Question

1. When using inferential statistics, it is critical to have:

   		More than one degree of freedom.
   		A truly random sample of the population.
   		A binomial random variable
   		A strong correlation with a Poisson distribution.
   		A normally distributed population.

1. The three ways of assessing probabilities are:

   		Classical, Empirical, and Subjective
   		Normal, Poisson, and Hypergeometric
   		Type I, Type II, and Secular
   		Binomial, Geometric, and a priori
   		Global test, Histogram, and Stepwise

1. If there are three, equally-likely events, the probability of each event occurring is:

   		unable to be determined.
   		1/3.
   		Greater than 1.
   		Only found by hypothesis testing.
   		The total divided by the square root of the events.

1. A probability is:

   		Always less than zero.
   		Can never be less than 1.
   		Will always be negative.
   		Will always be between 0 and 1, inclusive.
   		Sometimes calculated by the square root of the mean.

1. To be 95% confident in a hypothesis test, the significance level:

   		Means it is a two-tailed test.
   		Must be one less than the sample size.
   		Is the p-value.
   		Will be a t-value rather than a z-value.
   		Will be (1 – 0.95) or 0.05.

1. If the significance level of a hypothesis test is 0.01 and the p-value is 0.032:

   		We reject the null hypothesis and have evidence the alternate hypothesis is true.
   		The result is inconclusive
   		The probability of a success is 0.032 – 0.01 or 0.022.
   		We do not reject the null hypothesis and accept it to be true.
   		We accept both the null and alternate hypotheses.

1. When running a hypothesis test with 99% confidence, the significance level, 0.01 is:

   		You reject the null hypothesis, but the null hypothesis is true.
   		The alternate hypothesis is accepted, but the null hypothesis is true.
   		The alternate hypothesis is true, but the null hypothesis is not rejected.
   		Neither the null nor the alternate hypothesis is true.
   		Both the null and the alternate hypotheses are rejected.

1. The probability of a Type II error is directly related to ____________.

   		α
   		the standard deviation
   		the Type I error
   		the difference between the hypothesized mean and the critical value of the sample mean
   		r-squared

Answer 1