Information Pertaining to Exam 1
Basics
It'll be a closed book and closed notes exam. You can use a calculator (not on your phone), but not a computer.
I'll leave room on the exam for you to work the problems, so you won't need to bring paper
or an exam book. All you'll need is a pencil and perhaps a calculator (in addition to a mastery of
the material).
The exam will be composed of 4 problems, having a total of 5 parts. Each of the 5 parts will be worth 25 points, and
I'll sum your best 4 scores from these parts to arrive at your overall exam score.
Click
here to see the instructions for your midterm exam.
For examples of what I mean by defining events in solutions of problems, see the examples on pages 3-11, 3-13, and 3-14 of the
course notes. As for thorough justification in your solutions, if
you go from the probability of an intersection of two events to the product of their two probabilities, you can write ind. over
the = sign to indicate that you're using the independence of the two events, and if
you go from the probability of a union of two events to the sum of their two probabilities, you can write mut. excl. over
the = sign to indicate that you're using the fact that the two events are mutually exclusive.
Similarly, if you use Bayes's formula or one of De Morgan's laws, you can write Bayes or De Morgan over the = sign.
Click
here to see the midterm exam I gave my STAT 346 class in Fall 2022.
Your exam will be somewhat similar,
and so
I suggest that you print a copy and take the Fall 2022 exam (closed book) as practice for this semester's exam.
(Here are solutions to the midterm exam I gave my STAT 346 class in Fall 2022.)
What to Study
The exam will cover Chapters 1, 2, and 3, except for Sections 1.5, 1.6, 1.7, 2.5, 3.6, and smaller parts of the chapters I indicated
(in class or on the Blackboard site) that I'm
skipping. (Note: Even though I covered some of Sections 1.6 and 1.7 in class, you can ignore them for the purpose of this exam.)
Emphasis will be on the main important parts of each chapter. Messy details,
novel
lesser-used results, and somewhat complicated things that I skipped in class (e.g., gambler's ruin example on pp. 102-103) will
not be emphasized. In summary, focus on the material emphasized in class and specified in the guidelines below.
Some really important things (with ultraimportant ones in bold) are:
Chapter 1
- 1st paragraph of Sec. 1.2 (p. 3)
- bold-faced terms on pp. 4-5
- De Morgan's laws on p. 7
- bold-faced relation on p. 7, two lines below
De Morgan's laws
- Axioms of Probability on p. 13
- Theorem 1.1 on p. 13
- Theorem 1.2 on p. 14
- bold-faced result on last line of p. 14
- Theorem 1.3 on p. 16
- Theorem 1.4 on p. 18
- Corollary on p. 18
- Theorem 1.6 on p. 19
- special case of Inclusion-Exclusion Principle for 3 events (in bold face) on p. 20
- Theorem 1.7 on p. 21
Chapter 2
- Theorems 2.1 and 2.2 on pp. 45-46
- Definition on p. 55 and (2.1), (2.2), and (2.3) on pp. 56-57
- Example 2.15 on p. 57
- Theorem 2.4 on p. 58
- Definition on p. 62, and formula pertaining to number of combinatons near the top of p. 63
- Example 2.21 on p. 64
- Examples 2.22 and 2.23 on p. 65
Chapter 3
- Definition on p. 88
- Example 3.7 on p. 91
- (3.4) and (3.5) on p. 97
- Example 3.10 on p. 97
- Theorem 3.2 on p. 98
- Definition on p. 104
- Theorem 3.4 on p. 105 (also see Theorem 3.3 on p. 101)
- Theorem 3.5 on p. 112 (and also see the special case of Bayes' theorem on the bottom portion of p. 112 (in bold face))
- Definition on p. 120
- Theorem 3.6 and Corollary on p. 122
- Definition on p. 125
A half dozen good problems/parts to go over
are:
Problem 7 from HW 1,
Part 1(a) from HW 2,
Problem 2 from HW 2,
Part 3(a) from HW 3,
Part 3(b) from HW 3,
Problem 5 from HW 3.
I also suggest that you take another look at the example on pages 3-13 and 3-14 of the class notes, and also pages 2-24 and 2-25 of the class notes.