The following results were obtained when each of a series of standard silver solutions wasanalyzed by flame atomic spectrometry.0 51520253010Concentration, ng ml10.003 0.127 0.251 0.390 0.498 0.625 0.763Absorbancee. Standard deviation of the regression linef. Standard deviation and confidence limits of slope and interceptg. Xo- and Sko- values for a sample giving an absorbance of 0.456h. Limit of detection

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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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1. We wish to determine a regression equation that relates the length of an infant (in cm) to age (in days), gender and weight at birth (in kg). Below is portion of the regression analysis derived using a software. *Note: under the gender variable: male and female categories are assigned a value of 1 and 0, respectively. Source S df Coef. Std. Err. 316.8866 3 Residual 71.4734 Model 0.4798 0.0980 age weight gender intercept 8 0.4020 1.0454 1.3113 1.9591 19.53 7.7829 a. What is the sample size for this problem? b. Write the estimated regression equation, interpret each slope coefficients, use the proper unit of measurement. c. Test for significance of the Bage, Bweight, and ßgender at the 99% confidence level. d. From (b) which parameter/s islare statistically significant. e. Test whether or not there is a significant relationship between the infant's length and the independent variables. Use a .01 level of significance. Use only the critical value approach. f. Provide the Coefficient of…
The following estimated regression equation is based on 10 observations was presented. ŷ = 29.1270 + 0.5906x1 + 0.4980x2 Here SST = 6,871.500, SSR = 6,526.625 , si, = 0.0762, and Si, = 0.0612. a. Compute MSR and MSE (to 3 decimals). MSR MSE = b. Compute F and perform the appropriate F test (to 2 decimals). Use a = 0.05. Use the F table. F The p-value is between 0.025 and 0.05 At a = 0.05, the overall model is not significant c. Perform at test for the significance of B1 (to 2 decimals). Use a = 0.05. Use the t table. The p-value is between 0.02 and 0.05 v At a = 0.05, there is not a significant relationship between y and 01. d. Perform a t test for the significance of B2 (to 2 decimals). Use a = 0.05. Use the t table. The p-value is between 0.01 and 0.02 v At a = 0.05, there is not a significant v relationship between y and x2.
Wh ich of the following regressions represents the weakest linear relationship between x and y? Regression 1y=ax+by=ax+ba=11.9a=11.9b=0.1b=0.1r=0.7944r=0.7944 Regression 2y=ax+by=ax+ba=12.9a=12.9b=19.8b=19.8r=0.0346r=0.0346 Regression 3y=ax+by=ax+ba=9.8a=9.8b=15.6b=15.6r=0.2439r=0.2439 Regression 4y=ax+by=ax+ba=-9.4a=−9.4b=11b=11r=-0.5893r=−0.5893 Regression }1Regression 1 t{Regression }2Regression 2 {Regression }3Regression 3 {Regression }4Regression 4
The following estimated regression equation based on 10 observations was presented. ŷ = 27.1270 +0.5104x₁ + 0.4980x₂ 1 Here, SST = 6,736.125, SSR = 6,222.375, 5b₁ = 0.0813, and = 0.0567. 562
The following is a partial computer output of a multiple regression analysis of a data set containing 20 sets of observations on the dependent variableThe regression equation isSALEPRIC = 1470 + 0.814 LANDVAL + 0.820 IMPROVAL + 13.5 AREA Predictor Coef SE Coef T P Constant 1470 5746 0.26 0.801 LANDVAL 0.8145 0.5122 1.59 0.131 IMPROVAL 0.8204 0.2112 3.88 0.0001 AREA 13.529 6.586 2.05 0.057 S = 79190.48 R-Sq = 89.7% R-Sq(adj) = 87.8% Analysis of Variance Source DF SS MS Regression 3 8779676741 2926558914 Residual Error 16 1003491259 62718204 Total 19 9783168000 For the problem above, we want to carry out the significance test about the coefficient of LANDVAL, what is the t-value for this test, and is it significant? 46.66, significant 2.05, significant 1.59, not significant 0.26, not significant
Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal. Excel File: data14-41.xlsx Yes 5.29 ANOVA ▾to usage. Regression Residual Total Intercept Usage df 1 8 9 S.S 1575.76 349.14 1924.90 Coefficients Standard Error 0.9361 0.149 6.1092 0.8951 MS t Stat F If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). ŷ = 6.1092 +0.8951 € b. Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance (to 2 decimals, if necessary). Use Table 1 of Appendix B. t= p-value = 0.01 Reject the null hypothesis Monthly maintenance expense is related c. Did the estimated regression equation provide a good fit? P-value Significance F
The article "The Undrained Strength of Some Thawed Permafrost Soils" contained the accompanying data on the following. y shear strength of sandy soil (kPa) x₂-depth (m) x₂ water content (%) The predicted values and residuals were computed using the estimated regression equation 9-145.41-14.24x, +12.70x₂ +0.079x,-0.236 +0.441x where x₂-x₂²x₂-x₂², and x ₁2 Y 14.7 *2 9.1 31.6 48.0 36.5 27.1 25.6 36.7 25.8 10.0 6.0 39.2 16.0 7.0 39.3 16.8 7.0 38.4 20.7 7.4 34.0 38.8 8.3 33.7 16.9 6.4 28.0 27.0 8.1 33.0 16.0 4.6 26.4 24.9 9.8 37.9 7.3 2.8 34.5 12.8 1.9 36.3 Predicted y Residual 23.83 47.07 26.46 10.77 14.57 16.88 23.38 25.07 16.23 24.31 15.06 28.64 15.08 8.15 -9.13 0.93 -0.86 -0.77 1.43 -0.08 -2.68 13.73 0.67 2.69 0.94 -3.74 -7.78 4.65 (a) Use the given information to calculate SSResid, SSTO, and SSRegr. (Round your answers to four decimal places.) SSTO- 1x |x SSResid- SSRegr - Ix (b) Calculate R² for this regression model. (Round your answer to three decimal places.) R²-X How would you…
The price X (dollars per pound) and consumption y (in pounds per capita) of beef were samples for 10 randomly selected years. The following data should be used to answer the question that follows. n = 10 Ex = 36.19 Ex2 = 134.17 2.9 < x s 6.2 Ey = 774.7 Iy² = 60739.23 Exy = 2832.21 Before the slope of the line of best fit can be estimated, it is necessary to calculate SS Enter the value for SSx accurate to the nearest tenth.
The following readings were made regarding the analysis of arsenic in water. Create a calibration chart accordingly. The slope of the line, the point where it intersects the y-axis, calculate the standard deviation of the regression. mg As3+/L Signal Xi2 yi2 (xi.yi) 0,0 0,06 5,0 1,48 10,0 2,28 15,0 3,98 20,0 4,61 ∑Xi=50,00 ∑yi=22,17 ∑Xi2= 750,00 ∑yi2= 44,48 ∑(xi.yi)=182,1
Ms. Patsy Knowlet, a water quality engineer, noted that there seemed to be a close connection between an important streamflow water quality parameter, Y, and the flow, X m/s. She found that 9 pairs of observations yielded the following data: E*= 152 E* = 576 Ey= Ey* = 5183 y = 1726 45.6 Find the 95% confidence limits of the slope of the regression.
You may need to use the appropriate technology to answer this question. Following is a portion of the computer output for a regression analysis relating y = maintenance expense (dollars per month) to x = usage (hours per week) of a particular brand of computer termina Analysis of Variance SOURCE Regression Error Total Predictor Constant X DF Adj SS 1 1575.76 8 349.14 9 1924.90 Regression Equation Y = 6.1092 +0.8951 X O Ho: B₁ * 0 H₂: B₁ = 0 Coef SE Coef 0.9361 0.1490 (a) Write the estimated regression equation. ý =| 6.1092+ 0.8951r O Ho: B₁ 20 H₂: B₁ <0 |0 Ho: Boo Hà Bo=0 |0 Ho: Bo=0 = 0 Ha: Bo #0 6.1092 0.8951 Ho: B₁ = 0 H₂: B₁ * 0 (b) Use a t test to determine whether monthly maintenance expense (dollars per month) is related to usage (hours per week) at the 0.05 level of significance. State the null and alternative hypotheses. Adj MS 1575.76 43.64 Find the value of the test statistic. (Round your answer to two decimal places.) 36.11 X
The following output comes from regression using the actual HW9 scores and the Final test scores from intro stats one semester. Sample size: 50R (correlation coefficient) = 0.3658R-sq = 0.1338Estimate of error standard deviation: 10.36256Parameter estimates: Parameter Estimate Std. Err. DF T-Stat P-Value Intercept 43.558118 11.1716 48 3.899 0.0003 Slope 0.360048 0.132225 48 2.723 0.009 Assume no assumptions are violated. Form a 87% Confidence interval for how much your final is supposed to increase for each problem done on homework 9.Use 5 decimal places

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