4. Correlation and linear regression 4. A Zumba instructor remembers the data given in the following table, which shows the recommendedmaximum exercise heart rates for individuals of the given ages.Age (x years)20 40 60Maximum heart rate 170 153 136(y beats per minute)cucea. Find the linear correlation coefficient for the data.b. What is the significance of the value found in part a?c. Find the equation of the least-squares line.d. Use the equation from part c to predict the maximum exercise heart rate for a person who is 72.e. Is the procedure in part d an example of interpolation or extrapolation?

given data age x years 20 40 60 maximum heart rate y beats per minute 170 153 136 a) find…

Answered: 4. A Zumba instructor remembers the…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Example The marketing manager of Cadbury wants to test the effect of price on sales. Regression model: Sales = β0+ β1Price + error 1) In addition to price, the marketing researcher would like to find out whether there is a systematic trend in the sales. In other words, are sales increasing or decreasing over time? In order to test whether there is a systematic time trend in sales, in addition to the effects of price, please: Tip: the dependent variable is still sales. The independent variables would include price and weeknr (to capture time trend). Write the regression model for question 1 use the examle above to guide you?
Simple linear regression model helps to adjust out the effects of confounding factors in a statistical analysis. A. TrueB. FalseC. None of the above choices
Independent variable data is listed in cells B2 through B100, and dependent variable data is in cells C2 through C100. Which spreadsheet function would calculate the slope of a linear regression model of this data? Group of answer choices =SLOPE(B2:B100,C2:C100) =SLOPE(C2:C100,B2:B100) =SLOPE(B2,C2) =SLOPE(C2,C100,B2,B100)
x = number of traffic tickets y = Cost of auto insurance A test of linear correlation between traffic tickets and insurance cost produces a linear correlation coefficient of r = 0.705. Determine weather the regression line has a positive slope, or a negative slope
Linear Regression and Correlation. y 2 6.32 3 9.28 4 0.14 5 0.7 6 -4.04 7 3.22 Compute the equation of the linear regression line in the form y = mx + b, where m is the slope and b is the intercept. Use at least 3 decimal places. (Round if necessary) y = x + Compute the correlation coeficient for this data set. Use at least 3 decimal places. (Round if necessary) r= Compute the P-value (Use HA: slope = 0 for the alternative hypothesis.) Use at least 3 decimal places. (Round if necessary) P-value = At the alpha = 0.05 significance level, is the correlation significant? O Yes, significant correlation O No
1. Question: Malaria is a leading cause of infectious disease and death worldwide. It is also a popular example of a vector-borne disease that could be greatly aﬀected by the inﬂuence of climate change. Table 1 is a summary from a linear regression that uses dewpoint (°C) to predict malaria prevalence in West Africa.Fig. 1: Regression(a) Write the equation of the least square regression line. (b) Find the correlation coeﬃcient r. (c) IsthereastrongcorrelationbetweendewpointandmalariaprevalenceinWestAfrica? (d) Is there a negative association between dewpoint and malaria prevalence in West Africa?
Interpretation of the estimated coefficients of a Linear Regression Equation
Predict the average lifespan of an animal in years when the incubation/gestation time is 12 months. Animal: Nile crocodile, Aldabra giant tortoise, Lake sturgeon,Galápagos tortoise, Bowhead whale Average Lifespan (in Years):100 152 152 177 211 Incubation/ Gestation (in Months)3 8 0.25 4.7 regression equation and regression line if needed
Part and b. Thank you!
Demand for Smartphones The following table shows worldwide sales of a type of phone and their average selling prices in 2012, 2013, and 2017. Year 2012 2013 2017 Selling Price p ($100) 4 Sales q (billions) 0.5 3 1 2 2 Find the regression line (round coefficients to one decimal place). q(p) = 1.0166 X Use the regression line to estimate the demand (in millions of units sold) when the selling price was $320. 1016.6 million
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the following regression table where the dependent variable is the demandfor massage services in one city in the United States. Specifically, the dependent variable is the number of customers per hour (Models 1 and 2) or per day (Models 3 and 4). a) Explain why the coefficient for Population/1,000 in Model 2 is very different from the one in Model 4?

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