CHAPTER 1 EXERCISES
1. If a coin is fair, then heads and tails should have equal chance of
occurring.
a. Test the fairness of a coin by flipping it 10 times.
b. Test the fairness of the same coin by flipping it 50 times.
c. If heads and tails never reach 50-50 rate of occurrence, does
this mean that the coin is unfair? Explain.
No matter how many tosses you do, the coin remains
fair, because the expected occurrence of head and tail is 50-50
%. This simply indicates that the probability is binomial and
mutually exclusive and no other values will come out each
time the coin is tossed. If ever the total occurrence of being a
head of a tail does not reach a 50-50 chance, it is because the
event is caused by chance and the probability of having equal
number of occurrence or probability of success or failure is
dependent on other factors. The 50-50 rate is but an
expected event or sample size when tossing the coin. An
expectation even in real life does not always hold true.
2. What is the difference between a population and a sample?
The population is the entire group of individuals that
we want information about.
The sample is a subset of a population that we actually
examine in order to gather information. Since it is usually,
impractical to test every member of a population, a sample
from the population is typically the best approach available. It
should consider the following;
a. Must be collected randomly as far as possible.
b. Must be independent – collection or measurement of
one observation should effect the value of any other.
c. Must be large enough sample size (or replication) to be
truly representative – this is why we say “ 5 is good,
but 8 would be better, 10 or more is excellent” – and
not fall to chance variation.
d. “good” sample sizes depend on the study.
e. For ecology and other field studies, often easy to
collect hundreds of measurements quickly.
Lab experiments sometimes 5 replications is terrific
and perhaps all that is feasible.
3. How can the concepts of population and sample relate to
deductive reasoning and inductive reasoning?
Sample and population are two important basis of
conclusion or reasoning. There are two types of reasoning: a)
deductive reasoning makes reason out of a given general
knowledge or population such that what is true to general
population will also be true to a sample.
Deductive / Probability
Inductive / Statistics
Deductive:
population
sample
general
specific



Probability
In deductive reasoning, thinking proceeds from general
assumption to specific application
General and Specific
Aristotle and other early philosophers
o Drawing conclusions through categorical
syllogism
o All philosophers are moral. Socrates is a
philosopher. Therefore, Socrates rates is
moral.
o Resistance training makes one big and bulky
increasing body mass. Sandi is resistance

training. Therefore, Sandi will become big and
bulky.
Not sufficient as a source of new truth.
All mammals have lungs. A rabbit is a mammal.
Therefore, a rabbit has lungs.
Inductive:
sample
population
specific
general
Statistics
Example: if you take a poll and note the voting
preferences of this sample, we will be able to draw some
conclusions about the votes of the population
 Conclusions about event ….

Every rabbit that has been observed has lungs.
Therefore, every rabbit has lungs.
4. A newspaper article reports that “this morning’s demonstration
was attended by 8437 students.” Comment.
The news report has specifically mentioned the actual
head count of student attendees in the demonstration.
However, if the newspaper account is not based on actual
count, the figure given might be a wrong representation if it is
only based on estimate. It could mean that the newspaper
account could be attributed to the number of registrant that is
actually recorded on paper which means that the actual
number of demonstrator could be lesser or greater in number
but because the number was on record the account was used.
5. A college conducts a survey of its alumni in an attempt to
determine their median annual salary. Would alumni with very
low salaries be likely to respond? How would this affect the
result? Identify some other factors that might affect the result.
Alumni with low salaries may or may not likely to
respond in the survey depending on the situation, manner of
conducting the survey and reason for the conduct of survey.
The median may not be affected should they respond or not.
Median measures the middle value. It is better measure for
populations with possibly wide variations.
6. What differences are there between the following two
statements, and which one do you believed is more accurate/
a. Drunken drivers cause more than half of all fatal car crashes.
b. Of all fatal motor vehicle crashes, more than 50% involve
alcohol.
Between the two statements, I consider the first
statement to be more accurate and precise. It has definitely
and specifically stated that what causes more than half the
fatal car crashes are drunken drivers; unlike in the second
statement, fatal motor vehicle crashes were attributed to
anything that involved alcohol but not necessarily and
specifically identified as drunken drivers.