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jack5397
Joined: 13 Sep 2020
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The numbers of December comments; the numbers of years since the films were first released: Positive Correlation
The numbers of November comments; the numbers of December comments: Positive Correlation
The numbers of December comments; the combined-total numbers of November and December comments: Positive Correlation
Be sure to select an answer first to save it in the Error Log before revealing the correct answer (OA)!
Difficulty:
95%
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Question Stats:
49% (02:05) correct
51%
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wrong
based on 786
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The table provides some data regarding a film discussion website. For each film about which comments were first posted on the website in November, the table indicates the year in which the film was first released, the country in which it was produced, the number of comments about that film posted on the website in November, in December, and in November and December combined.
Based on the table, for each pair of sets of values described below, select Positive correlation if there is a positive correlation between the two sets of values. Otherwise, select Not a positive correlation.
GMAT-Club-Forum-5qncqrmd.png [ 240.67 KiB | Viewed 3747 times ]
| Film | Year first released | Produced in (country) | November comments | December comments | November and December comments (combined total) |
|---|---|---|---|---|---|
| Aaltra | 2004 | Belgium | 1 | 0 | 1 |
| Atanarjuat | 2001 | Canada | 3 | 0 | 3 |
| Chi Bi | 2008 | China | 1 | 1 | 2 |
| Chun can | 1933 | China | 5 | 4 | 9 |
| Dosti | 1964 | India | 4 | 3 | 7 |
| l! diavoio | 1963 | Italy | 1 | 0 | 1 |
| Lad ri di saponette | 1989 | Italy | 2 | 1 | 3 |
| Le placard | 2001 | France | 2 | 1 | 3 |
| Mababangong Bangungot | 1977 | Philippine | 2 | 2 | 4 |
| Mera Naam Joker | 1970 | India | 3 | 2 | 5 |
| Nosferatu | 1922 | Germany | 4 | 5 | 9 |
| Pauline à la plage | 1983 | France | 1 | 1 | 2 |
| Peau d'âne | 1970 | France | 1 | 0 | 1 |
| Swing! | 1938 | United States | 2 | 3 | 5 |
| The Boy and the Bridge | 1959 | United Kingdom | 1 | 3 | 4 |
| The Long, Long Trailer | 1953 | United States | 1 | 1 | 2 |
| Ugetsu | 1953 | Japan | 6 | 7 | 13 |
| Yasha-ga-ike | 1979 | Japan | 1 | 1 | 2 |
Based on the table, for each pair of sets of values described below, select Positive correlation if there is a positive correlation between the two sets of values. Otherwise, select Not a positive correlation.
Attachment:
GMAT-Club-Forum-5qncqrmd.png [ 240.67 KiB | Viewed 3747 times ]
| Positive Correlation | Not a positive correlation | |
| The numbers of December comments; the numbers of years since the films were first released | ||
| The numbers of November comments; the numbers of December comments | ||
| The numbers of December comments; the combined-total numbers of November and December comments |
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Official Answer
The numbers of December comments; the numbers of years since the films were first released: Positive Correlation
The numbers of November comments; the numbers of December comments: Positive Correlation
The numbers of December comments; the combined-total numbers of November and December comments: Positive Correlation
30 Sep 2024, 06:20
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EXPLANATION:
Background - on GMAT, as a rule of thumb, I just look for general correlation and not really a statistical formula applied to it. This idea of correlation has generally worked for me, and I would summarize it as "if one quantity increases, the other quantity should generally increase" for two quantities to be positively correlated. This does not necessarily mean that every quantity should increase. I would recommend practicing correlation problems specifically in order to develop that judgment.
(I am not trying to dumb it down - I am just saying that it is impractical to actually use the statistical formula for correlation on the GMAT. My approach may yield a false positive.)
Question 1 -
This is tricky phrasing until you read it carefully. It is basically asking for the correlation between years since the movie was released with the number of December comments. Normally you would just sort the "year of release" and see that the lower years of release correspond with the higher number of December comments, and think that this is a negative correlation. This would make you mark "not a positive correlation". However, we need to look at it in the opposite way.
Reason: the number of years since a film is released is longer for the smaller "years" because we are looking at dates. Older releases that happened in the 1900s have been released for a longer time than newer releases in the 2000s. This makes the correlation with the December comments positive. In other words, films released in 2000s have fewer December comments, and have been released for fewer years than films released in the 1900s.
Question 2 and Question 3 -
Generally, as the November comments are increasing, December comments are increasing too. Same as December and November-December combined.
Hence all three are positively correlated.
(If you have doubts, you can actually go through with the number crunching on Excel and figure out the actual correlation, and on the GMAT it will always work out right. But there is no way that the GMAT wants to test you on that. It just needs you to be able to reasonably get insights out of the presented data through quick, sharp statistical mental math)
Background - on GMAT, as a rule of thumb, I just look for general correlation and not really a statistical formula applied to it. This idea of correlation has generally worked for me, and I would summarize it as "if one quantity increases, the other quantity should generally increase" for two quantities to be positively correlated. This does not necessarily mean that every quantity should increase. I would recommend practicing correlation problems specifically in order to develop that judgment.
(I am not trying to dumb it down - I am just saying that it is impractical to actually use the statistical formula for correlation on the GMAT. My approach may yield a false positive.)
Question 1 -
This is tricky phrasing until you read it carefully. It is basically asking for the correlation between years since the movie was released with the number of December comments. Normally you would just sort the "year of release" and see that the lower years of release correspond with the higher number of December comments, and think that this is a negative correlation. This would make you mark "not a positive correlation". However, we need to look at it in the opposite way.
Reason: the number of years since a film is released is longer for the smaller "years" because we are looking at dates. Older releases that happened in the 1900s have been released for a longer time than newer releases in the 2000s. This makes the correlation with the December comments positive. In other words, films released in 2000s have fewer December comments, and have been released for fewer years than films released in the 1900s.
Question 2 and Question 3 -
Generally, as the November comments are increasing, December comments are increasing too. Same as December and November-December combined.
Hence all three are positively correlated.
(If you have doubts, you can actually go through with the number crunching on Excel and figure out the actual correlation, and on the GMAT it will always work out right. But there is no way that the GMAT wants to test you on that. It just needs you to be able to reasonably get insights out of the presented data through quick, sharp statistical mental math)
13 May 2024, 07:54
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What I've learnt is that a positive correlation doesnt imply a directly proportional relationship.
In simple terms what that means is that not every increase in X requires an increase in Y for the two to be positively correlated.
We look at the bigger picture here. If we plot a scatter plot graph between the two factors and then draw a trend line on said graph we can see the positive correlation between the facotrs.
Basically if for a majority of points Y increases as X increases then the two are positively correlated and we can ignore the outliers.
In simple terms what that means is that not every increase in X requires an increase in Y for the two to be positively correlated.
We look at the bigger picture here. If we plot a scatter plot graph between the two factors and then draw a trend line on said graph we can see the positive correlation between the facotrs.
Basically if for a majority of points Y increases as X increases then the two are positively correlated and we can ignore the outliers.
