1:.VA moodle.unizwa.edu.omالوقت المتبقي 0:32:35اQ1. [6 points] : From the following data set[23.6.611161 find correlation coefficients2. Estimate the simple linear regression model3. Find the predicted value of y when x-10Q2. [6 points] The weekly wages workmen are normally distributed around a mean of R.O. 70with a SD. of R.O. S. Find the probability of workers whose weekly wages will be@ between R.O. 69 and R.O. 72,(mless than R.O. 69,(m) Find the value of K such that P(X K) =0.3400 01 02 03 04os06 070160 0199oss7.06750714O753091009481064.1141O 17904154os1915.1217-1255.1293.1.368.14061443.1460.1517.1700201415911626.1736.17722123.1879.1950229121902224254919852019208821572324235724222704 273423092425170.72580261129102642293932122673276430512794202331062995326431313365 35893599 362138302967302330780.93159323631153340353134131. 364312341034303461346535543577366536 7on 379 37493493770379031038493925 394439973869A04939073962A015A177A0664222A357A115A131A14741621441921.543321.6 44521.7 ASS418 464119471320 A77221 A2122 406123 49324 4918A2074236425A2654292430643194370A4294535 4545AG25 A633A345AM2 A94A418452544744464A95 A50sAS05ASISASGAAS73A582AS91 4599AGOBAG16A6494656A719 A4726A664 467147324700A670A738 A4444994700AT50A75647614767ATTSA7904812 4817A826A830A834A3 A842AS46A8S4 48574871 A875 AS76 AS81As4491349344951190149044916A920492249254927 A929 4931 49324936A3404949A540ASSS4341.49432649532.7 4965494543464959 A96O4952496449744957496349734962496749604969A9704972282.9 49813.0 A987 A987A974497649774977ASTO49794980A962A5824963494 A04A98549064987 49e4990 49904999A923.1499032 A99 499 4994 49433 4 A9 A9s A99634 A997 AI97 A997 A997 A997 A97 A9 9 A97 me3.5 40 A9 4 A990 Aa A Ae 4 4e A9903.6| A99 A99 499e A9994991A9914991A2 Am2A94 AAA99249934993أقصی حجم ل لملف: 0 بایت، الحد الأقصی لعد د1:CLII IIإنهاء المحاولة .(Part I+Part II (STAT101 Final Exam

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Answered: 6. 11 6. 16 1.find correlation…

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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Consider a regression analysis with n = 47 and three potential independent variables. Suppose that one of the independent variables has a correlation of 0.95 with the dependent variable. Does this imply that this independent variable will have a very large Student’s t statistic in the regression analysis with all three predictor variables?
1. Plot the data points on a scatter diagram. 2. Determine the equation of the regression line and find Pearson product-moment correlation coefficient. 3. Determine the point estimate of y at x = 5.5
on the basis of the value of linear correlation coefficient, would you conclude, at the /r/>0.9 level, that the data can be reasonably modeled linear equation?
8)Suppose that Y is normal and we have three explanatory unknowns which are also normal, and we have an independent random sample of 11 members of the population, where for each member, the value of Y as well as the values of the three explanatory unknowns were observed. The data is entered into a computer using linear regression software and the output summary tells us that R-square is 0.86, the linear model coefficient of the first explanatory unknown is 7 with standard error estimate 2.5, the coefficient for the second explanatory unknown is 11 with standard error 2, and the coefficient for the third explanatory unknown is 15 with standard error 4. The regression intercept is reported as 28. The sum of squares in regression (SSR) is reported as 86000 and the sum of squared errors (SSE) is 14000. From this information, what is MSE/MST? .5000 NONE OF THE OTHERS .2000 .3000 .4000
24) If the R-square value for a simple linear regression model is 0.80 and the regression line has anegative slope, the correlation coefficient describing the relationship between the two variables is_____________.
9)Suppose that Y is normal and we have three explanatory unknowns which are also normal, and we have an independent random sample of 11 members of the population, where for each member, the value of Y as well as the values of the three explanatory unknowns were observed. The data is entered into a computer using linear regression software and the output summary tells us that R-square is 0.79, the linear model coefficient of the first explanatory unknown is 7 with standard error estimate 2.5, the coefficient for the second explanatory unknown is 11 with standard error 2, and the coefficient for the third explanatory unknown is 15 with standard error 4. The regression intercept is reported as 28. The sum of squares in regression (SSR) is reported as 79000 and the sum of squared errors (SSE) is 21000. From this information, what is the adjusted R-square? .8 .7 NONE OF THE OTHERS .6 .5
1) Indicate whether the following statements are true or false. Explain why and show your work. c) In the regression Y= B1+ B2X + B3Z+u , if there is a strong linear correlation between X and Z, then it is more likely you fail to reject the null hypotheses that individual slope parameters are insignificant.
5.1 Determine the equation of the relationship between the predictor variable (x) and the response variable (y). 5.2 What does the simple linear regression equation obtained in question 5.1 indicates on every 1 km/hr increase in speed? 5.3 Using the simple linear regression equation obtained in question 5.1, estimate the total fuel expenditure of a randomly selected driver of one of the newly launched Volvo trucks who drove at an average speed of 100 km/hr during a 900 km haulage. 5.4 Determine the Pearson Correlation Coefficient.
uppose IQ scores were obtained from randomly selected couplescouples. For 2020 such pairs of people, the linear correlation coefficient is 0.8900.890 and the equation of the regression line is ModifyingAbove y with caret equals negative 0.74 plus 1.02 xy=−0.74+1.02x, where x represents the IQ score of the husbandhusband. Also, the 2020 x values have a mean of 101.17101.17 and the 2020 y values have a mean of 102.7102.7. What is the best predicted IQ of the wifewife, given that the husbandhusband has an IQ of 9999? Use a significance level of 0.05. The best predicted IQ of the wifewife is nothing. (Round to two decimal places as needed.
The fish in my pond have mean length 14.73 inches with a standard deviation of 2.27 inches and mean weight 4.83 pounds with a standard deviation of .8 pounds. The correlation coefficient of length and weight is .6. If the length of a particular randomly selected fish is reported to be 17 inches, and if we use simple linear regression to predict the weight of a fish whose length is reported to be 15.8 inches long, then what is the expected squared error?
1.The head of the production department of a RM Electronic Company wants to determine the relationship between the number of workers who assemble the product and the number of units assembled per day. d.Test whether the correlation is significant at 5% level of significance. e.Determine the regression line. f.Predict the number of units used if there are 20 workers. g.How many workers is needed to produce 1000 units per day?
17) Suppose that Y is normal and we have three explanatory unknowns which are also normal, and we have an independent random sample of 41 members of the population, where for each member, the value of Y as well as the values of the three explanatory unknowns were observed. The data is entered into a computer using linear regression software and the output summary tells us that R-square is 0.9, the linear model coefficient of the first explanatory unknown is 7 with standard error estimate 2.5, the coefficient for the second explanatory unknown is 11 with standard error 2, and the coefficient for the third explanatory unknown is 15 with standard error 4. The regression intercept is reported as 28. The sum of squares in regression (SSR) is reported as 90000 and the sum of squared errors (SSE) is 10000. From this information, what is the number of degrees of freedom for the t-distribution used to compute critical values for hypothesis tests and confidence intervals for the individual…

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6. 11 6. 16 1.find correlation coefficients 2. Estimate the simple linear regression model 3. Find the predicted vahue of y when x-10