| Exam Board | CAIE |
|---|---|
| Module | FP2 (Further Pure Mathematics 2) |
| Year | 2018 |
| Session | June |
| Marks | 12 |
| Paper | Download PDF ↗ |
| Mark scheme | Download PDF ↗ |
| Topic | T-tests (unknown variance) |
| Type | Two-sample confidence interval difference of means |
| Difficulty | Standard +0.8 This is a two-sample t-test with unequal variances (Welch's t-test) requiring calculation of sample means and variances from summary statistics, followed by a one-tailed hypothesis test and confidence interval construction. While the procedure is standard for Further Maths Statistics, it involves multiple computational steps, careful handling of the Welch-Satterthwaite degrees of freedom approximation, and correct interpretation of the directional hypothesis. The question is more demanding than typical A-level statistics but represents expected Further Maths content rather than requiring novel insight. |
| Spec | 5.04a Linear combinations: E(aX+bY), Var(aX+bY)5.05c Hypothesis test: normal distribution for population mean |
| Answer | Marks | Guidance |
|---|---|---|
| \(H_0: \mu_P = \mu_Q,\ H_1: \mu_P > \mu_Q\) | B1 | State hypotheses (B0 for \(\bar{x}\ ...\)) |
| \(s_P^2 = (138\,200 - 2620^2/50)/49 = 18.61\) or \(912/49\) and \(s_Q^2 = (157\,000 - 3060^2/60)/59 = 15.93\) or \(940/59\) | M1 A1 | Estimate both population variances (to 3 s.f.) (allow biased: \(18.24\) and \(15.67\)) |
| \(s^2 = s_P^2/50 + s_Q^2/60 = 0.6378\) or \(0.7986^2\) | M1 A1 | Estimate combined variance (to 3 s.f.; may be implicit) |
| \(z_{0.9} = 1.28[2]\) | *B1 | State or use correct tabular \(z\) value |
| \(z = (\bar{y} - \bar{x})/s = (52.4 - 51)/s = 1.75\), \(z >\) tabular value so [accept \(H_1\) and] | M1 A1 | Calculate value of \(z\) (or \(-z\)) (or can compare \(\bar{y} - \bar{x} = 1.02\) with \(1.4\)) |
| college \(P\) students take more time | \(\text{B1}\sqrt{}\) (AEF) | Correctly stated conclusion (FT on \(z\), dep *B1) |
| [SC: \(s^2 = (912+940)/108 = 17.15\) or \(4.141^2\); \(z = 1.4/s\sqrt{1/50+1/60} = 1.77\)] | SC: Using pooled estimate of common variance can earn B1 M1 A1 (may be implied) M0 *B1 M0 \(\text{B1}\sqrt{}\) (max 5/9) |
| Answer | Marks | Guidance |
|---|---|---|
| \(\bar{x} - \bar{y} \pm zs\) (or \(\bar{y} - \bar{x} \pm zs\)) | M1 | Find confidence interval for difference |
| \(z_{0.95} = 1.64[5]\) | A1 | Use appropriate tabular value |
| \(1.4 \pm 1.31\) or \([0.09,\ 2.71]\), or \(-1.4 \pm 1.31\) or \([-2.71,\ -0.09]\) [SC: e.g. \(\bar{x} - \bar{y} \pm zs\sqrt{1/50+1/60} = 1.4 \pm 1.30\)] | A1 | Evaluate confidence interval (either form). SC: Allow M1 A1 if common variance used (max 2/3) |
| Answer | Marks | Guidance |
|---|---|---|
| \(\tfrac{1}{2}mv^2 = \tfrac{1}{2}mu^2 + mga\cos\theta\) and \(T = mv^2/a + mg\cos\theta\), \(T = mu^2/a + 3mg\cos\theta\) | M1, M1 A1 | Use conservation of energy (A0 if no \(m\)) and find tension \(T\) at \(P_1\) by using \(F = ma\) (A1 for both correct). Combine to verify \(\cos\theta\) |
| \((11/5)mg = 2mg/5 + 3mg\cos\theta\), \(\cos\theta = 3/5\) | M1 A1 (AG) | By substituting \(T = (11/5)mg\) and \(u = \sqrt{2ag/5}\) |
| \(v^2 = u^2 + 2ag\cos\theta = (2/5 + 6/5)ag = 8ag/5\); \(v = \sqrt{8ag/5}\) or \(\sqrt{1.6ag}\) or \(4\sqrt{a}\) | B1 (AEF) | Find \(v\) at \(P_1\) (can assume \(\cos\theta = 3/5\)) |
| Answer | Marks | Guidance |
|---|---|---|
| \(t = (a\sin\theta)/(v\cos\theta) = 4a/3v \quad [= \tfrac{1}{3}\sqrt{a}]\) | M1 A1 | Find time \(t\) to \(P_2\) by considering horizontal motion |
| \(h = (v\sin\theta)t + \tfrac{1}{2}gt^2 = 16a/15 + 5a/9 = 73a/45\) or \(1.62a\) | M1 A1 | Find height fallen at \(P_2\) by considering vertical motion |
| \(OP_2 = h + a\cos\theta = 20a/9\) or \(2.22a\) | M1 A1 | Find \(OP_2\) |
| Answer | Marks | Guidance |
|---|---|---|
| \(\sum x = 48,\ \sum y = 29+2p,\ \sum xy = 242+17p,\ \sum x^2 = 450,\ [\sum y^2 = 219+2p^2]\); \(S_{xy} = 242+17p - 48(29+2p)/6 = 10+p\); \(S_{xx} = 450 - 48^2/6 = 66\); \([S_{yy} = 219+2p^2-(29+2p)^2/6 = (8p^2-116p+473)/6]\) | M1 A1 | Find required values |
| \(0.25 = S_{xy}/S_{xx} = (10+p)/66,\quad p = 6.5\) | M1 A1 | Find \(p\) from gradient in equation of regression line |
| \((29+2p)/6 = 0.25 \times 48/6 + k,\quad k = 7 - 2 = 5\) | M1 A1 | Find \(k\) from means and regression line |
| Answer | Marks | Guidance |
|---|---|---|
| Answer | Marks | Guidance |
| \(\sum y = 42\), \(\sum y^2 = 303.5\), \(S_{yy} = 303.5 - \frac{42^2}{6} = 9.5\) | M1 | Find correlation coefficient \(r\) |
| \(r = \frac{S_{xy}}{\sqrt{S_{xx}S_{yy}}} = \frac{16.5}{\sqrt{66 \times 9.5}} = 0.659\) | A1 | |
| 2 |
| Answer | Marks | Guidance |
|---|---|---|
| Answer | Marks | Guidance |
| \(H_0: \rho = 0\), \(H_1: \rho > 0\) | B1 | State both hypotheses (\(B0\) for \(r \ldots\)) |
| \(EITHER:\) \(r_{6,\, 5\%} = 0.729\) | *B1 | State or use correct tabular one-tail \(r\)-value |
| Accept \(H_0\) if \(\ | r\ | <\) tab. \(r\)-value \(\quad\) (AEF) |
| \(OR:\) \(t_r = \frac{r\sqrt{(n-2)}}{(1-r^2)} = 1.75\), \(t_{4,\,0.95} = 2.132\) | (*B1) | (Rarely seen) |
| Accept \(H_0\) if \(\ | t_r\ | <\) tab. \(t\)-value \(\quad\) (AEF) |
| No positive correlation \(\quad\) (AEF) | A1 | Correct conclusion (dep \*A1, \*B1) |
| 4 |
## Question 10(i):
| $H_0: \mu_P = \mu_Q,\ H_1: \mu_P > \mu_Q$ | B1 | State hypotheses (B0 for $\bar{x}\ ...$) |
|---|---|---|
| $s_P^2 = (138\,200 - 2620^2/50)/49 = 18.61$ or $912/49$ and $s_Q^2 = (157\,000 - 3060^2/60)/59 = 15.93$ or $940/59$ | M1 A1 | Estimate both population variances (to 3 s.f.) (allow biased: $18.24$ and $15.67$) |
| $s^2 = s_P^2/50 + s_Q^2/60 = 0.6378$ or $0.7986^2$ | M1 A1 | Estimate combined variance (to 3 s.f.; may be implicit) |
| $z_{0.9} = 1.28[2]$ | *B1 | State or use correct tabular $z$ value |
| $z = (\bar{y} - \bar{x})/s = (52.4 - 51)/s = 1.75$, $z >$ tabular value so [accept $H_1$ and] | M1 A1 | Calculate value of $z$ (or $-z$) (or can compare $\bar{y} - \bar{x} = 1.02$ with $1.4$) |
| college $P$ students take more time | $\text{B1}\sqrt{}$ (AEF) | Correctly stated conclusion (FT on $z$, dep *B1) |
| [SC: $s^2 = (912+940)/108 = 17.15$ or $4.141^2$; $z = 1.4/s\sqrt{1/50+1/60} = 1.77$] | | SC: Using pooled estimate of common variance can earn B1 M1 A1 (may be implied) M0 *B1 M0 $\text{B1}\sqrt{}$ (max 5/9) |
---
## Question 10(ii):
| $\bar{x} - \bar{y} \pm zs$ (or $\bar{y} - \bar{x} \pm zs$) | M1 | Find confidence interval for difference |
|---|---|---|
| $z_{0.95} = 1.64[5]$ | A1 | Use appropriate tabular value |
| $1.4 \pm 1.31$ or $[0.09,\ 2.71]$, or $-1.4 \pm 1.31$ or $[-2.71,\ -0.09]$ [SC: e.g. $\bar{x} - \bar{y} \pm zs\sqrt{1/50+1/60} = 1.4 \pm 1.30$] | A1 | Evaluate confidence interval (either form). SC: Allow M1 A1 if common variance used (max 2/3) |
---
## Question 11A(i):
| $\tfrac{1}{2}mv^2 = \tfrac{1}{2}mu^2 + mga\cos\theta$ and $T = mv^2/a + mg\cos\theta$, $T = mu^2/a + 3mg\cos\theta$ | M1, M1 A1 | Use conservation of energy (A0 if no $m$) and find tension $T$ at $P_1$ by using $F = ma$ (A1 for both correct). Combine to verify $\cos\theta$ |
|---|---|---|
| $(11/5)mg = 2mg/5 + 3mg\cos\theta$, $\cos\theta = 3/5$ | M1 A1 (AG) | By substituting $T = (11/5)mg$ and $u = \sqrt{2ag/5}$ |
| $v^2 = u^2 + 2ag\cos\theta = (2/5 + 6/5)ag = 8ag/5$; $v = \sqrt{8ag/5}$ or $\sqrt{1.6ag}$ or $4\sqrt{a}$ | B1 (AEF) | Find $v$ at $P_1$ (can assume $\cos\theta = 3/5$) |
---
## Question 11A(ii):
| $t = (a\sin\theta)/(v\cos\theta) = 4a/3v \quad [= \tfrac{1}{3}\sqrt{a}]$ | M1 A1 | Find time $t$ to $P_2$ by considering horizontal motion |
|---|---|---|
| $h = (v\sin\theta)t + \tfrac{1}{2}gt^2 = 16a/15 + 5a/9 = 73a/45$ or $1.62a$ | M1 A1 | Find height fallen at $P_2$ by considering vertical motion |
| $OP_2 = h + a\cos\theta = 20a/9$ or $2.22a$ | M1 A1 | Find $OP_2$ |
---
## Question 11B(i):
| $\sum x = 48,\ \sum y = 29+2p,\ \sum xy = 242+17p,\ \sum x^2 = 450,\ [\sum y^2 = 219+2p^2]$; $S_{xy} = 242+17p - 48(29+2p)/6 = 10+p$; $S_{xx} = 450 - 48^2/6 = 66$; $[S_{yy} = 219+2p^2-(29+2p)^2/6 = (8p^2-116p+473)/6]$ | M1 A1 | Find required values |
|---|---|---|
| $0.25 = S_{xy}/S_{xx} = (10+p)/66,\quad p = 6.5$ | M1 A1 | Find $p$ from gradient in equation of regression line |
| $(29+2p)/6 = 0.25 \times 48/6 + k,\quad k = 7 - 2 = 5$ | M1 A1 | Find $k$ from means and regression line |
## Question 11B(ii):
| Answer | Marks | Guidance |
|--------|-------|----------|
| $\sum y = 42$, $\sum y^2 = 303.5$, $S_{yy} = 303.5 - \frac{42^2}{6} = 9.5$ | M1 | Find correlation coefficient $r$ |
| $r = \frac{S_{xy}}{\sqrt{S_{xx}S_{yy}}} = \frac{16.5}{\sqrt{66 \times 9.5}} = 0.659$ | A1 | |
| | **2** | |
---
## Question 11B(iii):
| Answer | Marks | Guidance |
|--------|-------|----------|
| $H_0: \rho = 0$, $H_1: \rho > 0$ | B1 | State both hypotheses ($B0$ for $r \ldots$) |
| $EITHER:$ $r_{6,\, 5\%} = 0.729$ | *B1 | State or use correct tabular one-tail $r$-value |
| Accept $H_0$ if $\|r\| <$ tab. $r$-value $\quad$ (AEF) | M1 | State or imply valid method for conclusion |
| $OR:$ $t_r = \frac{r\sqrt{(n-2)}}{(1-r^2)} = 1.75$, $t_{4,\,0.95} = 2.132$ | (*B1) | (Rarely seen) |
| Accept $H_0$ if $\|t_r\| <$ tab. $t$-value $\quad$ (AEF) | (M1) | |
| No positive correlation $\quad$ (AEF) | A1 | Correct conclusion (dep \*A1, \*B1) |
| | **4** | |
10 The times taken to run 400 metres by students at two large colleges $P$ and $Q$ are being compared. There is no evidence that the population variances are equal. The time taken by a student at college $P$ and the time taken by a student at college $Q$ are denoted by $x$ seconds and $y$ seconds respectively. A random sample of 50 students from college $P$ and a random sample of 60 students from college $Q$ give the following summarised data.
$$\Sigma x = 2620 \quad \Sigma x ^ { 2 } = 138200 \quad \Sigma y = 3060 \quad \Sigma y ^ { 2 } = 157000$$
(i) Using a 10\% significance level, test whether, on average, students from college $P$ take longer to run 400 metres than students from college $Q$.\\
(ii) Find a $90 \%$ confidence interval for the difference in the mean times taken to run 400 metres by students from colleges $P$ and $Q$.\\
\hfill \mbox{\textit{CAIE FP2 2018 Q10 [12]}}