Chi-squared goodness of fit: Poisson

A question is this type if and only if it tests whether observed frequency data fits a Poisson distribution, possibly with parameter estimated from data.

33 questions · Standard +0.4

Sort by: Default | Easiest first | Hardest first
Edexcel S3 Q8
20 marks Standard +0.3
8. A physicist believes that the number of particles emitted by a radioactive source with a long half-life can be modelled by a Poisson distribution. She records the number of particles emitted in 80 successive 5-minute periods and her results are shown in the table below.
No. of Particles012345 or more
No. of Intervals233214830
  1. Comment on the suitability of a Poisson distribution for this situation.
  2. Show that an unbiased estimate of the mean number of particles emitted in a 5 -minute period is 1.2 and find an unbiased estimate of the variance.
  3. Explain how your answers to part (b) support the fitting of a Poisson distribution.
  4. Stating your hypotheses clearly and using a \(5 \%\) level of significance, test whether or not these data can be modelled by a Poisson distribution. END
OCR MEI Further Statistics Minor Specimen Q6
15 marks Standard +0.3
6 At a bird feeding station, birds are captured and ringed. If a bird is recaptured, the ring enables it to be identified. The table below shows the number of recaptures, \(x\), during a period of a month, for each bird of a particular species in a random sample of 40 birds.
Number of
recaptures, \(x\)
012345678910
Frequency255910431010
  1. The sample mean of \(x\) is 3.4. Calculate the sample variance of \(x\).
  2. Briefly comment on whether the results of part (i) support a suggestion that a Poisson model might be a good fit to the data. The screenshot below shows part of a spreadsheet for a \(\chi ^ { 2 }\) test to assess the goodness of fit of a Poisson model. The sample mean of 3.4 has been used as an estimate of the Poisson parameter. Some values in the spreadsheet have been deliberately omitted.
    ABCDE
    1Number of recapturesObserved frequencyPoisson probabilityExpected frequencyChi-squared contribution
    20 or 170.14685.87370.2160
    3250.9560
    4390.21868.74470.0075
    54100.18587.43300.8865
    6540.12645.0544
    7\(\geq 6\)50.12955.17830.0061
  3. State the null and alternative hypotheses for the test.
  4. Calculate the missing values in cells
    • C3,
    • D3 and
    • E6.
    • Complete the test at the \(10 \%\) significance level.
    • The screenshot below shows part of a spreadsheet for a \(\chi ^ { 2 }\) test for a different species of bird. Find the value of the Poisson parameter used.
    ABCDE
    1Number of recapturesObserved frequencyPoisson probabilityExpected frequencyChi-squared contribution
    31100.2571612.85790.6352
    4270.2700213.50083.1302
    53150.189019.45063.2587
    6\(\geq 4\)110.161368.06791.0656
OCR MEI Further Statistics Major 2021 November Q6
14 marks Standard +0.3
6 Cosmic rays passing through the upper atmosphere cause muons, and other types of particle, to be formed. Muons can be detected when they reach the surface of the earth. It is known that the mean number of muons reaching a particular detector is 1.7 per second. The numbers of muons reaching this detector in 200 randomly selected periods of 1 second are shown in Fig. 6.1. \begin{table}[h]
Number of muons0123456\(\geqslant 7\)
Frequency3465552414620
\captionsetup{labelformat=empty} \caption{Fig. 6.1}
\end{table}
  1. Use the values of the sample mean and sample variance to discuss the suitability of a Poisson distribution as a model. The screenshot in Fig. 6.2 shows part of a spreadsheet to assess the goodness of fit of the distribution Po(1.7). \begin{table}[h]
    ABCDE
    1Number of muonsObserved frequencyPoisson probabilityExpected frequencyChi-squared contribution
    20340.182736.53670.1761
    3165
    42550.264052.79550.0920
    53240.149629.91751.1704
    64140.1299
    7\(\geqslant 5\)80.02965.92300.7284
    \captionsetup{labelformat=empty} \caption{Fig. 6.2}
    \end{table}
  2. Calculate the missing values in each of the following cells.
    • C3
    • D3
    • E3
    • Explain why the numbers for 5, 6 and at least 7 muons have been combined into the single category of at least 5 muons, as shown in Fig. 6.2.
    • In this question you must show detailed reasoning.
    Carry out the test at the 5\% significance level.
WJEC Further Unit 2 2024 June Q3
12 marks Standard +0.3
  1. A company makes bags. The table below shows the number of bags sold on a random sample of 50 days. A manager believes that the number of bags sold per day can be modelled by the Poisson distribution with mean \(2 \cdot 2\).
Number of
bags sold
012345 or more
Frequency71011967
  1. Carry out a chi-squared goodness of fit test, using a \(10 \%\) significance level.
  2. A chi-squared goodness of fit test for the Poisson distribution with mean \(2 \cdot 5\) is conducted. This uses the same number of degrees of freedom as part (a) and gives a test statistic of 1.53 . State, with a reason, which of these two Poisson models is a better fit for the data.
WJEC Further Unit 2 Specimen Q5
10 marks Standard +0.3
5. The manager of a hockey team studies last season's results and puts forward the theory that the number of goals scored per match by her team can be modelled by a Poisson distribution with mean 2.0. The number of goals scored during the season are summarised below.
Goals scored01234 or more
Frequency61115108
  1. State suitable hypotheses to carry out a goodness of fit test.
  2. Carry out a \(\chi ^ { 2 }\) goodness of fit test on this data set, using a \(5 \%\) level of significance and draw a conclusion in context.
Edexcel FS1 AS 2023 June Q4
12 marks Standard +0.3
  1. Table 1 below shows the number of car breakdowns in the Snoreap district in each of 60 months.
\begin{table}[h]
Number of car
breakdowns
012345
Frequency1211191431
\captionsetup{labelformat=empty} \caption{Table 1}
\end{table} Anja believes that the number of car breakdowns per month in Snoreap can be modelled by a Poisson distribution. Table 2 below shows the results of some of her calculations. \begin{table}[h]
Number of car breakdowns01234\(\geqslant 5\)
Observed frequency (O)1211191431
Expected frequency ( \(\mathbf { E } _ { \mathbf { i } }\) )9.929.644.34
\captionsetup{labelformat=empty} \caption{Table 2}
\end{table}
  1. State suitable hypotheses for a test to investigate Anja's belief.
  2. Explain why Anja has changed the label of the final column to \(\geqslant 5\)
  3. Showing your working clearly, complete Table 2
  4. Find the value of \(\frac { \left( O _ { i } - E _ { i } \right) ^ { 2 } } { E _ { i } }\) when the number of car breakdowns is
    1. 1
    2. 3
  5. Explain why Anja used 3 degrees of freedom for her test. The test statistic for Anja's test is 6.54 to 2 decimal places.
  6. Stating the critical value and using a \(5 \%\) level of significance, complete Anja's test.
Edexcel FS1 AS Specimen Q4
11 marks Standard +0.3
  1. The discrete random variable \(X\) follows a Poisson distribution with mean 1.4
    1. Write down the value of
      1. \(\mathrm { P } ( \mathrm { X } = 1 )\)
      2. \(\mathrm { P } ( \mathrm { X } \leqslant 4 )\)
    The manager of a bank recorded the number of mortgages approved each week over a 40 week period.
    Number of mortgages approved0123456
    Frequency101674201
  2. Show that the mean number of mortgages approved over the 40 week period is 1.4 The bank manager believes that the Poisson distribution may be a good model for the number of mortgages approved each week. She uses a Poisson distribution with a mean of 1.4 to calculate expected frequencies as follows.
    Number of mortgages approved012345 or more
    Expected frequency9.86r9.674.511.58s
  3. Find the value of r and the value of s giving your answers to 2 decimal places. The bank manager will test, at the \(5 \%\) level of significance, whether or not the data can be modelled by a Poisson distribution.
  4. Calculate the test statistic and state the conclusion for this test. State clearly the degrees of freedom and the hypotheses used in the test. \section*{Q uestion 4 continued} \section*{Q uestion 4 continued}
AQA Further Paper 3 Statistics 2024 June Q16
Moderate -0.8
16
256 2 The random variable \(T\) has an exponential distribution with mean 2 Find \(\mathrm { P } ( T \leq 1.4 )\) Circle your answer. \(\mathrm { e } ^ { - 2.8 }\) \(\mathrm { e } ^ { - 0.7 }\) \(1 - e ^ { - 0.7 }\) \(1 - \mathrm { e } ^ { - 2.8 }\) The continuous random variable \(Y\) has cumulative distribution function $$\mathrm { F } ( y ) = \left\{ \begin{array} { l r } 0 & y < 2 \\ - \frac { 1 } { 9 } y ^ { 2 } + \frac { 10 } { 9 } y - \frac { 16 } { 9 } & 2 \leq y < 5 \\ 1 & y \geq 5 \end{array} \right.$$ Find the median of \(Y\) Circle your answer. 2 \(\frac { 10 - 3 \sqrt { 2 } } { 2 }\) \(\frac { 7 } { 2 }\) \(\frac { 10 + 3 \sqrt { 2 } } { 2 }\) Turn over for the next question 4 Research has shown that the mean number of volcanic eruptions on Earth each day is 20 Sandra records 162 volcanic eruptions during a period of one week. Sandra claims that there has been an increase in the mean number of volcanic eruptions per week. Test Sandra's claim at the \(5 \%\) level of significance.
5 The continuous random variable \(X\) has probability density function $$f ( x ) = \begin{cases} \frac { 1 } { 6 } e ^ { \frac { x } { 3 } } & 0 \leq x \leq \ln 27 \\ 0 & \text { otherwise } \end{cases}$$ Show that the mean of \(X\) is \(\frac { 3 } { 2 } ( \ln 27 - 2 )\) 6 Over time it has been accepted that the mean retirement age for professional baseball players is 29.5 years old. Imran claims that the mean retirement age is no longer 29.5 years old.
He takes a random sample of 5 recently retired professional baseball players and records their retirement ages, \(x\). The results are $$\sum x = 152.1 \quad \text { and } \quad \sum ( x - \bar { x } ) ^ { 2 } = 7.81$$ 6
  1. State an assumption that you should make about the distribution of the retirement ages to investigate Imran's claim. 6
  2. Investigate Imran's claim, using the 10\% level of significance.