document.write( "Question 851042: Which of the following is true and applicable of the Central Limit Theorem?\r
\n" );
document.write( "\n" );
document.write( "Check all that apply\r
\n" );
document.write( "\n" );
document.write( "Question 2 options:
\n" );
document.write( "
\n" );
document.write( "The sample drawn from the population doesn't have to be randomized as long as the population is normal.\r
\n" );
document.write( "\n" );
document.write( "
\n" );
document.write( "The sample can be from any population, even a non-normal population as long as the sample is randomized and larger than 25 or 30.\r
\n" );
document.write( "\n" );
document.write( "
\n" );
document.write( "The mean of the sample distribution is equal to the mean of the population distribution.\r
\n" );
document.write( "\n" );
document.write( "
\n" );
document.write( "The standard deviation of the sampling distribution is equal to the population distribution divided by the square root of the number in the sample.\r
\n" );
document.write( "\n" );
document.write( "
\n" );
document.write( "As the number in the sample becomes larger and larger, then the mean of the sampling distribution is equal to the population distribution for any normal population. \n" );
document.write( "
Algebra.Com's Answer #512523 by stanbon(75887)![]() ![]() ![]() You can put this solution on YOUR website! Which of the following is true and applicable of the Central Limit Theorem? \n" ); document.write( "Check all that apply \n" ); document.write( "Question 2 options:\r \n" ); document.write( "\n" ); document.write( "The sample drawn from the population doesn't have to be randomized as long as the population is normal.:: false \n" ); document.write( "------------------------ \n" ); document.write( "The sample can be from any population, even a non-normal population as long as the sample is randomized and larger than 25 or 30 :: true \n" ); document.write( "------------------------ \n" ); document.write( "The mean of the sample distribution is equal to the mean of the population distribution:: true \n" ); document.write( "------------------------ \n" ); document.write( "The standard deviation of the sampling distribution is equal to the population distribution divided by the square root of the number in the sample:: true \n" ); document.write( "----------------------------- \n" ); document.write( "As the number in the sample becomes larger and larger, then the mean of the sampling distribution is equal to the population distribution for any normal population:: ? \n" ); document.write( "==================== \n" ); document.write( "Cheers, \n" ); document.write( "Stan H. \n" ); document.write( "===================== \n" ); document.write( " \n" ); document.write( " |