COB 191 Week 1 Notes
COB 191 Week 1 Notes COB 191
Popular in Business Statistics
Popular in Math
This 4 page Class Notes was uploaded by Hannah Schwenk on Thursday August 11, 2016. The Class Notes belongs to COB 191 at James Madison University taught by L. Dutt in Fall 2016. Since its upload, it has received 109 views. For similar materials see Business Statistics in Math at James Madison University.
Reviews for COB 191 Week 1 Notes
Report this Material
What is Karma?
Karma is the currency of StudySoup.
Date Created: 08/11/16
COB 191 Leslie Dutt 8/29 – 9/2 1. Statistics a. Mathematical Science that deals with the collection, analysis and presentation of data, used as the basis of inference and induction. 2. Business Use for Stats a. Marketing research b. Advertising c. Operations d. Finance and Economics 3. Data a. Values assigned to raw observations and measurements 4. Information a. Data that is transformed 5. Primary Data a. Data you collect yourself b. Direct Observations, Focus Groups, Experiments an Surveys 6. Secondary Data a. Data collected by someone else 7. Bias a. Occurs when question encourages a specific response 8. Qualitative Data a. Classified by a Descriptive Term 9. Quantitative Data a. Classified by Numerical Values 10. Types of Data a. Nominal i. Unimportant Labels, no Ranks b. Ordinal i. Ranks, but no meaning to Numerical Labels c. Interval i. Meaningful Numerical Labels, No true Zero d. Ratio i. Meaningful Numerical Labels, True Zero 11. Types of Variables a. Categorical i. Marital Status b. Numerical i. Discrete ii. Continuous 12. Time Series Data a. Value that corresponds to measurements taken over a range of time periods. 13. Cross Section Data a. Values collected from a number of subjects during a single time period 14. Descriptive Stats a. Collecting, summarizing and displaying data 15. Inferential Stats a. Making claims and conclusions about the data based on the sample 16. Population a. Represent all possible subjects that are of interest for a study 17. Sample a. Refers to the portion of the population actually selected for study. 18. Parameter a. Described characteristics about a population 19. Statistic a. Described characteristic of a sample 20. Biased Sample a. Sample does NOT represent the intended population 21. Graph Scale a. Avoid any distortion that may convey the wrong message 22. Why sample? a. Cant examine the entire population b. Sample info can be used to make an accurate assessment of the entire population 23. Probability Sample a. Every member of a population has a non-zero chance of being selected 24. Simple Random Sample a. All individuals have the same chance of being selected 25. Systematic Sample a. K^nth b. K= N/n i. N population size ii. n sample size c. Periodicity i. Potential pattern in the population that coincides with K, could cause inaccurate reading 26. Stratified Sampling a. Divides the population into mutually exclusive groups b. Based on factors that can have an impact on data and the results 27. Cluster a. Dividing population into groups and then selecting random groups b. Often based on geography c. Should be representative of the ENTIRE population 28. Resampling a. Samples are repeatedly drawn 29. Non-Probability Sampling a. No known Likelihood of any individual being selected 30. Convergence Sampling a. Sample is based only on accessibility 31. Survey Worthiness a. Purpose b. Based on Probability? c. Coverage errors? d. Nonresponse Errors? e. Sampling Errors? f. Measurement Errors?