EC255 Study Guide - Final Guide: Linear Regression, Null Hypothesis, Dependent And Independent Variables

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olivelizard309

12 Feb 2018

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The constant and coefficients are estimated from sample information, resulting in the following model: Example: a real estate study was conducted in a canadian town to determine what variables, if any, are related to the market price of warehouse space. Suppose the researcher wants to develop a regression model to predict the market price of a warehouse by two variables, total number of square feet in the warehouse and age of the warehouse. Regression constant, 57. 4, is the y intercept. y intercept - value of y(hat) if both x1 and x2 = zero. In practical terms, it may make little sense to say that a brand new or not yet built (x2=0) warehouse containing no square feet (x1=0) would cost ,400. All other variables being held constant, the addition of one square foot of space in the warehouse results in a predicted increase of . 70 in the price of the warehouse.

Related Questions

True/False Questions

Circle T or F for True or False. For full credit and reward for help, please provide a written answer using complete sentences for each question.

1. T F In a simple linear regression, if the independent variable has a small variance, the estimated slope coefficient, b^, will have a large p-value.

2. T F Demographic variables are included in an estimated demand function to proxy for tastes and preferences.

3. T F The estimated intercept, ?, in any simple or multiple regression has the same units of measure as the dependent variable, yi.

4. T F A trend variable in a linear regression model will shift the intercept up or down.

5. 5. T F In a simple regression, if the correlation between the dependent and independent variables is zero, the conditional mean of the dependent variable is equal to the unconditional mean.

Thank you to anyone able to help and I hope to hear from someone as soon as they can, I am trying to figure these out to reference for my test tomorrow. I am not sure how to properly state each of the answers and truly appreciate any help that anyone can give me in trying to help me with these questions.

ECON 3050

Q24. The coefficient of determination (r²) is calculated as 0.49, then the correlation coefficient:

Cannot be determined without the data

Should be - 0.70 or 0.70

Should be 0.

Neither of the above

Q25. A regression line is used for all of the following except one. Which one is not a valid use of a regression line?

To estimate the average value of Y at a specified value of X.

To predict the value of Y for an individual, given that individual's X-value.

To estimate the change in Y for a one-unit change in X.

To determine if a change in X causes a change in Y.

Q26. Which choice is not an appropriate description of YË in a regression equation?

Estimated response

Predicted response

Estimated average response

Observed response

Q27. Which of the following is the best way to determine whether or not there is a statistically significant linear relationship between two quantitative variables?

Compute a regression line from a sample and see if the sample slope is 0.

Compute the correlation coefficient and see if it is greater than 0.5 or less than â0.5.

Conduct a test of the null hypothesis that the population slope is 0.

Conduct a test of the null hypothesis that the population intercept is 0.

Q28. There is no relationship between variables unless the data points lie in a straight line.

True

False

Q29. The sample regression analysis

Is the same as the population regression line

Is used to estimate the population regression line

Shows the true relation between dependent and independent variables

None of the above.

Q30. In regression, a dependent variable is sometimes called a predictor variable.

True

False

Q31. In a linear regression equation of the form y = a + bx, the intercept shows

The amount that y changes when x changes by one unit

The amount that x changes when y changes by one unit

The value of y when x is zero

The value of x when y is zero.

Q32. In a linear regression equation of y = a + bx, the slope b shows

Y / b

X / b

Y / X

X / Y

yellowturtle964

Problem 1.

You are conducting a study on the price of houses in Los Angeles county, and studied data from n= 25 houses. Let the following variables denote your observations:

y^ = price of a house in thousands of dollars

x1= square footage

x2= distance in miles to nearest grocery store

x3 = a dummy variable that equals 1 if the house is in the top 50 state-

ranked school district and 0 otherwise.

x4= a dummy variable that equals 1 if the house is in Beverly Hills or Malibu

and 0 otherwise.

A) What do you predict would be the sign of each coefficient (bi) in the regression line? Briefly explain each.

B) Suppose b1=. 17 interpret the coefficient.

C) Suppose b4= 244.32. Interpret the coefficient

D) Suppose you run a restricted regression using x1, x2, and x4 yields R2 =

857. Furthermore, suppose the complete regression using x1, x2, x3 and x4 yields R2 = .772.

Which model do you think is better to use? Why?

E) Interpret R2 and R2 of the complete regression?

F) Why might the interaction term x1*x4 be useful to include in your

regression?

Thanks for your time

EC255 Study Guide - Final Guide: Linear Regression, Null Hypothesis, Dependent And Independent Variables

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