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# Prob/Stat Chapter 1

### Prob/Stat Chapter 1 + 14.1, 14.2

TermDefinition
Statistics science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data
3 examples of how Statistics is used in everyday life human endeavor (sports, public health, education), analyze results of a survey, and as a tool in scientific research to make decisions based on controlled experiments
3 reasons to use statistics To understand statistical studies, to be able to conduct research, design experiments, make predictions, and communicate results, and to become better consumers
branch areas of statistics Descriptive: collection, organization, summarization, and presentation of data Inferential: generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions
Examples of variables Qualitative: placed into distinct categories (gender, color, etc.) Quantitative: ordered by rank (age, height etc) Discrete variable: countable (number of children, etc) Continuous variable: infinite numbers between 2 numbers (height of kids, etc)
How to find boundaries Boundaries contain one more decimal place than the initial value, with it being .x5 less and more than the number where x is the number of decimal places in the original value. Ex. 14 (13.5 - 14.5) .43 (.425 - .435)
Examples of each of the measurement levels Nominal: Gender, zip code, etc. Ordinal: Letter grades, ranking (1st, 2nd, etc.) Interval: IQ Tests, SAT Scores, Temperature, etc. Ratio: Height, weight, area, etc.
2 purposes for data collection To describe situations or events, and to help people make better decisions before acting
3 ways to collect data Surveys, mailed questionnaires, sampling
Advantage and disadvantage for the 3 kinds of surveys Questionnaire: cover wider area, but interviewers need to be trained Telephone surveys - less costly, people may not be home Sampling - random people, but may not have a good sample
Examples of each of the sampling methods Random: numbering cards Systematic: numbering, then selecting every kth number Stratified: dividing population into groups based on characteristics, then getting a sampling from each group Cluster: dividing population in groups that represent clusters
Examples of the kinds of studies