Use the following for questions 3-5.A statistically-minded English teacher wonders if she can predict the lengths of essays that herrandom sample of 13 student papers (all produced by the same word-processing software)students submit on the basis of how large the computer files for the essays are. She selects aregression analysis of her data is given below. Assume all conditions for inference for slopeand compares file size (in kilobytes or KB) to the word count for each. A computerhave been met.PredictorConstantFile SizeTerence for QuaSCoefSE Coef-1450.376.50773.428.60145.851 R-Sq= 39.4%TP0.088-1.882.67 0.0227R-Sq (adj)33.9%linear regres+- test 5. If the teacher uses these data to test the hypotheses Ho: ß = 0 versus Ha: ß = 0 at the a =0.05 level, which of the following is an appropriate conclusion?we want to reject the Ho, thuctore not bze(a) Since the P-value of 0.022 is less than a, reject H. We have convincing evidence thatthere is a linear relationship between file size and word count.(b) Since the P-value of 0.022 is less than a fail to reject H. We do not have convincingevidence that there is a linear relationship between file size and word count.file) Since the P-value of 0.088 is greater than a, fail to reject H. We do not have convincingevidence that there is a linear relationship between file size and word count.Since the P-value of 0.088 is greater than a, accept H. We have convincing evidencethat the regression line relating word count to file size has a slope of 0.Since the value of 0.088 is greater than a, reject H. We have convincing evidence thatthere is a linear relationship between file size and word count.دکھا

Predictor Coef SE of coef T P Constant -1450.3 773.4 -1.88 0.088 File size 76.50 28.60 2.67…

Answered: Use the following for questions 3-5. A…

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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. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
For example, with five equally spaced values of the controlled variable the coded values could be -2, -1, 0, +1, +2; with six values the coded measurements could be -5, -3, -1, +1, 3, 5. cass Use this technique to find the regression line in the following case. Output (1000 tons) 11.1 12.3 13-7 14.6 15.6 1960 1961 1962 1963 1964 Year Estimate the output of the company in 1965.
Answer the following: 2. Describe the form, direction, and strength of the relationship between these variables. Does there appear to be any outliers? 3. The equation of least-squares regression line is y = 6.871 + 0.061x. This line goes through the points (0, 6.9) and (700, 49.5). Use these points to add the regression line to your scatterplot above. 4. One animal is farthest from the regression line and is an outlier for these two variables. Find the name of this animal and write a sentence describing how its position differs from the overall relationship among the other animals. 5. The elephant has the longest gestation period of these animals. a. Considering only the gestation variable, would you say that the elephant is an outlier? Write a sentence or two explaining why or why not? b. Considering both variables and the relationship between average life span and average gestation period, would you say the elephant is an outlier now? Write a sentence or two explaining why or why…
A medical experiment on tumor growth gives the following data table. X: 65, 70, 86, 100, 222. Y: 33, 35, 45, 52, 70. The least squares regression line was found. Using technology, it is determined that the total sum of squares (SST) was 898 and the sum of squares of regression (SSR) was 806.2. Calculate R2, rounded to three decimal places
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + bịx, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 47 49 50 51 58 Bone Density 360 353 336 333 310 Table Copy Data Step 5 of 6: Determine the value of the dependent variable y at x = 0. Answer 囲 Tables 国 Keypad Keyboard Shortcuts Previous step answers O bo O b, Ox Oy
Consider the following data: x¯ = 20, sx = 2, y¯ = −5, sy = 4, and b1 = 0.40. Which of the following is the sample regression equation?
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
Given the regression model above, do each of the following: A Make a claim about the fit of the model for Model #1. B Make a claim about the significance, degree, and form of the Literacy Rate variable as shown in the table for Model #1. C Write a paragraph to compare Model #1 vs. Model #2 and discuss the effect of the control variable (democracy or not). Use as much of the information from the table above as appropriate.(Hint - don't just discuss control, discuss changes to the fit of model, changes in coefficients, etc.). D Write out the equation of Model #2. E. For Model #2, estimate the government effectiveness score for a democratic country with a literacy rate of 68 and GDP per capital of $20,000. (Hint: Government effectiveness ranges from 0 to 100.)
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?
8. %24 %23 Find the slope (to 2 decimal places) of the Least Squares Regression Line from the following summary statistics. n=11, x=55.82, y=50.55, Sy=24.34, Sy=19.20, r-0. 3518 5x-614, y=556, x²-40198, Sy-31790, xy=32679 A Moving to another question will save this response. I14 f5 f4 米 & * 4 15 8. 3. ·B C.
Biologist Theodore Garland, Jr. studied the relationship between running speeds and morphology of 49 species of cursorial mammals (mammals adapted to or specialized for running). One of the relationships he investigated was maximal sprint speed in kilometers per hour and the ratio of metatarsal-to-femur length. A least-squares regression on the data he collected produces the equation ŷ = 37.67 + 33.18x where x is metatarsal-to-femur ratio and y is predicted maximal sprint speed in kilometers per hour. The standard error of the intercept is 5.69 and the standard error of the slope is 7.94. Construct a 96% confidence interval for the slope of the population regression line. Give your answers precise to at least two decimal places. contact us help 6:42 PM povecy polcy terms of use careers A E O 4») 18 -క90.4 58 12/14/2020 a 17 |耳即 delets prt sc insert 112 19 18 + 16 backspace f5 fA
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…

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