OCR Further Statistics 2024 June — Question 2 9 marks

Exam BoardOCR
ModuleFurther Statistics (Further Statistics)
Year2024
SessionJune
Marks9
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicHypothesis test of Pearson’s product-moment correlation coefficient
TypeCalculate PMCC from summary statistics
DifficultyStandard +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.
Spec5.08a Pearson correlation: calculate pmcc5.08d Hypothesis test: Pearson correlation

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 \(d\). \(\mathrm { n } = 16 \quad \sum \mathrm {~h} = 2880 \quad \sum \mathrm {~d} = 660 \quad \sum \mathrm {~h} ^ { 2 } = 519276 \quad \sum \mathrm {~d} ^ { 2 } = 30000 \quad \sum \mathrm { hd } = 119425\)
  1. Calculate the value of Pearson's product moment correlation coefficient for the data.
  2. State what your answer tells you about a scatter diagram illustrating the data.
  3. Use the data to test, at the \(5 \%\) significance level, the claim of the newspaper article.
  4. Explain whether the answer to part (a) would be likely to be different if the dogs' weights had been used instead of their heights.

Question 2:
AnswerMarks Guidance
2(a) 0.401 (0.400863)
[2]1.1
1.1Awrt 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)
AnswerMarks 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”.
AnswerMarks
(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
AnswerMarks
shoulder heightB2
B1
M1ft
A1ft
AnswerMarks
[5]1.1
2.5
1.1
1.1
AnswerMarks
2.2bAllow 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)
AnswerMarks
(d)Different as shoulder height → weight not a
linear transformation, or “probably similar as
AnswerMarks Guidance
taller dogs weigh more”, etcB1
[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.
AnswerMarks Guidance
Their hypothesesComment Mark
H : ρ = 0, H : ρ > 0, where ρ is the population pmcc
AnswerMarks Guidance
0 1Correct B2
H : r = 0, H : r > 0, where r is the pmcc between heights of students and dogs
AnswerMarks Guidance
0 1Correct, allow r B2
H : ρ = 0, H : ρ > 0, where  is the pmcc
AnswerMarks Guidance
0 1Both “population” and context omitted B1
H : ρ = 0, H : ρ  0, where  is the pmcc
AnswerMarks Guidance
0 1Two errors B0
H : no correlation between dog owner’s height and dog’s height, H : positive correlation
AnswerMarks Guidance
0 1Correct B2
H : no correlation between dog owner’s height and dog’s height, H : there is correlation
AnswerMarks Guidance
0 1“Positive” omitted B1
H : taller dog owners do not have taller dogs, H : taller dog owners have taller dogs
AnswerMarks Guidance
0 1As on MS B1
H : dog owner’s height and dog’s height independent, H : not independent
AnswerMarks Guidance
0 1Allow this B2
Their conclusionComments Mark
Accept H . Insufficient evidence of correlation between heights
AnswerMarks
0Correct, allow “accept H ”.
0M1A1
There is insufficient evidence of correlation
[Condone omission of “do not reject H ”]
AnswerMarks Guidance
0No context. M1A0
Do not reject H . There is significant evidence that there is no correlation between the heights
AnswerMarks Guidance
0Wrong M1A0
Do not reject H . The mean reading age is 10.75 in this district
AnswerMarks Guidance
0Too assertive M1A0
There is insufficient evidence to reject H . Taller students do not have taller dogs
AnswerMarks Guidance
0BOD M1A1
Unlikely as this is linear codingB0
Unlikely as weight is proportional to heightB0
No as taller dogs have greater weightB0
Not likely to be different: weight is just as random as heightB0
Probably, because taller owners probably have heavier dogsB0
Little to no difference as weight has some dependence on height,
AnswerMarks Guidance
so this is linear codingB0
Probably be different, as heavier dogs need stronger ownersB0
Quite similar because height & weight are correlatedB1
Would be similar as tall dogs are heavier but hard to tellB1
Weight proportional to height3 so PMCC would be largerB1
Probably not very different as tall dogs weigh moreB1
Height & weight correlated so r similar but weakerB1
Not much different as weight is often proportional to heightB1
Unclear as weight and height are correlated but hard to tellB1
QuestionAnswer 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]}}