Q2/The owner of a company would like to review the relationship between years on the job and weekly production units. Sample data of 5 employees revealed the table shown. A) Determine the regression equation. Years on Weekly Production job (x) units (y) B) Determine the 0.8 confidence interval for the mean weekly production for an employee worked for 7 years. 12 10 15 13 21

Q2/The owner of a company would like to review the relationship between years on the job and weekly production units. Sample data of 5 employees revealed the table shown. A) Determine the regression equation. Years on Weekly Production job (x) units (y) B) Determine the 0.8 confidence interval for the mean weekly production for an employee worked for 7 years. 12 10 15 13 21

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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ev The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting the number of bids an item will receive based on the list price. 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. Price in Dollars 28 33 36 42 45 Number of Bids 1 7 8 9 10 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next
Zagat restaurant guides publish ratings of restaurants for many large cities around the world. The restaurants are rated on a 0 to 30 point scale based on quality of food, decor, service, and cost. Suppose that someone wants to predict the cost of dinner at a restaurant in a city based on the Zagat food quality ratings. If 10 restaurants in a city are sampled and the regression output is given below, what can we conclude about the slope of food quality? Since we are not given the dataset, we do not have enough information to determine if the slope differs from 0. 2) The slope is 2.521 and therefore differs from 0. 3) The slope significantly differs from 0. 4) Not enough evidence was found to conclude the slope differs significantly from 0. 5) The slope is equal to 0.
< Prev 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 + b₁x, 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 40 61 62 68 69 Bone Density 357 350 343 340 315 Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places. Table Copy Data Next
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Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.7 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) Click the icon to view the critical values of the Pearson correlation coefficient r. F n example Get more help. The regression equation is y=-159.5+ 43.2 x (Round to one decimal place as needed.) 3 # The best predicted weight for an overhead width of 1.7 cm is kg. (Round to one decimal place as needed.) I 80 E 26 D 7.8 161 C $ 4 Q F4 8.3 212 R F Stv 9.9 276 07 20 V F5 T 9.1 215 G 6 B 9.7 262 746 MacBook Air FO 7.3 166 Y H & 7 N F7 U X +00 8 J DII FB - M ( 9 K O < I ) O |qqqqqqqqi L F10 Clear all P . V : ; F11 { + [ command option Check answer = ? 11 I F12 1
The following regression is fitted using variables identified that could be related to student requestedloan amount, LOAN-AMT($) for returning students of a certain University. ????−??? = ? + ? ?????? + ? ???? + ? ????Where ACCEPT = the percentage of applicants that was accepted by the university, PREV = previous loan amount and OUTS =outstanding loan amountThe data was processed using MNITAB and the following is an extract of the output obtained:EXHIBIT 2Predictor Coef StDev T PConstant -26780 6115 * 0.000ACCEPT 116.00 37.17 3.14 0.003PREV -4.21 14.12 -0.30 **OUTS 70.85 15.77 4.49 0.000S = 2685 R-Sq = 69.6% R-Sq(adj) = 67.7%Analysis of VarianceSource DF SS MS F PRegression 3 808139371 269379790 37.37 0.00Residual Error 49 353193051 7208021Total 52 1161332421a)What is dependent and independent variables? b)Fully write out the regression equation c)What is the sample size used in this investigation? d)Fill in the blanks identified by ‘*’ and ‘**’. e)Is β significant, at the 5% level of…
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What is the regression equation? (Round to decimal one) The best predicted weight of a bear with a chest size 43 inches is how many pounds???? Round to decimal one)
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Develop the relationship between correlation coefficient and regression coefficient. Mention the applications of correlation and regression.
Write your complete solutions. The final test and exam averages for 20 randomly selected students taking a course in engineering statistics and a course in operations research are in the table below. Assume that the final averages are jointly normally distributed. (a) Find the regression line relating the statistics final average to the OR final average. Graph the data. (b) Test for significance of regression using a = 0.05. (c) Estimate the correlation coefficient. (d) Test the hypothesis that p = 0, using a = 0.05. (e) Test the hypothesis that p = 0.5, using a = 0.05. equations on this slide to answer the question) (f) Construct a 95% confidence interval for the correlation coefficient. Statistics OR Statistics OR Statistics OR 86 80 86 81 83 81 75 81 71 76 75 69 75 65 72 71 75 81 84 85 90 92 71 72 94 95 62 65 83 80 90 93 76 84 97 70 73 72 80 98