How to handle missing values in panel data?
Introduction to K-means Clustering K -means clustering is a type of unsupervised learning, which is used when you have unlabeled data (i.e., data without defined categories or groups). The goal of this algorithm is to find groups in the data, with the number of groups represented by the variable K.
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The resulting missing data can complicate the analysis of the data. If you have only a few respondents to your questionnaire, then your options for handling missing data are relatively few. If you have thousands of respondents, then you have more options, but each of these will take time and careful consideration.
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Johnson and Albert (1999) analysed data on the grading of the same essay by five experts. Essays were graded on a scale of 1 to 10 with 10 being excellent. In this exercise we use the subset of the data limited to the grades from graders 1 to 5 on 198 essays ( essays.dta ).
Here are some limitations of SPSS. Default graphics are far from publication quality. They can be improved with chart editing - up to a point. In general, it’s better to use other programs for graphics. For some important questions (such as intera.