Suppose you have a survey where one of the variables is "Sex", and all of the 300people surveyed answered one of the following: 1) Male or 2) Female. Supposefurther that you create 2 dummy variables:D1 = 1 if male, zero otherwiseD2 = 1 if female, zero otherwiseWhat would happen if you include both dummy variables in your regression inExcel?O Excel will not be able to run a regression with both variables in the regression.Nothing. This is the correct way to do it.O Your regression will exhibit serial correlation.O Your regression will exhibit some multicollinearity, but can be remedied with "robuststandard errors."

The right way to do the analysis is by creating only one dummy variable that will have 0 for male…

Answered: Suppose you have a survey where one 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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Q2) Find the regression line for the following data, then predict the value of y when x is 5: X 0 2 4 6 8 y 2 4 3 8 10
A business statistics professor would like to develop a regression model to predict the exam scores for students based on their current GPAs, the number of hours they studied for the exam, and the number of times they were absent during the semester. The data for these variables can be found in this file. a) Run the multiple regression in Excel. Hint: set x1 = GPA, x2 = Hours, X3 = Absences. b) Find the R2 and explain its meaning. c) Explain the outcome of the F test. What does it mean? d) Explain the outcomes of the t tests for the slope coefficients. e) Write out the regression equation. f) Explain the meanings of the slope coefficients.
Marks obtained by students in a Chemistry test was adjusted because of an error in one of the questions. The marks are now classified as:A. Primary dataB. Secondary dataC. Regression dataD. External data
A simple regression was run where the dependent variable was the score on an individual's nationally given math test, and the independent variable was the number of math courses the individual had taken in high school. The following estimates were obtained. Y-500 25X In the equation above, the coefficient on the number of math courses tells us which of the following? OA) On average, for every additional test taken, the individual's test score increases by 525 points. OB) On average, for every additional test taken, an individual's test score increases by 25 points. OC) On average, an individual carns a score of 500 on the test. OD) On average, for every additional math course taken in high school, the individual's test score increases by 525 points. OE) On average, for every additional math course taken in high school, the individual's test score increases by 25 points.
Would I use the regression line to predict Y from X ? And what is the pattern of the scatterplot?
Use the following table to find the equation of the regression line, between x and y 2 3 4 1 2 3 y 1 2 3 3 2 O ý = 2.97x - 0.455 O ý = -0.455x + 2.97 O ý = 2.122x + 0.098 O ý = 0.098x + 2.122
solve c only
Fourteen hikers were surveyed at Algonquin Park, and asked for how many days have you been hikingand far did your travel in that time? The equation for the linear regression line is y+3x + 10.3 where x is the number of days and y is the distance travelled. Estimate the number of whole days a hiker would need to travel 35KM? Number of days hiked 1 1 2 3 3 5 5 6 7 7 9 10 11 12 Distance Traveled (km) 12 17 18 19 21 23 25 23 30 31 37 39 41 52
In a simple regression problem, r and B O may have opposite signs. O must have the same sign. O must have opposite signs. O are equal.
The following are the intelligence quotients (IQ) and the grade point average (GPA) of incoming Grade 12 students. If a significant relationship exists between the variables, perform a regression analysis. What GPA will students A and B obtain if their IQs are 159 and 92, respectively? Support your answer with computations/tables and draw the corresponding scatter diagram. Student IQ GPA 1 153 94 120 87 108 89 135 93 97 85 110 86 155 95 126 88 122 86 10 94 84 23455 6 7 8 9은
You may need to use the appropriate technology to answer this question. A regression analysis involving 45 observations relating a dependent variable and two independent variables resulted in the following information. ŷ = 0.406 + 1.3385x₁ + 2x₂ The SSE for the above model is 43. When two other independent variables were added to the model, the following information was provided. ŷ = 1.9 - 3x₁ + 12x2 + 4x3 + 8x4 This model's SSE is 36. At a 0.05 level of significance, test to determine if the two added independent variables contribute significantly to the model. State the relevant null and alternative hypotheses. O Ho: One or more of the parameters is not equal to zero. H₂: B₁ = P₂ = P3 =B4 = 0 B1 O Ho: One or more of the parameters is not equal to zero. H₂: B3 =B₁ = 0 O Ho: B3 = P4 = 0 H₂: None of the parameters are equal to zero. O Ho: B3 B4= = = H₂: One or more of the parameters is not equal to zero. O Ho: P₁ = P₂ = P3= P4= H: One or more of the parameters is not equal to zero. Find…
Find the least-squares regression line treating square footage as the explanatory variable. y = (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.)

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