The attached data contains observations from a country on the quantity of money in millions (Y); income, in millions(✗₁); and the local authority interest rate (X2). Estimate the model below and write a report on your findings. Whatcan be concluded from the Durbin-Watson statistic for the fitted regression?=YtBo+B1x1t+B2×2+ + Yyt− 1 + εtClick the icon to view the data.Click the icon to view a table of Durbin-Watson critical values.Estimate the model.ŷ₁ = 0 + 0 ×₁ + (1)×2 + (1) Yt-1(Round to two decimal places as needed.)...

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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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Provide an appropriate response. Based on findings from the Health and Nutrition Examination Survey conducted by the National Center for Health Statistics from April 1971 to June 1974, tF regression equation predicting the average weight of a male aged 18-24 (y) based on his height (x) is given by y = -172.63 + 4.842x. (www.cdc.gov/nchs/da alad/ad014acc.pdf) What is the best prediction for the weight of a male aged 18-24 who is 68 inches tall? Round your answer to the nearest pound. O 173 lb. O 68 in. O 157 lb. O 166 lb.
In the picture, there is a summary of regression analysis. Please write the regression equation and interpret the p-value which is indicated in output as p-value: < 2.2e-16.
• When fitting a linear regression, multiple regression lines may be equally as good to represent the data. True O False
Terminology Using the lengths (in.), chest sizes (in.), and weights (lb) of bears from Data Set 9 “Bear Measurements’’ in Appendix B, we get this regression equation: Weight = −274 + 0.426 Length +12.1 Chest Size. Identify the response and predictor variables.
Can brand, battery life, and internal storage capacity affect a smartphone's price? Use MegaStat and α = .05 to perform a regression analysis for the Smartphones01BS dataset and answer the following questions. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text.
Can brand, battery life, and camera resolution affect a smartphone's price? Use α = .05 to perform a regression analysis for the Smartphones01BC dataset and answer the following questions. Solve this problem using MegaStat, and write your complete answers in the Response Box so I know that you can interpret the output. Attach your MegaStat file so I can see that you used the correct analysis method to solve this problem. Download: Smartphones01BC a. Perform the regression and write the complete regression equation. b. Based on your regression equation, which brand increases the price of a smartphone the most? Use the statistics from your output to explain your answer. c. Which predictors are significant, and which are not? Use the statistics from your output to explain your answer. d. Use your regression equation to predict the price of an LG smartphone with a 40-hour battery and 12-megapixel camera.
I couldn't include the options for the graphs because it only allows me to add two pictures.
Please tell it is true or false
The data show The chest size and weight of several bears find regression equation, letting chest size be the independent variable then find the best predicted weight of a bear with a chest size of 51 inches is the result close to the actual weight of 422 pounds use a significance level of 0.05 Chest size : 45, 50, 43, 43, 52, 52. Weight : 352, 374, 275, 314, 440, 367.
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.
Q1: [Regression and Correlation] The index of biotic integrity (IBI) is a measure of water quality in streams. As a data analyst you must monitor, track, and predict changes in water quality. You want to create a simple linear regression model that will allow you to predict changes in IBI in forested area. The following table conveys sample data from a coastal forest region and gives the data for IBI and forested area in square kilometers. Let forest area be the predictor variable (x) and IBI be the response variable (y). IBI X 47 72 21 72234 19 58 49 Forest Area Y 38 59 27 24 63 49 45 Required a. Q2: [Naïve Bayes] a. Write the pseudo-code of the following Naïve Bayes algorithm b. Consider the given dataset that classifies animals into two distinct classes. The classes are labeled as 'cat' and 'dog'. Use Naive Bayes classifier to figure out the class (cat/dog) of an instance if it has the following values of attributed Plot Scatter graph b. Determine the regression equation c. Compute…
In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67 the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?

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