
Math 365 : Elementary Statistics
Course Description and Organization
Online Spring 2023 Course (Class No. 45282)
Course Materials
 The Testbook: The Book.
 Homework:
The HW Exercises,
The Due Dates: See CANVAS.
You will have to upload HWs from Canvas
Some HW Solutions
Meetings:
This is an online course.
There will be no face to face meetings. However, I give office hours, via zoom.
Other than that, you have to take a
proctored midterm and a proctored final,
according to the schedule below.
I am not flexible regarding proctored exams.
Zoom Office Hours
Zoom No: 976 2824 9890
Zoom Pass: 446137
Zoom Hr: Tu 89 PM (and by appointment)
Course Outline
There are nine chapters in this course (and the textbook), which can
be divided into three parts as mentioned later. The following is how this course is organized:
 Read the sections in the same order, as the homework appear.
Up to Chapter 7, they appear in the same order as the sections in the textbook.
I did some switching around in Chapter 8 and 9.
 Homework would have to be submitted (uploaded) in Canvas.
 You will need a TI84 Calculator. This course is heavily dependent on
TI84.
Grading Scheme:

Points 
Content

Homework 
100 
Chap. 19

Proctored Midtem 
100 
Chap. 3, 4, 5, 6 
Proctored Final 
100 
Chap. 7, 8, 9 
Feeling comfortable with homework is the key.
Schedule of Examinations:

Content  Date (Room no)  StartingTime 
Midterm  Chap. 3, 4, 5, 6 
March 28 Tue
(Kansas Union, Alderson Auditorium, 4th floor)

8:30am, 11:30am, 2:30pm

Final  Chap. 7, 8, 9 
May 8 Mon
(Kansas Union, Big 12 Room, 5th floor)

8:30am, 11:30am, 2:30pm, 5:30pm


Arrive at least 7 minutes prior to the start time.
Room will open 15 minutes prior to the exam start time.
 For both mideterm and the final, you would be allocated 2.5 hours .
 For both exams, you can bring two standard size papers (four sides) with formulas and notes.
You will also need to bring your T84
Do not take the test without T84.

Grading Scale:
Pts 
285+ 
270+ 
255+ 
240+ 
225+ 
210+ 
195+ 
180+ 
165+ 
150+ 
135+ 
else 
Grade 
A 
A 
B+ 
B 
B 
C+ 
C 
C 
D+ 
D 
D 
F 
Material
 A TI84 would be essential for this course. Make sure your version of TI84 has the invT function in the DISTRmenu.
Important Dates:
 Tuesday, January 17: First day of classes
 Monday, February 6: Last day to withdraw/drop without a "W"
 March 13 (Mon)19 (Sun): Spring Break
 Monday, April 17: Second Period Drop Ends
 Thursday, May 4: Last day of classes
Introduction (Goal)
The goal of this course is to learn some basic methods of statistical inferences. In Chapter 7 and 8, methods will be developed to estimate population parameters by intervals. In Chapter 9, methods of Significance Test would be developed to draw inferences about values of population parameters.
The following examples (from exercise sets) would give a more precise idea about the nature of statistical inferences that we will cover.

On interval estimation, the following are some examples of parameters that will be estimated:

the mean monthly consumption of electricity by the households,

the mean monthly cell phone minutes used by an individual,

the mean weight of a campus population,

the mean length of babies at birth,

the mean weight of salmon in a river,

the proportion p of individuals in a population who benefit from a vaccine.
 Following examples of significance test are considered
to make inferences regarding the following question:

Whether the mean life expectancy of a population is higher than 75 years or not?

Whether mean consumption of
gas by a new model of furnace is lower or not?

Whether mean weight of salmon in a river has reduced or not, as claimed
by some environmentalists?

Whether the proportion p_{1} of defective items produced by the new machine is lower than the
proportion p_{2} of defective items produced by the old machine or not.
Content and objectives:
There are nine chapters in this course. These can be divided into three parts:
Part 1 (Descriptive Statistics): Chapter 1 and 2 constitute the Descriptive Statistics part of this course. We discuss various representations
of data in pictorial and numerical manners. Among the numerical characteristics of data in Chapter 2, we discuss mean, median, standard deviation and others. You have seen much of this material before. You will use TI84 to compute these numerical constants.
 The main objective of the Chapter 1 would be to learn to compute frequency distributions using TI84. You need to follow the instructions given is those boxes to use TI and work out the homework problems.
 The main objective of the Chapter 2 would be to learn to compute mean, median, standard deviations and variance using TI84. You need to follow the instructions given is those boxes to use TI and work out the homework problems.
Part 2 (Probability and Mathematics): Chapter, 4, 5 and 6 constitute
the mathematical background and basis of this course. For its most part, we develop some understanding of probability theory and computations. Concept of probability would be needed for the remaining part of this
course (Chapter 7, 8, 9), where we discuss statistical inferences. Probability would be used as
measure chances of errors in statistical inferences. While we introduce mathematical concepts and formulas for probability computations, at least half the computations would be done using TI84.
 The objective of the Chapter 3 is first,
to learn the definition of the sample space and probability.
In section 3.2, you work out simple problems on probability.
In section 3.3, the objective is to learn some of the laws of probability.
In section 3.4, the objective is to learn some counting techniques and use them to compute probability.
In section 3.5, objective is to learn the concept of conditional probability and independent events.
Read the problems solutions in the respective sections and work out the homework problems.

The objective of Chapter 4 is to learn the concept of random variables and their probability distributions. You will also learn to compute the expected value (mean), variance and standard deviation of a random variable.
The objective of the section 4.2 is to introduce these concepts in a general context.
The objective of section 4.3 is to introduce a more specific random variable called Binomial random variable.
Other than computing expected value (mean), variance and standard deviation of a Binomial random variable,
you will use TI84 (silver edition) to compute probability for such random variables.

The objective of Chapter 5 is to learn to work with Normal random variable.
In this case, probability is defined as area under a bell shape curve.
Objective is also introduce inverse probability.
Objectives also include learning TI84 to compute normal probability.
The objective of section 5.3, would be to learn to use normal distribution to approximate Binomial probability.
Read and learn the solutions of the problems given and work out the homework problems.

The objective of Chapter 6, is to introduce Central Limit Theorem.
This means that normal distribution would be used to approximate sample distribution of sample mean and sample proportion.
Read and learn the solutions of the problems given and work out the homework problems.
Part 3 (Inferential Statistics): Chapter 7, 8, 9 constitutes the final part of the course where we do statistical inferences, which is the main goal of this course. In Chapter 7 and 8, we will discuss interval estimation. In Chapter9, Significance Test will be discussed. Again, much of the computations would be done with the aid of TI84.
 The objective of the Chapter 7 is to learn to estimate the mean, population proportion and variance by confidence intervals.
 The objective of the Chapter 8 is to learn to estimate the dirrference of means the difference of population proportions by confidence intervals.
 The objective of the Chapter 9 is to learn perform significance test to decide whether an hypothesis about the value of a parmater is correct or not.
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My Students have the permission to copy.
