could you help to check the solution to the 3 questions,is the answer correct?

Histogram of PULocationl Histogram of DOLocation! 40 80 120 20 40 60 Frequency Frequency O O 0 100 200 100 200 PULocationID DOLocationID (1) Depend on the histogram shown above, the PULocationID and DOLocationID is not normally distributed, the most frequency for the pickup and get off location from PULocationID is shown around 150 zone, and the most frequency for the pickup and get off location from DOLocationID is shown around to zone and 240 zone.+O O 50 100 O O O 8 total.amount O O O O 0 10 20 30 40 (2) travel.distance As the picture shown and the output shown in the console, there is a strong linear regression relationship between total.distance and total amount, the equation is: y = 0.279x + 1.356-residual plot Residuals for occupations I O O 0.0 Residual Frequency 100 200 -0.4 80 O 0 200 400 -0.6 -0.2 0.2 0.6 Index Residual (3) There are multi linear regression relationship between them, the equation is: y = 0.991x1+ 0.997x2+0.0188x3+0.985x4+0.986x5+ 1.163x6 + 1.894x7 + 0.0286+e. The 90% confidence interval of it is: 1.7290- Above picture and out put shown there is outliers which are 70 and 67, remove them.+Describe briey in one or two sentences the main research question. This is similar to the last sentence of our class examples. 0 4J ' (1 ). Summarize the data for PULocationID and DOLocationlD Calculate the ANOVA and make a histogram for PUlocationID and DOlocationID, describe the shape of the histogram check which area has the most people getting on and off} .J (2). Is there a linear regression relationship between the trip distance and the total amount payment? Please make a scatterplot using R and calculate the least squares regression equation that predicts the total amount from distance. (3)_Is there a multiple linear regression relationship between the total amount and several types of payment amounts? Make a tted value, are there any outliers? Please remove the outliers and make a histogram for the residual outliers. If the overall model was signicant, calculate 90% condence intervals where appropriated .J 4:! .J