EDA MIDTERM

Question 1

branch of mathematics that provides tools and methods for calculating and analyzing probabilities.

Answer 1

Probability

Question 2

A probability of 0 means the event is ______________, while a probability of 1 (or 100%) means the event is ___________.

Answer 2

• impossible to occur
• certain to happen

Question 3

It’s a numerical value, typically ______________, or expressed as a percentage, fraction, decimal point, and ratio representing the chance of an event happening.

Answer 3

Between 0 and 1

Question 4

It is distinct from certainty.

Answer 4

Probability

Question 5

means clearly different

Answer 5

Distinct

Question 6

means impossible or guaranteed.

Answer 6

Certainty

Question 7

A probability of 0 or 1 (or 0% or 100%) represents ___________, while all other values indicate varying degrees of likelihood.

Answer 7

certainty

Question 8

Formula in Solving Probability:

Answer 8

P = Total number of possible outcomes/ Total number of sample space

Question 9

This refers to any process with an uncertain outcome.

Answer 9

Random Experiment

Question 10

It is the set of all possible outcomes of a random experiment.

Answer 10

Sample space

Question 11

Example of Random Experiment

Answer 11

flipping a coin
rolling a die
drawing a card from a deck

Question 12

Each individual result of the experiment is an _______.

Answer 12

Outcome

Question 13

The sample space is the collection of all possible outcomes, often represented as a set, using

Answer 13

curly braces { }

Question 14

The probability of drawing or related to playing a card or collection of cards from a deck is called

Answer 14

Card Probability

Question 15

The sum of the probabilities for all possible outcomes must equal to _.

Answer 15

1

Question 16

It is another term for the discrete probability distribution, especially when expressed as a function.

Answer 16

Probability Mass Function (PMF)

Question 17

It is a ________ or ______ that lists the probabilities for each outcome of the random variable, X (capital x).

Answer 17

Table or formula

Question 18

is a probability distribution that deals with the countable outcomes.

Answer 18

Discrete probability distribution

Question 19

Types of discrete probability distributions:

Answer 19

Binomial Distributions
Poisson Distributions
Bernoulli Distribution
Discrete Uniform Distribution

Question 20

It is the branch of mathematics where we determine how likely an event is to occur.

Answer 20

Probability

Question 21

Probability can be calculated as:

Answer 21

Probability = FavorableOutcome/ TotalNumberofOutcomes

Question 22

Itrepresents the complete set of possible results an event can produce.

Answer 22

Total Number of Outcomes

Question 23

Itrefer to the outcome we are interested in.

Answer 23

Favorable Outcomes

Question 24

It describes the probabilities of a continuous random variable, which can take any value within a given range.

Answer 24

Continuous probability distribution

Question 25

is a variable that can take on any value within a given range.

Answer 25

Continuous Random Variable

Question 26

Common types of Continuous Probability distributions:

Answer 26

1. Normal 2. Exponential 3. Uniform

Question 27

It models the probability of a certain number of successes in a fixed number of independent trials, where each trial has only two possible outcomes (e.g., success or failure).

Answer 27

Binomial Distribution

Question 27

Continuous probability distributions are represented by a _____________, which describes the likelihood of the random variable falling within a specific range of values.

Answer 27

Probability Density Function (PDF)

Question 28

It looks like a symmetric bell looking thing. It is often called a bell curve.

Answer 28

Normal Distribution

Question 29

Between plus or minus one standard deviation, there is ___ of the distribution’s data.

Answer 29

68%

Question 30

Between plus or minus 3 standard deviations, there is of ____ the data.

Answer 30

99.7%

Question 31

Between plus or minus 2 standard deviations, there is of ___ the data.

Answer 31

95%

Question 32

It is the most popular distribution because it can be used for so many types of real-world applications.

Answer 32

Normal continuous distribution

Question 33

is a standardized value describing a score's location within a distribution, its distance from the mean in standard deviation units, and its sign.

Answer 33

z-score

Question 34

Formula of Z-score:

Answer 34

Z = (x - μ) / σ X = data points or raw score μ = mu symbol σ = standard deviation symbol (sigma)

Question 35

Why we standardize data for normal distributions?

Answer 35

Standardizing data can enhance data quality and accuracy, which helps users make reliable data-driven decisions

Question 36

Calculating Probability for Normal Distribution:

Answer 36

To calculate probability for normal distribution, instead of using formulas, we have to rely on using charts or tables.

Question 37

It is a type of probability distribution in which every outcome in a given range is equally likely to occur.

Answer 37

Uniform probability distribution

Question 38

It is also known as rectangular distribution.

Answer 38

Uniform probability distribution

Question 39

Every value within the range (a, b) has the same probability of occurring.

Answer 39

Equal Probability

Question 40

Defined by two parameters:

Answer 40

'a' (minimum value) 'b' (maximum value)

Question 41

It is constant within the range (a, b) and zero outside it. It is often referred to as a rectangular distribution.

Answer 41

Probability Density Function (PDF)

Question 42

The formula for the PDF is:

Answer 42

f(x) = 1/(b-a)

Question 43

Types of Uniform Distribution

Answer 43

•Discrete Uniform Distribution •Continuous Uniform Distribution

Question 44

It is a function that gives the probability that a discrete random variable is exactly equal to some value

Answer 44

Probability Mass Function (PMF)

Question 45

It describes the probability distribution of a discrete random variable.

Answer 45

Probability Mass Function (PMF)

Question 46

PDF mean

Answer 46

probability density function (PDF)

Question 47

probability distributions where the probability density function (PDF) is constant