1. What do the measures of central tendency tell us about? Which statistics measure central tendency?
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1. What do the measures of central tendency tell us about? Which statistics measure central tendency?
2. What do the measures of spread tell us about? Which statistics measure the spread of data?
3. There are specific “pairs” of central tendency and spread. What are these? (Which measures can only be used with each other?)
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- This question tests your understanding of data transformation. We did an assignment on this process. If you test your data and find that it is not suitable for testing, which mathematical function can you put each score through to make it usable and suitable for testing? Select one: a. There is no way to make the data usable. b. square root each number c. subtract the df from each number d. use the variance instead of each number Clear my choiceTESTING YOUR UNDERSTANDING Exercise 3-1. Consider the scenario described at the beginning of this chapter: When parents call to say that children are sick, we have to let their classroom teachers know, and if it's sports day and the child is on a school team, the sports teacher might have to sort out substitutes. Then we need to count up all the days missed to put on the child's report. The Department of Education needs the totals each term, too. Run through the steps in the summary section and sketch some use cases and an initial data model. Assume that the main objectives are to record the absences for the classroom teacher, for school reports, and for statistics given to the Department of Education.Analysts at a start-up company are analyzing 35 months of sales data. They partition the data (the first 20 observations are assigned to the training set; the most recent 15 months are in the test set). The only independent variable is T (month number, ranging from 1 to 35). Five models (polynomials of order 1 - 5) are fit to the data. The first order is just the linear model; the 2nd order polynomial is the quadratic model; order 3 is the cubic model, etc. In each case the model is fit on the training data, and scored on both the training and test data sets. The results are below. Based on this output, which is the best predictive model? Metrics AE RMSE MAE SSE Metrics AE RMSE MAE SSE Model 2 Model 3 Model 5 Model 4 Model 1 1 <0.000001 0.955978 0.792802 18.277907 1 -1.034550 1.424155 1.208991 30.423248 Training Data Scoring Models (Polynomial of order 1-5) 4 2 <0.000001 0.928791 0.759583 17.253086 3 <0.000001 <0.000001 0.928295 0.855568 0.761951 0.652212 17.234646 14.639962 Test Data…
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