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NEW QUESTION: 1
In the middle of a transaction, a user session was abnormally terminated but the instance is still up and the database is open. Which two statements are true in this scenario? (Choose two.)
A. The alert log file gives detailed information about the failure.
B. The transaction is rolled back by the next session that refers to any of the blocks updated by the failed transaction.
C. SMON rolls back the transaction and releases the locks.
D. PMON rolls back the transaction and releases the locks.
E. Data modified by the transaction up to the last commit before the abnormal termination is retained in the database.
F. Event Viewer gives more details on the failure.
Answer: D,E
NEW QUESTION: 2
Your database is running in ARCHIVELOG mode. One of the data files, USERDATA01.dbf, in the USERS tablespace is damaged and you need to recover the file until the point of failure. The backup for the datafile is available. Which three files would be used in the user-managed recovery process performed by the database administrator (DBA)? (Choose Three)
A. Archive Logs since the latest backup to point of failure
B. Control file
C. Redo logs
D. The latest backup of only the damaged data file
E. Temporary files of temporary tablespace
F. The latest backup of all the data file in the USERS tablespace
Answer: A,C,D
NEW QUESTION: 3
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、記載された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合もあれば、正しい解決策がない場合もあります。
このセクションの質問に回答すると、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
複数の列に欠損値を含む数値データセットを分析しています。
機能セットの次元に影響を与えることなく、適切な操作を使用して欠損値を消去する必要があります。
すべての値を含めるには、完全なデータセットを分析する必要があります。
解決策：最後の観測キャリーフォワード（IOCF）メソッドを使用して、欠落したデータポイントを補完します。
ソリューションは目標を達成していますか？
A. いいえ
B. はい
Answer: A
Explanation:
Instead use the Multiple Imputation by Chained Equations (MICE) method.
Replace using MICE: For each missing value, this option assigns a new value, which is calculated by using a method described in the statistical literature as "Multivariate Imputation using Chained Equations" or "Multiple Imputation by Chained Equations". With a multiple imputation method, each variable with missing data is modeled conditionally using the other variables in the data before filling in the missing values.
Note: Last observation carried forward (LOCF) is a method of imputing missing data in longitudinal studies. If a person drops out of a study before it ends, then his or her last observed score on the dependent variable is used for all subsequent (i.e., missing) observation points. LOCF is used to maintain the sample size and to reduce the bias caused by the attrition of participants in a study.
References:
https://methods.sagepub.com/reference/encyc-of-research-design/n211.xml
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3074241/
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