The following data was collected to explore how the average number of hours a student studies per night and the student's GPA affect their ACTscore. The dependent variable is the ACT score, the first independent variable (x) is the number of hours spent studying, and the secondindependent variable (x2) is the student's GPA.Effects on ACT ScoresStudy HoursGPA ACT Score02171220322554265426Step 1 of 2: Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places.Copy Data

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Answered: The following data was collected to…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question 4Beachcomber Ltd is a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model:SALES=?+?AGE+?MIL+?ENGWhere SALES= amount that a vehicle is sold for($000’s), AGE = age of the vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained:The regression equation is ***** Coef StDev t-ratio p-value Predict or Constant 1.7586 0.2525 6.9648 0.0000 AGE 0.2124 0.3175 * 0.5042 MIL -0.7527 0.3586 -2.0991 ** ENG 4.8124 ***…
Does more education lower a person’s level of prejudice? The number of years of education and the score on a prejudice test for ten people is given in the following table. Higher scores on the test indicate more prejudice. Years of Education 12 15 14 13 18 10 16 12 10 4 Score on Prejudice Test 1 6 2 3 2 4 1 5 5 10 Construct a scatterplot for the data and briefly explain the type of relationship between the two variables. positive, moderate linear correlation positive, weak linear correlation negative, moderate linear correlation negative, weak linear correlation
Data is collected on the number of ice cream cones sold in a shop on a certain day and the number of people wearing sunglasses visiting the shop that same day. What type of relationship is most likely to exist between these two variables? positive correlation and causal relationship negative correlation and causal relationship positive correlation but not causal relationship negative correlation but not causal relationship
Sarah is interested in whether the extent to which parents are involved in their children's school differs based on students’ grade in school (i.e., first, second, third, etc.). What is the independent variable in Sarah's research question? Group of answer choices students degree of parent involvement grade level parents
Requirement: 1. Decide on which correlation analysis to use 2. State the null and alternative hypothesis Medical researchers believe that there is a relationship between smoking and lung damage. Data were collected from smokers who have had their lung function assessed and their average daily cigarette consumption recorded. Lung function was assessed in such a way that higher scores represent greater health. The researchers believe that the relationship between these variables may be influenced by the number of years for which the person has been a smoker. Lung function 2 Average cigarettes a day 45 Years of smoking 28 8 18 1 20 7 21 1 33 13 7 18 1 2 51 25 24 34 10 1 52 35 2 33 12 1 49 32 20 1 19 3 22 3 27 6. 29 8 38 16 48 26 39 21 32 8 7 18 1 4 26 25 10 18 1
Determine if the relation between independent variable and dependent variable given below has a positive, negative or no correlation: The amount of tea a person drinks and the intelligence level of a person. The starting salary earned and the education level. The height of a person and the weight of a person. The speed of the car and time taken for a journey. Smoking and lung disease.
This sentence is true or false?
Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of thecompany wants to know how different variables affect the sales of his vehicles. A random sample ofyearly data was taken with the view to testing the model:SALES=?+?AGE+?MIL+?ENGWhere SALES= amount that a vehicle is sold for($000’s), AGE = age of the vehicle, MIL= the totalmileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data wasprocessed using MINITAB and the following is an extract of the output obtained:The regression equation is *****Predictor Coef StDev t-ratio p-valueConstant 1.7586 0.2525 6.9648 0.0000AGE 0.2124 0.3175 * 0.5042MIL - 0.7527 0.3586 -2.0991 **ENG 4.8124 0.6196 7.7664 0.0000Analysis of VarianceSource DF SS MS F pRegression 3 413.1291 138.7097 *** 0.00Error…
I. Background The Food and Drug Administration (FDA) tries to find out whether there is a relation between the number of years people smoked and the percentage of lung damage. FDA asks you for your help to find it out. You interviewed twenty people who have smoked and obtained the following data. II. Technical report: a) Draw a scatter plot. b) Based on the scatter plot, explain whether the number of years and the percentage of lung damage are correlated. If they are correlated, discuss the strength of correlation, and the direction (positive or negative). c) Find the correlation coefficient r. Explain what r implies. d) Choose your own significance level a (1 suggests 0.1, 0.05 or 0.01). State and test the hypothesis. Explain what your findings mean. e) Do your observations in part (b) agree to the results from part (c) and (d)? Explain f) Find the regression line equation. Explain what the line implies. g) Draw the regression line on your scatter plot. h) A man has…
Rail ridership during the summer months in the North-East is believed to beclosely related to the number of tourists visiting the region. The following tableshows the data on the number of tourists and North-East ridership for the past16 years.Year Tourists( in millions) Rail Ridership (in millions) 2000 9 2.32001 4 1.9 2002 7 1.7 2003 5 1.8 2004 12 2.8 2005 13 2.9 2006 14 2.42007 20 4.8 2008 7 1.3 2009 5 1.12010 9…
For the following pairs of variables, indicate whether you would expect a positive correlation, a negative correlation, or close to 0 correlation. Maximum daily temperature and cooling costs Interest rates and number of loans Incomes of husbands and wives in dual career families Height and IQ Height and shoe size Score on the Math SAT and Verbal SAT scores Time spent on video games and college GPA Use of fertilizer and yield of crops
Statistics are widely used in Major League Baseball. Are the number of runs batted in (RBI) correlated to a hitter's batting average (AVG)? The following is a chart of 25 baseball players' statistics from 2016. Let the explanatory variable x = RBI and the response variable y = AVG. Player RBI HR AVG Salary (in millions) Justin Turner 90 27 0.277 5.100 Chris Iannetta 24 7 0.210 4.550 Coco Crisp 55 13 0.231 11.000 Adam Jones 83 29 0.265 16.000 Adrian Gonzalez 90 18 0.285 21.857 Jason Heyward 49 7 0.230 21.667 Jayson Werth 70 21 0.244 21.571 Evan Gattis 72 32 0.251 3.300 Jorge Soler 31 12 0.238 3.667 Brian McCann 58 20 0.242 17.000 David Ortiz 127 38 0.315 16.000 Chris Davis 84 38 0.221 21.119 Matt Wieters 66 17 0.243 15.800 J.D. Martinez 68 22 0.307 6.750 Leonys Martin 47 15 0.245 4.150 Hunter Pence 57 13 0.289 18.500 Aaron Hill 38 10 0.262 12.000 Jean Segura 64 20 0.320 2.600 Shin-Soo Choo 17 7 0.242 20.000 Mike Trout 100 29 0.315 16.083…

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