fitting a least square line to n = 14 data points, the quantities below were computed. SSxx = 25 x-bar = 4 SSyy = 22 y-bar = 3 SSxy = 23 Find the following: (Show work) a- Find the least square line (Y-hat = Y-intercept + Slope * x) b- Calculate SSE c- Calculate s^2

fitting a least square line to n = 14 data points, the quantities below were computed. SSxx = 25 x-bar = 4 SSyy = 22 y-bar = 3 SSxy = 23 Find the following: (Show work) a- Find the least square line (Y-hat = Y-intercept + Slope * x) b- Calculate SSE c- Calculate s^2

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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Dr. V. noticed that the more frequently a student is late or absent from class the worse he or she performs on the final exam. He decided to investigate. Dr. V. collected a random sample of 22 students. This sample includes the number of times a student is absent and their grades on the final exam. The data can be found in the Excel file Assignment10.xlsx. Do not use any software that I did not assign. Times Late/ Final Exam Absent Grade 9 84.00 92.50 12 52.00 5 87.00 11 75.00 24 45.00 39.00 10 46.00 19 63.00 2 65.00 2 98.00 17 24.50 8 58.00 20 69.50 55 49.00 23 68.50 70.00 4 75.50 2 85.00 97.00 2 97.00 2 93.50 93.50 2 78.00 2 86.00 2 88.00 Question 1: Which or the two variables (times absent or grades on the final exam) is the independent variable and which is the dependent variable? Question 2: Using Microsoft Excel: (Excel file Assignment10.xlsx) SHOW YOUR WORK а. Count the number of XY variables. b. Calculate the mean and sample standard deviation of both the independent and…
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The foreign automobile dealer sells English, French, German, Japanese and Korean automobiels. Th enumber of such automobiles sold in a month follow; Country English French German Japanese Korean Number 3. 12 20 10 In words describe what descriptive method would you use to display the data to an audience? Comment on your choice. For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac).
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Describe in detail about regression lines?