tec 5143 sp11 last class final exam review0

8/6/2019 TEC 5143 SP11 Last Class Final Exam Review0

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Research in TechnologyMore stat/ Research Proposals /

Final Exam Review

TECH 5143Spring 2011 Dr. B


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TodayMore stats

Research Proposal presentations(Peer reviews)

Final feedback

Final exam review


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Statistical TechniquesParametric statistics

Based on normaldistributionTypically Ratio or Interval data typesCentral measure:Mean

Scores AgesExceptions?

Non-parametric statisticsBased on non-normaldistributionTypically Nominal or Ordinal data typesCentral measure:Median

IncomeIncidence of raredisease


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Parametric StatisticsT- Test

Analysis of Variance (ANOVA)

Analysis of Covariance (ANCOVA)RegressionFactor AnalysisStructural Equation Modeling (SEM)


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T-TestTo determine whether a statistically significantdifference exists between two means

For example:Teachers identified some of their students ashaving exceptional intellectual potential. Thesestudents got significantly higher test scores thanthe rest of the class

T-Test used to find if the performance differenceis statistically significant


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Analysis of Variance (ANOVA)To look for differences among three or moremeans by comparing the variances (s 2) both withinand across groups


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Analysis of Variance (ANOVA)For example:

D oes the presence of other people have an influenceon whether a person will help someone in distress

In a classic study, the experimenter (a female graduatestudent) had the subject wait in a room with either 0, 2,or 4 other peopleThe experimenter announces that the study will beginshortly and walks into an adjacent roomIn a few moments the person(s) in the waiting roomhear her fall and complain of ankle painThe dependent measure is the number of seconds ittakes the subject to help the experimenter (Darley &

Latan, 1969)


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Analysis of Variance (ANOVA)Study involved comparison of 3 means or a multigroup mean analysis

Differences can be due to:G roup Membership (i.e., the treatment effect or effect of being in a small vs. larger group).N ot due to group membership (i.e., chance or s ampling error ).


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Type I, Type II errorsNull hypothesis > reject null (to prove

hypothesis)

The harder you study, the higher your grades are likelyto beYour grades have no relation to how hard you study

Prove null > but reject it:

Type I error: false rejection of a true null

Disprove null > but retain it:Type II error: false retention of a false null


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Analysis of Covariance (ANCOVA)

Look for differences among means whilecontrolling for the effects of a variable that iscorrelated with the dependent variable (covariate)

Decreases the probability of Type II error (falseretention of a false null or prevent rejecting it)


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For example: A set of 20 third-graders, randomly sorted into twoindependent groups of 10 subjects each, with thedesign of teaching one group by Method A and theother by Method B.

The aim of the initial random sorting is to ensurethat the two groups are starting out approximatelyequal , on average, with respect to all pertinent

factors.


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It could happen through sampling error or sheer random variabilitythat the two groups do notstart out equal with respect to one or more factors

For instance, one of the groups may start out witha higher average level of intelligence or motivation, which would surely complicate the

situation

The analysis of covariance provides a way of measuring and removing the effects of such initialsystematic differences between the samples.


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Regression

To examine how efficiently one or more variablesallow you to predict the value of another (dependent) variable

A regression is a statistical analysis assessing theassociation between two variables .

Used to find the relationship between twovariables.


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Regression

Simple linear regression generates anequation where a single independent

variable yields a prediction for the dependentvariableusing a macroeconomic variable such aspersonal income to forecast home ownership

Temperature to predict thirst (water consumption)


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Regression

Multiple regression two or moreindependent variables are used to predict

the dependent variable

Thirst >

Temperature Activity levelType of activity (sports / mowing / sitting under shady tree)


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Factor Analysis

Examine the correlations among a number of variables and identify clusters of highly interrelatedvariables that reflect underlying themes or factorswithin the data


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Factor AnalysisFor example, consider the construct of "leadership" -"task skills" and "people skills"D eveloping a new questionnaire about leadership

20 items - 10 for "task" elements and 10 "people"elements,Pretest to verify validity

Factor analysis can be used to check if there are reallytwo factors, and if those factors represent thedimensions of task and people skills.If yes create two separate scales, by summing the

items on each dimension


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Structural Equation Modeling (SEM)

Examine correlations among a number of variablesin order to identify possible causal relationships(paths) among them

Typically used to test a previously hypothesizedmodel of how variables are causally interrelated


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Structural Equation Modeling (SEM)S uppose you have the list of numbers 1,2,3.These numbers have a mean of 2 and a s tandard deviation of 1

N ow, suppose you take these 3 numbers and multiplythem by 4. Then the mean would become 8, and thestandard deviation would become 4, the variance thus16

S o if you have a set of numbers X related to another setof numbers Y by the equation Y = 4X, then the varianceof Y mu s t be 16 times that of X, so you can test thehypothesis that Y and X are related by the equation Y =4X indirectly by comparing the variances of the Y and X

variables


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Structural Equation Modeling (SEM)

This idea generalizes, in various ways, to severalvariables inter-related by a group of linear equations

The rules become more complex, the calculationsmore difficult, but basically:

You can test whether variables are interrelatedthrough a set of linear relationships by examiningthe variances and covariances of the variables


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Meta Analysis

Analyze and draw conclusions from other researchers statistical analysis

Analysis of analysis > meta analysis

Integration of studies statistically (not descriptive)Conduct fairly extensive search for relevantstudiesIdentify appropriate studiesConverts each studies results to a common

statistical index > Effect Size


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Meta Analysis

Effect Size: how much of a difference anintervention makes ( in terms of standard deviation

units) in each study

Effect sizes for all studies used to computeaverage effect size for that intervention


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Finally: Interpreting the Data

CAUTION!

Relating the findings to the original researchproblem, to the specific research questionCome full circle

Relating the findings to pre-existing literatureFull circle to lit review

Practical significance versus statistical significanceIdentifying limitations of study

Report weaknesses as well


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Types of Research

http://www.mnstate.edu/wasson/ed603/ResearchTypes.JPG


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Proposal presentations

2 peer reviews each

Final feedback


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Final Exam Review

FormatS hort answers (concepts) any 4 of 6 150-200words (20)

True/False; Fill-in; Multiple Choice; S pot APA

errors; Basic stat; identify variables; identifydata types (25)

Alter your research question (5)


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S tate your research questionG ender differences in high school students intent tochoose technology majors

What research methodology are you using?Correlational research

Alter the question to fit either Qualitative or Correlational research (any given types)methodology

You may make slight modifications to what you areasking - if necessary

Qualitative analysis of high school students opinions abouttechnology: Case study of gender differences inCharleston High S chool

Final Exam Review: Heads up!


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S tate your research questionWhat research methodology are youusing?Alter the question to fit either _______or ______ (given) methodology (You

may make slight modifications to whatyou are asking - if necessary)

Final Exam Review: Heads up!


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J ane wants to test a construct: creativity andcompare scores across J unior High, and HighS chool cohorts. S he wants to test if creativity isrelated to age in anyway.S he included factors such as emotionalintelligence, participation, time on extra-curricular, awards etc. to describe the overallrating for creativity.Which statistical technique would she need toensure that the overall construct of creativity canbe fully described by the sub-factors sheidentified?

a. A NOV A b. S EM

c. A N COV A d. Factor Analysis

Final Exam Review: e.g. multiple choice


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J ane wants to test a construct: creativity andcompare scores across J unior High, and HighS chool cohorts. S he wants to test if creativity isrelated to age in anyway.S he included factors such as emotionalintelligence, participation, time on extra-curricular, awards etc. to describe the overallrating for creativity.Which statistical technique would she need toensure that the overall construct of creativity canbe fully described by the sub-factors sheidentified?

a. A NOV A b. S EM

c. A N COV A d. Factor Analysis



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There are two roughly comparablepopulations in terms of gender, ethnicity,and socio-economic status. However oneis largely comprised of seniors. Whatstatistical technique should be used tocompare means?

a. ANOV

A b.S

EMc. A N COV A d. Factor Analysis



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There are two roughly comparablepopulations in terms of gender, ethnicity,and socio-economic status. However oneis largely comprised of seniors. Whatstatistical technique should be used tocompare means?

a. ANOV

A b.S

EMc. A N COV A d. Factor Analysis



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D uring his S ophomore year Matt participated in a lotof extra-curricular activities, and thought he deservedextra credit. What statistical test can his instructor perform to assess whether Matts participation wassignificantly higher than the rest of the class?

a. Linear Regression b. t-Test

c. A NOV A d. no test is necessary



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D uring his S ophomore year Matt participated in a lotof extra-curricular activities, and thought he deservedextra credit. What statistical test can his instructor perform to assess whether Matts participation wassignificantly higher than the rest of the class?

a. Linear Regression b. t-Test

c. A NOV A d. no test is necessary



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____________ can be used to predict collegeadmission, based upon a criteria consisting of ACTscores, high school grades, and family income.

a. Linear Regression b. Multiple Regressionc. Factor Analysis d. A N COV A



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____________ can be used to predict collegeadmission, based upon a criteria consisting of ACTscores, high school grades, and family income.

a. Linear Regression b. Multiple Regressionc. Factor Analysis d. A N COV A



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Effect S ize is a statistical way to establishequivalence among widely varied research

studies. It is most often used in _______________

a. Factor Analysis b. t-Testc. Meta Analysis d. Linear Regression



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Effect S ize is a statistical way to establishequivalence among widely varied research

studies. It is most often used in _______________

a. Factor Analysis b. t-Testc. Meta Analysis d. Linear Regression



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It was found that the use of gaming deviceswas significantly higher among under-graduate students when compared to non-traditional students. The study also foundthat use differed significantly by gender inboth groups

D ependent VIndependent VModerator V

Final Exam Review: e.g. variables


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It was found that the use of gaming deviceswas significantly higher among under-graduate students when compared to non-traditional students. The study also foundthat use differed significantly by gender inboth groups

D ependent V : Use of gaming devicesIndependent V : Academic levelModerator V : G ender



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It was found that children who spent atleast 10-15 hrs in outdoor activities each

week were likely to score 1.5 times higher in social interaction skills than those whodidnt

D ependent V :Independent V :



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It was found that children who spent atleast 10-15 hrs in outdoor activities each

week were likely to score 1.5 times higher in social interaction skills than those whodidnt

D ependent V : social interaction scoresIndependent V : outdoor activities time



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O nline training was found to be as effectiveas on-site training as a predictor of employee performance. However,

employees with an experience of 10 yearsor more did not show any change in their performance by either training method

D ependent V :Independent V :Moderator V :



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O nline training was found to be as effectiveas on-site training as a predictor of employee performance. However,

employees with an experience of 10 yearsor more did not show any change in their performance by either training method

D ependent V : employee performanceIndependent V : training methodModerator V : length of employment



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The math and science scores of moststudents in the 9 th grade were likely to belower than their (same subject) scores in

the 6th

grade. The findings changed whenthe same results were compared in asingle-sex school

D ependent V :Independent V :Moderator V :



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The math and science scores of moststudents in the 9 th grade were likely to belower than their (same subject) scores in

the 6th

grade. The findings changed whenthe same results were compared in asingle-sex school

D ependent V : 9 th grade scoresIndependent V : 6 th grade scoresModerator V : type of school



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Calfee, R. C., (1991). APA guide to preparingmanuscripts for journal publication. Washington,D C: American Psychological Association

(J ust note what needs to be changed)

Final Exam Review: APA errors


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Calfee, R. C., (1991). APA guide to preparingmanuscripts for journal publication. Washington,D C: American Psychological Association

book title in italics



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Harlow, Harold F. (1983). Fundamentals for preparingpsychology journal articles. J ournal of Comparative and Physiological Psychology, 55,893-896.



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Harlow, Harold F. (1983). Fundamentals for preparingpsychology journal articles. J ournal of Comparative and Physiological Psychology, 55,893-896.

Harlow, H. F.,

N o quotation marks for titleJ ournal title italicize



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According to J ones, 1998, S tudents often had difficultyusing APA style, especially when it was their firsttime (p. 199).



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According to J ones, 1998, S tudents often had difficultyusing APA style, especially when it was their firsttime (p. 199).

According to J ones (1998), S tudents.time (p.199).



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There are 25 students in a high school sophomorehistory class. 18 are boys. Amy is the tallest girl inthe class, although six boys are taller than her.The class obtained a mean test score of 83.7 intheir midterm history exam during the S pring 2010term. This schools overall student demographic ischaracterized by largely middle and upper middleclass income group. 77% of all students areCaucasians, 12% are African Americans, 8% areHispanics, and 3% are international and/or multi-ethnic.

Fill in the following using the above description:a. Test scores are (continuous / discrete / ordinal

/ nominal) data

b. Heights of students are _(ratio / interval /ordinal / nominal) data


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c. Ethnicities of students are (continuous /discrete / interval / ratio) data

d. S ocio-economic status of students (incomegroup) is ________ (continuous / ratio / interval /nominal) data

e. S tudent gender is _____________ (ratio /nominal / ordinal / interval) data


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c. Ethnicities of students are (continuous /discrete / interval / ratio) data

d. S ocio-economic status of students (incomegroup) is ________ (continuous / ratio / interval /nominal) data

e. S tudent gender is _____________ (ratio /nominal / ordinal / interval) data


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Correlational research implies cause andeffect

Historical research makes extensive useof primary data sources

Final Exam Review e.g. True/False


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Correlational research implies cause andeffect

False

Historical research makes extensive useof primary data sources

True



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Historical research deals with past data,while Qualitative research deals with

current data

Correlational research involves themanipulation of treatment variable



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Historical research deals with past data,while Qualitative research deals with

current dataTrue

Correlational research involves themanipulation of treatment variable

False



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N ominal data type indicates some sort of order/ progression

O rdinal scale gives true measurementwith an absolute 0



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N ominal data type indicates some sort of order/ progression

False

O rdinal scale gives true measurementwith an absolute 0

False



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The following research involves narrative datatype:

D escriptiveCorrelationalHistoricalExperimental



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The following research involves narrative datatype:




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The following research involves cause andeffect relationships




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The following research involves cause andeffect relationships




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The following research is based on currentevents

D escriptiveCorrelationalQualitativeExperimental



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The following research predicts a relationship

DescriptiveCorrelational

QualitativeExperimental

Final Exam Review


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The following research predicts a relationship

DescriptiveCorrelational

QualitativeExperimental

Final Exam Review


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The following research involves numerical data, eventhough it does NO T involve cause/effect, and doesNO T predict relationships

D escriptiveCorrelationalQualitative

Experimental



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The following research involves numerical data, eventhough it does NO T involve cause/effect, and doesNO T predict relationships

D escriptiveCorrelationalQualitative

Experimental



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Explain what is meant by reliability, andvalidity of a survey questionnaire with

examples

What is Correlational research? How is it

different from Experimental research?Explain with an example

Example short answers


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What are some ways to make a surveyquestionnaire more user-friendly

What are some ways to increaseresponse rate of surveys?

Explain what is Meta Analysis? Whatstatistical index is used to comparewidely differing statistical studies?

Example short answers


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What is meant by directional hypothesis?How is it different from a non-

directional hypothesis? Explain withexamples

What is historical research? What type of data is generally useful for this type of research? How is this relevant intechnology?

Final Exam Review


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Explain how O rdinal data type differsfrom Interval data type with examples

Explain the focus of the various forms of qualitative research

Explain the difference betweenParametric and N on-Parametricstatistics. G ive at least 2 examples

Final Exam Review


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Identify and describe different ways aresearcher can identify problems

worthy of research.

What is the difference between apopulation and a sample? Explainwhy the larger the sample is, thesmaller the sampling error will be.

Final Exam Review


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If you want to include subgroups in your sample howwould this affect your sample size? Explain usingan example

What is Literature review? Why is it necessary? Howwould you select articles/ sources to include inyour literature review?

D escribe the following with examples:a. Assumptionsb. D elimitationsc. D efinitions

Final Exam Review


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Overall course concepts


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Research/ S cientific method/ Inductive reasoning/D eductive reasoning

Research types:

D ata typeAnalysis MethodsTime factor D ata manipulation

D ifference between Qualitative / QuantitativeExperimental / CorrelationalD escriptiveHistorical etc

Course Concepts


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Concepts:Hypothesis ( N ull) / Research question

Problem S tatementV ariables dependent/ independentD ata measurement > N ominal/ O rdinal/

Interval/ RatioV alidity / ReliabilityAssumptions / Limitations etc

Course Concepts


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purpose/ focus/ data collection/ analysisQualitative research: Case S tudy /Ethnography/ Phenomenology/G rounded Theory/ Content Analysis

D escriptive research: Measures of Central tendency/ variance / Basicstatistical techniques

Course Concepts


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purpose/ focus/ data collection/ analysisCorrelational: Coefficient of Correlation >magnitude / direction relationship prediction

Experimental: V ariable manipulation/ cause &effect

Historical: S ources of data / issues / examples / Primary vs S econdary data

D evelopmental studies longitudinal vs.

cross-sectional

Course Concepts


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Concepts:Ethical theories / ethical research guidelines /

IRB approval process

Academic writing conventions / basictechnical report format / writing style

APA spot issues with formatting in-text/reference list (book/ journal/ online) singleor several authors

Course Concepts


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S olve for:Mean / Median / Mode/ Range

Conceptual understanding: (with examples)Parametric vs. N on-parametricN ormal distribution

S kew-ness / KurtosisZ-scoret-test

Course Concepts


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Due dates

Fri Apr 29, 11:59pm on WebCT:Final Proposal report due (in teams)

Peer Reviews (2 each) due (individual)

Final Exam:

Tue May 3 : CA D Lab: 7:30pm sharp!

tec 5143 sp11 last class final exam review0

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