not use ai please The following data were collected during a study of consumer buying patterns:Observation112y7723075340834307655610064799726878207491374101073111780122983133286Click here for the Excel Data Fileb. Obtain a linear regression line for the data.Note: Round your intermediate calculations and final answers to 3 decimal places.y=Xc. What percentage of the variation is explained by the rearession line?D

Answered: Image /qna-images/answer/de6fb482-7c26-40ac-b532-705723f6873d.jpg

Answered: The following data were collected…

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 4GP

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Find the mean hourly cost when the cell phone described above is used for 240 minutes.
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The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
Type the regression equation for “Area” and “Biomass” in context into your document. Interpret the slope of the regression line (in context of this data set) for “Area” and “Biomass”. is it meaningful to interpret the y-intercept for “Area” and “Biomass”? Why or why not?
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Perform Linear Regression Analysis for all three tabs:a. Ln Safety Belt Rate Fatalities Ln Safety Belt Rate 1071 3.951243719 1138 4.058717385 996 4.257030144 991 4.374498368 1038 4.365643155 1004 4.348986781 1154 4.382026635 1148 4.404277244 1207 4.417635062 1110 4.410371108 969 4.455509411 848 4.49980967 862 4.515245478 895 4.477336814 865 4.494238625 853 4.577798989 820 4.561218298 850 4.535820108 1083 4.521788577 948 4.531523646 953 4.519612298 856 4.525044142 b. Ln Unemployment Rate Fatalities Ln Unemployment Rate 1071 1.504077397 1138 1.547562509 996 1.526056303 991 1.648658626 1038 1.774952351 1004 1.791759469 1154 1.722766598 1148 1.481604541 1207 1.386294361 1110 1.410986974 969 1.757857918 848 2.312535424 862 2.341805806 895 2.261763098 865 2.104134154 853 1.987874348 820 1.902107526 850 1.808288771 1083 1.774952351 948 1.526056303 953 1.360976553 856 1.098612289 c. Ln Median…
Statistics Question
The following are the intelligence quotients (IQ) and the grade point average (GPA) of incoming Grade 12 students. If a significant relationship exists between the variables, perform a regression analysis. What GPA will students A and B obtain if their IQs are 159 and 92, respectively? Support your answer with computations/tables and draw the corresponding scatter diagram. Student IQ GPA 1 153 94 120 87 108 89 135 93 97 85 110 86 155 95 126 88 122 86 10 94 84 23455 6 7 8 9은
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Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. height 775 619 519 508 491 474 (a) x=503 feet (b) x=644 feet Stories, y 53 47 44 42 39 38 (c) x=798 feet (d) x=734 feet

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