INTRODUCTION TO STATISTICS - Full of my life with ... · DEFINITIONS Descriptive Statistics -...
Transcript of INTRODUCTION TO STATISTICS - Full of my life with ... · DEFINITIONS Descriptive Statistics -...
INTRODUCTION TO
STATISTICS
DO WE NEED STATISTICS?
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WHAT IS MEANT BY STATISTICS?
Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions.
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TO COLLECT DATA FROM A SMALL
PART OF A LARGER GROUP
SO THAT WE CAN LEARN ABOUT
THE LARGER GROUP
GOAL OF STATISTICS
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•Observations that have been collected (e.g. measurements, survey responses)
Data
Statistics •A collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data.
DEFINITIONS
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WHO USES STATISTICS?
Statistical techniques are used
extensively by marketing,
accounting, quality control,
consumers, professional sports
people, hospital administrators,
educators, politicians, physicians,
etc...
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•DESCRIPTIVE STATISTICS
•INFERENTIAL STATISTICS
Describe about sample’s characteristics
Make inferences about population from sample statistics
TYPES OF STATISTICS
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DEFINITIONS
Descriptive Statistics - methods of organizing, summarizing, and presenting data in an informative way.
EXAMPLE 1: A Gallup poll found that 49% of the people in a survey knew the name of the first book of the Bible. The statistic 49 describes the number out of every 100 persons who knew the answer.
EXAMPLE 2: According to Consumer Reports, General Electric washing machine owners reported 9 problems per 100 machines during 2001. The statistic 9 describes the number of problems out of every 100 machines.
Inferential Statistics: A decision, estimate, prediction, or generalization about a population, based on a sample.
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Descriptive statistic
method of organizing, summarizing and presenting data in a
convenient and informative way.
Use numerical data and graphical techniques.
Collect data
e.g., Survey
Present data
e.g., Tables and graphs
Characterize data
e.g., Sample mean =
iX
n
DESCRIPTIVE STATISTICS
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Method used to draw conclusions and inferences
about characteristics of population based on sample
data.
Estimation
e.g., Estimate the population mean weight using the sample mean weight
Hypothesis testing
e.g., Test the claim that the population mean weight is 120 pounds
INFERENTIAL STATISTICS
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There are 3 Key Concepts in Statistics
Population
Sample
Statistical Inference
KEY CONCEPTS IN STATISTICS
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Statistical inference
Is a process of making an estimate, prediction, or decision making about population based on sample data.
Population is very large, so statistic is used to investigate characteristic of the population.
Estimation from sample is not 100% correct.
To measure this, confidence level and significance level are used to determine reliability of the measurement.
STATISTICAL INFERENCE
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a b c d
ef gh i jk l m n
o p q rs t u v w
x y z
Population
Sample b c
g i n
o r u
y
Measures used to describe
the population are called
parameters
Measures computed from
sample data are called
statistics
POPULATION AND SAMPLE
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•is the complete collection of all elements (e.g. measurements, scores, people, etc.) to be studied.
A population
A census •is the collection of data from every member of the population.
A sample •is the subcollection of members selected from a population.
DEFINITIONS
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A population is a collection of all possible individuals, objects, or
measurements of interest.
A sample is a portion, or part, of the population of interest
POPULATION versus SAMPLE
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•is a numerical measurement describing a particular characteristic of a population.
A parameter
A statistic •is a numerical measurement describing a particular characteristic of a sample.
DEFINITIONS
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Population
Is a complete collection of all items (people, or things) of interest.
Measures of population are called parameters (characteristics of interest).
It is very large and sometime infinite.
POPULATION
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Sample
Is a set of data drawn from a population.
Measures of sample are called statistics.
Since populations are very big and sometime infinite, we make use of statistics to make inferences about parameters.
SAMPLE
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To systematically present information
To make conclusions about population
based on sample information
To make reliable forecasts
Information obtained are use to improve
system and processes
WHY USE STATISTICS?
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CAN YOU INTERPRATE THIS
GRAPH?
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HOW DO WE OBTAIN DATA?
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RESULT OF A MEASUREMENT
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A raw data is the data obtained
before it is being processed or
arranged.
RAW DATA
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78, 74, 65, 74, 74, 67, 63, 67,
80, 58 74, 50, 65, 74, 86, 78,
63, 65, 80, 89
The raw scores for 20 students in a
test
COLLECT DATA
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Score
(X)
Frequency
(f)
50
58
63
65
67
74
78
80
86
89
1
1
2
3
2
5
2
2
1
1
Total
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Frequency distribution table for
ungrouped data
SUMMARIZING DATA
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0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10
Skor
Kekera
pan
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10
Score
Fre
qu
en
cy
50 60 70 80 90
PRESENTING DATA
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