Deck 6: Probability, Probability Distributions, and an Introduction to Inferential Statistics

Question 1

Probability would fall into the class of ______.

A) descriptive statistics
B) inferential statistics
C) causal statistics
D) generalizability statistics

Answer 1

B

Question 2

Probability can be defined as ______.

A) the number of times a specific even can occur relative to the total number of times that any event can occur
B) the total number of possible outcomes minus the number of ways a particular outcome may occur
C) the total number of ways a possible outcome can occur
D) the likelihood that the researcher would reject the null hypothesis

Answer 2

A

Question 3

The bounding rule of probabilities state that ______.

A) probabilities can be less than zero
B) probabilities can be greater than one
C) probabilities can be both less than zero and greater than one
D) probabilities can never be less than zero and greater than one

Answer 3

D

Question 4

The complement of an event is ______.

A) the set of all outcomes that are not the event of interest
B) the set of all outcomes that are and are not the event of interest
C) an event that is very similar to the event of interest
D) works alongside the event of interest

Question 5

When the joint probability of two events occurring is zero, the two events are said to be ______.

A) mutually exclusive
B) complementary
C) restrictive
D) additive

Question 6

The restricted addition rule of probabilities relates to ______.

A) determining the number of different ways a particular outcome can occur
B) the probability of either of two mutually exclusive events occurring is equal to the sum of their separate probabilities
C) the fact that the probability of an event occurring is between 0 and 100
D) the probability of two non-mutually exclusive events occurring is equal to the sum of their separate probabilities

Question 7

The following equation, $P(A \text { or } B)=P(A)+P(B)$ , represents ______.

A) conditional probability
B) restrictive multiplication rule of probabilities
C) restrictive addition rule of probabilities
D) general addition rule of probabilities

Question 8

Which rule of probability states that for two non-mutually exclusive events the probability of each event occurring is equal to the sum of their separate probabilities minus the probability of their joint occurrences?

A) bounding rule of probabilities
B) restricted addition rule of probabilities
C) general addition rule of probabilities
D) restricted multiplication rule of probabilities

Question 9

The following equation, $P(A \text { or } B)=P(A)+P(B)-P(A \text { and } B)$ , represents ______.

A) conditional probability
B) restrictive multiplication rule of probabilities
C) restrictive addition rule of probabilities
D) general addition rule of probabilities

Question 10

The question "What is the probability of a child being in school or the child offending?" is an example of ______.

A) general multiplication rule of probabilities
B) restrictive multiplication rule of probabilities
C) restrictive addition rule of probabilities
D) general addition rule of probabilities

Question 11

Which rule of probability states that for two mutually exclusive events the probability of each event occurring is equal to the product of their separate probabilities?

A) bounding rule of probabilities
B) restricted addition rule of probabilities
C) general addition rule of probabilities
D) restricted multiplication rule of probabilities

Question 12

The following equation, $P(A \text { and } B)=P(A)^{*} P(B \mid A)$ , represents ______.

A) general multiplication rule of probabilities
B) restrictive multiplication rule of probabilities
C) restrictive addition rule of probabilities
D) general addition rule of probabilities

Question 13

A binominal distribution has a variable that ______.

A) consists of three categories
B) consists of only one category
C) consists of multiple categories
D) consists of two categories

Question 14

The following equation. $P(r)=\left[\frac{n !}{r !(n-r) !} p^{r} q^{n-r}\right]$ , can be used to determine the probability of any number of successes, r, so long as there are only two outcomes-success(p) and failure(q). This is also called the ______.

A) probability theorem
B) binomial theorem
C) proportion theorem
D) probability distribution theorem

Question 15

When testing the null hypothesis a researcher begins with the assumption that ______.

A) the researcher can prove the null hypothesis is false
B) the researcher can prove the alternative hypothesis is false
C) the alternative hypothesis is true
D) the null hypothesis is true

Question 16

The risk we take in rejecting a true null hypothesis is called ______.

A) significance or alpha ( α)
B) assumption of null hypothesis
C) statistical power
D) type II error

Question 17

If an infinite number of random samples of size n are drawn from any population with mean µ and standard deviation σ, then as the sample size (n) becomes large, the sampling distribution of sample means will approach normality even if the population distribution is not normally distributed is known as the ______.

A) central limit theorem
B) normal distribution
C) sampling distribution
D) standard normal probability distribution

Question 18

Events that have only two possible outcomes are called Bernoulli Events

Question 19

For every normal distribution, .3413 (34.13%) of the are under the curve lies between the mean and a point that is one standard deviation either to the right or the left of the mean.

Question 20

For every normal distribution, .6826 (68.26%) of the are under the curve lies between the mean and a point that is one standard deviation to the right and one standard deviation to the left of the mean.

Question 21

For every normal distribution, .9544 (95.44%) of the are under the curve lies between the mean and a point that is two standard deviations to the right and two standard deviations to the left of the mean

Question 22

In a normal distribution, a z-score of at least $\pm$ 1.96 is indicative of a rare event because it occurs 5% of the time or less

Question 23

The larger a sample is the more imprecise the estimates are.

Question 24

For every normal distribution, .9974 (99.74%) of the are under the curve lies between the mean and a point that is three standard deviations to the right and is three standard deviations to the left of the mean

Question 25

State and describe the three characteristics of the sampling distribution of the mean based on the Central Limit Theorem