23. Fit a strai ht line trend to the followin data b the method of leastres •.Year201020112.0132.0152.016Sales Inlakhs8.12202.5

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Answered: 23. Fit a strai ht line trend to the…

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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16
5a.) Draw the graphs. Round your final answers up to 6 decimal places, if applicable. Give the correct units.
A traffic safety company publishes reports about motorcycle fatalities and helmet use. In the first accompanying data table, the distribution shows the proportion of fatalities by location of injury for motorcycle accidents. The second data table shows the location of injury and fatalities for 2073 riders not wearing a helmet. Complete parts (a) and (b) below. (a) Does the distribution of fatal injuries for riders not wearing a helmet follow the distribution for all riders? Use α = 0.10 level of significance. What are the null and alternative hypotheses? A. Ho: The distribution of fatal injuries for riders not wearing a helmet follows the same distribution for all other riders. H₁: The distribution of fatal injuries for riders not wearing a helmet does not follow the same distribution for all other riders. B. Ho: The distribution of fatal injuries for riders not wearing a helmet does not follow the same distribution for all other riders. H₁: The distribution of fatal injuries for…
24. A bivariate regression was conducted to determine the time to failure (seconds) based on the number of push-ups conducted, what term describes when the line of best fit crosses the vertical axis? Outlier Y-intercept Intercept
B6. Pinan Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below. ANOVA table Source Regression Residual Total Regression output Variables Intercept Distance-X Answer the following questions. SS 1,864.5782 1,344.4934 3,209.07 Coefficients 12.3601 4.7956 df 1 28 29 MS 1,864.5782 48.0176 Std. Error 3.2915 0.7696 F 38.83 t(df=28) 3.755 6.231 a) Write out the regression equation. Is there a direct or indirect relationship between the distance from the fire station and the amount of fire damage? b) How much damage would you estimate for a fire 5 miles from the nearest fire station?
The Abendigo Division of Block C Enterprises has a product designed to operate for 1000 hours with a failure rate of 2.2%. Calculate the Mean Time to Failure.
20. Find the coefficient of skewness from the tollowing intormation : Difference of two quartiles = 8 Mode = 11 eboM %3D Sum of two quartiles = 22 Mean = 8 %3D
In a random sample of sixteen different industries the percentage employment x in STEM (science, technology, engineering, mathematics) and mean annual compensation y(in thousands of dollars) were recorded, with the following results. The scatter diagram showed a linear trend. SSx = 1303.9 SSsy= 1503.0 SSy = 2660.2 Ey = 915 n= 16 %3D Ex = 150 .1 1sx<34 36.7 s y < 90.5 Predict the mean annual compensation in industries in which 30 percent of the workforce are in a Stem field. You answer should be entered in thousands of dollars. Example: If you calculate y-hat as 40.6 then the answer you enter should be 40,600
Assume that IQ scores are normally distributed with μ = 100 and σ = 15 What IQ score would be needed to score in the top 2% of IQ scores?
The total expenses of a hospital (dependent variable) are related to many factors. One of these factors is the number of admissions to the hospital (independent variable). Using the summary output below to answer, what is the meaning (analysis) of the coefficient of determination? SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Statistics Regression Residual Total df 0.98706 0.974288 0.972145 8.106794 Coefficients 14 1 12 13 SS 29883.07 788.6412 30671.71 Standard Error Intercept 1.518053 Admissions 0.668591 OA) is the value of Expenses with one unit increase in Admissions 3.248929 0.031354 MS 29883.07 65.7201 t Stat 0.467247 21.32375 F 454.7022 P-value 0.648693 6.59E-11 Significance F 6.59E-11 Lower 95% -5.56075 0.600276 Upper 95% 8.59686 0.736907

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23. Fit a strai ht line trend to the followin data b the method of least res •.