Stats crossword puzzle

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Across
  1. 1. , A numerical measure of the direction and strength of a linear association.
  2. 3. , An equation of the form ÿ = bo + b1x.
  3. 4. , the square of the correlation between y and x.Gives the fraction of the variability of y accounted for by the least squares linear regression on x.An overall measure of how successful the regression is in linearly relating y to x.
  4. 5. , shows the relationship between two quantitative variables measured in the same cases.
  5. 8. , The numbers in the model that have to be chosen to explicitly determine the value of the model.
  6. 9. , To check whether a linear model is appropriate, it is usually best to plot the residuals. A histogram of the residuals can be checked for multiple modes and y-outliers. A scatterplot of residuals against predicted values can reveal bends, groups, and model outliers.
  7. 12. , gives a starting value in y-units. It's the y-value when x is 0.
  8. 13. , the differences between data values and the corresponding values predicted by the regression model-or, more generally, values predicted by any model.
  9. 14. , response variable x-variable, y-variable, you must choose a role for each variable. Assign to the y-axis the variable that you hope to predict or explain. Assign to the x-axis the variable that accounts for, explains, predicts, or is otherwise responsible for the y-variable.
  10. 17. , Because the correlation is always less than 1.0 in magnitude each predicted y tends to be fewer standard deviations from its mean than its corresponding x was from its mean.
Down
  1. 2. , direction,form,scatter
  2. 6. satisfies the least squares criterion.
  3. 7. , The value of y found for each x value in the data. It is found by substituting the x-value in the regression equation. They are the values on the fitted line; the points (x, y) all lie exactly on the fitted line.
  4. 10. , Criterion specifies the unique line that minimizes the variance of the residuals or, equivalently, the sum of the squared residuals.
  5. 11. ,The particular linear equation y = bo + b1x
  6. 15. interpret we need to know the variables (along with their "W's") and their units.
  7. 16. , An equation or formula that simplifies and represents reality.
  8. 18. , Gives a value in "y-units per x-unit." Changes of one standard deviation in x are associated with changes of r standard deviations in predicted values of y.