3. The data below represent (hypothetical) energy consumption normalized to the year 1900.Plot the data. test the model Y = aeb* by plotting the transformed data. Estimate theparameters of the model graphically.1080198016.44 33.12 66.69| 134.29 | 270.43 544.57 1096.6340301900 1910 1920 1930 1940 1950 19604.06 8.17701970605090199020100Year2000Consumption Y1.00 2.01

Given that, Energy consumption normalized to the year 1900 is given below x 0 10 20 30 40 50 60…

Answered: 3. The data below represent…

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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Jllustration 22.1. The following data gives the number of women child bearing ages and yearly births by quinquinnial age groups for a city. Calculate the general fertility rate and total fertility rate. It the ratio of male to female children is 13: 12, what is the gross re- production rate? Age group 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Female pop. in (000) Births 16 15 14 13 12 11 6. 400 1710 2100 1430 960 330 36
Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPI) and the cost of a slice of tuna. We would like to build a model using the CPI to predict the cost of a slice of pizza in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 Cost of a slice of tuna(y) 0.15 0.35 1.00 1.25 1.75 2.00 Plot the data. Are we justified in creating a Linear Regression model to predict the price of a pizza slice using the CPI? Why or why not? Calculate the descriptive statistics. Calculate the sums of squares Calculate the slope, intercept, and correlation. What is this correlation value telling us? Assemble the prediction equation, and interpret the slope within the context of the problem. State the hypotheses for the hypothesis test for regression.
The table describes weekly usage of an appliance is proportional to its Maintenance expense, is that correct? Use regression model to discuss your answer.
The data in the following table relate grams plant dry weight (Y) to percent soil organic matter (X1) and kilograms of supplemental soil nitrogen added per 1000 square meters (X2). X1 X2 2.6 Y 78.5 7 74.3 1 2.9 104.3 | 11 | 5.6 87.6 95.9 11 3.1 7 5.2 109.2 | 11 5.5 102.7 3 7.1 Compute the sum of squares of errors e'e. ao- N
36
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The table shows the percents x and numbers y (in millions) of women in the work force for selected years. T 1970 1975 1980 1985 1990 1995 2000 2005 Percent, x 43.3 46.3 51.5 54.5 57.5 58.9 59.9 59.3 Number, y 31.5 37.5 45.5 51.1 56.8 60.9 66.3 69.3 Year (a) Use the regression capabilities of a graphing utility to find the least squares regression line for the data. (Round your coefficients to two decimal places) YM (b) According to this model, approximately how many women enter the labor force for each one-point increase in the percent of women in the labor force? (Round your answer to two decimal places.) million women
Don’t solve in excel please . q.5

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