2. Consider the foot length and foot width of six female grade 4 students inMorning Star Montessori School in 2006:Length of foot(cm) Y20.9Width of foot(cm) X8.524919.67.922.68.8218.821.69.3For the next five items, refer to the problem above, in the previous page.In addition to the female grade 4 students, below are some of the boys'measurements:Width of foot (cm) Length of foot (cm)Y8.422.48.823.49.722.523.29.88.923.19.723.77. Using the least squares regression line to estimate a boys foot lengthwhen width isa) 8.5b) 9.6c) 9.5d) 8e) 7.6

Using the least square regression line to estimate a boys foot length when widh is: a) 8.5 b) 9.6…

Answered: For the next five items, refer 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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Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + OBedroom + yHouse Size + ALot Size Coef SE Coef Predictor T Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 R-Sq=56.0% R-Sq (adj)=54.6% S= 25023 Source DF MS F P Regression 3 76501718347 25500572782 *** **** Residual Error 96 60109046053 626135896 Total 99 a) Write out the regression equation. b) Fill in the missing values *, **, c) Use the p-value approach to determine if ø is significant at the 5% significance level and d) Is y significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. f) Give an interpretation to the term "R-sq" and comment…
The following data was collected by a particular company to determine if a relationship between the number of people in a household and weekly food expenditures exists. Regression analysis is done using this data, and the following Excel see attached image Household Number in Household Weekly Food Expenses 1 2 $95 2 3 $137 3 5 $165 4 2 $105 5 4 $227 6 4 $240 7 5 $185 a. Using the least-squares regression line (from the excel output the regression equation is y=51.779 + 31.662x) , estimate the weekly food expenses for a household that has 10 people. b. Briefly describe any concerns that you may have with your forecast or extrapolation in question above. c. Give examples of two variables that should be included in the model above, explaining why these would make the model a better fit.
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 is as follows: bill = 16.2 + 3.58. size. Coefficients Estimate Std. Error (Intercept) 16.2 Size 3.58 0.47 0.68 Round your answer to three decimal places, and round any interim calculations to four decimal places. We are 99% confident that the mean annual electric bill increases by between dollars for every additional square foot in home size. dollars and
For Data Set 9 in Appendix B, “Bear Measurements,” we get this regression equation: Weight = -274 + 0.426 Length + 12.1 Chest Size, with R2 = 0.928. Interpret the multiple coefficient of determination – what does this value tell us?
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The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
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I want to solve the blanks and also the codes to write them in R studio Course name: probability and statistics for information technology. See attached pic.
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The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
Here are the scatter plots for two sets of bivariate data with the same response variable. The first compares the variables x & y. The second compares the variables w & y 00⁰0 889 Which explanatory variable has a stronger relationship with the response variable y? The first variable (x) has a stronger relationship with the response variable y. The second variable (w) has a stronger relationship with the response variable y.
Hello. How do you calculate this question on a TI-83? Thanks.

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