MATH2392语言讲解、辅导R程序、R编程讲解
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Assignment 4
Due date: Friday, 23 October, 2020
1. The data file satisfaction.csv (located on Canvas -> Assignment 4)
recoded satisfaction score for two flights. This data has been collected
from different group of passages. Complete the following tasks using R.
a. Read the data set into R. Write a simple code to compute the mean of
satisfaction score for each flight.
b. Create a comparison boxplot for the score of two flights.
c. Perform the hypothesis test for the satisfaction score of the two flights.
Does the sample provide enough evidence to support the claim that the
mean score satisfaction of flight 1 is less than the mean score
satisfaction of flight 2?
d. Extract p-value from your output results. Base on the p-value, make
simple conclusion about your test. (ie., whether or not the null
hypothesis should be rejected. The null hypothesis in this problem is:
mean score satisfaction of flight 1 is equal to the mean score
satisfaction of flight 2).
e. Check whether the assumption of equal variance is valid or not.
Copy and Paste the coding and output on your answer sheet.
Submit your answer sheet with simple answer to the question where it is
required.
(2 + 1 + 2 + 2 + 1 = 8 marks)
2. Researchers would like to know if the variation in the weight that plane
carries affect its fuel consumption. The dataset consumption.csv on
Canvas -> Assignment 4 presents the fuel consumption and the weight
that plane is carrying. Use R to complete the following tasks.
a. Read the data set consumption.csv into R. Compute the correlation
between fuel consumption and weight.
b. Create a scatter plot for fuel consumption and weight. Does the plot
indicate that there is linear relationship between the fuel consumption
and weight?
c. Create the regression model with fuel consumption as dependent
variable and weight as independent variable.
d. Check the result by extracting the estimated coefficient, the fitted
values and residuals;
e. Add a line of best-fit to the scatter plot.
Copy and Paste the coding and output on your answer sheet.
Submit your answer sheet with simple answer to the question where it is
required.
(2 + 1 + +1 + 2 + 1 = 7 marks)
Assignment 4
Due date: Friday, 23 October, 2020
1. The data file satisfaction.csv (located on Canvas -> Assignment 4)
recoded satisfaction score for two flights. This data has been collected
from different group of passages. Complete the following tasks using R.
a. Read the data set into R. Write a simple code to compute the mean of
satisfaction score for each flight.
b. Create a comparison boxplot for the score of two flights.
c. Perform the hypothesis test for the satisfaction score of the two flights.
Does the sample provide enough evidence to support the claim that the
mean score satisfaction of flight 1 is less than the mean score
satisfaction of flight 2?
d. Extract p-value from your output results. Base on the p-value, make
simple conclusion about your test. (ie., whether or not the null
hypothesis should be rejected. The null hypothesis in this problem is:
mean score satisfaction of flight 1 is equal to the mean score
satisfaction of flight 2).
e. Check whether the assumption of equal variance is valid or not.
Copy and Paste the coding and output on your answer sheet.
Submit your answer sheet with simple answer to the question where it is
required.
(2 + 1 + 2 + 2 + 1 = 8 marks)
2. Researchers would like to know if the variation in the weight that plane
carries affect its fuel consumption. The dataset consumption.csv on
Canvas -> Assignment 4 presents the fuel consumption and the weight
that plane is carrying. Use R to complete the following tasks.
a. Read the data set consumption.csv into R. Compute the correlation
between fuel consumption and weight.
b. Create a scatter plot for fuel consumption and weight. Does the plot
indicate that there is linear relationship between the fuel consumption
and weight?
c. Create the regression model with fuel consumption as dependent
variable and weight as independent variable.
d. Check the result by extracting the estimated coefficient, the fitted
values and residuals;
e. Add a line of best-fit to the scatter plot.
Copy and Paste the coding and output on your answer sheet.
Submit your answer sheet with simple answer to the question where it is
required.
(2 + 1 + +1 + 2 + 1 = 7 marks)