The following set of experimentally observed data (See Table below) seem to follow alinear relationship. Design a linear estimation model that best fits the data.x (Independent variables)1.02.03.04.05.0STEPS:y (Dependent variables)1.21.93.24.15.31. Calculate the slope and intercept of the model.2. Write the estimation function (i.e. the equation of the line).3. Plot the data in the table and the estimation function (model) on the same x-y axesusing tools like MATLAB, Python, etc.

Answered: Image /qna-images/answer/0d75b704-23cb-48cf-99b2-37326f0d1509.jpg

Answered: The following set of experimentally…

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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A consulting firm estimates the following quarterly sales forecasting model: Qt=a+bt+cD The equation is estimated using quarterly data from 2010-2020/// (-1. 43). The variable D is a dummy variable for the second quarter where: D=1 in the second quarter, and 0 otherwise. The results of the estimation are: DEPENDENT VARIABLE: OBSERVATIONS: VARIABLE INTERCEPT T D Multiple Choice O QT R-SQUARE 43 0.8644 O No, since 1.86 < 2.704 No, since 0.55 < 1,86 Give the above, at the 1 percent level of significance. Is there a statistically significant trend in sales? No. since 102 <2704 Yes, since 1.86 0.55 F-RATIO 127.5 Yes, since 3.38 2.704 PARAMETER STANDARD ESTIMATE 22.50 1.86 2.00 ERROR 9.32 0.55 0.71 P-VALUE ON F 0.0001 T-RATIO P-VALUE 2.41 0.0201 3.38 0.0016 2.82 0.0075
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.8 8.2 6.8 3.5 2.8 2.8 2.3 0.5 y 13.9 10.8 10.1 7.2 6.5 6.5 6.3 4.8 x = thousands of automatic weapons y = murders per 100,000 residents This data can be modeled by the equation y = 0.81x + 4.35. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. A) How many murders per 100,000 residents can be expected in a state with 7 thousand automatic weapons? Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 7.8 thousand automatic weapons? Answer = Answer = Round to 3 decimal places.
The owners of a chain of ice cream stores have the business objective of improving the forecast of daily sales so that staffing shortages can be minimized during the summer season. As a starting point, the owners decide to develop a simple linear regression model to predict daily sales based on atmospheric temperature. They select a sample of 15 consecutive days. The results are shown in the accompanying table. Complete parts (a) through (f) below. Click the icon to view the data table. E Click the icon to view a table of critical values of the Durbin-Watson statistic. a. Assuming a linear relationship, use the least-squares method to compute the regression coefficients b, and b,. b, = - 2.7630 (Round to four decimal places as needed.) %3D Ice cream sales b, = (Round to four decimal places as needed.) %3D Day Sales ($1,000) Temperature (°F) 63 1 2 1.52 1.68 71 75 3 1.92 1.79 74 76 4 2.02 2.36 6. 81 2.16 2.69 81 8 84 2.91 88 10 3.17 90 11 12 3.02 3.27 90 93 99 13 3.42 2.84 88 83 14 15…
# The table contains the state population and the number of licensed drivers in the state (both in millions) for the states with population under 1 million in 2014. The regression model for this data is y 0.7x where x is the state population (in millions) and y is the number of State licensed drivers (in millions) in the state. (A) Draw a scatter plot of the data and a graph of the model on the same axes. Choose the correct graph below OC Diverse) 07 Se pun CHANG The estimated population of state Jin 2014 is (Type a whole number Round to the nearest thousand as needed) 0.5 (8) If the population of state H in 2014 was about 1.6 million, use the model to estimate the number of licensed drivers in state H in 2014 The estimated number of licensed drivers in state H in 2014 is (Type a whole number. Round to the nearest thousand as needed) (C) If the number of licensed drivers in state J in 2014 was about 1,043.000, use the model to estimate the population of state Jin 2014 AOCDEFO А С OD…
Data were gathered and displayed on the scatter plot. 15 y 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Which of the following is the best equation to model the data? ŷ = 11.5(0.81)* Oŷ = 8.1(0.115)* Oŷ= -0.115x+8.1 Oŷ=-0.81x+11.5
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.8 8.4 7.2 3.6 2.7 2.7 2.2 0.7 yy 13.8 11.5 10 7.2 6.4 6.1 6.2 4.4 xx = thousands of automatic weaponsyy = murders per 100,000 residents This data can be modeled by the equation y=0.84x+4.06.y=0.84x+4.06. Use this equation to answer the following;A) How many murders per 100,000 residents can be expected in a state with 2.7 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 4.9 thousand automatic weapons?Answer = Round to 3 decimal places.
Fit a linear regression model for the following data.
Managers rate employees according to job performance and attitude. The results for several randomly selected employees are given below. Performance (x) / 10 / 5 / 6 / 6 / 9 / 3 / 3 / 4 / 5 / 9 Attitude (y) / 3 / 9 / 7 / 6 / 8 / 10 / 3 / 3 / 4 / 7 Use the given data to find the equation of the regression line. Enter the slope. (Round your answer to nearest thousandth.)
The measure of standard error can also be applied to the parameter estimates resulting from linear regressions. For example, consider the following linear regression equation that describes the relationship between education and wage: WAGE; = Bo + B1 EDUC; + e: where WAGE; is the hourly wage of person i (i.e., any specific person) and EDUC; is the number of years of education for that same person. The residual e; encompasses other factors that influence wage, and is assumed to be uncorrelated with education and have a mean of zero. Suppose that after collecting a cross-sectional data set, you run an OLS regression to obtain the following parameter estimates: WAGE; = –11.1+6.2 EDUC; If the standard error of the estimate of B, is 1.34, then the true value of B1 lies between and As the number of observations in a data set grows, you would expect this range to in size.
The Ipod Touch has been out for several years now and a lot of data has been collected. There is a functional relationship between the Price of an IPod Touch and Weekly Demand. Below is a table of data that have been collected Price P ($) Weekly Demand S (1,000s) 150 212 170 207 190 193 210 186 230 176 250 174 A.. Find the linear model that best fits this data using regression and enter the model below (for entry round the slope value to nearest 0.01 and constant parameter to nearest 1) T(p) = %3D Now answer these two questions: B.. What does the model predict will be the weekly demand if the price of an ipod touch is $231 ? (nearest 100) C.. According to the model at what should the price be set in order to have a weekly demand of 180,100 ipod Touches? $ (nearest $1)
The table contains price-supply data and price-demand data for corn. Find a linear regression model for the price-supply data where x is supply (in billions of bushels) and y is price (in dollars). Do the same for the price-demand data. Find the equilibrium price for corn. Price ($/bu) Supply (billion bu) Price ($/bu) Demand (billion bu) 2.14 6.41 2.06 9.96 2.25 7.38 2.15 9.42 2.34 7.51 2.26 8.33 2.41 7.78 2.32 8.08 2.46 8.13 2.36 7.86 2.57 8.35 2.48 6.96 ... Question content area right Part 1 Find a linear regression model for the price-supply data where x is supply (in billions ofbushels) and y is price (in dollars). y=enter your response here (Type an equation using x as the variable. Round to two decimal places as needed.)
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. Xx Y 11.8 14.1 11.5 9.8 7.1 6.2 6.5 x = thousands of automatic weapons y = murders per 100,000 residents 8.6 7 3.3 2.5 2.5 2.6 6 This data can be modeled by the equation y = 0.85x +4.07. Use this equation to answer the following; Answer decimal places. = A) How many murders per 100,000 residents can be expected in a state with 1.2 thousand automatic weapons? Answer = decimal places. Round to 3 0.9 4.7 B) How many murders per 100,000 residents can be expected in a state with 8.5 thousand automatic weapons? Round to 3

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