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which of the following are binomial experiments or can be reduced to binomial experiments?
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surveying 100 people to determine if they like sudsy soap
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tossing a coin 100 times to see how many heads occur
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drawing a card with replacement from a deck and getting a heart
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asking 1000 people which brand of cigarettes
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testing four different brands of aspirin to see which brands are effective
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the expected value of a random variable can be thought of as a long-run average
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the number of courses a student is taking this semester is an example of a continuous random variable
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when the binomial distribution is used, the outcomes must be dependent
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a binomial experiment has a fixed number of trials
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what is the sum of the probabilities of all outcomes in a probability distribution
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0
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1/2
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1
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it cannot be determined
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how many outcomes are there in a binomial experiment
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the number of trials for a binomial experiment
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can be infinite
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is unchanged
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is unlimited
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must be fixed
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the total area under a normal distribution is infinite
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the standard normal distribution is a continuous distribution
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all variables that are approximately normally distributed can be transformed to standard normal variables
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the z value corresponding to a number below the mean is always negative
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the area under the standard normal distribution to the left of z=0 is negative
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the central limit theorem applies to means of samples selected from different populations
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the mean of the standard normal distribution is
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approximately what percentage of normally distributed data values will fall within 1 standard deviation above or below the mean?
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which is not a property of the standard normal distribution?
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when a distribution is positively skewed, the relationship of the mean, median, and mode from left to right will be?
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mean, median, mode
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mode, median, mean
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median, mode, mean
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mean, mode, median
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the standard deviation of all possible sample means equals
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the population standard deviation
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the population standard deviation divided by the population mean
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the population standard deviation divided by the square root of the sample size
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the square root of the population standard deviation
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Interval estimates are preferred over point estimates since the confidence level can be specified
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for a specific confidence interval, the larger the sample size, the smaller the margin of error will be.
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an estimator is consistent if as the sample size decreases, the value of the estimator approaches the value of the parameter estimated
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to determine the sample size needed to estimate a parameter, you must know the margin of error
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when a 99% confidence interval is calculated instead of a 95% confidence interval with n being the same, the margin of error will be
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smaller
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larger
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the same
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it cannot be determined
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the best point of estimate of the population mean is
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the sample mean
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the sample median
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the sample mode
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the sample midrange
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when the population standard deviation is unknown and the sample size is less than 30, what table value should be used in computing a confidence interval for a mean
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z
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t
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chi-square
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none of the above
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No error is committed when the null hypothesis is rejected when it is false
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when you are conducting the t test, the population must be approximately normally distributed
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the test value separates the critical region from the noncritical region
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the values of chi-square test cannot be negative
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the chi-square test for variance is always one tailed
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when the value of alpha is increased, the probability of committing a type 1 error is
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decreased
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increased
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the same
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none of the above
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if you wish to test the claim that the mean of the population is 100, the appropriate null hypothesis is
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x(bar) = 100
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µ ≥ 100
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µ ≤ 100
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µ = 100
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the degrees of freedom for the chi-square test for variances or standard deviation are
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1
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n
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n - 1
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none of the above
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for the t test, one uses ________ instead of σ
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a negative relationship between two variables means that for the most part, as the x variable increases, the y variable decreases
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a correlation coefficient of -1 implies a perfect linear relationship between the variables
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even if the correlation coefficient is high (near +1) or low (near -1), it may not be significant
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when the correlation coefficient is significant, you can assume x causes y
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it is not possible to have a significant correlation by chance alone
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in multiple regression, there are several dependent variables and one independent variable
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the strength of the linear relationship between two quantitative variables is determined by the value of
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r
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a
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x
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s (subscript "est")
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to test the significance of r, a(n) ____ test is used.
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the test of significance for r has _______ degrees of freedom.
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the equation of the regression line used in statistics is
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x = a + by
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y = bx + a
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y' = a +bx
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x = ay + b
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the coefficient of determination is