This document defines sample and population and provides examples of how they are used. It explains that a population is all objects being studied, while a sample is a subset of the population. The sampling process involves defining the population, selecting a random sample from the population, and making inferences about the population based on the sample. Two examples are given demonstrating how to identify the population and sample in different contexts. An exercise at the end provides a practice problem and solution.
Meaning & Definition of Population & Sampling, Types of Sampling - Probability & Non-Probability Sampling Techniques, Characteristics of Probability Sampling Techniques, Types of Probability Sampling Techniques, Characteristics of Non-Probability Sampling Techniques, Types of Non-Probability Sampling Techniques, Errors in Sampling, Size of sample, Application of Sampling Technique in Research
concept of sample and sampling, sampling process and problems, types of samples: probability and non probability sampling, determination and sample size, sampling and non sampling errors
Introduction to Statistics - Basic concepts
- How to be a good doctor - A step in Health promotion
- By Ibrahim A. Abdelhaleem - Zagazig Medical Research Society (ZMRS)
Meaning & Definition of Population & Sampling, Types of Sampling - Probability & Non-Probability Sampling Techniques, Characteristics of Probability Sampling Techniques, Types of Probability Sampling Techniques, Characteristics of Non-Probability Sampling Techniques, Types of Non-Probability Sampling Techniques, Errors in Sampling, Size of sample, Application of Sampling Technique in Research
concept of sample and sampling, sampling process and problems, types of samples: probability and non probability sampling, determination and sample size, sampling and non sampling errors
Introduction to Statistics - Basic concepts
- How to be a good doctor - A step in Health promotion
- By Ibrahim A. Abdelhaleem - Zagazig Medical Research Society (ZMRS)
Topic: Population And Sample
Student Name: Sidera Saleem
Class: B.Ed. 2.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
Statistics is the science of dealing with numbers.
It is used for collection, summarization, presentation and analysis of data.
Statistics provides a way of organizing data to get information on a wider and more formal (objective) basis than relying on personal experience (subjective).
This ppt covers problems on Stratified Random Sampling in this you will find Equal Number of Units from Each Stratum
Proportional Allocation
Neyman’s Allocation
Optimum Allocation
Probability Sampling and Types by Selbin Babuselbinbabu1
The presentation will cover probability sampling and all the types of probability sampling like Random sampling , systematic random sampling, strtified random sampling, cluster random sampling and multi stage sampling.
This was a presentation that was carried out in our research method class by our group. It will be useful for PHD and master students quantitative and qualitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches, types of sampling in qualitative researches, and ethical Considerations in Data Collection.
Topic: Population And Sample
Student Name: Sidera Saleem
Class: B.Ed. 2.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
Statistics is the science of dealing with numbers.
It is used for collection, summarization, presentation and analysis of data.
Statistics provides a way of organizing data to get information on a wider and more formal (objective) basis than relying on personal experience (subjective).
This ppt covers problems on Stratified Random Sampling in this you will find Equal Number of Units from Each Stratum
Proportional Allocation
Neyman’s Allocation
Optimum Allocation
Probability Sampling and Types by Selbin Babuselbinbabu1
The presentation will cover probability sampling and all the types of probability sampling like Random sampling , systematic random sampling, strtified random sampling, cluster random sampling and multi stage sampling.
This was a presentation that was carried out in our research method class by our group. It will be useful for PHD and master students quantitative and qualitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches, types of sampling in qualitative researches, and ethical Considerations in Data Collection.
measurement and scaling is an important tool of research. by following the right and suitable scale will provide an appropriate result of research.this slide show will additionally provide the statistical testing for research measurement and scale.
Vermicomposting Classroom Activities
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http://scribd.com/doc/239851214
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http://scribd.com/doc/239851159
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Healthy Foods Dramatically Improves Student Academic Success
http://scribd.com/doc/239851348
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City Chickens for your Organic School Garden
http://scribd.com/doc/239850440
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Simple Square Foot Gardening for Schools - Teacher Guide
http://scribd.com/doc/239851110
1. Sample and Population
By:
Group 5
START!
1. Altafiyani Rahmatika
2. Gina Nuryustika Rizal
3. Jody Furqon Sanjaya
4. Wini Safitri
Class IX D
2. Select!
1.
DEFINITION 2. SAMPLE AND
POPULATION
IN DAILY LIFE
3.THE
SAMPLING
PROCESS 4.
EXAMPLE
5.
EXERCISE
3. Definition
What is the meaning of
And, what is the
meaning of sample?
population?
Sample is a part of
Population is all objects
population being studied
being studied.
or observed.
4. Sample and Population in Daily Life
Suppose we want to know the average weight of Junior High
School students in Subang. Considering limited time, labor and
cost, we cannot measure all the students. Thus, we should pick a
random sample consisting of all students from a number of
public or private schools.
In this case :
i. all Junior High School students in Subang constitute the
population,
ii. Students whose heights are measured constitute the
sample.
5. The Sampling Process
POPULATION (N)
INFERENCE
• Define population (N) to be
SAMPLE (n) sampled
• Determine sample (n) from
population (N) to be
observed
• Determine an inference of
population based on sample
6. Example 1
SMP B has 8 classes of students from each grade VII,
VIII, IX. Suppose that the principal wants to conduct a
research on the relation between parental socioeconomic
status and a student’s outcome, determine:
a. the population
b. the sample
Answer:
a. The population is all the students in SMP B.
b. The sample is some students from each grade VII, VIII,
and IX selected randomly.
7. Example 2
A research has been carried out to determine the pollution
level in a lake.
a. What is the population?
b. How to collect the sample?
Answer:
a. The population is a lake.
b. A research only observe some quantities of water
taken randomly as the sample of the lake (population)
to determine the pollution level in a lake.
8. Exercise
1. The department of National Education is conducting
a research on the result of the national final exam in
a province.
Determine.
a. the population
b. the sample
Answer:
a. The population is the result of the national final
exam in a national (all province)
b. The sample is the result of the national final
exam in a province.
9. 2. A farmer cultivate his ½ ha rice field. Being properly
cultivated, the rice field yields good quality crop. In
harvest time, he gets 8 kg of unhusked rice field
totaling 10 m2 in area.
a. What is the population?
b. What is the sample?
c. Based on the sample, estimate the total mass of
unhusked rice grains the farmer can harvest
Answer :
a. The population is ½ ha rice field.
b. The sample is 8 kg of unhusked rice grains from
different parts of his rice field totalling 10 m2 of
rice field.
10. c. The population = ½ ha rice field
= ½ hm2
= ½ x 10000
= 5000 m2
The sample = 8 kg of 10 m2 in area of ½ ha rice field
= 8 kg/10 m2
The total mass of unhusked rice grains =
Sample x Population
= x 5000 m2
2
= 4000 kg
Thus, the total mass of unhusked rice grains the farmer
can harvest is 4000 kg.