Heights and answers to the question, “How much would you like to weigh?” were recorded for n=126 women in a statistics class. A regression equation for y=desired weight (in pounds) and x=height (in inches) isEstimated mean desired weight = -65.4 + 2.90 (Height)c. What is the estimated mean desired weight for college women who are 65 inches tall?respond with number only, one decimal place[Text box for response]

The regression equation is y = -65.4 + 2.90x, where the independent variable x defines the height…

Answered: Heights and answers to the question,…

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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A packaging company fills bags so that each bags has an average weight of 250 grams. The owners take a sample of bags and records the weight (grams) of each. They found the following information: Five-Number Summary (in grams) Min 213.97 Q1 236.34 Q2 244.1 Q3 255.47 Max 272.5 75% of bags weigh more than which amount?
The percentage of scores falling below a z-score of .65
ABC company has recently experienced a sharp decline in its stock price. Its current (time 0) stock price is $42.65, and this morning, it paid $5.00 per share. Given that the stock price four years ago was $82.88, complete the following time series of data by determining the missing values. t= -3, Pt =$83.43, Divt = $16.03, Rt = (1)t= -2, Pt =$85.20, Divt =(2), Rt = 22.8482%t= -1, Pt =(3), Divt =$17.50, Rt = 20.6572%t= 0, Pt =$42.65, Divt =$5.00, Rt =(4)
The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. Copy-paste the data and run the analysis using MS Excel. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 What is the computed R square of the resulting multiple linear regression and its interpretation?
Please answer... I'm needed only 1 hours time to dd .... Thank u
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. (Answer in Excel showing formulas for answers)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…
Can you solve for the p-value and is H0 rejected or not rejected?
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The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $6 million. Is the result close to the actual number of viewers, 8.9 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) Click the icon to view the critical values of the Pearson correlation coefficient r. 98 3.5 3 7 13 12 13 10 2 6.8 6.3 10.2 8.5 4.4 1.8 2.7 What is the regression equation? y=+x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $6 million? The best predicted number of viewers for a television star with a salary of $6 million is million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 8.9 million? O A. The result is very close to the actual number of viewers of 8.9 million. O B. The…
Find Karl person's coefficient of correlation using regression coefficient byr=-0.56, bry=-0.83 Answer:
The accompanying table shows a portion of data that refers to the property taxes owed by a homeowner (in $) and the size of the home (in square feet) in an affluent suburb 30 miles outside New York City. Click here for the Excel Data File Taxes Size 21,987 2,403 17,353 2,451 29,238 2,866 a. Estimate the sample regression equation that enables us to predict property Taxes on the basis of the size of the home. (Round your answers to 2 decimal places.) Taxes = + Size. b. Interpret the slope coefficient. O As Property Taxes increase by 1 dollar, the size of the house increases by 6.71 ft. O As Size increases by 1 square foot, the property taxes are predicted to increase by $6.71. c. Predict the property Taxes for a 1,400-square-foot home. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.) Taxes
Suppose you are told your BMI is 32, the 70th percentile for your age and sex. Please interpret this percentile age: 28 Female

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