Edexcel AS Paper 2 2023 June — Question 2 4 marks

Exam BoardEdexcel
ModuleAS Paper 2 (AS Paper 2)
Year2023
SessionJune
Marks4
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicBivariate data
TypeAnalyze large data set correlations
DifficultyModerate -0.8 This is a straightforward data interpretation question requiring students to describe correlation from scatter diagrams and apply basic knowledge of the large data set. Parts (a)-(c) involve standard descriptive statistics (describing correlation, interpreting scatter plots, understanding interpolation), while part (d) tests recall of data set properties. No calculations or complex reasoning required—primarily reading graphs and recalling data set characteristics.
Spec2.01a Population and sample: terminology2.02c Scatter diagrams and regression lines2.02d Informal interpretation of correlation
  1. Fred and Nadine are investigating whether there is a linear relationship between Daily Mean Pressure, \(p \mathrm { hPa }\), and Daily Mean Air Temperature, \(t ^ { \circ } \mathrm { C }\), in Beijing using the 2015 data from the large data set.
Fred randomly selects one month from the data set and draws the scatter diagram in Figure 1 using the data from that month. The scale has been left off the horizontal axis. \begin{figure}[h]
\includegraphics[alt={},max width=\textwidth]{854568d2-b32d-44de-8a9c-26372e509c20-04_794_1539_589_264} \captionsetup{labelformat=empty} \caption{Figure 1}
\end{figure}
  1. Describe the correlation shown in Figure 1. Nadine chooses to use all of the data for Beijing from 2015 and draws the scatter diagram in Figure 2. She uses the same scales as Fred. \begin{figure}[h]
    \includegraphics[alt={},max width=\textwidth]{854568d2-b32d-44de-8a9c-26372e509c20-04_777_1509_1841_278} \captionsetup{labelformat=empty} \caption{Figure 2}
    \end{figure}
  2. Explain, in context, what Nadine can infer about the relationship between \(p\) and \(t\) using the information shown in Figure 2.
  3. Using your knowledge of the large data set, state a value of \(p\) for which interpolation can be used with Figure 2 to predict a value of \(t\).
  4. Using your knowledge of the large data set, explain why it is not meaningful to look for a linear relationship between Daily Mean Wind Speed (Beaufort Conversion) and Daily Mean Air Temperature in Beijing in 2015.
  5. Explain, in context, what Nadine can infer about the relationship between \(p\) and \(t\) using the information shown in Figure 2.
Question 2:
Part (a):
AnswerMarks Guidance
No (correlation)/weak (correlation)B1 Correct description of correlation (or equivalent); ignore reference to positive/negative; condone neutral
Part (b):
AnswerMarks Guidance
(Negative correlation...) As p(ressure) increases, t(emperature) decreasesB1 Correct inference, allow equivalent statements. "Negative correlation" on its own is B0. "Inversely proportional" on its own is B0.
Part (c):
AnswerMarks Guidance
990 to 1040 (hPa)B1 Answer in the range 990 to 1040 inclusive (ignore units)
Part (d):
AnswerMarks Guidance
Daily mean wind speed (Beaufort) is a qualitative variableB1 Correct explanation that wind speed (Beaufort) is qualitative/not quantitative. Allow 'categorical', e.g. 'given in words', e.g. 'wind speed is (always) light'. Do not allow 'not continuous' on its own. 
## Question 2:

**Part (a):**
No (correlation)/weak (correlation) | B1 | Correct description of correlation (or equivalent); ignore reference to positive/negative; condone neutral

**Part (b):**
(Negative correlation...) As p(ressure) increases, t(emperature) decreases | B1 | Correct inference, allow equivalent statements. "Negative correlation" on its own is B0. "Inversely proportional" on its own is B0.

**Part (c):**
990 to 1040 (hPa) | B1 | Answer in the range 990 to 1040 inclusive (ignore units)

**Part (d):**
Daily mean wind speed (Beaufort) is a qualitative variable | B1 | Correct explanation that wind speed (Beaufort) is qualitative/not quantitative. Allow 'categorical', e.g. 'given in words', e.g. 'wind speed is (always) light'. Do not allow 'not continuous' on its own.

---
\begin{enumerate}
  \item Fred and Nadine are investigating whether there is a linear relationship between Daily Mean Pressure, $p \mathrm { hPa }$, and Daily Mean Air Temperature, $t ^ { \circ } \mathrm { C }$, in Beijing using the 2015 data from the large data set.
\end{enumerate}

Fred randomly selects one month from the data set and draws the scatter diagram in Figure 1 using the data from that month.

The scale has been left off the horizontal axis.

\begin{figure}[h]
\begin{center}
  \includegraphics[alt={},max width=\textwidth]{854568d2-b32d-44de-8a9c-26372e509c20-04_794_1539_589_264}
\captionsetup{labelformat=empty}
\caption{Figure 1}
\end{center}
\end{figure}

(a) Describe the correlation shown in Figure 1.

Nadine chooses to use all of the data for Beijing from 2015 and draws the scatter diagram in Figure 2.

She uses the same scales as Fred.

\begin{figure}[h]
\begin{center}
  \includegraphics[alt={},max width=\textwidth]{854568d2-b32d-44de-8a9c-26372e509c20-04_777_1509_1841_278}
\captionsetup{labelformat=empty}
\caption{Figure 2}
\end{center}
\end{figure}

(b) Explain, in context, what Nadine can infer about the relationship between $p$ and $t$ using the information shown in Figure 2.\\
(c) Using your knowledge of the large data set, state a value of $p$ for which interpolation can be used with Figure 2 to predict a value of $t$.\\
(d) Using your knowledge of the large data set, explain why it is not meaningful to look for a linear relationship between Daily Mean Wind Speed (Beaufort Conversion) and Daily Mean Air Temperature in Beijing in 2015.\\
(b) Explain, in context, what Nadine can infer about the relationship between $p$ and $t$ using the information shown in Figure 2.\\

\hfill \mbox{\textit{Edexcel AS Paper 2 2023 Q2 [4]}}
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