| Exam Board | OCR MEI |
|---|---|
| Module | Further Statistics Minor (Further Statistics Minor) |
| Year | 2023 |
| Session | June |
| Marks | 10 |
| Paper | Download PDF ↗ |
| Mark scheme | Download PDF ↗ |
| Topic | Hypothesis test of Spearman’s rank correlation coefficien |
| Type | Hypothesis test for association |
| Difficulty | Standard +0.3 This is a straightforward application of Spearman's rank correlation coefficient with standard steps: identifying why Pearson's is inappropriate (likely one outlier visible in scatter diagram), ranking data, calculating rs using the formula, and performing a one-tailed hypothesis test using critical values from tables. All steps are routine for Further Statistics students with no novel problem-solving required. |
| Spec | 5.08e Spearman rank correlation5.08f Hypothesis test: Spearman rank5.08g Compare: Pearson vs Spearman |
| Competitor | A | B | C | D | E | F | G | H |
| Sawing | 17.1 | 16.7 | 14.3 | 14.0 | 12.8 | 21.5 | 15.3 | 14.4 |
| Chopping | 23.5 | 20.6 | 21.9 | 18.8 | 21.5 | 24.8 | 19.7 | 19.3 |
| Answer | Marks | Guidance |
|---|---|---|
| 6 | (a) | Because the scatter diagram does not appear to be |
| Answer | Marks |
|---|---|
| Normal. | E1 |
| Answer | Marks |
|---|---|
| [2] | 3.5a |
| 2.4 | For not elliptical. |
| Answer | Marks | Guidance |
|---|---|---|
| 6 | (b) | Rank saw 7 6 3 2 1 8 5 4 |
| Answer | Marks |
|---|---|
| 42 | M1 |
| Answer | Marks |
|---|---|
| [3] | 1.1 |
| Answer | Marks |
|---|---|
| 1.1 | For ranking saw or chop correctly |
| Answer | Marks | Guidance |
|---|---|---|
| 6 | (c) | H : There is no association between sawing and chopping |
| Answer | Marks |
|---|---|
| times (in the population) | B1 B1 |
| Answer | Marks |
|---|---|
| [5] | 3.3 |
| Answer | Marks |
|---|---|
| 2.2b | For first B1 need to see one correct hypothesis with context |
| Answer | Marks | Guidance |
|---|---|---|
| Rank saw | 7 | 6 |
| Rank chop | 7 | 4 |
| 𝑑2 | 0 | 4 |
Question 6:
6 | (a) | Because the scatter diagram does not appear to be
elliptical (due to the possible outlier)
so the (underlying) distribution is (probably) not bivariate
Normal. | E1
E1
[2] | 3.5a
2.4 | For not elliptical.
Alternatively, ‘the points appear to be funnel-shaped’
For full answer (dependent on first mark)
“data is not bivariate Normal” is E0
“Normal bivariate” is E0
6 | (b) | Rank saw 7 6 3 2 1 8 5 4
Rank chop 7 4 6 1 5 8 3 2
𝑑2 0 4 9 1 16 0 4 4
23
Spearman’s rank coefficient or 0.5476
42 | M1
depM1
A1
[3] | 1.1
1.1
1.1 | For ranking saw or chop correctly
For ranking saw and chop consistently (i.e. same way
round) with at most one adjacent pair of ranks transposed.
If rankings not seen they may be inferred from correct
𝑑 or 𝑑2 values or ∑𝑑2 = 38 seen
Accept 0.55 or better.
SC B1 only if 0.5476 stated with no working.
6 | (c) | H : There is no association between sawing and chopping
0
(times) in the population
H : There is positive association between sawing and
1
chopping (times) in the population
Critical value 0.6429
0.5476 < 0.6429 (so do not reject H /accept H )
0 0
There is insufficient evidence to suggest that there is
positive association between sawing and chopping
times (in the population) | B1 B1
B1
M1
A1FT
[5] | 3.3
1.2
3.4
1.1
2.2b | For first B1 need to see one correct hypothesis with context
(need not have population at this point).
For B1B1 need to see two correct hypotheses with each of
context and population in at least one of the hypotheses.
n = 8, 5%, 1-tailed
For comparison provided 0 < 𝑟 < 1
𝑠
FT their r and sensible critical value from correct table
s
A0 for “(Sufficient evidence to suggest) no association”.
Needs to include context.
Rank saw | 7 | 6 | 3 | 2 | 1 | 8 | 5 | 4
Rank chop | 7 | 4 | 6 | 1 | 5 | 8 | 3 | 2
𝑑2 | 0 | 4 | 9 | 1 | 16 | 0 | 4 | 4
6 Each competitor in a lumberjacking competition has to perform various disciplines for which they are timed. A spectator thinks that the times for two of the disciplines, chopping wood and sawing wood, are related. The table and the scatter diagram below show the times of a random sample of 8 competitors in these two disciplines.
\begin{center}
\begin{tabular}{ | l | c | c | c | c | c | c | c | c | }
\hline
Competitor & A & B & C & D & E & F & G & H \\
\hline
Sawing & 17.1 & 16.7 & 14.3 & 14.0 & 12.8 & 21.5 & 15.3 & 14.4 \\
\hline
Chopping & 23.5 & 20.6 & 21.9 & 18.8 & 21.5 & 24.8 & 19.7 & 19.3 \\
\hline
\end{tabular}
\end{center}
\includegraphics[max width=\textwidth, alt={}, center]{72215d69-c3e6-492d-bb3e-bdc28aeb4613-6_786_1130_708_239}
\begin{enumerate}[label=(\alph*)]
\item The spectator decides to carry out a hypothesis test to investigate whether there is any relationship.
Explain why the spectator decides that a test based on Pearson's product moment correlation coefficient may not be valid.
\item Determine the value of Spearman's rank correlation coefficient.
\item Carry out a hypothesis test at the $5 \%$ significance level to investigate whether there is positive association between sawing and chopping times.
\end{enumerate}
\hfill \mbox{\textit{OCR MEI Further Statistics Minor 2023 Q6 [10]}}