i14Xi41334yi16121713223.LO 4.Use the data set anxiety.csv, which is posted in Data Sets in Bb, topredict exam score from anxiety rating. FYI: a higher anxiety measurementindicates a higher level of pre-test anxiety.a. Calculate the estimated variance-covariance matrix of b.b. From your estimated variance-covariance matrix from part (a), find andinterpret s{bo, b1} and s²{b1}.C. From your estimated variance-covariance matrix from part (a), find andinterpret s{b1}.d. Calculate the hat matrix, H, and use it to find s?{e}. Report the first threeelements on the diagonal for EACH matrix.e. Interpret the first element on the diagonal for s?{e}.

Note: As per the guidelines, answer to first three subparts will be provided. The given data is as…

Answered: Use the data set anxiety.csv, which is…

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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The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a =0.01. Welght, x Varlablity in braking distance, y 5960 5390 6500 5100 5870 4800 2 1.75 1.95 1.93 1.57 1.64 1.50 E Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: P Vo Hạ: p Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical values are -to = and to = O B. The critical value is. Calculate the test statistic. t= (Round to three decimal places as needed.) What is your conclusion? a significant linear correlation between vehicle weight and variability in braking distance on a dry surface. There Venough evidence…
1.) Interpret the SPSS output below. (USING THE FIRST PICTURE) 2.) Based on the SPSS correlation matrix below, what do we know about the t-score value for each tested relationship? (USING THE SECOND PICTURE)
Note that this uses minitab. Make a scatterplot that will enable you to predict BBAC from number of beers consumed. What is the correlation coefficient?
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use α=0.01. Weight, x 5920 5370 6500 5100 5890 4800 Variability in 1.76 1.91 1.50 braking distance, y EEE Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: P Ha: P 0 0 1.86 1.62 1.67 M
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using a = 0.05, Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.1 7.5 178 Click here to view a table of critical values for the correlation coefficient. 9.6 9.4 8.8 8.2 Weight 112 205 238 204 188 OA. YB. OC. KD D. Aweight (kg) 300- A weight (kg) Aweight (kg) 300- Aweight (kg) 300- 300- .. 100 100+ 100 7. rect: 0 10 10 10 10 width (om) width (cm) width (on) widn (om) The linear correlation coefficient is r= (Round to three decimal places as needed.) Enter your answer in the answer box and then click Check Answer. O parts remaining Check Answer वी
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Can you please check my work
Actuaries use various parameters when evaluating the cost of a life insurance policy. The variance of the life spans of a population is one of the parameters used for the evaluation. Each year, the actuaries at a particular insurance company randomly sample 30 people who died during the year (with the samples chosen independently from year to year) to see whether the variance of life spans has changed. The life span data from this year and from last year are summarized below. Current Last Year Year x1 = 75.8 | x,= 76.2 si= 47.61 s3= = 92.16 (The first row gives the sample means and the second row gives the sample variances.) Assume that life spans are approximately normally distributed for each of the populations of people who died this year and people who died last year. Can we conclude, at the 0.05 significance level, that the variance of the life span for the current year, of, differs from the variance of the life span for last year, o,? Perform a two-tailed test. Then complete the…
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