Edexcel FS1 AS 2023 June — Question 3 16 marks

Exam BoardEdexcel
ModuleFS1 AS (Further Statistics 1 AS)
Year2023
SessionJune
Marks16
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicPoisson distribution
TypeFinding maximum n for P(X=0) threshold
DifficultyStandard +0.3 This is a straightforward Further Statistics 1 question testing standard Poisson distribution techniques: finding parameter from probability (inverse calculation with logarithms), binomial probability, expectation/variance, Poisson approximation to binomial, and a one-tailed hypothesis test. All parts follow routine procedures with no novel problem-solving required, though the multi-part structure and hypothesis testing elevate it slightly above average A-level difficulty.
Spec5.01a Permutations and combinations: evaluate probabilities5.02i Poisson distribution: random events model5.02j Poisson formula: P(X=x) = e^(-lambda)*lambda^x/x!5.02k Calculate Poisson probabilities5.02l Poisson conditions: for modelling5.02m Poisson: mean = variance = lambda5.05c Hypothesis test: normal distribution for population mean

  1. A machine produces cloth. Faults occur randomly in the cloth at a rate of 0.4 per square metre.
The machine is used to produce tablecloths, each of area \(A\) square metres. One of these tablecloths is taken at random. The probability that this tablecloth has no faults is 0.0907
  1. Find the value of \(A\) The tablecloths are sold in packets of 20
    A randomly selected packet is taken.
  2. Find the probability that more than 1 of the tablecloths in this packet has no faults. A hotel places an order for 100 tablecloths each of area \(A\) square metres.
    The random variable \(X\) represents the number of these tablecloths that have no faults.
  3. Find
    1. \(\mathrm { E } ( X )\)
    2. \(\operatorname { Var } ( X )\)
  4. Use a Poisson approximation to estimate \(\mathrm { P } ( X = 10 )\) It is claimed that a new machine produces cloth with a rate of faults that is less than 0.4 per square metre. A piece of cloth produced by this new machine is taken at random.
    The piece of cloth has area 30 square metres and is found to have 6 faults.
  5. Stating your hypotheses clearly, use a suitable test to assess the claim made for the new machine. Use a \(5 \%\) level of significance.
  6. Write down the \(p\)-value for the test used in part (e).

Question 3:
Part (a):
AnswerMarks Guidance
WorkingMark Guidance
\([F = \text{no. of faults in } A \text{ m}^2]\) \(F \sim Po(A \times 0.4)\)M1 For selecting the correct model \(Po(0.4A)\)
\([P(F=0) \Rightarrow]\) \(0.0907 = e^{-0.4A}\)M1 For a correct equation; may be implied by correct answer with no incorrect working
\(A = 6\)A1 For \(A = 6\) (or awrt 6.0)
Part (b):
AnswerMarks Guidance
WorkingMark Guidance
\([T = \text{no. of tablecloths with no faults}]\) \(T \sim B(20, 0.0907)\)M1 For selecting a correct model \(B(20, 0.0907)\)
\(P(T > 1) = 1 - P(T \leq 1)\)M1 For correctly interpreting "more than 1" to reach \(1 - P(T \leq 1)\); may be implied by A1
\(= 0.55276\ldots =\) awrt \(0.553\)A1 For awrt 0.553
Part (c)(i):
AnswerMarks Guidance
WorkingMark Guidance
\([X \sim B(100, 0.0907)]\)M1 For \(X \sim B(100, 0.0907)\) used; may be implied by correct \(E(X)\) or \(Var(X)\)
\(E(X) = 100 \times 0.0907 = 9.07\)A1 For 9.07
Part (c)(ii):
AnswerMarks Guidance
WorkingMark Guidance
\(Var(X) = 100 \times 0.0907 \times (1 - 0.0907) = 8.247351\ldots\) awrt \(8.25\)A1 For awrt 8.25. SC - award M0A1A0 for: using \(X \sim B(100, 0.4)\) leading to \(E(X)=40\), \(Var(X)=24\); or using \(X \sim B(100,p)\), \(0
Part (d):
AnswerMarks Guidance
WorkingMark Guidance
\(X \approx Po(9.07)\)M1 For selecting the correct Poisson model — ft their answer to (c)(i)
\(P(X = 10) \approx 0.11947\ldots\) \(\mathbf{0.1195}\) or awrt \(0.119\)A1 For 0.1195 or awrt 0.119
Part (e):
AnswerMarks Guidance
WorkingMark Guidance
\(H_0: \lambda = 0.4\) (or \(\lambda = 12\)) \(\quad H_1: \lambda < 0.4\) (or \(\lambda < 12\))B1 For both hypotheses correct in terms of \(\lambda\) or \(\mu\)
\([Y = \text{no. of faults from new machine}]\) \(Y \sim Po(12)\)M1 For selecting a suitable model; sight or use of \(Po(12)\); may be implied by 1st A1
\(P(Y \leq 6) = 0.04582\ldots\)A1 For a correct probability; must be 0.046 or better
[Significant] there is evidence to support the claimA1 For a correct conclusion in context using "claim" or "rate of faults"
Part (f):
AnswerMarks Guidance
WorkingMark Guidance
\(p\text{-value} = 0.04582\ldots\) awrt \(\mathbf{0.0458}\)B1ft B1ft for awrt 0.0458 o.e. e.g. 4.58%, or ft their answer to 1st A1 in (e)
# Question 3:

## Part (a):
| Working | Mark | Guidance |
|---------|------|----------|
| $[F = \text{no. of faults in } A \text{ m}^2]$ $F \sim Po(A \times 0.4)$ | M1 | For selecting the correct model $Po(0.4A)$ |
| $[P(F=0) \Rightarrow]$ $0.0907 = e^{-0.4A}$ | M1 | For a correct equation; may be implied by correct answer with no incorrect working |
| $A = 6$ | A1 | For $A = 6$ (or awrt 6.0) |

## Part (b):
| Working | Mark | Guidance |
|---------|------|----------|
| $[T = \text{no. of tablecloths with no faults}]$ $T \sim B(20, 0.0907)$ | M1 | For selecting a correct model $B(20, 0.0907)$ |
| $P(T > 1) = 1 - P(T \leq 1)$ | M1 | For correctly interpreting "more than 1" to reach $1 - P(T \leq 1)$; may be implied by A1 |
| $= 0.55276\ldots =$ awrt $0.553$ | A1 | For awrt 0.553 |

## Part (c)(i):
| Working | Mark | Guidance |
|---------|------|----------|
| $[X \sim B(100, 0.0907)]$ | M1 | For $X \sim B(100, 0.0907)$ used; may be implied by correct $E(X)$ or $Var(X)$ |
| $E(X) = 100 \times 0.0907 = 9.07$ | A1 | For 9.07 |

## Part (c)(ii):
| Working | Mark | Guidance |
|---------|------|----------|
| $Var(X) = 100 \times 0.0907 \times (1 - 0.0907) = 8.247351\ldots$ awrt $8.25$ | A1 | For awrt 8.25. SC - award M0A1A0 for: using $X \sim B(100, 0.4)$ leading to $E(X)=40$, $Var(X)=24$; or using $X \sim B(100,p)$, $0<p<1$ and $E(X)=100p$, $Var(X)=100p(1-p)$ |

## Part (d):
| Working | Mark | Guidance |
|---------|------|----------|
| $X \approx Po(9.07)$ | M1 | For selecting the correct Poisson model — ft their answer to (c)(i) |
| $P(X = 10) \approx 0.11947\ldots$ $\mathbf{0.1195}$ or awrt $0.119$ | A1 | For 0.1195 or awrt 0.119 |

## Part (e):
| Working | Mark | Guidance |
|---------|------|----------|
| $H_0: \lambda = 0.4$ (or $\lambda = 12$) $\quad H_1: \lambda < 0.4$ (or $\lambda < 12$) | B1 | For both hypotheses correct in terms of $\lambda$ or $\mu$ |
| $[Y = \text{no. of faults from new machine}]$ $Y \sim Po(12)$ | M1 | For selecting a suitable model; sight or use of $Po(12)$; may be implied by 1st A1 |
| $P(Y \leq 6) = 0.04582\ldots$ | A1 | For a correct probability; must be 0.046 or better |
| [Significant] there is evidence to support the claim | A1 | For a correct conclusion in context using "claim" or "rate of faults" |

## Part (f):
| Working | Mark | Guidance |
|---------|------|----------|
| $p\text{-value} = 0.04582\ldots$ awrt $\mathbf{0.0458}$ | B1ft | B1ft for awrt 0.0458 o.e. e.g. 4.58%, or ft their answer to 1st A1 in (e) |

---
\begin{enumerate}
  \item A machine produces cloth. Faults occur randomly in the cloth at a rate of 0.4 per square metre.
\end{enumerate}

The machine is used to produce tablecloths, each of area $A$ square metres. One of these tablecloths is taken at random.

The probability that this tablecloth has no faults is 0.0907\\
(a) Find the value of $A$

The tablecloths are sold in packets of 20\\
A randomly selected packet is taken.\\
(b) Find the probability that more than 1 of the tablecloths in this packet has no faults.

A hotel places an order for 100 tablecloths each of area $A$ square metres.\\
The random variable $X$ represents the number of these tablecloths that have no faults.\\
(c) Find\\
(i) $\mathrm { E } ( X )$\\
(ii) $\operatorname { Var } ( X )$\\
(d) Use a Poisson approximation to estimate $\mathrm { P } ( X = 10 )$

It is claimed that a new machine produces cloth with a rate of faults that is less than 0.4 per square metre.

A piece of cloth produced by this new machine is taken at random.\\
The piece of cloth has area 30 square metres and is found to have 6 faults.\\
(e) Stating your hypotheses clearly, use a suitable test to assess the claim made for the new machine. Use a $5 \%$ level of significance.\\
(f) Write down the $p$-value for the test used in part (e).

\hfill \mbox{\textit{Edexcel FS1 AS 2023 Q3 [16]}}