Question

you are conducting a regression analysis to explain the sales of a particular model of automobile....

you are conducting a regression analysis to explain the sales of a particular model of automobile. You want to include the color of the automobile. The model is available in red, white, blue and black. how many dummy variables should you use for color?

Homework Answers

Answer #1

Solution: There are four color's (red, white, blue and black) of the automobile. Dummy variable  is a numerical variable used in regression analysis to represent subgroups of the sample in your study. Here we will use three dummy variables for these four poosible color's of automobile.

Let's suppose we have 5 cars, with four possible color's

Here s1 denotes the dummy variable for color White, s2 denotes the dummy variable for blue and s3 denotes the dummy variable for black. Please note the color red has been treated as control group. so when all the values of dummy variables are 0 indicates the car is red.

As we can see, the car #1 is white color

car #2 is red color

car #3 is blue color

car #4 is red color

car #5 is black color

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Which of the following situations would require a categorical variable in a multiple linear regression model?...
Which of the following situations would require a categorical variable in a multiple linear regression model? -Thickness of a wooden plank in inches. -Color of a vehicle: blue, red, white, black. -Number of siblings. -Weight of a package in ounces.
Think about a healthcare scenario where multiple regression might be useful in a healthcare organization. Consider...
Think about a healthcare scenario where multiple regression might be useful in a healthcare organization. Consider what your dependent and independent variables might be for conducting a multiple regression analysis. Build a small example, and run the regression analysis. Post a description of the dependent and independent variables you will use for your multiple regression analysis, and then explain your regression model in terms of your dependent and independent variables. Explain how you might measure your variables. Be specific and...
(a) In regression analysis, often the researcher will encounter issues of omitted variable bias (OVB) or...
(a) In regression analysis, often the researcher will encounter issues of omitted variable bias (OVB) or their included variables are too closely related (multicollinearity). In you own words, (i) explain what is meant by OVB? (ii) what is multicollinearity (iii) How do these problems lead to type1/type 2 errors? (b) In your own words, describe your understanding of linear regression analysis. What is the causal fallacy? (c) How is the model fit measured? In your answer describe both the R-squared...
Essentially regression analysis is what this course is all about. When we do regression analysis, we...
Essentially regression analysis is what this course is all about. When we do regression analysis, we I. determine how to specify the model II. decide which explanatory variables to include in the model III. estimate the parameters of the model using the data IV. use the model to predict the response given the values of the explanatory variables V. assess the usefulness of the model in explaining the variability in the response variable Group of answer choices a. I, II...
Mileage tests are conducted for a particular model of automobile. If a 99% confidence interval with...
Mileage tests are conducted for a particular model of automobile. If a 99% confidence interval with a margin of error of  mile per gallon is desired, how many automobiles should be used in the test? Assume that preliminary mileage tests indicate the standard deviation is 2.7 miles per gallon.
1.One-way ANOVA can be applied to: a)Regression model with several dummy variables (created for a qualitative...
1.One-way ANOVA can be applied to: a)Regression model with several dummy variables (created for a qualitative independent variable) to test the overall usefulness of the model b)Regression model with several quantitative independent variables to test the overall usefulness of the model c)Both of the above D) none of the above 2. You need to decide whether you should invest in a particular stock.  You would like to invest if the price is likely to rise in the long run.  Assuming the past...
You are forecasting cash flows using regression analysis (sales is the independent variable). After estimating the...
You are forecasting cash flows using regression analysis (sales is the independent variable). After estimating the regression model, you have recorded the following regression equation: Net Cash Flow = $27,000 + (0.7*Sales). Use this model to: Forecast net cash flow, assuming the next month’s Sales will equal to $150,000 Evaluate your forecast from part (a), assuming that month has passed, in which the actual net cash flow was $145,000 Determine the impact of an additional $1 in sales on net...
Regression analysis is a tool that is used to forecast into the future. Explain how you...
Regression analysis is a tool that is used to forecast into the future. Explain how you would use regression analysis to forecast future customer demand for a new innovative product called the combination washer/dryer/ cloth folder unit.
Let us instead fit a linear regression model to the data on employee sales. in particular,...
Let us instead fit a linear regression model to the data on employee sales. in particular, we fit the model: sales = b0 + b1*employee group + e, where employee group is a categorical variable with values a, b, and c. we set group a to be the reference category.  from this model we get the following output. from this output, 1. what can we conclude is the mean sales for group a (in dollars/day)? 2.what can you conclude is the...
The commercial division of a real estate firm is conducting a regression analysis of the relationship...
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. The regression equation is Y = 20.0 + 7.27 X Predictor Coef SE Coef T Constant 20.000 3.2213 6.21 X   7.270 1.3626 5.29 Analysis of Variance SOURCE DF SS...