In a survey of students in a business statistics class, students were
asked what grade they expected in the course, and also whether
they worked additional problems beyond those assigned by the
instructor. The table gives proportions of students in each o

Chapter 1
Introduction and Data Collection
Statistics
Data Collection Organization Analysis Interpretation Conclusion
Collection of data is the process of obtaining measurements or counts. Valid conclusions
can result only from properly collected data.
Or

Examples:
1. For each of the following situations, indicate whether the priori, empirical, or
subjective approach would be most useful for determining the required probability
value.
a) Probability that a King card is drawn from a well-shuffled deck of ca

Chapter 4
Basic Probability
Key Probability Terms
A random experiment is a process that generates an uncertain outcome.
An outcome is the possible observation received from a random experiment.
An event is a set of one or more outcomes of a random experim

Examples:
1. Set up the probability distribution for the total number of heads obtained in three
tosses of a fair coin and give the probability mass function.
2. Two unbiased dice are rolled.
a) Construct the probability distribution for the sum of the sc

Suggested Solutions
1.
a)
b)
120 90
P( X 120) P Z
P(Z 2) 0.9772
15
112.5 90
90 90
P(90 X 112.5) P
Z
15
15
P(0 Z 1.5)
0.9332 0.5 0.4332
c)
75 90
P( X 75) P Z
P(Z 1) 1 0.8413 0.1587
15
d)
80 90
P( X 80) P Z
P(Z 0.67) 0.7486
15
e)
2.
110 90

Chapter 5
Discrete Probability Distributions
Random Variable
A random variable is a variable (typically represented by capital letter X) that has a single
numerical value, which is determined by chance, for each outcome for a random
experiment.
A discret

Examples:
1. An orange juice producer buys all his oranges from a large orange orchard. The
amount of juice squeezed from each of these oranges is assumed to be normally
distributed with a mean of 4.70 ounces and a standard deviation of 0.40 ounce.
Suppos

Chapter 2
Presenting Data in Tables and Charts
Example: The following is a data set containing the hourly wages for each of the 50
workers.
83
65
44
38
91
51
87
55
88
71
66
68
78
76
83
61
64
69
99
80
82
51
98
84
68
65
70
67
47
65
54
75
82
60
51
56
66
77
4

QMDS200 STATISTICS AND DATA ANALYSIS
Assignment # 2
Suggested Solutions
1.
Textbook, Problem 5.7, p.207.
Let X = the anticipated annual return for a $1,000 investment in stock X
Let Y = the anticipated annual return for a $1,000 investment in stock Y
a) E

QMDS200 STATISTICS AND DATA ANALYSIS
Assignment # 1
Suggested Solutions
1.
Textbook, Problem 1.5, p.34.
a)
b)
c)
d)
2.
numerical, continuous
numerical, discrete
categorical
categorical
Textbook, Problem 1.25, p.39.
a) The population of interest was the 2,

Chapter 2
Organizing and Visualizing Data
Example: The following is a data set containing the hourly wages for each of the 50 workers.
83
65
44
38
91
51
87
55
88
71
66
68
78
76
83
61
64
69
99
80
82
51
98
84
68
65
70
67
47
65
54
75
82
60
51
56
66
77
42
56

Chapter 6
The Normal Distribution
Probability Distributions with Continuous Random Variable
For continuous random variables, the possible values (with corresponding probabilities)
cannot be listed. Instead of listing all possible values, a continuous prob

QMDS200 STATISTICS AND DATA ANALYSIS
Assignment # 3
Please put the course code, course title, student submission number, student name, and student
number on the top left corner of the first page.
In order to obtain full marks, please show all calculatio

QMDS200 Statistics and Data Analysis
Assignment # 1
Deadline:
For Sections 001 and 002: 12 October 2015 (Monday)
For Sections 003, 004 and 005: 9 October 2015 (Friday)
Please submit your assignment in class.
Please put the course title, student submissio

QMDS200 STATISTICS AND DATA ANALYSIS
Assignment # 3
Deadline: November 17, 2015 (Submit in class)
Please put the course code, course title, student submission number, student name, and
student number on the top left corner of the first page.
In order to

QMDS200 Statistics and Data Analysis
Assignment # 2
Deadline:
For Sections 001 and 002: 22 October 2015 (Thursday)
For Sections 003, 004 and 005: 20 October 2015 (Tuesday)
Please submit your assignment in class.
Please put the course title, student submi

1.7 For each of the following variables, determine
whether the variable is categorical or numerical. If
the variable is numerical, determine whether the
variable is discrete or continuous. In addition,
determine the measurement scale for each
variable.
a.

Chapter 3
Numerical Descriptive Measures
Any set of data can be characterized by measuring its central tendency, variation and
shape.
Measures of Central Tendency
the extent to which all of the data values group around a central or typical value.
1. Arith

Chapter 7
Sampling and Sampling Distributions
Sampling Concepts
Sample statistics are used to make inferences (estimates or decisions) about unknown
population parameters. Typical of what we mean by statistic are the sample mean
and the sample proportion.

Chapter 6
The Normal Distribution
Probability Distributions with Continuous Random Variable
For continuous random variables, the possible values (with corresponding
probabilities) cannot be listed. Instead of listing all possible values, a continuous
prob

Chapter 7, Sample Distribution
A sampling distribution is a distribution of all of the possible values
of a statistic (say sample mean) for a given size sample selected from
a population.
Sample Distribution of the Mean is an
Unbiased Estimate of the Po

Chapter 7 Sampling and Sampling Distributions
Slide 1
Learning objectives
1. Understand Simple Random Sampling 2. Understand Point Estimation and be able to compute point estimates 3. Understand Sampling Distribution of x 4. Understand Sampling Distributi

Examples:
1. The following is a sample of 10 observations consisting of:
5
5
5
3
1
5
1
4
3
5
Determine the mean, median, and mode for these data.
2. The following table shows the number of machine breakdowns per day in the
engineering plant during a perio

Examples:
1.
a) P(X 120 = 90, = 15)
b) P(90 X 112.5 = 90, = 15)
c) P(X 75 = 90, = 15)
d) P(X 80 = 90, = 15)
e) P(80 < X < 110 = 90, = 15)
2.
The produce trucks which arrive at the Ptomaine Tavern distribution centers carry a
mean weight of 6,400 pounds of