Use the following data set to find the equation of the regression line. Show the output and the equation in an Excel file. Click on the download arrow to download the document. You must show your Excel output to receive full credit. time period sales 1 8 2 7 3 9 4 10 5 10 6 11 7 12 8 10 9 13 10 15 11 12 12 14

Use the following data set to find the equation of the regression line. Show the output and the equation in an Excel file. Click on the download arrow to download the document. You must show your Excel output to receive full credit. time period sales 1 8 2 7 3 9 4 10 5 10 6 11 7 12 8 10 9 13 10 15 11 12 12 14

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

See similar textbooks

Similar questions

Use Excel Spreadsheets, Google Sheets, or GeoGebra to create a scatter plot for the data below. (You will upload your graph in the next question.) Use the graph to answer the questions below the table. The following data are the morning and evening high tide levels for Charleston, SC from January 1-14,2017. The information for the PM high tide for January 4 is missing. Create a scatter plot. Find the regression line and use it to estimate the PM high tide for January 4. Then find the correlation coefficient. (NOTE: The first column identifies the day. This data will not be used in the scatter plot.) Day AM High (in feet), xx PM High (in feet), yy 1 5.6 4.8 2 5.5 4.8 3 5.4 4.9 4 5.2 5 5.0 5.1 6 5.2 5.0 7 5.4 4.9 8 5.7 5.0 9 6.0 5.1 10 6.3 5.3 11 6.4 5.4 12 6.5 5.4 13 6.4 5.4 14 6.2 5.3 Source: SCDHEC.gov
The table gives the amount of money (in dollars) spent on football by a major university. Letting a represent the number of years since 2005, and letting y represent the amount of money spent on football, in thousands of dollars, use the regression capabilities of a graphing calculator to find the equation of the line of best fit. Round values off to the nearest hundredth. Then, use your equation to make the following predictions. Year 2005 2006 2007 2008 2009 2010 Dollars spent on football 165,000 196,000 210,000 226,000 242,000 279,000 The equation of the line of best fit is: Hint Predict the amount of money that will be spent on football in the year 2024. +A Predict the amount of money that will be spent on football in the year 2041.
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, 2.9 million? Use a significance level of 0.05
The table gives the amount of money (in dollars) spent on football by a major university. Letting x represent the number of years since 2006, and letting y represent the amount of money spent on football, in thousands of dollars, use the regression capabilities of a graphing calculator to find the equation of the line of best fit. Round values off to the nearest hundredth. Then, use your equation to make the following predictions. Year 2006 Dollars spent on football 173,000 The equation of the line of best fit is: Hint 2009 2010 2011 2007 2008 19 000 210,000 223,000 243,000 271,000 Predict the amount of money that will be spent on football in the year 2022. Predict the amount of money that will be spent on football in the year 2041.
The table gives the amount of money (in dollars) spent on football by a major university. Letting r represent the number of years since 2010, and letting y represent the amount of money spent on football, in thousands of dollars, use the regression capabilities of a graphing calculator to find the equation of the line of best fit. Round values off to the nearest hundredth. Then, use your equation to make the following predictions. 2010 Dollars spent on football | 166,000 Year 2011 2012 2013 2014 2015 194,000 202,000 224,000 241,000 284,000 The equation of the line of best fit is: Hint Predict the amount of money that will be spent on football in the year 2023. Predict the amount of money that will be spent on football in the year 2043.
The average temperature in a certain city has a statistically significant correlation to the monthly precipitation, measured inches. The regression line y = 0.22x +11.69 models this relationship when the temperature is between 75 and 90 degrees. Use the line to predict the monthly precipitation if the temperature is 89 degrees. Round your answer to the nearest hundredth. Inches Keypad Keyboard Shortcuts
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.5 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.9 per 10 million people? Click the icon to view the data. Data table Find the equation of the regression line. Internet Users Per 100 Nobel Laureates V = + (Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) 79 5.4 79.6 24.5 78.7 8.5 44.7 0.1 83.6 6.1 38.6 0.1 90.2 25.5 89.4 7.7 79.1 9. 83.1 12.8 52.7 1.9 76.8 12.7 57.1 3.3 79.8 1.5 92.3 11.5 93.8 25.7 64.7 3.1 58.2 1.9 67.3 1.7 94 31.8 84.5 31.3 87 18.9 77.1 10.7
Please solve for A or B and the missing values
Spring is a peak time for selling houses. The file SpringHouses contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes sold in Ft. Thomas, Kentucky, in spring 2018 (realtor.com website) Click on the datafile logo to reference the data. DATA file a. The Excel output for the estimated regression equation that can be used to predict the selling price given the number of bathrooms, square footage, and number of bedrooms in the house: SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression statistics Regression Residual Total Multiple R R Square ANOVA Adjusted R Square Standard Error Observations 0.7429 0.5519 0.4907 61948.6931 Regression statistics Regression Residual Total df Intercept Sq Ft Beds Lower 95% 0.9353 -145129.5298 Intercept Baths 0.9528 -49383.5243 0.0180 Sq Ft Beds 0.0326 Does the estimated regression equation provide a good fit to the data? Explain. Hint: If R is greater than 45%, the…
Caselet #1 ADVERTISEMENT A marketing executive wishes to determine whether there is a relationship between the number of television commercials aired per week and the number of sales (in thousand pesos) of a product. The data for the sample follow. Number of Ads, x 2 8. 8. 10 12 Sales, y 2 4 7 6. 10
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.4 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.7 per 10 million people? X Click the icon to view the data. Find the equation of the regression line. ŷ=+x (Round the constant to one decimal place as needed. Round the coefficient to thre Data table Internet Users Per 100 80.1 79.2 78.4 45 82.9 38.4 89.5 88.8 79.1 83.3 52.7 76.5 57.1 79.4 93.1 94.8 64.5 57.7 67.3 94.1 84.6 86.6 78.5 Nobel Laureates 5.5 24.4 8.7 0.1 6.1 0.1 25.4 7.6 9 12.8 1.9 12.6 3.3 1.5 11.3 25.5 3.1 1.9 1.7 32 31.3 18.8 10.8
Data given below are on the adjusted gross income and the amount of itemized deductions taken by taxpayers. Data were reported in thousands of dollars. With the estimated regression equation = 4.68 +0.16x, the point estimate of a reasonable level of total itemized deductions for a taxpayer with an adjusted gross income of $52,500 is $13,080. Click on the datafile to reference the data. Excel File: data14-37.xlsx Adjusted Gross Income ($1000s) 22 27 32 48 65 85 120 Reasonable Amount of Itemized Deductions ($1000s) Use the estimated regression coefficients rounded to 2 decimals in your calculations. a. Develop a 95% confidence interval for the mean amount of total itemized deductions for all taxpayers with an adjusted gross income of $52,500 (to 2 decimals). Any deductions exceeding the $ 9.6 9.6 10.1 11.1 13.5 17.7 25.5 $9.2739 thousand to $ 16.886 thousand b. Develop a 95% prediction interval estimate for the amount of total itemized deductions for a particular taxpayer with an…