1 / 10

Multivariate Assumptions - Homework

Multivariate Assumptions - Homework. Sample Problem Steps in Solving Problems. Sample problem. The homework problems ask about normality and linearity for a pair of variables. Specifically, they ask tow things:

bruis
Download Presentation

Multivariate Assumptions - Homework

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Multivariate Assumptions - Homework Sample Problem Steps in Solving Problems

  2. Sample problem The homework problems ask about normality and linearity for a pair of variables. Specifically, they ask tow things: 1) Do the variables, either in original form or as a logarthmic transformation, satisfy the skewness and kurtosis criteria for normality? 2) Is the linear relationship as measured by the correlation coefficient statistically significant?

  3. Level of measurement Testing for normality and linearity requires that the variables be metric. Since both of these variables are metric, we can eliminate “Incorrect application of a statistic” as a possible answer.

  4. Testing normality with the script The problem does not specify which variable is the dependent variable, so I will treat poverty as the dependent variable and deathrat as the independent variable Mark the option button for testing the “Assumption of normality”. Click OK to produce the output. The problem only asks about the logarithmic transformation, so I will clear the check boxes for the other transformations.

  5. Normality for percent of the population below poverty line The variable "percent of the population below poverty line" [poverty] satisfied the criteria for a normal distribution. The skewness of the distribution (.179) was between -1.0 and +1.0 and the kurtosis of the distribution (-.642) was between -1.0 and +1.0.

  6. Normality for the logarithmic transformation of death rate The logarithmic transformation of "death rate" [LGDEATHR=LG10(DEATHRAT)] satisfied the criteria for a normal distribution. The skewness of the distribution (.137) was between -1.0 and +1.0 and the kurtosis of the distribution (-.273) was between -1.0 and +1.0.

  7. Testing linearity with the script The problem only asks about the logarithmic transformation for “Death rate” which I have designated as the independent variable, so I will clear the check boxes for the other transformations. Mark the option button for testing the “Assumption of linearity”. Click OK to produce the output.

  8. Linearity of the relationship The correlation between logarithmic transformation of "death rate" [LGDEATHR=LG10(DEATHRAT)] and "percent of the population below poverty line" [poverty] was statistically significant (r=.427, p<0.001). The variables have a statistically significant linear relationship. The answer to the problem is true.

  9. Are the variables to be evaluated metric? Incorrect application of a statistic No Yes No Yes Steps in answering questions about multivariate assumptions – 1 Statistical evidence supports normality for both variables? False

  10. No No Yes Steps in answering questions about multivariate assumptions – 2 Correlation between both variables statistically significant? False Yes Either variable is ordinal level? True True with caution

More Related