Please check the examination details below before entering your candidate information
Candidate surname Other names
Centre Number Candidate Number
Pearson Edexcel Level 3 GCE
reference 9FM0/4B
Paper
Time 1 hour 30 minutes
Further Mathematics
Advanced
PAPER 4B: Further Statistics 2
You must have: Total Marks
Mathematical Formulae and Statistical Tables (Green), calculator
A-Level Pearson Edexcel Level 3 GCE
AL Further Mathematics (9FM0)
Paper 4B Further Statistics 2 Summer
Exam Question paper
(AUTHENTIC MARKING SCHEME
ATTACHED)
P72096A *P72096A0124*
©2022 Pearson Education Ltd.
Q:1/1/1/
,1. Kwame is investigating a possible relationship between average March temperature,
t °C, and tea yield, y kg/hectare, for tea grown in a particular location.
He uses 30 years of past data to produce the following summary statistics for a linear
regression model, with tea yield as the dependent variable.
Residual Sum of Squares (RSS) = 1 666 567 Stt = 52.0 Syy = 1 774 155
least squares regression line: gradient = 45.5 y-intercept = 2080
(a) Use the regression model to predict the tea yield for an average March temperature
of 20 °C
(1)
He also produces the following residual plot for the data.
800
600
400
200
Residual 0
–200
–400
–600
17 18 19 20 21 22 23
Temperature (t °C)
(b) Explain what you understand by the term residual.
(1)
(c) Calculate the product moment correlation coefficient between t and y
(2)
(d) Explain why the linear model may not be a good fit for the data
(i) with reference to your answer to part (c)
(ii) with reference to the residual plot.
(2)
Question 1 continues on page 4
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*P72096A0224*
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*P72096A0324* Turn over
, Question 1 continued
Kwame also collects data on total March rainfall, w mm, for each of these 30 years.
For a linear regression model of w on t the following summary statistic is found.
Residual Sum of Squares (RSS) = 86 754
Kwame concludes that since this model has a smaller RSS, there must be a stronger
linear relationship between w and t than between y and t (where RSS = 1 666 567)
(e) State, giving a reason, whether or not you agree with the reasoning that led to
Kwame’s conclusion.
(1)
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*P72096A0424*
Candidate surname Other names
Centre Number Candidate Number
Pearson Edexcel Level 3 GCE
reference 9FM0/4B
Paper
Time 1 hour 30 minutes
Further Mathematics
Advanced
PAPER 4B: Further Statistics 2
You must have: Total Marks
Mathematical Formulae and Statistical Tables (Green), calculator
A-Level Pearson Edexcel Level 3 GCE
AL Further Mathematics (9FM0)
Paper 4B Further Statistics 2 Summer
Exam Question paper
(AUTHENTIC MARKING SCHEME
ATTACHED)
P72096A *P72096A0124*
©2022 Pearson Education Ltd.
Q:1/1/1/
,1. Kwame is investigating a possible relationship between average March temperature,
t °C, and tea yield, y kg/hectare, for tea grown in a particular location.
He uses 30 years of past data to produce the following summary statistics for a linear
regression model, with tea yield as the dependent variable.
Residual Sum of Squares (RSS) = 1 666 567 Stt = 52.0 Syy = 1 774 155
least squares regression line: gradient = 45.5 y-intercept = 2080
(a) Use the regression model to predict the tea yield for an average March temperature
of 20 °C
(1)
He also produces the following residual plot for the data.
800
600
400
200
Residual 0
–200
–400
–600
17 18 19 20 21 22 23
Temperature (t °C)
(b) Explain what you understand by the term residual.
(1)
(c) Calculate the product moment correlation coefficient between t and y
(2)
(d) Explain why the linear model may not be a good fit for the data
(i) with reference to your answer to part (c)
(ii) with reference to the residual plot.
(2)
Question 1 continues on page 4
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*P72096A0224*
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3
*P72096A0324* Turn over
, Question 1 continued
Kwame also collects data on total March rainfall, w mm, for each of these 30 years.
For a linear regression model of w on t the following summary statistic is found.
Residual Sum of Squares (RSS) = 86 754
Kwame concludes that since this model has a smaller RSS, there must be a stronger
linear relationship between w and t than between y and t (where RSS = 1 666 567)
(e) State, giving a reason, whether or not you agree with the reasoning that led to
Kwame’s conclusion.
(1)
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*P72096A0424*
