D. Mayo: Replication Research Under an Error Statistical Philosophy jemille6
D. Mayo (Virginia Tech) slides from her talk June 3 at the "Preconference Workshop on Replication in the Sciences" at the 2015 Society for Philosophy and Psychology meeting.
D. Mayo: Replication Research Under an Error Statistical Philosophy jemille6
D. Mayo (Virginia Tech) slides from her talk June 3 at the "Preconference Workshop on Replication in the Sciences" at the 2015 Society for Philosophy and Psychology meeting.
Importance of Hypothesis
Characteristics of Hypothesis
Formulation of Hypothesis
Forms of Hypothesis
Types of Hypothesis
Simple Hypothesis
Complex Hypothesis
Working or Research Hypothesis
Null hypothesis
Alternative hypothesis
Logical Hypothesis
Statistical hypothesis
A Hypothesis is a supposition or explanation (theory) that is provisionally accepted in order to interpret certain events or phenomena, and to provide guidance for further investigation. This presentation elucidates hypothesis in research.
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS7 MEDIA LIBRARY.docxtaishao1
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS
7: MEDIA LIBRARY
Premium Videos
Core Concepts in Stats Video
· Probability and Hypothesis Testing
Lightboard Lecture Video
· Hypothesis Testing
Difficulty Scale
(don’t plan on going out tonight)
WHAT YOU WILL LEARN IN THIS CHAPTER
· Understanding the difference between a sample and a population
· Understanding the importance of the null and research hypotheses
· Using criteria to judge a good hypothesis
SO YOU WANT TO BE A SCIENTIST
You might have heard the term hypothesis used in other classes. You may even have had to formulate one for a research project you did for another class, or you may have read one or two in a journal article. If so, then you probably have a good idea what a hypothesis is. For those of you who are unfamiliar with this often-used term, a hypothesis is basically “an educated guess.” Its most important role is to reflect the general problem statement or question that was the motivation for asking the research question in the first place.
That’s why taking the care and time to formulate a really precise and clear research question is so important. This research question will guide your creation of a hypothesis, and in turn, the hypothesis will determine the techniques you will use to test it and answer the question that was originally asked.
So, a good hypothesis translates a problem statement or a research question into a format that makes it easier to examine. This format is called a hypothesis. We will talk about what makes a hypothesis a good one later in this chapter. Before that, let’s turn our attention to the difference between a sample and a population. This is an important distinction, because while hypotheses usually describe a population, hypothesis testing deals with a sample and then the results are generalized to the larger population. We also address the two main types of hypotheses (the null hypothesis and the research hypothesis). But first, let’s formally define some simple terms that we have used earlier in Statistics for People Who (Think They) Hate Statistics.
SAMPLES AND POPULATIONS
As a good scientist, you would like to be able to say that if Method A is better than Method B in your study, this is true forever and always and for all people in the universe, right? Indeed. And, if you do enough research on the relative merits of Methods A and B and test enough people, you may someday be able to say that.
But don’t get too excited, because it’s unlikely you will ever be able to speak with such confidence. It takes too much money ($$$) and too much time (all those people!) to do all that research, and besides, it’s not even necessary. Instead, you can just select a representative sample from the population and test your hypothesis about the relative merits of Methods A and B on that sample.
Given the constraints of never enough time and never enough research funds, with which almost all scientists live, the next best strategy is to take a portion of a lar.
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS7 MEDIA LIBRARY.docxevonnehoggarth79783
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS
7: MEDIA LIBRARY
Premium Videos
Core Concepts in Stats Video
· Probability and Hypothesis Testing
Lightboard Lecture Video
· Hypothesis Testing
Difficulty Scale
(don’t plan on going out tonight)
WHAT YOU WILL LEARN IN THIS CHAPTER
· Understanding the difference between a sample and a population
· Understanding the importance of the null and research hypotheses
· Using criteria to judge a good hypothesis
SO YOU WANT TO BE A SCIENTIST
You might have heard the term hypothesis used in other classes. You may even have had to formulate one for a research project you did for another class, or you may have read one or two in a journal article. If so, then you probably have a good idea what a hypothesis is. For those of you who are unfamiliar with this often-used term, a hypothesis is basically “an educated guess.” Its most important role is to reflect the general problem statement or question that was the motivation for asking the research question in the first place.
That’s why taking the care and time to formulate a really precise and clear research question is so important. This research question will guide your creation of a hypothesis, and in turn, the hypothesis will determine the techniques you will use to test it and answer the question that was originally asked.
So, a good hypothesis translates a problem statement or a research question into a format that makes it easier to examine. This format is called a hypothesis. We will talk about what makes a hypothesis a good one later in this chapter. Before that, let’s turn our attention to the difference between a sample and a population. This is an important distinction, because while hypotheses usually describe a population, hypothesis testing deals with a sample and then the results are generalized to the larger population. We also address the two main types of hypotheses (the null hypothesis and the research hypothesis). But first, let’s formally define some simple terms that we have used earlier in Statistics for People Who (Think They) Hate Statistics.
SAMPLES AND POPULATIONS
As a good scientist, you would like to be able to say that if Method A is better than Method B in your study, this is true forever and always and for all people in the universe, right? Indeed. And, if you do enough research on the relative merits of Methods A and B and test enough people, you may someday be able to say that.
But don’t get too excited, because it’s unlikely you will ever be able to speak with such confidence. It takes too much money ($$$) and too much time (all those people!) to do all that research, and besides, it’s not even necessary. Instead, you can just select a representative sample from the population and test your hypothesis about the relative merits of Methods A and B on that sample.
Given the constraints of never enough time and never enough research funds, with which almost all scientists live, the next best strategy is to take a portion of a lar.
A hypothesis is an assumption that is made based on some evidence. This is the initial point of any investigation that translates the research questions into predictions. It includes components like variables, population and the relation between the variables. A research hypothesis is a hypothesis that is used to test the relationship between two or more variables.
Importance of Hypothesis
Characteristics of Hypothesis
Formulation of Hypothesis
Forms of Hypothesis
Types of Hypothesis
Simple Hypothesis
Complex Hypothesis
Working or Research Hypothesis
Null hypothesis
Alternative hypothesis
Logical Hypothesis
Statistical hypothesis
A Hypothesis is a supposition or explanation (theory) that is provisionally accepted in order to interpret certain events or phenomena, and to provide guidance for further investigation. This presentation elucidates hypothesis in research.
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS7 MEDIA LIBRARY.docxtaishao1
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS
7: MEDIA LIBRARY
Premium Videos
Core Concepts in Stats Video
· Probability and Hypothesis Testing
Lightboard Lecture Video
· Hypothesis Testing
Difficulty Scale
(don’t plan on going out tonight)
WHAT YOU WILL LEARN IN THIS CHAPTER
· Understanding the difference between a sample and a population
· Understanding the importance of the null and research hypotheses
· Using criteria to judge a good hypothesis
SO YOU WANT TO BE A SCIENTIST
You might have heard the term hypothesis used in other classes. You may even have had to formulate one for a research project you did for another class, or you may have read one or two in a journal article. If so, then you probably have a good idea what a hypothesis is. For those of you who are unfamiliar with this often-used term, a hypothesis is basically “an educated guess.” Its most important role is to reflect the general problem statement or question that was the motivation for asking the research question in the first place.
That’s why taking the care and time to formulate a really precise and clear research question is so important. This research question will guide your creation of a hypothesis, and in turn, the hypothesis will determine the techniques you will use to test it and answer the question that was originally asked.
So, a good hypothesis translates a problem statement or a research question into a format that makes it easier to examine. This format is called a hypothesis. We will talk about what makes a hypothesis a good one later in this chapter. Before that, let’s turn our attention to the difference between a sample and a population. This is an important distinction, because while hypotheses usually describe a population, hypothesis testing deals with a sample and then the results are generalized to the larger population. We also address the two main types of hypotheses (the null hypothesis and the research hypothesis). But first, let’s formally define some simple terms that we have used earlier in Statistics for People Who (Think They) Hate Statistics.
SAMPLES AND POPULATIONS
As a good scientist, you would like to be able to say that if Method A is better than Method B in your study, this is true forever and always and for all people in the universe, right? Indeed. And, if you do enough research on the relative merits of Methods A and B and test enough people, you may someday be able to say that.
But don’t get too excited, because it’s unlikely you will ever be able to speak with such confidence. It takes too much money ($$$) and too much time (all those people!) to do all that research, and besides, it’s not even necessary. Instead, you can just select a representative sample from the population and test your hypothesis about the relative merits of Methods A and B on that sample.
Given the constraints of never enough time and never enough research funds, with which almost all scientists live, the next best strategy is to take a portion of a lar.
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS7 MEDIA LIBRARY.docxevonnehoggarth79783
7 HYPOTHETICALS AND YOU TESTING YOUR QUESTIONS
7: MEDIA LIBRARY
Premium Videos
Core Concepts in Stats Video
· Probability and Hypothesis Testing
Lightboard Lecture Video
· Hypothesis Testing
Difficulty Scale
(don’t plan on going out tonight)
WHAT YOU WILL LEARN IN THIS CHAPTER
· Understanding the difference between a sample and a population
· Understanding the importance of the null and research hypotheses
· Using criteria to judge a good hypothesis
SO YOU WANT TO BE A SCIENTIST
You might have heard the term hypothesis used in other classes. You may even have had to formulate one for a research project you did for another class, or you may have read one or two in a journal article. If so, then you probably have a good idea what a hypothesis is. For those of you who are unfamiliar with this often-used term, a hypothesis is basically “an educated guess.” Its most important role is to reflect the general problem statement or question that was the motivation for asking the research question in the first place.
That’s why taking the care and time to formulate a really precise and clear research question is so important. This research question will guide your creation of a hypothesis, and in turn, the hypothesis will determine the techniques you will use to test it and answer the question that was originally asked.
So, a good hypothesis translates a problem statement or a research question into a format that makes it easier to examine. This format is called a hypothesis. We will talk about what makes a hypothesis a good one later in this chapter. Before that, let’s turn our attention to the difference between a sample and a population. This is an important distinction, because while hypotheses usually describe a population, hypothesis testing deals with a sample and then the results are generalized to the larger population. We also address the two main types of hypotheses (the null hypothesis and the research hypothesis). But first, let’s formally define some simple terms that we have used earlier in Statistics for People Who (Think They) Hate Statistics.
SAMPLES AND POPULATIONS
As a good scientist, you would like to be able to say that if Method A is better than Method B in your study, this is true forever and always and for all people in the universe, right? Indeed. And, if you do enough research on the relative merits of Methods A and B and test enough people, you may someday be able to say that.
But don’t get too excited, because it’s unlikely you will ever be able to speak with such confidence. It takes too much money ($$$) and too much time (all those people!) to do all that research, and besides, it’s not even necessary. Instead, you can just select a representative sample from the population and test your hypothesis about the relative merits of Methods A and B on that sample.
Given the constraints of never enough time and never enough research funds, with which almost all scientists live, the next best strategy is to take a portion of a lar.
A hypothesis is an assumption that is made based on some evidence. This is the initial point of any investigation that translates the research questions into predictions. It includes components like variables, population and the relation between the variables. A research hypothesis is a hypothesis that is used to test the relationship between two or more variables.
In this presentation you will get to learn about the formats of SAS. Here I have discussed about the SAS defined format. in the next ppt I will share tutorial of User defined Format.
This presentation will explain how to sort data by using SAS. You will also get that how to remove duplicate observation from SAS Data Sets by using nodupkey/nodup options.
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2. Definition
A statistical hypothesis test is a method of statistical inference
used to decide whether the data at hand sufficiently support a
particular hypothesis.
Hypothesis testing allows us to make probabilistic statements
about population parameters.
HANDSON SCHOOL OF DATA SCIENCE 2
Statistical Hypothesis
3. Example
If you loose your mobile first what you do that is you just make some idea that
where it can be and search those places like:
i) pocket of your last worn trouser or
ii) it can be on the desk or
iii) in the car that you drove last or
iv) it can be in the charge.
HANDSON SCHOOL OF DATA SCIENCE 3
Statistical Hypothesis
4. Hypothesis = Hypo + Thesis
Hypo = Less than
&
Thesis = A declaration or theory that is put forward as a idea to be retained or proved.
As hypothesis is not proved that is why it is mentioned as less than thesis, when it will be proved it will be
mentioned as thesis.
HANDSON SCHOOL OF DATA SCIENCE 4
Statistical Hypothesis
5. Characteristics
(i) Hypothesis Should be simple & clear.
(ii) It should be testable within a specific time.
(iii) It is a tentative Statement.
(iv) It is a part of research; but some research starts with a question, instead of
hypothesis.
(v) It should be able to relate the variables using in the research.
(vi) It must be specific.
Here are few key characteristics of Hypothesis
HANDSON SCHOOL OF DATA SCIENCE 5
Statistical Hypothesis
7. Null Hypothesis
A null hypothesis intends no relationship between two variables. Symbolized by H0, it is a negative
statement.
HANDSON SCHOOL OF DATA SCIENCE 7
Statistical Hypothesis
8. Alternative Hypothesis
Alternative hypothesis considered to be the conflicting a null hypothesis, an alternative hypothesis is
symbolized as H1 or Ha. It clearly states that the dependent variable affects the independent variable.
Alternative
Hypothesis
Directional
Hypothesis
Non-Directional
Hypothesis
HANDSON SCHOOL OF DATA SCIENCE 8
Statistical Hypothesis
9. Statistical Hypothesis
Example
Let’s assume we are doing an research on mental strength of Indian people.
Topic: A study on the difference of Mental Strength of Indian people with respect to their sex
Objective:
i) To study the Mental Strength of female teenagers in India.
ii) To study the difference Mental Strength of Male and Female in India.
HANDSON SCHOOL OF DATA SCIENCE 9
10. Example
Objective Null Hypothesis
(H0)
Non-Directional Hypothesis Directional
Hypothesis
To study the
Mental Strength
of female
teenagers in
India.
To study the
difference
Mental Strength
of Male and
Female in India
There is no
significant
difference of Mental
Strength among
female teenagers of
India.
There is no significant
difference of Mental
Strength among Male &
Female teenager in CB.
district.
There is significant difference
of Mental Strength among
female teenagers of India.
There is significant
difference of Mental
Strength among male and
female of India.
Mental Strength of state
board female teenagers
is higher then any other
board female teenagers
in India.
Mental Strength of
Female are higher than the
male in India.
HANDSON SCHOOL OF DATA SCIENCE 10
Alternative Hypothesis (H1
or Ha)
Statistical Hypothesis
11. School of Data Science
HANDSON SCHOOL OF DATA SCIENCE 11
Thank You
