The authors of the paper "Power-Load Prediction Based on Multiple Linear Regression Model"t were interested in predicting the load on the electric power system in China using data on y = Power consumption (in hundreds of millions of kwh), x, - Population (in millions), and x2 = Gross domestic product (in billions of dollars), for 21 years. The model equation proposed in the paper is y--113,527 + 0.974x, + 0.057x, + (a) According to this model, what is the mean power consumption (in hundreds of millions of kwh) for a year if the population was 160,000 million and the gross domestic product was 600,000 billion dollars? hundreds of millions of kwh (b) Interpret the value of , in this model. When the gross domestic product V v is fixed, the mean increase in (power consumption (in hundreds of millions of kwh) v v associated with a (1-million unit v increase in (population v is 0.974.

The authors of the paper "Power-Load Prediction Based on Multiple Linear Regression Model"t were interested in predicting the load on the electric power system in China using data on y = Power consumption (in hundreds of millions of kwh), x, - Population (in millions), and x2 = Gross domestic product (in billions of dollars), for 21 years. The model equation proposed in the paper is y--113,527 + 0.974x, + 0.057x, + (a) According to this model, what is the mean power consumption (in hundreds of millions of kwh) for a year if the population was 160,000 million and the gross domestic product was 600,000 billion dollars? hundreds of millions of kwh (b) Interpret the value of , in this model. When the gross domestic product V v is fixed, the mean increase in (power consumption (in hundreds of millions of kwh) v v associated with a (1-million unit v increase in (population v is 0.974.

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter3: Functions And Graphs

Section3.3: Lines

Problem 76E

See similar textbooks

Similar questions

What is regression analysis? Describe the process of performing regression analysis on a graphing utility.
Does Table 1 represent a linear function? If so, finda linear equation that models the data.
Groundwater is the main source of water in many countries. In a study of the quality of ground water in Yemen, the authors of the paper "Multiple Linear Regression Model for Chloride Estimation of Groundwater in Ash-Shihr Town and Its Outskirts Hadharamout-Yemen"t used a multiple regression model with two independent variables, where y = chloride concentration (mg/L) X1 = total alkalinity X2 = electrical conductivity. The model equation suggested in the paper is y = -183.560 + 1.589x, + 0.069x, + e. (a) Based on this model, what is the mean value of y (in mg/L) when x, = 320 and x, = 2,700? mg/L (b) Based on this model, what mean chloride concentration (in mg/L) is associated with a total alkalinity of 270 and an electrical conductivity of 2,900? mg/L
A study was done to look at the relationship between number of movies people watch at the theater each year and the number of books that they read each year. The results of the survey are shown below. Movies 8 2 7 9 9 2 0 7 4 4 9 Books 0 8 0 0 0 4 9 0 1 0 0 The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places) Use the model to predict the number of books read per year for someone who watches 6 movies per year.Books per year = (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: For every additional movie that people watch each year, there tends to be an average decrease of 0.88 books read. The slope has no practical meaning since people cannot read a negative number of books. As x goes up, y goes down. Interpret the y-intercept in the context of the question: If someone watches 0 movies per year, then that person will read…
Hormone replacement therapy (HRT) is thought to increase the risk of breast cancer. The accompanying data on x = percent of women using HRT and y = breast cancer incidence (cases per 100,000 women) for a region in Germany for 5 years appeared in the paper "Decline in Breast Cancer Incidence after Decrease in Utilization of Hormone Replacement Therapy." The authors of the paper used a simple linear regression model to describe the relationship between HRT use and breast cancer incidence. † HRT Use Breast Cancer Incidence 46.30 103.30 40.60 105.00 39.50 100.00 36.60 93.80 30.00 83.50 (a) What is the equation of the estimated regression line? (Round your numerical values to four decimal places.) ŷ = (b) What is the estimated average change in breast cancer incidence (in cases per 100,000 women) associated with a 1 percentage point increase in HRT use? (Round your answer to four decimal places.) cases per 100,000 women (c) What breast cancer…
Calculate Regression equation
Let X = height of the students in inches Let Y = Foot length of the students in centimeters Complete manual solutions for the SLRM coefficients, their interpretations and write down the best fitting linear regression equation. What is the predicted value of foot when height = 75?
It is believed that the electrical energy that a chemical plant consumes each month is related to the average environmental temperature, the number of days in the month, the average purity of the product, and the tons of product manufactured. Historical data is available for the previous year and is presented in the following table (seen in the image=. Perform simple linear regression analysis
researcher collects some socioeconomic variables of Turkey and wants to model the natural gas consumption arough years by multiple linear regression. Below is the table summarizing the coefficients of variables and their statistical parameters, and the figure showing the change of natural gas consumption in this time period • Actual constant term X₁: population (million people) X2: GDP per capita (thousand $) X3: Inflation percentage X4: Mean winter temperature coefficients -36.5 0.578 2.133 -0.0733 -0.0375 standard error 6.73 0.133 0.221 0.0126 0,201 t value -5.43 4.34 p-value 1.42* 10.5 2.20*10- 9.67 9.47*10-10 -0.19 -5.81 5.46* 10.6 0.853 Natural gas consumption (billon m²) 50 40 30 20 10 R¹ = 0.992 standard error 1.51 1986 1990 1994 1998 -Estimated 2002 Star 2006 2010 a) Write the multiple regression equation in its standard form: y =B₁ + B₁x₁ + ß₂x₂ + ... b) Which variables significantly affect the natural gas consumption? Why? c) Which variables positively, which variables…
What is the equation for a simple linear regression model that predicts the dependent variable Y based on a single independent variable X?
Show the best fitted line on scatter diagram and Find the predicted value for each y using the exposure time and the equation obtained in part b (b. Find the equation of regression line between radiation doses on exposure time .usingleast square method)
The monthly premium quoted by an insurance company for a critical illness policy was collected from a sample of 6 adult male smokers at different age. The data for the sample are shown: Age 28 25 50 39 47 31 Premium ($) 75 40 175 125 250 105 Using Age to predict premium, the Linear Regression equation is given by: ŷ =6.556X−112 and r2=0.813y^=6.556X−112 and r2=0.813 a. Identify the independent and Dependent variables. Dependent: Age Premium Independent: Age Premium b. Determine the slope. Slope = Slope = Round to 3 decimal places c. Determine |r||r| . |r|=|r|= Round to 3 decimal places d. Interpret rr : and e. Determine critical r value at 5% significance level and determine if there is a significant linear correlation exists. |r| critical=|r| critical= Round to 3 decimal places Linear Correlation:Linear Correlation: Significant Not Significant f. Predict the monthly premium for a 40 years old adult male smoker.…