Standard +0.3 This is a straightforward Further Maths Statistics question requiring standard application of the PMCC formula with given summary statistics, followed by a routine hypothesis test. While it involves multiple parts and careful arithmetic, all steps are procedural with no novel insight required. The formula is given in the formula booklet, and the hypothesis test follows a standard template. Slightly above average difficulty only due to the arithmetic care needed and being a Further Maths topic.
2 A newspaper article claimed that "taller dog owners have taller dogs as pets". Alex investigated this claim and obtained data from a random sample of 16 fellow students who owned exactly one dog. The results are summarised as follows, where the height of the student, in cm, is denoted by \(h\) and the height, in cm, of their dog is denoted by \(d\).
\(\mathrm { n } = 16 \quad \sum \mathrm {~h} = 2880 \quad \sum \mathrm {~d} = 660 \quad \sum \mathrm {~h} ^ { 2 } = 519276 \quad \sum \mathrm {~d} ^ { 2 } = 30000 \quad \sum \mathrm { hd } = 119425\)
Calculate the value of Pearson's product moment correlation coefficient for the data.
State what your answer tells you about a scatter diagram illustrating the data.
Use the data to test, at the \(5 \%\) significance level, the claim of the newspaper article.
Explain whether the answer to part (a) would be likely to be different if the dogs' weights had been used instead of their heights.
Awrt 0.401. SC: If B0, give B1 for any two of 54.75, 173.4, 39.06 or
any two of 876, 2775, 625 seen, or for answer 0.4(00)
Answer
Marks
Guidance
(b)
Points do not lie very close to a (straight) line
B1
[1]
2.4
OE, e.g. “moderately scattered” or “vaguely linear”. Must be in terms
of diagram, not e.g. “weak correlation”. Not “not very close together”,
not “weak gradient”, not just “positively correlated”. Ignore
comments about ellipses or bivariate normal. Allow sketch if
reasonably appropriate. No wrong extras, e.g. “through origin”.
Answer
Marks
(c)
H : = 0, H : > 0, where is the population
0 1
pmcc between student’s height and dog’s height
or H : no correlation between dog owner’s
0
height and dog’s height, H : positive
1
correlation (B1 if “positive” omitted)
CV 0.4259 or p = 0.0619(32)
0.401 < 0.4259 or 0.062 > 0.05 so do not reject
H
0
Insufficient evidence that there is (positive)
correlation between student height and dog
Answer
Marks
shoulder height
B2
B1
M1ft
A1ft
Answer
Marks
[5]
1.1
2.5
1.1
1.1
Answer
Marks
2.2b
Allow ρ defined in terms of either population or context (or both).
Allow H : 0. Allow r. Needs “coefficient” or “pmcc” oe
0
One error, e.g. two-tailed, or not defined as above: B1.
H : taller dog owners do not have taller dogs, H : taller dog owners
0 1
have taller dogs: B1.
Allow “association”, allow “independent” (but needs 1-tail for B2)
Either, for p allow awrt 0.062. (Two-tailed CV 0.4973 is B0 here)
FT on their r if 0 < r < 1, and FT from 0.4973 but no other CV. Needs
like-with-like.
Contextualised, acknowledge uncertainty; not “there is evidence that
there is not positive correlation”. Don’t need “positive” here
(2-tailed test typically B1B0, B0, M1A1)
Answer
Marks
(d)
Different as shoulder height → weight not a
linear transformation, or “probably similar as
Answer
Marks
Guidance
taller dogs weigh more”, etc
B1
[1]
2.3
“Yes”, “Different”, “not very different”, “little difference”, “similar”
but no stronger, or “unclear”, with reason based on a (positive)
relationship between height and weight of dogs; nothing completely
wrong seen.
Not “No”, “unlikely”, “probably not different”, “little to no
difference”, etc. Not relationship between owners and weights.
Answer
Marks
Guidance
Their hypotheses
Comment
Mark
H : ρ = 0, H : ρ > 0, where ρ is the population pmcc
Answer
Marks
Guidance
0 1
Correct
B2
H : r = 0, H : r > 0, where r is the pmcc between heights of students and dogs
Answer
Marks
Guidance
0 1
Correct, allow r
B2
H : ρ = 0, H : ρ > 0, where is the pmcc
Answer
Marks
Guidance
0 1
Both “population” and context omitted
B1
H : ρ = 0, H : ρ 0, where is the pmcc
Answer
Marks
Guidance
0 1
Two errors
B0
H : no correlation between dog owner’s height and dog’s height, H : positive correlation
Answer
Marks
Guidance
0 1
Correct
B2
H : no correlation between dog owner’s height and dog’s height, H : there is correlation
Answer
Marks
Guidance
0 1
“Positive” omitted
B1
H : taller dog owners do not have taller dogs, H : taller dog owners have taller dogs
Answer
Marks
Guidance
0 1
As on MS
B1
H : dog owner’s height and dog’s height independent, H : not independent
Answer
Marks
Guidance
0 1
Allow this
B2
Their conclusion
Comments
Mark
Accept H . Insufficient evidence of correlation between heights
Answer
Marks
0
Correct, allow “accept H ”.
0
M1A1
There is insufficient evidence of correlation
[Condone omission of “do not reject H ”]
Answer
Marks
Guidance
0
No context.
M1A0
Do not reject H . There is significant evidence that there is no correlation between the heights
Answer
Marks
Guidance
0
Wrong
M1A0
Do not reject H . The mean reading age is 10.75 in this district
Answer
Marks
Guidance
0
Too assertive
M1A0
There is insufficient evidence to reject H . Taller students do not have taller dogs
Answer
Marks
Guidance
0
BOD
M1A1
Unlikely as this is linear coding
B0
Unlikely as weight is proportional to height
B0
No as taller dogs have greater weight
B0
Not likely to be different: weight is just as random as height
B0
Probably, because taller owners probably have heavier dogs
B0
Little to no difference as weight has some dependence on height,
Answer
Marks
Guidance
so this is linear coding
B0
Probably be different, as heavier dogs need stronger owners
B0
Quite similar because height & weight are correlated
B1
Would be similar as tall dogs are heavier but hard to tell
B1
Weight proportional to height3 so PMCC would be larger
B1
Probably not very different as tall dogs weigh more
B1
Height & weight correlated so r similar but weaker
B1
Not much different as weight is often proportional to height
B1
Unclear as weight and height are correlated but hard to tell
B1
Question
Answer
Marks
Question 2:
2 | (a) | 0.401 (0.400863) | B2
[2] | 1.1
1.1 | Awrt 0.401. SC: If B0, give B1 for any two of 54.75, 173.4, 39.06 or
any two of 876, 2775, 625 seen, or for answer 0.4(00)
(b) | Points do not lie very close to a (straight) line | B1
[1] | 2.4 | OE, e.g. “moderately scattered” or “vaguely linear”. Must be in terms
of diagram, not e.g. “weak correlation”. Not “not very close together”,
not “weak gradient”, not just “positively correlated”. Ignore
comments about ellipses or bivariate normal. Allow sketch if
reasonably appropriate. No wrong extras, e.g. “through origin”.
(c) | H : = 0, H : > 0, where is the population
0 1
pmcc between student’s height and dog’s height
or H : no correlation between dog owner’s
0
height and dog’s height, H : positive
1
correlation (B1 if “positive” omitted)
CV 0.4259 or p = 0.0619(32)
0.401 < 0.4259 or 0.062 > 0.05 so do not reject
H
0
Insufficient evidence that there is (positive)
correlation between student height and dog
shoulder height | B2
B1
M1ft
A1ft
[5] | 1.1
2.5
1.1
1.1
2.2b | Allow ρ defined in terms of either population or context (or both).
Allow H : 0. Allow r. Needs “coefficient” or “pmcc” oe
0
One error, e.g. two-tailed, or not defined as above: B1.
H : taller dog owners do not have taller dogs, H : taller dog owners
0 1
have taller dogs: B1.
Allow “association”, allow “independent” (but needs 1-tail for B2)
Either, for p allow awrt 0.062. (Two-tailed CV 0.4973 is B0 here)
FT on their r if 0 < r < 1, and FT from 0.4973 but no other CV. Needs
like-with-like.
Contextualised, acknowledge uncertainty; not “there is evidence that
there is not positive correlation”. Don’t need “positive” here
(2-tailed test typically B1B0, B0, M1A1)
(d) | Different as shoulder height → weight not a
linear transformation, or “probably similar as
taller dogs weigh more”, etc | B1
[1] | 2.3 | “Yes”, “Different”, “not very different”, “little difference”, “similar”
but no stronger, or “unclear”, with reason based on a (positive)
relationship between height and weight of dogs; nothing completely
wrong seen.
Not “No”, “unlikely”, “probably not different”, “little to no
difference”, etc. Not relationship between owners and weights.
Their hypotheses | Comment | Mark
H : ρ = 0, H : ρ > 0, where ρ is the population pmcc
0 1 | Correct | B2
H : r = 0, H : r > 0, where r is the pmcc between heights of students and dogs
0 1 | Correct, allow r | B2
H : ρ = 0, H : ρ > 0, where is the pmcc
0 1 | Both “population” and context omitted | B1
H : ρ = 0, H : ρ 0, where is the pmcc
0 1 | Two errors | B0
H : no correlation between dog owner’s height and dog’s height, H : positive correlation
0 1 | Correct | B2
H : no correlation between dog owner’s height and dog’s height, H : there is correlation
0 1 | “Positive” omitted | B1
H : taller dog owners do not have taller dogs, H : taller dog owners have taller dogs
0 1 | As on MS | B1
H : dog owner’s height and dog’s height independent, H : not independent
0 1 | Allow this | B2
Their conclusion | Comments | Mark
Accept H . Insufficient evidence of correlation between heights
0 | Correct, allow “accept H ”.
0 | M1A1
There is insufficient evidence of correlation
[Condone omission of “do not reject H ”]
0 | No context. | M1A0
Do not reject H . There is significant evidence that there is no correlation between the heights
0 | Wrong | M1A0
Do not reject H . The mean reading age is 10.75 in this district
0 | Too assertive | M1A0
There is insufficient evidence to reject H . Taller students do not have taller dogs
0 | BOD | M1A1
Unlikely as this is linear coding | B0
Unlikely as weight is proportional to height | B0
No as taller dogs have greater weight | B0
Not likely to be different: weight is just as random as height | B0
Probably, because taller owners probably have heavier dogs | B0
Little to no difference as weight has some dependence on height,
so this is linear coding | B0
Probably be different, as heavier dogs need stronger owners | B0
Quite similar because height & weight are correlated | B1
Would be similar as tall dogs are heavier but hard to tell | B1
Weight proportional to height3 so PMCC would be larger | B1
Probably not very different as tall dogs weigh more | B1
Height & weight correlated so r similar but weaker | B1
Not much different as weight is often proportional to height | B1
Unclear as weight and height are correlated but hard to tell | B1
Question | Answer | Marks | AO | Guidance
2 A newspaper article claimed that "taller dog owners have taller dogs as pets". Alex investigated this claim and obtained data from a random sample of 16 fellow students who owned exactly one dog. The results are summarised as follows, where the height of the student, in cm, is denoted by $h$ and the height, in cm, of their dog is denoted by $d$.\\
$\mathrm { n } = 16 \quad \sum \mathrm {~h} = 2880 \quad \sum \mathrm {~d} = 660 \quad \sum \mathrm {~h} ^ { 2 } = 519276 \quad \sum \mathrm {~d} ^ { 2 } = 30000 \quad \sum \mathrm { hd } = 119425$
\begin{enumerate}[label=(\alph*)]
\item Calculate the value of Pearson's product moment correlation coefficient for the data.
\item State what your answer tells you about a scatter diagram illustrating the data.
\item Use the data to test, at the $5 \%$ significance level, the claim of the newspaper article.
\item Explain whether the answer to part (a) would be likely to be different if the dogs' weights had been used instead of their heights.
\end{enumerate}
\hfill \mbox{\textit{OCR Further Statistics 2024 Q2 [9]}}