Given the data from weekly sampling inspection of Eutectic die attach operation,The pull test strength exceeding the limit of 1.8.Weekly (X)1Pull Strength(Y) 2253 41185141. Find the variance2. Find the standard deviation3. Find the regression equation of Y on X4. Find the value of Y when X = 6, 7, 8, 9, & 105.Explain the result on d6. What is your conclusion on the correlation of the data, show calculationusing Pearson r

Since there are multiple sub-parts, as per the honor code the first three sub-parts will be solved.…

Answered: Given the data from weekly sampling…

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 sample of 100 bears was treated like it was the whole population of Jellystone Park bears, and the mean weight was found to be 800 pounds with standard deviation 12 pounds, the mean blood pressure was 150 with standard deviation 6, and the sample correlation coefficient of weight with blood pressure was found to be .4. Based on this information, what is the regression slope for the SLR equation for predicting blood pressure using observed weight for Jellystone bears?
Based on the scatter plot above, describe the relationship between the amount of cost damage and the distance from nearest fire station to the residential. Determine the regression line for the above regression output. Interpret the slope coefficient of distance to the nearest station affecting the amount of fire cost damage. Compute the correlation coefficient and interpret its meaning. Does the distance to the nearest fire station has significant influence on the cost damage amount? Conduct a test at 1% significance level. ] Predict the fire cost damage generated if the distance from nearest fire station is 2.5 kilometers. Is this estimate reliable? Explain. []
On the first statistics exam, the coefficient of determination between the hours studied and the grade earned was 80%. The standard error of estimate was 10. There were 15 students in the class. Develop an ANOVA table for the regression analysis of hours studied as a predictor of the grade earned on the first statistics exam. (Round your DF answers to nearest whole number and other answers to 2 places.) Source DF SS MS Regression 1 Error Total 13 14
I need help with these questions 1. do the covariates and factors interact? 2. can you conclude a homogeneity of regression slopes? 3. can you conclude homogeneity of variance?
Several bakeries in a town were asked the price for different amounts of donuts at their shop. The scatter plot with Total Cost (in dollars) 876543 ~ TO 0 0 1 Donut Pricing 2 3 4 5 Number of Donuts 6 7 8 line of best fit was created from the data gathered. Part A: Estimate the correlation coefficient. Explain your reasoning for the given value. Part B: How many positive and negative residuals are there? Explain your reasoning. Part C: State the point with the largest absolute value residual and interpret the point in terms of the context of the data.
32.
42. When a correlation is sufficiently high, what statistic is used to predict the outcome of the dependent variable from a single independent variable? Stepwise comparison Bivariate regression Coefficient of determination
Shown below is a portion of a computer output for regression analysis relating y (dependent variable) and x (independent variable). ANOVA df SS Regression 1 24.061 Residual 10 67.979 Coefficients Standard Error Intercept 11.064 2.049 x −0.566 0.301 (a) What has been the sample size for the above regression analysis? (b) Perform a t-test and determine whether or not x and y are related. Let ? = 0.05. State the null and alternative hypotheses. (Enter != for ≠ as needed.) H0: Ha: Find the value of the test statistic. (Round your answer to three decimal places.) Find the p-value. (Round your answer to four decimal places.) p-value = What is your conclusion? .
Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model: SALES=a+BAGE+YMIL+SENG Where SALES= amount that a vehicle is sold for($000's), AGE = age of the vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained:
Do the following plots show 1. Constant variability 2. Nearly normal residuals 3. Independent observations for SLR (conditions for linear regression)
24) Below is some of the regression output from a simple regression of the number of wins for a major league baseball team and the size amount of money the team is paying its players (expressed in millions of $'s) *fill in blanks of the table* Based on the regression output, what is the correlation between the two variables? *round to 3 decimal places*

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