Run a regression analysis on the following data set, where y is the final grade in a math class and xis the average number of hours the student spent working on math each week.hours/weekGradeXy577111213131718184662.857.869.476.883.282.210095.2100State the regression equation y=mx+b, with constants accurate to two decimal places.What is the predicted value for the final grade when a student spends an average of 13 hours eachweek on math?Grade =Round to 1 decimal place.

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Answered: Run a regression analysis on the…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 6PPS

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.
What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.953 b=25.096 r2-0.9409 r=-0.97 Use this to predict the number of situps a person who watches 13 hours of TV can do (to one decimal place)
Estimate the number of server users y (employees) when the amount of memory storage used x (GB) is x = 15.4 in a time slot based on the regression line for your data. a. 30 employees b. 31 employees c. 32 employees d. 11.77 GB
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+ba=-1.044b=37.382Use this to predict the number of situps a person who watches 3 hours of TV can do (round to one decimal place)
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-0.962 b=32.772 r2=0.502681 r=-0.709 Use this to predict the number of sit ups a person who watches 7.5 hours of TV can do, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.721 b=24.707 r2-0.919681 r=-0.959 Use this to predict the number of situps a person who watches 11.5 hours of TV can do (to one decimal place) Question Help: Message instructor

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