Which estimator did you use?O s/xOs Consider the accompanying data on flexural strength (MPa) for concrete beams of a certain type.8.7 7.27.7 6.5 7.87.011.89.7 7.98.1 6.3 7.67.86.011.6 7.0 10.7 7.3 6.89.06.87.7 9.76.3 8.6 7.4 11.3(a) Calculate a point estimate of the mean value of strength for the conceptual population of all beams manufactured in this fashion. [Hint: Ex; = 220.3.] (Round your answer to three decimal places.)MPаState which estimator you used.O s/x(b) Calculate a point estimate of the strength value that separates the weakest 50% of all such beams from the strongest 50%.MPаState which estimator you used.O s/X(c) Calculate a point estimate of the population standard deviation o. [Hint: Ex;² = 1868.85.] (Round your answer to three decimal places.)MPаInterpret this point estimate.This estimate describes the spread of the data.This estimate describes the bias of the data.This estimate describes the center of the data.This estimate describes the linearity of the data.

Given: Data, x 8.7 7.2 7.7 6.5 7.8 7 11.8 9.7 7.9 8.1 6.3 7.6 7.8 6…

Answered: (a) Calculate a point estimate of 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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A recent Nielsen analysis found that the typical U.S. smartphone user is spending an average of 220 minutes per day using apps. We speculate that the average time spent using apps for Generation X smartphone users (aged 41-56 years) is less than the national average. The hypotheses are Ho: H = 220 minutes versus Ha: µ < 220 minutes. Summary results from R are provided. Summary Statistics Std. Dev (s) Mean Sample Size (n) 205 minutes 63.25 minutes 31
After three exams Denny has a mean score of 74 with only one exam remaining in the class what is the minimum score she will need on that exam to have an overall of an 80
Q1. A study was conducted to investigate the relationship between premature birth and mental development at 12 months. The infant's birth weight was used as an index of prematurity. At age 12 months, the child's mental development was recorded. The results are shown below (the weights are in pounds): Birth 4 6 7 8 Weight(x) Developmental 85 Quotients(y) 88 87 94 96 Summary: n = 5, £x=30, £x² = 190, Ey= 450, Ey² = 40590, Exy = 2728 . a. Find the least square prediction equation, y on x. b. Obtain a 95% confidence interval for the average value of y when x 6.5 (i.e., a C.I. for E(y|x= 6.5)). c. Obtain the coefficient of correlation (r) and interpret the result. d. Test the hypothesis that H, :p= 0 vs. H, : p0. Use a =0.05.
In California, we need more rain to sustain the health of our natural environment, argriculture, and economic. A group of statistics students in Oxnard College recorded the amount of rain during 2016-2017 school year, measuring the intensity by the inches of rain, and the results were: Inches of Rain 1 2 3 4 5 6 Frequency 1 2 8 2 1 1 The mean (¯xx¯) rain intensity: inches (Please show your answer to 1 decimal place.)The median rain intensity: inchesThe mode rain intensity: inches (Please separate your answers by ',' in the bimodal situation. Enter DNE if there is no mode or if there are more than two modes.)
If we multiply the data values by a constant (say, c), how this will affect the geometric mean? Use the equation in image to prove it, and give an example.
Assume that we have made 10 repeated measurements of a quantity, and as a result the error assigned to the “best estimate” of the mean is 6. If we then expand our data set to a total of 20 measurements, the error in the mean will reduce to just 3. True or False
Suppose the mean of X is 94. What does the mean of X become if you multiply X by 1.22? (Use two decimal places, ex: 12.34)
Given the below output, interpret R-squared. Note: the response variable is Charges Coefficients: (Intercept) age bmi regionnorthwest -979.86 regionsoutheast 64.83 regionsouthwest -1562.19 Estimate Std. Error t value Pr(>|t|) -5510.16 1814.88 -3.036 0.00244 ** 22.30 10.893 < 2e-16 *** 53.62 5.994 2.64e-09 *** 893.36 -1.097 0.27291 897.84 0.072 0.94245 896.58 -1.742 0.08167 . 242.97 321.37 signif. codes: 0 ***' 0.001 **' 0.01 ** 0.05 .' 0.1'1 Residual standard error: 11380 on 1332 degrees of freedom Multiple R-squared: 0.1203, F-statistic: 36.44 on 5 and 1332 DF, p-value: < 2.2e-16 Adjusted R-squared: 0.117 O a) 11.7% of the variation in Charges can be explained by the regression model b) 12.03% of the variation in Charges can be explained by the regression model c) 12.03% of the variation in Charges can be explained by the variation of the regression model d) 11.7% of the variation in Charges can be explained by the variation of the regression model

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