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Amélie runs a bakery. She wants to find out whether her cake sales are affected by the weather conditions. She recorded the daily temperature and the number of cakes she sold on different days of the year. The table shows the data she gathered.

\begin{tabular}{|r|r|}
\hline Daily Temperature ([tex]${ }^{\circ}$[/tex] F) & Cakes Sold \\
\hline 42 & 39 \\
\hline 45 & 52 \\
\hline 48 & 31 \\
\hline 54 & 61 \\
\hline 59 & 72 \\
\hline 62 & 35 \\
\hline 64 & 61 \\
\hline 65 & 34 \\
\hline 67 & 58 \\
\hline 75 & 24 \\
\hline 84 & \\
\hline
\end{tabular}

The correlation coefficient is close to [tex]$\square$[/tex].

Based on this information, we can conclude that Amélie's cake sales are [tex]$\square$[/tex] affected by the daily temperature.

Sagot :

To determine how Amélie's cake sales are affected by the daily temperature, we first calculate the correlation coefficient between the daily temperatures and the number of cakes sold. The correlation coefficient quantifies the type and strength of the relationship between two variables.

1. The correlation coefficient is close to [tex]\(\boxed{-0.1008}\)[/tex].

This numerical value indicates the strength and direction of the relationship between temperature and cake sales:

- A correlation coefficient close to 1 indicates a strong positive relationship.
- A correlation coefficient close to -1 indicates a strong negative relationship.
- A correlation coefficient around 0 indicates no relationship.

2. Based on this information, we can conclude that Amélie's cake sales are [tex]\(\boxed{\text{weakly}}\)[/tex] affected by the daily temperature.

The correlation coefficient of -0.1008 suggests there is a very weak negative relationship between daily temperature and the number of cakes sold, meaning that temperature has very little impact on the number of cakes sold.
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