The following table shows the hot dogs bought from a street vendor over the course of eight days ("Demand"). Also shown is the temperature for each day in degrees Celsius. Complete parts a and b below. Temperature (°C) Demand 18 12 22 19 8 13 18 23 D 49 32 34 41 19 23 44 33 a. Calculate the slope and y-intercept for the linear regression equation for these data. (Round to two decimal places as needed.) b. Predict the demand for hot dogs on a day with a temperature of 21°C. The predicted demand for hot dogs on a day with a temperature of 21°C is (Round to the nearest integer as needed.)

The following table shows the hot dogs bought from a street vendor over the course of eight days ("Demand"). Also shown is the temperature for each day in degrees Celsius. Complete parts a and b below. Temperature (°C) Demand 18 12 22 19 8 13 18 23 D 49 32 34 41 19 23 44 33 a. Calculate the slope and y-intercept for the linear regression equation for these data. (Round to two decimal places as needed.) b. Predict the demand for hot dogs on a day with a temperature of 21°C. The predicted demand for hot dogs on a day with a temperature of 21°C is (Round to the nearest integer as needed.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

The table shows the approximate chirping rate at various temperatures for one type of cricket. Use the linear regression feature on a graphing calculator to determine an equation of the line that best fits the data. Round to the hundredths. ⒸEncikAn/Shutterstock.com X Temperature (°F) 50 60 70 80 100 Chirps per Minute 20 80 115 150 250
A cafe company wants to determine how the money they spend on Google ads impacts their monthly revenue. Over 6 consecutive months, they vary the amount they spend on their Ads (in $) and record the associated revenue (in $) for each month. The data is shown below: l Revenue 50 427 75 472 100 467 125 529 150 518 175 543 A) Develop a regression equation for predicting monthly revenue based on the amount spent with Ads. What is the y-intercept? B) What is the sample correlation between these two variables? C) What is the slope of your regression equation? Give your answer to two decimal places. D) Using a 0.05 level of significance, does this regression equation appear to have any value for predicting revenue based on Ads?
The following table shows the hot dogs bought from a street vendor over the course of eight days ("Demand"). Also shown is the temperature for each day in degrees Celsius. Complete parts a and b below. Temperature (°C) 20 Demand 49 11 23 32 36 19 40 5 17 10 21 16 44 20 D 34 a. Calculate the slope and y-intercept for the linear regression equation for these data. ŷ=+* (Round to two decimal places as needed.)
Use the data in the table below to complete parts (a) through (d). x 37 34 40 46 42 50 62 56 51 y 22 20 25 32 27 30 30 25 28 Find the equation of the regression line. y=
(please solve within 15 minutes I will give thumbs up)
The ages (in years) of five men and their systolic pressures. (You can use technology) Age, x 16 25 39 45 49 Systolic blood pressure, y 109 122 143 132 199 a. calculate the correlation coefficient, r b. calculate the critical r c. Is there a significant linear relationship between x and y? d. find the equation of regression line e Interpret the slope and the y-intercept f. Predict the systolic blood pressure for a man who is 40 years old.
Q.4. Obtain the equation of the line of regression of y on x from the following data and estimate the blood pressure when the age is 50 years. Age in years x Blood pressure y 50 142 40 120 71 162 35 110 60 140 45 125 52 155 47 140 36 111 40 135 65 150 59 153
At an online diamond trader site, the price for a diamond is dependent upon the weight of the diamond. The pricing information is given in the table below. x: Weight (in carats) 0.5 0.6 0.7 0.8 0.9 1.0 y: Price (in dollars) 2600 3000 3500 3950 4800 5700 a) Find the linear regression equation for this data where x is the weight of a diamond (in carats) and y is the corresponding price of the diamond (in $). The slope and y-intercept for the linear regression equation are as follows: slope = Blank 1. Fill in the blank, read surrounding text. y-intercept = Blank 2. Fill in the blank, read surrounding text. b) Use the linear regression equation to estimate the price of a diamond that weighs 0.65 carats. Blank 3. Fill in the blank, read surrounding text. dollars (Do not use the $ sign in the answer box.)
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. The equation of the regression line is y = 1.597x- 169.203. Wages (state), x Wages (federal), y 742 775 783 802 842 890 912 939 949 954 1,002 1,039 1,097 1,145 1,199 1,242 1,271 1,299 1,335 1,398 Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. There is a 90% chance that the predicted average weekly wages of federal government employees is between S and S given a state average weekly wage of $825. O B. We can be 90%…
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. The equation of the regression line is y = 1.454x- 36.984. Wages (state), x Wages (federal), y 712 778 789 801 843 878 927 937 939 958 1,014 1,054 1,116 1,146 1,191 1,248 1,270 1,302 1,335 1,401 Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. We can be 95% confident that when the average weekly wages of state government employees is $895, the average weekly wages of federal government employees will be between $ and…
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through o. Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs OxBillable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) Monthly Overhead Costs and Billable Hours Data Overhead Costs $385,000 Billable Hours 3,000 $425,000 4,000 $445.000 5,000 $497,000 6,000 $570,000 7,000 $590,000 8,000
The following table shows the hot dogs bought from a street vendor over the course of eight days ("Demand"). Also shown is the temperature for each day in degrees Celsius. Complete parts a and b below. Temperature (°C) 22 13 22 20 5 Demand 30 35 38 16 13 16 21 O 21 41 31 47 a. Calculate the slope and y-intercept for the linear regression equation for these data. ŷ=+x (Round to two decimal places as needed.) b. Predict the demand for hot dogs on a day with a temperature of 7°C. The predicted demand for hot dogs on a day with a temperature of 7°C is (Round to the nearest integer as needed.) of