Normal Distribution - [Statistics 2]. Flashcards

1
Q

How do you write a Normal Distribution?

A

X~N(μ, σ2).

μ = Mean.
σ2 = Variance.

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

What shape is a Normal Distribution Graph?

A

A Bell-Shaped Curve where there is the largest area in the middle and smallest sections on the outside.

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

What percentage of values lie within 1 standard deviation of the mean?

For a Normal Distribution?

What else lies 1 S.D away from the mean?

A

2/3 (67%).

Points of Inflection.

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

What percentage of values lie within 2 standard deviation of the mean?

A

95%.

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

What percentage of values lie within 3 standard deviation of the mean?

A

99.8%.

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

How do you calculate x̄ from ∑x, ∑(x-x̄)2 and n?

A

x̄ = ∑x / n.

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

How do you calculate the Standard Deviation from ∑x, ∑(x-x̄)2 and n?

A

S.D = √(∑(x-x̄)2) / n.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What things do you need to write to explain why you can use a Normal Distribution?

A
  • The Data is Symmetrical.
  • The Data is Continuous.
  • Most of the Data lies in the middle.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What equation allows you to Standardise the vales of X to Z?

A

Z = X - μ / σ.

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

If P(Z < z) = 0.5, what is the Area, Tail, μ and σ to use in InvN, given that Z~N(0, 12)?

A
  • Area = 0.5.
  • Tail = Left Tail.
  • μ = 0.
  • σ = 1.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

If σ2 = Variance, then what does Standard Deviation equal?

A

S.D = σ = √σ2 = √Variance.

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

When can a Normal Distribution be used to approximate a Binomial Distribution?

A
  • When ‘n’ is large (n ≥ 20) and p ≈ 0.5.
    OR
  • np ≥ 5 and n(1-p) ≥ 5.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly