A survey of workers' well-being grouped respondents according to

Question

A survey of workers' well-being grouped respondents according to occupation. For each occupation, the table shows the percentages of respondents who indicated feeling satisfaction in their occupation, being in a positive mood with respect to their occupation at the time of the survey, and having a sense of purpose in their occupation.

For each of the following statements, select  Yes  if the information provided indicates that the statement is correct. Otherwise, select  No .

Occupation  
  Satisfaction  
  Positive mood  
  Purpose  
 
  2 
 76% 
 39% 
 74% 
 
  4 
 63% 
 39% 
 74% 
 
  5 
 55% 
 60% 
 46% 
 
  3 
 53% 
 55% 
 55% 
 
  6 
 31% 
 80% 
 44% 
 
  1 
 30% 
 76% 
 39%

ID: 700247

egmat · Accepted Answer

This is surely a time saver question. So, make sure you know how to analyze a dataset to determine correlation. In addition, this question has a very important application of visualization of data to determine if there is overlap or not. Watch this solution especially for Statement 3 to get a refresher of this visualization. In essence – given a dataset, can you draw inferences about whether there is an overlap or not.

https://www.youtube.com/watch?v=vH8ZJmK9NQs

DivyaSharma26 · Answer

When satisfaction % goes from 53 to 55, the purpose % goes from 55 to 46. How are these positively correlated?

T4Star · Answer

There is a positive correlation between the percentages for satisfaction and those for purpose. -  Yes. We see a general trend that as the % for satisfaction increases, so does the % for purpose.

There is a negative correlation between the percentages for positive mood and purpose. -  Again, Yes. Same reasoning as first statement. As % for positive mood increases, the % for purpose decreases indicating negative correlation

A majority of all respondents who indicated feeling satisfaction also indicated having a sense of purpose.  No. It is not necessary that the same set of people who are satisfied also have a sense of purpose. For eg., in occupation 3, the 53% of people who are satisfied may be different from the 55% of people who have a sense of purpose.

_MUF__ · Answer

even i have the same question

should we look only at the majority ?
as most are positively corelated

Iwillget770 · Answer

Below is the Official Answer:-

RO1

Sorting the table by  Satisfaction  and looking at the corresponding values in the  Purpose  column shows a positive correlation between this pair of quantities.

The correct answer is  Yes .

RO2

Sorting the table by  Positive mood  and looking at the corresponding values in the  Purpose  column shows a negative correlation between this pair of quantities.

The correct answer is  Yes   .

RO3

Because the relative sizes of the groupings by occupation are not known and nothing is known about the sizes of the overlaps for the responses of “satisfaction” and “purpose”, it cannot be concluded that a majority of all respondents who indicated feeling satisfaction also indicated having a sense of purpose. For example, if 99% of all respondents belonged to Occupation 1 and for this occupation all 30% of those who indicated satisfaction were among the 61% who did not indicate having a sense of purpose, then it would NOT be correct that a majority of all respondents who indicated feeling satisfaction also indicated having a sense of purpose.

The correct answer is  No .

harshchougule · Answer

TBH this official answer gives no explaination.

akshatcy · Answer

Refer the below image. As you can see in the first case of positive correlation, some points drop during the increasing trend. But the trend line (red) shows a positive correlation. So if one value decreases during an increasing trend but most of the values are increasing, on a general note we consider it as positive correlation. Vice versa goes for the negative correlation. https://gmatclub.com/forum/download/file.php?id=82769 GMAT-Club-Forum-yz00aato.png

kanikaa9 · Answer

To identify correlation just make sure majority of the datasets are following correlation. Eg: Out of 6, 4 data points should show some correlation either positive or negative. So (1) and (2) is  YES

For statement (3) - we are not given that each occupation has same # of people so it could be the case that majority of the total respondents lie in occupations 1 and 6 and hence we are not sure. So answer to (3) is  NO

pinkman27 · Answer

can anybody explain part 3?

iampm1 · Answer

Yes

ShadeFlight · Answer

Postive corelation in GMAT terms means majority of the terms have the same 'trend'. I you have two columns and have taken a difference of their values (given the values are comparable of course) then majority (>50%) of those would have the same sign. It does not have to be absolute.

DivyaSharma26

When satisfaction % goes from 53 to 55, the purpose % goes from 55 to 46. How are these positively correlated?

socialsloth · Answer

Hi @ _MUF_ and DivyaSharma26 , I too had the same doubt, and I remembered another question - https://gmatclub.com/forum/the-table-li ... 19994.html So my understanding is - If the question mentions correlation, then Majority (>50%) values should adhere to the trend. If the question mention proportionality, then ALL the value should adhere AND have the same ratio. An @experts confirmation would be helpful.

egmat · Answer

Correlation describes a general tendency for two quantities to move together across many observations. We call it positive when Y tends to rise as X rises, and negative when Y tends to fall as X rises. The crucial word is tend. Correlation is a trend, not a law — it does not promise anything about any single case.
That's the most important distinction to hold onto: correlation is not the same as perfect correlation.

A  perfect relationship  would mean every increase in X comes with a matching, predictable increase in Y, every time. Real correlations almost never look like that. Instead, you see a cloud of points drifting in one direction, with plenty of individual exceptions scattered around it.

Those exceptions are not failures of the rule —  they're what makes it a correlation in the first place . They happen because an output usually depends on many inputs at once, not just one. Y might depend on A, B, C, and X together. So on any given occasion, X can go up while Y goes down, simply because one of the other factors moved at the same time and pulled harder. Across many observations those other influences tend to average out, and the underlying X–Y trend shows through.

Two refinements worth being precise about:

First, the  strength of a correlation  is about consistency, not step size. A strong correlation means the points hug the trend tightly with few exceptions; a weak one means they scatter loosely around it. This is separate from how much Y changes per unit of X. You can have a strong correlation with a gentle slope, or a weak one with a steep slope — strength and magnitude are two different things.

Second,  correlation does not establish causation.  Two things moving together tells you exactly that — they move together. It does not, on its own, tell you that one drives the other. They might both be driven by a third factor, or the link might be coincidence.

Two examples to illustrate this!!
 
- A positive correlation that's real but imperfect: study hours and test scores. Across a class, students who study more tend to score higher — a clear upward trend. But it isn't a straight line. A student who studied ten hours might score below one who studied six, because they were ill, or got a harder set of questions, or had already mastered the material. Those individual cases run against the trend without breaking it.

- A positive correlation that isn't causation: across a year, ice-cream sales and drowning incidents rise and fall together. Neither causes the other — a third factor, hot weather, drives both. This is the perfect illustration of the "Y depends on A, B, C and X" idea: when you watch only two variables, you can see them move together for reasons that have nothing to do with one causing the other.

Rhitib · Answer

For the first question it is Yes. Now most of you are asking why Yes when there is a one value negatively correlated.
Normally when we deal with % we see the majority. So one out of 6 is not going to define whether it is negatively correlated. If we plot a simple graph of this data, the graph will show a positive upward slope after a fit. And mostly the negative correlated point will not come on the fitting line.

Same goes with question 2, 4 out of 6 values are negative with one value same (55%), so the Graph will mostly show a negative slope. So yes negatively correlated. We have to take the majority for this question in both the cases.

Hope it helps

A survey of workers' well-being grouped respondents according to

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My Rewards

Occupation	Satisfaction	Positive mood	Purpose
2	76%	39%	74%
4	63%	39%	74%
5	55%	60%	46%
3	53%	55%	55%
6	31%	80%	44%
1	30%	76%	39%

Occupation	Satisfaction	Positive mood	Purpose
2	76%	39%	74%
4	63%	39%	74%
5	55%	60%	46%
3	53%	55%	55%
6	31%	80%	44%
1	30%	76%	39%

GMAT Graphs and Tables (G&T) Questions

A survey of workers' well-being grouped respondents according to

Prep Toolkit

615 to 715 in 15 Days (Ria's Strategies)

More than Quant/Verbal Abilities: Speed vs. Accuracy

745 with Only Self-Prep and GMAT Club

From 555 to 765: 210-point Improvement

Perfect 805 Score Debrief by Julia

My Rewards

Occupation	Satisfaction	Positive mood	Purpose
2	76%	39%	74%
4	63%	39%	74%
5	55%	60%	46%
3	53%	55%	55%
6	31%	80%	44%
1	30%	76%	39%