Biostatistics III definitions

Question 1

a random event is something unpredictable

Answer 1

random event

Question 2

a random variable is a numerical measurement of outcomes of a random event.

Answer 2

Random Variable (RV)

Question 3

any measurement that can have different values across individuals and can have values that are labels or numbers?

Answer 3

variable

Question 4

when a RV is equal to a certain value.

Answer 4

event

Question 5

the likelihood or chance that an event will occur, expressed as a number from 0 to 1.

Answer 5

probablility

Question 6

gives the probabilities that the variable equals each possible values.

Answer 6

discrete random variable

Question 7

takes on infinite number of possible values, area under a smooth curve gives the probability.

Answer 7

continuous random variable

Question 8

this distribution has one mode?

Answer 8

unimodal distribution

Question 9

this distribution has two modes?

Answer 9

bimodal distribution

Question 10

name this skewed distribution from the following description?

Tail to the left
Mean

Answer 10

Negative (Left) Skewed Distribution

Question 11

name this skewed distribution from the following description?

Tail to the right
Mean>Median>Mode

Answer 11

Positive (Right) Skewed Distribution

Question 12

when the mean is greater than median and mode? this is what type of skewed distribution

Answer 12

positive skewed distribution

Question 13

when the mean is lesser than median and mode? this is what type of skewed distribution

Answer 13

negative skewed distribution

Question 14

this type of distribution is commonly used for continuous RVs(e.g., height, weight, blood pressure).

A large number of statistical tests and calculations can be used if the test statistic follows a normal distribution.

Answer 14

normal distribution

Question 15

what is normal distribution shaped like?

Answer 15

bell shaped curve

Question 16

this type of distribution is more spread out than the standard normal distribution.

Answer 16

t Distribution

Question 17

the parameter for certain distributions (such as t, F, and chi-square distribution)

Answer 17

degrees of freedom

Question 18

for normal distribution what is the term for the following definition?

symmetric and unimodal (bell-shaped)

Answer 18

Shape

Question 19

for normal distribution what is this definition?

possible values): (-∞,+∞

Answer 19

Support

Question 20

for normal distribution what is this definition?

μ denotes the mean and 𝜎^2 denotes the variance.

Answer 20

Parameters

Question 21

for normal distribution what is this definition?

when X is normally distributed with mean μ and variance 𝜎^2, then we write as 𝑋~𝑁 (𝜇, 𝜎^2)

Answer 21

Notation

Question 22

for normal distribution what is this definition?

if μ=0 and 𝜎^2=1, we have standard normal distribution, written as Z~𝑁 (0,1)

Answer 22

Special cases

Question 23

for normal distribution, the lower pth percentile for Z is denoted by?

Answer 23

zp.

Question 24

indicates the value below which a given percentage of observations fall.

Answer 24

percentile

Question 25

this is the term for the following definition of a binomial distribution property? Symmetric, Skew Left, Skew Right - depending on the value of parameters

Answer 25

shape

Question 26

this is the term for the following definition of a binomial distribution property? (possible values): 0, 1, 2, …, n

Answer 26

support

Question 27

this is the term for the following definition of a binomial distribution property? n denotes number of trials and p denotes the probability of “success” on each trial

Answer 27

parameters

Question 28

this is the term for the following definition of a binomial distribution property? If X counts the number of successes among n trials where each trial has a probability of “success” equals p, and X is binomially distributed, then we write X ~Bin(n, p)

Answer 28

notation

Question 29

this is the term for the following definition of a binomial distribution property? if n=1, we have the Bernoulli distribution and we write X ~ Ber (p)

Answer 29

special cases