The table below lists weights (carats) and prices (dollars) of randomly selected diamonds. Find the (a)explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidenceo support a claim of a linear correlation, so it is reasonable to use the regression equation when makingpredictions. For the prediction interval, use a 95% confidence level with a diamond that weighs 0.8 carats.WeightPrice0.3$508a. Find the explained variation.0.4$11530.5$1332Round to the nearest whole number as needed.). Find the unexplained variation.Round to the nearest whole number as needed.)c. Find the indicated prediction interval.

Answered: The table below lists weights (carats)…

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 table lists the average monthly cost to workers for family health insurance for various years. a) Use a graphing calculator to fit a regression line to the data. b) Predict the average monthly cost to workers for family health insurance in 2016, and compare the value with $426.98, which is obtained using the points (1,335) and (4,381). c) Find the correlation coefficient for the regression line, and determine whether the line fits the data closely COCO a) The finear equation of the regression line that best models the data is y=x+ (Round to the nearest hundredth as needed.) Year, x 2009, 0 2010, 1 2011, 2 2012.3 2013, 4 2014, 5 Average Monthly Cost to Workers for Family Health Insurance $293 335 343 360 381 403
The accompanying data resulted from an experiment in which weld diameter and shear strength (in pounds) were determined for five different spot welds on steel. Below are the data collected and the regression equation. Diameter Strength 200.1 813.7 210.1 785.3 220.1 960.4 230.1 1118.0 240.0 1076.2 Strength = -941.6992 + 8.5988*Diameter a)The predicted y-hat value for a diameter of 201 is 864. Interpret this predicted value. b)what is the predicted strength of a weld with a diameter of 51?
Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with an altitude of 6327 ft (or 6.327 thousand feet). Altitude 2 8 13 23 28 31 32 Temperature 56 40 27 −1 −34 −41 −50 a. Find the explained variation. (Round to two decimal places as needed.) b. Find the unexplained variation. (Round to five decimal places as needed.) c. Find the indicated prediction interval. ______°F<y<______°F
Which statement below is correct? Select one: A. The value of a correlation between X and Y is reported by a researcher to be r = -0.5, it indicates that the X variable explains 25% of the variability in the Y variable in a univariate regression. B. QQ plot can be used to judge whether there is an outlier effect in the regression. C. Capital asset pricing theory asserts that individual stock returns are best explained by multiple factors. D. You are running a regression of Y on X, if you scale Y and X by dividing them by 100, it will have no effect on intercept and coefficient of X.
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, ý = bo + b,x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. 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. Hours Unsupervised 1 1.5 4 4.5 5.5 Overall Grades 87 86 79 78 76 67 65 Table Copy Data Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Prev 田 Tables E Keypad AnswerHow to enter your answer (opens in new window Keyboard Shortcuts © 2021 Hawkes Learning JIS A
Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude 11 13 24 28 31 32 Temperature 57 32 24 1 - 31 - 41 - 52 a. Find the explained variation. (Round to two decimal places as needed.)
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Listed below are amounts of court income and salaries paid to the town justices for a certain town. All amounts are in thousands of dollars. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 99% confidence level with a court income of $800,000. $66 $27 $417 $46 $1576 $1130 $258 $57 $252 $57 $151 $30 $108 $25 $19 Court Income Justice Salary $91 $49 $21 a. Find the explained variation. (Round to three decimal places as needed.) b. Find the unexplained variation. (Round to three decimal places as needed.) c. Find the indicated prediction interval. I
Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude Temperature 2 55 a. Find the explained variation. 8 40 10370.30 (Round to two decimal places as needed.) b. Find the unexplained variation. (Round to five decimal places as needed.) 13 25 20 - 3 28 - 26 31 41 34 - 53
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 + bjx, 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 21 23 29 43 50 Number of Bids 1 2 4 7 Table Copy Data Step 5 of 6: Determine if the statement "All points predicted by the linear model fall on the same line" is true or false.
Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude Temperature a. Find the explained variation. (Round to two decimal places as needed.) 2 57 36 16 22 21 27 -35 31 -41 34 - 60
You have estimated a multiple regression model with 6 explanatory variables and an intercept from a sample with 46 observations. What is the critical value of the test statistic (tc) if you want to perform a test for the significance of a single right-hand side (explanatory) variable at α = 0.05? a.) 2.023 b.) 2.708 c.) 2.423 d.) 2.704

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