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Fundamentals: Ph.D. Dissertation, Master's Thesis and Research Reports


DISSERTATION, RESEARCH PROJECT, AND THESIS OUTLINE


NOTE ON TITLE SELECTION:

A. Precise identification of problem area, often including specification of independent and dependent variables and identification of target population.

B. Sufficient clarity and conciseness for indexing of title

C. Effective arrangement of words in title


CHAPTER ONE: THE PROBLEM

Introduction

Description and statement of problem

Includes demographics of the problem


Background of the problem

Sufficient delimitation of the problem area

Narrowing of the scope without becoming concerned with a trivial problem.

Trends related to the problem, unresolved issues, social - legal - policy or other concerns


Statement of the problem

Basic difficulty ‑ area of concern

Statement of basic or felt difficulty or problem situation

Significance and importance of the problem area explored in basic or applied research.

Problem is clearly stated

Data showing that the problem is significant

Assumptions are clearly stated


Purpose of the study

(Goal oriented)‑emphasizing practical outcomes or products

Succinct, precise, and unambiguous statement of the research problem (including the delineation of independent, dependent, and classificatory variables), of the major questions to be resolved, or of the objectives to be investigated

Include information from the research proposal

RATIONALE

THEORETICAL FRAMEWORK

Questions and objectives to be investigated

Distinction (if required) between problems or questions that are either factually oriented or value oriented.

ASSUMPTIONS

Conceptual And Substantive Assumptions

Postulates

Note any distinctions between the

  • 1. Purpose [which is often goal‑oriented or instrumental in relation to certain pragmatic objectives], and
  • 2. Research problem [which is primarily directed toward the finding of relationships, the making of comparisons, or the noting of changes or possible cause and effect relationships] relative to operationally formulated research hypotheses.

Statement of methodological assumption such as

1]. Adequacy of reliability and validity of measures

2]. Representativeness of sample

3]. Fulfillment of appropriate requirements for carrying out statistical tests


Rationale and theoretical framework

Based upon literature in the field when appropriate


Delineation of the research problem

Logical and orderly exposition in terms of the framework of the hypotheses, deductions, objectives, or questions asked in conjunction with the statement of the problem.

Careful analysis of known and suspected facts and explanation of existing information and knowledge that may have some bearing on problem

Systemic and orderly presentation of the interrelationship of relevant factors, facts, and concepts underlying the problem

Spell out factors giving rise to the basic difficulty, of their interrelationships, and of their relevance to the problem area.

Explication of relationships among variables or comparisons to be considered

Relationship of the problem to previous research is made clear


Statement of hypotheses

Soundness of the logic underlying selection of variables

Soundness of factors to be studied

Note the relationship of the variables and factors to the problem area

Hypotheses are clearly stated

Conceptual rendition subsequently followed by operational statements in Chapter I or in Methodology Chapter


Importance of the study

Systematic and orderly presentation of the interrelationships of relevant facts and concepts related to the problem.

May overlap with statement of problem situation


Definition of terms

Clear identification of the problem statement through use of an appropriate heading or paragraph caption (the same requirement holding for other major categories of the research).

Definitions of terms

1. Clarity in the definitions of key terms and variables (especially constructs).

2. Use of operational definitions whenever possible - will be covered in more detail in Methodology Chapter.


delimitations of the study

Imitations of the study are stated

Narrowing of focus


Summary of PROBLEM


OUTLINE OF THE THESIS OR DISSERTATION

Outline of the remainder of the thesis or proposal


CHAPTER TWO: REVIEW OF RELATED LITERATURE

overview

Introduction and Organization of the present chapter - overview

Review of the literature pertinent to the problem areas.

Evaluate the literature pertinent to the problem areas.


Historical background

(If necessary)

Purposes to be served by review of research literature

What has been previously discovered or thought

Who has done what work? 

Establish possible need for study and likelihood for obtaining meaningful, relevant, and significant results


REVIEW APPROACH

HISTORICAL OVERVIEW

THEORETICAL ISSUES

EMPIRICAL ISSUES


RELATED RESEARCH FINDINGS

THEORETICAL LITERATURE

EMPIRICAL LITERATURE

INSTRUMENTS USED


methodological issues

When and where latest research studies were completed

What approaches involving research methodology, instrumentation, and statistical analyses were followed (literature review of methodology sometimes saved for chapter on methodology)

Adequacy and relevance of the previous investigation cited with reference to the basic difficulty posed, design of the current investigation, procedures followed, and projected analysis of data.

Appropriate development of a rationale or theoretical framework from the research studies cited with reference to the current problem under investigation.

Furnish from delineation of various theoretical positions, a conceptual framework affording bases for generation of hypotheses and statement of their rationale (when appropriate)

Note: In some highly theoretical studies, the chapter "Review of Literature" may need to precede "The Problem" chapter so that the theoretical framework is established for a succinct statement of the research problem and hypotheses. In such a case, an advance organizer in the form of a brief general statement of the purpose of the entire investigation should come right at the beginning of the "Review of Literature" chapter.


LITERATURE REVIEW

General integrative reviews cited that relate to the problem situation or research problem

Specific books, monographs, and bulletins, reports, and research articles ‑ preference shown in most instances for literature of the last ten years

Unpublished materials (e.g., dissertations, theses, papers presented at recent professional meetings not yet in published form, but possibly available through ERIC)

Selection and arrangement of literature review often in terms of questions to be considered, hypotheses set forth, or objectives or specific purposes de­lineated in problem chapter


CRITIQUE OF LITERATURE


CONTRIBUTION STUDY WILL MAKE TO THE LITERATURE


Summary of literature reviewed

(Very brief)


CHAPTER THREE: METHODOLOGY OR PROCEDURES

Overview

Clear statement of the conceptions, assumptions, or postulates that underlie the problem being investigated.

Precise statement of the

(1) Hypotheses or

(2) Deduced consequences of theories or

(3) Study objectives (especially in survey and descriptive research).

Hypotheses involving relationships and comparisons.

Presentation of deducible consequences or predictions (if any) that are logically consistent with a hypothesis (i.e., antecedent‑consequent statement: If A exists, then B follows).

Important terms are defined

Largely conceptual; operational definitions


Description of research methodology or approach

(E.g., experimental, quasi-experimental, correlation, causal‑comparative, or survey)

Logic, structure, and strategy of study carefully delineated.


Research design

Research design is described fully

Spell out independent, dependent and classificatory variables and sometimes formulate an operational statement of the research hypotheses in null form so as to set the stage for an appropriate research design permitting statistical inferences.)

Distinction made between whether the research involves variables manipulated and controlled by the investigator (usually found in experimental research) or whether an ex post facto situation exists involving the analysis of data already available or collected as in most field studies and correlation investigations.

Research design is appropriate for the solution of the problem

Research design is free of specific weaknesses

Method of sampling is appropriate

Data‑gathering methods or procedures are described

Data‑gathering methods or procedures are appropriate to the solution of the problem

Data‑gathering methods or procedures are utilized correctly


NULL HYPOTHESES

OPERATIONAL DEFINITIONS


Pilot studies

As they apply to the research design, development of instruments, data collection techniques, and characteristics of the sample

Evidence of a preparatory pilot study having been conducted.


Selection of subjects

Sample described

Population described

Clear description of samples studied.

1. Mode of selection of subject cited (e.g., random assignment, matching, voluntary participation, or convenience by being available).  Weaknesses of mode noted in limitations section of this chapter

2. Data regarding how representative a sample is relative to a population.

3. Information on possible operation bias

Selective dropout and/or

"Survival of the fittest"

POPULATION

SAMPLING


Instrumentation

Adequate information pertaining to the reliability, validity, and standardization properties of instrumentation: psychometric characteristic of scales or tests used.

Tests

Measures

Observations

Scales

Questionnaire


Procedures

Field, classroom or laboratory procedures

Instructions to subjects or distribution of materials

Sufficient description of operational or field procedures followed in the collection of data‑where, when, and how data were obtained.


Data collection and recording

Coordination of the specification of the relationship between the

Null (statistical) hypotheses and the

Research (problem) hypotheses.


Data processing and analysis

Procedure clearly enough described so that other investigators can replicate (repeat) the study performed under essentially comparable conditions in the future.

Note the appropriateness of the statistical treatment and data processing procedures.

Statistical analysis


ELEMENTARY DESCRIPTIVE STATISTICS


Percentages, proportions, ratios, tables, charts, and graphs are all common techniques used for presenting research results.

Proportions and percentages standardize raw data to the base of 1.00 and 100 respectively. They are easier to read and understand than frequencies when comparing groups of different sizes.

Proportion (p) is the value calculated by dividing the quantity in one category by the total of all categories.

(p) =f/N

Percentage (%) is a proportion that has been multiplied by one hundred.

% = (f/N) x 100,

Where f = frequency, the number of cases in any category

           N = the number of cases in all categories

Percentages and proportions are sensitive to small sample sizes (i.e., fewer than 20) and hence frequencies are the preferred statistic to report. Also when reporting proportions and percentages always report the number of observations as it helps judge the adequacy of the sample size and also prevents the researcher from lying.[1]


RATIOS AND RATES


Ratio is the number of cases in one category divided by the number of cases in another category (i.e., males: females). They give a precise measure of the relative frequency by telling the researcher the exact way one category outnumbers the other.   Ratio = f1/f2

Where f1= the number of cases in the first category

           F2 = the number of cases in the second category

Rate is a ratio of the actual occurrence in a group category by the number of possible occurrences per some unit of time. Rates are multiplied by some power of 10 toe eliminate decimal points. For example, the crude death rate for a population is defined as the number of deaths in that population (actual occurrences) divided by the number of people in the population (possible occurrences) per year. The formula is as follows:


Initial consideration would have to be given to the population's sex ratio, birth rate, general fertility rate, age specific rate, completed fertility rates, child-woman ratios, abortion rates, abortion ratios, death rates, age-specific death rates, cause specific death rates, proportion dying of a specific cause, infant mortality rate, maternal mortality rates, life expectancy, incidence rate, prevalence rate, case rate, case fatality rate, immigration rate, emigration rate, net migration rate, balancing equation, natural increase, rate of natural increase, and doubling time.  Instead of the incomplete fragments of records, indigenous population must be extrapolated from a base population (p1) to present using the tools of demography.Included would be:

Population Size. The total number of inhabitants of a specified area at a specified date.

Census Enumeration. An organized campaign to count the number of inhabitants residing within a specified area as of a specified date, enumerating their demographic, social, and economic characteris­tics in the process. 

Population Change. Increase or decrease in population size between two dates.

Average Annual Rate of Change. The average percentage increase or decrease per annum required to ac­count for the population change between two dates.

Components of Population Change. Births, deaths, immigration, and emigration.

Reproductive Change (Natural Increase). Births minus deaths.

Crude Birth Rate. Number of births during a year per 1,000 midyear population in that year.

Crude Death Rate. Number of deaths during a year per 1,000 midyear population in that year.

Net Migration Rate. Amount of net migration during a year per 1,000 midyear population in that year.

Population Projection. Estimate of what the population will be at a future date, based on assumptions about the future course of birth, death, and migration rates.

Crude death rate=Number of deaths in year x 1000

                                    Total Population




[1]



FUNDAMENTALS OF ORGANIZATION: DATA MATRIX


The Data Matrix

The entry point into descriptive statistics is the data matrix. When dealing with a lot of data: Organize the data Summarize data in such a way important info is preserved and the rest is deleted. Do this by a data matrix: rows = cases columns=variables the data matrix is a table identifying each subject (case) and Showing his/her (person, subject, or case) score on each Variable in the study.  Data from the matrix can be readily summarized by a frequency distribution.

How to construct data matrix List persons by subject number in rows of a matrix.  Begin with the lowest subject number and list in numerical order to the highest. Label variables in the columns of the matrix. Assign numerical values to non-numerical variables.  Enter appropriate value for each person in appropriate column for numerical values; enter the value of each person inappropriate column. Descriptive Statistics Descriptive statistics is "the branch of statistics concerned with summarizing the distribution of a single variable or (2) measuring the relationship between two or more variables."


A major goal of single variable descriptive statistical procedures is called data reduction ("The process of allowing a few numbers to summarize many numbers"). Descriptive statistics that measure the relationship between two or more variables are called measures of association ("statistics that summarize the strength and direction of the relationship between variables").  Both vicariate (two variable) and multivariate (more than two variables) descriptive statistics recovered in later pages. The next page illustrates a summary of descriptive data analysis.  This section will explain the elements of the diagramming more detail. Single Variable Descriptive Statistics.


We can look at single variable descriptive statistics within three realms: The whole distribution of the variable the centrality of the variable and the dispersion of the variable. The data matrix organizes and summarizes data so that important information is preserved and the irrelevant information discarded. This matrix identifies each subject or case and shows his/her score on each variable in the study. In SPSS 16.0 the rows represent the cases (i.e., subjects) and the columns the variables (i.e., questions). Data from the matrix can be readily summarized by a frequency distribution. In sum, a data matrix is a table or matrix of scores in which persons, subjects, or cases are listed in rows and the information collected on each subject is listed along the columns of each table.[1]

STATISTICAL PROCEDURE: CONSTRUCT DATA MATRIX


  • 1. List person by subject or case number in rows of a matrix. Begin with the lowest subject number and list in numerical order to the highest.
  • 2. Label the variables in the columns of the matrix.
  • 3. Assign numerical values to non-numerical variables. Enter the appropriate value for each person in the appropriate column.
  • 4. For numerical values enter the value of each person in the appropriate column.

In looking at the whole distribution, we would use such techniques as: Percentages or proportions Ratios or rates Frequency distributions Graphs In order to describe a distribution, one must know the location obits center or its average value and the amount of its spread (variability).


In looking at the variable's central tendency, we would use, as appropriate to the variable's level of measurement, such techniques as: Mode Median Mean In looking at the variable's dispersion, we would use, as appropriate to the variable's level of measurement, such techniques as: Range Semi-interquartile range Standard deviation Variance All of these will be explained in the next sections.

Ratios and Rates" Ratios are especially useful for comparing categories in terms of relative frequency...Ratios are a precise measure of the relative frequency of one category per unit of the other category."

Ratios are determined by dividing the frequency of one category by the frequency of another. Ratio =where    = the number of cases in the first category= the number of cases in the second category" Ratios are often multiplied by some power of 10 to eliminate decimal points...  To ensure clarity, the comparison units for the ratio are often expressed as well.

Rates are defined as the number of actual occurrences of some Phenomenon divided by the number of possible occurrences presume unit of time. For example:    If there were 100 deaths during a given year in town of 7000 people, what is the crude death rate? Crude death rate =


Descriptive Statistics:  Looking at the whole distribution Percentages and Proportions" Percentages and proportions supply a frame of reference for reporting research results in the sense that they standardize the raw data: percentages to the base of 100 and proportions to the base of 1.00."

Percentage (%)      = f   X   100NProportion (p)  = f N where f = frequency, the number of cases in any category N= the number of cases in all Some tips when using percentages or proportions is: With small samples (N<20), "it is usually preferable to report the actual frequencies... With a small number of cases, the percentages can change drastically with relatively minor changes in data.

Always report the number of observations with % and p's, as this permits the reader to judge the adequacy of the sample size.

Data Organization-Frequency Distributions: A frequency distribution is a table that summarizes the distribution of a variable by listing categories or scores and the frequency of each.  It orders scores values from the lowest to the highest and gives the number of subjects earning the score value. One general rule is that the categories must be exhaustive and mutually exclusive.  Basically, each case will fall within only one category. Frequency distributions can be grouped or ungrouped. 

An ungrouped frequency distribution has one score value per interval.  A grouped frequency distribution has two or more score values within each interval.

Validity and reliability of the evidence gathered are established

Appropriate methods are selected to analyze the data

Methods utilized in analyzing the data are applied correctly

Results of the analysis are presented clearly


Methodological assumptions

State all of the methodological assumptions.


Limitations

Weaknesses

Possible restatement of

a].  Conceptual hypotheses from problem chapter in operational form relative to instrumentation and experimental procedure

b].  Design followed (operationally stated hypotheses can also be put in null form to furnish an optional third set of hypotheses amenable to statistical testing)‑if not done elsewhere.


Conceptual hypotheses

Restate conceptual hypotheses from problem chapter in operational form relative to instrumentation and experimental procedures or design followed.

Operationally stated hypotheses can also be put in null form to furnish an optional third set of hypotheses amenable to statistical testing if not done elsewhere.


Summary of METHODOLOGY OR PROCEDURES

Brief review


CHAPTER FOUR: RESULTS AND FINDINGS


INTRODUCTION


DESCRIPTION OF DATA COLLECTION


DEMOGRAPHIC DATA


RESULTS [BASED ON ORGANIZATION OF HYPOTHESES OR FINDINGS

In addition to text, findings are presented in tables or charts when appropriate

Findings reported with respect to furnishing evidence for each question asked or each hypothesis posed in problem statement

Appropriate headings are established to correspond to each main question or hypothesis considered

Factual information is kept separate from interpretation, inference, and evaluation (one section for findings and one section for interpretation or discussion)

Appropriate use of paradigms, flow charts, or schematic models.

Appropriate and clear use of charts, tables, figures, and graphs.

In certain historical, case‑study and anthropological investigations, factual and interpretive material may need to be interwoven to sustain interest level, although the text should clearly reveal what is fact and what is interpretation.


NON-PREDICTED NONSIGNIFICANT FINDINGS Discussion

Specification of threats to external and internal validity of the design employed.

1. Present objective findings rather than subjective or speculative presentation.

2. Analysis consistent with and supported by the facts obtained.

3. Make sure that there is an absence of over generalizations or sweeping statements that go beyond the data.

4. Relationships of the findings to previously cited research explicitly shown.

5. Negative findings relative to the hypotheses as well as positive findings presented with minimal distortion or bias.

6. Uncontrolled factors influencing data outcomes appropriately cited and discussed.

7. Weaknesses in the data honestly conceded and discussed with appropriate emphases.

8. Lack of confusion between facts and inferences clearly shown‑separation of analysis of findings from interpretation and discussion of findings.

9. Resolution of contradictions, inconsistencies, or misleading elements in the findings


Interpretation

Evaluation [ties together findings in relation to theory, review of literature, or rationale


Summary of FINDINGS, ANALYSIS, AND EVALUATION


CHAPTER 5: SUMMARY AND CONCLUSIONS


Brief Summary

Everything covered in first three chapters and in findings portion of Chapter Four


METHODOLOGY

SUBJECTS

INSTRUMENTATION

PROCEDURE


RESULTS


CONCLUSIONS

STATISTICAL ANALYSIS

THEORETICAL UNDERSTANDING


Conclusions

A. Precise and accurate statement of the

(1) Problem,

(2) Methodology followed, and

(3) Findings [without the introduction of new or irrelevant information]

B. Conclusions at a scope and level of generality justified by the data presented.

C. Appropriate caution exercised and necessary qualifications made in drawing conclusions.

D. Conclusions in a form that other investigators can understand and subsequently verify.

E. Conclusions coordinated with the tentative acceptance or rejection of the research hypotheses presented or with the objectives or questions posed.

"So what" of findings

Hypotheses may be restated as inferences with some degree of definitive commitment and generalizability

Conclusion are clearly stated

The evidence presented substantiates conclusions

Generalizations are confined to the population from which the sample was drawn


ALTERNATIVE EXPLANATIONS OF THE FINDINGS


LIMITATIONS


IMPLICATIONS

CHANGES IN POLICY,

KNOWLEDGE,

THEORY,

PRACTICES, AND/OR

PROCEDURES 


RECOMMENDATIONS FOR FURTHER RESEARCH

Practical suggestions for implementation of findings or for additional research

New questions set forth for possible investigation‑recommendations for additional research in the problem area study.

Recommendations concerning implementation of the research findings when appropriate relative to the objectives stated in the purpose of the investigation (most frequently encountered in survey studies and action research).


SUMMARY


NOTE:

Report is clearly written

  Report is logically organized

Tone of the report displays an unbiased, impartial scientific attitude

Past tense is used in all areas of the report.

Explain, in great detail any deviation from the research protocol.

Carefully document all audit requirements

APA manual is used appropriately





[1]

The entry point into descriptive statistics is the data matrix. When dealing with a lot of data: Organize the data Summarize data in such a way important info is preserved and the rest is deleted. Do this by a data matrix: rows = cases columns=variables the data matrix is a table identifying each subject (case) and Showing his/her (person, subject, or case) score on each Variable in the study.  Data from the matrix can be readily summarized by a frequency distribution.

How to construct data matrix List persons by subject number in rows of a matrix.  Begin with the lowest subject number and list in numerical order to the highest. Label variables in the columns of the matrix. Assign numerical values to non-numerical variables.  Enter appropriate value for each person in appropriate column for numerical values; enter the value of each person inappropriate column. Descriptive Statistics Descriptive statistics is "the branch of statistics concerned with summarizing the distribution of a single variable or (2) measuring the relationship between two or more variables."


A major goal of single variable descriptive statistical procedures is called data reduction ("The process of allowing a few numbers to summarize many numbers"). Descriptive statistics that measure the relationship between two or more variables are called measures of association ("statistics that summarize the strength and direction of the relationship between variables").  Both vicariate (two variable) and multivariate (more than two variables) descriptive statistics recovered in later pages. The next page illustrates a summary of descriptive data analysis.  This section will explain the elements of the diagramming more detail. Single Variable Descriptive Statistics.


We can look at single variable descriptive statistics within three realms: The whole distribution of the variable the centrality of the variable and the dispersion of the variable. The data matrix organizes and summarizes data so that important information is preserved and the irrelevant information discarded. This matrix identifies each subject or case and shows his/her score on each variable in the study. In SPSS 16.0 the rows represent the cases (i.e., subjects) and the columns the variables (i.e., questions). Data from the matrix can be readily summarized by a frequency distribution. In sum, a data matrix is a table or matrix of scores in which persons, subjects, or cases are listed in rows and the information collected on each subject is listed along the columns of each table.[1]

STATISTICAL PROCEDURE: CONSTRUCT DATA MATRIX


  • 1. List person by subject or case number in rows of a matrix. Begin with the lowest subject number and list in numerical order to the highest.
  • 2. Label the variables in the columns of the matrix.
  • 3. Assign numerical values to non-numerical variables. Enter the appropriate value for each person in the appropriate column.
  • 4. For numerical values enter the value of each person in the appropriate column.

In looking at the whole distribution, we would use such techniques as: Percentages or proportions Ratios or rates Frequency distributions Graphs In order to describe a distribution, one must know the location obits center or its average value and the amount of its spread (variability).


In looking at the variable's central tendency, we would use, as appropriate to the variable's level of measurement, such techniques as: Mode Median Mean In looking at the variable's dispersion, we would use, as appropriate to the variable's level of measurement, such techniques as: Range Semi-interquartile range Standard deviation Variance All of these will be explained in the next sections.

Ratios and Rates" Ratios are especially useful for comparing categories in terms of relative frequency...Ratios are a precise measure of the relative frequency of one category per unit of the other category."

Ratios are determined by dividing the frequency of one category by the frequency of another. Ratio =where    = the number of cases in the first category= the number of cases in the second category" Ratios are often multiplied by some power of 10 to eliminate decimal points...  To ensure clarity, the comparison units for the ratio are often expressed as well.

Rates are defined as the number of actual occurrences of some Phenomenon divided by the number of possible occurrences presume unit of time. For example:    If there were 100 deaths during a given year in town of 7000 people, what is the crude death rate? Crude death rate =


Descriptive Statistics:  Looking at the whole distribution Percentages and Proportions" Percentages and proportions supply a frame of reference for reporting research results in the sense that they standardize the raw data: percentages to the base of 100 and proportions to the base of 1.00."

Percentage (%)      = f   X   100NProportion (p)  = f N where f = frequency, the number of cases in any category N= the number of cases in all Some tips when using percentages or proportions is: With small samples (N<20), "it is usually preferable to report the actual frequencies... With a small number of cases, the percentages can change drastically with relatively minor changes in data.

Always report the number of observations with % and p's, as this permits the reader to judge the adequacy of the sample size.

Data Organization-Frequency Distributions: A frequency distribution is a table that summarizes the distribution of a variable by listing categories or scores and the frequency of each.  It orders scores values from the lowest to the highest and gives the number of subjects earning the score value. One general rule is that the categories must be exhaustive and mutually exclusive.  Basically, each case will fall within only one category. Frequency distributions can be grouped or ungrouped. 

An ungrouped frequency distribution has one score value per interval.  A grouped frequency distribution has two or more score values within each interval.

Validity and reliability of the evidence gathered are established

Appropriate methods are selected to analyze the data

Methods utilized in analyzing the data are applied correctly

Results of the analysis are presented clearly


Methodological assumptions

State all of the methodological assumptions.


Limitations

Weaknesses

Possible restatement of

a].  Conceptual hypotheses from problem chapter in operational form relative to instrumentation and experimental procedure

b].  Design followed (operationally stated hypotheses can also be put in null form to furnish an optional third set of hypotheses amenable to statistical testing)‑if not done elsewhere.


Conceptual hypotheses

Restate conceptual hypotheses from problem chapter in operational form relative to instrumentation and experimental procedures or design followed.

Operationally stated hypotheses can also be put in null form to furnish an optional third set of hypotheses amenable to statistical testing if not done elsewhere.


Summary of METHODOLOGY OR PROCEDURES

Brief review


CHAPTER FOUR: RESULTS AND FINDINGS


INTRODUCTION


DESCRIPTION OF DATA COLLECTION


DEMOGRAPHIC DATA


RESULTS [BASED ON ORGANIZATION OF HYPOTHESES OR FINDINGS

In addition to text, findings are presented in tables or charts when appropriate

Findings reported with respect to furnishing evidence for each question asked or each hypothesis posed in problem statement

Appropriate headings are established to correspond to each main question or hypothesis considered

Factual information is kept separate from interpretation, inference, and evaluation (one section for findings and one section for interpretation or discussion)

Appropriate use of paradigms, flow charts, or schematic models.

Appropriate and clear use of charts, tables, figures, and graphs.

In certain historical, case‑study and anthropological investigations, factual and interpretive material may need to be interwoven to sustain interest level, although the text should clearly reveal what is fact and what is interpretation.


NON-PREDICTED NONSIGNIFICANT FINDINGS Discussion

Specification of threats to external and internal validity of the design employed.

1. Present objective findings rather than subjective or speculative presentation.

2. Analysis consistent with and supported by the facts obtained.

3. Make sure that there is an absence of over generalizations or sweeping statements that go beyond the data.

4. Relationships of the findings to previously cited research explicitly shown.

5. Negative findings relative to the hypotheses as well as positive findings presented with minimal distortion or bias.

6. Uncontrolled factors influencing data outcomes appropriately cited and discussed.

7. Weaknesses in the data honestly conceded and discussed with appropriate emphases.

8. Lack of confusion between facts and inferences clearly shown‑separation of analysis of findings from interpretation and discussion of findings.

9. Resolution of contradictions, inconsistencies, or misleading elements in the findings


Interpretation

Evaluation [ties together findings in relation to theory, review of literature, or rationale


Summary of FINDINGS, ANALYSIS, AND EVALUATION


CHAPTER 5: SUMMARY AND CONCLUSIONS


Brief Summary

Everything covered in first three chapters and in findings portion of Chapter Four


METHODOLOGY

SUBJECTS

INSTRUMENTATION

PROCEDURE


RESULTS


CONCLUSIONS

STATISTICAL ANALYSIS

THEORETICAL UNDERSTANDING


Conclusions

A. Precise and accurate statement of the

(1) Problem,

(2) Methodology followed, and

(3) Findings [without the introduction of new or irrelevant information]

B. Conclusions at a scope and level of generality justified by the data presented.

C. Appropriate caution exercised and necessary qualifications made in drawing conclusions.

D. Conclusions in a form that other investigators can understand and subsequently verify.

E. Conclusions coordinated with the tentative acceptance or rejection of the research hypotheses presented or with the objectives or questions posed.

"So what" of findings

Hypotheses may be restated as inferences with some degree of definitive commitment and generalizability

Conclusion are clearly stated

The evidence presented substantiates conclusions

Generalizations are confined to the population from which the sample was drawn


ALTERNATIVE EXPLANATIONS OF THE FINDINGS


LIMITATIONS


IMPLICATIONS

CHANGES IN POLICY,

KNOWLEDGE,

THEORY,

PRACTICES, AND/OR

PROCEDURES 


RECOMMENDATIONS FOR FURTHER RESEARCH

Practical suggestions for implementation of findings or for additional research

New questions set forth for possible investigation‑recommendations for additional research in the problem area study.

Recommendations concerning implementation of the research findings when appropriate relative to the objectives stated in the purpose of the investigation (most frequently encountered in survey studies and action research).


SUMMARY


NOTE:

Report is clearly written

  Report is logically organized

Tone of the report displays an unbiased, impartial scientific attitude

Past tense is used in all areas of the report.

Explain, in great detail any deviation from the research protocol.

Carefully document all audit requirements

APA manual is used appropriately





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