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Week 4 Concepts
Week 4 Concepts
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#MCD2080 #statistics #business #quiz #week4
Flashcards
27 cards
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Practice quiz
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Questions
27
Answers
1
If the z score of
X
~N(µ= 50, σ
2
= 25) is 2, then the x score is
x = 55
x = µ + z𝞼 = 60
x = µ + z𝞼 = 52
x = 50
2
Let p=0.30, n = 10, Find P(X is no more than 2)
0.3828
0.8497
No idea!
0.6496
3
The probability of a given customer being an international traveller and flying economy is
26/150
47/150
52/150
25/150
4
Probability can best be described as
A BBQ utensil
The chance, likelihood, possibility of an event will occur
The meaning of life
Link between Descriptive and Inferential statistics
5
A Random Variable can be
Continuous only
Either Discrete or Continuous
Impossible to determine
Discrete only
6
Given that p is probability of success, how does one calculate the mean E(X) for the binomial?
E(X) = n - p
E(X) = n + p
E(X) = n * p
E(X) = p
7
Let p=0.05, n = 10, Find the P(X is at least 2 or more)
1 - 0.9885 = 0.115
0.9885
No idea!
1 - P(X is at least 1 or less) = 1 - 0.9139 = 0.0861
8
The Expected Value or E(X) can be found by
Guessing
0+1+2+3+4
0.05+0.15+0.25+0.45+0.10
(0*0.5)+(1*0.15)+(2*0.25)+(3*0.45)+(4*0.10)
9
X
~N(µ= 50, σ
2
= 25) has a mean of
50
25
none
5
10
To calculate the z score of a given x score for a Normal random variable X, use
z = x - µ/𝞼
x = µ + z𝞼
z = (x - µ)/𝞼
x = (µ + z)𝞼
11
If the z score of
X
~N(µ= 50, σ
2
= 25) is 2, then the x score is
x = µ + z𝞼 = 52
x = µ + z𝞼 = 60
x = 55
x = 50
12
Which one(s) is/are a Discrete probability distribution
Chi-Squared
Binomial
Uniform
Gaussian (Normal)
13
The most distinguishable feature of The Binomial Distribution is
It is a Continuous Probability Distribution
It is a Discrete Probability Distribution
It has only TWO possible outcomes (p=success, 1-p = failure)
It is Gender neutral
14
In the accompanying diagram, what are the z scores of x = 31 and x = 21?
-2 and -1
none
2 and 1
1.5 and -1.0
15
If P(X=0) = 0.05; evaluate P(X=2)
0.10
0.05
0,20
0.25
16
A Random Variable is
A mystery number
A variable that randomly appears out of nowhere
A numerical description of outcomes of an event (experiment)
Someone who sleeps-walk randomly at night
17
What is P(X>1)?
0.20
0.5
0.80
0.05
18
If X
~N(µ= 25, σ
2
= 16) , then The probability of
X
≤ 29 equals
The probability of Z < (29 - 25)/4 = 0.8413
The probability of Z = 1
The probability of Z = (29 - 25)/4 = 0
The probability of Z < (29 - 25)/16 = 0.5987
19
Let p=0.10, n = 10, Find P(X ≤ 1)
0.7361
0.9139
0.3487
0.5987
20
Let p=0.50, n = 10, Find P(X ≤ 2)
0.0547
0.001
0.9453
0.1719
21
The probability of a given customer being a domestic traveller and not flying economy class is
52/150
25/150
26/150
47/150
22
What is P(0<X<4)?
0.05
0.85
0.75
0.50
23
Probability is a numeric value that is between
0-1
1-100
-infinity to +infinity
0-3
24
Together
, µ and 𝞼 fully determine a Normal Distribution
True
Never
Sometimes
False
25
If the z score of
X
~N(µ= 50, σ
2
= 25) is 2, then the x score is
x = µ + z𝞼 = 60
x = 55
x = µ + z𝞼 = 52
x = 50
26
If p is probability of success, how does one calculate the variance, V(X) for the binomial?
V(X) = n + p + (1-p)
V(X) = n+p
V(X) = n p ( 1-p)
V(X) = n p
27
The number of BMWs sold from a car-yard can be best seen as
An unexpected phenomenon
Continuous random variable
A mixture of Discrete and Continuous
Discrete random variable
