Regression AnalysisDependent variable is: Prediction Error (mi)R squared = 58.5%s = 69.66 with 20 - 2 = 18 degrees of freedomVariableInterceptYear since 1970Coefficient SE(Coeff) t-ratio472.67235.4013.4- 8.469431.682- 5.04P-value0.00000.0001 Shown to the right is a scatterplot of the error (in nautical miles) for predicting hurricanelocations 72 hours in the future vs. the year in which the prediction (and the hurricane)occurred. Complete parts a and b.Click the icon to view the regression analysis.Prediction Error (mi)525-100-a) Explain in words and numbers what the regression says. Choose the correct answer below.According to the model, the error made in predicting a hurricane's path was aboutaverage, in 1970. It has beenat a rate of about350Years (since 1970)nautical miles, onnautical miles per year.

Answered: Image /qna-images/answer/abf12656-b213-40fe-b754-170b90dafdae.jpg

Answered: Shown to the right is a scatterplot of…

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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Refer to the data set: x -1 1 -2 3 0 2 y 9 2 15 1 4 1.5 Part a: Make a scatterplot and determine which type of model best fits the data.Part b: Find the regression equation, round decimals to one place.Part c: Use the equation from Part b to determine y when x = 5.
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 784 838 822 949 1188 813 Temperature (°F) 65.7 67.8 66.2 79.9 92.3 73.5 What is the regression equation? What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000chirps per minute are? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an…
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Name: Shalisha Robertson Topic 30-8th Core Hours spent looking for Shooting Stars Number of shooting stars seen 0 2 0 3 2 4 1 4 2 6 4 6 2 7 What is the equation of your regression line for this data eate a scatter plot with your regression line drawn in.
Using the data, run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. What should be the attendance if the number of wins is 10? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500
Interpret the regression results.
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 63 inches. Is the result close to the actual weight of 522 pounds? Use a significance level of 0.05. Chest size (inches) 58 50 65 59 59 48 D 414 312 499 450 456 260 Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 63 inches? The best predicted weight for a bear with a chest size of 63 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 522 pounds? O A. This result is not very close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear. O C. This result is close to the actual weight of the…
Used cars 2010 Vehix.com offered several used ToyotaCorollas for sale. The following table displays the ages ofthe cars and the advertised prices. a) Make a scatterplot for these data.b) Do you think a linear model is appropriate? Explain.c) Find the equation of the regression line. d) Check the residuals to see if the conditions for infer-ence are met. Age (yr) Price ($) Age (yr) Price ($)1 15988 6 99951 13988 6 119882 14488 7 89903 10995 8 94883 13998 8 89954 13622 9 59904 12810 10 41005 9988 12 2995
Using your dataset, run a regression of Y=GPA and X=# Friends.(do not need your actual data, just the regression results)a) State what this regression is attempting to analyze. “By running this regression, we areattempting to show.....”b) Write out the regression equation and describe what it shows (if Friends increase by 1, then. . . ).c) Find your hypothesized GPA when the # friends equals 17.d) Is the slope of # of Friends significantly different from zero?Include Ho, Ha, decision rule, t statistic from table, tc, decision, and conclusion.e) Is the r-squared of # of Friends significantly different from zero?Include Ho, Ha, decision rule, F statistic from table, Fc, decision, and conclusion.
2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. (a) x 503 feet (c) x = 318 feet (b) x = 649 feet (d) x = 724 feet 766 494 484 520 44 620 508 Height, x Stories, y 51 46 43 39 38 (c) Predict the value of y for x=318. Choose the correct answer below. O A. 34 B. 50 O C. 47 O D. not meaningful (d) Predict the value of y for x=724. Choose the correct answer below. O A. 34 O B. 41 50
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y (b) x = 649 feet (d) x = 724 feet 766 620 520 508 494 484 (a) x = 503 feet 51 46 44 43 39 38 (c) x = 318 feet Find the regression equation. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O A. O B. O C. O D. 60- 60- 60 60- 0- 800 800 800 Height (feet 800 Height (feet) Height (Teet) Stories Stories:

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