Hope this helps but I think it might be:
Part A: c=0.75p
the cost of shipping for 2 pounds
c=0.75p
c=0.75*2
c=$1.50
Part B: c=0.05p
Answer:
y(.82)*1.08
Step-by-step explanation:
You multiply by .82 to get the cost of the game after the discount and then by 1.08 to add the tax and total amount.
Answer:
Residual = -2
The negative residual value indicates that the data point lies below the regression line.
Step-by-step explanation:
We are given a linear regression model that relates daily high temperature, in degrees Fahrenheit and number of lemonade cups sold.

Where y is the number of cups sold and x is the daily temperature in Fahrenheit.
Residual value:
A residual value basically shows the position of a data point with respect to the regression line.
A residual value of 0 is desired which means that the regression line best fits the data.
The Residual value is calculated by
Residual = Observed value - Predicted value
The predicted value of number of lemonade cups is obtained as

So the predicted value of number of lemonade cups is 23 and the observed value is 21 so the residual value is
Residual = Observed value - Predicted value
Residual = 21 - 23
Residual = -2
The negative residual value indicates that the data point lies below the regression line.
Answer:
0.25
Step-by-step explanation:
72% of courses have final exams and 46% of courses require research papers which means probability of 0.72 for courses that have final exams and 0.46 for courses that require research papers.
31% of courses have a research paper and a final exam, which means probability of 0.31 for both courses with exams and research papers, using Venn diagram approach, find picture attached to the solution.
P(R or E) = P(R) + P(E) - P(R and E), which gives:
P(R or E) = 0.15 + 0.41 - 0.31
P(R or E) = 0.25.