Probability Flashcards

1
Q

What is Continuous Probability Distribution?

A
  • probability distribution in which random variable X takes on any value + describes it {P(X = x) = 0}
  • uses probability density function
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What is the discrete probability distrubution?

A

probability distribution counts occurrences that have countable or finite outcomes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What are the features of a continuous distribution?

A
  • normal distribution
  • Uni-modal & symmetrical
  • extreme values away from centre
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What is the standard normal distribution for continuous distribution probability?

A

σ = 1, μ = 0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What happens when the mean is changed on a normal distribution?

A

The curve changes where it is centred on the x-axis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What happens when the standard deviation is changed on a normal distribution?

A

Adjusting σ changes the shape of the curve

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

List the properties of a normal distribution

A
  • 68% -> 1 SD either side of mean
  • 95% -> 2 SD either side of mean (1.96 exactly)
  • 99.75% -> under 3 SD but extremely rare
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What are the 3 properties of sampling distribution?

A
  • variability in sample estimates
  • higher sample size = less variable in samples -> more representative sample
  • larger samples = point-estimate from samples are closer to population value
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What is the difference between a smaller and larger standard error?

A

Large standard error = more distributed
Small standard error = grouped in one area; it’s closer to the population parameter

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What happens when the number of samples increase?

A
  • sampling distribution becomes normal
  • samples x̄s pile around µ
  • the SE of sampling distribution becomes narrower
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What is the central limit theorem?

A

Taking large samples from a population, the sample mean will be normally distributed even if the population isn’t

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What is analytic probability?

A
  • Probability of event equal to ratio of successful outcomes to all possible outcomes
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is the law of large numbers?

A
  • larger the number the more proportion represents ground truth, representing the world
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is the range probability rule and what does it mean?

A
  • probability of any event falls between 0 and 1
  • P(A) approaches 1 means more likely to occur
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What is the Sum of outcomes probability rule and what does it mean?

A
  • Sum of probabilities of all possible outcomes = 1
  • all sample includes all possible outcomes of experiment so some outcomes must occur
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What is the complement rule probability rule and what does it mean?

A
  • Probability of A^c(NOT A) =1- probability of A
    -
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

What is the Simple addition rule probability rule and what does it mean?

A
  • Probability one or both events occur
  • adding probability of one event to another
  • used for mutually exclusive events as can’t coexist together
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What is the general addition rule probability rule and what does it mean?

A
  • Probability one or both events occur when events not mutually exclusive
  • Also used when events are mutually exclusive -> probability both occur together is 0
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

What is the multiplication rule probability rule and what does it mean?

A
  • Probability of intersection of A and B if they are independent events.
  • Probability of A and B always less than or equal to the probability of either single events
20
Q

What is the conditional probability rule and what does it mean?

A
  • The probability of one of the other happens
  • Multiply probability of A with the probability of B given A
21
Q

What is the conditioned probability?

A

Probability of B given A
- events are dependent on likelihood of one event changing based on the outcome of the other event

22
Q

What is the difference between the conditioned probability and multiplication rule?

A
  • When A and B are independent P(B|A) = P(B) is the simple multiplication rule BUT

conditioned probability when A and B are dependent

23
Q

What is Bayes’ rule?

A
  • Calculating conditional probabilities when intersection unknown
  • Follow on from conditioned probability
  • Allows update assessment of probability as more evidence gathered
24
Q

What is a sample space?

A

All possible outcomes

25
Q

What is a simple event?

A

singular event

26
Q

What are discrete distributions?

A
  • mapping values of random variables to probability of it occurring
  • range of p across variables
27
Q

What is the probability mass function?

A
  • probability each discrete random variable exactly equals specific value
28
Q

What does this mean f(x)= P(X= x)

A

X = random variable
x = specific event in X

29
Q

What is the process of the probability mass function?

A
  1. Sum frequencies
  2. Divide frequency of each outcome by total frequency
  3. Provided with discrete probability distribution
30
Q

What are the characterisitcs of binomial distributions?

A
  • two outcomes: success or failure
  • fixed number of observations
  • observations are independent
  • probability of success same as each observation
31
Q

What is the interest in binomial distributions?

A

number of successes given a fixed number of trials

32
Q

What is the cumulative probability function?

A

Total probability of all values before or after a given point
Sums the probability of individual outcomes

33
Q

What is the difference between continuous probability distribution vs. discrete probability distribution?

A

Discrete: describes random variables producing discrete set of outcomes vs. continuous describes random variable producing continuous set of outcomes.

34
Q

What is used to describe continuous distributions?

A

Probability density function

35
Q

What is used to describe discrete density functions?

A
  • Probability mass function
  • Binomial distribution
36
Q

What change occurs when the mean is changed on a normal distribution?

A

changing the mean changes where the curve is centred on x-axis

37
Q

What change occurs when the standard deviation is changed on a normal distribution?

A

changes the shape of the curve
- Higher SD = flatter curve
- Lower SD = higher curve

38
Q

What do continuous random variables tell us?

A

Probability of a range of scores occuring

39
Q

What is needed for the value under the curve for continuous distribution?

A

the integral and probability density function

40
Q

Why are z-scores used?

A
  • present normal distribution
  • standardise the value of x
41
Q

What is a point-estimate?

A
  • sample value of variable of interest
42
Q

What is a population parameter?

A
  • population value of variable of interest
43
Q

What is a sample?

A
  • subset of population to collect data to make inference
44
Q

What is a sampling distribution?

A

probability distribution of stats obtained from sampling population repeatedly

45
Q
A