stat 110: general statisticsfmalam.kau.edu.sa/files/0007085/files/157188_stat_110_ch... ·...

STAT 110: General Statistics

FAROUQ MOHAMMAD A. ALAM, PHDDepartment of StatisticsFaculty of ScienceBuilding 90A, 2nd Floor, Room 26F27Office Hours: by appointmentWebsite: http://fmalam.kau.edu.sa

Contact:

App: myKAUEMAIL: fmalam@kau.edu.sa

5 RULES

(1) Attendance is MANDATORY!

(25% absence = DN)

(2) Cellphones/AirPods must NOT be used during class!

(3) Talking during class for NO APPARENT REASON is not tolerated!

5 RULES (Cont.)

(4) Students who are late more than TEN MINUTES OR ONCE THE CLASS DOOR IS CLOSED are considered absent.

(5) Absent students must provide reasonable excuses as soon as possible (e.g. authentic medical reports, etc.) that includes their NAME, UNIVERSITY ID, SECTION NUMBER, AND ABSENCE DATE.

STAT 110 Textbook

Most of the information mentioned in these slides

are from:

Bluman, A. G. (2016). Elementary Statistics: A

Step by Step Approach. McGraw-Hill

Education. Customized edition for the

Department of Statistics at KAU

Syllabus & Timeline: At a Glance

Chapter 1: The Nature of Probability and Statistics

Chapter 2*: Frequency Distributions and Graphs

Chapter 3*: Data Description

Midterm # 1

Chapter 10*: Correlation and Regression

Chapter 13*: Nonparametric Statistics

Chapter 4: Probability and Counting Rules

Chapter 5*: Discrete Probability Distributions

Midterm # 2

Chapter 6*: The Normal Distribution

Final Exam

* Excel/MegaStat application.

Course Grading

10% (Weekly) Homework.

25% Midterm #1.

25% Midterm #2.

40% Final exam.

Chapter 1: The Nature of Probability and Statistics

Objectives:

❑ Understand the meaning of Statistics.

❑ Differentiate between descriptive statistics and inferential statistics.

❑ Identify types of variables, and understand the nominal and ordinal measurement levels for qualitative variable.

❑ Identify the four basic sampling techniques.

❑ Understand the difference between an observational study and an experimental study.

Overview of Chapter 1

Sec. # Title Page(s)

Introduction 2

1 - 1 Descriptive and Inferential Statistics 3 - 4

1 - 2 Variables and Types of Data 6 - 8

1 - 3 Data Collection and Sampling Techniques 11 - 16

1 - 4 Experimental Designs 18 - 19

Introduction

Statistics is the science of conducting studies to

collect, organize, summarize, analyze and

draw conclusions from data.

Introduction

Statistics is the science of conducting studies to

collect, organize, summarize, analyze and

draw conclusions from data.

What is data?Inferential

Methods!

Descriptive

Methods!

The Joy of Stats!

1 – 1: Descriptive and Inferential

Statistics

Data are the values (measurements or observations)

that variables under study can assume. A collection

of data is called a dataset.

A variable is a characteristic or attribute that can

assume different values.

What is the difference between a measurement and

an observation?

Descriptive and Inferential Statistics

Statistics

Descriptive Statistics

Inferential Statistics

Data Collection

Data Organization

Data Summarization

Data Presentation

Descriptive and Inferential Statistics

Statistics

Generalizing from

Samples to Populations

Estimations and

Hypothesis Tests

Determining Relationships

among Variables

Making Predictions

Statistics (cont.)

A population consists of all subjects (human or

otherwise) that are being studied.

A sample is a group of subjects selected from a

population.

Statistics (cont.)

Source: NCES Blog | Statistical concepts in brief: How and why does NCES use sample surveys?

Part of Example 1 – 1 (page 4)

Determine whether descriptive of inferential

statistics were used:

The average jackpot for the top five lottery winners

was $367.6 million.

A study done by the American Academy of Neurology

suggests that older people who had a high caloric diet

more than doubled their risk of memory loss.

Determine whether descriptive of inferential

statistics were used:

The average jackpot for the top five lottery winners

was $367.6 million. (Descriptive statistics)

A study done by the American Academy of Neurology

suggests that older people who had a high caloric diet

more than doubled their risk of memory loss.

(Inferential statistics)

Why using a sample? (5 min.)

❑ Write down your thoughts.

❑ Discuss your thoughts with nearby students.

Group Activity!

Why using a sample?

In general, researchers consider studying a sample rather than the population due to the following reasons:

Studying a sample is less costly and less time consuming than studying the whole population.

Measuring the variable(s) of interest may involve the destruction of the population unit (e.g. blood sample).

A population may be infinite.

1 – 2: Variables and Types of Data

General classification:

Variable

Qualitative Quantitative

Discrete Continuous

Classify each of the following variables as discrete

or continuous:

(a) The highest wind speed of a hurricane.

Ans. Continuous

(b) The weight of baggage on airplane.

Ans. Continuous

(c) The number of pages in a statistics textbook.

Ans. Discrete

Variable

Qualitative

Nominal Ordinal

Quantitative

Interval Ratio

Measurement scale classification:

Variable

Qualitative

Nominal Ordinal

Quantitative

Interval Ratio

Measurement scale classification:

What level of measurement would be used to each variable?

(a) The ranking of movies released this month.

Ans. Ordinal

(b) Color of athletic shirts sold by Oak Park Health Club.

Ans. Nominal

1 – 3: Data Collection and Sampling

Techniques

One common way to collect data is via surveys.

Methods of survey:

Telephone surveys.

Mailed (emailed) questionnaire surveys.

Personal interview surveys.

Surveying records.

Direct observation of situations.

Sampling Techniques

There are four main sampling techniques:

Random sampling.

Systematic sampling.

Stratified sampling.

Cluster sampling.

Sampling Techniques (cont.)

A random sample is a sample in which all members

of the population have an equal chance to be

selected.

Random Sample

Source: Sampling (statistics) - Wikipedia

A systematic sample is a sample obtained by

selecting every kth member of the population

where k is a counting number.

Note: This type of sampling involves a random start

and then proceeds with the selection process

mentioned above.

Systematic Sample

A stratified sample is a sample obtained

by dividing the population into strata

according to some characteristic relevant

to the study. Then subjects are randomly

selected from each stratum.

Stratified Sample

A cluster sample is obtained by dividing

the population into clusters and then

selecting one or more cluster and using

all members in the cluster(s) as the

members of the sample.

Cluster Sample

For similar details see Figure 1 – 3 in

, and Table 1 – 4 in page 16.

Example 1 – 5: Sampling Method

(page 16)

State which sampling method was used.

(a) Out of 10 hospital in a municipality, a

researcher selects one and collects records for a

24-hour period on the types of emergences that

were treated there.

Ans. Cluster.

Example 1 – 5 (cont.)

(b) A researcher divided a group of students

according to gender, major field, and low,

average, high grade point average (GPA). Then

she randomly selects six students from each

group to answer questions in a survey.

Ans. Stratified.

(c) The subscribers to a magazine are numbered.

Then a sample of these people is selected using

random numbers.

Ans. Random.

(d) Every 10th bottle of Cola is selected, and the

amount of liquid in the bottle is measured. The

purpose is to see if the machines that fill the

bottles are working properly.

Ans. Systematic.

1 – 4: Experimental Designs

In an observational study, the researcher merely

observes what is happening or what has happened

in the past and tries to draw conclusions based on

these observations.

In an experimental study, the researcher

manipulates one of the variables and tries to

determine how the manipulation influences other

variables.

Types of variables in experimental designs

Independent variable

influencesDependent variable

Independent variable vs. dependent variable

Statistical studies usually include one or more independent variables and one or, sometimes, more than one dependent variable.

The independent variable in an experimental study is the one that is being manipulated by the researcher. The independent variable is also called the explanatory variable.

The resultant variable is also called the dependent variable or the outcome variable.

Experimental Designs (7.5 min.)

❑ Think about a study and write it down.

❑ Discuss the type of the study, and determine the independent and dependent variables with nearby students.

Group Activity!

An observational study

Researchers want to study the influence of drinking at least one

cup of tea on sleeping habits. They took a random sample of

adults and asked them about the daily amount of tea they

consume and the time at which they sleep.

Independent variable: daily amount of tea.

Dependent variable: the time at which they sleep.

An experimental study

Researchers want to study the influence of drinking at least one

cup of tea on sleeping habits. They took a random sample of

adults and divided them into three groups. The first group are

told to drink tea less than usual, the second group are told

to drink tea as usual, and the third group are told to drink

tea more than usual. After a while, the people are asked

about the daily amount of tea they consumed and the time at

which they slept.

Independent variable: daily amount of tea.

Dependent variable: the time at which they sleep.

stat 110: general statisticsfmalam.kau.edu.sa/files/0007085/files/157188_stat_110_ch... ·...

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