Answer the following questions regarding the two variables under consideration in a regression analysis.a. What is the dependent variable called?b. What is the independent variable called?What other name(s) refer(s) to the dependent variable? Select all that apply.outlierexplanatoryextrapolationleast-squaresWhat other name(s) refer(s) to the independent variable? Select all that apply.least-squarespredictorextrapolationinfluentialerrorresponsepredictorinfluentialerrorresponseexplanatoryoutlier

a. The dependent variable is the variable that is being predicted or explained by the independent…

Answered: Answer the following questions…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

We expect a car's highway gas mileage to be related to its city gas mileage (in miles per gallon, mpg). Data for all 1259 vehicles in the government's 2019 Fuel Economy Guide give the regression line highway mpg = 8.720 + (0.914x city mpg) for predicting highway mileage from city mileage. 1 O Macmillan Learning (b) What is the intercept? Give your answer to three decimal places. intercept: Why is the value of the intercept not statistically meaningful? The value of the intercept is an average value calculated from a sample. The value of the intercept represents the predicted highway mileage for city gas mileage of 0 mpg, and such a prediction would be invalid since 0 is outside the range of the data. The value of the intercept represents the predicted highway mileage for slope 0. O The value of the intercept represents the predicted city mileage for highway gas mileage of 0 mpg, and such a car does not exist. mpg
19. You might think that increasing the resources available would elevate the number of plant spe- cies that an area could support, but the evidence suggests otherwise. The data in the accompany- ing table are from the Park Grass Experiment at Rothamsted Experimental Station in the U.K., where grassland field plots have been fertilized annually for the past 150 years (collated by Harpole and Tilman 2007). The number of plant species recorded in 10 plots is given in response to the number of different nutrient types added Plot 1 2 3 4 5 6 7 8 9 10 Number of nutrients added 0 0 0 3144 E2 3 Number of plant species 36 36 32 34 33 30 20 23 21 16
In baseball, two statistics, the ERA (Earned Run Average) and the WHIP (Walks and Hits per Inning Pitched), are used to measure the quality of pitchers. For both measures, smaller values indicate higher quality. The following computer output gives the results from predicting ERA by using WHIP in a least-squares regression for the 2017 baseball season. Variable DF Estimate SE T Intercept 1 -5.0 0.26 - 19.3 WHIP 1 6.8 0.14 47.4 Which of the following statements is the best interpretation of the value 6.8 shown in the output? ERA is predicted to increase by 6.8 units for each 1 unit increase of WHIP. WHIP is predicted to increase by 6.8 units for each 1 unit increase of ERA. For a pitcher with 0 units of WHIP, the ERA is predicted to be approximately 6.8 units. For a pitcher with 0 units of ERA, the WHIP is predicted to be approximately 6.8 units. Approximately 6.8% of the variability in ERA is due to its linear relationship with WHIP.
A scatter plot shows the relationship between two quantitative variables. Each of the six scatter plots pictured shows the least-squares regression line for the corresponding data set. Classify each scatter plot according to whether the least-squares regression line has a meaningful ?y-intercept value.
The data in the table represent the number of licensed drivers in various age groups and the number of fatal accidents within the age group by gender. Complete parts (a) to (c) below. Click the icon to view the data table. C... (a) Find the least-squares regression line for males treating the number of licensed drivers as the explanatory variable, x, and the number of fatal crashes, y, as the response variable. Repeat this procedure for female Find the least-squares regression line for males. ŷ=0x+0 (Round the slope to three decimal places and round the constant to the nearest integer as needed.) Data for licensed drivers by age and gender. 21-24 25-34 35-44 45-54 55-64 65-74 > 74 Number of Male Fatal Licensed Age Drivers (000s) < 16 12 16-20 6,424 6,914 18,068 20,406 Number of Number of Female Fatal Crashes Licensed (Males) Drivers (000s) 227 12 6,139 Crashes (Females) 77 2,113 1,534 5,180 5,016 6,816 8,567 17,664 2,780 7,990 20,047 2,742 19,984 14,441 8,386 5,375 19,898 14,328 8,194…
Statistical software is generally used to test the significance of a regression model. The table below shows software output for a least squares regression line. Fill in the blanks with the correct answers, using the table above. Assume a significance level of 0.05. The variable "unemp" is the_______variable. The value of the slope of the regression line is_______. The slope of the regression line is not significantly different from______because the p-value is______ which is larger than 0.05.
Home Sale Prices. Regarding the relationship between the sale price of a home and the predictor variables size in square feet and type of roof (tile or non-tile). In that exercise, we considered the regression of price on size and roof, the indicator variable for type of roof. a. Obtain a plot of price versus size with different plot symbols for homes having a tile roof and for homes having a non-tile roof. Based on this plot, does it appear that roof is a useful predictor variable? Explain your answer. b. Obtain the regression analysis of price on size and roof. Conduct the t-tests for the individual utility of the two predictor variables at the 5% level of significance. Interpret your results. c. Based on the output in part (b), obtain the individual regression equations relating price to size for homes having tile roofs and for homes having non-tile roofs. d. Obtain plots of residuals versus fitted values, residuals versus size, residuals versus roof, and a normal probability plot…
when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
4. Housing Prices in New YorkWe have looked at predicting the price (in s) of New York homes based on the size (in thousands of square feet), using the data in HomesForSaleNY. Two other variables in the dataset are the number of bedrooms and the number of bathrooms. Use technology to create a multiple regression model to predict price based on all three variables: size, number of bedrooms, and number of bathrooms. Price Size Beds Baths 145 1.3 3 1.5 875 2.9 7 3.75 300 1.5 3 2.5 370 1.1 2 1 268 1.5 2 2 1399 4.8 6 5 1125 3.1 3 2.5 299 1.4 3 2 110 1.2 3 1 2999 6 7 8 170 1 2 1 269 1.5 3 1.5 150 1 2 1.5 288 1.8 3 2.1 350 1.3 3 2 120 0.9 1 1 309 2.4 4 2.5 1500 1.5 2 1.5 635 2.5 4 2.5 350 0.9 2 1 459 1.8 4 2.5 275 2.9 4 1.5 275 1.8 3 2 2500 3.7 3 3 187 1.4 3 1.5 238 1.7 3 1.5 155 0.7 1 1 175 1.6 3 1.5 569 3.2 4 2 105 1.2 2 2.5 a) Which of the variables which are significant at the 5% level? b) Which variable is the most…
Do movies of different types have different rates of return on their budgets? Here's a regression of USGross (SM) on Budget for comedies and action movies with an indicator variable. Complete parts (a) through (d). Dependent variable is: USGross ($M) Coefficient SE(Coeff) - 6.78278 16.95 1.00523 Variable Constant Budget ($M) Comedy 24.0373 0.1613 11.73 t-ratio P-value -0.400 0.6907 6.23 <0.0001 2.05 0.0451 a) Write out the regression model. USGross = + ( Budget + (Comedy R-squared = 32.8% R-squared (adjusted) = 31.0% s = 47.51 55 degrees of freedom
Which of the following data sets or plots could have a regression line with a negative slope? Select all that apply. Select all that apply: the difference in the number of ships launched by competing ship builders as a function of the number of months since the start of last year the number of hawks sighted per day as a function of the number of days since the two-week study started the total number of ships launched by a ship builder as a function of the number of months since the start of last year the average number of hawks sighted per day in a series of studies as a function of the number of days since the ten-week study started
The data shows a systolic and a diastolic blood pressure of certain patients. Find the linear regression eqation, using the first variable (systolic) as the independent variable. Find the best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140. Use a significance level of x Systolic Diastolic 116 82 124 88 112 72 144 95 138 96 112 76 145 88 124 76 130 90 129 94 1)Find the correlation coefficient. 2)State the appropriate critical r value to use to test the claim that the correlation between systolic blood pressure and diastolic blood pressure is significantly different from 0 3)The correlation between diastolic blood pressure and systolic blood pressure is: significant, not significant, weak, none 4)The best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140 is closest to 1pts

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS