| Exam Board | CAIE |
|---|---|
| Module | FP2 (Further Pure Mathematics 2) |
| Year | 2018 |
| Session | November |
| Marks | 12 |
| Paper | Download PDF ↗ |
| Mark scheme | Download PDF ↗ |
| Topic | Linear regression |
| Type | Calculate x on y regression line |
| Difficulty | Standard +0.8 This is a multi-part regression question requiring systematic application of several formulas (finding means from regression equations, computing the second regression line, calculating correlation coefficient, and hypothesis testing). While conceptually straightforward for Further Maths students, it demands careful algebraic manipulation across multiple steps with opportunities for error propagation, placing it moderately above average difficulty. |
| Spec | 5.08a Pearson correlation: calculate pmcc5.08d Hypothesis test: Pearson correlation5.09c Calculate regression line |
| Answer | Marks | Guidance |
|---|---|---|
| 10(i) | x = (y – 1.1664) / 0.4604 = 11.02 or Σ x = 110.2 | M1 |
| Answer | Marks | Guidance |
|---|---|---|
| yy | M1 | Find S and S |
| Answer | Marks | Guidance |
|---|---|---|
| = 0.4604 × 205.576 / 50.304 = 1.88[15] | M1A1 | Find gradient b to 3 s.f. in x – x = b (y – y) |
| Answer | Marks | Guidance |
|---|---|---|
| xy yy | (M1A1) | |
| (x – 11.02) = b (y – 6.24), x = 1.88y – 0.721 | M1A1 | and hence eqn. of regression line of x on y |
| Answer | Marks |
|---|---|
| 10(ii) | r = S / √(S S ) = 94.647 / √(205.576 × 50.304) |
| Answer | Marks | Guidance |
|---|---|---|
| or √(0.4604 × b) = √(0.4604 × 1.8815) (AEF) | M1 | Find correlation coefficient r |
| = 0.931 | *A1 |
| Answer | Marks | Guidance |
|---|---|---|
| 10(iii) | H : ρ= 0, H : ρ> 0 | |
| 0 1 | B1 | State both hypotheses (B0 for r …) |
| Answer | Marks | Guidance |
|---|---|---|
| 10, 5% | *B1 | State or use correct tabular one-tail r-value |
| Answer | Marks | Guidance |
|---|---|---|
| 0 | M1 | State or imply valid method for conclusion |
| Answer | Marks | Guidance |
|---|---|---|
| r 8,0.95 | (*B1 | (Rarely seen) |
| Reject H if | t | > tab. t-value (AEF) |
| 0 r | M1) | |
| Evidence of positive correlation (AEF) | A1 | Correct conclusion (dep *A1, *B1) |
| Answer | Marks | Guidance |
|---|---|---|
| Question | Answer | Marks |
| 11A(i) | ½mv 2 = ½mu2 + mga (1 – cos α) [v 2 = u2 + (2/5) ag] | |
| C C | M1A1 | Find speed v at C by conservation of energy (A0 if no m) |
| Answer | Marks | Guidance |
|---|---|---|
| A | B1 | Find reaction R at A by using F = ma |
| Answer | Marks | Guidance |
|---|---|---|
| C C | B1 | Find reaction R at C by using F = ma |
| Answer | Marks | Guidance |
|---|---|---|
| 8 {ag + u2 + (2/5) ag} = 9 {(4/5) ag + u2) | M1 | Verify u2 using R / R = 9/8 |
| Answer | Marks |
|---|---|
| u2 = (8 + 16/5 – 36/5) ag = 4ag AG | A1 |
| Answer | Marks |
|---|---|
| 11A(ii) | ½mv 2 = ½mu2 – 2mga cos α |
| Answer | Marks | Guidance |
|---|---|---|
| C C | M1 | Find speed v at B by conservation of energy (A0 if no m) |
| Answer | Marks | Guidance |
|---|---|---|
| B | *A1 | |
| ⩾ 0 so P reaches height of B (AEF; dep *A1) | A1 | (or valid argument based on R ) |
| Answer | Marks | Guidance |
|---|---|---|
| A B | M1**A1 | Find reaction R at B by using F = ma |
| Answer | Marks |
|---|---|
| ⩾ 0 so P still [just] in contact at B (AEF; dep **A1) | A1 |
| Answer | Marks | Guidance |
|---|---|---|
| 11B(i) | x = (1/200) Σ x f(x) = 30 064 / 200 = 150.3[2] | M1A1 |
| Answer | Marks | Guidance |
|---|---|---|
| Question | Answer | Marks |
| 11B(ii) | P(151 ⩽ X < 152) |
| Answer | Marks | Guidance |
|---|---|---|
| = 0.9522 – 0.7975 [= 0.1547] (to 4 s.f.) | M1A1 | Find P(151 ⩽ X < 152) |
| Answer | Marks | Guidance |
|---|---|---|
| 151 | A1 | and hence expected frequency for 151 ⩽ x < 152 |
| Answer | Marks | Guidance |
|---|---|---|
| 11B(iii) | H : [Normal] distribution fits data (AEF) | |
| 0 | B1 | State (at least) null hypothesis in full |
| Answer | Marks | Guidance |
|---|---|---|
| i | M1 | Combine values consistent with all exp. values ⩾ 5 |
| X2 = 4.501 + 2.038 + 0.945 + 1.517 + 0.828 + 5.790 | M1 | Find value of X2 from Σ (E – O)2 / E [or Σ O2/E – n ] |
| Answer | Marks |
|---|---|
| = 15.6 (to 3 s.f.) | A1 |
| Answer | Marks | Guidance |
|---|---|---|
| n-1, 0.95 | B1 | State or use consistent tabular value χ 2 (to 3 s.f.) |
| Answer | Marks | Guidance |
|---|---|---|
| 1 | M1 | State or imply valid method for conclusion |
| 15.6 [± 0.1] > 11.1 so distn. doesn’t fit [data] (AEF) | A1 | Conclusion (requires both values correct) |
Question 10:
--- 10(i) ---
10(i) | x = (y – 1.1664) / 0.4604 = 11.02 or Σ x = 110.2 | M1 | Find x or Σ x using eqn. of regression line of y on x
S = 1419.98 – 110.22/10 = 205.576
xx
S = 439.68 – 62.42/10 = 50.304 (AEF)
yy | M1 | Find S and S
xx yy
(may be earned in part (ii))
EITHER: b = S / S = (S / S ) × (S / S )
xy yy xy xx xx yy
= 0.4604 × 205.576 / 50.304 = 1.88[15] | M1A1 | Find gradient b to 3 s.f. in x – x = b (y – y)
OR: S = 0.4604 × S = 94.647
xy xx
b = S / S = 94.647 / 50.304 = 1.88[15]
xy yy | (M1A1)
(x – 11.02) = b (y – 6.24), x = 1.88y – 0.721 | M1A1 | and hence eqn. of regression line of x on y
6
--- 10(ii) ---
10(ii) | r = S / √(S S ) = 94.647 / √(205.576 × 50.304)
xy xx yy
or √(0.4604 × b) = √(0.4604 × 1.8815) (AEF) | M1 | Find correlation coefficient r
= 0.931 | *A1
2
--- 10(iii) ---
10(iii) | H : ρ= 0, H : ρ> 0
0 1 | B1 | State both hypotheses (B0 for r …)
EITHER: r = 0.549
10, 5% | *B1 | State or use correct tabular one-tail r-value
Reject H if r > tab. r-value (AEF)
0 | M1 | State or imply valid method for conclusion
OR: t = r√((n–2) / (1 – r2)) = 7.21, t = 1.86
r 8,0.95 | (*B1 | (Rarely seen)
Reject H if | t | > tab. t-value (AEF)
0 r | M1)
Evidence of positive correlation (AEF) | A1 | Correct conclusion (dep *A1, *B1)
4
Question | Answer | Marks | Guidance
11A(i) | ½mv 2 = ½mu2 + mga (1 – cos α) [v 2 = u2 + (2/5) ag]
C C | M1A1 | Find speed v at C by conservation of energy (A0 if no m)
C
R = mg cos α + mu2/a
A | B1 | Find reaction R at A by using F = ma
A
R = mg + mv 2/a
C C | B1 | Find reaction R at C by using F = ma
C
8 {ag + u2 + (2/5) ag} = 9 {(4/5) ag + u2) | M1 | Verify u2 using R / R = 9/8
C A
u2 = (8 + 16/5 – 36/5) ag = 4ag AG | A1
6
11A(ii) | ½mv 2 = ½mu2 – 2mga cos α
B
or ½mv 2 – mga (1 + cos α) [v 2 = (22/5) ag]
C C | M1 | Find speed v at B by conservation of energy (A0 if no m)
B
v 2 = (4 – 16/5) ag or (22/5 – 18/5) ag = (4/5) ag
B | *A1
⩾ 0 so P reaches height of B (AEF; dep *A1) | A1 | (or valid argument based on R )
A
R = m v 2/a – mg cos α = 4mg/5 – 4mg/5 = 0
A B | M1**A1 | Find reaction R at B by using F = ma
B
⩾ 0 so P still [just] in contact at B (AEF; dep **A1) | A1
6
11B(i) | x = (1/200) Σ x f(x) = 30 064 / 200 = 150.3[2] | M1A1 | Find sample mean to 4 s.f. using mid-interval values
(B1 for 29 964 / 200 = 149.8[2] or 30 164 / 200 = 150.8[2])
2
Question | Answer | Marks | Guidance
11B(ii) | P(151 ⩽ X < 152)
= P((151 – 150)/1.2 ⩽ Z < (152 – 150)/1.2)
= P(0.833 ⩽ Z < 1.667)
= 0.9522 – 0.7975 [= 0.1547] (to 4 s.f.) | M1A1 | Find P(151 ⩽ X < 152)
E = 190.44 – 159.5 or 200 × 0.1547 = 30.94 AG
151 | A1 | and hence expected frequency for 151 ⩽ x < 152
3
11B(iii) | H : [Normal] distribution fits data (AEF)
0 | B1 | State (at least) null hypothesis in full
O: 3 23 52 69 36 17
i
E: 9.56 30.94 59.50 59.50 30.94 9.56
i | M1 | Combine values consistent with all exp. values ⩾ 5
X2 = 4.501 + 2.038 + 0.945 + 1.517 + 0.828 + 5.790 | M1 | Find value of X2 from Σ (E – O)2 / E [or Σ O2/E – n ]
i i i i i
= 15.6 (to 3 s.f.) | A1
No. n of cells: 8 7 6 5
χ 2: 14.07 12.59 11.07 9.488
n-1, 0.95 | B1 | State or use consistent tabular value χ 2 (to 3 s.f.)
n–1, 0..95
[FT on number, n, of cells used to find X2]
Accept H if X2 > tabular value (AEF)
1 | M1 | State or imply valid method for conclusion
15.6 [± 0.1] > 11.1 so distn. doesn’t fit [data] (AEF) | A1 | Conclusion (requires both values correct)
7
For a random sample of 10 observations of pairs of values $(x, y)$, the equation of the regression line of $y$ on $x$ is $y = 1.1664 + 0.4604x$. It is given that
$$\Sigma x^2 = 1419.98 \quad \text{and} \quad \Sigma y^2 = 439.68.$$
The mean value of $y$ is 6.24.
\begin{enumerate}[label=(\roman*)]
\item Find the equation of the regression line of $x$ on $y$. [6]
\item Find the product moment correlation coefficient. [2]
\item Test at the 5\% significance level whether there is evidence of positive correlation between the two variables. [4]
\end{enumerate}
\hfill \mbox{\textit{CAIE FP2 2018 Q10 [12]}}