ECE STAT1100 - Wallingford Public Schools
... special arrangements are made with the teacher upon return. Failure to do so will result in a zero. It is the student’s responsibility to inquiry about work that was missed in absenteeism. Quizzes: Unannounced quizzes. (Approximately four to eight per marking period)Missed quizzes will be made up fo ...
... special arrangements are made with the teacher upon return. Failure to do so will result in a zero. It is the student’s responsibility to inquiry about work that was missed in absenteeism. Quizzes: Unannounced quizzes. (Approximately four to eight per marking period)Missed quizzes will be made up fo ...
Data Mining in Forecasting
... Program is going to compute a distance associated to each attribute Continuous Variables are measured in different scales Categorical attributes will use a weighted mechanism Example is will they respond to marketing to take a loan ...
... Program is going to compute a distance associated to each attribute Continuous Variables are measured in different scales Categorical attributes will use a weighted mechanism Example is will they respond to marketing to take a loan ...
Association
... – How tall children are compared to their parents? – He thought he had made a discovery when he found that child’s heights tend to be more moderate than that of their parents. • For example, if the parents were very tall their children tended to be tall, but shorter than the parents. • This discover ...
... – How tall children are compared to their parents? – He thought he had made a discovery when he found that child’s heights tend to be more moderate than that of their parents. • For example, if the parents were very tall their children tended to be tall, but shorter than the parents. • This discover ...
CHAPTER 15: TIME SERIES FORECASTING
... To get quarterly trend values, new slope is 1.68 / 4 = 0.42 and new intercept is 95.35 - 1.5 (0.42) To get monthly trend values, new slope is 1.68 / 12 = 0.14 and new intercept is 95.35 - 5.5 (0.14) Example 5: Data on annual sales (in millions) for Ford Motor Company for 1982 to 1990 are given below ...
... To get quarterly trend values, new slope is 1.68 / 4 = 0.42 and new intercept is 95.35 - 1.5 (0.42) To get monthly trend values, new slope is 1.68 / 12 = 0.14 and new intercept is 95.35 - 5.5 (0.14) Example 5: Data on annual sales (in millions) for Ford Motor Company for 1982 to 1990 are given below ...
Review of Chapters 6-9
... • The linear regression equation E(y) = + b x is part of a model. The model has another parameter σ that describes the variability of the conditional distributions; that is, the variability of y values for all subjects having the same x-value. • For an observation, difference y yˆ between obser ...
... • The linear regression equation E(y) = + b x is part of a model. The model has another parameter σ that describes the variability of the conditional distributions; that is, the variability of y values for all subjects having the same x-value. • For an observation, difference y yˆ between obser ...
Coefficient of determination
In statistics, the coefficient of determination, denoted R2 or r2 and pronounced R squared, is a number that indicates how well data fit a statistical model – sometimes simply a line or a curve. An R2 of 1 indicates that the regression line perfectly fits the data, while an R2 of 0 indicates that the line does not fit the data at all. This latter can be because the data is utterly non-linear, or because it is random.It is a statistic used in the context of statistical models whose main purpose is either the prediction of future outcomes or the testing of hypotheses, on the basis of other related information. It provides a measure of how well observed outcomes are replicated by the model, as the proportion of total variation of outcomes explained by the model (pp. 187, 287).There are several definitions of R2 that are only sometimes equivalent. One class of such cases includes that of simple linear regression where r2 is used instead of R2. In this case, if an intercept is included, then r2 is simply the square of the sample correlation coefficient (i.e., r) between the outcomes and their predicted values. If additional explanators are included, R2 is the square of the coefficient of multiple correlation. In both such cases, the coefficient of determination ranges from 0 to 1.Important cases where the computational definition of R2 can yield negative values, depending on the definition used, arise where the predictions that are being compared to the corresponding outcomes have not been derived from a model-fitting procedure using those data, and where linear regression is conducted without including an intercept. Additionally, negative values of R2 may occur when fitting non-linear functions to data. In cases where negative values arise, the mean of the data provides a better fit to the outcomes than do the fitted function values, according to this particular criterion.