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Several bakeries in town were asked the price for different amounts of donuts in their shop. The scatter plot with a line of best fit was created from the data gathered.

Scatter plot included in picture.
Part A: Estimate the correlation coefficient. Explain your reasoning for the given value.
Part B: How many positive and negative residuals are there? Explain your reasoning.
Part C: Start with the point with the largest absolute value and interpret the point in terms of the context of the data.

1 Answer

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Final answer:

To estimate the correlation coefficient, examine the scatter plot. Determine the number of positive and negative residuals by comparing actual and predicted y-values. Interpret the point with the largest absolute value by considering the context of the data.

Step-by-step explanation:

To estimate the correlation coefficient, examine the scatter plot. If the points appear to be following a linear trend, then the correlation coefficient will be close to 1 or -1. If the points are scattered and have no apparent pattern, then the correlation coefficient will be close to 0. Use the scatter plot to estimate the correlation coefficient by visually determining the direction and strength of the relationship between the variables.

To determine the number of positive and negative residuals, compare the actual y-values (observed data) with the predicted y-values (values on the line of best fit). If the actual y-value is greater than the predicted y-value, the residual is positive. If the actual y-value is less than the predicted y-value, the residual is negative. Count the number of positive and negative residuals to determine how many of each there are.

To interpret the point with the largest absolute value, locate the point on the scatter plot and identify the corresponding values for the independent and dependent variables. Then, consider the context of the data. For example, if the scatter plot represents the price of donuts based on the quantity purchased, the point with the largest absolute value could indicate an outlier where the price is significantly higher or lower than expected for a particular quantity of donuts.

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