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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Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R? = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year Write a sentence explaining the value of the slope for this regression line. For every increase in year, the number of vehicle registrations in the US increases by 3.0161 million. For every increase in year, the number of vehicle registrations in the US increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 3.0161 million. Registrations (in millions)
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.
NISH Boom Cardsl - Play boom.combg.com/play/1Dwb@fgH9jdMjFmxn/?Lenchcrld AYANWBBrodXKJA its X + 000000000000000000000 13 boomcardsk Use the following regression equation to predict the height of an 8-year-old American girl. Round all answers to the nearest hundredth (2 places after the decimal) and type it in the space below. y = 2.59x + 29.31 An average 8-year-old American girl is approximately 5 centimeters tall. W y tip Type here 90 C Submit X Give up Skip Q Overview ★ Save Card O P Dec 3 1
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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.
Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 1.5.
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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.
An ice cream truck owner collects data on the number of sales made each day and the average temperature that day. He computes a regression line for predicting the number of sales based on how far the daily temperature is from freezing (0 degrees Celsius) and finds sales = 3.22 - 1.8 (degrees over 0 Celsius). Identify the "y-intercept". A. -1.8 B. 1.8 C. 3.22 D. 0
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?

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