Tech App 1 Week 3 Project - STAT 3001 Student Name: Date: Instructions: To complete this project, you will need the following materials: · USE STATDISK.COM · username XXXXXXXXXX · Password Fatty11!...

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Tech App 1 Week 3 Project - STAT 3001 Student Name: Date: Instructions: To complete this project, you will need the following materials: · USE STATDISK.COM · username [email protected] · Password Fatty11! Part I. Analyze Data Instructions Answers 1. Open the file Car Measurements using menu option Datasets and then Elementary Stats, 13th Edition. This file contains information on a number of measurements related to cars. How many observations are there in this file? Look at the number of rows of data and the number of variables. 2-5 Analyze the data in this file and complete the following table, indicating for each variable what type of data it represents. Variable Qualitative/ Quantitative Discrete/ Continuous/ Neither Level of Measurement 1. Size 2. Braking (distance) 3. City (MPG) 4. Car 6. Would you consider this data to represent a sample or a population? Why? Part II. ScatterPlots 7. Create a scatterplot for the data in the Length (inches) and Braking distance (feet) columns. Paste it here. You may need to resize the plot once it is in this file. 8. Explain the visual relationship between Length and Braking distance. Is the relationship positive or negative, based on the scatter of points around the line, is the correlation weak, moderate or strong? 9. Create a scatterplot for the data in Displacement (liters) and Highway (MPG) columns. Paste it here. You may need to resize the plot once it is in this file. 10. Explain the visual relationship between Displacement and Highway MPG. Is the relationship positive or negative, based on the scatter of points around the line, is the correlation weak, moderate or strong? Part III. Correlation 11.Using Statdisk, calculate the linear correlation between the data in the Length and Braking distance columns. Paste your results in the answer box. 12.Explain the mathematical relationship between Length and Braking distance based on the linear correlation coefficient. Be certain to include comments about the magnitude and the direction of the correlation. 13.List the sample size and the degrees of freedom for this computation. 14.Using Statdisk, calculate the linear correlation coefficient between the data in the Displacement and Highway MPG columns. 15.Compare and contrast these two relationships: Length and Braking distance Displacement and Highway MPG How are they similar? How are they different? [Hint: Read Page 236 “Types of Correlation”] Part IV. Simple Regression Let’s say that we wanted to be able to predict the city MPG of a car based on its Weight in pounds. Using this sample data, perform a simple-linear regression to determine the line-of-best fit. Use the Weight as your x (independent) variable and City MPG as your y (response) variable. Use 3 places after the decimal in your answer. 16. Paste your results here: Answer the following questions related to this simple regression 17. What is the equation of the line-of-best fit? Insert the values for bo and b1 from above into y = bo + b1x. 18. What is the slope of the line? What does it tell you about the relationship between the Weight and City MPG data? Be sure to specify the proper units. 19.What is the y-intercept of the line? What does it tell you about the relationship between Weight and City MPG? 20. Using the regression equation, what would you predict for the City MPG of a car weighing 2250 pounds? Show your calculation and round to the nearest tenth. 21. Using the regression equation, let’s say you have a car with a City MPG of 29, what would the car weigh? Round to the nearest whole number. 22. Find the coefficient of determination (R2 value) for this data. What does this tell you about this relationship? [Hint: see definition on Page 255.] Part V. Multiple Regression Let’s say that we wanted to be able to predict the Highway MPG of a car based on · Displacement · Length · Braking Using this sample data, perform a multiple-regression using Displacement, Length, Braking distance with Highway MPG as the dependent variable. Refer to page 14 in the Stat Disk User’s Manual. 23. Paste your results here: 24. What is the equation of the line-of-best fit? The form of the equation is Y = bo + b1X1 + b2X2 + b3X3 (fill in values for b0, b1, b2, and b3). [Round coefficients to 2 decimal places.] 25. Using the multiple regression equation, what would you predict for the Highway MPG of a car whose · Length in inches is 184 · Braking distance in feet is 139 · Displacement in liters is 2.2 Round to the nearest tenth. 26. What is the R2 value for this regression? What does it tell you about the regression? [Hint: see definition on Page 255.] Submit your final draft of your Word file by going to Week 3, Project, and follow the directions under Week 3 Assignment 2. Please use the naming convention "WK3Assgn2+last name + first initial" as the Submission Title. 1
stat-3001-week-3-project-insturctions-ujjwunog.docx
Answered Same DayJan 31, 2021

Answer To: Tech App 1 Week 3 Project - STAT 3001 Student Name: Date: Instructions: To complete this project,...

Mohd answered on Feb 01 2021
141 Votes
Week 3 Project - STAT 3001
Student Name:     
Date:    
Instructions: To complete this project, you will need the following materials:
· USE STATDISK.COM
· username [email protected]
· Password Fatty11!
Part I. Analyze Data
    Instructions
    Answers
    1. Open the file Car Measurements using menu option Datasets and then Elementary Stats, 13th Edition. This file contains information on a number of measurements related to cars. How many observations are there in this file? Look at the number of rows of data and the number of variables.
    21 observations
10 Variables
    2-5 Analyze the data in this file and complete the following table, indicating for each variable what type of data it represents.
    Variable
    Qualitative/ Quantitative
    Discrete/ Continuous/ Neither
    Level of Measurement
    
    Size
    Qualitative
    Discrete
    Small-medium-large
    
    Braking (distance)
    Quantitative
    Continuous
    feet
    
    City (MPG)
    Quantitative
    Continuous
    mile_per_gallon
    
    Car
    Qualitative
    Discrete
    Name
    6. Would you consider this data to represent a sample or a population? Why?
    I would consider this data as a sample. Because it has only 21 observations, which is low.
Part II. ScatterPlots
    7. Create a scatterplot for the data in the Length (inches) and Braking distance (feet) columns. Paste it here. You may need to resize the plot once it is in this file.
    
    8. Explain the visual relationship between Length and Braking distance. Is the relationship positive or negative, based on the scatter of points around the line, is the correlation weak, moderate or strong?
    The relationship between length and braking distance is significantly moderate and positive.
    9. Create a scatterplot for the data in Displacement (liters) and Highway (MPG) columns. Paste it here. You may need to resize the plot once it is in this file.
    
    10. Explain the visual relationship between Displacement and Highway MPG. Is the relationship positive or negative, based on the scatter of points around the line, is the correlation weak, moderate or strong?
    The relationship between Displacement and highway MPG is significantly negative.
Strong reletionaship.
Part III. Correlation
    11.Using Statdisk, calculate the linear correlation between the...
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