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655-705 Level|   Non-Math Related|   Word Problems|               
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kop18
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­The table shows the sales forecast from January to June of last year 02 Jul 2024, 18:15
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I agree with karishma B - There's nothing in the question that would indicate the line is +/-. It says there's a linear correlation in the actual vs forecast.
If I use statement A and try to plot all the values in a negative slope I do find it a little difficult to perfectly make a negative line but again that would still make my answer C not B.

GMATCoachBen Please could you post the official explanation.
GMATNinja Bunuel could u please help­
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­The table shows the sales forecast from January to June of last year 10 Jul 2024, 00:52
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Any update on this Q, why a negative slope is not possible?
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­The table shows the sales forecast from January to June of last year 16 Jul 2024, 14:43
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I think the key here is: does the "constant linear relationship" means it cannot be y=kx+b, but only y=kx?­ Can anyone help to confirm this? 
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­The table shows the sales forecast from January to June of last year 20 Aug 2024, 10:06
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OG solution

This statement tells us only the actual number of units sold in March but nothing about the actual number of units sold in April. If the actual sales varied from the forecast sales in a random way from month to month, then it is possible that March’s sales were less than, more than, or the same as April’s sales; NOT sufficient.

Because this statement tells us that there is an unchanging linear relationship between the forecast and the actual number of units of Product Z sold through the months given in the graph, we know that for any month X given in the graph, if another month Y was forecast to have lower sales than X, then the actual sales of Y were lower than the sales of X. Therefore, since the forecast for units sold for March was lower than the forecast for units sold for April, then the actual sales for March were lower than the actual sales for April; SUFFICIENT.
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­The table shows the sales forecast from January to June of last year 29 Sep 2024, 20:04
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Hi karishma,

Even in that case won't answer just change from "Yes" to "No". But it's still a definitive answer I believe..
KarishmaB
KarishmaB

manasp35
How about Actual + Forecast = 28 ?

Is this a constant linear relationship ?

KarishmaB can you please help




I don't understand the term "constant linear relationship". I would have taken it as a linear relation and since a line can have positive or negative slope, I would have marked the answer here as (E). If it is used in certain specific curricula this way, then I don't know about it.

y = kx is a direct relation.

­
­Further explanation of this upon request:

A "linear relationship" is a line. When I say x and y have a linear relation, it represents a line on the xy axis. i.e. y = mx + c

I do not understand what is meant by a "constant linear relationship". I would just take it as a line i.e. a linear relationship.
I would not think that it means y = mx. As I mentioned before, if there is some particular curriculum in which a constant linear relationship means "y = mx" then I do not know. But a google search did not give any such information. So I doubt many people would equate "constant linear relationship" to y = Constant * x and hence the question would not pass the GMAT filter.

We know that y = constant * x is direct variation and I would look for that term to arrive at the conclusion that I have to use that relation here.

Hence, in this question, as given, this is what I imagine is also possible:
Attachment:
Screenshot 2024-04-05 at 5.05.49 PM.png

Hence it is possible that the actual number of units sold in April is less than the number sold in March even using the data from both statements.

Hence my answer here would be (E).
­
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­The table shows the sales forecast from January to June of last year 13 Oct 2024, 08:38
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i think that the question has some problems here. Like KarishmaB was saying a linear relationship might be negative or positive (depending on the sign of the angular coefficient of the line)
infact i answered E. and i'm pretty sure that should be the right answer

forecastactual
march16a
april20b
is a-b <0?

statement 1 x= 12 clearly not sufficient

statement 2
we know that
unit sold = K * unit forecasted + Q

now we know that plugging the number in the table
a = K * 16 + Q
b = K * 20 + Q

let's make the difference between the 2 equations, we get:


a-b = K * 16 - K * 20 = -4*K

thus a-b will be greater than zero if K<0 (negative relationship)
and a-b will be less than zero if K>0 (positive relationship)

THUS it is not sufficient.


statement 1 and 2 together do not help in any way. INFACT the only thing that taking both together is doing, is giving us a POINT (the actual and forecasted values in MARCH) on a LINE (the linear relationship). and we know that through a point pass a INFINITE number of LINES. thus neither both statement together can be used to check if the relation is positive or negative.
answer E IMO


Bunuel, can you please check if my line of reasoning makes sense?
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­The table shows the sales forecast from January to June of last year 08 Nov 2024, 03:17
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guys, we need to note that "no" is also an answer.

Although option 2 only indicates a linear relationship

in the first case, where there is a positive correlation, you can answer the question "was... less than?" with "yes."

In the second case, if there is a negative correlation, your answer would be "no."

Whether positive or negative, each scenario provides only one definitive answer, so option B is sufficient.
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­The table shows the sales forecast from January to June of last year 28 Nov 2024, 05:27
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KarishmaB
KarishmaB

I don't understand the term "constant linear relationship". I would have taken it as a linear relation and since a line can have positive or negative slope, I would have marked the answer here as (E). If it is used in certain specific curricula this way, then I don't know about it.

y = kx is a direct relation.

­
­Further explanation of this upon request:

A "linear relationship" is a line. When I say x and y have a linear relation, it represents a line on the xy axis. i.e. y = mx + c

I do not understand what is meant by a "constant linear relationship". I would just take it as a line i.e. a linear relationship.
I would not think that it means y = mx. As I mentioned before, if there is some particular curriculum in which a constant linear relationship means "y = mx" then I do not know. But a google search did not give any such information. So I doubt many people would equate "constant linear relationship" to y = Constant * x and hence the question would not pass the GMAT filter.

We know that y = constant * x is direct variation and I would look for that term to arrive at the conclusion that I have to use that relation here.

Hence, in this question, as given, this is what I imagine is also possible:
Attachment:
Screenshot 2024-04-05 at 5.05.49 PM.png

Hence it is possible that the actual number of units sold in April is less than the number sold in March even using the data from both statements.

Hence my answer here would be (E).
­
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Hi Karishma,

I dont think your graph is correct.

12 = k 16
then k would be 3/4
and for 20 it will be 15 which is higher than 12.

for graph to have negative slope , k should be -ve right?
But, since these are real items -ve doesnt work?

I could be wrong and missing something.
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­The table shows the sales forecast from January to June of last year 29 Nov 2024, 12:00
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Given the brevity of information provided the answer to this question should be (E). I don't know why the questions has not been corrected when so many users have pointed out an obvious flaw.
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­The table shows the sales forecast from January to June of last year 29 Nov 2024, 19:03
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Jaffer99
Given the brevity of information provided the answer to this question should be (E). I don't know why the questions has not been corrected when so many users have pointed out an obvious flaw.
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How can it be E?
You need k to be -ve to have a slanting slope right? Y=kx+c

Even if k is between 0 and 1. The values are reducing in same direction.

But, these are items and actual and predicted can’t have a negative relationship.

Maybe I’m missing something obvious here. Bunuel could you please weigh in?
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­The table shows the sales forecast from January to June of last year 30 Nov 2024, 10:44
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They for sure can if the negative relationship is bound to the first quadrant in a graph. This is possible.

Adarsh_24
Jaffer99
Given the brevity of information provided the answer to this question should be (E). I don't know why the questions has not been corrected when so many users have pointed out an obvious flaw.
How can it be E?
You need k to be -ve to have a slanting slope right? Y=kx+c

Even if k is between 0 and 1. The values are reducing in same direction.

But, these are items and actual and predicted can’t have a negative relationship.

Maybe I’m missing something obvious here. Bunuel could you please weigh in?
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­The table shows the sales forecast from January to June of last year 30 Nov 2024, 19:30
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Jaffer99
They for sure can if the negative relationship is bound to the first quadrant in a graph. This is possible.

Adarsh_24
Jaffer99
Given the brevity of information provided the answer to this question should be (E). I don't know why the questions has not been corrected when so many users have pointed out an obvious flaw.
How can it be E?
You need k to be -ve to have a slanting slope right? Y=kx+c

Even if k is between 0 and 1. The values are reducing in same direction.

But, these are items and actual and predicted can’t have a negative relationship.

Maybe I’m missing something obvious here. Bunuel could you please weigh in?
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How so?
One year 20 items predicted. How can actual be -ve items in reality?
Unless I’m missing something.
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­The table shows the sales forecast from January to June of last year 01 Dec 2024, 12:53
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Adarsh_24
Mate it could be the following case: January predicted is 12 and sold is 15, February predicted is 16 and sold is 14, March predicted is 16 and sold is 12, April predicted is 20 and sold is 9 ,May predicted is 20 and sold is 6, June predicted is 24 and sold is 2.
In this given case none of the values are actually negative however if you were to use these values to compute the gradient then it would indeed be negative. Also notice how all these values would be negatively correlated but also in the first quadrant. This is completely possible as statement 2 does not say if the relationship is positive and linear. Hence, you can't just guess that it is.
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­The table shows the sales forecast from January to June of last year 01 Dec 2024, 20:15
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Jaffer99
Adarsh_24
Mate it could be the following case: January predicted is 12 and sold is 15, February predicted is 16 and sold is 14, March predicted is 16 and sold is 12, April predicted is 20 and sold is 9 ,May predicted is 20 and sold is 6, June predicted is 24 and sold is 2.
In this given case none of the values are actually negative however if you were to use these values to compute the gradient then it would indeed be negative. Also notice how all these values would be negatively correlated but also in the first quadrant. This is completely possible as statement 2 does not say if the relationship is positive and linear. Hence, you can't just guess that it is.
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Ok I see your point. Thanks.
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­The table shows the sales forecast from January to June of last year 22 Dec 2024, 23:10
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I never said that the products sold are in negative, I am talking about negative coorelation.

Anyway looking at the discussion there is still some misunderstanding about the question.
Thanks for the reply tho.
Bisleri
Ayushi0002
Can the linear constant also lead to negative coorelation between the Actual VS Predicted sold products?
­No,

Number of Products sold can never be negative.
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­The table shows the sales forecast from January to June of last year 03 Jan 2025, 10:02
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But the constant can also be negative.
GMATCoachBen

Ayushi0002
Can the linear constant also lead to negative coorelation between the Actual VS Predicted sold products?
­No, this wording and context implies a positive correlation, where Actual = (Some Constant) * (Predicted)
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­The table shows the sales forecast from January to June of last year 17 May 2025, 16:56
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Can someone please help with option B? I understand that it says the relationship is linear from January to June but individual months can vary yet still have the same linear trajectory?
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­The table shows the sales forecast from January to June of last year 20 May 2025, 03:20
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How i interpreted it is it is in linear correlation with forecast so if forecast increases so does actual.
so in that case we can be sure April > March

GMATCoachBen
­
The table shows the sales forecast from January to June of last year, by the sales team of Company X, for the number of units of Product Z each month.

Was the actual number of units of Product Z sold in March less than the number sold in April?

(1) Twelve units of Product Z were sold in March.

(2) From January through June of last year, there was a constant, linear relationship between the forecast and actual number of units of Product Z sold.­

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­The table shows the sales forecast from January to June of last year 04 Jun 2025, 01:06
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How does the wording and context imply a positive correlation?
GMATCoachBen

Ayushi0002
Can the linear constant also lead to negative coorelation between the Actual VS Predicted sold products?
­No, this wording and context implies a positive correlation, where Actual = (Some Constant) * (Predicted)
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­The table shows the sales forecast from January to June of last year 13 Jun 2025, 21:54
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