Each of 25 adult women was asked to provide her own height (y), in inches, and the height of her father. The scatterplot below displays the results. Only 22 of the 25 pairs are distinguishable because some of the (x, y) pairs were the same. The equation of the least square regression line is .

One father’s height was x = 67 inches and his daughter’s height
was y = 61 inches. Draw and find the residual.

refer to following table .assume that the total population is 265 million and that the class under 5 contains babies who are not yet 1year old .determine the number of individuals in million to one decimal point in each age group

To find the residual for a given data point, we need to calculate the difference between the actual y-value (the daughter's height) and the predicted y-value (the y-value on the regression line for the given x-value, which is the father's height).

In this case, we are given that the father's height (x) is 67 inches and the daughter's height (y) is 61 inches. We need to find the residual for this data point.

To find the predicted y-value on the regression line, we can use the equation of the least square regression line. However, since you have not provided the equation, I am unable to calculate it and find the predicted y-value for you.

Please provide the equation of the least square regression line, or any additional information needed to calculate it, so that I can assist you further.

To find the residual for the given (x, y) pair, we need to first determine the predicted height of the daughter (ŷ) based on the least square regression line equation.

Since the equation of the least square regression line is not provided, we cannot directly calculate the predicted height. However, we can use the scatterplot to estimate the equation of the line and then find the predicted height.

Using the scatterplot, locate the point (67, 61) on the graph. Draw a vertical line from this point to the line of best fit. The point where this line intersects the line of best fit will give us the predicted height of the daughter.

Once we have the predicted height (ŷ), we can find the residual by subtracting the observed height (y) from the predicted height (ŷ).

Unfortunately, without the scatterplot or the equation of the least square regression line, I am unable to provide the specific values required to calculate the residual in this case.