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		<title>übungstest exam A00-240 Prüfungsfragen dumps</title>
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		<description><![CDATA[übungstest exam A00-240 Prüfungsfragen dumps SAS Advanced Programming Exam for SAS 9 (ICND2 v3.0) www.it-pruefungen.ch QUESTION NO: 1 When mean imputation is performed on data after the data is partitioned for honest assessment, what is the most appropriate method for &#8230; <a href="https://deutsch.pruefungsfrage.ch/2018/08/19/uebungstest-exam-a00-240-pruefungsfragen-dumps/">Weiterlesen <span class="meta-nav">&#8594;</span></a>]]></description>
			<content:encoded><![CDATA[<p><a href="https://www.it-pruefungen.ch/A00-240.htm">übungstest exam A00-240 Prüfungsfragen dumps</a> SAS Advanced Programming Exam for SAS 9 (ICND2 v3.0) www.it-pruefungen.ch</p>
<p>QUESTION NO: 1<br />
When mean imputation is performed on data after the data is partitioned for honest assessment, what is the most appropriate method for handling the mean imputation?</p>
<p>A. The sample means from the validation data set are applied to the training and test data sets.<br />
B. The sample means from the training data set are applied to the validation and test data sets.<br />
C. The sample means from the test data set are applied to the training and validation data sets.<br />
D. The sample means from each partition of the data are applied to their own partition.</p>
<p>Answer: B</p>
<p>QUESTION NO: 2<br />
An analyst generates a model using the LOGISTIC procedure. They are now interested in getting the sensitivity and specificity statistics on a validation data set for a variety of cutoff values.<br />
Which statement and option combination will generate these statistics?</p>
<p>A. Scoredata=valid1 out=roc;<br />
B. Scoredata=valid1 outroc=roc;<br />
C. mode1resp(event= &#8217;1&#8242;) = gender region/outroc=roc;<br />
D. mode1resp(event&#8221;1&#8243;) = gender region/ out=roc;</p>
<p>Answer: B</p>
<p>QUESTION NO: 3<br />
In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)</p>
<p>A. Simple random sampling without replacement<br />
B. Simple random sampling with replacement<br />
C. Stratified random sampling without replacement<br />
D. Sequential random sampling with replacement</p>
<p>Answer: A,C</p>
<p>Prüfungsvorbereitung Studienmaterial A00-240 deutsch SAS Advanced Programming Exam for SAS 9 www.it-pruefungen.ch</p>
<p>QUESTION NO: 4<br />
In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?</p>
<p>A. Training: 50% Validation: 0% Testing: 50%<br />
B. Training: 100% Validation: 0% Testing: 0%<br />
C. Training: 0% Validation: 100% Testing: 0%<br />
D. Training: 50% Validation: 50% Testing: 0%</p>
<p>Answer: D</p>
<p>QUESTION NO: 5<br />
A confusion matrix is created for data that were oversampled due to a rare target.<br />
What values are not affected by this oversampling?</p>
<p>A. Sensitivity and PV+<br />
B. Specificity and PV<br />
C. PV+ and PV<br />
D. Sensitivity and Specificity</p>
<p>Answer: D</p>
<p>IT-Prüfungen <a href="https://www.it-pruefungen.ch/A00-240.htm">A00-240</a> SAS Advanced Programming Exam for SAS 9 www.it-pruefungen.ch</p>
<p>QUESTION NO: 7<br />
An analyst has a sufficient volume of data to perform a 3-way partition of the data into training, validation, and test sets to perform honest assessment during the model building process.<br />
What is the purpose of the test data set?</p>
<p>A. To provide a unbiased measure of assessment for the final model.<br />
B. To compare models and select and fine-tune the final model.<br />
C. To reduce total sample size to make computations more efficient.<br />
D. To build the predictive models.</p>
<p>Answer: A</p>
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