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Prob&Stat Ch. 1

Chapter 1 Terms

Variable A characteristic or attribute that can assume different values
Data The values a variable assumes
Random Variable Variables are determined by chance
Data Set A collection of data values
Data Value- Datum Each value of the data set
Probability The chance of an event happening
Population Consists of all subjects being studied
Sample A group of subjects selected from a population
Statistics The science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data.
How is Statistics used in everyday life? 1) Fields of human endeavour 2)To analyze the results of a survey 3)As a tool in scientific research 4) Operations, quality control estimation, and predictions
Reasons to study statistics 1) To understand statistical studies 2) To be able to conduct research, design experiments, and conduct studies 3)To become better consumers
Find the boundaries of .43 sec .425- .435
Nominal Level of Measurment Classifies data into mutually exclusive (non overlapping) exhausting categories where no order or rank can be imposed on the data
Interval Level of Measurment Ranks data and precise differences between units of measure do not exist; however there is no meaningful zero
Ratio Level of Measurment Interval measurement but there is a meaningful zero
What are the 2 purposes of data collection? 1 ) To describe situations or events 2) To help people make better choices before acting
3 ways to collect data Surveys, mailed questionnaire, and personal interview
Telephone surveys Less costly, can be candid, not face to face Not all people can be surveyed, may not be home, unlisted
Mailed Questionnaire Can cover a wide geographic area, less expensive to conduct, respondents can remain anon Low # of responses
Personal Interview Can obtain in depth responses Interviewers need to be trained, cost more, can be biased
Random Sampling Sampling technique where you randomly select a group from a larger group of subjects
Systematic Sampling Take a random sample of the population by using every kth variable
Stratified Sampling Take samples from each stratum ( sub group ) of a population
Cluster Sampling Population is divided into clusters, and a group is selected from cluster
Sequential Sampling Successive units taken from product line and tested to make sure they meet requirements
Double Sampling Large population is given questionnaire to see who meets requirements for study. After the results are studied, a smaller sample is chosen from this population
Things that make a survey bad Asking biased questions Using confusing words Asking double barreled questions Using double negatives in a question Odd order of questions
Qualitative Variables Can be placed into distinct categories- characteristics not numbers
Descriptive Statistics The collection, organization, summarization, and presentation of data.
Inferential Statistics Generalizing from samples, performing estimations, determining relationships among variables, and making predictions
Quantitative Variables Numerical and can be ordered/ ranked
Discrete Variables Variables that assume values that can be counted
Ordinal Level of Measurment Classifies data into variables that can be ranked. Precise differences between the ranks do exist
Continuous Variables Variables that can assume an infinite amount of values between any specific two values. (Usually obtained by measuring, fractions or decimals)
Created by: bbogan