Session 6 Session 6

ReviewReview

Name 5 types of research.Name 5 types of research. What are the 2 types of Research, by Philosophy?What are the 2 types of Research, by Philosophy? What are the 4 purposes of research?What are the 4 purposes of research? What are the Criteria for Research Project?What are the Criteria for Research Project? What is a Population in terms of research?What is a Population in terms of research? What is the purpose of a review of literature?What is the purpose of a review of literature? Where can you go to do a review of literature?Where can you go to do a review of literature? Why is sampling important?Why is sampling important?

Now Your Now Your AssignmentAssignment

The two articles to review…..The two articles to review….. Open ended…..not much direction--for a reason…Open ended…..not much direction--for a reason… Ask for a short summary, ½ to 1 page, of what you Ask for a short summary, ½ to 1 page, of what you

can learn or tell me about the research. can learn or tell me about the research. Last week we had discussed different kinds of Last week we had discussed different kinds of

research, etc…..based just on that discussion research, etc…..based just on that discussion alone you might come up with some things to look alone you might come up with some things to look for associated with each article….for associated with each article….

What can be learned from a What can be learned from a research article?research article?

Purpose of any research article is to share Purpose of any research article is to share results results – Conclusions & RecommendationsConclusions & Recommendations

Before you accept the conclusions and Before you accept the conclusions and recommendations of any research article recommendations of any research article whatwhat do you need to know? do you need to know?

What Did You Learn From Your What Did You Learn From Your Review of the Two Articles? Review of the Two Articles?

What kind of study was this?What kind of study was this?– SurveySurvey– ExperimentalExperimental– Historical Historical – ExperimentalExperimental– CorrelationalCorrelational– EvaluationEvaluation– NaturalisticNaturalistic

What was the purpose of the study? What was the purpose of the study? – What were the research questions? Were they questions or hypotheses?What were the research questions? Were they questions or hypotheses?

What was the population? What was the population? – Was there a sample? Did the paper describe how the sample was taken?Was there a sample? Did the paper describe how the sample was taken?– How big was the sample? Did it describe how they determine sample sizeHow big was the sample? Did it describe how they determine sample size

Was it qualitative or quantitative? How can you tell?Was it qualitative or quantitative? How can you tell? Did the author give a good intro to the problem?Did the author give a good intro to the problem? Describe the methods used?Describe the methods used? What statistics were used? What statistics were used? How was the paper divided? What were the sections?How was the paper divided? What were the sections?

Article 1: Article 1:

What kind of study was this?What kind of study was this? What was the purpose of the study?What was the purpose of the study? What was the population?What was the population? Was it qualitative or quantitative? How can you Was it qualitative or quantitative? How can you

tell?tell? Did the author give a good intro to the problem?Did the author give a good intro to the problem? Describe the methods used?Describe the methods used? What statistics were used?What statistics were used?

Article 2: Evaluation of a Livestock Article 2: Evaluation of a Livestock Ethics Curriculum for High School YouthEthics Curriculum for High School Youth

What kind of study was this? What kind of study was this? This used a quasi-experimental designThis used a quasi-experimental design What was the population? What was the population? Agricultural Education students from Indiana high schoolsAgricultural Education students from Indiana high schools ..

– Was there a sample?  yesWas there a sample?  yes– Did the paper describe how the sample was taken? yesDid the paper describe how the sample was taken? yes– How big was the sample? 305 studentsHow big was the sample? 305 students– Did it describe how they determine sample size? noDid it describe how they determine sample size? no

Was it qualitative or quantitative?   Was it qualitative or quantitative?   QualitativeQualitative How can you tell? How can you tell? Answered questions like a surveyAnswered questions like a survey What was the purpose of the study? What was the purpose of the study? Evaluate effectiveness of a livestock ethics curriculum developed for high Evaluate effectiveness of a livestock ethics curriculum developed for high

school students in Agricultural Education classes.school students in Agricultural Education classes.– Are participants aware of the principles involved in making ethical choices when faced with decisions in youth Are participants aware of the principles involved in making ethical choices when faced with decisions in youth

livestock programs?livestock programs?– Are participants able to determine whether certain practices at a youth livestock show are ethical or unethical?Are participants able to determine whether certain practices at a youth livestock show are ethical or unethical?– Will participants make ethical choices when faced with decisions in youth livestock programs as demonstrated Will participants make ethical choices when faced with decisions in youth livestock programs as demonstrated

by real life case study analysis?by real life case study analysis?– Will demographics such as current grade in school, gender, years enrolled in 4-H, years enrolled in FFA, years Will demographics such as current grade in school, gender, years enrolled in 4-H, years enrolled in FFA, years

enrolled in beef, swine, sheep. Horse, dairy, and other livestock projects, or previous participation in a livestock enrolled in beef, swine, sheep. Horse, dairy, and other livestock projects, or previous participation in a livestock ethics curriculum; help explain the difference in pre and post-test scores amongst participants?ethics curriculum; help explain the difference in pre and post-test scores amongst participants?

Pre-test and post-test; given before and after the curriculum is taught.Pre-test and post-test; given before and after the curriculum is taught. Describe the methods used? Describe the methods used? Stats used? Stats used? Descriptive. Descriptive. What were the parts of the article? What were the parts of the article?

Article 3: Teacher Attrition Among Women Article 3: Teacher Attrition Among Women in Secondary Agricultural Educationin Secondary Agricultural Education

What kind of study was this? What kind of study was this? Mixed-method case studyMixed-method case study What was the population? What was the population? Female students who took at least one Female students who took at least one

pre service course at Oklahoma State University between 1999 to 2004.pre service course at Oklahoma State University between 1999 to 2004. n=36; N=78n=36; N=78

Was it qualitative or quantitative? Was it qualitative or quantitative? Qualitative, it says soQualitative, it says so.. Purpose of the Study? Purpose of the Study? To investigate female under-To investigate female under-

representation in AGED through the lens of Grissmer & Kirby’s representation in AGED through the lens of Grissmer & Kirby’s theory of teacher attrition to better understand this phenomenon.theory of teacher attrition to better understand this phenomenon.

Res QuestionsRes Questions Profile the women demographically.Profile the women demographically. Analyze attrition trends of the students in the pre service program.Analyze attrition trends of the students in the pre service program. Qualitatively explore women’s experiences in the AGED context.Qualitatively explore women’s experiences in the AGED context.

Methods? Methods? Interviews; semi-structured interview protocol.Interviews; semi-structured interview protocol. Stats? Stats? DescriptiveDescriptive

Article 4: A Study of Supervisor and Employee Article 4: A Study of Supervisor and Employee Perceptions of Work Attitudes in Information Perceptions of Work Attitudes in Information

Age Manufacturing Industries.Age Manufacturing Industries. What kind of study was this?What kind of study was this? Experimental designExperimental design What was the population?What was the population? Employees of manufacturing industries in central Illinois area.Employees of manufacturing industries in central Illinois area. Sample group? Sample group? Cluster sampling (without replacement where each industry was treated as a cluster)Cluster sampling (without replacement where each industry was treated as a cluster) -1209 for six industries-1209 for six industries -yes; n=N/(N(d)^2+1) where n = sample size, N= total population, d= level of significance (0.05)-yes; n=N/(N(d)^2+1) where n = sample size, N= total population, d= level of significance (0.05) Was it qualitative or quantitative?Was it qualitative or quantitative? Qualitative, Qualitative, used questionnaires used questionnaires What was the purpose of the study?What was the purpose of the study? To investigate (a) whether the type of job (i.e. information job To investigate (a) whether the type of job (i.e. information job

versus non-information job) was related to employee work attitudes. (b) if there existed any difference between versus non-information job) was related to employee work attitudes. (b) if there existed any difference between work attitudes as perceived by employees and as perceived by their supervisors, and (c) if there existed any work attitudes as perceived by employees and as perceived by their supervisors, and (c) if there existed any relationship between employee work attitudes and demographic variables such as age, gender, level of relationship between employee work attitudes and demographic variables such as age, gender, level of education, and length of service.education, and length of service.

– Hypotheses:Hypotheses: H01: At the pH01: At the p 0.05 level of confidence, there is no significant difference between the self-perceptions of work attitudes of industrial 0.05 level of confidence, there is no significant difference between the self-perceptions of work attitudes of industrial

employees with information jobs and their work attitudes as rated by their supervisors.employees with information jobs and their work attitudes as rated by their supervisors. H02: At the pH02: At the p 0.05 level of confidence, there is no significant difference between the self-perceptions of work attitudes of industrial 0.05 level of confidence, there is no significant difference between the self-perceptions of work attitudes of industrial

employees with non-information jobs and their work attitudes of industrial jobs and their work attitudes as rated by their supervisors.employees with non-information jobs and their work attitudes of industrial jobs and their work attitudes as rated by their supervisors. H03: At the pH03: At the p 0.05 level of confidence, there is no significant difference between the perceptions of work attitudes of industrial 0.05 level of confidence, there is no significant difference between the perceptions of work attitudes of industrial

employees with non-informational jobs and industrial employees with information jobs.employees with non-informational jobs and industrial employees with information jobs. H04: At the pH04: At the p 0.05 level of confidence, there is no significant relationship between the work attitudes of information employees and the 0.05 level of confidence, there is no significant relationship between the work attitudes of information employees and the

variables of gender, age, level of education, and length of service.variables of gender, age, level of education, and length of service. H05: At the pH05: At the p 0.05 level of confidence, there is no significant relationship between the work attitudes of non- 0.05 level of confidence, there is no significant relationship between the work attitudes of non-

information information Describe the methods used?Describe the methods used? Stats?Stats?

For TonightFor Tonight

Statistics for TeachersStatistics for Teachers

Based on:Based on:Hyperstat Online and Learning Statistics Through Hyperstat Online and Learning Statistics Through

Playing Cards by Thomas R. Knapp (1996)Playing Cards by Thomas R. Knapp (1996)Adapted by: Adapted by: Tammie Pannells and David AgnewTammie Pannells and David Agnew

StatisticsStatistics“If you can assign a number to it, “If you can assign a number to it,

you can measure it”you can measure it”Dr. W. Edward DemmingDr. W. Edward Demming

StatisticsStatistics– refers to calculated quantities regardless of whether or refers to calculated quantities regardless of whether or

not they are from a sample not they are from a sample – is defined as a numerical quantity is defined as a numerical quantity – Often used incorrectly to refer to a range of techniques Often used incorrectly to refer to a range of techniques

and procedures for analyzing data, interpreting data, and procedures for analyzing data, interpreting data, displaying data, and making decisions based on data. displaying data, and making decisions based on data. Because that is the basic learning outcomes of a Because that is the basic learning outcomes of a statistics course. statistics course.

Stating the ProblemStating the Problem Developing a hypothesisDeveloping a hypothesis::

– Methods: estimation and hypothesis testing.Methods: estimation and hypothesis testing. Estimation, the sample is used to estimate a Estimation, the sample is used to estimate a

parameterparameter and a and a confidence intervalconfidence interval about the about the estimate is constructed. estimate is constructed.

– Parameter: Parameter: numerical quantity measuring some numerical quantity measuring some aspect aspect

– Confidence Interval: Confidence Interval: range of values that estimates a range of values that estimates a parameter for a high proportion of the time parameter for a high proportion of the time

Hypothesis Testing: the most common useHypothesis Testing: the most common use– Hypothesis: an intelligent guess or assumption that guides Hypothesis: an intelligent guess or assumption that guides

the design of the studythe design of the study– Null hypothesis: there is no difference or there is no effectNull hypothesis: there is no difference or there is no effect– Alternative hypothesis: there is a difference or there is an Alternative hypothesis: there is a difference or there is an

effecteffect– Hypotheses: more than hypothesis, which are related to the Hypotheses: more than hypothesis, which are related to the

populationpopulation

Inferential statisticsInferential statistics

Inferential statisticsInferential statistics– Infers or implies something about Infers or implies something about populationpopulation from a from a

samplesample.. Population: A total group Population: A total group Sample: A few from the whole groupSample: A few from the whole group Representative sample: a sample that is equally Representative sample: a sample that is equally

propionate to the populationpropionate to the population Random Sample: a sample that is chosen strictly by Random Sample: a sample that is chosen strictly by

chance is not “hand-picked”chance is not “hand-picked”– Probability: the percentage of change that an event will Probability: the percentage of change that an event will

occuroccur

VariablesVariables

A variable: any measured characteristic or attribute that differs for A variable: any measured characteristic or attribute that differs for different subjects. different subjects.

Two types:Two types:– Quantitative: Quantitative: sometimes called "categorical variables.“sometimes called "categorical variables.“

measured on one of three scales:measured on one of three scales:– Ordinal: first second or third choice (most of the children Ordinal: first second or third choice (most of the children

preferred red popsicles, and grape was the second choice)preferred red popsicles, and grape was the second choice)– Interval: direct time periods between two events ( time it Interval: direct time periods between two events ( time it

takes a child to respond to a question)takes a child to respond to a question)– Ratio scale: compares the number of times one event Ratio scale: compares the number of times one event

happens in comparison to another event. (example: the happens in comparison to another event. (example: the number of time a black card is pulled in comparison to the number of time a black card is pulled in comparison to the number of times a red card is pulled) number of times a red card is pulled)

– Qualitative:Qualitative: measured on a measured on a nominalnominal scale. scale.

VariablesVariables Two categories:Two categories: IndependentIndependent

– Variables in an experiment or study which are Variables in an experiment or study which are not easily to be manipulated without changing not easily to be manipulated without changing the participants. the participants. Age, gender, year, classroom teacher, any Age, gender, year, classroom teacher, any

personal background data, etcpersonal background data, etc DependentDependent

– Variables which are changed in an experimentVariables which are changed in an experiment Hours of sleep, amount of food, time given to Hours of sleep, amount of food, time given to

complete an activity, curriculum, instructional complete an activity, curriculum, instructional method, etc.method, etc.

Descriptive statisticsDescriptive statistics Descriptive statisticsDescriptive statistics

– summarize a collection of data in a clear and understandable way. summarize a collection of data in a clear and understandable way. Example: Scores of 500 children on all parts of a standardized test.Example: Scores of 500 children on all parts of a standardized test. Methods: numerical and graphical. Methods: numerical and graphical.

– Numerical: more precise- uses numbers as accurate measureNumerical: more precise- uses numbers as accurate measure meanmean the arithmetic average which is calculated by adding a the arithmetic average which is calculated by adding a

the scores or totals and then dividing by the number of the scores or totals and then dividing by the number of scores.scores.

standard deviation.standard deviation. These statistics convey information These statistics convey information about the average degree of shyness and the degree to about the average degree of shyness and the degree to which people differ in shyness. which people differ in shyness.

– Graphical: better for identifying patternsGraphical: better for identifying patterns stem and leaf displaystem and leaf display : a graphical method of displaying data : a graphical method of displaying data

to show how several data are aligned on a graphto show how several data are aligned on a graph box plot. Graphical method to show what data are included. box plot. Graphical method to show what data are included.

The box stretches from the 25th percentile to the the 75th The box stretches from the 25th percentile to the the 75th percentile percentile

historgrams. historgrams. Since the numerical and graphical approaches compliment each Since the numerical and graphical approaches compliment each

other, it is wise to use both.other, it is wise to use both.

Data AnalysisData Analysis Explaining and interpreting the data:Explaining and interpreting the data:

– Data are pluralData are plural You are looking at more than one number or group of numbers; You are looking at more than one number or group of numbers;

subject-verb agreement is important when writing. subject-verb agreement is important when writing. Central Tendency: measures of the location of the middle or the center Central Tendency: measures of the location of the middle or the center

of the whole data base for a variable or group of variablesof the whole data base for a variable or group of variables– Frequency: the number of times a number appearsFrequency: the number of times a number appears– Mean: the arithmetic averageMean: the arithmetic average– Mode: the number that appears most oftenMode: the number that appears most often– Median: the number in the middle when numbers are arranged by Median: the number in the middle when numbers are arranged by

valuevalue– Skew: A distribution is skewed if one of its tails is longer than the Skew: A distribution is skewed if one of its tails is longer than the

other. Data may be skewed positively or negatively. other. Data may be skewed positively or negatively. Standard deviation: the amount of variance between each sigmaStandard deviation: the amount of variance between each sigma

Parameters or Parametric DataParameters or Parametric Data Parameter: a numerical Parameter: a numerical

quantity measuring some quantity measuring some aspect of a population of aspect of a population of scores. scores. – Parameters are usually Parameters are usually

estimated by statistics estimated by statistics computed in samples computed in samples

Quantity Parameter Quantity Parameter Greek letters are Greek letters are commonly accepted for commonly accepted for writing formulaswriting formulas

Statistical symbols are Statistical symbols are most common in most common in reporting actual data reporting actual data analysis in reports or analysis in reports or articles. articles.

Quantity Quantity Parameter Parameter Statistic Statistic

MeanMean μμ MM

Standard deviationStandard deviation σσ ss

ProportionProportion ππ pp

CorrelationCorrelation ρρ rr

Greek letters are used to designate parameters

Tools for MeasuringTools for Measuring

Measurement is the assignment of numbers to objects or Measurement is the assignment of numbers to objects or events in a systematic fashion. events in a systematic fashion. – Four levels:Four levels:

nominal: assigning items to groups or categories nominal: assigning items to groups or categories – Examples: Classroom, color, sizeExamples: Classroom, color, size

Ordinal: ordered in the sense that higher numbers represent higher Ordinal: ordered in the sense that higher numbers represent higher values values

– Examples 1= freshmen, 2= sophomoreExamples 1= freshmen, 2= sophomore Interval: one unit on the scale represents the same magnitude on the Interval: one unit on the scale represents the same magnitude on the

trait or characteristic being measured across the whole range of the trait or characteristic being measured across the whole range of the scale. scale.

– Interval scales Interval scales do not havedo not have a "true" zero point, a "true" zero point, it is not possible to make statements about how many times higher it is not possible to make statements about how many times higher

one score is than another. one score is than another. Ratio: represents the same magnitude on the trait or characteristic Ratio: represents the same magnitude on the trait or characteristic

being measured across the whole range of the scale. being measured across the whole range of the scale. – DO haveDO have true zero points true zero points

Research TechniquesResearch Techniques

Types of hypothesis testing:Types of hypothesis testing:– T-test: comparing the mean of two groupsT-test: comparing the mean of two groups– ANOVA: Analysis of Variance – used to compare the ANOVA: Analysis of Variance – used to compare the

means of several variablesmeans of several variables– Correlation: compares the relationship of two groupsCorrelation: compares the relationship of two groups– Chi Square of independence: explains if is a relationship Chi Square of independence: explains if is a relationship

between the attributes of two variables. between the attributes of two variables. – Linear regression: the prediction of one variable based Linear regression: the prediction of one variable based

on another variable, when the relationship between the on another variable, when the relationship between the variables is assumed to assumed to be linear.variables is assumed to assumed to be linear.

ReferencesReferences

David M. Lance David M. Lance HyperStat Online Statistics TextbookHyperStat Online Statistics Textbook hhttp://davidmlane.com/hyperstat/ttp://davidmlane.com/hyperstat/

Knap, T. R. (1996). Knap, T. R. (1996). Learning Statistics Through Playing Learning Statistics Through Playing CardsCards. SAGE publications London. SAGE publications London

Sanocki, T. (2001). Sanocki, T. (2001). Student Friendly StatisticsStudent Friendly Statistics. PrenticeHall . PrenticeHall Upper Saddle River NJUpper Saddle River NJ

Fox, J. A. & Levin, J. ( 2005). Fox, J. A. & Levin, J. ( 2005). Elementary Statistics in the Elementary Statistics in the Criminal Justice Reseach The EssentialsCriminal Justice Reseach The Essentials Pearson Boston Pearson Boston

Review from last week, Answers Review from last week, Answers

Criteria for Research Criteria for Research ProjectProject

UniversalityUniversality -- can be completed by -- can be completed by anyoneanyone

ReplicationReplication -- can be repeated under -- can be repeated under same conditions with same resultssame conditions with same results

ControlControl -- use parameters to control as -- use parameters to control as many variables as possiblemany variables as possible

MeasurementMeasurement -- important to quantify as -- important to quantify as much as possiblemuch as possible

Types of Research Types of Research -- by Method-- by Method

ExperimentalExperimental CorrelationalCorrelational EvaluationEvaluation HistoricalHistorical NaturalisticNaturalistic SurveySurvey

Types of Research Types of Research -- by Philosophy-- by Philosophy

QuantitativeQuantitative -- (Positivistic) -- (Positivistic)– Things are meaningful only if we can verify Things are meaningful only if we can verify

them with our five senses.them with our five senses.

QualitativeQualitative -- (Post-positivistic) -- (Post-positivistic)– All research is value-laden. Can’t remove All research is value-laden. Can’t remove

self from research.self from research.

What is the Purpose of What is the Purpose of Research?Research?

DescribeDescribe -- Ex: settings -- Ex: settings PredictPredict -- Ex: success based on ACT -- Ex: success based on ACT ImproveImprove--Ex: teaching methods--Ex: teaching methods ExplainExplain -- answers “why?” -- answers “why?”