probability distribution

Question 1

it applies the theory of probability to describe the behavior of the random variable

Answer 1

probability distribution

Question 2

determines the probability associated using either a graph or a mathematical formula.

Answer 2

continuous

Question 3

specifies all possible outcomes of the random variables along with the probability that each will occur.

Answer 3

discrete

Question 4

calculated from a finite amount of data.

Answer 4

empirical probabiliity

• is the likelihood of an event happening based on actual data or past experiences. Instead of theoretical predictions, it uses real-world observations to calculate how often something occurs. For example, if you flip a coin 100 times and it lands on heads 55 times, the empirical probability of getting heads is 55/100, or 55%.

It’s like saying, “Based on what we’ve seen happen before, this is how often we expect it to happen again.”

Question 5

distribution of many other variables of interest based on theoretical considerations.

Answer 5

theoretical probability

Question 6

can take on one of two values of the variables

Answer 6

binomial distribution
failure = 0
success = 1

Question 7

what does it mean if in binomial distribution , the outcomes are exhaustive

Answer 7

it is the complete coverage, all possible outcomes/ results f an experiment or scenario are accountable for = complete and accurate

Question 8

When the distance of an event X is very rare and is dwarfed by the total population,

Answer 8

poisson distribution

Question 9

poisson distribution is aka

Answer 9

distribution of rare events

Question 10

which distribution is continous and discrete

Answer 10

continuous - normal distribution
discrete - binominal and poisson

Question 11

what happens as the number of possible values approaches infinity and the intervals between them approach zero

Answer 11

the curve is more smooth and continuous

Question 12

gaussian curve and bell curve is aka

Answer 12

bell shape curve or simple bell surge

*it is the common continous distribution

Question 13

explain why the gaussian curve does not touch both ends

Answer 13

as they have outliers

Question 14

A smooth curve is used to represent the probability distribution of a continuous random variable

Answer 14

probability density

*probability are represented by the area under the curve ratheer than the individual points

Question 15

it shows the likelihood of different values occurring within the distribution

Answer 15

probability density function
(it is the curve itself)