StudyGuideforBNAD276.pdf BNAD 276 003
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This 6 page Study Guide was uploaded by Hannah DeSanto on Tuesday September 22, 2015. The Study Guide belongs to BNAD 276 003 at University of Arizona taught by Dr. Suzanne Delaney in Fall 2015. Since its upload, it has received 31 views. For similar materials see Statistical Inference in Management in Business, management at University of Arizona.
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Date Created: 09/22/15
Study Guide for BNAD 276 Appendix D vocab Variable anything that can change Theory broad idea or set of closely related ideas that attempts to explain observations Hypothesis an educated guess that derives logicaly from a theory a prediction that can be tested Constructs The theoretical concepts that make up our variables of interest what we are hoping to better understand through our measurements Examples include happiness memory customer satisfaction management effectiveness public image etc Metaanalysis a method that allows researchers to combine the results of several different studies on a similar topic in order to establish the strength of an effect Descriptive research Research that determines the basic dimensions of a phenomenon de ning what it is how often it occurs and so on Case Study or Case history an indepth look at a single individual Longitudinal design a study that takes repeated measurements over time The intention may be to look for general trends over time within a culture or business market or to look for changes over time within an individual Crosssectional design a study that measures multiple groups at some point in time as though we are taking quotslicesquot or measurements for each group The intention is to compare the different groups True experiment a carefully regulated procedure in which the researcher manipulates one or more variables that are believed to in uence some other variable A crucial characteristic is the random assignment of participants to the different levels of the independent variable Only true experiments can provide evidence for causeand effect relationships Quasiexperiment A research design that resembles a true experiment but lacks the control of a true experiment most notably lacks random assignment and is more vulnerable to bias due to confounding variables Therefore it cannot provide evidence for a ca useandeffect relationship Random Assignment Researchers assignment of participants to groups by chance to reduce the likelihood that an experiment s results will be due to preexisting differences between groups CauseandEffect Evidence requires the manipulation of the one variable of interest while holding all of the other possible confounding reasons True experiments which include random assignment of subjects to each level of the independent variable eliminates confounding variables and allows us to establish causality Quasiexperiments do not eliminate all confounding variables so they cannot be used as evidence of a causeandeffect relationship Independent Variable A manipulated experimental factor the variable that the experimenter changes to see what its effects are Confounding variable not controlled for in a study and varies systematically with the different levels of the independent variable making it impossible to know the reason or cause of the effect on the dependent variable Quasiexperiments are more likely to have confounding variables Confederate Person given a role to play in a study Dependent Variable The outcome factor that can change in the experiment in response to changes in the independent variable Experimental Group participants in an experiment who receive the drug or other treatment under study Control Group Group being tested on without the manipulated factor BetweenParticipant Design Each subject participates in only one level of independent variable no overlap Withinparticipant design each subject partipates in every level of the independent variable total overlap External Validity The degree to which an experimental design re ects the real world issues Internal Validity The degree to which changes in the dependent variable are due to the manipulation of the independent variable Experimenter Bias Occurs when the experimenter s expectations in uence the outcome of the research Demand characteristics Any aspects of a study that communicate to the particpants how the experimenter wants them to behave Research Participant Bias Occurs when the behavior of research participatns during the experiment is in uenced by how they think they are supposed to behave Doubleblind experiment An experimental design in which neither the experimenter nor participants are aware of which participants are in the experimental group and which are in the control group until the results are calculated Random Sample A sample taken that gives every member of the population an equal chance of being selected Descriptive Statistics mathematical procedures that describe and summarize sets of data Mean Measure of central tendency that is the average for a sample Median a measure of central tendency that is the middle score in a sample Mode A measure of central tendency that is the most common score in a sample Range A measure of dispersion that is the difference between the highest and lowest scores Standard deviation A measure of dispersion that tells how much scores in a samples differ from the mean of the sample Bimodal distribution Distribution with two most frequent observations 2 peaks lnferential Statistics Mathematical methods that are used to indicate whether results for a sample are likely to generalize to a population Correlational Research Research that examines the relationships between variables whose purpose is to examine whether and how two variables change together Third variable problem The circumstance where a variable that has not been measured accounts for the relationship between two other variables Steps 1 Observe some phenomenon 2 Formulate hypothesis and predictions 3 Test through empirical research 4 Drawing Conclusions 5 Evaluating the Theory Appendix E What to consider when constructing questions Question wording Simplicity DoubleBarreled Questions asking two questions quotShould senior citizens be given more money for recreation and food programsquot Loaded questions lead people to respond in one way Avoid using words like Rape waste ungodly Negative wording avoid negatives appendix F is only vocab LECTURE 1 Experimental Methodology Quasiexperimental methodology Operational De nition de nition of a constructed or characteristic in terms of how it is measured speci cally for a particular context Constructs represent relatively abstract concepts quotOperational de nitionsquot de ne how constructs are measured Measurements assess observable characteristics or behaviors resulting in a reduction of uncertainty Continuous variable Variables that can assume any value There are in principle an in nite number of values between any two numbers Discrete variable Variables that can only assume whole numbers There are no intermediate values between the whole numbers Validity the extent to which a test measures what it intends to measure Reliability the extent to which a test yields consistent results Low High validity Validity LEW reliability Higll reliability LECTURE 2 Categorical data also called qualitative data a set ofobservations where any single observation is a word or a number that represents a class or category Nominal data classi cation differences in kind names of categories Ordinal data order rankings differences in degree Numerical data also called quantitative data a set of observations where any single observation is a number that represents an amount or count Interval data measurable differences in amount equal intervals Ratio data measurable differences in amount with a quottrue zero LECTURE 3 Time series design Each observation represents a measurement at some point in time Repeated measurements allow us to see trends Crosssectional design Each observation represents a measurement at some point in time Comparing across groups allows us to see differences Sample frame how you de ne population Parameter Measurement or characteristic of the population Usualy unknown only estimated Usualy represented by Greek letters u Statistic Numerical value calculated from a sample Usual y represented by Roman letters X Descriptive statistics organizing and summarizing data lnferential statistics generalizing beyond actual observations making quotinferencesquot based on data collected Systematic random sampling A probability sampling technique that involves selecting every kth person from a sampling frame Strati ed sampling sampling technique that involves dividing a sample into subgroups or strata and then selecting samples from each of these groups Cluster sampling sampling technique divides a population sample into subgroups or clusters by region or physical space Can either measure everyone or select samples for each cluster Convenience sampling sampling technique that involves sampling people nearby Nonrandom sample and vulnerable to bias Snowball sampling a nonrandom technique in Which one or more members of a population are located and used to lead the researcher to other members of the population Judgment sampling sampling technique that involves sampling people Who an expert says would be useful Pareto Chart Categories are displayed in descending order of frequency Body Shop Defects 3 QNbmmG Number of Defects 55 0 58 Vo q be 9 04quot 0 Q 7 lt2 2 O 0 lt 8433 g Kg 3quot 9 Qquot f Brody Location Stacked Bar Chart Bar Height is the sum of several subtotas Medical School Applications by Gender 50000 lMen 40000 30000 20000 Applicants 1 0000 Simple Line Charts Often used for time series data continuous data Monthly Basic Rate for Cable TV 1975 2005 68 annual growth rate V 0 llllllllllIIIllllllllllllllllllllll 1975 1980 1985 1990 1995 2000 2005 Pie Charts General idea of data that must sum to a total use With much caution Where Did You Buy Your Statistics Textbook Web 29 Amazon 18 Campus Bookstore 54 Retail Outlet 25 LECTURE 4 Positive correlation as values on one variable go up so do values for the other variable Negative correlation as values on one variable go up the values for the other variahle go down This sham 39thgjs39rr 1 1 EllEl engage 8 Ian 52 55 Era54 TE m 39 Hzig 39 a Dagmar ij39lchuji LECTURE 5 MEMORIZE v No le
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