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Construct your initial multivariate model by selecting a dependent variable Y and two independent variables X. Clearly define what each variable represents and how this relates to the overall theme you've been assigned. Explain the reasons for constructing this model by discussing the expected relationship between the Y and each X variable.
Step Simple Regression Analysis
Complete a separate simple regression analysis for Y and each X that you have selected for the model. Provide the equation, interpret the slope, and state its significance.. Also discuss the overall model performance for each X variable by looking at the adjusted R square. You should also plot the relationship between Y and each X in your model. Use the results of this step to comment on whether the chosen independent variables are suitable for inclusion in a multiple regression analysis. If you determine that an X variable is not appropriate, you should replace it with another variable.
The following dataset is from a study of the effects of second hand smoking in Baltimore, MD, and Washington, DC. For the 25 children involved in this study the outcome variable is
In simple regression the dependent variable Y was assumed to be linearly related to a single variable X. In real life, however, we often find that a dependent variable may depend o
Importance of official statistic
Read the “JET Copies” Case Problem on pages 678-679 of the text. Using simulation estimate the loss of revenue due to copier breakdown for one year, as follows: 1. In Excel, use a
10. If a set of scores has a sample mean of 25 and a sample variance of 4, find the following: a. the z-score for a raw score of 31 b. the z-score for a raw score of 18 c. the raw
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The file Midterm Data.xls has a tab labeled "Many vs. S&P" which presents historical price data for several assets, a volatility condition (VIDX = 1 if the NYSE volatility is grea
X 110 120 130 120 140 135 155 160 165 155 Y 12 18 20 15 25 30 35 20 25 10
Caveat We must be careful when interpreting the meaning of association. Although two variables may be associated, this association does not imply that variation in the independ
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