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BNAD 276 Week 1 Notes

by: madelinef

BNAD 276 Week 1 Notes BNAD 276 001

Marketplace > University of Arizona > BNAD 276 001 > BNAD 276 Week 1 Notes
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About this Document

These notes consist of the material covered in week 1 of BNAD 276.
Statistic Inference in Management
Dr. Suzanne Delaney
Class Notes
intro to statistics




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This 2 page Class Notes was uploaded by madelinef on Saturday August 27, 2016. The Class Notes belongs to BNAD 276 001 at University of Arizona taught by Dr. Suzanne Delaney in Fall 2016. Since its upload, it has received 118 views.


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Date Created: 08/27/16
BNAD 276 Week 1 Conducting Analyses that are Relevant and Useful starts with Measurement Designed to Decrease Uncertainty • Operational definition- definition of a construct/characteristic in terms of how it is measured specifically for a particular thing o Construct- represents relatively abstract concepts o Operational definition- how constructs are measured o Measurements- assess observable characteristics or behaviors in a reduction of uncertainty o Example: Laughter/smilesà humorànumber of smiles detected in x amount of time § Memorableà how many people remember x after y seconds § status of productàrank 1-10 on coolness of a car • Evaluating operational definitions o Validity- are you measuring what you intend to? o Reliability- the extent to which a test yields consistent results § Ex: proper ruler= valid and reliable § Homemade ruler- reliable § Bungee ruler- neither o Reliability is a measure of consistency of measurement. Validity is a measure of the scores • Dependent variable- the variable being measured by investigation o The data that is being recoded • Independent variable- the factor that is being manipulated (or compared) by the investigator o EX: are commercials funnier with animals? o Dependent variable (DV)- rating 1-10 of funniness of commercial o Independent variable (IV)- if there is an animal or not in the commercial • Within participant design- each subject participated in every level of variable (repeated measures) o Level being if you are testing 3 types of ice cream, 1 person tests all 3 • Between participant design- each subject participated in only 1 level of independent variable o You only test 1 type of ice cream • Random assignment- any subject has an equal chance of getting assigned to either condition o If you have random assignment, you may have a true experiment thus have cause and effect. Called true experiment. If NO random assignment you have a quasi experiment and can NOT talk about cause and effect. (Ex: height and weight causing more or less truthfulness…gender and spending more money) • Correlation does not affect causation! • Random sampling- each person in population has an equal chance of being selected to be in the sample. o Nothing to do with quasi and true! • Population- the entire group you want to study (ex: U of A freshman) • Sample- subset of population who participated (ex: 1000 U of A freshman polled…) o Ex: is Ginseng associated with feelings of satisfaction? § Group 1- placebo pill § Group 2- ginseng § IV: did they get ginseng? § DV: satisfaction level? § Levels? 2 (ginseng or not) § Within because they were tested twice according to example statement.


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