English women at the time the study was made were living an average of twelve years longer than Japanese women.
Professor Helen M. Walker has worked out an amusing illustration of the folly in assuming there must be cause and effect whenever two things vary together. In investigating the relationship between age and some physical characteristics of women, begin by measuring the angle of the feet in walking. You will find that the angle tends to be greater among older women. You might first consider whether this indicates that women grow older because they toe out, and you can see immediately that this is ridiculous. So it appears that age increases the angle between the feet, and most women must come to toe out more as they grow older.
Any such conclusion is probably false and certainly unwarranted. You could only reach it legitimately by studying the same women—or possibly equivalent groups—over a period of time. That would eliminate the factor responsible here, which is that the older women grew up at a time when a young lady was taught to toe out in walking, while the members of the younger group were learning posture in a day when that was discouraged.
When you find somebody—usually an interested party—making a fuss about a correlation, look first of all to see if it is not one of this type, produced by the stream of events, the trend of the times. In our time it is easy to show a positive correlation between any pair of things like these: number of students in college, number of inmates in mental institutions, consumption of cigarettes, incidence of heart disease, use of X-ray machines, production of false teeth, salaries of California school teachers, profits of Nevada gambling halls. To call some one of these the cause of some other is manifestly silly. But it is done every day.
1) The author’s conclusion about the relationship between age and the ways women walk indicates he believes that
(A) toeing out is associated with aging
(B) toeing out is fashionable with the younger generation
(C) toeing out was fashionable for an older generation
(D) studying equivalent groups proves that toeing out increases with age
(E) studying the same women over a period of time proves that toeing out increases with age
2) The author describes the posited relationship between toeing out and age (lines 29-40) in order to
(A) illustrate a folly
(B) show how social attitudes toward posture change
(C) explain the effects of aging
(D) illustrate a medical problem
(E) offer a method to determine a woman’s age from her footprints
3) Given the author’s statements in the passage, his advice for evaluating statistics that show a high positive correlation between two conditions could include all the following statements EXCEPT
(A) look for an explanation in the stream of events
(B) consider some trend of the times as the possible cause of both conditions
(C) account for the correlations in some way other than causality
(D) determine which of the two conditions is the cause and which is the effect
(E) decide whether the conclusions have been reached legitimately and the appropriate groupings have been made
4) Assume that there is a high statistical correlation between college attendance and individual earnings. Given this, the author would most probably agree with which one of the following statements about the cause-effect relationship between college attendance and income?
(A) Someone’s potential earnings may be affected by other variables, like wealth or intelligence, that are also associated with college attendance.
(B) Someone who attends graduate school will be rich.
(C) Someone who attends graduate school will earn more money than someone who does not.
(D) Someone who attends college will earn more money than someone who does not attend college.
(E) Someone who attends college will earn more money only because she does attend college.
5) According to the author, Professor Walker believes that
(A) women who toe out age more rapidly than women who do not
(B) most women toe out as they grow older because age increases the angle between the feet
(C) older women tend to walk with a greater angle between the feet
(D) toeing out is the reason why women grow old
(E) a causal relationship must exist whenever two things vary together
6) The author would reject all the following statements about cause-effect relationships as explanations for the statistics that show an increase in cancer rates EXCEPT that the
(A) Ceylonese drink more milk than the English
(B) Swiss produce and consume large quantities of dairy products
(C) Women of New England drink more milk than the women who live in some states of the southern United States
(D) People of Wisconsin have relatively high life expectancies
(E) People who live in some states of the southern United States have relatively high life expectancies
7) How would the author be most likely to explain the correlation between the “salaries of California school teachers [and the] profits of Nevada gambling halls” (Lines 63-64)?
(A) There is a positive correlation that is probably due to California teachers’ working in Las Vegas on weekends to increase both their salaries and increase both their salaries and Nevada’s gambling profits.
(B) There is a positive correlation that is probably linked to general economic trends, but no direct causal relationship exists.
(C) There is a negative correlation that is probably linked to general economic trends, but no direct causal relationship exists.
(D) There is a negative correlation because the element that controls Las Vegas gambling probably has agents in the California school system.
(E) The author would deny the existence of any correlation whatsoever.
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