Description
Describing about the Hypothesis formulation, Research design & Data Collection Techniques and covers the topics like the different steps included in hypothesis formulation.
RESEARCH METHODOLOGY
•
Hypothesis formulation design Collection Techniques
•Research •Data
HYPOTHESIS FORMULATION
Hypothesis is a proposition – a tentative assumption which a researcher want to test for its logical or empirical consequences. Steps involved in hypothesis testing: i. Formulate a hypothesis, ii. Set up a suitable significance level, iii. Choose a test criterion, iv. Compute the statistics, and v. Make decision
?
STEP 1: FORMULATE A HYPOTHESIS
?Null
Hypothesis and alternative hypothesis
?In
statistical analysis if we want to compare method A with method B and if we proceed with the assumption that both methods are equally good then this assumption is termed as null hypothesis.
?As
against this we may feel that method A is better than method B then we call it as alternative hypothesis
?Null
Hypothesis is generally is termed as H0 and alternative hypothesis symbolized as Ha
The null hypothesis, H0 represents a theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved. ? The alternative hypothesis, Ha, is a statement of what a statistical hypothesis test is set up to establish ? Eg. H0: there is no significant difference between the two drugs on average. H1: the two drugs have different effects, on average
?
FOLLOWING CONSIDERATIONS ARE KEPT
IN VIEW We give special consideration to the null hypothesis. This is due to the fact that the null hypothesis relates to the statement being tested, whereas the alternative hypothesis relates to the statement to be accepted if / when the null is rejected. ? We either 'reject H0 in favor of H1' or 'do not reject H0 '; we never conclude 'reject H1', or even 'accept H1'
?
STEP 2: SETTING UP SUITABLE SIGNIFICANCE LEVEL
Type I error: occurs when the null hypothesis is rejected when it is in fact true; that is, H0 ? Type II error: occurs when the null hypothesis H0, is not rejected when it is in fact false is wrongly rejected. ? A type I error is often considered to be more serious, and therefore more important to avoid, than a type II error. ? The hypothesis test procedure is therefore adjusted so that there is a guaranteed 'low' probability of rejecting the null hypothesis wrongly
?
CTND….
Level of significance signifies the probability of committing Type I error It is the probability of a type I error and is set by the investigator in relation to the consequences of such an error and generally it is taken as equal to 5%(?= 0.05)
STEP 3: CHOOSE A TEST CRITERION
Selection of suitable probability distribution that can be used for the available information under consideration a) Normal distribution: Z characteristic, this is normally used, when the samples used are more than 30 b) t- distribution: used for small samples only c) F test and Chi Square Test
?
STEP 4: COMPUTE THE TEST STATISTICS
It involves actual collection and computation of the sample data. ? For the case under consideration we have to find the sample mean(x) and then compute calculated ‘Z’ ? This calculated (absolute) is compared with tabulated value. ? Tabulated value will be decided depending upon nature of test i.e. one tailed or two tailed test.
?
STEP 5: MAKE DECISION
If calculated value of test characteristics is greater than the tabulated value, the null hypothesis is rejected and alternate hypothesis is accepted. ? This value of calculated characteristic falls outside the accepted region
?
RESEARCH DESIGN
?Research
design involves the development of research plan for carrying out the study. ?It gives a framework for collecting and analyzing the data.
Research design
Exploratory
Conclusive
Descriptive
11
Causal
EXPLORATORY RESEARCH
The main objective is to formulate the problems more precisely, clarify the concepts, gather explanations, to gain insights and to form hypotheses ? This can be performed using literature search, surveying certain people about their experiences, focus groups and case studies ? An example – a manufacturer wants to identify ten most important variables his consumers use to decide on whether to buy his brand
?
DESCRIPTIVE RESEARCH (1/2)
?
?
?
This is more rigid than exploratory research and seeks to describe users of product or predict the future demand for the product Descriptive research defines questions, people surveyed and methods of analysis prior to begin data collection. It should answer the – who, what, where, when, why and how aspects of the research There are two basic types of descriptive studies –
? ?
Longitudinal studies Cross-sectional studies
DESCRIPTIVE RESEARCH (2/2)
?
Longitudinal studies are time series analysis that make repeated measurements of same individuals.
?
It helps to monitor the behavior such as brand switching
?
Cross sectional studies take the sample from the population to make measurements at specific point of time.
?
It helps in long term demand forecasting of a product
CAUSAL RESEARCH
Causal research helps to find out the cause and effect relationship between the variables. It is generally done through laboratory and field experiments. It helps to study how actions taken now will affect a business in future ? It explores the effect of one variable on another. For example, Has new advertising campaign we designed resulted ids increased sales?
?
DATA TYPES AND SOURCES
• Types of data are classified into two types – • I. Secondary data and II. Primary data
Secondary data sources ? ? ? ? ?
Primary data sources ? ? ? ? ? ?
Company literature Syndicated reports Internet Newspapers Magazines
Demographics Lifestyles characteristics Attitudes and opinion Awareness Purchase intention Consumer behavior
METHODS OF DATA COLLECTION
Observation ? Experiments / clinical trials ? Telephone interviews ? Postal or mail questionnaire ? Personal interviews ? Panel research ? Group interview Technique ? CAPI ? Web-based questionnaire
?
LIMITATIONS OF PRIMARY DATA COLLECTION
Unwillingness of respondents to provide information ? Inability of respondents to provide information:
?
Lack of knowledge ? Lapse of memory ? Human biases of respondents: i.e. ego etc. ? Semantic difficulties: different interpretation of same question.
?
METHODS FOR SECONDARY DATA COLLECTION
Various publication of central and state gov., foreign gov., international bodies. ? Technical and trade journals ? Books, magazines and newspapers ? Report and publications of various associations connected with business and industry, banks ? Reports prepared by research scholars, in different fields. ? Public records and statistic historical documents and other sources of published information
?
doc_564488020.pptx
Describing about the Hypothesis formulation, Research design & Data Collection Techniques and covers the topics like the different steps included in hypothesis formulation.
RESEARCH METHODOLOGY
•
Hypothesis formulation design Collection Techniques
•Research •Data
HYPOTHESIS FORMULATION
Hypothesis is a proposition – a tentative assumption which a researcher want to test for its logical or empirical consequences. Steps involved in hypothesis testing: i. Formulate a hypothesis, ii. Set up a suitable significance level, iii. Choose a test criterion, iv. Compute the statistics, and v. Make decision
?
STEP 1: FORMULATE A HYPOTHESIS
?Null
Hypothesis and alternative hypothesis
?In
statistical analysis if we want to compare method A with method B and if we proceed with the assumption that both methods are equally good then this assumption is termed as null hypothesis.
?As
against this we may feel that method A is better than method B then we call it as alternative hypothesis
?Null
Hypothesis is generally is termed as H0 and alternative hypothesis symbolized as Ha
The null hypothesis, H0 represents a theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved. ? The alternative hypothesis, Ha, is a statement of what a statistical hypothesis test is set up to establish ? Eg. H0: there is no significant difference between the two drugs on average. H1: the two drugs have different effects, on average
?
FOLLOWING CONSIDERATIONS ARE KEPT
IN VIEW We give special consideration to the null hypothesis. This is due to the fact that the null hypothesis relates to the statement being tested, whereas the alternative hypothesis relates to the statement to be accepted if / when the null is rejected. ? We either 'reject H0 in favor of H1' or 'do not reject H0 '; we never conclude 'reject H1', or even 'accept H1'
?
STEP 2: SETTING UP SUITABLE SIGNIFICANCE LEVEL
Type I error: occurs when the null hypothesis is rejected when it is in fact true; that is, H0 ? Type II error: occurs when the null hypothesis H0, is not rejected when it is in fact false is wrongly rejected. ? A type I error is often considered to be more serious, and therefore more important to avoid, than a type II error. ? The hypothesis test procedure is therefore adjusted so that there is a guaranteed 'low' probability of rejecting the null hypothesis wrongly
?
CTND….
Level of significance signifies the probability of committing Type I error It is the probability of a type I error and is set by the investigator in relation to the consequences of such an error and generally it is taken as equal to 5%(?= 0.05)
STEP 3: CHOOSE A TEST CRITERION
Selection of suitable probability distribution that can be used for the available information under consideration a) Normal distribution: Z characteristic, this is normally used, when the samples used are more than 30 b) t- distribution: used for small samples only c) F test and Chi Square Test
?
STEP 4: COMPUTE THE TEST STATISTICS
It involves actual collection and computation of the sample data. ? For the case under consideration we have to find the sample mean(x) and then compute calculated ‘Z’ ? This calculated (absolute) is compared with tabulated value. ? Tabulated value will be decided depending upon nature of test i.e. one tailed or two tailed test.
?
STEP 5: MAKE DECISION
If calculated value of test characteristics is greater than the tabulated value, the null hypothesis is rejected and alternate hypothesis is accepted. ? This value of calculated characteristic falls outside the accepted region
?
RESEARCH DESIGN
?Research
design involves the development of research plan for carrying out the study. ?It gives a framework for collecting and analyzing the data.
Research design
Exploratory
Conclusive
Descriptive
11
Causal
EXPLORATORY RESEARCH
The main objective is to formulate the problems more precisely, clarify the concepts, gather explanations, to gain insights and to form hypotheses ? This can be performed using literature search, surveying certain people about their experiences, focus groups and case studies ? An example – a manufacturer wants to identify ten most important variables his consumers use to decide on whether to buy his brand
?
DESCRIPTIVE RESEARCH (1/2)
?
?
?
This is more rigid than exploratory research and seeks to describe users of product or predict the future demand for the product Descriptive research defines questions, people surveyed and methods of analysis prior to begin data collection. It should answer the – who, what, where, when, why and how aspects of the research There are two basic types of descriptive studies –
? ?
Longitudinal studies Cross-sectional studies
DESCRIPTIVE RESEARCH (2/2)
?
Longitudinal studies are time series analysis that make repeated measurements of same individuals.
?
It helps to monitor the behavior such as brand switching
?
Cross sectional studies take the sample from the population to make measurements at specific point of time.
?
It helps in long term demand forecasting of a product
CAUSAL RESEARCH
Causal research helps to find out the cause and effect relationship between the variables. It is generally done through laboratory and field experiments. It helps to study how actions taken now will affect a business in future ? It explores the effect of one variable on another. For example, Has new advertising campaign we designed resulted ids increased sales?
?
DATA TYPES AND SOURCES
• Types of data are classified into two types – • I. Secondary data and II. Primary data
Secondary data sources ? ? ? ? ?
Primary data sources ? ? ? ? ? ?
Company literature Syndicated reports Internet Newspapers Magazines
Demographics Lifestyles characteristics Attitudes and opinion Awareness Purchase intention Consumer behavior
METHODS OF DATA COLLECTION
Observation ? Experiments / clinical trials ? Telephone interviews ? Postal or mail questionnaire ? Personal interviews ? Panel research ? Group interview Technique ? CAPI ? Web-based questionnaire
?
LIMITATIONS OF PRIMARY DATA COLLECTION
Unwillingness of respondents to provide information ? Inability of respondents to provide information:
?
Lack of knowledge ? Lapse of memory ? Human biases of respondents: i.e. ego etc. ? Semantic difficulties: different interpretation of same question.
?
METHODS FOR SECONDARY DATA COLLECTION
Various publication of central and state gov., foreign gov., international bodies. ? Technical and trade journals ? Books, magazines and newspapers ? Report and publications of various associations connected with business and industry, banks ? Reports prepared by research scholars, in different fields. ? Public records and statistic historical documents and other sources of published information
?
doc_564488020.pptx