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ADO.NET is a disconnected-data-centric environment. Disconnected data retrieves the data from the data store and then closes the connection. An advantage of this model is that the data can be downloaded to the client, the connection can be closed, and the user can work with the data while offline. Updates can be sent back to the server when appropriate. A data provider supplies a bridge from the application to the data source. Think of the data provider as a set of drivers that are specific to a data store. The following data objects are provider specific: the Connection, DataAdapter, Command, Parameter, CommandBuilder, and DataReader. The Command object is used to issue a command to the data store. The command can be a command to retrieve data or a command to insert, update, or delete data. The DataSet is a complete in-memory database. The DataTable contains DataRows, DataColumns, Constraints, and references to ParentRelations and ChildRelations. The DataView is a window into a DataTable that provides filtering and sorting.

Table 12-15 Analysis of Variance of Example 12-12 Source of Variation Regression SSR 1 1 0 0 2 SSR 1 2 0 1, Error Total Sum of Squares 1012.0595 130.6091 881.4504 7.7943 1019.8538 Degrees of Freedom 2 1 1 17 19 Mean Square 506.0297 130.6091 881.4504 0.4508 f0 1103.69 284.87 1922.52 P-value 1.02E-18 4.70E-12 6.24E-19

The analysis of variance for this model is shown in Table 12-15. Note that the hypothesis H0: 1 0 (significance of regression) would be rejected at any reasonable level of 2 significance because the P-value is very small. This table also contains the sums of squares SSR SSR 1 SSR 1

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The DataAdapter is responsible for moving data between a data store and a DataTable or DataSet. Before changes can be made to the DataTable, the DataTable s PrimaryKey property should be assigned. The DataGrid has abilities for adding, deleting, and in-place editing, sorting, and paging. A DataRow can be edited by assigning new contents to the DataRow. Using this method, however, triggers validation with each change. It is better to use the BeginEdit method of the DataRow, which will postpone validation until the EndEdit method is executed.

1, 2 0 10 02 02

1, 0 2

8

so a test of the hypothesis H0: 2 0 can be made. Since this hypothesis is also rejected, we conclude that tool type has an effect on surface finish. It is also possible to use indicator variables to investigate whether tool type affects both the slope and intercept. Let the model be Y

where x2 is the indicator variable. Now if tool type 302 is used, x2 Y If tool type 416 is used, x2

1. What is the proper method for creating a DataRow 2. How is a DataReader created 3. What is the purpose of BeginEdit and EndEdit 4. Name two of the objects that are contained in a DataSet. 5. Name four data providers. 6. What method of which object is used to send all of the modified data in a DataSet back to the data store 7. What is the most efficient method of the Command object that can retrieve the result of the following SQL statement: Select count(*) from Employees

0 1x1

0 0 1 x1 22

3 x1

1. Use the DataTable s NewRow method. 2. Use the Command s ExecuteReader method. 3. BeginEdit postpones validation checking until the EndEdit method is executed. 4. DataTable and DataRelation objects. 5. Sql, OleDb, Odbc, and Oracle. 6. The Update method of the DataAdapter. 7. Use the ExecuteScaler method.

3 2 x1

Note that 2 is the change in the intercept and that 3 is the change in slope produced by a change in tool type. Another method of analyzing these data is to fit separate regression models to the data for each tool type. However, the indicator variable approach has several advantages. First, only one regression model must be fit. Second, by pooling the data on both tool types, more degrees of freedom for error are obtained. Third, tests of both hypotheses on the parameters 2 and 3 are just special cases of the extra sum of squares method.

3

12-6.3

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An important problem in many applications of regression analysis involves selecting the set of regressor variables to be used in the model. Sometimes previous experience or underlying theoretical considerations can help the analyst specify the set or regressor variables to use in a particular situation. Usually, however, the problem consists of selecting an appropriate set of

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