Answered: ogistic Regre

Math

Statistics

ogistic Regre

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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Sky Eyes manufactures drones for security and enforcement organizations. They would like to predict production cost using a regression model. The regression model is based on historic production values. The regression statistics from Excel are provided below. Intercept Machine Hours Labor Hours Production Output Coefficients -477.7647341 44.97381045 -0.08890915 55.06503861 Standard Error 62.63384 -7.627901659 7.518943592 0.083252 -1.067948403 5.957718 9.242639029 t Stat 5.9814 P-value 1.20603E-09 1.74367E-09 0.291239564 5.77595E-12 What can be concluded based on the output of the regression statistics? (Select all that apply.) The regression equation is y 44.97 x (machine hours) - 0.0889 x (labor hours) + 55.065 x (production output). Labor hours is significant variable in the regression model. Machine hours is a significant variable in the regression model. The regression equation is y=-477.76+44.97 x (machine hours) - 0.0889x (labor hours) + 55.065x (production output).
Pls help ASAP. Pls show all work.
The local utility company surveys 12 randomly selected customers. For each survey participant, the company collects the following: annual electric bill (in dollars) and home size (in square feet). Output from a regression analysis appears below: Bill = 15.9 + 4.45*Size Coefficients Estimate Std. Error (Intercept) 15.9 0.3 Size 4.45 0.57 We are 98% confident that the mean annual electric bill increases by between dollars and dollars for every additional square foot in home size.
Seven North American Green Frogs (Rana clamitans) had their jumping distance recorded (in mm) multiple times in a laboratory. The mean jumping distance for these frogs along with their length (measured from snout to vent in miMillimeters) are presented in the table below. Length of Frog 52 68 37 65 77 81 59 Mean Jumping Distance 546 673 415 659 793 814 563 (a) Determine the linear regression model that will best predit the mean jumping distance of a North American Green Frog based on the frog's length. (b) How well does the linear regression model fit this sample data? (c) Use the linear regression model to predict the mean jumping distance of a North American Green Frog that is 48 mm in length. No excel, please.
Develop a scatter diagram between Risk of Stroke and Age. The scatter diagram should include a proper title, a solid trend line, axis titles, a regression equation, and the Coefficient of Determination (R –square). (Note: the dependent variable is usually in the y-axis and independent variable in the x-axis.) Risk of Stroke (%) Age Pressure Smoker (Yes=1) 12 57 152 0 24 67 163 0 13 58 155 0 56 86 177 1 28 59 196 0 51 76 189 0 18 56 155 1 31 78 120 0 37 80 135 1 15 78 98 0 22 71 152 0 36 70 173 1 15 67 135 1 48 77 209 0 15 60 199 0 36 82 119 1 8 66 166 0 34 80 125 1 3 62 117 0 37 59 207 1
Predicting Percent Body FatThis problem uses the dataset BodyFat, which gives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (in pounds), Height (in inches), and circumference (in cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist.1Using Neck Circumference to Predict Body FatThe regression line for predicting body fat percent using neck circumference is BodyFat^=-47.9+1.75(Neck). Click here for the dataset associated with this question. (a) What body fat percent does the line predict for a person with a neck circumference of 35 cm?Round your answer to two decimal places.BodyFat^= %What body fat percent does the line predict for a person with a neck circumference of 40 cm?Round your answer to one decimal place.BodyFat^= % (b) One of the men in the study had a neck circumference of 38.7 cm and a body fat percent of 11.3. Find the residual for this man.Round your answer to three decimal places.residual= %…
What mean physical health score would you expect in a group of 28-year-old women with a graduate degree?
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below: Which of the independent variables in the model are significant at the 5% level? Formulate the hypothesis and explain the answer. How far can you rely upon this model? Or, what is the percentage variation in House explained by the model? What is the predicted house size (in hundreds of square feet) for an individual earning an annual income of IDR 400 million and having a family size of 4?
Using a sample of 46 college students, we want to determine if there is a significant correlation between weight (in lbs.) and weekly exercise (in minutes). The results of a correlation and regression analysis are indicated in the Excel output below. The mean weight (the independent variable) was 166.80 lbs., and the mean weekly exercise time (the dependent variable) was 158.83 minutes. SUMMARY OUTPUT Regression Statistics Multiple R 0.027082077 R Square 0.000733439 Adjusted R Square -0.021977165 Standard Error 79.41761298 Observations 46 ANOVA df SS MS F Significance F Regression 1 203.6896 203.6896 0.032295 0.858207 Residual 44 277514.9 6307.157 Total 45 277718.6 Coefficients Standard Error t Stat P-value Lower 95%…
A nonprofit analyst considered two independent variables as a predictor for the dependent variable Commitment, the percent of total expenses that are allocated to charitable services. The independent variables are Revenue, total revenue in billions of dollars, andEfficiency, the percent of private donations remaining after fundraising expenses. The regression analysis resulted in this ANOVA table. Determine whether there is a significant relationship between commitment and the two independent variables at the 0.01 level of significance. Source Degrees of Freedom Sum of Squares Mean Square F p-value Regression 2 3640.0416 1820.02 51.0429 <.0001 Error 87 3102.1301 35.66 Total 89 6742.1717 Determine the p-value. The p-value is ________ (Round to three decimal places as needed.)
In an ANOVA table for a multiple regression analysis, the global test of significance is based on the _________. Select one: a. Regression mean square divided by the mean square error b. Treatment mean square and block mean square c. Treatment mean square divided by the error variation d. Block and error variation
In order to use a certain polymer, its firmness must be greater than 48 MPa. 14 specimens were sampled from a polymer package and a mean of 48.4 and a standard deviation of 1.0 were obtained. You want to do a hypothesis test to find out if that package of polymers can be used. Obtain the value of the t-statistic needed to perform the test and on your procedure sheet explain whether or not to reject the null hypothesis. Round to 2 decimal places.