Data was collected on h, the number of hot dogs sold, and p, the number of people attending a fair over a two week period. The least squares regression line has equation 0. 6p10. 0. The residual for the day when 520 people attended was 35. How many hot dogs were sold that day?.

The line that best matches a linear connection between two variables in data is called a least-squares regression line because it minimizes the vertical distance between the data points and the regression line.

The given equation is, y = 0.6p + 10.0

The residual for the day when 520 people attended was 35.

So, p = 520.

Plug 520 in the above equation, we get

y = 0.6(520) + 10.0

y = 312 + 10

y = 322

As, people attended was 35

So,

y = 322 + 35

y = 357

Hence, there are 357 dogs are sold that day.

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Data was collected on​ h, the number of hot dogs​ sold, and​ p, the number of people attending a fair over a two week period. The least squares regression line has equation 0. 6p10. 0. The residual for the day when 520 people attended was 35. How many hot dogs were sold that​ day?.

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Data was collected on h, the number of hot dogs sold, and p, the number of people attending a fair over a two week period. The least squares regression line has equation 0. 6p10. 0. The residual for the day when 520 people attended was 35. How many hot dogs were sold that day?.