本次CS代写的主要涉及如下领域: 北美程序代写,加拿大程序代写
Stat 151: Introduction to Applied Statistics
Assignment 2 Total Marks: 65
Please read the following instructions carefully:
 Assignment 2 is composed of THREE parts: Part 1: Lecture Problems and Part 2: Combined Lab and Lecture Problems, Part 3: Practice Problems (not for grading).
 For Part 1, please complete all of the assigned exercises by hand. In Part 2, use procedures you were taught in the lectures and you may either type the answers or write them by hand.
 Please organize and clearly label your solutions to each problem and staple ALL of your solutions together and hand them in altogether as instructed.
Part 1: Lecture Problems






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 CrownRump Length. In the article “The Human Vomeronasal Organ. Part II: Prenatal Develop ment” (Journal of Anatomy , Vol. 197, Issue 3, pp. 421–436), T. Smith and K. Bhatnagar examined the controversial issue of the human vomeronasal organ, regarding its structure, function, and identity. The following table shows the age of fetuses (x), in weeks, and length of crownrump (y), in millimeters.
(20 Marks: 6 Marks for a., 4 Marks for b., and 2 Marks for each of c. – g.)
x 
10 
10 
13 
13 
18 
19 
19 
23 
25 
28 
y 
66 
66 
108 
106 
161 
166 
177 
228 
235 
280 



 find the regression equation for the data points.
 graph the regression equation and the data points.
 describe the apparent relationship between the two variables under consideration.
 interpret the slope of the regression line.
 identify the predictor and response variables.
 identify outliers and potential influential observations.
 predict the crownrump length of a 19weekold fetus.





SSE are as follows:
SST =
Σ y2 −
( yi)2 n
SSR =
[ x y ( x y ) /n]2



SSE = SST − SSR.
 compute the coefficient of determination, r2.
 determine the percentage of variation in the observed values of the response variable explained by the regression, and interpret your answer.
 state how useful the regression equation appears to be for making predictions.
In 14.122  14.126, fill in the blanks.
14.122 
A value of r close to indicates that there is either no linear relationship between the variables or 
14.126 
a weak one. (1 Mark) If y tends to decrease linearly as x increases, the variables are linearly correlated. (1 Mark) 
14.128 
Determine whether r is positive, negative, or zero. (1 Mark) 
14.132 The linear correlation coefficient of a set of data points is 0.846. (3 Marks: 2 for a., 1 Mark for b.)
 Is the slope of the regression line positive or negative? Explain your answer.
 Determine the coefficient of determination.
14.150 Height and Score. A random sample of 10 students was taken from an introductory statistics class. The following data were obtained, where x denotes height, in inches, and y denotes score on the final exam. (8 Marks: 2 Marks for a., 6 Mark for b.)
x 
71 
68 
71 
65 
66 
68 
68 
64 
62 
65 
y 
87 
96 
66 
71 
71 
55 
83 
67 
86 
60 


 What sort of value of r would you expect to find for these data? Explain your answer.
 Compute r.
Part 2: Lab Problems
Complete the following: LAB 14.1, 14.2
LAB 14.1 Recently, statistics students at MacEwan completed a survey. Raw data can be found in the file STATISTICSSTUDENTSSURVEY. It contains the columns MOAGESTUDBIRTH (a variable that measures the age of a student’s mother when the student was born) and YRSFIRSTPHONE (a variable that measures the age at which students got their first mobile phone). A scatterplot of these two variables can be found below. Make sure you can create it. (14 marks: 1 mark for a, 1 mark for b, 2 marks for c, 2 marks for d, 1 mark for e, 1 mark for f, 3 marks for g, 3 marks for h)
 What is the range of data for the ages at which students obtained their first mobile phone?
 What is the range of data for the ages of mothers when their student children were born?
 Is there a discernible pattern to this data? Why do you think you see what you see?
 Assuming that there is no typo in the data, notice that one student appears to be an outlier in our data. That student was born when their mother was 32 years old and did not obtain their first mobile phone until they were 26 years old. Suggest a possible reason for this.
 Find the equation for the line of best fit for this data.
 Find the correlation for this data.
 Write down the correct answer from those within the brackets.
 The correlation between these two variables is (mild, moderate, strong) and (positive, negative).
 The slope of the line of best fit for this data is (positive, negative).
 The correlation coefficient of two variables and the slope of the line of best fit through the two variables will always have (different, the same) sign.
 Predict the age in years when a student obtained their first phone for a mother who was 50 years old when the student was born. Give two reasons why you would not be comfortable with the prediction.
LAB 14.2 Recently, a sample of 30 students was taken and the two variables “Weekly Hours on Social Media (X)” and “Final Average” (Y ) were measured. MINITAB generated the following output for this data. Find, by hand, the correlation for this data. Show your work. (3 marks)
Part 3: Practice Problems Not for Marks
P1. Height and Score. A random sample of 10 students was taken from an introductory statistics class. The following data were obtained, where x denotes height, in inches, and y denotes score on the final exam.
x 
71 
68 
71 
65 
66 
68 
68 
64 
62 
65 
y 
87 
96 
66 
71 
71 
55 
83 
67 
86 
60 

i i
 find the regression equation for the data points.
 interpret the slope of the regression line.
 compute and interpret the correlation coefficient r.
 compute and interpret the coefficient of determination r2.
 predict the score of a student who studies for 15 hours.
P2. Check your answers in P1. using MINITAB.