If the following data is known for core porosity versus core permeability (k) obtained from well data, a. Well data plot!! b. Estimate and plot the linear regression curve between log k and !! c. Analysis of the linear relationship between variables in the data by calculating the correlation coefficient !!

If the following data is known for core porosity versus core permeability (k) obtained from well data, a. Well data plot!! b. Estimate and plot the linear regression curve between log k and !! c. Analysis of the linear relationship between variables in the data by calculating the correlation coefficient !!

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Let kids denote the number of children ever born to a woman, and let educ denote years of education for the woman. A simple model relating fertility to years of education is: kids; = Bo + B1educ; + uż. 1. What are the parameters in the model? 2. What kinds of factors are contained in u? Are these likely to be cor- related with level of education? 3. Will a simple regression analysis uncover the ceteris paribus effect of education on fertility? Explain.
Personal wealth tends to increase with age as older individuals have had more opportunities to earn and invest than younger individuals. The following data were obtained from a random sample of eight individuals and records their total wealth (Y) and their current age (X). Person Total wealth (‘000s of dollars) Y Age (Years) X A 280 36 B 450 72 C 250 48 D 320 51 E 470 80 F 250 40 G 330 55 H 430 72 A part of the output of a regression analysis of Y against X using Excel is given below: SUMMARY OUTPUT Regression Statistics Multiple R 0.954704 R Square 0.91146 Adjusted R Square 0.896703 Standard Error 28.98954 Observations 8 ANOVA df SS MS F Significance F Regression 1 51907.64 51907.64 Residual 6 5042.361 840.3936 Total 7 56950…
Fit these three regression models and then discuss the similarities and differences between them, particularly as relates to slope estimates (use CI’s) and R2. Also address why this is a “special case” and we wouldn’t necessarily expect to see these model characteristics for a typical dataset. a) Additive model including both predictors (output attached) b) Model including only Moisture (output attached) c) Model including only Sweetness BrandLiking = 68.62 + 4.38 Sweetness Term 95% CI P-ValueConstant (50.16, 87.09) 0.000Sweetness (-1.46, 10.21) 0.130 S R-sq R-sq(adj)10.8915 15.57% 9.54%
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Is the price elasticity of demand for cars statistically significant at 10% significant level? Explain.
A market study found that the sales for a firm were related to advertising expenditure, as follows: Advertising Expenditure (Kshs ‘000’) Sales (Kshs ‘000’) 0 13 1 16 2 14 3 22 4 17 5 21 6 26 Required Draw a scatter diagram with the line of best fit to show the relationship. Determine the regression line equation for estimating the sales for a given level of advertising expenditure What is the estimated sale in thousand, if no advertising expenditure is incurred?
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The following table shows both current and projected data on the number, in millions, of Facebook users in a certain country. t = years since 2012 F = number of Facebookusers (millions) 0 9.7 1 10.5 2 10.8 3 12.2 4 13.1 5 13.2 6 13.8 (a) Plot the data. (b) Find the equation of the regression line. (Round regression line parameters to two decimal places.) F(t) = Add the graph of the regression line to the plot from part (a). (c) Explain in practical terms the meaning of the slope of the regression line. (Round your answers to two decimal places). The slope of the regression line is million users per year. The slope means that, from 2012 on, the number of Facebook users in the country is expected to increase by million each year.
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This table reports the regression coefficients when the returns of the size-institutionalownership portfolio (columns 1 and 2) returns are regressed on three variables: a constant(column 3), the stock market returns (column 4), and the change of the value weighted discountof the closed end fund industry (column 6). Columns 5 and 7 report the corresponding t-statistics of the coefficient estimates. Note that a t-statistic with an absolute value above 1.96means the coefficient estimate is significantly different from 0 at the 1% level. Column 8reports the R square of the regressions. Column 9 reports the mean institutional ownership ofeach portfolio. The last column reports the F-statistics for a multivariate test of the null hypothesis that the coefficient on ΔVWD in the Low (L) ownership portfolio is equal to theHigh (H) ownership portfolio. Two-tailed p-values are in parentheses. 1. What is the main finding of this Table? 2. What is the explanation for…
The table below shows (lifetime) peptic ulcer rates (per 100 population), UU, for various family incomes, xx, as reported by the 1989 National Health Interview Survey. Income 4000 6000 8000 12000 16000 20000 30000 45000 60000 Ulcer rate 14.1 13.1 13.8 12.6 11.8 11.7 11.5 9.3 7.6 (a) Find the equation of the regression line. Ulcer rate, U(x)= . (b) Estimate the peptic ulcer rate for an income level of x0= 25000 according to the linear model in part (a). Ulcer rate, U(x0)= .